scholarly journals Atmospheric rivers and associated precipitation patterns during the ACLOUD/PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model

2021 ◽  
Author(s):  
Carolina Viceto ◽  
Irina V. Gorodetskaya ◽  
Annette Rinke ◽  
Marion Maturilli ◽  
Alfredo Rocha ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
The Arctic ◽  
Phase Precipitation ◽  
Atmospheric Rivers ◽  
Tracking Algorithms ◽  
North Eastern ◽  
Sea Ice Edge

Abstract. Recently, a significant increase in the moisture content has been documented over the Arctic, where both local contributions and poleward moisture transport from lower latitudes can play a role. This study focuses on the anomalous moisture transport events confined to long and narrow corridors, known as atmospheric rivers (ARs) which are expected to have a strong influence on Arctic moisture amounts, precipitation and energy budget. During the two concerted intensive measurement campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL), which took place from May 22 to June 28, 2017, at and near Svalbard, three high water vapour transport events were identified as ARs, based on two tracking algorithms: on 30 May, 6 and 9 June. We explore in detail the temporal and spatial evolution of the events identified as ARs and the associated precipitation patterns, using measurements from the AWIPEV research station in Ny-Ålesund, satellite-borne measurements, several reanalysis products (ERA5, ERA-Interim, MERRA-2, CFSv2 and JRA-55) and HIRHAM5 regional climate model. Results show that the tracking algorithms detected the events differently partly due to differences in spatial resolution, ranging from 0.25 to 1.25 degree, in temporal resolution, ranging from 1 hour to 6 hours, and in the criteria used in the tracking algorithms. Despite being consecutive, these events showed different synoptic evolution and precipitation characteristics. The first event extended from western Siberia to Svalbard, causing mixed-phase precipitation and was associated with a retreat of the sea-ice edge. The second event a week later had a similar trajectory and most precipitation occurred as rain, although in some areas mixed-phase precipitation or only snowfall occurred, mainly over the north-eastern Greenland’s coast and northeast of Iceland and no differences were noted in the sea-ice edge. The third event showed a different pathway extending from north-eastern Atlantic towards Greenland, and then turning southeastward reaching Svalbard. This last AR caused high precipitation amounts in the east coast of Greenland in the form of rain and snow and showed no precipitation in Svalbard region. The vertical profiles of specific humidity show layers of enhanced moisture, simultaneously with dry layers during the first two events, which were not captured by all reanalysis datasets, while the model misrepresented the entire vertical profiles. Regarding the wind speed, there was an increase of values with height during the first and last events, while during the second event there were no major changes in the wind speed. The accuracy of the representation of wind speed by the reanalyses and the model depended on the event. This study shows the importance of both the Atlantic and Siberian pathways of ARs during spring-beginning of summer in the Arctic, AR-associated strong heat and moisture increase as well as precipitation phase transition, and the need of using high spatiotemporal resolution datasets when studying these intense short duration events.

scholarly journals Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model

2022 ◽  
Vol 22 (1) ◽  
pp. 441-463
Author(s):  
Carolina Viceto ◽  
Irina V. Gorodetskaya ◽  
Annette Rinke ◽  
Marion Maturilli ◽  
Alfredo Rocha ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
The Arctic ◽  
Atmospheric Rivers ◽  
The North ◽  
Tracking Algorithms ◽  
North Eastern ◽  
Sea Ice Edge

Abstract. Recently, a significant increase in the atmospheric moisture content has been documented over the Arctic, where both local contributions and poleward moisture transport from lower latitudes can play a role. This study focuses on the anomalous moisture transport events confined to long and narrow corridors, known as atmospheric rivers (ARs), which are expected to have a strong influence on Arctic moisture amounts, precipitation, and the energy budget. During two concerted intensive measurement campaigns – Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) – that took place at and near Svalbard, three high-water-vapour-transport events were identified as ARs, based on two tracking algorithms: the 30 May event, the 6 June event, and the 9 June 2017 event. We explore the temporal and spatial evolution of the events identified as ARs and the associated precipitation patterns in detail using measurements from the French (Polar Institute Paul Emile Victor) and German (Alfred Wegener Institute for Polar and Marine Research) Arctic Research Base (AWIPEV) in Ny-Ålesund, satellite-borne measurements, several reanalysis products (the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) Interim (ERA-Interim); the ERA5 reanalysis; the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2); the Climate Forecast System version 2 (CFSv2); and the Japanese 55-Year Reanalysis (JRA-55)), and the HIRHAM regional climate model version 5 (HIRHAM5). Results show that the tracking algorithms detected the events differently, which is partly due to differences in the spatial and temporal resolution as well as differences in the criteria used in the tracking algorithms. The first event extended from western Siberia to Svalbard, caused mixed-phase precipitation, and was associated with a retreat of the sea-ice edge. The second event, 1 week later, had a similar trajectory, and most precipitation occurred as rain, although mixed-phase precipitation or only snowfall occurred in some areas, mainly over the coast of north-eastern Greenland and the north-east of Iceland, and no differences were noted in the sea-ice edge. The third event showed a different pathway extending from the north-eastern Atlantic towards Greenland before turning south-eastward and reaching Svalbard. This last AR caused high precipitation amounts on the east coast of Greenland in the form of rain and snow and showed no precipitation in the Svalbard region. The vertical profiles of specific humidity show layers of enhanced moisture that were concurrent with dry layers during the first two events and that were not captured by all of the reanalysis datasets, whereas the HIRHAM5 model misrepresented humidity at all vertical levels. There was an increase in wind speed with height during the first and last events, whereas there were no major changes in the wind speed during the second event. The accuracy of the representation of wind speed by the reanalyses and the model depended on the event. The objective of this paper was to build knowledge from detailed AR case studies, with the purpose of performing long-term analysis. Thus, we adapted a regional AR detection algorithm to the Arctic and analysed how well it identified ARs, we used different datasets (observational, reanalyses, and model) and identified the most suitable dataset, and we analysed the evolution of the ARs and their impacts in terms of precipitation. This study shows the importance of the Atlantic and Siberian pathways of ARs during spring and beginning of summer in the Arctic; the significance of the AR-associated strong heat increase, moisture increase, and precipitation phase transition; and the requirement for high-spatio-temporal-resolution datasets when studying these intense short-duration events.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

scholarly journals Evaluation of Arctic sea-ice drift and its dependency on near-surface wind and sea-ice concentration and thickness in the coupled regional climate model HIRHAM-NAOSIM

2019 ◽  
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea-ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM-NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea-ice conditions. Considering the seasonal cycle of Arctic basin averaged drift speed, the model reproduces the summer-autumn drift speed well, but significantly overestimates the winter-spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with near-surface wind. The model calculates a realistic negative relationship between drift speed and ice thickness and between drift speed and ice concentration during summer-autumn when concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive relationship between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for calm conditions. The correlation under low-wind conditions is overestimated in the simulations, compared to observation/reanalysis. A sensitivity experiment demonstrates the significant effects of sea-ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modelled drift speed/wind speed ratio with observations based on reanalysis for wind and remote sensing for sea ice drift. An improvement might be possible, among others, by tuning the open parameters of the parameterization in future.

scholarly journals Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic

2013 ◽  
Vol 6 (3) ◽  
pp. 849-859 ◽  
Author(s):  
P. Berg ◽  
R. Döscher ◽  
T. Koenigk
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled System ◽  
The Arctic ◽  
Spectral Nudging ◽  
The North ◽  
Temperature And Precipitation

Abstract. The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX (COordinated Regional climate Downscaling EXperiment) region, with an emphasis on its suitability to be coupled to a regional ocean and sea ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too-high pressure centred over the North Pole in summer of over 5 hPa, and too-low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea ice biases in a future coupled system. The large-scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large-scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables, such as surface radiative components, two-metre temperature and precipitation.

scholarly journals Effects of sea ice change on the Arctic climate: insights from experiments with a polar atmospheric regional climate model

2021 ◽  
Author(s):  
Xiying Liu ◽  
Chenchen Lu
Keyword(s):  
Sea Ice ◽  
Boundary Conditions ◽  
Regional Climate Model ◽  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Arctic Climate ◽  
The Arctic ◽  
Sea Ice Concentration

Abstract To get insights into the effects of sea ice change on the Arctic climate, a polar atmospheric regional climate model was used to perform two groups of numerical experiments with prescribed sea ice cover of typical mild and severe sea ice. In experiments within the same group, the lateral boundary conditions and initial values were kept the same. The prescribed sea ice concentration (SIC) and other fields for the lower boundary conditions were changed every six hours. 10-year integration was completed, and monthly mean results were saved for analysis in each experiment. It is shown that the changes in annual mean surface air temperature have close connections with that in SIC, and the maximum change of temperature surpasses 15 K. The effects of SIC changes on 850 hPa air temperature is also evident, with more significant changes in the group with reduced sea ice. The higher the height, the weaker the response in air temperature to SIC change. The annual mean SIC change creates the pattern of differences in annual mean sea level pressure. The degree of significance in pressure change is modulated by atmospheric stratification stability. In response to reduction/increase of sea ice, the intensity of polar vortex weakens/strengthens.

scholarly journals The influence of ocean heat transport in the Barents Sea on the regional sea ice and the atmospheric static stability

2019 ◽  
Vol 59 (4) ◽  
pp. 529-538
Author(s):  
M. G. Akperov ◽  
V. A. Semenov ◽  
I. I. Mokhov ◽  
M. A. Dembitskaya ◽  
D. D. Bokuchava ◽  
...  
Keyword(s):  
Sea Ice ◽  
Regional Climate Model ◽  
Climate Model ◽  
Barents Sea ◽  
Regional Climate ◽  
Static Stability ◽  
The Arctic ◽  
Oceanic Water ◽  
Ensemble Simulations ◽  
The Barents Sea

The influence of the oceanic heat inflow into the Barents Sea on the sea ice concentration and atmospheric characteristics, including the atmospheric static stability during winter months, is investigated on the basis of the results of ensemble simulations with the regional climate model HIRHAM/NAOSIM for the Arctic. The static stability of the atmosphere is the important indicator of the spatial and temporal variability of polar mesocyclones in the Arctic region. The results of the HIRHAM/NAOSIM regional climate model ensemble simulations (RCM) for the period from 1979 to 2016 were used for the analysis. The initial and lateral boundary conditions for RCM in the atmosphere were set in accordance with the ERA-Interim reanalysis data. An analysis of 10 ensemble simulations with identical boundary conditions and the same radiation forcing for the Arctic was performed. Various realizations of ensemble simulations with RCM were obtained by changing the initial conditions for integrating the oceanic block of the model. Different realizations of ensemble simulations with RCM are obtained by changing the initial conditions of the model oceanic block integration. The composites method was used for the analysis, i.e. the difference between the mean values for years with the maximum and minimum inflow of oceanic water into the Barents Sea. The statistical significance of the results (at a significance level of p < 0.05) was estimated using Student's t-test. In general, the regional climate model reproduces the seasonal changes in the inflow of the oceanic water and heat into the Barents Sea reasonably well. There is a strong relationship between the changes in the oceanic water and ocean heat inflow, sea ice concentration, and surface air temperature in the Barents Sea. Herewith, the increase in the oceanic water inflow into the Barents Sea in winter leads to a decrease in static stability, which contributes to changes in regional cyclonic activity. The decrease of the static stability is most pronounced in the southern part of the Barents Sea and also to the west of Svalbard.

scholarly journals Observations and simulations of meteorological conditions over Arctic thick sea ice in late winter during the Transarktika 2019 expedition

2021 ◽  
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

&lt;p&gt;The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model CCLM. In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data shows a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.&lt;/p&gt;

scholarly journals Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM

2020 ◽  
Vol 14 (5) ◽  
pp. 1727-1746
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.

scholarly journals Verification of the regional atmospheric model CCLM v5.0 with conventional data and Lidar measurements in Antarctica

2019 ◽  
Author(s):  
Rolf Zentek ◽  
Günther Heinemann
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Weddell Sea ◽  
Good Representation ◽  
Near Surface ◽  
Turbulence Parametrization ◽  
Lidar Measurements ◽  
The Antarctic

Abstract. The non-hydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data. We prescribed sea-ice concentration from satellite data, and used a thermodynamic sea-ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, AWS over land and sea ice, operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau. Differences in other regions were small. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for one year showed small biases for temperature around 1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around zero and a RMSE of 1–2 K for temperature and of 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler Lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. These results encourage for further studies using CCLM data for the regional climate in the Antarctic at high resolutions and the study of atmosphere-ice-ocean interactions processes.

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