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NASA NTRS1995

Remote sensing of cirrus cloud optical and microphysical properties using AVHRR data

The importance of understanding the radiative and microphysical properties of cirrus clouds in weather and climate research has been articulated by Liou (1986). This importance has also been recognized in view of the intensive field observations that have been conducted as a major component of the First ISCCP Regional Experiment (FIRE) in October-November 1986 (Starr 1987) and more recently in November-December 1991 (FIRE-II) as well as the European experiments on cirrus (ICE/EUCREX) that has been carried out in 1989. One of the fundamental objectives of the FIRE program has been and is to apply the field campaign and theoretical results to develop and verify improved techniques for the inference of cloud radiative and microphysical properties from satellite and surface-based data. A program is designed for the validation of the satellite retrived optical depth and mean effective ice crystal size utilizing in situ replicator observations for ice crystal size distributions and shapes. To minimize the effect of the horizontal size variability of the microphysical structure and the problem associated with collocation and coincidence, an averaging procedures was developed for both the satellite retrieved cloud parameters and the measured ice crystal data.

Liou, K. N.↗
NASA NTRS1993

Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

Emery, William↗
NASA NTRS1990

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the FIRE Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4-km visible (0.65 micro-m) and 8-km infrared window (11.5 micro-m) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 0.62 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance, extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface- based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature were ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperatures and cloud thicknesses from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. The parameterization of visible reflectance in terms of cloud optical depth and clear-sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous AVHRR data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloudy pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study of cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗
NASA NTRS2003

The Cloud Radar System

Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

Racette, Paul↗
NASA NTRS1996

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground based, aircraft, and satellite measurements taken as part of the First ISCCP Region Experiment (FIRE) cirrus intensive field observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center and top heights and the corresponding temperatures. Coincident GOES-4 4-km visible (0.65 micrometer) and 8-km infrared window (11.5 micrometer) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 062 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance , extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface-based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature wer ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperature and cloud thickness from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. the parameterization of visible reflectance in terms of cloud optical depth and clear sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous advanced very high resolution radiometer (AVHRR) data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloud pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study or cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗
NASA NTRS2005

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗
NASA NTRS2005

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗
NASA NTRS1983

Spaceborne SAR and sea ice

A number of remote sensing systems deployed in satellites to view the Earth which are successful in gathering data on the behavior of the world's snow and ice covers are described. Considering sea ice which covers over 10% of the world ocean, systems that have proven capable to collect useful data include those operating in the visible, near-infrared, infrared, and microwave frequency ranges. The microwave systems have the essential advantage in observing the ice under all weather and lighting conditions. Without this capability data are lost during the long polar night and during times of storm passage, periods when ice activity can be intense. The margins of the ice pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time.

Weeks, W. F.↗
NASA NTRS2007

Remote Sensing of the Radiative and Microphysical Properties of Clouds during TC4: Results from MAS, MASTER, MODIS, and MISR

The MODIS Airborne Simulator (MAS) and MODIS/ASTER Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.3 (12.9 m for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Clouds and Climate Coupling Experiment (TC4) conducted over Central America and surrounding Pacific and Atlantic Oceans between July 17 and August 8, 2007. Multispectral images in eight distinct bands were used to derive a confidence in clear sky (or alternatively the probability of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of this cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm as that implemented operationally to process MODIS cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER date in TC4, is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals used three distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to MISR data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis will be presented and discussed.

King, Michael D.↗
NASA NTRSDate not supplied

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗
NASA NTRS2006

Comparison of Balloonsonde and Remote Sensing Atmospheric Measurements

As part of its aircraft icing research program, the NASA Glenn Research Center is conducting a program to develop technologies for the remote sensing of atmospheric conditions. A suite of instruments, currently ground-based, are used to identify a region of supercooled liquid water which is labeled as hazardous if its liquid water content is sufficiently high. During the recently completed Alliance Icing Research Study (AIRS II), these instruments were deployed in conjunction with those of other U.S. and Canadian researchers at the Mirabel Airport near Montreal. As part of the study, balloonsondes were employed to provide in-situ measurement of the atmospheric conditions that were being concurrently remotely sensed. Balloonsonde launches occurred daily at 1200 GMT to provide AIRS forecasters with local data and additionally when research aircraft were present in the airspace. In this paper, we compare the processed data from the NASA remote sensing instruments, which included an X-band radar, lidar and two radiometers, to the data gathered from the 70 soundings conducted while the NASA instruments were active. Among the parameters compared are cloud upper and lower boundaries, temperature and humidity profiles and freezing levels.

Brinker, David J.↗
NASA NTRS2005

Improvements in Virtual Sensors: Using Spatial Information to Estimate Remote Sensing Spectra

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high resolution spectral measurements may be too costly to perform on a large sample and therefore lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. In past work [1], we addressed this problem using Virtual Sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. We demonstrated this method by using models trained on the high spectral resolution Terra MODIS instrument to estimate what the equivalent of the MODIS 1.6 micron channel would be for the NOAA AVHRR2 instrument. The scientific motivation for the simulation of the 1.6 micron channel is to improve the ability of the AVHRR2 sensor to detect clouds over snow and ice. This work contains preliminary experiments demonstrating that the use of spatial information can improve our ability to estimate these spectra.

Oza, Nikunj C.↗
NASA NTRS2000

A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications: Simulation of TRMM Observations - Part 2

The one-dimensional, steady-state melting layer model developed in Part I of this study is used to calculate both the microphysical and radiative properties of melting precipitation, based upon the computed concentrations of snow and graupel just above the freezing level at applicable horizontal gridpoints of 3-dimensional cloud resolving model simulations. The modified 3-dimensional distributions of precipitation properties serve as input to radiative transfer calculations of upwelling radiances and radar extinction/reflectivities at the TRMM Microwave Imager (TMI) and Precipitation Radar (PR) frequencies, respectively. At the resolution of the cloud resolving model grids (approx. 1 km), upwelling radiances generally increase if mixed-phase precipitation is included in the model atmosphere. The magnitude of the increase depends upon the optical thickness of the cloud and precipitation, as well as the scattering characteristics of ice-phase precipitation aloft. Over the set of cloud resolving model simulations utilized in this study, maximum radiance increases of 43, 28, 18, and 10 K are simulated at 10.65, 19.35 GHz, 37.0, and 85.5 GHz, respectively. The impact of melting on TMI-measured radiances is determined not only by the physics of the melting particles but also by the horizontal extent of the melting precipitation, since the lower-frequency channels have footprints that extend over 10''s of kilometers. At TMI resolution, the maximum radiance increases are 16, 15, 12, and 9 K at the same frequencies. Simulated PR extinction and reflectivities in the melting layer can increase dramatically if mixed-phase precipitation is included, a result consistent with previous studies. Maximum increases of 0.46 (-2 dB) in extinction optical depth and 5 dBZ in reflectivity are simulated based upon the set of cloud resolving model simulations.

Olson, William S.↗
NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗
NASA NTRS2003

Passive and Active Detection of Clouds: Comparisons between MODIS and GLAS Observations

The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the Aqua satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, MODIS scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the MODIS data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.

Mahesh, Ashwin↗
NASA NTRS2001

Resolution Enhancement of Spaceborne Radiometer Images

Our progress over the last year has been along several dimensions: 1. Exploration and understanding of Earth Observatory System (EOS) mission with available data from NASA. 2. Comprehensive review of state of the art techniques and uncovering of limitations to be investigated (e.g. computational, algorithmic ...). and 3. Preliminary development of resolution enhancement algorithms. With the advent of well-collaborated satellite microwave radiometers, it is now possible to obtain long time series of geophysical parameters that are important for studying the global hydrologic cycle and earth radiation budget. Over the world's ocean, these radiometers simultaneously measure profiles of air temperature and the three phases of atmospheric water (vapor, liquid, and ice). In addition, surface parameters such as the near surface wind speed, the sea surface temperature, and the sea ice type and concentration can be retrieved. The special sensor microwaves imager SSM/I has wide application in atmospheric remote sensing over the ocean and provide essential inputs to numerical weather-prediction models. SSM/I data has also been used for land and ice studies, including snow cover classification measurements of soil and plant moisture contents, atmospheric moisture over land, land surface temperature and mapping polar ice. The brightness temperature observed by SSM/I is function of the effective brightness temperature of the earth's surface and the emission scattering and attenuation of the atmosphere. Advanced Microwave Scanning Radiometer (AMSR) is a new instrument that will measure the earth radiation over the spectral range from 7 to 90 GHz. Over the world's ocean, it will be possible to retrieve the four important geographical parameters SST, wind speed, vertically integrated water vapor, vertically integrated cloud liquid water L.

Krim, Hamid↗
NASA NTRS2024

Antarctic polar stratospheric cloud composition as observed by ACE, CALIPSO and MIPAS

The composition of polar stratospheric clouds (PSCs) in the Antarctic is measured by infrared absorption spectroscopy by the Atmospheric Chemistry Experiment (ACE) satellite and compared to lidar (CALIPSO) and emission spectroscopy (MIPAS) results. ACE observations are compared first to CALIPSO for the period 2006–2020, then to MIPAS for the period 2005–2011, and then a set of triple coincidences is studied. In both CALIPSO-ACE and MIPAS-ACE comparisons, nitric acid trihydrate (NAT) detections are in excellent agreement (∼80 % of coincident compositions is found). Supercooled ternary solution (STS) detections are in good agreement for CALIPSO-ACE (∼60 %) but in poor agreement for MIPAS-ACE (39 %). This contrasts with ice detections, in poor agreement for CALIPSO-ACE (∼30 %) and in better agreement for MIPAS-ACE (45 %). Triple coincidences show that ACE STS detections are more reliable than MIPAS STS detections. The comparison between ACE observations and homogeneous CALIPSO PSCs shows that for 11 events, CALIPSO reports STS rather than supercooled nitric acid (SNA) clouds.

Atmospheric Chemistry Experiment↗
NASA NTRS2010

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

King, Michael D.↗