The study of climate and climate change is hindered by a lack of information on the effect of clouds on the radiation balance of the earth, referred to as the cloud-radiative forcing. Quantitative estimates of the global distributions of cloud-radiative forcing have been obtained from the spaceborne Earth Radiation Budget Experiment (ERBE) launched in 1984. For the April 1985 period, the global shortwave cloud forcing [-44.5 watts per square meter (W/m ² )] due to the enhancement of planetary albedo, exceeded in magnitude the longwave cloud forcing (31.3 W/m ² ) resulting from the greenhouse effect of clouds. Thus, clouds had a net cooling effect on the earth. This cooling effect is large over the mid- and high-latitude oceans, with values reaching -100 W/m ² . The monthly averaged longwave cloud forcing reached maximum values of 50 to 100 W/m ² over the convectively disturbed regions of the tropics. However, this heating effect is nearly canceled by a correspondingly large negative shortwave cloud forcing, which indicates the delicately balanced state of the tropics. The size of the observed net cloud forcing is about four times as large as the expected value of radiative forcing from a doubling of CO ₂ . The shortwave and longwave components of cloud forcing are about ten times as large as those for a CO ₂ doubling. Hence, small changes in the cloud-radiative forcing fields can play a significant role as a climate feedback mechanism. For example, during past glaciations a migration toward the equator of the field of strong, negative cloud-radiative forcing, in response to a similar migration of cooler waters, could have significantly amplified oceanic cooling and continental glaciation.

We use a global climate model to compare the effectiveness of many climate forcing agents for producing climate change. We find a substantial range in the “efficacy” of different forcings, where the efficacy is the global temperature response per unit forcing relative to the response to CO₂ forcing. Anthropogenic CH₄ has efficacy ∼110%, which increases to ∼145% when its indirect effects on stratospheric H₂O and tropospheric O₃ are included, yielding an effective climate forcing of ∼0.8 W/m² for the period 1750–2000 and making CH₄ the largest anthropogenic climate forcing other than CO₂. Black carbon (BC) aerosols from biomass burning have a calculated efficacy ∼58%, while fossil fuel BC has an efficacy ∼78%. Accounting for forcing efficacies and for indirect effects via snow albedo and cloud changes, we find that fossil fuel soot, defined as BC + OC (organic carbon), has a net positive forcing while biomass burning BC + OC has a negative forcing. We show that replacement of the traditional instantaneous and adjusted forcings, Fi and Fa, with an easily computed alternative, Fs, yields a better predictor of climate change, i.e., its efficacies are closer to unity. Fs is inferred from flux and temperature changes in a fixed‐ocean model run. There is remarkable congruence in the spatial distribution of climate change, normalized to the same forcing Fs, for most climate forcing agents, suggesting that the global forcing has more relevance to regional climate change than may have been anticipated. Increasing greenhouse gases intensify the Hadley circulation in our model, increasing rainfall in the Intertropical Convergence Zone (ITCZ), Eastern United States, and East Asia, while intensifying dry conditions in the subtropics including the Southwest United States, the Mediterranean region, the Middle East, and an expanding Sahel. These features survive in model simulations that use all estimated forcings for the period 1880–2000. Responses to localized forcings, such as land use change and heavy regional concentrations of BC aerosols, include more specific regional characteristics. We suggest that anthropogenic tropospheric O₃ and the BC snow albedo effect contribute substantially to rapid warming and sea ice loss in the Arctic. As a complement to a priori forcings, such as Fi, Fa, and Fs, we tabulate the a posteriori effective forcing, Fe, which is the product of the forcing and its efficacy. Fe requires calculation of the climate response and introduces greater model dependence, but once it is calculated for a given amount of a forcing agent it provides a good prediction of the response to other forcing amounts.

Clouds cover about 70% of Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR sounders, and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature, or altitude), cloud thermodynamic phase, and cloud radiative and bulk microphysical properties (optical depth or emissivity, effective particle radius, and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

Action at a Distance: Snowfall in the Sierra Nevada provides a large fraction of the water that California receives as precipitation. Knowing what factors influence the amount of snow that falls is thus critical for projecting how water availability may change in the future. Aerosols have an important effect on cloud processes and precipitation. Creamean et al. (p. 1572 , published online 28 February) found that dust and biological aerosols originating from as far away as the Sahara facilitate ice nuclei formation and ice-induced precipitation in the Sierra Nevada and show how dust and biological articles from places as distant as Africa and Asia can influence precipitation over the western United States.

The National Aeronautics and Space Administration's Clouds and the Earth's Radiant Energy System (CERES) Project was designed to improve our understanding of the relationship between clouds and solar and longwave radiation. This is achieved using satellite broad-band instruments to map the top-of-atmosphere radiation fields with coincident data from satellite narrow-band imagers employed to retrieve the properties of clouds associated with those fields. This paper documents the CERES Edition-2 cloud property retrieval system used to analyze data from the Tropical Rainfall Measuring Mission Visible and Infrared Scanner and by the MODerate-resolution Imaging Spectrometer instruments on board the Terra and Aqua satellites covering the period 1998 through 2007. Two daytime retrieval methods are explained: the Visible Infrared Shortwave-infrared Split-window Technique for snow-free surfaces and the Shortwave-infrared Infrared Near-infrared Technique for snow or ice-covered surfaces. The Shortwave-infrared Infrared Split-window Technique is used for all surfaces at night. These methods, along with the ancillary data and empirical parameterizations of cloud thickness, are used to derive cloud boundaries, phase, optical depth, effective particle size, and condensed/frozen water path at both pixel and CERES footprint levels. Additional information is presented, detailing the potential effects of satellite calibration differences, highlighting methods to compensate for spectral differences and correct for atmospheric absorption and emissivity, and discussing known errors in the code. Because a consistent set of algorithms, auxiliary input, and calibrations across platforms are used, instrument and algorithm-induced changes in the data record are minimized. This facilitates the use of the CERES data products for studying climate-scale trends.