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NASA NTRS2001

Carbon Dioxide Snow Storms During the Polar Night on Mars

The Mars Orbiter Laser Altimeter (MOLA) detected clouds associated with topographic features during the polar night on Mars. While uplift generated from flow over mountains initiates clouds on both Earth and Mars, we suggest that the Martian clouds differ greatly from terrestrial mountain wave clouds. Terrestrial wave clouds are generally compact features with sharp edges due to the relatively small particles in them. However, we find that the large mass of condensible carbon dioxide on Mars leads to clouds with snow tails that may extend many kilometers down wind from the mountain and even reach the surface. Both the observations and the simulations suggest substantial carbon dioxide snow precipitation in association with the underlying topography. This precipitation deposits CO2, dust and water ice to the polar caps, and may lead to propagating geologic features in the Martian polar regions.

Toon, Owen B.↗
NASA NTRS2001

Cirrus and Polar Stratospheric Cloud Studies using CLAES Data

We've concluded a 3 year (Period of Performance- January 21, 1998 to February 28, 2001) study of cirrus and polar stratospheric clouds using CLAES (Cryogenic Limb Array Etalon Spectrometer) data. We have described the progress of this study in monthly reports, UARS (Upper Atmosphere Research Satellite) science team meetings, American Geophysical Society Meetings, refereed publications and collaborative publications. Work undertaken includes the establishment of CLAES cloud detection criteria, the refinement of CLAES temperature retrieval techniques, compare the findings of CLAES with those of other instruments, and present findings to the larger community. This report describes the progress made in these areas.

Mergenthaler, John L.↗
NASA NTRS2002

Deuterium Abundance Toward G191-B2B: Results from the Far Ultraviolet Spectroscopic Explorer (FUSE) Mission

High-resolution spectra of the hot white dwarf G191-B2B covering the wavelength region 905-1187A were obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE). This data was used in conjunction with existing high-resolution Hubble Space Telescope STIS observations to evaluate the total H(sub I), D(sub I), O(sub I) and N(sub I) column densities along the line of sight. Previous determinations of N(D(sub I)) based upon GHRS (Goddard High Resolution Spectrograph) and STIS (Space Telescope Imaging Spectrograph) observations were controversial due to the saturated strength of the D(sub I) Lyman alpha line. In the present analysis the column density of D(sub I) has been measured using only the unsaturated Lyman beta and Lyman gamma lines observed by FUSE. A careful inspection of possible systematic uncertainties tied to the modeling of the stellar continuum or to the uncertainties in the FUSE instrumental character series has been performed. The column densities derived are: log N(D(sub I)) = 13.40+/-0.07, log N(O(sub I)) = 14.86+/-0.07, and log N(N(sub I)) = 13.87+/-0.07 quoted with 2sigma, uncertainties. The measurement of the H(sub I) column density by profile fitting of the Lyman alpha line has been found to be unsecure. If additional weak hot interstellar components are added to the three detected clouds along the line of sight, the H(sub I)) column density can be reduced quite significantly, even though the signal-to-noise ratio and spectral resolution at Lyman alpha are excellent. The new estimate of N(H(sub I)) toward G191-B2B reads: logN(H (sub I)) = 18.18+/-0.18 (2sigma uncertainty), so that the average (D/H) ratio on the line of sight is: (D/H)= 1.66(+0.9/-0.6) x 10(exp -5) (2sigma uncertainty).

Lemoine, M.↗
NASA NTRS2002

Intercalibration of Mars Global Surveyor Datasets

The calibration and validation of satellite soundings of atmospheric variables is always a difficult prospect, but this difficulty is greatly magnified when the measurements are made at a different planet, whose meteorology is poorly known and poorly constrained, and for which there are virtually no prospects of obtaining ground truth. The Mars Global Surveyor which has been circling Mars in its mapping orbit since early 1999 includes a variety of instruments capable of making atmospheric observations: the Thermal Emission Spectrometer (TES) which takes more than 100,000 nadir-view infrared spectra per day (although these observations are confined to the 2am - 2pm time of the sun-fixed orbit); much less frequent TES limb scans (still only at 2am and 2pm); the Mars Horizon Sensor Assembly measures side-looking broadband 15 micrometer radiation; Radio Science occultations at favorable seasons give high resolution temperature profiles; the Mars orbiter Camera and Mars Orbiter Laser Altimeter have made water, dust, and carbon dioxide cloud detections. These observations are now being supplemented by high-resolution 15 micron measurements by THEMIS on Mars Odyssey. Thus, all of these observations are made at different times and places. Data assimilation techniques are being used to fuse this vast array of observations into a single dataset that best represents our understanding of the Martian atmosphere, its current meteorological state, and the relevant instrumental properties.

Houben, Howard↗
NASA NTRS2003

MOD06 Optical and Microphysical Retrievals

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

King, Michael D.↗
NASA NTRS2004

Clear-Sky Narrowband Albedo Variations Derived from VIRS and MODIS Data

A critical parameter for detecting clouds and aerosols and for retrieving their microphysical properties is the clear-sky radiance. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the visible (VIS; 0.63 m) and near-infrared (NIR; 1.6 or 2.13 m) channels available on same satellites as the CERES scanners. Another channel often used for cloud and aerosol, and vegetation cover retrievals is the vegetation (VEG; 0.86- m) channel that has been available on the Advanced Very High Resolution Radiometer (AVHRR) for many years. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. Snow albedo is typically estimated without considering the underlying surface type. The albedo for a surface blanketed by snow, however, should vary with surface type because the vegetation often emerges from the snow to varying degrees depending on the vertical dimensions of the vegetation. For example, a snowcovered prairie will probably be brighter than a snowcovered forest because the snow typically falls off the trees exposing the darker surfaces while the snow on a grassland at the same temperatures will likely be continuous and, therefore, more reflective. Accounting for the vegetation-induced differences should improve the capabilities for distinguishing snow and clouds over different surface types and facilitate improvements in the accuracy of radiative transfer calculations between the snow-covered surface and the atmosphere, eventually leading to improvements in models of the energy budgets over land. This paper presents a more complete analysis of the CERES spectral clear-sky reflectances to determine the variations in clear-sky top-of-atmosphere (TOA) albedos for both snow-free and snow-covered surfaces for four spectral channels using data from Terra and Aqua.. The results should be valuable for improved cloud retrievals and for modeling radiation fields.

Sun-Mack, Sunny↗
NASA NTRS2005

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

Schwemmer, Geary K.↗
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 NTRS2005

The Venus SAGE Atmospheric Structure Investigation

Experiment goals and objectives are: a) To accurately define the state properties as a function of altitude from below the 10(exp -4) mb level (approx.150 km) to 92 bars (surface); b) To measure the stability of the atmosphere, and identify convective layers and stable layers, where they exist; c) To detect cloud levels from changes in the lapse rate at their boundaries; d) To provide state properties within the cloud levels, and thus provide supplementary information on cloud composition; e) To search for and characterize wave structure within the atmosphere; f) To search for and measure the intensity and scale of turbulence; g) To measure descent and surface wind speed and direction; h) To provide Lander altitude and attitude during decent for descent imaging analysis; and i) To provide a back-up landing sensor.

Colaprete, Anthony↗
NASA NTRS2007

Comparison of TWP-ICE Satellite and Field Campaign Aircraft Derived Cloud Properties

Cloud and radiation products derived from the MTSAT-1R satellite have been developed for TWP-ICE. These include pixel-level, gridded, and ground site and aircraft matched. These products are available from the Langley website and the ARM data center. As shown in Figs 2, and 4-6, these products compare favorably with in-situ ground and aircraft based measurements. With additional quantitative validation these products can provide valuable information about tropical convection and its impact on the radiation budget and climate. As new algorithm improvements, such as multi-layer cloud detection, are implemented these products will be reprocessed and updated.

Ayers, J. K.↗
NASA NTRS2007

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Nguyen, L.↗
NASA NTRS2010

The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

The next generation Geostationary Operational Environmental Satellite (GOES-R) series is a follow on to the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral (3x), spatial (4x), and temporal (5x) resolution for the Advanced Baseline Imager (ABI). The GLM, an optical transient detector and imager operating in the near-IR at 777.4 nm will map all (in-cloud and cloud-to-ground) lighting flashes continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate Day-1 user readiness for this new capability.

Goodman, Steven J.↗
NASA NTRS2010

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗
NASA NTRS2011

The GOES-R Series Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), which will have just completed Critical Design Review and move forward into the construction phase of instrument development. The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (an engineering development unit and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms

Goodman, Steven J.↗
NASA NTRS2011

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗
NASA NTRS2011

Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

Oswald, Hayden↗
NASA NTRS2011

The Goes-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Goodman, Steven J.↗
NASA NTRS2011

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Goodman, Steven↗