Intercomparison of Surface Radiative Fluxes in the Arctic Ocean

Recent satellite data analysis has provided improved data sets relevant to the surface energy budget in the Arctic Ocean. In this paper, surface radiation properties in the Arctic Ocean obtained from the Surface Radiation Budget（SRB3.0） and the International Satellite Cloud Climatology Project（ISCCP-FD） during 1984– 2007 are analyzed and compared. Our analysis suggests that these datasets show encouraging agreement in basin-wide averaged seasonal cycle and spatial distribution of surface albedo; net surface shortwave and all-wave radiative fluxes; and shortwave, longwave, and all-wave cloud radiative forcings. However, a systematic large discrepancy is detected for the net surface longwave radiative flux between the two data sets at a magnitude of ~ 23 W m–2, which is primarily attributed to significant differences in surface temperature, particularly from April to June. Moreover, the largest difference in surface shortwave and all-wave cloud radiative forcings between the two data sets is apparent in early June at a magnitude of 30 W m–2.

Calculating the Climatology and Anomalies of Surface Cloud Radiative Effect Using Cloud Property Histograms and Cloud Radiative Kernels

Cloud radiative kernels(CRK)built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere(TOA)fluxes,and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes,which determines the regional surface temperature change and variability.In this study,CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model(RRTM).Longwave cloud radiative effect(CRE)at the surface is primarily driven by cloud base properties,while TOA CRE is primarily decided by cloud top properties.For this reason,the standard version of surface CRK is a function of latitude,longitude,month,cloud optical thickness(τ)and cloud base pressure(CBP),and the TOA CRK is a function of latitude,longitude,month,τand cloud top pressure(CTP).Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present,the surface CRKs on CBP-τhistograms were converted to CTP-τfields using the statistical relationship between CTP,CBP andτobtained from collocated CloudSat and MODIS observations.For both climate model outputs and satellites observations,the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes.The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth's Radiant Energy System(CERES)surface irradiances products.