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NASA NTRS2005

Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

Wang, Zhien↗

NASA NTRS2012

On the Cloud Observations in JAXA's Next Coming Satellite Missions

The use of JAXA's next generation satellites, the EarthCARE and the GCOM-C, for observing overall cloud systems on the Earth is discussed. The satellites will be launched in the middle of 2010-era and contribute for observing aerosols and clouds in terms of climate change, environment, weather forecasting, and cloud revolution process study. This paper describes the role of such satellites and how to use the observing data showing concepts and some sample viewgraphs. Synergistic use of sensors is a key of the study. Visible to infrared bands are used for cloudy and clear discriminating from passively obtained satellite images. Cloud properties such as the cloud optical thickness, the effective particle radii, and the cloud top temperature will be retrieved from visible to infrared wavelengths of imagers. Additionally, we are going to combine cloud properties obtained from passive imagers and radar reflectivities obtained from an active radar in order to improve our understanding of cloud evolution process. This is one of the new techniques of satellite data analysis in terms of cloud sciences in the next decade. Since the climate change and cloud process study have mutual beneficial relationship, a multispectral wide-swath imagers like the GCOM-C SGLI and a comprehensive observation package of cloud and aerosol like the EarthCARE are both necessary.

satellite remote sensing↗

NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) algorithm theoretical basis document: Determination of surface and atmosphere fluxes and temporally and spatially averaged products (subsystems 5-12) - volume 4

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and the Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 4 details the advanced CERES techniques for computing surface and atmospheric radiative fluxes (using the coincident CERES cloud property and top-of-the-atmosphere (TOA) flux products) and for averaging the cloud properties and TOA, atmospheric, and surface radiative fluxes over various temporal and spatial scales. CERES attempts to match the observed TOA fluxes with radiative transfer calculations that use as input the CERES cloud products and NOAA National Meteorological Center analyses of temperature and humidity. Slight adjustments in the cloud products are made to obtain agreement of the calculated and observed TOA fluxes. The computed products include shortwave and longwave fluxes from the surface to the TOA. The CERES instantaneous products are averaged on a 1.25-deg latitude-longitude grid, then interpolated to produce global, synoptic maps to TOA fluxes and cloud properties by using 3-hourly, normalized radiances from geostationary meteorological satellites. Surface and atmospheric fluxes are computed by using these interpolated quantities. Clear-sky and total fluxes and cloud properties are then averaged over various scales.

Wielicki, Bruce A.↗

NASA NTRS1995

Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets. 2: Validation and first results

We use global, multiyear observations of the properties of clouds, the atmosphere, and the surface to calculate global shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere and at the surface at a resolution of 280 km and 3 hours for every third month from April 1985 to January 1989. Our validation studies suggest that the specification of cloud effects is no longer the dominant uncertainty in reconstructing the radiative fluxes at the top of atmosphere and at the surface. Rather cloud property uncertainties are now roughly equal contributors to the flux uncertainty, along with surface and atmospheric properties. The resulting SW and LW flux data sets suggest the following conclusions: (1) The net SW heating of Earth appears predominantly at the surface, whereas the net LW cooling arises predominantly from the atmosphere. The net cooling effect of clouds on top of atmospheric radiation appears primarily at the surface rather than in the atmosphere. (2) Clouds have almost no net effect on the global mean radiation balance of the atmosphere, but they enhance the latitudinal gradient in the LW cooling and reinforce the radiative forcing for the mean atmospheric circulation. Clouds act to mute seasonal contrasts however. (3) Clouds enhance the land-ocean contrasts of the atmospheric cooling, reinforcing the growth of standing eddy motions; but reduce land-ocean contrasts of the surface heating.

Rossow, W. B.↗

NASA NTRS1981

Cloud retrieval using infrared sounder data - Error analysis

An error analysis is presented for cloud-top pressure and cloud-amount retrieval using infrared sounder data. Rms and bias errors are determined for instrument noise (typical of the HIRS-2 instrument on Tiros-N) and for uncertainties in the temperature profiles and water vapor profiles used to estimate clear-sky radiances. Errors are determined for a range of test cloud amounts (0.1-1.0) and cloud-top pressures (920-100 mb). Rms errors vary by an order of magnitude depending on the cloud height and cloud amount within the satellite's field of view. Large bias errors are found for low-altitude clouds. These bias errors are shown to result from physical constraints placed on retrieved cloud properties, i.e., cloud amounts between 0.0 and 1.0 and cloud-top pressures between the ground and tropopause levels. Middle-level and high-level clouds (above 3-4 km) are retrieved with low bias and rms errors.

Wielicki, B. A.↗

NASA NTRS1990

Cloud absorption properties as derived from airborne measurements of scattered radiation within clouds

Researchers briefly review the diffusion domain method for deriving the cloud similarity parameter and present preliminary analyses of the results thus far obtained. The presentation concentrates on the following points: (1) intercomparison of calibrated reflected intensities between the cloud absorption radiometer and the U.K. multispectral cloud radiometer; (2) quality control tests required to select those portions of an aircraft flight for which measurements are obtained within the diffusion domain; (3) case studies of the spectral similarity parameter of marine stratocumulus clouds; and comparisons of the experimentally-derived similarity parameter spectrum with that expected theoretically from the cloud droplet size distribution obtained from in situ observations.

King, Michael D.↗

NASA NTRS1998

Clouds, Radiation, and Climate from the Earth Observing System

In this presentation, I will present and discuss key areas of scientific uncertainty in understanding climate and global change, focusing on specific examples of how EOS will contribute to improving our understanding of global change. In particular, I will describe how scientists intend to use MODIS, an earth-viewing cross-track scanning spectroradiometer to be flown on the Earth Observing System (EOS) AM-1 satellite to be launched in summer 1998, for the remote sensing of cloud properties. MODIS will scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and will provide images in 36 spectral bands between 0.415 and 14-235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmosphere processes. As part of this presentation, I will review the various methods that have been developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. Additional applications of MODIS data to the determination of precipitable water over land will be described, as will the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, shadows on the ground, and fires. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application to aircraft and/or satellite measurements.

King, Michael D.↗

NASA NTRS2002

GOES Cloud Detection at the Global Hydrology and Climate Center

The bi-spectral threshold (BTH) for cloud detection and height assignment is now operational at NASA's Global Hydrology and Climate Center (GHCC). This new approach is similar in principle to the bi-spectral spatial coherence (BSC) method with improvements made to produce a more robust cloud-filtering algorithm for nighttime cloud detection and subsequent 24-hour operational cloud top pressure assignment. The method capitalizes on cloud and surface emissivity differences from the GOES 3.9 and 10.7-micrometer channels to distinguish cloudy from clear pixels. Separate threshold values are determined for day and nighttime detection, and applied to a 20-day minimum composite difference image to better filter background effects and enhance differences in cloud properties. A cloud top pressure is assigned to each cloudy pixel by referencing the 10.7-micrometer channel temperature to a thermodynamic profile from a locally -run regional forecast model. This paper and supplemental poster will present an objective validation of nighttime cloud detection by the BTH approach in comparison with previous methods. The cloud top pressure will be evaluated by comparing to the NESDIS operational CO2 slicing approach.

Laws, Kevin↗

NASA NTRS2020

Examining Biases in Diurnally-Integrated Shortwave Irradiances due to Two- and Four-Stream Approximations in Cloudy Atmosphere

Shortwave irradiance biases due to two- and four-stream approximations have been studied for the last couple of decades, but biases in estimating Earth’s radiation budget have not been examined in earlier studies. In order to quantify biases in diurnally-averaged irradiances, we integrate the two- and four-stream biases using realistic diurnal variations of cloud properties from Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) hourly product. Three approximations are examined in this study, delta-two-stream-Eddington (D2strEdd), delta- two-stream-quadrature (D2strQuad), and delta-four-stream-quadrature (D4strQuad). Irradiances computed by the Discrete Ordinates Radiative Transfer (DISORT) and Monte Carlo (MC) methods are used as references. The MC noises are further examined by comparing with DISORT results. When the biases are integrated with a one-day of solar zenith angle variation, regional biases of D2strEdd and D2strQuad reach up to 8 W/sq.m, while biases of D4strQuad reach up to 2 W/sq.m. When the biases are further averaged monthly or annually, regional biases of D2strEdd and D2strQuad can reach –1.5 W/sq.m in SW top-of-atmosphere (TOA) upward irradiances and +3 W/sq.m in surface downward irradiances. In contrast, regional biases of D4strQuad are within +0.9 for TOA irradiances and –1.2 W/sq.m for surface irradiances. Except for polar regions, monthly and annual global mean biases are similar, suggesting that the biases are nearly independent to season. Biases in SW heating rate profiles are up to –0.008 K/d for D2strEdd and –0.016 K/d for D2strQuad, while the biases of the D4strQuad method are negligible.

Ham, Seung-Hee↗

NASA NTRSDate not supplied

TPSAS-NF1676L-27483-DND

scene to retrieve their microphysical properties. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the infrared channels (6.72 Âμm, 7.33 Âμm, 13.3 Âμm,13.6 Âμm, 13.9 Âμm, and 14.2 Âμm) available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to build its algorithms to retrieval cloud properties. Unfortunately, The Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi-NPP (National Polar-Orbiting Partnership) lacks these particular measurements. While conducting research using VIIRS data, it is desirable to bring these data into the VIIRS resolution. The Cross-track Infrared Sounder (CrIS), which is also on board Suomi-NPP, has these infrared channels. This paper describes a method to map the CrIS spectral radiances of CO2 and water vapor to VIIRS, with the mapping software in ATOVS and AVHRR Pre-processing (AAPP) package provided by Satellite Application Facilities for Numerical Weather Prediction (NWP SAF). This method is validated comparing mapped10.763 Âμm from CrIS with M15 from VIIRS. The mapped CO2 and water vapor channels were then created and combined with the conventional VIIRS product, as well as compared against corresponding channels of Aqua MODIS instrument.

Yan Chen↗

NASA NTRS2001

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

King, Michael D.↗

NASA NTRS2002

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

King, Michael D.↗

NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document: Cloud Analyses and Determination of Improved Top of Atmosphere Fluxes (Subsystem 4) - Volume 3

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.

Source record↗

NASA NTRS1999

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Oreopoulos, Lazaros↗

NASA NTRSDate not supplied

Cloud Climate Data Records from Geostationary Satellites to Support CERES: Challenges and Recent Progress

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record at all times of day during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. A brief overview of the current CERES/GEO cloud property data record constructed from three generations of GEOsat imagers for CERES Edition-4 is presented. In this version, different algorithms were applied to different satellites to take advantage of as much spectral information as possible for each satellite. Under this approach, the derived cloud properties were found to become accurate (and more similar to MODIS) for the GEOsat imagers with more spectral information. However, this approach also led to some discontinuities in cloud properties across platforms. Significant differences were also found between daytime and nighttime cloud properties. This paper will highlight the major issues in the Edition-4 record and discuss new strategies and early results from the next version of the SatCORPS GEOsat cloud property time series in development for CERES Edition-5 with the goal of improving day-night and cross-platform consistency during the CERES record.

clouds↗

NASA NTRS2000

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Platnick, Steven↗

NASA NTRSDate not supplied

An Observationally-Based Determination of the Arctic Sea Ice-Cloud Feedback Since 2000: Isolating the Arctic Cloud Response to Sea Ice Loss

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C Taylor↗

NASA NTRSDate not supplied

Estimating the Arctic Cloud-Sea Ice Feedback With Observations during the EOS Period

Patrick C. Taylor↗