Abstract

A two-stream radiative transfer model is used to examine the radiative properties of cirrus clouds and compare simulations with the observations made during the cirrus FIRE IFO. The sensitivity of cirrus cloud radiative properties to altitude and size distribution changes are examined. The net radiative effect of cirrus in the infrared is largely determined by the amount of ice in the cloud and the surface—cloud base temperature difference (and thus altitude). Increases (decreases) of this temperature difference produce a net radiative heating (cooling). Cloud-top solar heating increases (decreases) with increasing (decreasing) altitude as the optical path of the atmosphere above the cloud layer decreases (increases). The impact of varying concentrations of ice particles less than 100 μm in diameter is also examined. The addition of these particles greatly enhances the longwave absorption and shortwave albedo of cirrus clouds in a manner that is spectrally dependent. Model simulations using observed microphysical and environmental conditions are compared to measured cirrus cloud radiative properties. Although cloud inhomogeneties are shown to be quite large, broad agreement in the cloud emittance is found between the highly uncertain observations of FIRE, other aircraft observations, and model simulations. Similar comparisons of the solar albedo reveal cirrus clouds to be significantly brighter than predicted by the model. Possible explanations of this brightening anomaly suggest that it may not be possible to use Mie scattering to model the cloud albedo.

Abstract

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⁻².

Abstract

This paper examines the effects of the relationship between cirrus cloud ice water content and cloud temperature on climate change. A simple mechanistic climate model is used to study the feedback between ice water content and temperature. The central question studied in this paper concerns the extent to which both the radiative and microphysical properties of cirrus cloud influence such a feedback. To address this question, a parameterization of the albedo and emissivity of clouds is introduced. Observations that relate the ice water content to cloud temperature are incorporated in the parameterization to introduce a temperature dependence to both albedo and emittance. The cloud properties relevant to the cloud feedback are expressed as functions of particles size r_e , asymmetry parameter g and cloud temperature and analyses of aircraft measurements, lidar and ground based radiometer data are used to select r_e and g. It was shown that scattering calculations assuming spherical particles with a distribution described by r_e = 16 μm reasonably matched the lidar and radiometer data. However, comparison of cloud radiation properties measured from aircraft to those parameterized in this study required values of g significantly smaller than those derived for spheres but consistent with our understanding of nonspherical particle scattering.

The climate simulations revealed that the influence of cirrus cloud on climate was strongly affected by the choice of r_e and g: parameters that are both poorly known for cirrus. It was further shown that the effect of ice water feedback on a CO₂ warming simulation could be either positive or negative depending on the value of r_e assumed. Based on these results, it was concluded that prediction of cirrus cloud feedback on climate is both premature and limited by our lack of understanding of the relationship between size and shape of ice crystals and the gross radiative properties of cirrus.

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.

Abstract

The surface radiation budget of a region is strongly tied to its climate. An 8-yr climatology of surface radiation budget components for 2.5° regions over the earth is examined in order to learn how the regional climate and surface radiation are related. The yearly cycles of a few individual regions were studied by plotting monthly mean net longwave flux as a function of net shortwave flux at the surface. These plots show trajectories that are characteristic of the climate class. The behavior of the trajectories of surface radiation and their relation to the regional climate can be understood with simple conceptual models for many cases.

From an examination of these trajectories, a set of parameters is developed, such as mean net longwave flux and range of net shortwave flux, which distinguish various climate classes on the basis of the surface radiation. These criteria are applied to produce a map of regional climate classes based on surface radiation, similar to those of Koeppen or Trewartha and Horn, which were based on vegetation, temperature, and precipitation. The current maps can be used to explore the relationships between surface radiation and regional climate.

Abstract

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).

Abstract

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m⁻² each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30 W m⁻² over trade wind cumulus regions, yet smaller CRE by about −30 W m⁻² over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15 W m⁻² smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

Abstract

The Clouds and the Earth’s Radiant Energy Systems (CERES) project utilizes radiometric measurements taken aboard the Terra and Aqua spacecrafts to derive the world-class data products needed for climate research. Achieving the exceptional fidelity of the CERES data products, however, requires a considerable amount of processing to assure quality and to verify accuracy and precision, which results in the CERES data being released more than 6 months after the satellite observations. For most climate studies such delays are of little consequence; however, there are a significant number of near–real time uses for CERES data products. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was therefore developed to provide a rapid release version of the CERES results, which could be made available to the research and applications communities within 1 week of the satellite observations by exchanging some accuracy for speed. FLASHFlux has both achieved this 1-week processing objective and demonstrated the ability to provide remarkably good agreement when compared with the CERES data products for both the instantaneous single-scanner footprint (SSF) fluxes and the time- and space-averaged (TISA) fluxes. This paper describes the methods used to expedite the production of the FLASHFlux SSF fluxes by utilizing data from the CERES and Moderate Resolution Imaging Spectroradiometer instruments, as well as other meteorological sources. This paper also reports on the validation of the FLASHFlux SSF results against ground-truth measurements and the intercomparison of FLASHFlux and CERES SSF results. A complementary paper will discuss the production and validation of the FLASHFlux TISA fluxes.

Abstract

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.

Abstract

Four different types of estimates of the surface downwelling longwave radiative flux (DLR) are reviewed. One group of estimates synthesizes global cloud, aerosol, and other information in a radiation model that is used to calculate fluxes. Because these synthesis fluxes have been assessed against observations, the global-mean values of these fluxes are deemed to be the most credible of the four different categories reviewed. The global, annual mean DLR lies between approximately 344 and 350 W m⁻² with an error of approximately ±10 W m⁻² that arises mostly from the uncertainty in atmospheric state that governs the estimation of the clear-sky emission. The authors conclude that the DLR derived from global climate models are biased low by approximately 10 W m⁻² and even larger differences are found with respect to reanalysis climate data. The DLR inferred from a surface energy balance closure is also substantially smaller that the range found from synthesis products suggesting that current depictions of surface energy balance also require revision. The effect of clouds on the DLR, largely facilitated by the new cloud base information from the CloudSat radar, is estimated to lie in the range from 24 to 34 W m⁻² for the global cloud radiative effect (all-sky minus clear-sky DLR). This effect is strongly modulated by the underlying water vapor that gives rise to a maximum sensitivity of the DLR to cloud occurring in the colder drier regions of the planet. The bottom of atmosphere (BOA) cloud effect directly contrast the effect of clouds on the top of atmosphere (TOA) fluxes that is maximum in regions of deepest and coldest clouds in the moist tropics.