Polar WRF模式海冰密集度方案对北极海雾模拟效果的个例研究
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摘要
全球变暖的背景下,北极航线的常规通航甚至商业运营有望实现,而海雾会严重影响航道上船只的航行安全。海冰的存在使海气之间相互作用变得更为复杂,是研究北极海雾不可忽略的因素。船载观测发现,与中纬度常见平流冷却雾形成时气温下降速度往往超过海水降温速度不同,北极海雾发生时海冰的存在还会使海水降温速度超过空气降温速度。然而目前海冰分布是否会影响模式模拟海雾的准确性还不得而知,因此本文利用Polar WRF(Polar Weather Research and Forecasting)模式模拟了中国第七次北极考察中观测到的一次海雾过程,并进行海冰密集度敏感性试验。通过与船载观测和欧洲中期天气预报中心再分析数据比对发现,在低浮冰区内(海冰密集度小于50%)考虑海冰分布时可以更加准确地刻画潜热通量与水汽通量,模拟出与观测事实相符的表层空气降温与增湿过程以及相对湿度的变化,因此能够更好地刻画海雾的三维结构及其生消演变。
Under the background of global warming,it is possible to open the Arctic summer route and even to conduct commercial utilization. The Arctic sea fog would seriously affect the navigation safety of ships along the channel. The existence of sea ice makes the interaction between sea and air very complicated,which is a problem that cannot be ignored in the study of Arctic sea fog. Ship-based observations show that unlike the common mid-latitude advection cooling fog whose formation sees the rate of surface air temperature drop generally greater than that of sea water temperature drop,the Arctic sea fog occurs when the rate of sea water temperature drop exceeds that of surface air temperature drop because of sea ice. However,it remains a doubt whether or not the distribution of sea ice would affect the accuracy of the model simulation of sea fog. In this paper,Polar Weather Research and Forecasting( Polar WRF) model is used to simulate a sea fog case observed during China's seventh expedition to Arctic in summer and sensitivity experiments on sea ice fraction are conducted. The experiments are verified by ship-based observations and the reanalysis data of European Centre for Medium-Range Weather Forecasts. The results show that in areas of low floating ice fraction( sea ice fraction lower than50%),when considering distribution features of sea ice,Polar WRF model can more accurately describe latent heat flux and upward water vapor flux and simulate the process of surface air temperature drop and humidification and the change of relative humidity. Therefore,Polar WRF model with sea ice fraction can better describe the three-dimensional structure and the evolution of Arctic sea fog.
Under the background of global warming,it is possible to open the Arctic summer route and even to conduct commercial utilization. The Arctic sea fog would seriously affect the navigation safety of ships along the channel. The existence of sea ice makes the interaction between sea and air very complicated,which is a problem that cannot be ignored in the study of Arctic sea fog. Ship-based observations show that unlike the common mid-latitude advection cooling fog whose formation sees the rate of surface air temperature drop generally greater than that of sea water temperature drop,the Arctic sea fog occurs when the rate of sea water temperature drop exceeds that of surface air temperature drop because of sea ice. However,it remains a doubt whether or not the distribution of sea ice would affect the accuracy of the model simulation of sea fog. In this paper,Polar Weather Research and Forecasting( Polar WRF) model is used to simulate a sea fog case observed during China's seventh expedition to Arctic in summer and sensitivity experiments on sea ice fraction are conducted. The experiments are verified by ship-based observations and the reanalysis data of European Centre for Medium-Range Weather Forecasts. The results show that in areas of low floating ice fraction( sea ice fraction lower than50%),when considering distribution features of sea ice,Polar WRF model can more accurately describe latent heat flux and upward water vapor flux and simulate the process of surface air temperature drop and humidification and the change of relative humidity. Therefore,Polar WRF model with sea ice fraction can better describe the three-dimensional structure and the evolution of Arctic sea fog.
引文
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[15]DEE D P,UPPALA S M,SIMMONS A J,et al.The ERA-Interim reanalysis:configuration and performance of the data assimilation system[J].Quart J Roy Meteor Soc,2011,137(656):553-597.
[16]Polar Meteorology Group(Byrd Polar Research Center,The Ohio State University).The Polar WRF:Description[EB/OL].(2018-01-23)[2018-12-29].http://polarmet.osu.edu/PWRF/.
[17]ROGERS E,BLACK T,FERRIER B,et al.Changes to the NCEP Meso Eta Analysis and Forecast System:Increase in resolution,new cloud microphysics,modified precipitation assimilation,modified 3DVAR analysis[R].Silver Spring,Maryland:National Weather Service,2001.
[18]KAIN J S.The Kain-Fritsch convective parameterization:An updat[J].J Appl Meteor,2008,43(1):170-181.
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[20]HONG S Y,NOH Y,DUDHIA J.A new vertical diffusion package with an explicit treatment of entrainment processes[J].Mon Wea Rev,2006,134(9):2318-2341.
[21]CHEN F,DUDHIA J.Coupling an advanced land surfacehydrology model with the Penn State-NCAR MM5modeling system.Part II:Preliminary model validation[J].Mon Wea Rev,2001,129(4):587-604.
[22]张苏平,鲍献文.近十年中国海雾研究进展[J].中国海洋大学学报(自然科学版),2008,38(3):359-366.
[23]ZHANG S P,LEWIS J M.Synoptic processes[M]//KORACˇIN D,DORMAN C E.Marine fog:Challenges and advancements in observations,modeling,and forecasting.Switzerland:Springer International Publishing,2017:291-343.
[24]DEVASTHALE A,SEDLAR J,TJERNSTRM M.Characteristics of water-vapour inversions observed over the Arctic by Atmospheric Infrared Sounder(AIRS)and radiosondes[J].Atmos Chem Phys,2011(11):9813-9823.
[25]FAIRALL C W,BRADLEY E F,ROGERS D P,et al.Bulk parameterization of air-sea fluxes for Tropical OceanGlobal Atmosphere Coupled-Ocean Atmosphere Response Experiment[J].J Geophys Res:Oceans,1996,101(C2):3747-3764.
[2]李振福.北极航线的中国战略分析[J].中国软科学,2009(1):1-7.
[3]高从琴.气象与海难事故[J].气象,1996,22(10):54-57.
[4]解思梅,薛振和,曲绍厚,等.北冰洋夏季的海雾[J].海洋学报,2001,23(6):40-50.
[5]王彬华.海雾[M].北京:海洋出版社,1983:1.
[6]CURRY J A,SCHRAMM J L,EBERT E E.Sea ice-albedo climate feedback mechanism[J].J Climate,1995,8(2):240-247.
[7]EBERT E E,CURRY J A.An intermediate onedimensional thermodynamic sea ice model for investigating ice-atmosphere interactions[J].J Geophys Res:Oceans,1993,98(C6):10085-10109.
[8]SCHWEIGER A J,LINDSAY R W,VAVRUS S,et al.Relationships between Arctic sea ice and clouds during autumn[J].J Climate,2008,21(18):4799-4810.
[9]CURRY J A,SCHRAMM J L,SERREZE M C,et al.Water vapor feedback over the Arctic Ocean[J].J Geophys Res:Atmos,1995,100(D7):14223-14229.
[10]马永锋.Polar WRF对南极地区天气过程的模拟试验研究[D].北京:中国气象科学研究院,2012.
[11]HINES K M,BROMWICH D H.Development and testing of Polar Weather Research and Forecasting(WRF)Model.Part I:Greenland ice sheet meteorology[J].Mon Wea Rev,2008,136(6):1971-1989.
[12]BROMWICH D H,HINES K M,Bai L S.Development and testing of Polar Weather Research and Forecasting model:2.Arctic Ocean[J].J Geophys Res:Atmos,2009,114(D8):D08122.
[13]WILSON A B,BROMWICH D H,HINES K M.Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain:Surface and upper air analysis[J].J Geophys Res:Atmos,2011,116(D11):D11112.
[14]WILSON A B,BROMWICH D H,HINES K M.Evaluation of Polar WRF forecasts on the Arctic System Reanalysis Domain:2.Atmospheric hydrologic cycle[J].J Geophys Res:Atmos,2012,117(D4):D04107.
[15]DEE D P,UPPALA S M,SIMMONS A J,et al.The ERA-Interim reanalysis:configuration and performance of the data assimilation system[J].Quart J Roy Meteor Soc,2011,137(656):553-597.
[16]Polar Meteorology Group(Byrd Polar Research Center,The Ohio State University).The Polar WRF:Description[EB/OL].(2018-01-23)[2018-12-29].http://polarmet.osu.edu/PWRF/.
[17]ROGERS E,BLACK T,FERRIER B,et al.Changes to the NCEP Meso Eta Analysis and Forecast System:Increase in resolution,new cloud microphysics,modified precipitation assimilation,modified 3DVAR analysis[R].Silver Spring,Maryland:National Weather Service,2001.
[18]KAIN J S.The Kain-Fritsch convective parameterization:An updat[J].J Appl Meteor,2008,43(1):170-181.
[19]IACONO M J,DELAMERE J S,MLAWER E J,et al.Radiative forcing by long-lived greenhouse gases:Calculations with the AER radiative transfer models[J].JGeophys Res:Atmos,2008,113(D13):D13103.
[20]HONG S Y,NOH Y,DUDHIA J.A new vertical diffusion package with an explicit treatment of entrainment processes[J].Mon Wea Rev,2006,134(9):2318-2341.
[21]CHEN F,DUDHIA J.Coupling an advanced land surfacehydrology model with the Penn State-NCAR MM5modeling system.Part II:Preliminary model validation[J].Mon Wea Rev,2001,129(4):587-604.
[22]张苏平,鲍献文.近十年中国海雾研究进展[J].中国海洋大学学报(自然科学版),2008,38(3):359-366.
[23]ZHANG S P,LEWIS J M.Synoptic processes[M]//KORACˇIN D,DORMAN C E.Marine fog:Challenges and advancements in observations,modeling,and forecasting.Switzerland:Springer International Publishing,2017:291-343.
[24]DEVASTHALE A,SEDLAR J,TJERNSTRM M.Characteristics of water-vapour inversions observed over the Arctic by Atmospheric Infrared Sounder(AIRS)and radiosondes[J].Atmos Chem Phys,2011(11):9813-9823.
[25]FAIRALL C W,BRADLEY E F,ROGERS D P,et al.Bulk parameterization of air-sea fluxes for Tropical OceanGlobal Atmosphere Coupled-Ocean Atmosphere Response Experiment[J].J Geophys Res:Oceans,1996,101(C2):3747-3764.
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