It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes...It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).展开更多
The mesoscale numerical weather prediction model (MM4) in which the computations of the turbulent exchange coefficient in the boundary layer and surface fluxes are improved, is used to study the influences of boundary...The mesoscale numerical weather prediction model (MM4) in which the computations of the turbulent exchange coefficient in the boundary layer and surface fluxes are improved, is used to study the influences of boundary layer parameterization schemes on the predictive results of the mesoscale model. Seven different experiment schemes (including the original MM4 model) designed in this paper are tested by the observational data of several heavy rain cases so as to find an improved boundary layer parameterization scheme in the mesoscale meteorological model. The results show that all the seven different boundary layer parameterization schemes have some influences on the forecasts of precipitation intensity, distribution of rain area, vertical velocity, vorticity and divergence fields, and the improved schemes in this paper can improve the precipitation forecast. Key words Boundary layer parameterization - Mesoscale numerical weather prediction (MNWP) - Turbulent exchange coefficient - Surface fluxes - Heavy rain This paper was supported by the National Natural Science Foundation of China (Grant No. 49875005 and No. 49735180).展开更多
Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surf...Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.展开更多
The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric...The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.展开更多
In this study,the performances of the Community Atmosphere Model(CAM)and Pleim–Xiu(PX)surface layer parameterization schemes are investigated by using field observations.The parameterization schemes are evaluated aga...In this study,the performances of the Community Atmosphere Model(CAM)and Pleim–Xiu(PX)surface layer parameterization schemes are investigated by using field observations.The parameterization schemes are evaluated against continuous momentum and sensible heat flux observations measured at two flat and homogeneous grassland sites in the suburb of Nanjing,eastern China.The observations were conducted from 30 December 2014 to 18 April 2017 at Jiangxinzhou and from 9 February 2015 to 26 March 2018 at Jiangning.It is found that the momentum flux is overall in good agreement with the observation,and the sensible heat flux is overestimated.The parameterizations of the momentum and sensible heat fluxes well capture the diurnal and seasonal patterns seen in the observations at the two sites.At Jiangxinzhou,the PX parameterization underestimates the momentum flux throughout the day and the CAM parameterization slightly overestimates it around the noon,while they underestimate the momentum flux throughout the year.The two parameterizations overestimate the sensible heat flux in the daytime as well as over the entire year.At Jiangning,the two parameterizations overestimate the momentum flux throughout the day and the sensible heat flux in the daytime,and overestimate both of them over the entire year.The two parameterizations are not significantly different from each other in reproducing the turbulent fluxes at the same site,while they perform differently at the two sites in terms of statistics.In addition,the parameterized fluxes increase with increased roughness length.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFE0106300)the National Natural Science Foundation of China(Grant Nos.42105072,41941009,41922044)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2021A1515012209,2020B1515020025)the China Postdoctoral Science Foundation(Grant Nos.2021M693585)the Norges Forskningsråd(Grant No.328886).
文摘It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).
文摘The mesoscale numerical weather prediction model (MM4) in which the computations of the turbulent exchange coefficient in the boundary layer and surface fluxes are improved, is used to study the influences of boundary layer parameterization schemes on the predictive results of the mesoscale model. Seven different experiment schemes (including the original MM4 model) designed in this paper are tested by the observational data of several heavy rain cases so as to find an improved boundary layer parameterization scheme in the mesoscale meteorological model. The results show that all the seven different boundary layer parameterization schemes have some influences on the forecasts of precipitation intensity, distribution of rain area, vertical velocity, vorticity and divergence fields, and the improved schemes in this paper can improve the precipitation forecast. Key words Boundary layer parameterization - Mesoscale numerical weather prediction (MNWP) - Turbulent exchange coefficient - Surface fluxes - Heavy rain This paper was supported by the National Natural Science Foundation of China (Grant No. 49875005 and No. 49735180).
基金This study was a part of the Sino-Finnish long-term sea-ice research cooperationsupported by the National Natural Science Foundation of China under contract Nos 40233032 and 40376006.
文摘Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.
基金This work was supported by the National Natural Science Foundation of China(41976214)The European Union's Horizon 2020 research and innovation programme provided support to BC and TV through the Polar Regions in the Earth System project(PolarRES,101003590)to MAG through the Climate Relevant interactions and feedbacks:the key role of sea ice and Snow in the polar and global climate system project(CRiceS,101003826).
文摘The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.
基金Supported by the National Natural Science Foundation of China(41375075)Meteorological Collaborative Innovation Foundation in Huadong Area(QYHZ201604)National Key Research and Development Program of China(2017YFC1502104)
文摘In this study,the performances of the Community Atmosphere Model(CAM)and Pleim–Xiu(PX)surface layer parameterization schemes are investigated by using field observations.The parameterization schemes are evaluated against continuous momentum and sensible heat flux observations measured at two flat and homogeneous grassland sites in the suburb of Nanjing,eastern China.The observations were conducted from 30 December 2014 to 18 April 2017 at Jiangxinzhou and from 9 February 2015 to 26 March 2018 at Jiangning.It is found that the momentum flux is overall in good agreement with the observation,and the sensible heat flux is overestimated.The parameterizations of the momentum and sensible heat fluxes well capture the diurnal and seasonal patterns seen in the observations at the two sites.At Jiangxinzhou,the PX parameterization underestimates the momentum flux throughout the day and the CAM parameterization slightly overestimates it around the noon,while they underestimate the momentum flux throughout the year.The two parameterizations overestimate the sensible heat flux in the daytime as well as over the entire year.At Jiangning,the two parameterizations overestimate the momentum flux throughout the day and the sensible heat flux in the daytime,and overestimate both of them over the entire year.The two parameterizations are not significantly different from each other in reproducing the turbulent fluxes at the same site,while they perform differently at the two sites in terms of statistics.In addition,the parameterized fluxes increase with increased roughness length.
基金supported by the National Key R&D Pro-gram of China[grant number 2017YFE0111800]the National Natural Science Foundation of China[grant numbers 41790472 and 41822502]。
