Simulation of arctic surface radiation and energy budget during the summertime using the single-column model

The surface heat budget of the Arctic Ocean （SHEBA） project has shown that the study of the surface heat budget characteristics is crucial to understanding the interface process and environmental change in the polar region. An arctic single - column model （ARCSCM） of Colorado University is used to simulate the arctic surface radiation and energy budget during the summertime. The simulation results are analyzed and compared with the SHEBA measurements. Sensitivity analyses are performed to test microphysical and radiative parameterizations in this model. The results show that the ARCSCM model is able to simulate the surface radiation and energy budget in the arctic during the summertime, and the different parameterizations have a significant influence on the results. The combination of cloud microphysics and RRTM parameterizations can fairly derive the surface solar shortwave radiation and downwelling longwave radiation flux. But this cloud microphysics parameterization scheme deviates notably from the simulation of surface sensible and latent heat flux. Further improvement for the parameterization scheme applied to the Arctic Regions is necessary.

An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models

To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance,the 2001–2014 Arctic Basin surface radiation budget,clouds,and the cloud radiative effects(CREs)in 22 coupled model intercomparison project 6(CMIP6)models are evaluated against satellite observations.For the results from CMIP6 multi-model mean,cloud fraction(CF)peaks in autumn and is lowest in winter and spring,consistent with that from three satellite observation products(Cloud Sat-CALIPSO,CERESMODIS,and APP-x).Simulated CF also shows consistent spatial patterns with those in observations.However,almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x.On average,clouds warm the surface of the Arctic Basin mainly via the longwave(LW)radiation cloud warming effect in winter.Simulated surface energy loss of LW is less than that in CERES-EBAF observation,while the net surface shortwave(SW)flux is underestimated.The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models.These two biases compensate each other,yielding similar net surface radiation flux between model output(3.0 W/m2)and CERES-EBAF observation(6.1 W/m2).During 2001–2014,significant increasing trend of spring CF is found in the multi-model mean,consistent with previous studies based on surface and satellite observations.Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path(LWP/IWP),large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year,indicating the influences of different cloud parameterization schemes used in different models.Cloud Feedback Model Intercomparison Project(CFMIP)observation simulator package(COSP)is a great tool to accurately assess the performance of climate models on simulating clouds.More intuitive and credible evaluation results can be obtained based on the COSP model output.In the future,with the release of more COSP output of CMIP6 models,it is expected that those inter-model spreads and the model-observation biases can be substantially reduced.Longer term active satellite observations are also necessary to evaluate models’cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.

Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite(GLASS)longwave radiation product

In this paper,time extension methods,originally designed for clear-sky land surface conditions,are used to estimate high-spatial resolution surface daily longwave(LW)radiation from the instantaneous Global LAnd Surface Satellite(GLASS)longwave radiation product.The performance of four time methods were first tested by using ground based flux measurements that were collected from 141 global sites.Combined with the accuracy of daily LW radiation estimated from the instantaneous GLASS LW radiation,the linear sine interpolation method performs better than the other methods and was employed to estimate the daily LW radiation as follows:The bias/Root Mean Square Error(RMSE)of the linear sine interpolation method were−6.30/15.10 W/m^(2)for the daily longwave upward radiation(LWUP),−1.65/27.63 W/m2 for the daily longwave downward radiation(LWDN),and 4.69/26.42 W/m^(2)for the daily net longwave radiation(LWNR).We found that the lengths of the diurnal cycle of LW radiation are longer than the durations between sunrise and sunset and we proposed increasing the day length by 1.5 h.The accuracies of daily LW radiation were improved after adjusting the day length.The bias/RMSE were−4.15/13.74 W/m2 for the daily LWUP,−1.3/27.52 W/m^(2)for the daily LWDN,and 2.85/25.91 W/m^(2)for the daily LWNR.We are producing long-term surface daily LW radiation values from the GLASS LW radiation product.

Remote sensing of earth’s energy budget:synthesis and review

The Earth’s climate is largely determined by its energy budget.Since the 1960s,satellite remote sensing has been used in estimating these energy budget components at both the top of the atmosphere(TOA)and the surface.Besides the broadband sensors that have been traditionally used for monitoring Earth’s Energy Budget(EEB),data from a variety of narrowband sensors aboard both polar-orbiting and geostationary satellites have also been extensively employed to estimate the EEB components.This paper provides a comprehensive review of the satellite missions,state-of-the art estimation algorithms and the satellite products,and also synthesizes current understanding of the EEB and spatiotemporal variations.The TOA components include total solar irradiance,reflected shortwave radiation/planetary albedo,outgoing longwave radiation,and energy imbalance.The surface components include incident solar radiation,shortwave albedo,shortwave net radiation,longwave downward and upwelling radiation,land and sea surface temperature,surface emissivity,all-wave net radiation,and sensible and latent heat fluxes.Some challenges,and outlook such as virtual constellation of different satellite sensors,temporal homogeneity tests of long time-series products,algorithms ensemble,and products intercomparison are also discussed.