The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations
The interpretation of satellite-observed radiances to derive cloud optical depth and effective particle size requires radiative transfer calculations relating these parameters to the reflectance, transmittance, and emittance of the cloud. Such computations can be extremely time consuming when used in an operational mode to analyze routine satellite data. Adding-doubling (AD) radiative transfer models are used here to compute reflectance and effective emittance at wavelengths commonly used by operational meteorological satellite imagers for droplet effective radii ranging from 2 to 32 m and for distributions of randomly oriented hexagonal ice crystals with effective diameters varying from 6 to 135 m. Cloud reflectance lookup tables were generated at the typical visible-channel wavelength of 0.65 m and the solar-infrared (SI) at wavelengths of 3.75 and 3.90 m. A combination of four-point Lagrangian and linear interpolation between the model nodal points is the most accurate and economical method for estimating reflectance as a function of particle size for any set of solar zenith, viewing zenith, and relative azimuth angles. Compared to exact AD calculations, the four-point method retrieves the reflectance to within 3%-9% for water droplets and ice crystals, respectively. Most of the error is confined to scattering angles near distinct features in the phase functions. The errors are reduced to 2% for ice when the assessment is constrained to only those angles that are actually useful in satellite retrievals. Effective emittance, which includes absorption and scattering effects, was computed at SI, infrared (IR; 10.7 and 10.8 m), and split-window (WS; 11.9 and 12.0 m) wavelengths for a wide range of surface and cloud temperatures using the same ice crystal and water droplet distributions. The results were parameterized with a 32-term polynomial model that depends on the clear-cloud radiating temperature difference, the clear-sky temperature, and viewing zenith angle. A four-point Lagrangian method is used to interpolate between optical depth nodes. The model reproduces the adding-doubling results with an overall accuracy better than 2%, 0.4%, and 0.3%, respectively, for the SI, IR, and WS emittances, a substantial reduction in the error compared to earlier para-meterizations. Temperatures simulated with the emittance models are within 0.6 and 1 K for water droplets and ice crystals, respectively, in the SI channels. The IR temperatures are accurate to better than 0.05 K. During the daytime, the simulations of combined reflectance and emittance for the SI channels are as accurate as the emittance models alone except at particular scattering angles. The magnitudes of the errors depend on the angle, particle size, and solar zenith angle. Examples are given showing the parameterizations applied to satellite data. Computational time exceeds that of previous models but the accuracy gain should yield emittances that are more reliable for retrieval of global cloud microphysical properties.
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