ALBERT

Description: In this study, we integrate recent in situ measurements with satellite retrievals of dust physical and radiative properties to quantify dust direct radiative effects on shortwave (SW) and longwave (LW) radiation (denoted as DRESW and DRELW, respectively) in the tropical North Atlantic during the summer months from 2007 to 2010. Through linear regression of the CERES-measured top-of-atmosphere (TOA) flux versus satellite aerosol optical depth (AOD) retrievals, we estimate the instantaneous DRESW efficiency at the TOA to be -49.7±7.1 W m−2 AOD−1 and -36.5±4.8 W m−2 AOD−1 based on AOD from MODIS and CALIOP, respectively. We then perform various sensitivity studies based on recent measurements of dust particle size distribution (PSD), refractive index, and particle shape distribution to determine how the dust microphysical and optical properties affect DRE estimates and its agreement with the above-mentioned satellite-derived DREs. Our analysis shows that a good agreement with the observation-based estimates of instantaneous DRESW and DRELW can be achieved through a combination of recently observed PSD with substantial presence of coarse particles, a less absorptive SW refractive index, and spheroid shapes. Based on this optimal combination of dust physical properties we further estimate the diurnal mean dust DRESW in the region of −10 W m−2 at TOA and −26 W m−2 at the surface, respectively, of which ∼ 30 % is canceled out by the positive DRELW. This yields a net DRE of about −6.9 and −18.3 W m−2 at TOA and the surface, respectively. Our study suggests that the LW flux contains useful information on dust particle size, which could be used together with SW observations to achieve a more holistic understanding of the dust radiative effect.

Description: According to climate model simulations, the changing altitude of middle and high clouds is the dominant contributor to the positive global mean longwave cloud feedback. Nevertheless, the mechanisms of this longwave cloud altitude feedback and its magnitude have not yet been verified by observations. Accurate, stable, and long-term observations of a metric-characterizing cloud vertical distribution that are related to the longwave cloud radiative effect are needed to achieve a better understanding of the mechanism of longwave cloud altitude feedback. This study shows that the direct measurement of the altitude of atmospheric lidar opacity is a good candidate for the necessary observational metric. The opacity altitude is the level at which a spaceborne lidar beam is fully attenuated when probing an opaque cloud. By combining this altitude with the direct lidar measurement of the cloud-top altitude, we derive the effective radiative temperature of opaque clouds which linearly drives (as we will show) the outgoing longwave radiation. We find that, for an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m−2. Similarly, the longwave cloud radiative effect of optically thin clouds can be derived from their top and base altitudes and an estimate of their emissivity. We show with radiative transfer simulations that these relationships hold true at single atmospheric column scale, on the scale of the Clouds and the Earth's Radiant Energy System (CERES) instantaneous footprint, and at monthly mean 2° × 2° scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin-cloud coverage is 36 % and contributes 27 % of the global mean cloud radiative effect. The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated provides a simple formulation of the cloud radiative effect in the longwave domain and so helps us to understand the longwave cloud altitude feedback mechanism.

Description: According to climate models’ simulations, cloud altitude change is the dominant contributor of the positive ensemble mean longwave cloud feedback. Nevertheless, the cloud altitude longwave feedback mechanism and its amplitude struggle yet to be verified in observations. An accurate, stable in time, and potentially long-term observation of a cloud property summarizing the cloud vertical distribution and driving the longwave cloud radiative effect is needed to hope to achieve a better understanding of the cloud altitude longwave feedback mechanism. This study proposes the direct lidar measurement of the atmosphere opacity altitude is a good candidate to derive the needed observed cloud property. This altitude is the level at which a space-borne lidar beam is fully attenuated when probing an optically opaque cloud. By combining this altitude with the direct lidar measurement of the cloud top altitude, we derive the radiative temperature of opaque clouds that linearly drives, as we show, the outgoing longwave radiation. This linear relationship provides a simple formulation of the cloud radiative effect in the longwave domain for opaque clouds and so, helps to understand the cloud altitude longwave feedback mechanism. We find that in presence of an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m−2. We show that this linear relationship holds true at single atmospheric column scale with radiative transfer simulations, at instantaneous radiometer footprint scale of the Clouds and the Earth's Radiant Energy System (CERES), and at monthly mean 2° x 2° gridded scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin clouds cover 36 % and contribute to 27 %.

Description: In this study, we integrate recent aircraft measurements of dust microphysical and optical properties with satellite retrievals of aerosol and radiative fluxes to quantify the dust direct radiative effects on the shortwave (SW) and longwave (LW) radiation (denoted as DRESW and DRELW, respectively) at both the top of atmosphere (TOA) and surface in the tropical North Atlantic during summer months. Through linear regression of CERES measured TOA flux versus satellite aerosol optical depth (AOD) retrievals under cloud-free and dust-laden atmospheric conditions, we estimate the instantaneous DRESW efficiency at the top of the atmosphere (TOA) to be –49.7±7.1 W/m2/AOD and –36.5±4.8 W/m2/AOD based on AOD from MODIS and CALIOP, respectively. The corresponding DRESW at TOA is –14.2±2.0 W/m2 and –10.4±1.4 W/m2, respectively. We also estimate the instantaneous DRELW at TOA to be between +2.7±0.32 W/m2 to +3.4±0.32 W/m2 based on the difference between computed dust-free outgoing longwave radiation (OLR) and CERES-measured OLR. We then perform various sensitivity studies with recent measurements of dust particle size distribution (PSD), refractive index, and particle shape distribution to determine how the dust microphysical and optical properties affect DRE estimates and its agreement with abovementioned satellite-derived DREs. Our analysis shows that a good agreement with the observation-based estimates of instantaneous DRESW and DRELW can be achieved through a combination of recently observed PSD with substantial presence of coarse particles, a less absorptive SW refractive index, and spheroid shapes. Based on this optimal combination of dust physical and optical properties we further estimate the diurnal mean dust DRESW efficiency of –28 W/m2/AOD at TOA and –82 W/m2/AOD at surface. The corresponding TOA and surface DRESW in the region is approximately –10 W/m2 and –26 W/m2, respectively, of which ~30% is canceled out by the positive DRELW. This yields a net DRE of about –6.9 W/m2 and –18.3 W/m2 at TOA and surface, respectively. Our study suggests that the LW flux contains useful information of dust particle size, which could be used together with SW observation to achieve more holistic understanding of the dust radiative effect.

Description: Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.