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Zhonghai Jin and Andrew Lacis

Abstract

A computationally efficient method is presented to account for the horizontal cloud inhomogeneity by using a radiatively equivalent plane-parallel homogeneous (PPH) cloud. The algorithm can accurately match the calculations of the reference (rPPH) independent column approximation (ICA) results but uses only the same computational time required for a single plane-parallel computation. The effective optical depth of this synthetic sPPH cloud is derived by exactly matching the direct transmission to that of the inhomogeneous ICA cloud. The effective scattering asymmetry factor is found from a precalculated albedo inverse lookup table that is allowed to vary over the range from −1.0 to 1.0. In the special cases of conservative scattering and total absorption, the synthetic method is exactly equivalent to the ICA, with only a small bias (about 0.2% in flux) relative to ICA resulting from imperfect interpolation in using the lookup tables. In principle, the ICA albedo can be approximated accurately regardless of cloud inhomogeneity. For a more complete comparison, the broadband shortwave albedo and transmission calculated from the synthetic sPPH cloud and averaged over all incident directions have RMS biases of 0.26% and 0.76%, respectively, for inhomogeneous clouds over a wide variation of particle size. The advantages of the synthetic PPH method are that 1) it is not required that all the cloud subcolumns have uniform microphysical characteristic, 2) it is applicable to any 1D radiative transfer scheme, and 3) it can handle arbitrary cloud optical depth distributions and an arbitrary number of cloud subcolumns with uniform computational efficiency.

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Andrew A. Lacis and James Hansen

Abstract

A method is described for rapidly computing the amount of solar energy absorbed at the earth's surface and in the atmosphere as a function of altitude. The method is a parametric treatment, but the form of the solution and the coefficients involved are based on accurate multiple-scattering computations. In this treatment the absorption varies with the amount and type of clouds, the humidity, the zenith angle of the sun, and the albedo of the earth's surface. Within the stratosphere the absorption also depends on the vertical distribution of ozone.

This parameterization for solar radiation is being used in current versions of the global atmospheric circulation model developed at the Goddard Institute for Space Studies.

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William B. Rossow and Andrew A. Lacis

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Global, daily, visible and infrared radiance measurements from the NOAA-5 Scanning Radiometer (SR) are analyzed for the months of January, April, July and October 1977 to infer cloud and surface radiative properties and their effects on the Earth and surface radiation budgets. The analysis makes use of several additional datasets to help isolate the cloud contributions. The cloud properties inferred from satellite data are found to be about as accurate as the validation datasets available from other sources, but significant improvements are needed for better diagnosis of cloud-radiative feedbacks. Consequently, advances in cloud retrievals from satellite data will be like “new measurement” that have no independent validation. Reconstruction of regional, monthly mean Earth radiation budgets (ERB) from cloud, atmosphere and surface data is also nearly as accurate as can be checked with summaries of other, more direct measurements, improvements require detailed intercomparisons at smaller space/time scales. Currently, there is no global dataset with which to validate the reconstructed surface radiation budget (SRB). Comparison of monthly, regional mean quantities with those simulated by the GISS climate GCM shows that the differences are only a little larger than the uncertainties in the results; thus, better data and more detailed comparisons will be needed to improve the GCMs.

Despite important limitations in these results, several fundamental conclusions about the role of clouds in the radiation balance of Earth are apparent. 1) The magnitude of cloud property variations and their effects on radiation increase strongly with decreasing space/time scales, going from global, annual means to regional, monthly means; 2) Cloud properties are systematically different between land and ocean: oceans have larger cloud cover with somewhat larger optical thicknesses and lower cloud top altitudes; 3) Although cloud variations appear to be the primary cause of regional radiation budget variability at 5–30 day time scales, the effects of their seasonal variations at larger spatial scales are less important than the changes associated with changes in solar declination and atmospheric/surface temperatures, 4) The largest seasonal Variations in radiation occur in the 30°–60° latitude band in each hemisphere, 5) Cloud variations tend to enhance regional and seasonal radiation variations at lower latitudes and mute them at higher latitudes; however, they also affect the average latitudinal gradients of heating/cooling; 6) Although clouds have a net cooling effect in the global, annual mean radiation balance at both the top of the atmosphere and the surface, their net effect on regional, seasonal balances is much more varied; 7) Conclusions (5) and (6), together, are equivalent to saying that the relation between cloud properties and their effect on ERB and SRB depend crucially on the regional and seasonal circumstances of the clouds; 8) Regional cloud and surface seasonal change amplitudes and phase exhibit a wide variety of values; moreover, the correlations between surface temperature and cloud properties vary greatly; 9) There appears to be no simple relation between global mean surface temperature, global mean cloud properties and their global mean effects on ERB and SRB, implying that cloud radiative effects on the seasonal temperature cycle must be described as multiple feedbacks, and 10) The complexity of the cloud radiative effects and the data accuracy required to diagnose cloud-radiative feedbacks indicate the challenge of this problem.

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Brian Cairns, Andrew A. Lacis, and Barbara E. Carlson

Abstract

The effect on absorption in clouds of having an inhomogeneous distribution of droplets is shown to depend on whether one replaces a homogeneous cloud by an inhomogeneous cloud that has the same mean optical thickness, or one that has the same spherical albedo. For the purposes of general circulation models (GCMs), the more appropriate comparison is between homogeneous and inhomogeneous clouds that have the same spherical albedo, so that the radiation balance of the planet with space is maintained. In this case it is found, using Monte Carlo and independent pixel approximation calculations, that inhomogeneous clouds can absorb more than homogeneous clouds. It is also found that because of the different effects of cloud inhomogeneity on absorption and on the transmission of the direct beam the absorption efficiency of an inhomogeneous cloud may be either greater (for low and high optical depths) or lesser (for intermediate optical depths) than that for a homogeneous cloud of the same mean optical depth. This effect is relevant both to in-cloud absorption and to absorption below clouds. In order to include these effects in GCMs a simple renormalization of the single-scattering parameters of radiative transfer theory is derived that allows the effects of cloud inhomogeneities to be included in plane-parallel calculations. This renormalization method is shown to give reasonable results when compared with Monte Carlo calculations, has the appropiate limits for conservative and completely absorbing cases, and provides a simple interpretation of the effects of cloud inhomogeneities that could readily be incorporated in a GCM.

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Qingyuan Han, William B. Rossow, and Andrew A. Lacis

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A global survey of cloud particle size variations can provide crucial constraints on how cloud processes determine cloud liquid water contents and their variation with temperature, and further, may indicate the magnitude of aerosol effects on clouds. A method, based on a complete radiative transfer model for AVHRR-measured radiances, is described for retrieving cloud particle radii in liquid water clouds from satellite data currently available from the International Satellite Cloud Climatology Project. Results of sensitivity tests and validation studies provide error estimates. AVHRR data from NOAA-9 and NOAA-10 have been analyzed for January, April, July, and October in 1987 and 1988. The results of this first survey reveal systematic continental and maritime differences and hemispheric contrasts that are indicative of the effects of associated aerosol concentration differences: cloud droplet radii in continental water clouds are about 2–3 µm smaller than in marine clouds, and droplet radii are about 1 µm smaller in marine clouds of the Northern Hemisphere than in the Southern Hemisphere. The height dependencies of cloud droplet radii in continental and marine clouds are also consistent with differences in the vertical profiles of aerosol concentration. Significant seasonal and diurnal vacations of effective droplet radii are also observed, particularly at lower latitudes. Variations of the relationship between cloud optical thickness and droplet radii may indicate variations in cloud microphysical regimes.

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William B. Rossow, Leonid C. Garder, and Andrew A. Lacis

Abstract

Global, daily, visible and infrared radiance measurements from the NOAA-5 Scanning Radiometer (SR) are analyzed for the months of January, April, July and October 1977 to infer cloud and surface radiative properties. In this first paper in a three part series, the data and analysis method are described. A unique feature of the method is that it utilizes radiative transfer models that simulate the SR measurements using explicit parameters representing the properties of the surface, atmosphere, and clouds. The simulations also account for variations that depend on viewing geometry. The analysis combines several datasets so that the cloud contributions to the SR measurements can be isolated. The accuracy of all the results depends primarily on the proper separation of the total radiance distribution into those parts representing clear and cloudy scenes. Comparison of the surface properties retrieved from the clear scene radiances [see also Rossow et al. (1989)], sensitivity tests of the cloud detection algorithm, and comparisons of the resulting cloud amounts (see also Part II) provide an assessment of the accuracy of the method.

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Jing Li, Barbara E. Carlson, William B. Rossow, Andrew A. Lacis, and Yuanchong Zhang

Abstract

Because of the importance of clouds in modulating Earth’s energy budget, it is critical to understand their variability in space and time for climate and modeling studies. This study examines the consistency of the spatiotemporal variability of cloud amount (CA) and cloud-top pressure (CTP) represented by five 7-yr satellite datasets from the Global Energy and Water Cycle Experiment (GEWEX) cloud assessment project, and total cloud fraction observation from the Extended Edited Cloud Reports Archive (EECRA). Two spectral analysis techniques, namely combined maximum covariance analysis (CMCA) and combined principal component analysis (CPCA), are used to extract the dominant modes of variability from the combined datasets, and the resulting spatial patterns are compared in parallel. The results indicate that the datasets achieve overall excellent agreement on both seasonal and interannual scales of variability, with the correlations between the spatial patterns mostly above 0.6 and often above 0.8. For seasonal variability, the largest differences are found in the Northern Hemisphere high latitudes and near the South African coast for CA and in the Sahel region for CTP, where some differences in the phase and strength of the seasonal cycle are found. On interannual scales, global cloud variability is mostly associated with major climate modes, including El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IODM), and the datasets also agree reasonably well. The good agreement across the datasets supports the conclusion that they are describing cloud variations with these climate modes.

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Mikhail D. Alexandrov, Andrew A. Lacis, Barbara E. Carlson, and Brian Cairns

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Measurements from ground-based sun photometer networks can be used both to provide ground-truth validation of satellite aerosol retrievals and to produce a land-based aerosol climatology that is complementary to satellite retrievals that are currently performed mostly over ocean. The multifilter rotating shadowband radiometer (MFRSR) has become a popular network instrument in recent years. Several networks operate about a hundred instruments providing good geographical coverage of the United States. In addition, international use of the MFRSR has continued to increase, allowing MFRSR measurements to significantly contribute to aerosol climatologies.

This study investigates the feasibility of creating a ground-based aerosol climatology using MFRSR measurements. Additionally, this analysis allows for testing of the performance of the retrieval algorithm under a variety of conditions. The retrieval algorithm is used for processing MFRSR data from clear and partially cloudy days to simultaneously retrieve daily time series of column mean aerosol particle size, aerosol optical depth, NO2, and ozone column amounts together with the instrument's calibration constants directly from the MFRSR measurements for a variety of sites covering a range of atmospheric and surface conditions. This analysis provides a description of seasonal changes in aerosol parameters and in column amounts of ozone and NO2 as a function of geographical location. In addition, the relationship between NO2 column amount and aerosol optical depth as a potential indicator of tropospheric pollution is investigated. Application of this analysis method to the measurements from growing numbers of MFRSRs will allow for expansion on this developing climatology.

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Mikhail D. Alexandrov, Andrew A. Lacis, Barbara E. Carlson, and Brian Cairns

Abstract

A retrieval algorithm for processing multifilter rotating shadowband radiometer (MFRSR) data from clear and partially cloudy days is described and validated. This method, while complementary to the Langley approach, uses consistency between the direct normal and diffuse horizontal measurements combined with a regression technique to simultaneously retrieve daily time series of column mean aerosol particle size, aerosol optical depth, NO2, and ozone amounts along with the instrument's calibration constants. Comparison with the traditional Langley calibration method demonstrates two advantages of the approach described here: greater calibration stability and a decreased sensitivity of retrievals to calibration errors.

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Igor V. Geogdzhayev, Michael I. Mishchenko, William B. Rossow, Brian Cairns, and Andrew A. Lacis

Abstract

Described is an improved algorithm that uses channel 1 and 2 radiances of the Advanced Very High Resolution Radiometer (AVHRR) to retrieve the aerosol optical thickness and Ångström exponent over the ocean. Specifically discussed are recent changes in the algorithm as well as the results of a sensitivity study analyzing the effect of several sources of retrieval errors not addressed previously. Uncertainties in the AVHRR radiance calibration (particularly in the deep-space count value) may be among the major factors potentially limiting the retrieval accuracy. A change by one digital count may lead to a 50% change in the aerosol optical thickness and a change of 0.4 in the Ångström exponent. On the other hand, the performance of two-channel algorithms weakly depends on a specific choice of the aerosol size distribution function with less than 10% changes in the optical thickness resulting from replacing a power law with a bimodal modified lognormal distribution. The updated algorithm is applied to a 10-yr period of observations (Jul 1983–Aug 1994), which includes data from NOAA-7, NOAA-9 (Feb 1985–Nov 1988), and NOAA-11 satellites. (The results are posted online at http://gacp.giss.nasa.gov/retrievals.)

The NOAA-9 record reveals a seasonal cycle with maxima occurring around January–February and minima in June–July in the globally averaged aerosol optical thickness. The NOAA-7 data appear to show a residual effect of the El Chichón eruption (Mar 1982) as increased optical thickness values in the beginning of the record. The June 1991 eruption of Mt. Pinatubo resulted in a sharp increase in the aerosol load to more than double its normal value. The NOAA-9 record shows no discernible long-term trends in the global and hemisphere averages of the optical thickness and Ångström exponent. On the other hand, there is a discontinuity in the Ångström exponent values derived from NOAA-9 and NOAA-11 data and a significant temporal trend in the NOAA-11 record. The latter is unlikely to be related to the Mt. Pinatubo eruption and may be indicative of a serious calibration problem.

The NOAA-9 record shows that the Northern Hemisphere mean optical thickness systematically exceeds that averaged over the Southern Hemisphere. Zonal means of the optical thickness exhibit an increase in the tropical regions of the Northern Hemisphere associated with annual desert dust outbursts and a springtime increase at middle latitudes of the Northern Hemisphere. Increased aerosol loads observed at middle latitudes of the Southern Hemisphere are probably associated with higher sea salt particle concentrations. Reliable extension of the retrieval record beyond the NOAA-9 lifetime will help to corroborate these findings.

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