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he Areal Averaged Albedo VAP yields areal averaged surface spectral albedo estimates from MFRSR measurements collected under fully overcast conditions via a simple one-line equation (Barnard et al., 2008), which links cloud optical depth, normalized cloud transmittance, asymmetry parameter, and areal averaged surface albedo under fully overcast conditions.
The Areal Averaged Albedo VAP yields areal averaged surface spectral albedo estimates from MFRSR measurements collected under fully overcast conditions via a simple one-line equation (Barnard et al., 2008), which links cloud optical depth, normalized cloud transmittance, asymmetry parameter, and areal averaged surface albedo under fully overcast conditions.
Top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth s Radiant Energy System (CERES) are estimated from empirical angular distribution models (ADMs) that convert instantaneous radiance measurements to TOA fluxes. This paper evaluates the accuracy of CERES TOA fluxes obtained from a new set of ADMs developed for the CERES instrument onboard the Tropical Rainfall Measuring Mission (TRMM). The uncertainty in regional monthly mean reflected shortwave (SW) and emitted longwave (LW) TOA fluxes is less than 0.5 W/sq m, based on comparisons with TOA fluxes evaluated by direct integration of the measured radiances. When stratified by viewing geometry, TOA fluxes from different angles are consistent to within 2% in the SW and 0.7% (or 2 W/sq m) in the LW. In contrast, TOA fluxes based on ADMs from the Earth Radiation Budget Experiment (ERBE) applied to the same CERES radiance measurements show a 10% relative increase with viewing zenith angle in the SW and a 3.5% (9 W/sq m) decrease with viewing zenith angle in the LW. Based on multiangle CERES radiance measurements, 18 regional instantaneous TOA flux errors from the new CERES ADMs are estimated to be 10 W/sq m in the SW and, 3.5 W/sq m in the LW. The errors show little or no dependence on cloud phase, cloud optical depth, and cloud infrared emissivity. An analysis of cloud radiative forcing (CRF) sensitivity to differences between ERBE and CERES TRMM ADMs, scene identification, and directional models of albedo as a function of solar zenith angle shows that ADM and clear-sky scene identification differences can lead to an 8 W/sq m root-mean-square (rms) difference in 18 daily mean SW CRF and a 4 W/sq m rms difference in LW CRF. In contrast, monthly mean SW and LW CRF differences reach 3 W/sq m. CRF is found to be relatively insensitive to differences between the ERBE and CERES TRMM directional models.
This study examines variability in marine low cloud properties derived from semi-global observations by the Tropical Rainfall Measuring Mission (TRMM) satellite, as linked to the aerosol index (AI) and lower-tropospheric stability (LTS). AI is derived from the Moderate Resolution Imaging Spectroradiometer (Terra MODIS) sensor and the Goddard Chemistry Aerosol Radiation and Transportation (GOCART) model, and is used to represent column-integrated aerosol concentrations. LTS is derived from the NCEP/NCAR reanalysis, and represents the background thermodynamic environment in which the clouds form. Global statistics reveal that cloud droplet size tends to be smallest in polluted (high-AI) and strong inversion (high-LTS) environments. Statistical quantification shows that cloud droplet size is better correlated with AI than it is with LTS. Simultaneously, the cloud liquid water path (CLWP) tends to decrease as AI increases. This correlation does not support the hypothesis or assumption that constant or increased CLWP is associated with high aerosol concentrations. Global variability in corrected cloud albedo (CCA), the product of cloud optical depth and cloud fraction, is very well explained by LTS, while both AI and LTS are needed to explain local variability in CCA. Most of the local correlations between AI and cloud properties are similar to the results from the global statistics, while weak anomalous aerosol-cloud correlations appear locally in the regions where simultaneous high (low) AI and low (high) LTS compensate each other. Daytime diurnal cycles explain additional variability in cloud properties. CCA has the largest diurnal cycle in high-LTS regions. Cloud droplet size and CLWP have weak diurnal cycles that differ between clean and polluted environments. The combined results suggest that investigations of marine low cloud radiative forcing and its relationship to hypothesized aerosol indirect effects must consider the combined effects of aerosols, thermodynamics, and the diurnal cycle.
The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms.
In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.
A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.
Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.
This study aims to create observation-based cloud radiative kernel (CRK) datasets and evaluate them by direct comparison of CRK and the CRK-derived cloud feedback datasets. Based on the International Satellite Cloud Climatology Project (ISCCP) H datasets, we calculate CRKs (called FH CRKs) as 2D joint function/histogram of cloud optical depth and cloud top pressure for shortwave, longwave, and their sum, Net, at the top of atmosphere (TOA), as well as, for the first time, at the surface (SFC) and in the atmosphere (ATM). The direct comparison shows that FH agrees reasonably well with three other TOA CRK datasets. With cloud fraction change (CFC) datasets of the same histogram for doubled-CO2 simulation from 10 CFMIP1 models, we derive all the TOA, SFC and ATM cloud feedback using the FH CRKs. Our TOA cloud feedback is highly similar to the previous counterparts. Based on the comparison for the 4 CRK datasets and the 10 CFC datasets, we estimate the uncertainty budget for the CRK-derived cloud feedback and show that the CFC-associated uncertainty contributes > 98.5% of the total cloud feedback uncertainty while CRK’s is very small. Our preliminary evaluation shows that some near-zero/small cloud feedback in the TOA-alone feedback indeed results from the compensation of sizable cloud feedback of the SFC and ATM feedback, demonstrating that they help reveal some significant surface and atmospheric cloud feedback whose sum appears insignificant in TOA-alone feedback
This study aims to create observation-based cloud radiative kernel (CRK) datasets and evaluate them by direct comparison of CRK and the CRK-derived cloud feedback datasets. Based on the International Satellite Cloud Climatology Project (ISCCP) H datasets, we calculate CRKs (called ISCCP-FH or FH CRKs) as 2D joint function/histogram of cloud optical depth and cloud top pressure for shortwave (SW), longwave (LW), and their sum, Net, at the top of atmosphere (TOA), as well as, for the first time, at the surface (SFC) and in the atmosphere (ATM). With cloud fraction change (CFC) datasets from doubled-CO2 simulation and short-term observational anomalies, we derive all the TOA, SFC and ATM cloud feedback for SW, LW and Net using our CRKs.The direct comparison with modeled and observed CRKs (or cloud radiative effects), cloud feedback from previous model results and the Clouds and the Earth's Radiant Energy System products show that our CRKs and CRK-derived cloud feedback are reasonably well validated. We estimate the uncertainty for the CRK-derived cloud feedback and show that the CFC-associated uncertainty contributes >98.5% of the total cloud feedback uncertainty while CRK's is very small. Our preliminary evaluation also shows that some near-zero/small cloud feedback in the TOA-alone feedback indeed results from the compensation of sizable cloud feedback of the SFC and ATM feedback and reveals some significant surface and atmospheric cloud feedback whose sum appears insignificant in TOA-alone feedback. In addition, the atmospheric longwave cloud feedback seems to play a role in enhancing meridional atmospheric energy transport.
The NASA/GEWEX Surface Radiation Budget Version 4 (SRB Rel4) product is now publicly available, covering the period from July 1983 through June 2017. This supersedes the SRB Rel3 (Stackhouse et al., 2011) product which has been used in the community for a wide variety of applications, including climate model validation, agriculture, solar energy, and architecture. SRB Rel4 uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Rel3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters. Rel4 incorporates several important algorithm improvements. These include recalculated shortwave (SW) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both shortwave and longwave (LW) now also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MACv1). LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we evaluate the SRB Rel4 top of atmosphere (TOA) and surface fluxes in the context of weather states and oceanic regions. Weather states (Tselioudis et al., 2013, Tselioudis et al., 2021) are defined by K-means clustering 2-D histograms of satellite-retrieved cloud optical depths and cloud top pressures. The most recent (Tselioudis et al., 2021) weather states derived from the International Satellite Cloud Climatology Project (ISCCP) H-series data results in eight cloud weather states and one clear sky weather state, for a total of nine weather states. We examine the statistics of SRB Rel4 fluxes for each weather state and a variety of relevant land and ocean regions. We compare to similar analyses performed on CERES EBAF and SYN1Deg flux products, and validate against Baseline Surface Radiometer Network (BSRN) land stations and Pacific Marine Environmental Laboratory (PMEL) ocean buoy data. It is demonstrated that the weather state concept is valuable when examining the comparative strengths and weaknesses of satellite radiative flux algorithms.
Cloud parameters derived from visible and infrared window data from the Geostationary Operational Environmental Satellite (GOES) are compared to corresponding properties determined from instrumentation on San Nicolas Island off the coast of California during the First ISCCP Regional Experiment marine stratocumulus intensive field observations period in July 1987. Examination of the satellite imagery revealed that the apparent bias can be explained by the persistence of the clouds over the northwest part of the island during periods of clearing around the island. Diurnal variations in the cloud cover were very significant; minimum cloudiness occurred during the late afternoon and maximum cloudiness early in the morning. Relationships were established between the satellite-derived cloud optical depth and two surface-observed quantities: cloud liquid water path and cloud thickness. Simultaneous observations of liquid water path and satellite-derived cloud optical depth were used to infer effective cloud-droplet radius, resulting in good agreement with correlative data. The diurnal variations in cloud amount are accompanied by changes in cloud thickness, cloud-top height, cloud liquid water path, and effective droplet size. These observations provide the most complete picture, to date, of the diurnal cycle of marine stratocumulus clouds, confirming previous satellite-based inferences of the diurnal behavior of marine stratocumulus at larger scales.
While solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth’s atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m−2 (50 %) and 329Wm-2 (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon’s shadow caused a reduction of approximately 7 %–8% in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon’s shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.
We present images of the nightside of Venus taken in the near-infrared windows at 1.0, 1.1, 1.18, 1.28, 1.31, and 2.3 microns with the new infrared camera/spectrometer IRIS on the Anglo-Australian Telescope. These data were taken in spectral-mapping mode. This technique involves scanning the telescope perpendicular to the slit, while collecting spectra at successive slit positions across the planet. We produce data cubes with one spectral and two spatial dimensions. Images can be extracted over any wavelength regions. Each image has square pixels of 0.8 inch resolution. We reduced the scattered light from the sunlit crescent in images extracted from each window by subtracting images taken on either side of the window, where the Venus atmosphere is opaque. Unlike the short wavelength windows, which reveal thermal contrasts that originate primarily from the surface and deep atmosphere, the emission in the 2.3 microns window is produced at much higher altitudes (30-40 km). Emission contrasts seen near 2.3 microns are associated with horizontal variations in the cloud optical depths, and have rotation periods of about six days. We detect large contrasts in infrared emission (20-40 percent) across the disc of Venus in the 1.0-, 1.1-, 1.18-, 1.28-, and 1.31-micron images. Contrasts at these wavelengths may be due to a combination of variations in the optical depths of the overlying sulfuric acid clouds and differences in surface emission. Comparison with the 2.3-micron images show that the patterns seen in the 1.28- and 1.31-micron windows are consistent with cloud optical depth variations alone and require no contribution from the surface. However, images at 1.0, 1.1, and 1.8 microns from July 1991 show a dark feature having a contrast that increases with decreasing wavelength. This behavior is contrary to that expected of cloud absorption. Images taken on three successive days in October show another dark feature that is stationary with respect to the surface. These regions of lower emission correspond closely to the high-altitude surface regions of Beta Regio and Aphrodite Terra. The images can potentially reveal the near-infrared emissiveity of the surface of Venus, thereby complementing Magellan radar reflectivity and ground based radio emissivity measurements. The contrast ratio between highlands and plains is much smaller than would be expected for blackbody radiation from the surface along. Unlike at radio wavelengths, where the atmosphere is essentially transparent, at near-infrared wavelengths the atmosphere emits, absorbs, and scatters radiation, and can modify the observed topographically induced contrasts. The additional radiation from the atmosphere reduces the contrast, and further modification would be expected if terrain at different altitudes has different emissivities. A fit to our data therefore requires, and may constrain, a model of the lowest scale height of the atmosphere.
An extensive verification of cloud property retrievals has been conducted for two algorithms using zenith radiances measured by the Atmospheric Radiation Measurement (ARM) Program ground-based passive two-channel (673 and 870 nm) Narrow Field-Of-View Radiometer. The underlying principle of these algorithms is that clouds have nearly identical optical properties at these wavelengths, but corresponding spectral surface reflectances (for vegetated surfaces) differ significantly. The first algorithm, the RED vs. NIR, works for a fully three-dimensional cloud situation. It retrieves not only cloud optical depth, but also an effective radiative cloud fraction. Importantly, due to one-second time resolution of radiance measurements, we are able, for the first time, to capture detailed changes in cloud structure at the natural time scale of cloud evolution. The cloud optical depths tau retrieved by this algorithm are comparable to those inferred from both downward fluxes in overcast situations and microwave brightness temperatures for broken clouds. Moreover, it can retrieve tau for thin patchy clouds, where flux and microwave observations fail to detect them. The second algorithm, referred to as COUPLED, couples zenith radiances with simultaneous fluxes to infer 2. In general, the COUPLED and RED vs. NIR algorithms retrieve consistent values of tau. However, the COUPLED algorithm is more sensitive to the accuracies of measured radiance, flux, and surface reflectance than the RED vs. NIR algorithm. This is especially true for thick overcast clouds where it may substantially overestimate z.
It has been well known that convection tends to be more intense over land than over ocean and continental convection generally contains wider cores that are protected from entrainment than their oceanic counterparts. How does this difference in convective intensity impact the rest of cloud types and associated cloud radiative effects (CREs)? We select five regions in the tropical “chimney” zones, with two regions over land (Africa and Amazon) and three regions over ocean (eastern and western Pacific, and Atlantic) to understand the differences in the cloud-type mean cloud properties and associated CREs using 20-years high-resolution (2x2 km2) CERES satellite data. The cloud types are based upon the ISCCP classification using the joint cloud-top pressure and cloud optical depth distribution. These five regions are compared to the entire tropics (25°S to 25°N). First, we compare the frequencies of occurrence of cloud types among the regions. Compared to the entire tropics, the “chimney” zones are cloudier, particularly, for cloud types with moderate cloud optical depths in the middle and upper troposphere. Except for the eastern Pacific region, the low-level cloud types are less abundant over land (due to higher boundary layers) and ocean (due to weaker lower-tropospheric subsidence). Over Africa, upper-level clouds are scarcer, due perhaps to weak production of convective anvils related to the drier atmosphere. Second, liquid water path (LWP) and ice water path (IWP) are compared among the regions. Compared to the entire tropics, mean LWPs for moderate cloud optical depths are higher for oceanic regions but lower for Africa while they are slightly lower in the lower troposphere but slightly higher in the middle troposphere for Amazon. Not surprisingly, mean IWPs are higher over land than over ocean, which is directly related to the difference in convective intensity. That is, the explanations to this result are the relatively weak convective intensity over the eastern Pacific and the abundance of anvil clouds over the western Pacific. Both reduce the mean IWPs. The CRE results are still being analyzed because the totally-clear grids (1° x 1°) of the CERES data product should be removed before taking a regional mean of clear-sky fluxes, which cause the wrong signs of CREs for a few cloud types.
The NASA/GSFC Scanning Raman Lidar (SRL) was stationed on Andros Island in the Bahamas during August - September, 1998 as a part of the third Convection and Moisture Experiment (CAMEX-3) which focussed on hurricane development and tracking. During the period August 21 - 24, hurricane Bonnie passed near Andros Island and influenced the water vapor and cirrus cloud measurements acquired by the SRL. Two drying signatures related to the hurricane were recorded by the SRL (Scanning Raman Lidar) and other sensors. Cirrus cloud optical depths (at 351 nm) were also measured during this period. Optical depth values ranged from approximately 0.01 to 1.4. The influence of multiple scattering on these optical depth measurements was studied with the conclusion that the measured values of optical depth are less than the actual value by up to 20% . The UV/IR cirrus cloud optical depth ratio was estimated based on a comparison of lidar and GOES measurements. Simple radiative transfer model calculations compared with GOES satellite brightness temperatures indicate that satellite radiances are significantly affected by the presence of cirrus clouds if IR optical depths are approximately 0.02 or greater. This has implications for satellite cirrus detection requirements.
The NASA/GSFC Scanning Raman Lidar (SRL) was stationed on Andros Island in the Bahamas during August - September, 1998 as a part of the third Convection and Moisture Experiment (CAMEX-3) which focussed on hurricane development and tracking. During the period August 21 - 24, hurricane Bonnie passed near Andros Island and influenced the water vapor and cirrus cloud measurements acquired by the SRL. Two drying signatures related to the hurricane were recorded by the SRL and other sensors. Cirrus cloud optical depths (at 351 nm) were also measured during this period. Optical depth values ranged from approximately 0.01 to 1.4. The influence of multiple scattering on these optical depth measurements was studied with the conclusion that the measured values of optical depth are less than the actual value by up to 20%. The UV/lR cirrus cloud optical depth ratio was estimated based on a comparison of lidar and GOES measurements. Simple radiative transfer model calculations compared with GOES satellite brightness temperatures indicate that satellite radiances are significantly affected by the presence of cirrus clouds if IR optical depths are approximately 0.02 or greater. This has implications for satellite cirrus detection requirements.