Abstract

Aircraft observations and high resolution Landsat Multispectral Scanner digital data are used to determine the sizes of spatial inhomogeneities (“holes”) in cumulus clouds. The majority of holes are found near cloud edges, but the larger holes tend to be found in cloud interiors. Aircraft measurements show these cloud spatial inhomogeneities in the range of 100 to 500 m, while Landsat data show them in the range of 100 m to 3 km.

The number of holes per cloud decreases exponentially with increasing hole diameter. Small clouds not only have smaller holes, but also fewer holes than large clouds. Large clouds have large holes in them, as well as large numbers of the smaller holes. The total cloud area occupied by holes increases with increasing cloud size.

Abstract

Three boundary layer cloud object types—overcast, stratocumulus, and cumulus—that occurred over the Pacific Ocean during January–August 1998 are identified from the Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint data. Characteristics of each cloud object type matched with atmospheric states are examined for large regions in the tropics and subtropics and for different size categories. Stratocumulus cloud objects dominate the entire boundary layer cloud population in all regions and size categories. Overcast cloud objects, which have the largest average size, are more prevalent in the subtropics and near the coastal regions, while cumulus cloud objects are prevalent over the open oceans and the equatorial regions, particularly within the small-size categories. Cloud objects with equivalent diameters less than 75 km are excluded in the analysis.

The differences between the tropical and subtropical statistical distributions of cloud properties are small for liquid water path (LWP), cloud optical depth, and top-of-the-atmosphere (TOA) albedo, but large for cloud-top temperature and outgoing longwave radiation (OLR), for each of the three cloud object types. The larger cloud objects have higher LWPs, cloud optical depths, TOA albedos, and OLRs, but lower SSTs and cloud-top heights for the stratocumulus and overcast types. Lower-tropospheric stability seems to be the primary factor for the differences in the distributions of cloud physical properties between the regions or between the size categories. Atmospheric dynamics also play a role in determining the differences in the distributions of cloud physical properties between the size categories, but not a significant role for those between the types or between the regions. The latter may be due to uncertainties in the matched vertical velocity data. When the three cloud object types are combined in small regions, lower-tropospheric stability determines the transition of boundary layer cloud types along a Pacific transect. The proportion of each type is the most important factor for diagnosing the combined cloud properties along this transect, such as LWP, cloud optical depth, and TOA albedo. Atmospheric dynamics also play complicated roles in determining the combined cloud properties along this transect.

Abstract

A technique is developed that uses a multispectral, multiresolution (MSMR) method to improve the overall retrieval of mid-to high-level cloud properties by combining HIRS sounding channel data with higher spatial resolution AVHRR radiometric data collocated with the HIRS footprint. Cirrus cloud radiative and physical properties are determined using satellite data, surface-based measurements provided by rawinsondes and lidar, and aircraft-based lidar data collected during the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE) in Wisconsin during the months of October and November 1986. HIRS cloud-height retrievals are compared to ground-based lidar and aircraft lidar when possible. Retrieved cloud heights are found to have close agreement with lidar for thin cloud, but are higher than lidar for optically thick cloud. The fact that the retrieved cloud height is higher than lidar for optically thick cloud is probably due to the attenuation of the lidar signal before the signal reaches through the cloud, while the satellite is viewing the cloud from above. AVHRR visible (0.63-μm) and infrared (11-μm) radiances are analyzed to determine the cloud emittances and reflectances collocated with each HIRS pixel. The bidirectional reflectances from the AVHRR visible-channel data are corrected for solar direct and diffuse surface reflection to isolate the cloud reflectance. The individual AVHRR pixel emittances are calculated using the cloud-top temperature derived from the HIRS cloud-retrieval analysis. The results of the reflectance-emittance relationships derived in this fashion are compared to theoretical scattering model results for both water-droplet spheres and randomly oriented hexagonal ice crystals. It is found that the assumption of 10-μm water droplets is inadequate to describe the reflectance-emittance relationship for the ice clouds seen here. Use of this assumption would lead to lower cloud heights using the ISCCP approach. The theoretical results show that use of hexagonal ice-crystal phase functions could lead to much improved results for cloud retrieval algorithms using a bispectral approach.

Abstract

The Independent Pixel approximation (IPA) is one of the simplest methods of computing solar radiative fluxes for inhomogencous clouds. It claims that if p(τ) is a normalized probability density function for cloud optical depth τ and R_pp (τ) is plane-parallel, homogeneous (PPH) albedo, mean cloud albedo can be approximated by integrating p(τ)R_pp (τ) over all τ. The purpose of this study is to assess the ability of the gamma distribution function to represent p(τ) for marine boundary layer clouds and to examine the accuracy of the ensuing gamma IPA albedos.

In a separate study, pixel values of τ were inferred from high spatial resolution Landsat imagery of marine boundary layer clouds. The present study utilizes 45 images, each measuring (58 km)². For each image, a density function p _obs(τ) is estimated, and, using the mean τ¯ and variance of τ, a corresponding truncated gamma distribution function p _γ(τ) is defined. For a diverse range of clouds, p _γ(τ) usually approximate p _obs(τ) well. The best results are for overcast stratocumulus and small, broken cumulus, while the worst results are for streets of moderately thick cumulus observed at relatively large solar zenith angles. After both p _obs(τ) and corresponding p _obs(τ) are filtered through the IPA; however, resulting solar zenith angle dependent and spherical albedos often agree to well within 5%, regardless of cloud type. Furthermore, disparities between IPA albedos using p _obs(τ) and p _γ(τ) are roughly 10 times smaller than disparities between IPA albedos using p _obs(τ) and corresponding PPH albedos [R _pp(τ¯)].Thus, for marine boundary layer clouds, the gamma IPA can be expected to remove most of the PPH bias currently present in GCMs. A simple parameterization, dependent on cloud fraction, is furnished that may enable the gamma IPA to be used in GCMs.

Abstract

This study presents an objective classification methodology that uses Earth Observing System (EOS) satellite data to classify distinct “cloud objects” defined by cloud-system types, sizes, geographic locations, and matched large-scale environments. This analysis method identifies a cloud object as a contiguous region of the earth with a single dominant cloud-system type. It determines the shape and size of the cloud object from the satellite data and the cloud-system selection criteria. The statistical properties of the identified cloud objects are analyzed in terms of probability density functions (PDFs) based upon the Clouds and the Earth’s Radiant Energy System (CERES) Single Satellite Footprint (SSF) data.

Four distinct types of oceanic cloud objects—tropical deep convection, boundary layer cumulus, transition stratocumulus, and solid stratus—are initially identified from the CERES data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite for this study. Preliminary results are presented from the analysis of the grand-mean PDFs of these four distinct types of cloud objects associated with the strong 1997/98 El Niño in March 1998 and the very weak 2000 La Niña in March 2000. A majority of the CERES footprint statistical characteristics of observed tropical deep convection are similar between the two periods in spite of the climatological contrast. There are, however, statistically significant differences in some cloud macrophysical properties such as the cloud-top height and cloud-top pressure and moderately significant differences in outgoing longwave radiation (OLR), cloud-top temperature, and ice diameter. The footprint statistical characteristics of the three observed boundary layer cloud-system types are distinctly different from one another in all cloud microphysical, macrophysical, optical properties, and radiative fluxes. The differences between the two periods are not significant for most cloud microphysical and optical properties and the top-of-the-atmosphere albedo, but are statistically significant for some cloud macrophysical properties and OLR. These characteristics of the grand-mean PDFs of cloud microphysical, macrophysical, and optical properties and radiative fluxes can be usefully compared with cloud model simulations.

Furthermore, the proportion of different boundary layer cloud types is changed between the two periods in spite of small differences in their grand-mean statistical properties. An increase of the stratus population and a decrease of the cumulus population are evident in the El Niño period compared to the very weak La Niña period. The number of the largest tropical convective cloud objects is larger during the El Niño period, but the total number of tropical convective cloud objects is approximately the same in the two periods.

Abstract

Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type.

It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed toward high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precession cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This evidence supports the fixed anvil temperature hypothesis of Hartmann and Larson for the large-size category. Combined with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SST ranges, statistical characteristics of cloud microphysical properties, optical depth, and albedo are not sensitive to the SST, but those of cloud macrophysical properties are dependent upon the SST. This result is related to larger differences in large-scale dynamics among the SST ranges than among the satellite precession cycles. Frequency distributions of vertical velocity from the European Centre for Medium-Range Weather Forecasts model that is matched to each cloud object are used to further understand some of the findings in this study.

Abstract

Observations of cirrus and altocumulus clouds during the First International Satellite Cloud Climatology Project Regional Experiment (FIRE) are compared to theoretical models of cloud radiative properties. Three tests are performed. First, Landsat radiances are used to compare the relationship between nadir reflectance at 0.83 μm and beam emittance at 11.5 μm with that predicted by model calculations using spherical and nonspherical phase functions. Good agreement is found between observations and theory when water droplets dominate. Poor agreement is found when ice particles dominate, especially if scattering phase functions for spherical particles am used. Even when compared to a laboratory measured ice particle phase function (Volkovitskiy et al. 1980), the observations show increased side scattered radiation relative to the theoretical calculations. Second, the anisotropy of conservatively scattered radiation is examined using simultaneous multiple-angle views of the cirrus from Landsat and ER-2 aircraft radiometers. Observed anisotropy gives good agreement with theoretical calculations using the laboratory measured ice-particle phase function and poor agreement with a spherical-particle phase function. Third, Landsat radiances at 0.83 μm, 1.65 μm, and 2.21 μm are used to infer particle phase and particle size. For water droplets, good agreement is found with King Air FSSP particle probe measurements in the cloud. For ice particles, the Landsat radiance observations predict an effective radius of 60 μm versus aircraft observations of about 200 μm. It is suggested that this discrepancy may be explained by uncertainty in the imaginary index of ice and by inadequate measurements of small ice particles by microphysical probes.

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.