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NASA NTRS1997

Parameterizing Grid-Averaged Longwave Fluxes for Inhomogeneous Marine Boundary Layer Clouds

This paper examines the relative impacts on grid-averaged longwave flux transmittance (emittance) for Marine Boundary Layer (MBL) cloud fields arising from horizontal variability of optical depth tau and cloud sides, First, using fields of Landsat-inferred tau and a Monte Carlo photon transport algorithm, it is demonstrated that mean all-sky transmittances for 3D variable MBL clouds can be computed accurately by the conventional method of linearly weighting clear and cloudy transmittances by their respective sky fractions. Then, the approximations of decoupling cloud and radiative properties and assuming independent columns are shown to be adequate for computation of mean flux transmittance. Since real clouds have nonzero geometric thicknesses, cloud fractions A'(sub c) presented to isotropic beams usually exceed the more familiar vertically projected cloud fractions A(sub c). It is shown, however, that when A(sub c)less than or equal to 0.9, biases for all-sky transmittance stemming from use of A(sub c) as opposed to A'(sub c) are roughly 2-5 times smaller than, and opposite in sign to, biases due to neglect of horizontal variability of tau. By neglecting variable tau, all-sky transmittances are underestimated often by more than 0.1 for A(sub c) near 0.75 and this translates into relative errors that can exceed 40% (corresponding errors for all-sky emittance are about 20% for most values of A(sub c). Thus, priority should be given to development of General Circulation Model (GCM) parameterizations that account for the effects of horizontal variations in unresolved tau, effects of cloud sides are of secondary importance. On this note, an efficient stochastic model for computing grid-averaged cloudy-sky flux transmittances is furnished that assumes that distributions of tau, for regions comparable in size to GCM grid cells, can be described adequately by gamma distribution functions. While the plane-parallel, homogeneous model underestimates cloud transmittance by about an order of magnitude when 3D variable cloud transmittances are less than or equal to 0.2 and by approx. 20% to 100% otherwise, the stochastic model reduces these biases often by more than 80%.

Barker, Howard W.↗

NASA NTRS2005

Evaluation of a New Cloud Droplet Activation Parameterization wtih in Situ Data from CRYSTAL-FACE and CSTRIPE

The accuracy of the 2003 prognostic, physically based aerosol activation parameterization of A. Nenes and J. H. Seinfeld (NS) with modification introduced by C. Fountoukis and A. Nenes in 2005 (modified NS) is evaluated against extensive microphysical data sets collected on board the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft for cumuliform and stratiform clouds of marine and continental origin. The cumuliform cloud data were collected during NASA's Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE, Key West, Florida, July 2002), while the stratiform cloud data were gathered during Coastal Stratocumulus Imposed Perturbation Experiment (CSTRIPE, Monterey, California, July 2003). In situ data sets of aerosol size distribution, chemical composition, and updraft velocities are used as input for the NS parameterization, and the evaluation is carried out by comparing predicted cloud droplet number concentrations (CDNC) with observations. This is the first known study in which a prognostic cloud droplet activation parameterization has been evaluated against a wide range of observations. On average, predicted droplet concentration in adiabatic regions is within -20% of observations at the base of cumuliform clouds and -30% of observations at different altitudes throughout the stratiform clouds, all within experimental uncertainty. Furthermore, CDNC is well parameterized using either a single mean updraft velocity w or by weighting droplet nucleation rates with a Gaussian probability density function of w. This study suggests that for nonprecipitating warm clouds of variable microphysics, aerosol composition, and size distribution the modified NS parameterization can accurately predict cloud droplet activation and can be successfully implemented for describing the aerosol activation process in global climate models.

Meskhidze, Nicholas↗

NASA NTRS2021

Identifying Meteorological Influences on Marine Low Cloud Mesoscale Morphology Using Satellite Classifications

Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited 10by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective 15 self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.

Johannes Mohrmann↗

NASA NTRS2016

Observation of the Spectrally Invariant Properties of Clouds in Cloudy-to-Clear Transition Zones During the MAGIC Field Campaign

We use the spectrally invariant method to study the variability of cloud optical thickness τau and droplet effective radius r(sub eff) in transition zones (between the cloudy and clear sky columns) observed from Solar Spectral Flux Radiometer (SSFR) and Shortwave Array Spectroradiometer-Zenith (SASZe) during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. The measurements from the SSFR and the SASZe are different, however inter-instrument differences of self-normalized measurements (divided by their own spectra at a fixed time) are small. The spectrally invariant method approximates the spectra in the cloud transition zone as a linear combination of definitely clear and cloudy spectra, where the coefficients, slope and intercept, characterize the spectrally invariant properties of the transition zone. Simulation results from the SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model demonstrate that (1) the slope of the visible band is positively correlated with the cloud optical thickness τ while the intercept of the near-infrared band has high negative correlation with the cloud drop effective radius r(sub eff)even without the exact knowledge of τau; (2) the above relations hold for all Solar Zenith Angle (SZA) and for cloud-contaminated skies. In observations using redundant measurements from SSFR and SASZe, we find that during cloudy-to-clear transitions, (a) the slopes of the visible band decrease, and (b) the intercepts of the near-infrared band remain almost constant near cloud edges. The findings in simulations and observations suggest that, while the optical thickness decreases during the cloudy-to-clear transition, the cloud drop effective radius does not change when cloud edges are approached. These results support the hypothesis that inhomogeneous mixing dominates near cloud edges in the studied cases.

spectral invariance↗

NASA NTRSDate not supplied

Characterizing the Seasonal and Diurnal Aerosol Cycles using CATS Space-Based Lidar

The broader effects aerosols have on the earth and climate system is determined by a host of factors including their composition and vertical distribution. Characterizing the vertical distribution of clouds and aerosols is especially important considering it remains one of the greatest uncertainties in climate predictions. Space-based lidar, such as Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud-Aerosol Transport System (CATS), is especially well suited as a remote sensing tool in determining this vertical distribution. CALIOP has been used for over a decade to observe the global and vertical distribution of clouds and aerosols but is limited by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations’ (CALIPSO’s) polar orbit to set equatorial crossing times of ~1:30AM/PM. This limited temporal sampling limits the use of CALIOP in determining the full diurnal variability of clouds and aerosols. On the International Space Station (ISS), with its inclined orbit and variable equatorial crossing times, the CATS lidar provided an opportunity to study the vertical profile of clouds and aerosols at a variety of local times. With this 33-month CATS record, we show that CATS captured the seasonal changes in global aerosol distributions and compares favorably with other instruments and models. Specifically targeting biomass burning regions, we also find CATS could observe the documented diurnal cycle in aerosol altitudes with some caveats. With the next generation of proposed space-based lidars including designs in similar orbits as the ISS and CATS, future studies of the aerosol diurnal and seasonal cycles would also be possible.

Kenneth Christian↗

NASA NTRS2019

Cloud Edge Properties Measured by the ARM Shortwave Spectrometer over Ocean and Land

We use the spectrally-invariant method to study the variability of cloud optical thickness () and droplet effective radius (reff) in transition zones between the cloudy and clear sky columns observed by Shortwave Array Spectroradiometer-Zenith (SASZe) at the Southern Great Plains Central Facility site (SGP C1) and during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. The spectrally-invariant method approximates the spectra in the transition zone as a linear combination of definitely clear and definitely cloudy spectra. The slope and intercept of the linear relations characterize and reff in the transition region, respectively. The radiative transfer model simulations show that that (i) the slope of the visible (VIS) band is positively correlated with while (ii) the intercept of the near-infrared (NIR) band has a high negative correlation with reff. We have analyzed 22 cloud edge cases from the SGP and MAGIC and found that from cloud to clear in the transitions (a) the slopes of the VIS band decrease, indicating the decrease of towards cloud edges; (b) the intercepts of the NIR band show a much more significant increase at the SGP than from the MAGIC. The results from observed cases suggest that while decreases for all cases, the decrease in reff is much more significant for cloud over land at the SGP site compared to the ocean counterpart during the MAGIC campaign.

Yang, Weidong↗

NASA NTRS2000

Spatial and Temporal Variability of Satellite-Derived Cloud and Surface Characteristics During FIRE-ACE

Advanced very high resolution radiometer (AVHRR) products calculated for the western Arctic for April-July 1998 are used to investigate spatial, temporal, and regional patterns and variability in energy budget parameters associated with ocean- ice-atmosphere interactions over the Arctic Ocean during the Surface Heat Budget of the Arctic Ocean (SHEBA) project and the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). The AVHRR-derived parameters include cloud fraction, clear-sky and all-sky skin temperature and broadband albedo, upwelling and downwelling shortwave and longwave radiation, cloud top pressure and temperature, and cloud optical depth. The remotely sensed products generally agree well with field observations at the SHEBA site, which in turn is shown to be representative of a surrounding region comparable in size to a climate-model grid cell. Time series of products for other locations in the western Arctic illustrate the magnitude of spatial variability during the study period and provide spatial and temporal detail useful for studying regional processes. The data illustrate the progression of reduction in cloud cover, albedo decrease, and the considerable heating of the open ocean associated with the anomalous decrease in sea ice cover in the eastern Beaufort Sea that began in late spring. Above-freezing temperatures are also recorded within the ice pack, suggesting warming of the open water areas within the ice cover.

Maslanik, J. A.↗

NASA NTRS2019

Seasonal and Diurnal Opportunities for XCH4, XCO2, and XCO for the Amazonian Rainforest Region Allowing Sampling and Validation

There is considerable interest in the aggregate methane emissions from the Amazon and similar moist tropical regions, and XCH4 measurements are well suited to constrain sources to the global atmosphere. Similarly, XCO2 measurements constrain CO2 in the region. XCO helps to partition CO2 patterns among burning and respiration processes. GeoCarb may allow these column measurements over the Western Hemisphere, but satellite retrieval require exacting calibration and validation by sun-focused Fourier transform spectrometers (FTS). The rarity of sufficiently large gaps in the cloud cover over the Amazon and similar rainforests restricts the validation opportunities for useful FTS observations and even more the opportunities for accurate retrievals. TropOMI observational statistics are extremely poor for the region. We have used two data sources to evaluate FTS opportunities at Manaus, Brazil, an FTS operated for 8 months near Manaus by Mavendra Dubey, and also sun-photometer measurements at several stations. The promise of using data from other satellites, e.g. GOES-16 ( (Geostationary Operational Environmental Satellite) and CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization gaps and aerosol layering will be described. We report initial results on five questions: (1) how frequent are observing opportunities of FTS?, (2) What evidence is there that gaps in clouds are wide enough for satellite retrievals at an appropriate accuracy, (3) What is the diurnal and seasonal variability of cloud gaps?, and (4) What limitations are currently suggested for unbiased FTS measurement of XCH4 due to diurnal effects, and (5) What evidence is there for incidence of problematic high aerosol extinction at higher layers of the troposphere (800 hPa to 120 hPa) which alter the XCH4 light-paths?

Chatfield, Robert↗

NASA NTRS2012

Assessing the Time Variability of Jupiter's Tropospheric Properties from 1996 to 2011

We acquired and analyzed mid-infrared images of Jupiter's disk at selected wavelengths from NASA's Infrared Telescope Facility (IRTF) from 1996 to 2011, including a period of large-scale changes of cloud color and albedo. We derived the 100-300 mbar temperature structure, together with tracers of vertical motion: the thickness of a 600- mbar cloud layer, the 300-mbar abundance of the condensable gas NH3, and the 400- mbar para- vs. ortho-H2 ratio. The biggest visual change was detected in the normally dark South Equatorial Belt (SEB) that 'faded' to a light color in 2010, during which both cloud thickness and NH3 abundance rose; both returned to their pre-fade levels in 2011, as the SEB regained its normal dark color. The cloud thickness in Jupiter's North Temperate Belt (NTB) increased in 2002, coincident with its visible brightening, and its NH3 abundance spiked in 2002-2003. Jupiter's Equatorial Zone (EZ), a region marked by more subtle but widespread color and albedo change, showed high cloud thickness variability between 2007 and 2009. In Jupiter's North Equatorial Belt (NEB), the cloud thickened in 2005, then slowly decreased to a minimum value in 2010-2011. No temperature variations were associated with any of these changes, but we discovered temperature oscillations of approx.2-4 K in all regions, with 4- or 8-year periods and phasing that was dissimilar in the different regions. There was also no detectable change in the para- vs. ortho-H2 ratio over time, leading to the possibility that it is driven from much deeper atmospheric levels and may be time-invariant. Our future work will continue to survey the variability of these properties through the Juno mission, which arrives at Jupiter in 2016, and to connect these observations with those made using raster-scanned images from 1980 to 1993 (Orton et al. 1996 Science 265, 625).

Orton, G. S.↗

NASA NTRS2018

The Diurnal Cycle of Cloud Profiles over Land and Ocean Between 51degS and 51degN, Seen by the CATS Spaceborne Lidar from the International Space Station

We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51 deg S and 51 deg N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11-16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4-8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future Earth-CARE mission.

Noel, Vincent↗

NASA NTRS1983

Influence of clouds on the earth's radiation budget determined from GOES data

Estimates of the cloud radiative effects on the earth's regional and zonal radiation budgets derived from GOES data during November 1978 are presented. The diurnal cloud cover variability is shown to affect both the radiation-budget measurements and the estimation of the overall effect of clouds on the net flux. For this data set, the cloud cover causes a decrease in the net flux from the clear-sky value. Thus, the cloud albedo effect outweights the greenhouse effect of the clouds. It is found that the value of the change in the radiation balance is closely related to the amount of incident solar radiation and to the zonal distributions of low, middle, and high cloud cover.

Harrison, E. F.↗

NASA NTRS2001

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

Evans, K. Franklin↗

NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Cloud Fraction and Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.

Dong, Xiquan↗

NASA NTRS1983

Climate variability and atmospheric teleconnection from satellite observed cloud fluctuations

To investigate the low-frequency variability of the large-scale circulation over the tropics and its relationship with different regions of the globe, statistics of cloud fluctuations, as inferred from outgoing longwave radiation (OLR) are used. The data consists of seven years of global OLR in a 2.5 x 2.5-deg grid derived from NOAA polar orbiting satellite observations. The time series of area-averaged monthly deviation from the seven-year mean of OLR over an equatorial Central Pacific region is presented. It is shown that positive and negative deviations reflect local drier and wetter than normal conditions, respectively. Consideration is given to teleconnection based on the Central Pacific variations and to southern oscillation contributions.

Lau, K. M.↗

NASA NTRS1998

A Simple Model of Cirrus Horizontal Inhomogeneity and Cloud Fraction

A simple model of horizontal inhomogeneity and cloud fraction in cirrus clouds has been formulated on the basis that all internal horizontal inhomogeneity in the ice mixing ratio is due to variations in the cloud depth, which are assumed to be Gaussian. The use of such a model was justified by the observed relationship between the normalized variability of the ice water mixing ratio (and extinction) and the normalized variability of cloud depth. Using radar cloud depth data as input, the model reproduced well the in-cloud ice water mixing ratio histograms obtained from horizontal runs during the FIRE2 cirrus campaign. For totally overcast cases the histograms were almost Gaussian, but changed as cloud fraction decreased to exponential distributions which peaked at the lowest nonzero ice value for cloud fractions below 90%. Cloud fractions predicted by the model were always within 28% of the observed value. The predicted average ice water mixing ratios were within 34% of the observed values. This model could be used in a GCM to produce the ice mixing ratio probability distribution function and to estimate cloud fraction. It only requires basic meteorological parameters, the depth of the saturated layer and the standard deviation of cloud depth as input.

Smith, Samantha A.↗

NASA NTRS1990

ER-2 lidar measurements of stratocumulus cloud top structure on July 14, 1987

On July 14, 1987 NASA's ER-2 high altitude aircraft flew a mission to measure the structure of stratocumulus clouds off the coast of California. A flight pattern was executed so that the two-dimensional variability of the clouds could be detected. The technique of analysis of the lidar data to measure cloud tops follows. First each signal is searched for its maximum in return strength. This maximum is caused by scattering of the laser light off cloud particles or from the ocean surface. Next the variance of the signal return above the level of maximum backscatter is determined. Cloud top is assigned to a level (above the level of maximum backscatter) where the backscatter exceeds the average variance. This two-step process is necessary because the level of maximum backscatter does not correspond to the cloud top. Ocean surface returns are easily separated from cloud returns in this process, described in detail by Boers, Spinhirne, and Hart (1988). Analysis of the data so far has shown that there were very few breaks in the clouds. Furthermore the layer top was very flat with local oscillations not exceeding 30 m. Such small cloud top variations are still well within the range of detectability, because the precision of this technique of cloud top detection has previously been established to be 13 to 15 m. Data are presently being analyzed to compute cloud top distributions and fractional cloudiness. The aim of this research is to relate the fractional cloudiness to the mean thermodynamic structure of the boundary layer. Researchers plan to compute spectral scales of the cloud top variability in two dimensions to determine the orientation of the clouds with respect to the mean wind. Furthermore the lidar derived cloud top distribution will be used in the computation of the thermodynamic and radiation budget of the boundary layer.

Boers, Reinout↗

NASA NTRS1982

A proposal for observations of upper and middle tropospheric clouds

A proposal for a multi-institutional investigation of the processes involved in the growth and maintenance of high level extended clouds is presented. Mapping of variability of the cloud and of its radiative characteristics in terms of the meteorological environment of the cloud; performance of case studies involving observation of the cloud microphysics and radiation characteristics; and investigation of the processes responsible for the generation, maintenance, and dissipation of the cloud system are recommended. Both modeling and monitoring activities are considered. The specific research projects which the author proposes to carry out are described. Suggestions for the administrative organization of the total effort are presented.

Source record↗

NASA NTRS1993

Comparison of ISCCP and other cloud amounts

A new 8-year global cloud climatology has been produced by the International Satellite Cloud Climatology Project (ISCCP) that provides information every 3 h at 280-km spatial resolution covering the period from July 1983 through June 1991. If cloud detection errors and differences in area sampling are neglected, individual ISCCP cloud amounts agree with individual surface observations to within 15% rms with biases of only a few percent. When measurements of small-scale, broken clouds are isolated in the comparison, the rms differences between satellite and surface cloud amounts are about 25%, similar to the rms difference between ISCCP and Landsat determinations of cloud amount. For broken clouds, the average ISCCP cloud amounts are about 5% smaller than estimated by surface observers (difference between earth cover and sky cover), but about 5% larger than estimated from very high spatial resolution satellite observations (overestimate due to low spatial resolution offset by underestimate due to finite radiance thresholds). Detection errors caused by errors in the ISCCP clear-sky radiances or incorrect radiance threshold magnitudes, are the dominant source of error in monthly average cloud amounts. The ISCCP cloud amounts appear to be too low over land by about 10%, somewhat less in summer and somewhat more in winter, and about right (maybe slightly low) over oceans. In polar regions, ISCCP cloud amounts are probably too low by about 15%-25% in summer and 5%-10% in winter. Comparison of the ISCCP climatology to three other cloud climatologies shows excellent agreement in the geographic distribution and seasonal variation of cloud amounts; there is little agreement about day/night contrasts in cloud amount. Notable results from ISCCP are that the gobal annual mean cloud amount is about 63%, being about 23% higher over oceans than over land, that it varies by less than 1% rms from month to month, and that it has varied by about 4% on a time scale approximately equal to 2-4 years. The magnitude of interannual variations of local (280-km scale) monthly mean cloud amounts is about 7%-9%. Longitudinal contrasts in cloud amount are just as large as latitudinal contrasts. The largest seasonal variation of cloud amount occurs in the tropics, being larger in summer than in winter; the seasonal variation in the middle latitudes has the opposite phase. Polar regions may have little seasonable variability in cloud amount. The ISCCP results show slightly more nightime than daytime cloud amount over oceans and more daytime than nightime cloud amount over land.

Rossow, William B.↗