Patrick W. Heck

Stratocumulus Cloud Properties Derived from Simultaneous Satellite and Island-based Instrumentation during FIRE

Abstract Cloud parameters derived from visible and infrared window data from the Geostationary Operational Environmental Satellite (GOES) are compared to corresponding properties determined from instrumentation on San Nicolas Island off the coast of California during the First ISCCP Regional Experiment (FIRE) marine stratocumulus intensive field observations period in July 1987. Mean cloud amounts derived by applying the hybrid bispectral threshold method to the GOES data were 5% less than the island ceilometer measurements. Examination of the satellite imagery revealed that the apparent bias can be explained by the persistence of the clouds over the northwest part of the island during periods of clearing around the island. Diurnal variations in the cloud cover were very significant; minimum cloudiness occurred during the late afternoon and maximum cloudiness early in the morning. The satellite retrievals track this variation quite well. Satellite-derived mean cloud-top height is 53 m lower than that obse...

Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. II - Verification of theoretical cirrus radiative properties

Abstract A methodology is developed to apply a parameterization of radiative transfer calculations to satellite analyses of cirrus clouds. Cloud heights and optical depths are derived from visible and infrared window measurements taken during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) when cirrus clouds were present. Geostationary satellite retrievals are compared to lidar-derived cloud heights and retrievals from a polar-orbiting satellite taken at different angles to determine which theoretical models of scattering phase function and single-scattering albedo best represent actual cirrus clouds. Models using small hexagonal ice crystals with a diameter of 20 μm (C20) and a size distribution of slightly larger hexagonal ice crystals representing a cirrostratus (CS) cloud produce the best results. The resulting mean cloud heights are within ±0.3 km of the lidar results and have instantaneous uncertainties of ±1.3 km. Mean cloud heights derived using a mod...

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

The micro- and macrophysical properties of clouds play a crucial role in Earth’s radiation budget. The NASA Clouds and Earth’s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Near-real time cloud retrievals from operational and research meteorological satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

Global cloud database from VIRS and MODIS for CERES

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

The 27–28 October 1986 FIRE IFO Cirrus Case Study: Cloud Parameter Fields Derived from Satellite Data

Abstract A methodology for estimating cirrus cloud amounts and altitudes using visible and infrared satellite data was developed and tested using FIRE Cirrus Intensive Field Observation (IFO) coincident lidar and satellite data with a theoretical cloud albedo model. On average, cloud center heights could be determined to within ±0.9 km of the lidar-derived values using the satellite data alone. Satellite-derived, total cloud tops are generally 0.5 ± 0.9 km lower than the lidar cloud tops. If only high clouds are considered, the avenge cloud top is 0.1 ± 0.6 km higher than the lidar cloud top. The accuracies of the lidar cloud-center and cloud-top heights are estimated to be within ±0.7 km of the actual values. Satellite-derived average cloud emittance and visible optical depths can be determined to within ±0.05 and ±0.13, respectively, of the reference cloud emittance. Cirrus cloud thickness was also derived. The satellite retrieval yields cloud depths that are 0.3±1.0 km thinner than the lidar-derived cl...

Regional Apparent Boundary Layer Lapse Rates Determined from CALIPSO and MODIS Data for Cloud-Height Determination

AbstractReliably determining low-cloud heights using a cloud-top temperature from satellite infrared imagery is often challenging because of difficulties in characterizing the local thermal structure of the lower troposphere with the necessary precision and accuracy. To improve low-cloud-top height estimates over water surfaces, various methods have employed lapse rates anchored to the sea surface temperature to replace the boundary layer temperature profiles that relate temperature to altitude. To further improve low-cloud-top height retrievals, collocated Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data taken from July 2006 to June 2007 and from June 2009 to May 2010 (2 yr) for single-layer low clouds are used here with numerical weather model analyses to develop regional mean boundary apparent lapse rates. These parameters are designated as apparent lapse rates because they are defined using the cloud-top te...

Near-real-time cloud properties and aircraft icing indices from GEO and LEO satellites

Imagers on many of the current and future operational meteorological satellites in geostationary Earth orbit (GEO) and lower Earth orbit (LEO) have enough spectral channels to derive cloud microphysical properties useful for a variety of applications. The products include cloud amount, phase, optical depth, temperature, height and pressure, thickness, effective particle size, and ice or liquid water path, shortwave albedo, and outgoing longwave radiation for each imager pixel. Because aircraft icing depends on cloud temperature, droplet size, and liquid water content as well as aircraft variables, it is possible to estimate the potential icing conditions from the cloud phase, temperature, effective droplet size, and liquid water path. A prototype icing index is currently being derived over the contiguous USA in near-real time from Geostationary Operational Environmental Satellite (GOES-10 and 12) data on a half-hourly basis and from NOAA-16 Advanced Very High Resolution (AVHRR) data when available. Because the threshold-based algorithm is sensitive to small errors and differences in satellite imager and icing is complex process, a new probability based icing diagnosis technique is developed from a limited set of pilot reports. The algorithm produces reasonable patterns of icing probability and intensities when compared with independent model and pilot report data. Methods are discussed for improving the technique for incorporation into operational icing products.

CERES cloud properties derived from multispectral VIRS data

The Clouds and Earths Radiant Energy System (CERES) experiment, the first satellite project devoted to monitoring cloud macrophysical and microphysical properties simultaneously with the broadband radiation field, is designed to dramatically improve our understanding of the relationship between clouds and the Earths radiation budget. The first CERES instruments flew on the Tropical Rainfall Measuring Mission (TRMM) satellite between 35 degrees N and 35 degrees S with the Visible Infrared Scanner (VIRS), a 2-km resolution imager with five channels: 0.65, 1.6, 3.75, 10.8, and 12 micrometer beginning in January 1998. Cloud amount, height, temperature, phase, effective particle size, and water path are derived from the VIRS radiances and validated using surface radar and lidar data. Droplet radii are largest over ocean and smallest over land. Mean droplet radius is larger than that from earlier studies. The mean ice diameter is 61 micrometer. Variations of cloud parameters with temperature and viewing and solar zenith angle are given. Surface observations of liquid water path and droplet size agree well with the VIRS retrievals. This is the first analysis of cloud microphysical properties covering all times of day using all available pixels and viewing angles for half of the globe. Seasonal and diurnal variations of the cloud properties are presented.

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

ABSTRACT A set of physically based retrieval algorithms has beendeveloped to derive from multispectral satellite imagery avariety of cloud properties that can be used to diagnoseicing conditions when upper-level clouds are absent.The algorithms are being applied in near-real time to theGeostationary Operational Environmental Satellite(GOES) data over Florida, the Southern Great Plains, andthe midwestern USA. The products are available in imageand digital formats on the world-wide web. The analysissystem is being upgraded to analyze GOES data overthe CONUS. Validation, 24-hour processing, andoperational issues are discussed. INTRODUCTION Locations of aircraft icing conditions are currentlyavailable to pilots as a result of forecast model predictionsor from pilot reports (PIREPS). These diagnoses aregenerally valuable but leave much room for improvementbecause of forecast errors or because of the age andsparse distribution of PIREPS. It has been recognizedfor many years that GOES data might be used to increasethe spatial coverage and timeliness of icing reportsbecause, the satellite imager provides direct informationon cloud temperature [1] and some indication of cloudphase form the 3.9-µm channel [2]. The interpretation ofthe radiances is complicated by the angular dependenceof the reflected intensities and ambiguity between iceand liquid water in some conditions. Thus, furtheradvancement in satellite icing detection requires a morequantitative analyses of the satellite-observed radiances.With the need for better understanding of the role ofclouds in climate, physically based algorithms have beendeveloped to retrieve cloud microphysical propertiesfrom polar orbiting sat ellites for climate research, inparticular, the NASA Clouds and the Earth’s RadiantEnergy System Project [3]. The same algorithms are alsoapplicable to the GOES imager data and have been usedfor near-real-time analysis over the Atmos phericRadiation Measurement (ARM) southern Great Plains(SGP) domain [4]. Because the retrieved cloud productsinclude the cloud phase, temperature Tc, dropleteffective radius re, and liquid water path LWP, theyshould be valuable for diagnosing icing conditions,which require the presence of supercooled liquid waterSLW, larger droplets, and large liquid water contentLWC. Smith et al. [5,6] showed that the GOES analysisyielded SLW in 98% of the available positive icingPIREPS for a variety of viewing and illuminationconditions, demonstrating the excellent potential for thephysical retrieval approach. Efforts to better quantifyicing conditions from the GOESretrievals are continuing[7]. For effective use by the USA air traffic system, it isnecessary to have near-real time data available over theentire contiguous USA (CONUS). This paper describesthe development of an expansion of the currently limitedGOESprocessing to include the CONUS in parallel withthe efforts to quantitatively relate the retrieved c loudproperties to objective measures of icing.