Robert F. Arduini

CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part I: Algorithms

The National Aeronautics and Space Administrations Clouds and the Earths 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.

Parameterizations of Reflectance and Effective Emittance for Satellite Remote Sensing of Cloud Properties

Abstract The interpretation of satellite-observed radiances to derive cloud optical depth and effective particle size requires radiative transfer calculations relating these parameters to the reflectance, transmittance, and emittance of the cloud. Such computations can be extremely time consuming when used in an operational mode to analyze routine satellite data. Adding–doubling (AD) radiative transfer models are used here to compute reflectance and effective emittance at wavelengths commonly used by operational meteorological satellite imagers for droplet effective radii ranging from 2 to 32 μm and for distributions of randomly oriented hexagonal ice crystals with effective diameters varying from 6 to 135 μm. Cloud reflectance lookup tables were generated at the typical visible-channel wavelength of 0.65 μm and the solar–infrared (SI) at wavelengths of 3.75 and 3.90 μm. A combination of four-point Lagrangian and linear interpolation between the model nodal points is the most accurate and economical metho...

Advanced retrievals of multilayered cloud properties using multispectral measurements

Received 6 June 2004; revised 2 September 2004; accepted 4 October 2004; published 13 April 2005. [1] Current satellite cloud retrievals are usually based on the assumption that all clouds consist of a homogenous single layer despite the frequent occurrence of cloud overlap. As such, cloud overlap will cause large errors in the retrievals of many cloud properties. To address this problem, a multilayered cloud retrieval system (MCRS) is developed by combining satellite visible and infrared radiances and surface microwave radiometer measurements. A two-layer cloud model was used to simulate ice-over-water cloud radiative characteristics. The radiances emanating from the combined low cloud and surface are estimated using the microwave liquid water with an assumption of effective droplet size. These radiances replace the background radiances traditionally used in single-layer cloud retrievals. The MCRS is applied to data from March through October 2000 over four Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) sites. The results are compared to the available retrievals of ice water path (IWP) from radar data and show that the MCRS clearly produces a more accurate retrieval of ice-over-water cloud properties. MCRS yields values of IWP that are closest to those from the radar retrieval. For ice-over-water cloud systems, on average, the optical depth and IWP are reduced, from original overestimates, by approximately 30%. The March–October mean cloud effective temperatures from the MCRS are decreased by 10 ± 12K,whichtranslatestoanaverageheightdifferenceof � 1.4km.Theseresultsindicatethat ice-cloud height derived from traditional single-layer retrieval is underestimated, and the midlevel ice cloud coverage is over classified. Effective ice crystal particle sizes are increased by only a few percent with the new method. This new physically based technique should be robust and directly applicable when data are available simultaneously from a satellite imager and the appropriate satellite or surface microwave sensor.

Ice cloud properties in ice-over-water cloud systems using Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and TRMM Microwave Imager data

A multilayered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) measurements acquired over the Tropics between January and August 1998. Lookup tables of top-of-atmosphere 0.65-mu m reflectance are developed for ice-over-water cloud systems using radiative transfer calculations for various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave ( MW), visible ( VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible-Infrared Solar-infrared Split-Window technique (VISST), which matches the VIRS IR, 3.9 mu m, and VIS data to the multilayer cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42 and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values and exceed those of single-layered clouds by 7 and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites, and the standard deviations of the differences are similar to those for single-layered clouds. Examples of a method for applying the MCRS over land without MW data yield similar differences with the surface retrievals. By combining the MCRS with other techniques that focus primarily on optically thin cirrus over low water clouds, it will be possible to more fully assess the IWP in all conditions over ocean except for precipitating systems.

Daytime and nighttime polar cloud and snow identification using MODIS data

The Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, with its high horizontal resolution and frequent sampling over Arctic and Antarctic regions, provides unique data sets to study clouds and the surface energy balance over snow and ice surfaces. This paper describes a polar cloud mask using MODIS data. The daytime cloud and snow identification methods were developed using theoretical snow bi-directional reflectance models for the MODIS 1.6 and 3.75 micron channels. The model-based polar cloud mask minimizes the need for empirically adjusting the thresholds for a given set of conditions and reduces the error accrued from using single-value thresholds. During night, the MODIS brightness temperature differences (BTD) for 3.75 - 11, 3.75 - 12, 8.55 - 11, and 6.7 - 11 micron are used to detect clouds while snow and ice maps are used to determine snow and ice surfaces. At twilight, the combination of the 1.6 micron reflectance and the 3.75 - 11 micron BTD are used to detect clouds. Examples of the cloud mask results from daytime, nighttime, and twilight data show good agreement with visual interpretation of the imagery. Comparisons of the modeled and observed reflectances for clear snow areas reveal good agreement at 1.6 micron, but 10 - 35% overestimates of the 3.75 micron reflectance by the model. Over the Arctic, the modeled visible reflectance is significantly greater than the observed values. Better agreement is obtained over the Antarctic where snow melt is less significant.

Cloud coverage and height during FIRE ACE derived from AVHRR data

Cloud cover and height are derived from NOAA-12 and NOAA-14 advanced very high resolution radiometer (AVHRR) data taken over the Arctic Ocean for an 8° latitude by 30° longitude domain centered on the Surface Heat Budget of the Arctic Ocean (SHEBA) ship Des Groseilliers. Multispectral thresholds were determined subjectively and applied to each image, providing excellent temporal coverage during the May-July 1998 First ISCCP Regional Experiment Arctic Clouds Experiment (FIRE ACE). Mean cloud amounts were near 70% for the entire period but varied regionally from 55 to 85%. On the basis of a limited climatology of ship observations, these values appear to be typical for this part of the Arctic, suggesting that most of FIRE ACE was conducted in representative cloud conditions. A diurnal cycle of mean cloud amount was found for the domain during June and July having a range of 10% with a middle-to-late morning maximum. The AVHRR-derived cloud amounts are in good agreement with visual and radar measurements taken from the Des Groseilliers, except for a few subvisual and low cloud cases. Average AVHRR-derived cloudiness differ from the mean values obtained at the surface by −1 to +3%; this represents a significant improvement over previous satellite retrievals. The satellite-derived cloud heights are very accurate for most of the low cloud cases. Higher cloud altitudes are less certain because cloud optical depths were not available to adjust the temperature observed for the optically thin high clouds, and the radiating temperature of many of the high clouds is representative of some altitude deep in the cloud rather than the highest altitude level of condensate. The development of a more accurate automated algorithm for detecting polar clouds at AVHRR wavelengths will require inclusion of variable thresholds to account for the angular dependence of the surface reflectance as well as the seasonally changing albedos of the ice pack. The use of a 1.6-μm channel on the AVHRR, or other complement of instruments, will greatly enhance the capabilities for detecting clouds over poles during summer.

Clear-sky narrowband albedos derived from VIRS and MODIS

The Clouds and Earth’s Radiant Energy System (CERES) project is using multispectral imagers, the Visible Infrared Scanner (VIRS) on the tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, operating since spring 2000, and Aqua, operating since summer 2002, to provide cloud and clear-sky properties at various wavelengths. This paper presents the preliminary results of an analysis of the CERES clear-sky reflectances to derive a set top-of-atmosphere clear sky albedo for 0.65, 0.86, 1.6, 2.13 μm, for all major surface types using the combined MODIS and VIRS datasets. The variability of snow albedo with surface type is examined using MODIS data. Snow albedo was found to depend on the vertical structure of the vegetation. At visible wavelengths, it is least for forested areas and greatest for smooth desert and tundra surfaces. At 1.6 and 2.1-μm, the snow albedos are relatively insensitive to the underlying surface because snow decreases the reflectance. Additional analyses using all of the MODIS results will provide albedo models that should be valuable for many remote sensing, simulation and radiation budget studies.

Retrieval of Ice Cloud Properties Using Variable Phase Functions

An enhancement to NASA Langley’s Visible Infrared Solar‐infrared Split‐window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real‐time retrievals at Langley.