scholarly journals Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN–HIRLAM numerical weather prediction system version 38h1

2018 ◽  
Vol 11 (8) ◽  
pp. 3347-3368 ◽  
Author(s):  
Yurii Batrak ◽  
Ekaterina Kourzeneva ◽  
Mariken Homleid
Keyword(s):  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Mean Absolute Error ◽  
Weather Prediction ◽  
Absolute Error ◽  
The Arctic ◽  
Polar Regions ◽  
Form Drag ◽  
Numerical Weather ◽  
Ice Surface Temperature

Abstract. Sea ice is an important factor affecting weather regimes, especially in polar regions. A lack of its representation in numerical weather prediction (NWP) systems leads to large errors. For example, in the HARMONIE–AROME model configuration of the ALADIN–HIRLAM NWP system, the mean absolute error in 2 m temperature reaches 1.5 ∘C after 15 forecast hours for Svalbard. A possible reason for this is that the sea ice properties are not reproduced correctly (there is no prognostic sea ice temperature in the model). Here, we develop a new simple sea ice scheme (SICE) and implement it in the ALADIN–HIRLAM NWP system in order to improve the forecast quality in areas influenced by sea ice. The new parameterization is evaluated using HARMONIE–AROME experiments covering the Svalbard and Gulf of Bothnia areas for a selected period in March–April 2013. It is found that using the SICE scheme improves the forecast, decreasing the value of the 2 m temperature mean absolute error on average by 0.5 ∘C in areas that are influenced by sea ice. The new scheme is sensitive to the representation of the form drag. The 10 m wind speed bias increases on average by 0.4 m s−1 when the form drag is not taken into account. Also, the performance of SICE in March–April 2013 and December 2015–December 2016 was studied by comparing modelling results with the sea ice surface temperature products from MODIS and VIIRS. The warm bias (of approximately 5 ∘C) of the new scheme is indicated for areas of thick ice in the Arctic. Impacts of the SICE scheme on the modelling results and possibilities for future improvement of sea ice representation in the ALADIN–HIRLAM NWP system are discussed.

scholarly journals Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN-HIRLAM numerical weather prediction system version 38h1

2018 ◽  
Author(s):  
Yurii Batrak ◽  
Ekaterina Kourzeneva ◽  
Mariken Homleid
Keyword(s):  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Mean Absolute Error ◽  
Weather Prediction ◽  
Absolute Error ◽  
The Arctic ◽  
Polar Regions ◽  
Form Drag ◽  
Numerical Weather ◽  
General Evaluation

Abstract. Sea ice is an important factor affecting weather regimes, especially in polar regions. A lack of its representation in numerical weather prediction (NWP) systems leads to large errors. For example, in the HARMONIE-AROME model configuration of the ALADIN-HIRLAM NWP system, the mean absolute error in 2 metre temperature reaches 1.5 °C after 15 forecast hours for Svalbard. A possible reason for that is that the sea ice properties are not reproduced correctly (there is no prognostic sea ice temperature in the model). Here, we develop a new SImple sea iCE scheme (SICE) and implement it into the ALADIN-HIRLAM NWP system in order to improve the quality of its forecasts in areas influenced by sea ice. General evaluation of the new parameterization is performed within HARMONIE-AROME by experiments covering the Svalbard and Gulf of Bothnia areas for a selected period in March–April 2013. It is found that using the SICE scheme improves the forecast, decreasing the value of the 2 metre temperature mean absolute error on average by 0.5 °C in areas that are influenced by sea ice. The new scheme is sensitive to the representation of the form drag: it may increase the 10 metre wind speed bias on average by 0.4 m s−1 when the form drag is not taken into account. Also, the modelling results are compared with the sea ice surface temperature observations from MODIS. The warm bias (of approximately 5 °C) of the new scheme is indicated for the areas of thick ice in the Arctic. Impacts of the SICE scheme on the modelling results and possibilities for future improvement of sea ice representation in the ALADIN-HIRLAM NWP system are discussed.

scholarly journals The Assimilation of Observations from the Advanced Microwave Sounding Unit over Sea Ice in the French Global Numerical Weather Prediction System

2014 ◽  
Vol 142 (1) ◽  
pp. 125-140 ◽  
Author(s):  
Fatima Karbou ◽  
Florence Rabier ◽  
Catherine Prigent
Keyword(s):  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
The Arctic ◽  
Polar Regions ◽  
Numerical Weather ◽  
Temperature And Humidity ◽  
Microwave Sounding ◽  
Nwp Model

Abstract The aim of this study is to test the feasibility of assimilating microwave observations from the Advanced Microwave Sounding Units (AMSU-A and AMSU-B) through the implementation of an appropriate parameterization of sea ice emissivity. AMSU observations are relevant to the description of air temperature and humidity, and their assimilation into numerical weather prediction (NWP) helps better constrain models in regions where very few observations are assimilated. A sea ice emissivity model suitable for AMSU-A and AMSU-B data is described in this paper and its impact is studied through two assimilation experiments run during the period of the Arctic winter. The first experiment is representative of the operational version of the Météo-France NWP model whereas the second simulation uses the sea ice emissivity parameterization and assimilates a selection of AMSU channels above polar regions. The assimilation of AMSU observations over sea ice is shown to have a significant effect on atmospheric analyses (in particular those of temperature and humidity). The effect on temperature induces a warming in the lower troposphere, especially around 850 hPa. This leads to an increase in the Arctic inversion strength over the ice cap by almost 2 K. An improvement in medium-range forecasts is also noticed when the NWP model assimilates AMSU observations over sea ice.

Evaluation of the Rapid Refresh Numerical Weather Prediction Model Over Arctic Alaska

2021 ◽  
Author(s):  
Matthew T. Bray ◽  
David D. Turner ◽  
Gijs de Boer
Keyword(s):  
Boundary Layer ◽  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Numerical Weather ◽  
Arctic Alaska ◽  
Short Term Forecasting ◽  
Northern Alaska ◽  
Mixed Phase Clouds

AbstractDespite a need for accurate weather forecasts for societal and economic interests in the U.S. Arctic, thorough evaluations of operational numerical weather prediction in the region have been limited. In particular, the Rapid Refresh Model (RAP), which plays a key role in short-term forecasting and decision making, has seen very limited assessment in northern Alaska, with most evaluation efforts focused on lower latitudes. In the present study, we verify forecasts from version 4 of the RAP against radiosonde, surface meteorological, and radiative flux observations from two Arctic sites on the northern Alaskan coastline, with a focus on boundary-layer thermodynamic and dynamic biases, model representation of surface inversions, and cloud characteristics. We find persistent seasonal thermodynamic biases near the surface that vary with wind direction, and may be related to the RAP’s handling of sea ice and ocean interactions. These biases seem to have diminished in the latest version of the RAP (version 5), which includes refined handling of sea ice, among other improvements. In addition, we find that despite capturing boundary-layer temperature profiles well overall, the RAP struggles to consistently represent strong, shallow surface inversions. Further, while the RAP seems to forecast the presence of clouds accurately in most cases, there are errors in the simulated characteristics of these clouds, which we hypothesize may be related to the RAP’s treatment of mixed-phase clouds.

scholarly journals The influence of non-static sea ice on Antarctic and Southern Ocean numerical weather prediction

2021 ◽  
Author(s):  
Zhaohui Wang ◽  
Alexander D. Fraser ◽  
Phillip Reid ◽  
Richard Coleman ◽  
Siobhan P. O'Farrell
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather

Impact of assimilation of radiosonde and UAV observations on numerical weather prediction analyses and forecasts in the Arctic and Antarctic

2020 ◽  
Author(s):  
Timo Vihma ◽  
Tuomas Naakka ◽  
Qizhen Sun ◽  
Tiina Nygård ◽  
Michael Tjernström ◽  
...  
Keyword(s):  
Wind Speed ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
The Arctic ◽  
Observation Site ◽  
Near Surface ◽  
Numerical Weather ◽  
Background Fields ◽  
The Impact

<p>Weather forecasting in the Arctic and Antarctic is a challenge above all due to rarity of observations to be assimilated in numerical weather prediction (NWP) models. As observations are expensive and logistically challenging, it is important to evaluate the benefit that additional observations could bring to NWP.</p><p>Considering the Arctic, in this study the effects of the spatial coverage of the network on numerical weather prediction were evaluated by comparing radiosonde observations from land station taken from Integrated Global Radiosonde Archive (IGRA) and radiosonde observations from expeditions in the Arctic Ocean with operational analyses and background fields (12‐hr forecasts) of the European Centre for Medium Range Weather Forecasts (ECMWF). The focus was on 850 hPa level temperature for the period January 2016 – September 2018. Comparison of the analyses and background fields showed that radiosoundings had a remarkable impact on improving operational analyses but the impact had a large geographical variation. In particular, radiosonde observations from islands (Jan Mayen and Bear Island) in the northern North Atlantic and from Arctic expeditions substantially improved analyses suggesting that those observations were critical for the quality of analyses and forecasts. Comparison of two cases with and without assimilation of radiosonde sounding data from expeditions of Icebreaker Oden in 2016 and 2018 in the central Artic Ocean showed that satellite observations were not able to compensate for the large spatial gap in the radiosounding network. In the areas where the network is reasonably dense, the density of the sounding network was not the most critical factor for the quality of background fields. Instead, the quality of background field was more related to how radiosonde observations were utilized in the assimilation and to the quality of those observations.</p><p>Considering the Antarctic, we applied radiosonde sounding and Unmanned Aerial Vehicles (UAV) observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting (Polar WRF) model. Our experiments revealed small or moderate impacts of radiosonde and UAV data assimilation. In any case, the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature, wind speed, and humidity at the observation site for most of the time. Further, the impact on the results of 5-day long Polar WRF experiments was often felt over distances of at least 300 km from the observation site. All experiments succeeded in capturing the main features of the evolution of near-surface variables, but the effects of data assimilation varied between different cases. Due to the limited vertical extent of the UAV observations, the impact of their assimilation was limited to the lowermost 1-2 km layer, and assimilation of radiosonde data was more beneficial for modelled sea level pressure and near-surface wind speed. Considering the perspectives for technological advance, atmospheric soundings applying UAV have a large potential to supplement conventional radiosonde sounding observations.</p><p>The differences in the results obtained for the Arctic and Antarctic are discussed.</p>

scholarly journals The Impact of Radiosounding Observations on Numerical Weather Prediction Analyses in the Arctic

2019 ◽  
Vol 46 (14) ◽  
pp. 8527-8535 ◽  
Author(s):  
T. Naakka ◽  
T. Nygård ◽  
M. Tjernström ◽  
T. Vihma ◽  
R. Pirazzini ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
The Arctic ◽  
Numerical Weather ◽  
The Impact
Sign in / Sign up

Export Citation Format

Share Document