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Clouds and the Earth’s Radiant Energy System (CERES) FluxByCldTyp Edition 4 Data Product1. Introduction One of the greatest challenges in climate model projections of warming in response to anthropogenic forcing is the representation of clouds and their interactions with Earth’s radiation budget in climate models ( Boucher et al. 2013 ). Cloud processes occur over a range of time and space scales, which makes them difficult to model. Climate models agree that feedbacks collectively amplify the surface temperature response to external forcing, but the strengths of the
1. Introduction One of the greatest challenges in climate model projections of warming in response to anthropogenic forcing is the representation of clouds and their interactions with Earth’s radiation budget in climate models ( Boucher et al. 2013 ). Cloud processes occur over a range of time and space scales, which makes them difficult to model. Climate models agree that feedbacks collectively amplify the surface temperature response to external forcing, but the strengths of the
Simulating Radiative Fluxes through Southeastern Pacific Stratocumulus Clouds during VOCALS-RExparameterization of processes important to the clouds. Cloud radiative forcing, as well as cloud microphysical and dynamical processes, remains as one of the largest sources of uncertainty in projecting future climate ( Bony et al. 2006 ). Model simulations show differing responses by boundary layer clouds to such forcing factors as increasing sea surface temperatures ( Zhang et al. 2013 ), greenhouse gases ( Bretherton et al. 2013 ), and aerosol properties ( Caldwell and Bretherton 2009 ); therefore, models
parameterization of processes important to the clouds. Cloud radiative forcing, as well as cloud microphysical and dynamical processes, remains as one of the largest sources of uncertainty in projecting future climate ( Bony et al. 2006 ). Model simulations show differing responses by boundary layer clouds to such forcing factors as increasing sea surface temperatures ( Zhang et al. 2013 ), greenhouse gases ( Bretherton et al. 2013 ), and aerosol properties ( Caldwell and Bretherton 2009 ); therefore, models
, α ( ν ) −1 , for each AERI spectral “microwindow.” The resultant iterated values of α ( ν ), as shown in section 7b , represent a spectrum of visible-to-infrared optical depth ratios across the atmospheric infrared window. The scale factor α ( ν ) is derived from data near the peak of both downwelling solar radiation (lidar wavelength) and upwelling terrestrial radiation (infrared microwindows); thus, it provides a mechanism for measuring the effective cloud forcing in a spectral region that
, α ( ν ) −1 , for each AERI spectral “microwindow.” The resultant iterated values of α ( ν ), as shown in section 7b , represent a spectrum of visible-to-infrared optical depth ratios across the atmospheric infrared window. The scale factor α ( ν ) is derived from data near the peak of both downwelling solar radiation (lidar wavelength) and upwelling terrestrial radiation (infrared microwindows); thus, it provides a mechanism for measuring the effective cloud forcing in a spectral region that
parameterization of the lidar ratio for ice and liquid water clouds is fundamental for current space-based lidar systems to accurately compute extinction and backscatter coefficients. This parameterization should account for the dependence of lidar ratio on geographic location. However, more research is needed to improve our understanding of the relationship between lidar ratio and cloud generation mechanism, which consequently should improve the accuracy of cloud radiative forcing estimations from space
parameterization of the lidar ratio for ice and liquid water clouds is fundamental for current space-based lidar systems to accurately compute extinction and backscatter coefficients. This parameterization should account for the dependence of lidar ratio on geographic location. However, more research is needed to improve our understanding of the relationship between lidar ratio and cloud generation mechanism, which consequently should improve the accuracy of cloud radiative forcing estimations from space
intercompared withtwo independent products, the Air Force Real-Time Nephanalysis (RTNEPH), and the International SatelliteCloud Climatology Project (ISCCP). The ISCCP cloud database is a climate product processed retrospectivelysome years after the data are collected. Thus, only CLAVR and RTNEPH can satisfy the real-time requirementsfor numerical weather prediction (NWP) models. Compared with RTNEPH and ISCCP, which only use twochannels in daytime retrievals and one at night, CLAVR utilizes all five
intercompared withtwo independent products, the Air Force Real-Time Nephanalysis (RTNEPH), and the International SatelliteCloud Climatology Project (ISCCP). The ISCCP cloud database is a climate product processed retrospectivelysome years after the data are collected. Thus, only CLAVR and RTNEPH can satisfy the real-time requirementsfor numerical weather prediction (NWP) models. Compared with RTNEPH and ISCCP, which only use twochannels in daytime retrievals and one at night, CLAVR utilizes all five
A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Cloudslimited applicability to the research community. Previous studies have shown the feasibility of using Air Force weather data for characterizing single and multiple scattering through clouds at optical wavelengths ( Roadcap et al. 2015 ). This research seeks to describe the development of an integrated internal LEEDR capability leveraging these external datasets relevant to cloud microphysical properties in a near-real-time environment. LEEDR’s modularity and ability to ingest NWP data are exploited to
limited applicability to the research community. Previous studies have shown the feasibility of using Air Force weather data for characterizing single and multiple scattering through clouds at optical wavelengths ( Roadcap et al. 2015 ). This research seeks to describe the development of an integrated internal LEEDR capability leveraging these external datasets relevant to cloud microphysical properties in a near-real-time environment. LEEDR’s modularity and ability to ingest NWP data are exploited to
. Barkstrom, V. Ramanathan, R. D. Cess, and G. G. Gibson, 1990: Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J. Geophys. Res., 95, 18 687–18 703. 10.1029/JD095iD11p18687 House, F. B., A. Gruber, G. E. Hunt, and A. T. Mecherikunnel, 1986:History of satellite missions and measurements of the Earth Radiation Budget (1957–1984). Rev. Geophys., 24, 357–378. 10.1029/RG024i002p00357 Iqbal, M., 1983: An Introduction to Solar Radiation. Academic
. Barkstrom, V. Ramanathan, R. D. Cess, and G. G. Gibson, 1990: Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J. Geophys. Res., 95, 18 687–18 703. 10.1029/JD095iD11p18687 House, F. B., A. Gruber, G. E. Hunt, and A. T. Mecherikunnel, 1986:History of satellite missions and measurements of the Earth Radiation Budget (1957–1984). Rev. Geophys., 24, 357–378. 10.1029/RG024i002p00357 Iqbal, M., 1983: An Introduction to Solar Radiation. Academic
1. Introduction The success, or failure, of global numerical climate simulations can be traced directly to the accuracy of the empirical relationships and input parameters required to replicate significant dynamic and radiative processes. Knowledge of the vertical structure of cloud and aerosol scattering properties or layers from varying climate regimes is fundamental. Analysis of surface or top-of-the-atmosphere radiative fluxes is not sufficient in itself. Models that can correctly define
1. Introduction The success, or failure, of global numerical climate simulations can be traced directly to the accuracy of the empirical relationships and input parameters required to replicate significant dynamic and radiative processes. Knowledge of the vertical structure of cloud and aerosol scattering properties or layers from varying climate regimes is fundamental. Analysis of surface or top-of-the-atmosphere radiative fluxes is not sufficient in itself. Models that can correctly define
1. Introduction The interactions of aerosols with clouds represent a leading source of uncertainty in quantifying anthropogenic radiative forcing of climate globally since preindustrial times ( Solomon et al. 2007 ). Clouds are also reported to constitute the largest source of uncertainty in climate sensitivity to radiative forcing in current coupled ocean–atmosphere climate models ( Soden and Held 2006 ). In the tropics, differences in the predicted sensitivity of marine boundary layer clouds
1. Introduction The interactions of aerosols with clouds represent a leading source of uncertainty in quantifying anthropogenic radiative forcing of climate globally since preindustrial times ( Solomon et al. 2007 ). Clouds are also reported to constitute the largest source of uncertainty in climate sensitivity to radiative forcing in current coupled ocean–atmosphere climate models ( Soden and Held 2006 ). In the tropics, differences in the predicted sensitivity of marine boundary layer clouds
well as to short-term instrument andLOWTRAN7 input variations. LOWTRAN7 and the observations agree better, in the mean, than the commonlyaccepted uncertainties for either would suggest. Maximum cloud radiative forcing at the surface for each site isquantified as a by-product of the comparison process.1. Introduction The spectrally integrated, 2~r-sr downward longwaveirradiance at the surface, DLs, is a major componentof the earth's radiation (and subsequently the earth'senergy) budget, which
well as to short-term instrument andLOWTRAN7 input variations. LOWTRAN7 and the observations agree better, in the mean, than the commonlyaccepted uncertainties for either would suggest. Maximum cloud radiative forcing at the surface for each site isquantified as a by-product of the comparison process.1. Introduction The spectrally integrated, 2~r-sr downward longwaveirradiance at the surface, DLs, is a major componentof the earth's radiation (and subsequently the earth'senergy) budget, which
