Douglas A. Spangenberg

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.

The Mixed-Phase Arctic Cloud Experiment

The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted from 27 September through 22 October 2004 over the Department of Energys Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The primary objectives were to collect a dataset suitable to study interactions between microphysics, dynamics, and radiative transfer in mixed-phase Arctic clouds, and to develop/evaluate cloud property retrievals from surface-and satellite-based remote sensing instruments. Observations taken during the 1977/98 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds by utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the ACRF site on the North Slope of Alaska. The measureme...

CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part II: Examples of Average Results and Comparisons With Other Data

Cloud properties were retrieved by applying the Clouds and Earths Radiant Energy System (CERES) project Edition-2 algorithms to 3.5 years of Tropical Rainfall Measuring Mission Visible and Infrared Scanner data and 5.5 and 8 years of MODerate Resolution Imaging Spectroradiometer (MODIS) data from Aqua and Terra, respectively. The cloud products are consistent quantitatively from all three imagers; the greatest discrepancies occur over ice-covered surfaces. The retrieved cloud cover (~59%) is divided equally between liquid and ice clouds. Global mean cloud effective heights, optical depth, effective particle sizes, and water paths are 2.5 km, 9.9, 12.9 μm , and 80 g·m-2, respectively, for liquid clouds and 8.3 km, 12.7, 52.2 μm, and 230 g·m-2 for ice clouds. Cloud droplet effective radius is greater over ocean than land and has a pronounced seasonal cycle over southern oceans. Comparisons with independent measurements from surface sites, the Ice Cloud and Land Elevation Satellite, and the Aqua Advanced Microwave Scanning Radiometer-Earth Observing System are used to evaluate the results. The mean CERES and MODIS Atmosphere Science Team cloud properties have many similarities but exhibit large discrepancies in certain parameters due to differences in the algorithms and the number of unretrieved cloud pixels. Problem areas in the CERES algorithms are identified and discussed.

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.

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.

Cloud radiative forcing at the top of the atmosphere during FIRE ACE derived from AVHRR data

Cloud radiative forcing at the top of the atmosphere is derived from narrowband visible and infrared radiances from NOAA-12 and NOAA-14 advanced very high resolution radiometer (AVHRR) data taken over the Arctic Ocean during the First ISCCP Regional Experiment Arctic Cloud Experiment (FIRE ACE) during spring and summer 1998. Shortwave and longwave fluxes at the top of the atmosphere (TOA) were computed using narrowband-to-broadband conversion formulae based on coincident Earth Radiation Budget Experiment (ERBE) broadband and AVHRR narrowband radiances. The NOAA-12/NOAA-14 broadband data were validated using model calculations and coincident broadband flux radiometer data from the Surface Heat Budget of the Arctic Ocean experiment and from aircraft data. The AVHRR TOA albedos agreed with the surface- and aircraft-based albedos to within one standard deviation of ±0.029 on an instantaneous basis. Mean differences ranged from −0.012 to 0.023 depending on the radiometer and platform. AVHRR-derived longwave fluxes differed from the model calculations using aircraft- and surface-based fluxes by −0.2 to −0.3 W m−2, on average, when the atmospheric profiles were adjusted to force agreement between the observed and the calculated downwelling fluxes. The standard deviations of the differences were less than 2%. Mean total TOA albedo for the domain between 72°N and 80°N and between 150°W and 180°W changed from 0.695 in May to 0.510 during July, while the longwave flux increased from 217 to 228 W m−2. Net radiation increased from −89 to −2 W m−2 for the same period. Net cloud forcing varied from −15 W m−2 in May to −31 W m−2 during July, while longwave cloud forcing was nearly constant at ∼8 W m−2. Shortwave cloud forcing dominated the cloud effect, ranging from −22 W m−2 during May to −40 W m−2 in July. The mean albedos and fluxes are consistent with previous measurements from the ERBE, except during May when the albedo and longwave flux were greater than the maximum ERBE values. The cloud-forcing results, while similar to some earlier estimates, are the most accurate values hitherto obtained for regions in the Arctic. When no significant melting was present, the clear-sky longwave flux showed a diurnal variation similar to that over land under clear skies. These data should be valuable for understanding the Arctic energy budget and for constraining models of atmosphere and ocean processes in the Arctic.

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds ( about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS 532-nm channel, the primary channel for atmospheric products. Solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (i) calibration with coincident airborne and GLAS observations, (ii) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds, and (iii) calibration from first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Determining the Flight Icing Threat to Aircraft with Single-Layer Cloud Parameters Derived from Operational Satellite Data

AbstractAn algorithm is developed to determine the flight icing threat to aircraft utilizing quantitative information on clouds derived from meteorological satellite data as input. Algorithm inputs include the satellite-derived cloud-top temperature, thermodynamic phase, water path, and effective droplet size. The icing-top and -base altitude boundaries are estimated from the satellite-derived cloud-top and -base altitudes using the freezing level obtained from numerical weather analyses or a lapse-rate approach. The product is available at the nominal resolution of the satellite pixel. Aircraft pilot reports (PIREPs) over the United States and southern Canada provide direct observations of icing and are used extensively in the algorithm development and validation on the basis of correlations with Geostationary Operational Environmental Satellite imager data. Verification studies using PIREPs, Tropospheric Airborne Meteorological Data Reporting, and NASA Icing Remote Sensing System data indicate that the ...

Improved modeling of cloudy‐sky actinic flux using satellite cloud retrievals

Clouds play a critical role in modulating tropospheric radiation and thus photochemistry. We develop a methodology for calculating the vertical distribution of tropospheric ultraviolet (300–420 nm) actinic fluxes using satellite cloud retrievals and a radiative transfer model. We demonstrate that our approach can accurately reproduce airborne-measured actinic fluxes from the 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign as a case study. The actinic flux is reduced below optically moderate-thick clouds inversely with cloud optical depth, and can be enhanced by a factor 2 above clouds. Inside clouds, the actinic flux can be enhanced by 2–3 times in the upper part of clouds or reduced by 90% in the lower parts of clouds. Our study suggests that the use of satellite-derived actinic fluxes as input to chemistry-transport models can improve the accuracy of photochemistry calculations.

Evaluation of model‐simulated upper troposphere humidity using 6.7 μm satellite observations

Use of mesoscale models to simulate details of upper tropospheric relative humidity (UTRH) fields represents an important step toward understanding the evolution of small-scale water vapor structures that are responsible for cirrus growth and dissipation. Because mesoscale model UTRH simulations require initialization and verification and since radiosonde measurements of relative humidity are unreliable in the upper troposphere, we use GOES 6.7 μm water vapor observations to validate the Pennsylvania State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) simulations of UTRH. To accomplish this task, MM5 temperature and moisture profiles are used in a forward calculation of the clear-sky 6.7 μm brightness temperature (T 6.7 ), which is converted into UTRH. A statistical analysis is done to evaluate MM5 simulations of T 6.7 and UTRH against the GOES 7 observations. For the simulations, an average correlation coefficient of 0.80 was found with a dry bias of 1.6 K. In terms of UTRH, the average correlation coefficient was 0.65 with a dry bias of 3.3%. We also found that MM5 fails to simulate accurately extrema in the UTRH field.