Improved simulation of feedbacks between atmosphere and sea ice over the Arctic Ocean in a coupled regional climate model

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.

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

Journal of Water and Climate Change ◽

10.2166/wcc.2021.206 ◽

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.

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The distribution of snow black carbon observed in the Arctic and compared to the GISS-PUCCINI model

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-11245-2012 ◽

2012 ◽

Vol 12 (5) ◽

pp. 11245-11274

Author(s):

T. Dou ◽

C. Xiao ◽

D. T. Shindell ◽

J. Liu ◽

J. Ming ◽

...

Keyword(s):

Spatial Distribution ◽

Sea Ice ◽

Arctic Ocean ◽

Radiative Forcing ◽

Climate Model ◽

The Arctic ◽

Northern Eurasia ◽

Russian Arctic ◽

Radiative Forcings ◽

The Arctic Ocean

Abstract. In this study, we focus on the latest NASA GISS composition-climate model to evaluate its performance in simulating the spatial distribution of snow BC (sBC) in the Arctic relative to present observations. The radiative forcing due to BC deposition to the Arctic snow and sea ice is also estimated. Two sets of model simulations have been done in the analysis, where meteorology is linearly relaxed towards National Centers for Environmental Prediction (NCEP) and towards NASA Modern Era Reanalysis for Research and Applications (MERRA) reanalyses. Results indicate that both of the modeled sBC are in good agreement with present-day observations in and around the Arctic Ocean, except for underestimation at a few sites in the Russian Arctic. The overall ratio of observed to modeled sBC is 1.1. The result from the NCEP run is slightly better than that from the MERRA run. This suggests that the latest GISS-E2-PUCCINI model does not have significant biases in its simulated spatial distribution of BC deposition to the Arctic, and underestimation of biomass burning emissions in Northern Eurasia is preliminarily considered to be the main cause of the simulation biases in the Russian Arctic. The combination of observations and modeling provides a comprehensive distribution of sBC over the Arctic. On the basis of this distribution, we estimate the decrease in snow and sea ice albedo and the resulting radiative forcing. It is concluded that the averaged decrease in snow and sea ice albedo in and around the Arctic Ocean (66–90° N) due to BC deposition is 0.4–0.6% from spring 2007–2009, leading to regional surface radiative forcings of 0.7 W m−2, 1.1 W m−2 and 1.0 W m−2, respectively in spring 2007, 2008 and 2009.

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

Journal Ice and Snow ◽

10.15356/2076-6734-2019-4-417 ◽

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.

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

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-495-2013 ◽

2013 ◽

Vol 6 (1) ◽

pp. 495-520 ◽

Cited By ~ 3

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 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.

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Not just sea ice: other factors important to near‐inertial wave generation in the Arctic Ocean

Geophysical Research Letters ◽

10.1029/2020gl090508 ◽

2020 ◽

Author(s):

J. D. Guthrie ◽

J. H. Morison

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

Wave Generation ◽

The Arctic ◽

The Arctic Ocean ◽

Inertial Wave

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

Atmosphere ◽

10.3390/atmos12020174 ◽

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.

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