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Numerical systems used for weather and climate predictions have substantially improved over the past decades. Numerical prediction systems have reached a sufficient level of maturity to examine and critically assess the suitability of Earths current observing systems remote and in situ, for prediction purposes. They can also provide evidence-based support for the deployment of future observational networks. We illustrate this point by presenting recent, co-ordinated international efforts focused on Arctic observing systems, led in the framework of the Year of Polar Prediction and the H2020 project APPLICATE. We highlight that existing state-of-the-art datasets and targeted sensitivity experiments produced with numerical prediction systems can inform of the added value of existing or even hypothetical Arctic observations, in the context of predictions from hourly to interannual timescales. Based on these efforts we suggest that (a) conventional in situ observations in the Arctic play a particularly important role in initializing numerical weather forecasts in winter, (b) observations from satellite microwave sounders play a particularly important role in summer, and their enhanced usage over snow and sea ice is expected to further improve their impact on predictive skill in the Arctic region and beyond, (c) the deployment of a small number of in situ sea-ice thickness monitoring devices at strategic sampling sites in the Arctic could be sufficient to monitor most of the large-scale sea-ice volume variability, and (d) sea-ice thickness observations can improve the simulation of both the sea ice and near-surface air temperatures on seasonal time-scales in the Arctic and beyond.
Observations from highly elliptical orbits (HEO) are particularly well suited for Arctic monitoring and can address the current sparsity in spatial and temporal coverage of the polar regions by geostationary and polar orbiting satellites. The Arctic Observing Mission (AOM) is a satellite mission concept currently under study by the CSA in partnership with ECCC. AOM would use a HEO to enable frequent observations of meteorological variables, greenhouse gases (GHGs), air quality and space weather over northern regions.
A meteorological imager in HEO would support global Numerical Weather and Environmental Predictions (NWEP) by providing key information over the Arctic such as atmospheric motion vectors and brightness temperature observations. Northern GHG observations would improve our ability to detect and monitor changes in the Arctic and boreal carbon cycles, including CO2 and CH4 emissions from permafrost thaw. Air quality observations would enhance our ability to monitor anthropogenic emissions and mid-latitude pollution transport, which will improve air quality forecasts. Space weather observations would support operational space weather forecasting to protect valuable space-based assets and improve our scientific understanding of solar-terrestrial interactions.
International collaboration and partnership is vital to AOMs success. Improved meteorological and space weather observations of the North are of interest to the US and Europe, with NOAA, NASA and EUMETSAT participating in early mission development activities with Canada. This presentation will provide an update on plans and progress of the Canadian-led AOM mission in the ongoing effort to produce high quality quasi-geostationary northern Earth observation and space weather data.
Polar regions benefit from a high-density coverage of satellite observations that could compensate for the sparse network of conventional data. However, due to large model errors at these latitudes, the satellite observations are underused.
To improve the assimilation of surface-sensitive channels, we need to better model the surface parameters. Karbou et al. (2006) demonstrated that one can retrieve this information using the brightness temperature from a window channel and allocate the retrieval to assimilate adjacent sounding channels at higher frequencies. In a regional model, this study describes the impact of using a better representation of the surface to improve the radiative transfer simulations and 3D-VAR data assimilation of observations from AMSU-A, MHS over land, snow and sea ice. Assimilation experiments have been run in the framework of HARMONIE-AROME giving neutral to positive impacts on forecast skills.
Focusing on sea ice surfaces, another methodology has been explored. In fact, sea ice surface temperature in AROME-Arctic is not constrained by the observations and freely evolves forced by the atmospheric model and a simple parameterization. The sea ice component of the HARMONIE-AROME NWP system was extended by implementing a data assimilation module, which uses an NRT L2 ice surface temperature satellite product to constrain the ice temperature in the model. The data assimilation module is based on the EKF formulations and additionally performs explicit estimation of the modelled ice surface temperature bias. Assimilation experiments show a positive impact on the ice surface temperature and 2m Temperature.
We evaluated the relative impacts of different observations assimilated in global and regional data assimilation (DA) systems on the accuracy of the regional AROME-Arctic forecasts. ECMWF forecasts were used as lateral boundary conditions. The control experiment was the one which comprised all the studied observations. The impact of each observation was checked by taking them out one by one from the data assimilation system, i.e through observing system experiments (OSE). Using two global and Arctic OSEs as LBCs in the regional OSE allowed us to evaluate the relative impact of both Arctic and mid-latitude observations on the AROME-Arctic forecasts. The importance of the regular observing network was also evaluated on top of the additional ones.
Our results demonstrated that Arctic observations impact the quality of AROME-Arctic forecasts both through regional DA and through the assimilation of the observations in the global NWP system used to create the LBCs. Similarly, mid-latitude observations have also non-negligible impact on the forecasts of the AROME-Arctic. The total impact on the upper-air forecasts was dominated by the impact through the LBCs, while the total impact on surface fields was dominated by the impact through regional DA.
The present study suggested that a full assessment of the benefit from observations in a regional system should take into account the impact of observations in both the regional DA and in the global assimilation system that provides the LBCs.
This presentation will also show some of the yet not published results of this study.
Nowadays, satellite observations are providing primary information for initial conditions of state-of-the-art numerical weather prediction (NWP) systems and the amount of remote sensing data in the Global Observing System increases rapidly. However, the way such data are assimilated is usually conservative in high-resolution limited-area models. Our objective is to improve the use of satellite observations from polar-orbiting satellites by taking into account the observation footprint and improving the spatial representativeness in data assimilation.
The Arctic project called ALERTNESS (Advanced models and weather prediction in the Arctic) aims to improve weather forecasts and warnings over high latitudes supporting maritime operations, business, and society. In the focus of the project, AROME-Arctic model is run operationally and developed at the Norwegian Meteorological Institute. The use of satellite observations is already employed, but the footprint of such observations is not taken into account in the data assimilation system of the AROME-Arctic model. A new observation operator was developed and observing system experiments were carried to investigate the importance of the satellite footprint representation for scatterometer ocean winds, Aeolus wind profiles, and satellite radiances.
We summarize some YOPP studies on the use of vertical profile observations from different decades in evaluation of atmospheric reanalyses and NWP model products as well as in data denial experiments. Considering the Antarctic sea ice zone, sounding observations from 1990s revealed that all reanalyses evaluated were generally too warm in the boundary layer. Evaluation of NWP models in winter 2013 revealed that models performed the poorest in locations with complex terrain along the coast of Antarctica and better over the sea ice zone. Data denial experiments applying Polar WRF showed that the assimilation of both radiosonde and UAV data improved the analyses of air temperature, wind speed, and humidity for most of the time. In the circumpolar Arctic, for the period January 2016 - September 2018, comparison of the ECMWF operational analyses, background fields, and observations showed that radiosonde soundings had a remarkable impact on improving the analyses. Soundings from Jan Mayen, Bear Island, and research vessels in the central Arctic were particularly beneficial. In the areas where the sounding network is reasonably dense, the quality of background field was more related to how radiosonde observations were utilized in the assimilation and to the quality of those observations. Data denial experiments applying the HARMONIE-AROME model for Fennoscandia for the YOPP SOP in February-March 2018 showed that an increased frequency of radiosonde soundings (without additional sounding sites) had much smaller impacts on the analyses than those generated by soundings from the central Arctic in summer 2018.
Detailed long-term hydrometeorological hindcast for Russian Arctic was created using regional nonhydrostatic atmospheric model COSMO-CLM for 19802016 with ~12 km grid and shared online partially onthe Figshare service.The hindcast includes about a hundred hydrometeorological variables at both surface and 50 model levels, and coversthe Barents, Kara and Laptev Seas.
The added values of high wind speed frequencies based on COSMO-CLM hindcast showed an increase compared to ERA-Interim, especially over Barents Sea, Arctic islands, seacoasts and mainland areas.Significant regional details in mean and 1% percentile temperature patterns manifested in relief and lakes: over Scandinavian, Eastern Siberian mountains, Taymyr highlands, Novaya Zemlya ranges.
Roshydromet Russian Arctic stations temperature and wind speed data were used to evaluate the COSMO-CLM hindcast. Mean wind speedbiases are within +-2 m/s and up to -5 m/s for 95% wind speed percentiles. Maximal temperature biases are within -4 C, 1% temperature percentile errors do not exceed -6 C.
Model capability to reproduce wind speed during strong downslope windstorms evaluated according to observations over Novaya Zemlya, Svalbard and Tiksi.According to stations extreme wind speed frequency and statistics is better for ASRv2 reanalysisthan COSMO-CLM hindcast. However, COSMO-CLM hindcast is better in most cases for maximal wind speed and extreme percentiles according to high-resolution SAR Radarsat-2 data.
Future plans include prolongation to 2019, sharing more data online; extreme and severe events statistics assessment (downslope windstorms, polar lows, MCAO climatologies using satellite data); quality estimation based on other datasets (ERA5, Arctic CORDEX, CARRA, satellites).
Atmospheric boundary layers at high latitudes mediate the fluxes of heat and momentum between the atmosphere and sea-ice, land or ocean surface and pose challenging tasks to weather and climate models. Strong stable stratification over ice surfaces has long been known to be difficult to represent in models, and mixed-phase cloud processes have been identified as an important issue in CMIP5 models. Here, I review these lonstanding model issues in high-latitude boundary layers and show how CMIP6 models represent atmospheric profiles and surface fluxes observed in the characteristic clear and cloudy states of the Arctic (and Antarctic) wintertime boundary layers.
Stochastic parameterisations are an important way to represent uncertainty in the deterministic forecasting models underlying ensemble prediction systems. Current stochastic parameterisation approaches use random correlation patterns that are unrelated to the atmospheric flow to induce coherent perturbations to parameterisations. Here we replace these patterns by accumulated tendency fields from parameterized physical processes in the HARMONIE-AROME system. Our rationale is that by perturbing the parameterisations with a field that reflects where parameterisations are most active, rather than random, the model obtains a more targeted increase in the degrees-of-freedom to represent forecasting uncertainty.
Here we study a large marine cold-air outbreak over the Norwegian Sea. Strong heat fluxes persisted near the ice edge, and shallow convection dominated in the center of the model domain. Perturbation fields are diagnosed from individual tendency diagnostics implemented in AROME-Arctic within ALERTNESS. Total physical tendencies for the horizontal winds, for temperature and humidity are accumulated with a time filtering throughout the 66 h forecast period.
Accumulated tendencies show overlapping and differing centers of activity. Wind parameterisations are active near the ice edge, and with smaller scale variability over land areas. Temperature tendency patterns show activity more confined to the ice edge, and the coast of northern Scandinavia. Such spatially coherent patterns of parameterisation activity are meaningfully related to current weather. Sensitivity tests of cloud parameterisation parameters in a single-column model version MUSC and the full model version illustrate our progress towards the use of diagnostic perturbation patterns for stochastically perturbed perturbations in the HarmonEPS system.
Winter precipitation measurements from standard instrumentation at synoptic stations are affected by the undercatch of solid precipitation in windy conditions. Verification against these under-estimated measurements can lead to the erroneous diagnosis of solid precipitation over-forecasts. Quality Control (QC) of operational verification systems then flags solid precipitation measurements in windy conditions, so that they are discarded prior to the calculation of verification scores. This selective screening, however, dramatically reduces the sampled precipitation events and systematically eliminates major snow storms (which usually occur under windy conditions). As a result, most hit events are not scored, while false alarms dominate the verification results, preventing once again the correct diagnosis of the forecast true quality.
The WMO Solid Precipitation Inter-Comparison Experiment (SPICE) has performed a multi-site inter-comparison and evaluation of instruments for measuring solid precipitation. Comparison with Double Fence Automated Reference installation enabled the quantification of the instrument catch efficiencies. The SPICE literature proposes then adjustment functions to correct the solid precipitation undercatch under windy conditions.
The impact of wind-induced undercatch on verification of regional and global models has been investigated over Fennoscandia and North America, during the YOPP winter Special Observing Period (Feb-March 2018). Verification of precipitation forecasts for the Canadian deterministic prediction systems is performed against QC, not QC, and SPICE-adjustedsolid precipitation measurements. Despite the uncertainty associated with the SPICE adjustments, verification results were found to be more reliable, consistent, and informative than against unadjusted measurements. Our recommendation for operational environments is to adjust the solid precipitation measurements prior verification.
Antarctica is the largest reservoir of continental fresh water on Earth: sensitivity to climate change may induce mass balance change and result in significant impact on global sea-level. The surface mass balance of the cap is mainly fueled by precipitation, which is expected to increase by the end of the 21st century according to climate projections. However, there is still limited knowledge and understanding of the processes involved because observations are limited as a results of remoteness and extreme weather conditions.
The OMM project dedicated to improving meteorological research and prediction at the poles (YOPP: Year of Polar Prediction) had a Southen Hemisphere special observing period between November 2018 and February 2019, during which unique observations were made, in particular at the Dumont dUrville station YOPP supersite in East Antarctica. Models were also run in this framework. In addition to the conventional approach the surface accumulation of precipitation the vertical dimension of snowfall is studied, allowing to account for microphysics and dynamics throughout the atmospheric column.
Snowfall occurrences and fluxes from various weather forecast and atmospheric circulation models are evaluated. The use of diagnostics to detect snowing events and of 3 scores exhibits model overestimation both in terms of frequency and intensity. A fair representation of subtle processes such as re-evaporation in the lowest levels even in global models is encouraging but progress is still needed to correctly account for the observations.
Blizzard conditions occur regularly in the Canadian Arctic, with high impact on travel and life there. These extreme conditions are challenging to forecast for this vast domain because the observation network is sparse and remote sensing coverage is limited. To establish occurrence statistics we analyzed METeorological Aerodrome Reports (METARs) from Canadian Arctic stations between October and May 2014-2018. We will show statistics for occurrence of blizzard conditions and for the fraction of blizzard occurrences that are clear sky, that is, due to blowing snow alone without precipitation.
In the Meteorological Services of Canadas National Lab West, we produce three products that forecast blizzard conditions from post-processed NWP model output. The blizzard potential (BP), generated from experts rules, is intended for warning well in advance of areas where blizzard conditions may develop. A second product (BH) stems from regression equations for the probability of visibility 1 km in blowing snow and/or concurrent snow derived by Baggaley and Hanesiak (2005). A third product (RF), generated with the Random Forest ensemble classification algorithm, makes a consensus YES/NO forecast for blizzard conditions. Receiver Operator Characteristic curves and critical success index scores show RF forecasts have greater accuracy than BP and BH forecasts at all lead times. These blizzard prediction models run with CCMEP global, regional, and high resolution operational NWP model output data. We will describe the products, provide verification, and show forecasts for a significant blizzard event. This work was recently published: https://doi.org/10.1175/WAF-D-20-0077.1 .
Atmospheric Reanalyses are widely used to estimate the past atmospheric near-surface state over the sea ice, providing crucial boundary conditions for uncoupled sea ice and ocean simulations. These products are widely used because physically consistent, available over the last 40 to 70 years, and with uniform spatial coverage. Nevertheless, previous research revealed systematic near-surface temperature biases over sea ice for most atmospheric reanalyzes, a fact that has been linked to a poor representation of the snow over the sea ice in the forecast models used to produce the reanalysis. Developed and continuously updated by the ECMWF, ERA5 is arguably one of the most mature and detailed reanalyses currently available, reaching a spatial resolution of 30km and a time resolution of 1h. As with other products, also ERA5 shows positive temperature biases over the Arctic sea ice when compared to in-situ and satellite observations (up to +10K in winter under clear-sky conditions), compromising the employment of this product in support of sea ice research. While ECMWF and other numerical weather prediction centers will likely correct this issue in future products, this study explores the possibility of improving the existing generation of reanalyzes, starting with the ERA5 2m and skin temperatures, by training a machine-learning algorithm that learns from in-situ and remote sensing observations. The impact of the correction on uncoupled sea ice and ocean simulations will be quantified and compared to the effect of tuning key thermodynamical parameters of the sea ice model: the snow conductivity and surface albedo.
The drive to develop environmental predictions systems that are seamless across both weather and climate timescales has culminated in the development and use of Earth system models for medium-range weather forecasts. One region where such coupling has the potential to significantly influence the meteorology is in the polar and sub-polar seas, where fluxes of heat, moisture and momentum are strongly influenced by the position of the sea ice edge. In this study we demonstrate that dynamic coupling results in improved sea ice edge position forecasts in the northern hemisphere in the medium-range compared to the uncoupled model. Further, this improves forecasts of boundary layer temperature and humidity downstream of the sea ice edge in some regions during periods of rapid change in the sea ice. Challenges and limitations, such as the quality of the ocean analysis and the inability of the coupled system to capture the rate of sea ice concentration change during periods of ice advance and retreat will also be discussed.
AROME-Arctic is the numerical weather forecast model for the European Arctic run operationally at MET Norway. The model is used by forecasters in Svalbard and Northern Norway, and is also used on yr.no for Svalbard. Although the model code is based on common cycles in MetCoOp and HIRLAM/ACCORD, developments in AROME-Arctic happen independently of these consortia. Implementations are mainly a result of dedicated projects targeting issues particular for a model in an Arctic domain, where synoptic observations are sparse, sea ice is present and remote sensing observations are of particular importance.
YOPP has been an important driver for developments in AROME-Arctic. We will in this presentation give an overview of the role of AROME-Arctic in some YOPP projects, and how these have led to concrete implementations in the operational model. We will give some insight on the general Research to Operations process, how feedback from forecasters impact decision making, and demonstrate how YOPP has contributed to improving forecasting capabilities in the European Arctic over the last five years and beyond.
Numerous socio-economic activities in the Arctic, such as transportation, tourism, search and rescue operations, and scientific fieldwork, are dependent on accurate and reliable predictions of local small-scale weather features. The complex terrain in Svalbard challenges the prediction of such atmospheric conditions in the operational kilometre-scale numerical weather prediction (NWP) model applied at the Norwegian Meteorological Institute. Increased model spatial resolution can potentially improve the quality of forecasts.
A set of NWP forecasts with 0.5 km horizontal grid spacing for winter periods from 2018 to 2022 are presented. The forecasts are compared to the operational NWP model (2.5 km grid spacing) at the Norwegian Meteorological Institute, and observations from permanent weather stations and field campaigns including automatic weather stations, a tethersonde and measurements on mobile platforms.
Increased model resolution improves how the model captures terrain-induced flows, such as valley wind channelling, lee waves, gap winds, drainage flows and wake winds, which is reflected in the objective verification scores for wind speed. The impact on near-surface temperature is more complex and depends on the weather situation. For both wind speed and temperature, there are large differences between the 0.5 km forecasts and the lower resolution operational system. The work demonstrates the potential of sub-kilometre NWP systems for forecasting weather over complex Arctic terrain. The information on the benefits of the sub-km resolution system is used for further model development and for studying the feasibility of employing such a model system in operational use, also considering the computational costs.
Modeling the interactions between the ocean and atmosphere is important to both advance our understanding of the physical mechanisms operating in rapidly changing Arctic environments and to improve the predictability of extreme weather events, wave activity, and sea ice behavior. This study presents the newly developed two-way coupled atmosphere-wave numerical weather prediction (NWP) system in the Arctic as well as an evaluation of the coupled model performance and sensitivity experiments. We use a convective-scale weather forecasting system for the European Arctic in combination with sea ice and wave models to analyze the impact of a more accurate description of the kilometer-scale characteristics of the sea ice and waves in a coupled regional Earth system model with a 2.5 km resolution. The HARMONIE-AROME configuration of the ALADIN-HIRLAM NWP system (AROME-Arctic) is coupled to the wave model WaveWatch III using the OASIS3 model coupling toolkit. Sea ice coupling is currently captured through the utilization of a 1 dimensional thermodynamic sea ice scheme contained within the surface component of AROME-Arctic. To assess the coupled models realism and uncertainties we use a multitude of observations, including multi-satellite significant wave height products, wave-in-ice measurements, and standard satellite and in-situ observations. We will show the results from the assessments of the coupled atmosphere, sea ice, and wave model with comparisons to satellite observations such as Advanced Scatterometer surface wind data as well as significant wave height based on Jason-3 and Sentinel-3A altimeter data.
To improve our capability to predict Arctic sea ice and climate,we have developed a coupled sea ice-atmosphere-ocean-wave model configured for the Arctic with sufficient flexibility. Specifically, Los Alamos Sea ice Model is coupledwith Weather Research and Forecasting Model, Regional Ocean Modeling System, and Simulating Waves Nearshore Model. A number of sensitivity experiments with different physics options (i.e. ice thermodynamics, cloud microphysics, ocean advection, sea ice-wave interactions) have been performed to understand physical links between Arctic sea ice changes and various physical parameterizations, and determine the optimal physics configuration that provides reasonable simulation of Arctic sea ice and climate. To generate realistic and skillful model initialization needed to improve predictive skill of Arctic sea ice, Parallel Data Assimilation Framework has been implemented into the modeling system to assimilate satellite-based sea ice parameters (i.e. concentration and thickness) using a localized error subspace transform ensemble Kalman filter. We have conducted Arctic sea ice prediction during the melting season in recent years. Results show that this regional coupled modeling system can reasonably predict Arctic sea ice evolution during the melting season, and remains skillful beyond the melting season, which may have potential values for stakeholders making decisions for socioeconomical activities in the Arctic.
The Spanish Meteorological Agency (AEMET) is in charge of obtaining instrumental measurements of atmospheric variables at the Antarctic Spanish stations as well as making weather forecasts to guarantee the personal safety and optimize scientific and logistic activities. For this reason, we have participated in the Year of Polar Prediction, providing observations as well as carrying out small scientific and operational projects. During the Year of Polar Prediction, AEMET has provided data from the two main Spanish stations: Juan Carlos I in Livingston Island and Gabriel de Castilla in Deception Island, both in the South Shetland Islands. We have also obtained data from the eastern Antarctic Plateau through a scientific-educational project consisting of a meteorological station (M-AWS) onboard a zero-emissions polar vehicle called Windsled. Regarding prediction activities, we have adapted our high-resolution (2.5 km horizontal resolution) ensemble prediction system AEMET-SREPS to the Antarctic Peninsula, running 12 multi-boundary conditions and multi-model members during the summer season. AEMETs future plans in Antarctica are to modernize and install new surveillance AWSs, increase the number of members of the AEMET-SREPS to 16 and to install a double-fence automated reference (DFAR) in the Spanish Antarctic Station Juan Carlos I to serve as a reference platform of precipitation in the region. All these activities will benefit in many ways the scientific activities of the Spanish Polar Program in Antarctica.
Seas of the Eurasian Arctic are of key interest to a number of scientific and applied topics including transpolar drift, fresh water and sediments input as well as area of the most intense navigation. Due to a number of reasons - both logistical and natural the Eurasian Arctic was characterized by the least density of the buoy observations during the last decade. The situation changed since the beginning of YOPP as the AARI started to deploy the SVP-B buoys within cooperation with the WMO/EUMETNET/IABP. Totally 40 ice strengthened buoys of SVP-B /iceST-B type were manufactured by the Russian Marlin-Yug company and deployed by the institute in the seas from Barents to Chukchi during March 2018 July 2021 using expeditions of opportunity. During most of their operating period all buoys contributed to the WMO GBON in the Eurasian Arctic with hourly SLP and surface temperature measurements with average/median operational time 213/166 days. Significant features of the buoy drift trajectories included transcoastal drift from Chukchi to Laptev Sea or a much slower annual drift of a buoy to the North Pole a year after MOSAiC campaign. Lessons learned include that lifetime fully depends how homogeneous is the environment regardless of its type, or drogue utilization should be carefully considered or that additional sensors inside the buoys hull would facilitate estimates of the buoy status. Experience gained during the YOPP gives an incentive to support of the buoys network in the Eurasian Arctic and extension of their types during the next years.
Results of the study of the dynamic state of drifting ice in the MOSAIC expedition are considered. The data were obtained using the spatial arrangement of autonomous seismic stations on the ice. The development of physical and mechanical processes in the ice under various meteorological conditions is reflected in the graphs of intense events.
New data about the peculiarities of compression and ridging phenomena have been obtained. Vertical oscillations of ice in the periods range up to 35 seconds or more are described. The graphs are of the dispersive nature of waves arriving from distant storm phenomena. Such results allow to estimate the distance to the region of origin of a gravitational wave.
Data on horizontal oscillation in ice are considered as signs of stress drop during horizontal shifts in solid ice. Periodic semi-daily bursts of displacement velocity lasting several hours are noted. It is assumed that these are signs of the mechanical interaction of ice fields during tidal or inertial oscillation/ movements in the ocean.
Greenland ice sheet experienced an intensive melting in the last decades, which may affect the freshwater budget of the North Atlantic leading to changes in the Atlantic Meridional Overturning Circulation. Yet, to obtain a realistic representation of the melting using an interactive ice sheet component remains a computing challenge for global climate model. Here we propose to externally force a set of historical simulations of two climate models: EC-Earth3 and IPSL-CM6-LR with an observation-based estimate of the freshwater fluxes spanning from 1960 to 2014. The estimate is based on runoff fluxes coming from Greenland land ice sheet and surrounding glaciers and ice caps. Input from iceberg melting is also included and spatially distributed over the North Atlantic following an observed climatology. We investigate the impact of the supplementary freshwater input on the convection in the North Atlantic and the Nordic Seas and on the surface salinity in the Arctic, which was increased in previous hosing experiments.
Recent changes in the Arctic minimum sea ice extent are most prominent in the Beaufort and Chukchi Seas with episodic formation of a polynya at the center of the Beaufort Gyre as observed in e.g. 2006 and 2021. These changes are coincident with a significant warming of the summer Pacific Waters in the Canada Basin observed at approximately 60-100 m depth. These observations question the concept of an Amerasian Basin composed of two layers largely independent from one another, with a sharp halocline insulating the freezing surface layer from the subsurface heat reservoir formed by summer Pacific Waters. The goal of the project is to estimate vertical ocean heat fluxes in the Canada Basin associated with the ventilation of summer Pacific waters and their multi-year impact on the sea -ice mass balance. To this end, we use a coupled 1.5D ice-ocean model of the Canada Basin forced by lateral ocean heat flux from Pacific summer waters and constrained by observed AIDJEX and ITP temperature and salinity profiles. This model provides bounds on vertical ocean heat fluxes in the Canada Basin and an estimate of their impact on the sea ice mass balance. Finally, we discuss the impact of this missing vertical ocean heat flux for General Circulation Models that generally misrepresent Pacific Waters in the Canada Basin.
Atlantic water is a major heat source for the Artic Ocean, and any changes in the Atlantic water inflow can affect the heat balance and sea ice in the region. To understand the decadal variations of the ocean currents, temperature and salinity, NEMO 3.6 is implemented in the Arctic Ocean, forced by PHC temperature (salinity), GLORYS currents and JRA-55 atmospheric surface fields (1958-2019). Compared to observations, NEMO can reproduce mean sea ice, water temperature and salinity. In addition, the ocean temperature and salinity in the Barents Sea tend to increase in recent decades, showing significant decadal variations. Moreover, there are increased Atlantic water inflows in the 1960s and 1990s. While the increases in the ocean temperature and salinity are associated with the decadal variations of atmospheric surface forcing, the changes in the Atlantic water inflow through Fram Strait are correlated with the storm density near Fram Strait. When there are fewer storms near Fram Strait, the northwestern Barents Sea and Eurasian Basin are dominated by northerly wind anomalies, which tend to increase fresh water transport from the central Arctic Ocean to the northern Barents Sea, which reduces surface mixing and enhances water volume transport through Fram Strait.
The Southern Ocean (SO) dynamics, and the various fronts of the Antarctic Circumpolar Current in particular, are well known to display a very energetic variability covering a wide range of spatial and temporal scales. Since a substantial fraction of such variability is known to be intrinsic, and therefore basically chaotic, predictability in this part of the world ocean is particularly poor.
In this context, the YOPP-endorsedIPSODESprojectis aimed at improving process understanding concerning the predictability of the SO dynamics through ensemble simulation (ES) hindcasts analyzed by means of various statistical techniques supported by dynamical interpretations, with special focus on multiscale interactions linking high-frequency (up to seasonal) and low-frequency (interannual and larger) variability. IPSODES uses existing state-of-the-art eddy-permitting global ocean-sea ice model ESs and coupled global atmosphere-ocean-sea ice model ESs developed for decadal climate predictions. Moreover, new ESs performed with a regional ocean model specifically developed for IPSODES are carried out: sensitivity numerical experiments to assess model uncertainty are performed with these new simulations. The study of transport of marine debris provides an application of such modelling effort, and contributes also to model validation through the use of an available valuable data set.
This contribution illustrates advances achieved so far in IPSODES towards improving our understanding of the predictability properties of oceanic variability of the SO dynamics.
Canada’s vast, heterogeneous landscape poses numerous challenges to weather and environmental prediction. Among these challenges, providing accurate estimates of current and future conditions in the Canadian Arctic is one of the greatest. Few in situ measurements, harsh conditions, and relatively poorly understood physical processes severely limit the skill of forecasts. Rapid changes at high latitudes in response to a warming planet provide an additional level of complexity. Moreover, these changes are occurring in an increasingly digital world with greater needs for accurate and user-relevent environmental prediction products.
In response to these needs Environment and Climate Change Canada (ECCC) has participated strongly in the Year of Polar Prediction (YOPP). Here, we describe the improvements to prediction systems made as part of YOPP. These include the development of a high-resolution pan-Arctic coupled atmosphere-ice-ocean forecasting system to study the importance of small-scale interactions on polar forecasts. New methods were also developed to provide automated retrievals of SAR data to improve initial conditions. A coupled global ensemble system was developed, in part, to provide improved long-range sea ice forecasts. New verification metrics and calibration techniques were necessary to adequately understand forecast errors and provide reliable products. An overview of these and other developments will be presented with a view to challenges that lie ahead.
Increasingly unpredictable weather patterns and changing sea ice has made it more difficult and riskier for Inuit to hunt and travel safely. Inuit knowledge supporting safe travel is also being affected and shared less often between generations. Inuit increasingly use online weather, marine, and ice products and services to develop locally relevant forecasts to support travel safety on the land. Additionally, Inuit are utilizing technology to monitor their own sea ice conditions (Smartice.org) and rejuvenating their sea ice travel knowledge to teach the next generation how to plan, prepare, identify, and test the ice for safety while traveling.
This plenary will feature Governor General’s Innovation Award winning speakers, Indigenous Knowledge holders Mrs. Natasha Simonee and Mr. Andrew Arreak (Mittimatalik, Nunavut) and community-based researchers Dr. Natalie Carter (McMaster University) and Dr. Katherine Wilson (SmartICE). They will discuss a range of topics including:
Challenging aspects of weather prediction in the Arctic, including fog formation and stable boundary layer are strongly related to surface conditions. The Arctic land surface is subject to a number of highly non-linear processes related to freezing and thawing of soil and snow water, directly affecting moisture and energy fluxes eventually modifying the atmospheric state. In numerical weather prediction models, the surface schemes tend to be fairly simple compared to state of the art surface models used in climate research and often act as a sink for errors. An improved representation of the land surface in numerical weather prediction models will not only increase the potential for better forecasts, but also opens for novel use of observations in validation and data assimilation. In this work the AROME-Arctic forecasting suite is set up with a multi-layer, diffusive soil and explicit snow scheme in a preoperational environment. By solving the heat and moisture transport explicitly at each model depth, the multi-layer schemes can keep memory of past weather that will influence forecasts through land-atmosphere interactions the following days and weeks. We compare these multi-layer schemes with the operational system, where the representation of the surface is done by a 3-layer force restore method and a single layer snow scheme. Preliminary validation results show improvement over the reference during the snow melting season, and in particular reduced errors of 2 metre temperature.
A new, simple parameterisation scheme for heat and moisture (scalar) exchange over sea ice and the marginal ice zone is tested in the Met Office Unified Model as used operationally for weather and climate prediction. The new scheme introduces the influence of aerodynamic roughness on the relationship between scalar and momentum exchange over uninterrupted sea ice, in line with long-standing theory and recent field observations. In model sensitivity experiments, the atmosphere is sensitive to the change from the current operational scheme to the new scheme. During a strong cold air outbreak event over the Iceland and Greenland Seas, differences in surface sensible heat flux over the marginal ice zone are typically 30-80 W m-2and are associated with differences in low-level air and ice (surface) temperatures of 1-1.5 K. The impact of the new scheme extends hundreds of kilometres downwind, with changes in the boundary layer evolution and associated weather conditions. Simulations with the new scheme generally outperform those using the existing scheme in comparisons with Arctic field observations of surface heat fluxes and low-level atmospheric conditions. However, these improvements are conditional on the prescription of an appropriate surface roughness length for momentum over uninterrupted sea ice, which is known to vary significantly on a regional and seasonal basis due to differences in sea ice morphology.
Turbulent fluxes in the atmospheric boundary layer have a large impact on the development of cyclones. For example, Ekman pumping is a well-known mechanism by which friction leads to cyclone spin-down, dampening a low-level cyclonic circulation through a reduction of potential vorticity (PV) above the cyclone centre. Previous studies have used a PV framework (PV is not materially conserved in the presence of frictional and diabatic processes) to identify the mechanisms by which boundary layer processes impact mid-latitude cyclones. However, boundary layer processes acting in Arctic cyclones have not yet been investigated. Differences are expected in the Arctic due to the additional sea ice surface, and the variety of different cyclone structures. In this work, a boundary layer PV tendency equation is used to investigate the role of boundary layer processes in the evolution of two Arctic cyclone cases from summer 2020 during the MOSAiC study period. One cyclone develops as a baroclinic wave with a low-level warm-core structure. The other cyclone has a markedly different evolution, developing with a tropopause polar vortex, forming a long-lived vertically stacked cold-core structure. Using ECMWF ERA5 reanalysis and IFS model runs, PV tendencies arising from the dominant boundary layer processes are demonstrated. These PV tendencies are related to the cyclone depth-integrated circulation, highlighting the different impact of boundary layer processes on the evolution of each cyclone. Understanding these mechanisms is important to inform model development in the Arctic, especially over sea ice where there are uncertainties in the representation of turbulent exchange.
Polar lows (PLs) are intense maritime mesoscale cyclones associated with severe weather such as gale-force winds and heavy snow showers. These storms form in sub-Arctic and Arctic basins as well as in the Southern Ocean, near the sea-ice edge and the snow-covered continents during marine cold air outbreaks. Given their small size and short lifetime, PLs are challenging to forecast.
We conducted a case study of a PL that made landfall in Norway on 25 March 2019. The PL was simulated using the developmental version of the convection-permitting Canadian Regional Climate Model (CRCM6/GEM4) with a grid mesh of 2.5 km and 62 vertical levels. The model was driven by ERA5 reanalysis with a grid spacing of 31 km, and 1-hour atmospheric fields. An ensemble of eight short-range forecasts were obtained by initializing the model every six hours from 23 March at 00:00 UTC onward. The simulation was verified against surface observations in Norway and available drifting buoys to assess the impact of initial conditions on the representation of the PL, as well as the skill of the model at reproducing the observed PL. The results showed that the two latest initialised simulations captured best the development of the PL, confirming that the PL forecast skill strongly depends on initial conditions. Finally, the development mechanisms of the PL were analysed using the simulated fields of the best simulation. In particular, the role of baroclinic conversion and surface heat fluxes was analysed.
The Arctic has experienced dramatic changes over recent decades, and is projected to have ice-free summers by the 2050s in the future climate scenarios. It has been suggested that these changes in environmental conditions could lead to changes in extreme cyclones and the air-sea interactions. Coarse resolution GCMs tend to underestimate the number and intensities of these small-scale systems, and therefore lead to deficiencies in their estimates for the poleward energy transport into the Arctic, and associated surface heat fluxes and radiations. In our study, we conducted a simulation of the Arctic climate using a high-resolution implementation of the Polar WRF3.6 model, driven by the coarse resolution climate model HadGEM-ES2 outputs, following IPCC5 climate scenarios RCP8.5 4.5 and 2.6 over the period 1970-2099. Polar WRF results provide significantly improved simulations of the frequency and intensity of cyclones, compared to the HadGEM2-ES simulations over the historical period. In the RCP8.5 climate scenario, by end-of-the-century, the surface circulation system the Beaufort High becomes weakening in winter (DJF) which is associated with the increased cyclones over the west-central Arctic; while the Beaufort High becomes intensified in summer (JJA), which is associated with increased SLP over the polar continents. There are some differences in the changes of Arctic cyclones between the HadGEM results and Polar WRF simulations. In the RCP4.5 and 2.6 scenarios, these surface systems show consistent but weaker trends. We also discuss the mechanisms for such responses.
The atmospheric water cycle in the European Arctic is strongly modulated by cold air outbreaks (CAOs) and warm air intrusions. We apply Lagrangian particle dispersion model based on operational weather prediction model simulations, together with observations taken during the ISLAS2020 field campaign in Ny lesund for characterising source-sink relationships in the water cycle. During the field campaign, we observed an alternating sequence of CAOs and warm air intrusions (WAI) over the key measurement sites of Svalbard and northern Norway. Meteorological and stable water isotope measurements have been collected at multiple sites both upstream and downstream of the CAOs and WAIs. The Lagrangian model FLEXPART is run with the input data from the regional convection-permitting numerical weather prediction model AROME-Arctic at 2.5 km resolution to investigate transport patterns.The combination of observations and model simulations allows us to quantify the connection between source and sink for different weather systems, as well as the link between large-scale transport and stable water isotopes. Mixing of air between the boundary layer and free atmosphere is an important factor influencing the conservation of the stable water isotopes during transport. We perform a range of sensitivity studies with different turbulent modes affecting mixing and boundary layer growth to assess the dependency of conservation on model parameterizations. Our findings can thereby contribute to a better understanding of processes in the water cycle and the degree of conservation of isotopic signals during transport.
Those travelling on vessels in the Canadian Arctic rely on accurate weather, water, ice, and climate (WWIC) information to make safe navigational decisions. Despite the necessity of accurate WWIC information, it is currently unknown what services are being accessed by users on vessels in the Canadian Arctic, and whether user needs are being fully met by available WWIC products. To address this gap, a mixed-methods survey using Qualtrics online software was established to target individuals who have experience using WWIC information while travelling onboard marine vessels of various sizes and types (e.g., cargo ships, yachts, and cruise ships) in the Canadian Arctic. Preliminary results showed that just over half of survey participants (63%) noted that their navigation needs were met frequently, but 68% said that their voyages would benefit from additional WWIC services. Participants identified sea ice concentration and drift as the two most important information needs to support safe navigation. Most respondents (56%) said they need information about sea ice concentration on a one-day time scale, and some (39%) indicated they need access to real-time information. Lancaster Sound and Baffin Bay were identified as regions where information about sea ice concentration was regularly inaccurate and where improvement is needed. This work is ongoing, and further analysis of text responses will be completed using constant comparison and thematic coding. Based on participant responses, results will be shared with service providers in order to help stimulate the co-production of meaningful WWIC products to aid safer vessel traffic in the Canadian Arctic.
Weather, water, ice, and climate (WWIC) information and services are not meeting the needs of Inuit and northerners needs. This is especially problematic because weather, water, and ice conditions in Inuit Nunangat (Inuit homelands in the Canadian Arctic) are increasingly unpredictable. Social and political changes have also impacted the intergenerational transfer of Inuit knowledge and subsistence harvesting practices, creating challenges for Inuit to travel safely on the land, water and ice. Our collaborative approach focused on engaging community-based researchers in creating and facilitating a survey to document WWIC uses and needs, to understand how environmental information is shared and used in Inuit communities.
We will share responses and key messages for polar service providers from surveys in five communities in Nunavut: Arviat, Gjoa Haven, Iqaluit, Sanikiluaq, and Pond Inlet. Thirteen Local Research Coordinators (LRC) independently facilitated 285 questionnaires in their home communities. Preliminary results were analyzed during a collaborative analysis workshop involving LRCs, Elders, and academics. We will highlight qualitative and quantitative results including Nunavummiut-identified: 1) travel habits (spatial, temporal, and purpose); 2) environmental conditions that inform decision-making about travel safety; 3) information sources from national, regional and other polar service providers (source type, access, and challenges); and 4) key messages related to provision and use of WWIC information. We present these findings to enhance understanding of Inuit uses and needs for WWIC information, and articulate Inuit-identified recommendations to inform service providers as they work to tailor products to meet polar users needs
Weather, water, and ice conditions in Inuit Nunangat (Inuit homelands in the Canadian Arctic) are increasingly unpredictable. Social and political change has impacted intergenerational transfer of Inuit knowledge and subsistence harvesting practices, creating challenges for Inuit to travel safely on the land, water and ice. Weather, water, ice, and climate (WWIC) information and services are not meeting Inuit Nunangat communities needs. Our goal is to build a broader understanding of available WWIC information, and how it is shared and used in communities.
We will share our collaborative approach that follows the Aajiiqatigiingniq Research Framework and involves: 1) building relationships and meaningful community engagement; 2) building understanding; 3) using narratives and diverse methodologies to document lived experiences; and 4) relational consensus building. We will emphasize how we used this process throughout survey development, facilitation, and collaborative analysis working with 13 Local Research Coordinators (LRCs) across 5 five Nunavut communities: Arviat, Gjoa Haven, Iqaluit, Pond Inlet, and Sanikiluaq. Emerging from a collaborative analysis workshop, LRCs identified key messages for local, regional, national, and international polar service providers surrounding: 1) provision of real-time weather information; 2) the level of detail and specificity of information needed; 3) installation of additional weather and tide stations; 4) raising users awareness of services; 5) enhancing access to web and mobile applications; and 6) improving communication sources reliability. We will present these messages in the context of societal and economic implications of (not) having accessible, relevant, and useable forecasts, and describe the process involved in building consensus around these messages.
A combination of less predictable environmental conditions and a reduction in the intergenerational transfer of knowledge and skills create challenges for Inuit in travelling safely on land, water, and ice. This has led to an increase in search-and-rescue incidents in Inuit Nunangat (Inuit homelands in Canada) over the past decade. In response, Inuit are seeking diverse weather, water, ice, and climate (WWIC) information and services to support their travel decision-making.
Through an ArcticNet-funded and YOPP-endorsed project, we co-developed a survey to better understand how Inuit use and access WWIC information and services in support of safe travel. Survey results contribute to a baseline understanding of travel habits, and the WWIC conditions checked and information sources used by Inuit when making travel decisions.
Between December 2019 and November 2020, 66 Iqalungmiut (people of Iqaluit) completed the survey. Respondents identified knowledge of wind speed and direction, and a period of clear weather, to be the most important environmental variables when planning safe travel. When required, this information was accessed through a range of available WWIC services and products (e.g., weather forecasts, tide tables). Despite the prevalence of electronic technology to access and share WWIC information, there continues to be a strong reliance on personal observations and knowledge (98%), as well as local word of mouth about WWIC conditions (97%), when making safe travel decisions. These and other survey responses will be discussed in the presentation. Results of this project can help polar service providers enhance their WWIC products and services.
The Canadian Centre for Climate Services (CCCS) provides Canadians with information and support to consider climate change in their decisions.
Canadas climate has changed and will continue to change. This means that people need to consider climate information in their decision-making. To help facilitate this, CCCS offers reliable climate information, data, and tools, and provides client support to help advance climate resilience across Canada. Some key offerings from the CCCS are client support and training, including a national support desk. CCCS also supports climate data portals that provide information suitable for a diverse set of users, including Climate Atlas of Canada, ClimateData.ca and PAVICS.
CCCS acknowledges that data for the North is often hard to access and that datasets are sparse and can have large geographical gaps and periods with missing data. Because of this, CCCS is working to address northern climate services needs by assisting northern clients, undertaking needs assessments, producing inventory of available products, conducting outreach or engagement activities, and developing and supporting projects to enhance northern climate products. For example, CCCS is working to develop community climate summaries for northern communities. More work is needed to further tailor information and tools for northern climate information and data users and CCCS is working to engage with northern data users to better understand their needs. This presentation will share early learnings on our efforts in the North and provide opportunities for feedback.
A review of current UK Met Office Arctic modelling capability, covering both the atmosphere and ocean over timescales ranging from short-range to seasonal and climate, is presented. We explore some of the modelling challenges and future developments that are required to deliver services to support users and decision-makers operating in the region.
A selection of case studies is used, with a focus on those developed by people operating in the region, to provide greater insight into understanding the benefits associated with different model configurations. For example, increasing model resolution, application of an ensemble (probabilistic) approach as opposed to deterministic and whether it is more effective to improve physical processes/calculations within the models or increase processing of available observation data within data assimilation systems. To achieve this, identifying and establishing international partnerships will be essential and collaborative efforts are outlined as part of this presentation.
The overarching goals of the SACIA (Signatures of Aerosol-Cloud Interaction over the Arctic) SACIA-2 projects are to characterize aerosol, cloud and aerosol-cloud interaction events using ground-based remote sensing (RS) and surface microphysics measurements with (i) a focus on the PEARL (Polar Environment Arctic Research Lab) at Eureka, NU and (ii) a broader satellite-based RS context employing retrievals from near-Eureka orbits as well as pan-Arctic retrievals. These measurements are in turn employed as evaluation data for GEOS-Chem TOMAS (TwO Moment Aerosol Sectional) model for detailed aerosol simulations and CRCM6 (Canadian Regional Climate Model v6) for cloud simulations.
We will present results obtained over the past five years. These results include (a) the analysis of specific types of aerosol events from surface and ground-based RS measurements at PEARL as well as satellite-based RS measurements across the Arctic, (b) linkages between surface and columnar measurements for different aerosol types at PEARL, (c) climatological-scale AERONET analyses at PEARL and other Arctic sites, (d) CALIOP/CloudSat-based evaluation of ice crystal simulations during the polar winter, (e) the RS signature of warm water clouds at PEARL and across the Arctic during the polar spring and (f) aerosol-cloud interaction analyses of 1st and 2nd indirect effects using, respectively, a phenomenological analysis of pan-Arctic MODIS retrievals and surface microphysical retrievals combined with TOMAS simulations at Eureka and (g) the analysis of tropospheric water cloud formation related to the dynamics of PSC (polar stratospheric cloud) formation and water vapour transport during the extreme spring-2020 ozone-hole event over Eureka.
Warm biases in near-surface temperature in nocturnal stable boundary layers over snow-covered surfaces pose a long-standing issue for numerical weather prediction models. Past studies have connected these biases to shortcomings in the surface scheme, the surface-atmosphere coupling, and the employed physical parameterisation schemes. Here, we investigate the contributions from parameterised processes in the operational weather prediction model AROME-Arctic, in use at the Norwegian Meteorological Institute. We utilise a novel combination of tools that (1) include the output of individual temperature tendencies, and (2) allow for the output of selected variables, at model time-step resolution (75 s). Focussing on the Sodankyl supersite in Finland during YOPP SOP-NH1, we analyse the near-surface temperature response of two surface scheme configurations.
Two different boundary layer regimes, termed here coupled and weakly coupled, form in close spatial proximity in the simulations. The coupled regime is characterised by a continuous turbulent exchange between near-surface levels and positive turbulent heating rates (~ 2 K/h), yielding the anticipated warm bias of up to 7 K. The weakly coupled regime is characterised by smaller turbulent exchange and negative turbulent heating rates close to the surface (~ -2 K/h). The weakly coupled regime does not exhibit a warm bias and agrees well with Sodankyl observations. The new surface scheme enhances the characteristics of both regimes. Our approach successfully disentangles the spatial and temporal interplay between parameterised processes and provides valuable insights for further model development and scientific research.
The YOPPsiteMIP is designed to facilitate process-based validation of numerical weather prediction (NWP) models during a few Special Observing Periods (SOPs). One key component of YOPPsiteMIP are the Merged Observatory Data Files (MODFs) being created for several well-instrumented polar locations. MODFs are being designed in collaboration with interested scientists at NWP centers and will contain, to the extent possible, high-resolution observations of the same geophysical variables that will be provided in the model output data files produced by participating NWP centers for those same locations. How do we ensure that multivariate observational files created by researchers at several institutions are as similar as possible, in terms of nomenclature, metadata, and structureand also comparable to model-output files created by scientists at multiple NWP centers? A series of tables in a 2018 white paper, listing model variables and the measurements against which they could be compared, has evolved into a published tool providing guidelines for creating MODFs with consistent variable names and metadata. This updatable H-K Table is available in both human- and computer-readable forms. It relies on standards and conventions commonly used in the earth sciences, including netCDF encoding with CF Conventions. The prescribed metadata make data provenance clear and encourage proper attribution of the observations. The H-K Table enables observational groups to create modeller-ready MODFs using current requirements and their software of choice, and gives NWP partners guidance in creating comparable model output files.
Sodankyl Supersite contributes to the Site Model Inter-comparison Project (YOPPsiteMIP) providing in-situ observations to evaluate and further improve numerical weather prediction (NWP) models for the Arctic. The supersite accommodates a unique integrated observation system that monitors the interaction between the Earths surface, snowpack, biosphere and the atmosphere employing a suite of automated sensors and manual monitoring programs. The multidisciplinary and comprehensive dataset is ideal for the process-oriented model evaluation envisaged in the YOPPsiteMIP project. The supersite is located in the Arctic boreal forest zone of northern Finland (67.367N, 26.629E, 179m). The environment is characterized by alternation of patches of dense and sparse forest, wetland, lakes, and rivers. Each of these surface types contributes to the land scene captured in model grid cells and in the footprints of satellite sensors. Hence, the supersite includes disseminated stations and instrument installations over a large area to measure the key variables for the processes specific to the different surface types. The presentation will describe the structure of the Sodankyl Merged Observatory Data File (MODF) created to facilitate the comparison with the NWP model outputs, highlighting the different observational sites and the observations carried out in each of them.
The diurnal water vapour cycle is a critical component of the hydrological cycle and an important qualifier variable due to its dependence on multiple processes. Yet, very few measurements of this important process exist in the Arctic. The Vaisala pre-production Differential Absorption Lidar (DIAL) for water vapour was installed in late 2018 at the Iqaluit, Nunavut (63.75N, 68.55W) Environment and Climate Change Canada (ECCC) supersite. The DIALs high vertical and temporal resolution make it an excellent tool for measuring height-resolved diurnal water vapour cycles.
We present height-resolved diurnal water vapour cycles measured by the DIAL and integrated water vapour (IWV) diurnal cycles from the co-located and Global Positioning System (GPS) and compare them to the ECMWF Reanalysis 5th Generation (ERA5) model and the ECCC Numerical Weather Prediction (NWP) model GEM HRDPS (Global Environmental Multiscale- High Resolution Deterministic Prediction System). Both models reproduce the DIALs diurnal water vapour cycle in phase in the first 1 km of altitude. ERA5s amplitudes are significantly smaller than the DIAL amplitudes at all altitudes; GEM HRDPS amplitudes are consistently larger in the first few hundred meters and smaller above 1 km. Neither ERA5 nor GEM HRDPS are able to reproduce the 12-hr component of the diurnal cycle in either the height-resolved or IWV cycles, suggesting that the representation of some underlying process in the models is incomplete. In conclusion, the numerical products are able to reproduce the overall behaviour of the diurnal cycle, but certain altitude regions require deeper investigation.
Numerical systems used for weather and climate predictions have substantially improved over the past decades. Numerical prediction systems have reached a sufficient level of maturity to examine and critically assess the suitability of Earths current observing systems remote and in situ, for prediction purposes. They can also provide evidence-based support for the deployment of future observational networks. We illustrate this point by presenting recent, co-ordinated international efforts focused on Arctic observing systems, led in the framework of the Year of Polar Prediction and the H2020 project APPLICATE. We highlight that existing state-of-the-art datasets and targeted sensitivity experiments produced with numerical prediction systems can inform of the added value of existing or even hypothetical Arctic observations, in the context of predictions from hourly to interannual timescales. Based on these efforts we suggest that (a) conventional in situ observations in the Arctic play a particularly important role in initializing numerical weather forecasts in winter, (b) observations from satellite microwave sounders play a particularly important role in summer, and their enhanced usage over snow and sea ice is expected to further improve their impact on predictive skill in the Arctic region and beyond, (c) the deployment of a small number of in situ sea-ice thickness monitoring devices at strategic sampling sites in the Arctic could be sufficient to monitor most of the large-scale sea-ice volume variability, and (d) sea-ice thickness observations can improve the simulation of both the sea ice and near-surface air temperatures on seasonal time-scales in the Arctic and beyond.
An objective of the Sea Ice Rheology Experiment (SIREx) was to compare the different approaches for representing rheology in sea ice models. Because SIREx is an intercomparison of models with a wide range of spatial and temporal resolutions, using different forcing fields and parameterizations, it is difficult to draw strong conclusions and to identify why a simulation performs better than another one. Nevertheless, the results of SIREx suggest that yield curves with a larger ratio of shear strength (S*) over compressive strength (P*) tend to better simulate deformations. Bouchat and Tremblay 2017 also concluded that increasing the ratio S* over P* leads to deformations in better agreement with observations. Compared to the standard ellipse, both approaches of reducing P* while keeping S* constant or increasing S* while keeping P* constant led to more realistic deformations. Using additional metrics (ice thickness and spatial scaling), Bouchat and Tremblay 2017 concluded that the former approach (reduced P*, S* constant) should be favored. Overall, this leads to a smaller yield curve than the standard one. We wish to revisit this conclusion. We argue that the yield curve should be larger than the standard one. This hypothesis is proposed following simulations that exhibit too thick ice and an underestimation of landfast ice in tidally active regions (Lemieux et al. 2018). We will show the impact of larger yield curves using a coupled ice-ocean model. Results at 12-15 km and 4-5 km resolutions will be presented and evaluated against drifting buoys, deformations and landfast ice data.
Narrow lines of deformation dominate sea ice dynamics. These lines are called linear kinematic features or LKFs. High-resolution sea ice models can recreate LKFs. However, the intersection angles between these LKFs are too large. In other words, the models do not create enough small and acute intersecting angles. The overestimation affects the models capacity to predict sea ice motion after a few days. In an idealized setup, we investigate sea ice viscous-plastic rheologies with non-elliptical yield curves, namely the teardrop yield curve and the Mohr-Coulomb yield curve. Results show that they can create smaller angles than the widely used elliptical yield curve. These yield curves are good candidates for use in state-of-the-art, high-resolution sea ice models; and could improve sea ice dynamics predictability.
We investigate the spread-error relationship in Environment and Climate Change Canadas (ECCCs) Global Ensemble Prediction System using the relationship between the spatial probability score (SPS) and the integrated ice edge error (IEEE) to give information on the spread in probability.
Deterministic scores from GEPS and a companion deterministic system, the global deterministic prediction system (GDPS) show enhanced predictiability over persistence for all but the months of May and June, when problems concerning the forecasting of sea ice in shallow seas and coastal shelf regions create biases in the systems. Furthermore, an investigation of differences amongst sea ice analysis shows this is a period with the largest uncertainty in the initial sea ice state, suggesting a lack of representation of initial sea ice uncertainty in the ensemble spread, with current ensemble spread in GEPS being generated solely through the initial conditions and forward integration perturbations in the atmosphere. Even during periods with good forecasting skill the potential of better representing uncertainty in the sea ice initial conditions is seen in the probabilistic scores of the system. Potential ways to rectify this situation may then be discussed.
The Alfred-Wegener-Institut (AWI) has developed a coupled forecast system based on the AWI Climate Model (AWI-CM-3; OpenIFS coupled to FESOM2) over the last years, with ensemble data assimilation only in the ocean/sea-ice model component, focusing on polar climate and sea ice at sub-seasonal-to-seasonal timescales. So far, the atmospheric component was left completely unconstrained, besides the influence exerted by the ocean and sea-ice.
To better tap the atmosphere predictability as well as to further improve the initialization of the ocean and sea-ice state, we plan to complement the forecast system with spectral nudging of the large-scale atmospheric circulation towardsERA5 reanalysis data. Here we present preparatory work where spectral nudging was applied to AWI-CM-3 without ocean/sea-ice data assimilation.Sensitivity experiments have been performed using various e-folding times, spectral truncations, and vertical profiles to evaluate the response of AWI-CM-3 to the different nudging parameters. Estimates of nudging increments and comparisons with reanalysis data were used to identify optimal nudging configurations. Particular attention was given to the reproduction of anomalies in the sea-ice state and other sea ice-relevant variables such as SSTs, near-surface winds, and snowfall. Moreover, ensembles of nudged simulations were generated to investigate the effect of spectral nudging on the spread of quantities driving the ocean/sea-ice spread (e.g., near-surface winds), a crucial aspect when combining atmospheric nudging with the ocean/sea-ice ensemble data assimilation.
Our results reveal the potential of integrating atmospheric spectral nudging in the coupled forecast system with ocean/sea-ice data assimilation and shed light on the impact of nudging parameters.
In operational flood forecast systems, the effect of sea ice is typically neglected or poorly parameterized solely in terms of ice concentration. This study shows the inclusion of sea ice effects can lead to significant improvements in forecasts of total water level (TWL) at very low computational cost. The method is illustrated using a simplified baroclinic high-resolution (1/12 degree) model with global coverage. The effects of landfast and drift ice are included through a modification of the surface stress. The ice-ocean stress under drift ice is derived from forecast fields produced by an operational ice-ocean model. The effects on tides are accounted for by friction induced by landfast ice. The value of adding sea ice is demonstrated using observations of TWL made in the Arctic and Hudson Bay. The separate roles of landfast and drift ice are discussed. Significant improvements are found in the Canadian Arctic where surge overestimations approaching 1 m are corrected. About 50% of this attenuation is explained by landfast ice when present. Significant improvements are also found to the predicted tides in the Canadian Arctic and Hudson Bay (up to 50% in amplitude and 40 degree in phase). Compared to a coupled ice-ocean model, landfast ice can account for most of the under-ice tidal friction. Exceptions are found in several regions including the Bering Strait and eastern Hudson Bay where drift ice makes a relatively large contribution.
Human activities in the Antarctic are inherently risky due to the remoteness of the Southern Ocean and Antarctic continent and the extreme conditions humans face there. Sea and ice conditions, even over the summer months, challenge operators and require diligent planning as well as the ability to respond quickly and flexibly to changes in, for instance, sea ice conditions or changes in the weather.
Temporally and spatially sensitive environmental forecasting information is critical but fraught with difficulties due to the poor bandwidth and meteorological data gaps in parts of the Southern Ocean and Antarctica. Operators have learnt to adapt and draw on a suite of innovative solutions to ensure the safety of their vessels, equipment and people while aiming to complete their mission, whether this is a tourist or a scientific expedition, or logistics support.
This session will explore, in a discussion setting, what some of the key risks are in relation to operating in the Antarctic, and how operators try to minimise those risks. Our guests will share their expertise and insights on what operational needs are met by existing forecasting services and what requirements are not being addressed yet. They will explore a range of innovative solutions as well as ‘work-arounds’ that have been adopted to bridge gaps between available science and forecasting services and operators’ specific information needs operators.
Our discussion will conclude with a look ahead and an examination of how currently existing operational challenges and barriers relating to environmental forecasting data and services could be overcome in the future.
Lagrangian tracking of sea ice has several applications ranging from seasonal forecasting, sea ice transport problems, drift-expedition planning and educational activities (e.g., http://icemotion.labs.nsidc.org/SITU/). We present a new optimally interpolated seamless sea ice drift dataset based on observations.This dataset builds on theNSIDC Polar Pathfinder ice motion vectors (Tschudi et al., 2020). New features include state-dependent and bias-corrected free drift ice motion estimates (Brunette et al., 2021) and a new optimal interpolation scheme with weights calculated from the seasonally varying decorrelation length scale of sea ice drift, along with fully documented, spatially and temporally varying errors for each of the individual raw data products. The new dataset is compared with an independent buoy dataset (ITP, etc.) as well as with the current Polar Pathfinder dataset.
Since more than a decade, Mercator Ocean International develop and produce Global Ocean Reanalysis with a 1/4 resolution system. Based on the NEMO modelling platform, observations are assimilated by a reduced order Kalman filter. In-situ CORA data base, altimetric data, sea surface temperature and sea ice concentration are jointly assimilated to constrain the ocean and sea ice model.
Sea ice is a key element in our climate system, and it is very sensitive to climate change. Sea ice volume is an important parameter although very challenging to estimate precisely since it is a combination of sea ice area and sea ice thickness.
In previous reanalysis products, long-term sea ice volume drift has been observed in the Arctic. In order to better constrain sea ice thickness, Cryosat-2radar Freeboard data are assimilated jointly to the sea ice concentration. After describing this global sea ice reanalysis system, we present results on the abilities of this configuration to reproduce sea ice extent and volume interannual variability without assimilation and, secondly, the impact of assimilating sea ice data on the sea ice cover with hindcasts experiments. Snow depth influences significantly the Freeboard measurement: including snow information allows us to estimatea comprehensive snow and ice volume from CryoSat-2radarFreeboard.
These experiments take place in acontext of special interest inpolar regions and prepare the launch of Copernicus Sentinel expansion satellite missions.
Recent studies suggested a bright future for Arctic sea ice edge prediction on subseasonal time scales. For instance, the European Centre for Medium-Range Weather Forecasts (ECMWF) can make skillful forecasts 1.5 months ahead. However, ECMWFs performance of Arctic sea ice thickness (SIT) predictions is still unclear. Here, based on a well-developed SIT reanalysis dataset, the Arctic SIT reforecasts from ECMWF on subseasonal time scales is evaluated for the first time. The results show that ECMWF reforecasts of Arctic SIT are more skillful than persistence forecasts (PF) during the transition seasons for lead time longer than 30 days, indicating the advantage of dynamical prediction. However, suffering from the large initial error of SIT, ECMWF has a lower Arctic SIT predictive skill than PF, especially from March to June. Our results reveal that, in contrast to the very skillful sea ice edge predictions, the Arctic SIT prediction on subseasonal time scales still faces many challenges. In particular, an improved sea-ice mean state and assimilation of sea-ice thickness observations need urgent attention.
Ocean-sea ice coupled models constrained by varied observations provide different ice thickness estimates in the Antarctic. We evaluate contemporary monthly ice thickness from four reanalyses in the Weddell Sea, the German contribution of the Estimating the Circulation and Climate of the Ocean project, Version 2 (GECCO2), the Southern Ocean State Estimate (SOSE), the Nucleus for European Modelling of the Ocean (NEMO) based ocean-ice model (called NEMO-EnKF), and the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), and with reference observations from ICESat-1, Envisat, upward-looking sonars and visual sea-ice observations. Compared with ICESat-1 altimetry and in situ observations, all reanalyses underestimate ice thickness near the coast of the western Weddell Sea, even though ICESat-1 and visual observations may be biased low. GECCO2 and NEMO-EnKF can well reproduce the seasonal variation of first-year ice thickness in the eastern Weddell Sea. In contrast, GIOMAS ice thickness performs best in the central Weddell Sea, while SOSE ice thickness agrees most with the observations in the southern coast of the Weddell Sea. In addition, only NEMO-EnKF can reproduce the seasonal spatial evolution of ice thickness distribution well, characterized by the thick ice shifting from the southwestern and western Weddell Sea in summer to the western and northwestern Weddell Sea in spring. We infer that the thick ice distribution is correlated with its better simulation of northward ice motion in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis for understanding the recent variability of sea-ice volume in the Antarctic.
Several dynamical sea-ice models are able to produce skillful forecasts of sea-ice edge at sub-seasonal to seasonal timescales. However, recent studies have noted that many such forecasts have large initial errors, or mismatch against observed ice conditions already at day 1. While errors at further lead times may be caused by model bias or chaotic error growth, this is unlikely to be the case at the start of the forecast period. In this context, we are comparing ice-edge output from several models against different observational datasets to measure the initial mismatch and investigate the source of this issue. Some of this mismatch can be attributed to the difference in ice condition between the dataset used for verification vs the dataset used for the model analysis. Therefore, we are also analysing the differences between the different observational dataset in terms of ice presence and ice extent. In most of the cases, mismatch in ice-presence occurs in the Marginal Ice Zone and is highest in the summer (July-August for the Arctic and Jan-Dec for Antarctic). The ice-extent measured by the different datasets can also vary by as much as 20% in both hemispheres. Proper understanding of the bias patterns in the initial state of the models or systematic differences in observational datasets can help improve the overall sea-ice observing and modeling capabilities.
Sea ice conditions that have occurred at the start of MOSAiC expedition in 2019 and have arisen in Eurasian Arctic due to precursors in atmosphere and polar ocean during summer 2019 defined background for setting the Distributed Network (DN) and many of ice properties recorded during the expedition. Sea ice conditions within the area in 2019 due to record surface air temperatures (SAT) and high upper ocean heat content (HC) led to highly deteriorated residual ice with thicknesses 50-70 cm. That complicated search of the floes and defined fast Polarstern poleward drift with observations on a weakened fast-growing first-year and second-year ice. By summer 2020 sea ice conditions in this region were characterized by even weaker ice due to both greater SAT and HC anomalies including that to 2019. Located at a typical distance of ~50100 km from the ice edge (200250 km in 2019) the area was absolutely inapplicable for MOSAiC goals. However, the sea ice conditions in 2021 appeared strikingly different due to zero or negative SAT and HC anomalies (relative both to 1991-2020 period and 2019-2020). Ice cover in the region following shipborne and CryoSAT-2 observations was at a distance of 300400 km from ice edge in a form of vast floes 100150 cm thick and was experiencing much slower drift following information from YOPP buoys. Start of MOSAiC expedition in 2021 as well as in next 2022 would lead to other DN setting and longer expedition drift with ice observations on mostly second-year ice.
The ice sheet mass loss contribution to sea level rise has drastically increased during the last two decades with an important contribution from West Antarctica and particularly the Antarctic Peninsula (AP). The western and northern regions of the AP have been a hotspot of climate change characterized by a strong increase in precipitation and a significant near-surface air warming with occasional temperature records and major surface melt events. Among the most important controlling factors of both precipitation and surface melt are warm/moist air intrusions, particularly those associated with atmospheric rivers (ARs). We use observations during the Year of Polar Prediction (YOPP) in the Southern Hemisphere (SH) summer special observing period to explore the double role of ARs, as carriers of both heat and moisture, in their impacts on cloud radiative forcing and precipitation at the AP. We show that ARs play an important role in precipitation phase transitions (frequently causing rainfall) as well as increases in cloud liquid water content, both in the austral summer and winter seasons. Measurements from several stations are combined using enhanced YOPP and regular observations: at Escudero and King Sejong stations located on King George Island, Akademik Vernadsky station in the western AP, and Punta Arenas in southern South America. YOPP observations are used for evaluation and analyzed together with ERA5 reanalysis and the Polar-WRF model. Summer observations are compared to the winter months during previous years (based on ERA5) in preparation for the winter YOPP-SH special observing period (April-July 2022).
Both the Southern Annular Mode (SAM) and the El Nio Southern Oscillation (ENSO) are two critical factors contributing to the Antarctic sea ice variability, with strong correlation with each other. The impacts of combined ENSO and SAM on the Antarctic seasonal sea ice anomalies budget are assessed in this study by investigating sea ice concentration (SIC) observations and atmospheric reanalysis data. Based on the monthly ENSOSAM standardized indices four special situations are selected. In phase events (LN/SAM+ EN/SAM) are characterized with distinct sea level pressure anomalies in the Amundsen Sea and an 850-hPa temperature dipole over the West Antarctic coastal oceans, while out of phase events (EN/SAM+ LN/SAM) with only pressure anomalies over the whole Antarctic and few temperature anomalies. All the four situations contribute to the similar spatial patterns of sea ice concentration anomalies with seasonal variations, presenting a dipole over the Atlantic and Pacific sectors. Sea ice dynamic and thermodynamic budget analyses are conducted to determine the leading processes involving the sea ice anomalies. The results show that thermodynamic processes dominate in summer and spring, due to the increased short-wave radiation fluxes and the ice-albedo feedback. Meanwhile, sensible and latent heat fluxes result in the thermodynamically sea ice anomalies. Dynamic processes have larger contributions in autumn and winter than other seasons, with advection causes sea ice anomalies at the ice edge and divergence works in the inner ice pack.
There is controversy over the extent that Arctic change can influence midlatitude extreme weather and vis-versa. Part of the uncertainty is due to the intermittency of the connection through the jet stream and polar vortex that leads to different emphases when communicating research. We provide two observational examples. Three interactive physical processes are involved through atmospheric dynamics: 1) internal atmospheric jet stream/polar vortex processes that add to the persistence of a wavy jet stream; 2) warm and humid air transport into an existing longwave atmospheric pattern; and 3) local thermodynamic surface forcing, often associated with loss of sea ice. All three atmospheric processes were active in two recent studies. Both cases impacted sea ice loss and the entire marine ecosystem food chain, and resulted in downstream cold air transport into midlatitudes. Both the North American and eastern Asia examples show a causal connection from atmospheric and ocean physics to human impacts. Thus global warming influences can be more than a local heating response, which can follow a chain of events involving disruption of the jet stream.
The Chukchi Sea, on the Pacific side of the Arctic Ocean, recorded its largest ice-free area in the winter of 201718, a period when the Arctic Oscillation (AO) was persistently in its negative phase. In association with the negative AO, East Asia suffered its coldest winter since 1985 while the Arctic region was anomalously warm. Recent studies argued that the decline in Chukchi Sea ice forced the jet stream to meander southward over Asia and America, allowing cold air to spread there. However, cold Asian winters are typically explained by La Nia and reduced Arctic ice in the Atlantic sector. As Chukchi Sea ice coverage has severely declined in recent years, the importance of its role with respect to these traditional factors should be investigated on a multiannual time scale in light of anticipated global warming. Here we present a statistical analysis showing that 201718 was the only winter since 1985 in which declining ice in the Chukchi Sea played a leading role and that previously its contribution was much smaller than those of Barents Sea ice and La Nia. A simple numerical experiment involving an anomalous heat source over the Pacific sector of the Arctic successfully simulated a cold Asia and warm Arctic. Thus, an anomalous negative AO along with the cold Asian winter of 201718 may be partially explained by the decline in Chukchi Sea ice. In the context of global warming, long-term forecasts of Chukchi Sea ice may improve predictions of Asian climate.
Surface melt over West Antarctica is increasingly recognized as a contributor to ice mass loss, through processes such as hydrofracturing of ice shelves that buttress ice sheets. We identify the large-scale meteorological drivers of surface energy balance variability over West Antarctica that govern surface melt, and link these patterns to major modes of atmospheric variability including El Nio Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the first Pacific-South American Pattern (PSA-1). We diagnose these drivers by comparing satellite-observed surface melt patterns to anomalies of near-surface air temperature, winds, satellite-derived cloud cover and radiative fluxes spanning the austral summers 1979-2017. Through k-means clustering analysis over a geographic domain encompassing West Antarctica, the Amundsen and Bellingshausen Seas and the Antarctic Peninsula, we identify nine large-scale circulation patterns that together describe the continuum of atmospheric flow. Six patterns enhance surface melt somewhere along the Amundsen Sea Embayment (ASE), while three are less conducive to ASE melt conditions. Summertime melt-inducing surface warming is favored by Amundsen Sea (AS) blocking activity and a negative phase of the SAM, both of which correlate with ENSO conditions in the tropical Pacific Ocean. Extensive melt events in the Ross-Amundsen sector of the West Antarctic Ice Sheet (WAIS) are linked to persistent AS blocking anticyclones that force intrusions of marine air over the ice sheet. By linking ASE surface melt patterns to major modes of atmospheric variability, these results offer the potential for detailed projections of future surface melt extent and duration in a warming climate.
This study examines the evolution of the interannual warm Arctic-cold continents (WACC) pattern over the North American sector, which is referred to as WACNA, and explores its driving mechanism. WACNA features a pair of opposite surface air temperature anomalies centered over the Chukchi-Bering Seas and Northern American Great Plains. A negative phase of the warm Arctic-cold Eurasia (WACE) pattern tends to lead a positive phase of the WACNA pattern by about 25 days. Negative Asian-Bering-North American (ABNA) and Pacific-North American (PNA) like atmospheric circulation patterns also appear upstream and precede a positive WACNA by about 25 days, gradually develop, reach their peaks when both circulation patterns lead the WACNA by 5 days, and weaken afterwards. The negative ABNA-like pattern can be driven by the Siberian snow decline that is related to a negative WACE pattern and its featured Eurasian warming, whereas the negative PNA-like pattern is influenced by negative SST anomalies over the tropical central-eastern Pacific that resemble the tropical ENSO variability. The surface signatures of both patterns highlight a horseshoe shaped high-pressure anomaly straddling over Gulf of Alaska, Alaska and northwestern Canada. The anomalous warm advection from the North Pacific and cold advection from Arctic that follow the circulation anomalies, as well as sea ice declines over the Chukchi-Bering Seas and growth over Hudson Bay, lead to the formation of the positive WACNA pattern. Processes with circulation anomalies of opposite signs will likewise lead to the negative WACNA pattern.
High quality weather forecasts have been one of the backbones of the successful MOSAiC expedition. But, how good have they been? In the project SynopSys, we tackle this question by looking into the data for the ICON-NWP model that has been primarily used operationally during the expedition. How good was the forecast compared to the analysis? How large is the impact from additionally radiosondes launched during the MOSAiC expedition and YOPP targeted observing periods? How do they compare to the observations on the ground and in the vertical column? MOSAiC observational data, model experiments with the forecast model as well as high-resolution regional model simulations will give us the answer and first results will be presented here. SynopSys also takes a more detailed look into processes between troposphere and stratosphere. Ozone data from satellite remote sensing products will be utilized to learn about the quality of the forecast model in this regard. The combination of all these assessments will provide a unique view on the forecast reliability not only on local but also on large scales. Improving forecasts in this context will not only benefit forecasts in the Arctic region alone, but potentially leads to improvements for lower latitudes as well through large-scale linkages.
Air masses, during their exchange between the Arctic region and the mid-latitudes, undergo a vast transformation that has a major impact on the Arctic and global climate, but is often poorly represented by weather prediction models. In this study, we use the coupled Atmosphere-Ocean Single Column Model (AOSCM) to simulate a Warm Air Intrusion (WAI) event that was observed by the MOSAiC experimental campaign to the north of Svalbard, at the end of April 2020. Through direct comparison with the available in-situ measurements, we are able to test the models ability to predict the observed boundary layer structure, cloud properties and near-surface energy budget. We use the results to identify and discuss the deficiencies in the representation of the physical mechanisms that drive the air mass transformation during its pole-ward advection.
The aim of MIDO (2017-to date) has been to record year-round datasets in the ice-covered part of the Arctic Ocean by means of innovative autonomous buoy arrays. The core of this project is the continuous monitoring of several multidisciplinary key variables across the atmosphere-snow-sea ice-ocean interfaces, with a particular focus on the links between physical properties, biological processes and biogeochemical cycles in the central Arctic.
As part of MIDO, buoy observatories have been deployed during several field campaigns to the Arctic Ocean basin, most notably during AO18 in 2018 (IB Oden), T-ICE in 2018 (Ak Tryoshnikov) and MOSAiC in 2019/20 (RV Polarstern).
This contribution details the MIDO approach, describes the implementation, and highlights selected results. We will further give an outlook into the future, building on the past operational experience related to MOSAiC, in particular, and the closely-linked activity within Frontiers in Arctic Marine Monitoring (FRAM).
This model intercomparison uses observations taken during MOSAiC in wintertime (here defined as the period without solar radiation, 15 Oct 2019 15 Mar 2020) to evaluate coupled processes unique to the Arctic, such as; The representation of liquid-bearing clouds at cold temperatures; The representation of a persistent stable boundary layer; and the limiting impact of atmospheric variability on sea ice by snow. Short-term forecasts are used in this study to identify potential errors in the representation of fast processes, such as cloud feedbacks and surface fluxes, that cause biases in climate model projections of Arctic climate change.The relative importance of these processes in the models is studied from the perspective of the surface energy balance and the net impact of surface energy budget terms on surface temperature tendencies and sea ice growth.
Process diagnostics designed using observations of snow/sea-ice characteristics (from IMBs), the atmospheric structure (from soundings), cloud characteristics (based on radar/lidar), and surface fluxes (from the 3 separate atmospheric flux stations and the 23-meter tower) are used to identify systematic biases. Currently forecasts from nine experimental and operational forecast systems are included in the intercomparison, additional forecasts will be included as they become available.
Motivated by the need for an improved process understanding and the current lack of high-quality continuous aerosol-cloud-precipitation datasets for the Southern Ocean region, the Leipzig Aerosol and Cloud Remote Observations System (LACROS) has been operated at Punta Arenas, Chile (53.1S, 70.9W) for a 3-year period from austral spring of 2018 to austral spring 2021. LACROS comprises a set of state-of-the-art remote-sensing instruments such as a 35-GHz scanning polarimetric cloud radar, multi-wavelength polarization Raman lidars, Doppler lidar, micro rain radar, microwave radiometer, laser disdrometer, as well as sensors for direct and diffuse solar and terrestrial radiation. The observations were performed in collaboration with the University of Magallanes in the YOPP-endorsed project DACAPO-PESO (Dynamics, Aerosol, Cloud and Precipitation Observations in the Pristine Environment of the Southern Ocean). The resulting dataset resembles the first of that kind in the western part of the Southern Ocean.
The major findings in terms of heterogeneous ice formation in shallow mixed-phase clouds will be presented. They include the importance of orographic gravity waves for maintaining the liquid phase in the presence of ice and the relevance of a coupling state of a cloud to the aerosol-rich boundary layer.
The upcoming deployment of a similar suite of instruments to Neumayer III station (70.67S, 8.27W) will collect a similar dataset between 2022 and 2024. This dataset will allow for detailed studies on aerosols and clouds, providing a broader context for the results obtained during DACAPO-PESO.
This program demonstrates how state-of-the-art atmospheric and remote sensing equipment can be deployed in very remote polar locations with limited personnel and infrastructure, to progressively gather data relevant to climate model evaluation and improvement. Surface melt over West Antarctica is increasingly recognized as a contributor to ice mass loss. Radiative fluxes are the largest components of the surface energy balance (SEB) that governs the onset of surface melt, and these fluxes are strongly modulated by cloud cover and are therefore sensitive to cloud microphysical properties. Presently, cloud microphysical parameterizations in climate models are inadequate for reliable simulations of West Antarctic surface melt conditions. To provide useful data for improving these parameterizations, we deployed an instrument suite at Siple Dome in West Antarctica (81.65 S, 149.01 W) during December 2019, consisting of (1) measurements of all SEB flux components and (2) a shortwave spectroradiometer for cloud remote sensing. The spectroradiometer data, via near-infrared spectral variability in the 1.6-micron window, allow identification of cloud thermodynamic phase and retrieval of cloud optical depth and effective particle size. For example, our data show subtle shifts in cloud radiative properties, and concomitant effects on the SEB, as mixed-phase clouds advect up the Dome from lower elevations and precipitate throughout the morning, becoming mainly liquid-water clouds by afternoon. Successful field programs of this scope, with all equipment solar-powered and transportable by small aircraft, can collectively make substantial contributions to climate model improvement and hence more reliable projections of climatic change at remote high latitude locations.
Arctic maritime actors and sectors, including cruise tourism, cargo shipping, subsistence hunting, and fishing, are operating in increasingly dynamic ice-infested waters. Moreover, steady increases in maritime activities and growing societal demands for sustainable development are generating a growing demand for innovative, accurate and salient metocean information and forecasting services. Recent investments in Arctic monitoring and observing have improved the availability of data, and advances in technologies and modelling skills have made great strides in improving the predictability of sea ice. Nevertheless, a range of technological, institutional and practical obstacles remains to challenge the delivery and optimal uptake of salient sea-ice services. Building on the concept of the last mile in the provision of climate information in support of local adaptation (Celliers et al. 2021), we present an analysis of the last mile gap in the delivery of sea-ice services in the European Arctic. We report the findings from an international, multistakeholder project dedicated to bridging the divide between sea-ice information (what is provided), demand (what is needed to increase stakeholder awareness), and action (information guiding marine operations). We argue that bridging the last mile is an increasing challenge, whereby marine actors requirements for decision support is an ever-moving target, prompting service providers to turn to transdisciplinary coproduction for answers. This results in a threefold technological challenge of 1) reaching end users with more accurate services; 2) connecting to widely different spatial temporal decision making contexts; and 3) overcoming wider societal and political obstacles.
World Meteorological Organization (WMO) Regional Climate Centres (RCCs) are centres of excellence that operationally generate regional climate products including climate monitoring and prediction in support of regional and national climate activities and thereby strengthen the capacity of WMO members in a given region to deliver better climate services to national users. The Pan-Arctic RCC Network (ArcRCC-N) has been in demonstration phase since May 2018—a year after the beginning of YOPP. ArcRCC-N has active contributions from all the Arctic Council member countries through three sub-regional geographical nodes: Asia, Nordic/Europe and North America. The Arctic Climate Forum (ACF) is a flagship activity of ArcRCC-N and is held twice a year. The key objectives of ACFs are to 1. Develop a consensus statement on the current status and future outlook of Arctic Essential Climate Variables (ECVs) on a seasonal scale; 2. Raise awareness about new climate products and services for the Arctic, and; 3. Stimulate user-producer interactions around climate information, including associated impacts and risks, and needs for climate information for planning. ACFs have built in several ways to facilitate engagement with (end) users of seasonal information. These include user-dedicated timeslots and presentations during ACF sessions, and a semi-annual feedback survey. In this presentation the methods for systematic user engagement are illustrated, lessons learned during YOPP and beyond are shared, and challenges are discussed. Together, these reflections give input into the ongoing discussion about how to co-create meaningful seasonal forecast information for the variety of stakeholders and shareholders across the Arctic.
As polar research, infrastructure and observing systems come of age, there is increasing interest in sharing information about logistical resources, which in turn makes it possible for the resources themselves to be shared across institutions and nations, facilitating multi-agency collaboration. To support this, Polardex is new online discovery and planning tool for polar infrastructure and logistics. Led by the European Polar Board (EPB), Polardex has been developed by a wide team of partners and with data and information provided by many organisations and projects. Polardex is an evolution of the European Polar Infrastructure Database, combining it with the Southern Ocean Observing System (SOOS) DueSouth database to be an integrated platform for physical infrastructure (field facilities, vessels, aircraft and other assets) and logistics (planned routes, cruises, transects, etc.). Polardexs modern, cloud-based, serverless technology provides high availability and high performance, with a scalable platform to be made available to the polar communities. This facilitates easy access to search and discovery of polar logistics and infrastructure resources and information, helping to maximise use and international collaboration in Arctic and Antarctic research. This presentation, on behalf of the EPB Action Group on Infrastructure, will introduce Polardex and its features, and outline the process by which it was built and continues to develop.
For over 70 years the Australian Bureau of Meteorology (BoM) and the Australian Antarctic Division (AAD) have collaborated to support Antarctic operations and science. This relationship started with observations, and expanded with technology, into highly integrated forecasting services supporting station life, aviation, shipping, ice and land travel, and special science projects (e.g., SOCRATES). Over the summer operational period forecasters are deployed to stations and onboard ships.
Tailored weather services assist with operational prioritisation, efficiency, and human safety. Each season, products are adapted to AAD operations, whilst maintaining an ongoing theme that allows for continuity of service over time. Competencies and training for embedded forecasters include significant customer focus and knowledge of operational contexts, allowing for contingency planning and decision support. Location specific, task specific, station forecasts, and verbal weather briefings are provided daily and on demand. Pilots, operations co-ordinators, boating teams, field workers, and ships masters interact with the forecasters building strong relationships and trust, leading to service improvements. Due to resource constraints, during the austral winter daily forecasts are unavailable and expeditioners self-brief, relying on their own interpretation of model data, however services are provided for high-risk activities and emergencies.
Difficulties arising from this service model include customer expectation management, personnel training and competency, fatigue and staff living in their workplace.
The case study of BoM contributions to the Australian Antarctic Program demonstrates the successful tailoring of weather services for Antarctic users. It illuminates issues around managing integrated services and geographically dispersed, remote, and isolated teams and operations.
Hurtigruten Expeditions, a member of the International Association of Antarctica Tour Operators (IAATO) and the Association of Arctic Expedition Cruise Operators (AECO) has been visiting the fragile polar environments for two decades, witnessing the effects of climate change. Tourism and the number of ships in the polar regions has grown significantly. As a stakeholder aware of the need for long-term protection of these regions, we promote safe and environmentally responsible operations, invest in the understanding and conservation of the areas we visit, and focus on the enrichment of our guests.
We developed our science program with the goal of educating our guests about the natural environments they are in, as well as to support the scientific community by providing our ships as platforms of opportunity for spatial and temporal data collection. Participation in Citizen Science programs that complement our lecture program provides an additional education opportunity for guests to better understand the challenges the visited environment faces while contributing to filling scientific knowledge gaps in remote areas and providing data for evidence-based decision making .
We aim to work alongside the scientific community and continue developing partnerships. We believe that scientific research, as well as polar prediction and monitoring in the Arctic and Antarctic can hugely benefit from the reoccurring presence of our vessels in these areas, as shown by the many projects we have supported so far.
Weather impacts people in the Antarctic and sub-Antarctic every day. To improve forecasts, weather services, environmental protection, and humandecision-making and safety in these regions we must first understand how, when, and why people use weather and climate information. There is limited research on peoples weather-related decision-making contexts, perceived risks, concerns, and informational needs and constraints. We explored these knowledge gaps through an online survey and semi-structured interviews with participants recently deployed with National Antarctic Programs, government organisations, logistics providers, and tourism operators in a variety of roles and locations. Weather information was used to plan and schedule outdoor activities, monitor environmental conditions, make go/ no go and start/ stop decisions, and manage safety. Criteria and context-based weather limits for outdoor activities were set by individuals personal risk tolerances, experience, and rules of thumb, or imposed by organisational procedures, and participants supervisors. Planning and decisions were constrained by weather information availability and accuracy, timelines, and task complexity. Experienced expeditioners expected and prepared for adverse weather, creating contingency plans, and adapting to changing weather conditions and opportunities. Deploying organisations provided limited weather education and training. Therefore, expeditioners with experience, alongside weather professionals, were viewed as invaluable sources of information, weather and uncertainty interpretation, mentorship, and advice. Weather information is important to participants ability to function in the Antarctic and sub-Antarctic. Further research into weather information use and investment in services and education would be beneficial to expeditioners, operators, and deploying organisations, to reduce risks to human safety and build resilient operations.
In the European Arctic Ocean environment, as well as in polar ocean in general, maritime sectors and users are facing increasingly dynamic conditions, which in turn require services and products that are increasingly tailored to the contextualised need and uptake of information in operations and planning. Closing gaps between advances in science, product development, service delivery and the specific information needs of users requires collaboration across the Weather, Water, Ice, and Climate (WICC) information value chains. This session takes the form of a moderated dialogue between professionals representing the producer-user environments of WICC information services, to discuss the barriers and opportunities for optimizing WWIC information value chains in the European Arctic Ocean context. Session guests bring to the table ample experience in transdisciplinary collaborations on co-producing salient services, and will share their insights based on extensive expertise ranging from numerical weather and ice prediction research and development to operational uptake of information services for Arctic navigation. Our guests will be invited to provide their view on the barriers currently faced in the process of closing the service delivery and uptake gaps, as well as to identify opportunities to overcome these barriers. The session closes by providing the opportunity to the audience to take part in this dialogue.
This program was last updated: August 29, 2022.
Year of of Polar Prediction
Final Summit
29 August - 1 September, 2022
The Centre Mont-Royal
Montréal, Québec, Canada
Email:
Phone: 902-422-1886 (UTC-4)
10251 : 2595
2022-08-29
Welcome to The YOPP Final Summit
Welcome to the Year of Polar Prediction Final Summit, in person and online, in Montréal, Québec, Canada to discuss and celebrate scientific advances and the legacy of the Polar Prediction Project.
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