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An improvement was developed and tested for surface longwave flux algorithms used in the Clouds and the Earth's Radiant Energy System processing based on lessons learned during the validation of global results of those algorithms. The algorithms involved showed significant overestimation of downward longwave flux for certain regions, especially dry--arid regions during hot times of the day. The primary cause of this overestimation was identified and the algorithms were modified to (i) detect meteorological conditions that would produce an overestimation, and (ii) apply a correction when the overestimation occurred. The application of this correction largely eliminated the positive bias that was observed in earlier validation studies. Comparisons of validation results before and after the application of correction are presented. DOI: 10.1175/2010JAMC2463.1

Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic, This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce 20 three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-averaged transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction (i.e., the cloud fraction with respect to the solar beam direction).

Conventional observations of climate parameters are sparse in space and/or time, and the representativeness of such information needs to be optimized. Observations from satellites provide improved spatial coverage over point observations; however, they pose new challenges for obtaining homogeneous coverage. Surface radiative fluxes, the forcing functions of the hydrologic cycle and biogeophysical processes, are now becoming available from global-scale satellite observations. They are derived from independent satellite platforms and sensors that differ in temporal and spatial resolution and in the size of the footprint from which information is derived. Data gaps, degraded spatial resolution near boundaries of geostationary satellites, and different viewing geometries in areas of satellite overlap could result in biased estimates of radiative fluxes. In this study will be discussed issues related to the sources of inhomogeneity in surface radiative fluxes as derived from satellites, development of an approach to obtain homogeneous datasets, and application of the method to the widely used International Satellite Cloud Climatology Project data that currently serve as a source of information for deriving estimates of surface and top-of-the-atmosphere radiative fluxes. Introduced is an empirical orthogonal function (EOF) iteration scheme for homogenizing the fluxes. The scheme is evaluated in several ways, including comparison of the inferred radiative fluxes with ground observations, both before and after the EOF approach is applied. On the average, the latter reduces the RMS error by about 2-3 W [m.sup.-2].

An objective method is developed to monitor the stability of spaceborne instruments, aimed at distinguishing climate trend from instrument drift in satellite-based climate observation records. This method is based on four-years of Clouds and the Earth's Radiant Energy System (CERES) broadband observations of deep convective cloud systems with cloud-top temperature lower than 205 K and with large optical depths. The implementation of this method to the CERES instrument stability analysis reveals that the monthly albedo distributions ate practically the same for deep convective clouds with CERES measurements acquired from both the Tropical Rainfall Measuring Mission and Terra satellite platforms, indicating that CERES instruments ate well calibrated and stable during both missions. Furthermore, with a nonlinear regression neural network narrowband-broadband conversion, this instrument-stability monitoring method can also be applied to narrowband instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Scanner (VIRS). The results show that the drifts associated with both VIRS and MODIS instruments ate less than 1% during a four-year period. Since the CERES albedo measurements are highly accurate, the absorptance of these opaque clouds can be reliably estimated. The absorptions of these clouds from observations ate around 25%, whereas the absorptions from theory can be as low as 18%, depending on ice cloud microphysics. Index Terms--Absorption anomaly, albedo, deep convective cloud, instrument stability, radiative transfer.

This article presents the latest parameters and delivery, methods that provide global solar energy and meteorological resources on the Internet. Over the past several years the number of parameters in the Surface meteorology and Solar Energy Data Set has tripled. The newest parameters include solar geometry, a suite of wind speed and wind direction data, diffuse, direct normal and tilted surface solar irradiance. Requests by users and recommendations by the renewable energy industry have prompted the growth. [DOI: 10.1115/1.1748466]

This paper describes a classroom project that exposes students to research data collected during the Cirrus II First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment Information Systems Office from Parsons, Kansas, during November and December 1991. The data employed in this project were primarily those obtained from a Michelson interferometer. The students were assigned a number of tasks that were aimed at (i) providing them with a basic understanding of a Michelson interferometer and, most importantly, an appreciation of the importance of calibration, (ii) understanding the spectral distribution of clear-sky emission and identifying major gaseous absorption features, (iii) understanding the effects of cirrus clouds on the emission spectrum, and finally (iv) learning how these spectra may be used to derive certain properties of the clouds and in so doing appreciate some of the limitations and ambiguities of this particular type of remote sensing.

Weather anomalies that increase clouds influence the reliability of both renewable energy and building environmental-control systems. Non-grid solar power systems may run out of capacity for such items as communications electronics, flood-warning stream gages, refrigerators, and small village power systems. This paper provides 1 X 1-degree resolution global maps that identify those regions which experienced large abnormal solar energy during a 10-year period. A source is identified where specific values for maximum year-to-year variability can be obtained in regions where ground-site measurements do not exist. The information may aid in the selection of safety factors for solar power systems. [DOI: 10.115/1.1384570]