The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been...The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature （SAT） over the Arctic Ocean, which contribute to the sea ice concentration （SIC） and sea surface temperature （SST） biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a large extent by its components, the WRF/PCE and the ROMS-CICE.展开更多
Using a regional atmospheric model for Arctic climate simulation, two groups of numerical experiments were carried out to study the influence of changes in the underlying surface （land surface, sea surface, and sea i...Using a regional atmospheric model for Arctic climate simulation, two groups of numerical experiments were carried out to study the influence of changes in the underlying surface （land surface, sea surface, and sea ice （LS/SS/SI）） from mild ice years to severe ice years on Arctic climate. In each experiment in the same group, the initial values and lateral boundary conditions were identical. The underlying surface conditions were updated every six hours. The model was integrated for 10 a and monthly mean results were saved for analysis. Variations in annual mean surface air temperature were closely correlated with changes in LS/SS/SI, with a maximum change of more than 15 K. The impact of changes in LS/SS/SI on low-level air temperature was also evident, with significant changes seen over the ocean. However, the maximum change was less than 2 K. For air temperature above 700 hPa, the impact of LS/SS/SI changes was not significant. The distribution of annual mean sea level pressure differences was coincident with the distribution of annual mean sea ice concentration. The difference centers were located in the Barents Sea, the Kara Sea, and the East Siberian Sea, with the maximum value exceeding 3 hPa. For geopotential height, some results passed and some failed a t-test. For results passing the t-test, the area of significance did not decrease with height. There was a significant difference at high levels, with a value of 27 gpm in the difference center at 200 hPa.展开更多
基金The National Natural Science Foundation of China under contract No.41276190
文摘The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature （SAT） over the Arctic Ocean, which contribute to the sea ice concentration （SIC） and sea surface temperature （SST） biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a large extent by its components, the WRF/PCE and the ROMS-CICE.
基金sponsored by the Natural Science Foundation of China (Grant no.41276190)
文摘Using a regional atmospheric model for Arctic climate simulation, two groups of numerical experiments were carried out to study the influence of changes in the underlying surface （land surface, sea surface, and sea ice （LS/SS/SI）） from mild ice years to severe ice years on Arctic climate. In each experiment in the same group, the initial values and lateral boundary conditions were identical. The underlying surface conditions were updated every six hours. The model was integrated for 10 a and monthly mean results were saved for analysis. Variations in annual mean surface air temperature were closely correlated with changes in LS/SS/SI, with a maximum change of more than 15 K. The impact of changes in LS/SS/SI on low-level air temperature was also evident, with significant changes seen over the ocean. However, the maximum change was less than 2 K. For air temperature above 700 hPa, the impact of LS/SS/SI changes was not significant. The distribution of annual mean sea level pressure differences was coincident with the distribution of annual mean sea ice concentration. The difference centers were located in the Barents Sea, the Kara Sea, and the East Siberian Sea, with the maximum value exceeding 3 hPa. For geopotential height, some results passed and some failed a t-test. For results passing the t-test, the area of significance did not decrease with height. There was a significant difference at high levels, with a value of 27 gpm in the difference center at 200 hPa.
