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A 3-Channel Algorithm for Retrieving Spatially and Temporally Continuous Cloud Properties Across Different Geostationary Satellite Imagers

Cloud property retrieval algorithms for passive satellite imagers are generally designed to take advantage of all the useful spectral information available for a particular satellite. This strategy optimizes accuracy and reduces misidentification and retrieval biases, particularly for modern satellites with many spectral channels. However, the application of dissimilar algorithms tailored for different satellite sensor scan present a problem within the climate data record (CDR). Algorithm inconsistencies can introduce artificial trends in the CDR that are tied to instrument changes rather than physical changes, especially when older satellites with limited spectral information are included. The NASA CERES (Clouds and the Earth’s Radiant Energy System) data record provides global cloud property retrievals across 23 years and more than 25 satellites. With the goal of producing a spatially and temporally continuous record of cloud properties, the CERES cloud working group has developed algorithms that use only 3 channels that are common to most geostationary satellite imagers: 0.65, 3.9, and 10.8 μm.

Sarah Bedka↗

NASA NTRS2017

On the Relationship Between Sub-Daily Instantaneous and Daily Total Gross Primary Production: Implications for Interpreting Satellite-Based SIF Retrievals

Spatially and temporally continuous estimation of plant photosynthetic carbon fixation (or gross primary production, GPP) is crucial to our understanding of the global carbon cycle and the impact of climate change. Besides spatial, seasonal and interannual variations, GPP also exhibits strong diurnal variations. Satellite retrieved solar-induced chlorophyll fluorescence (SIF) provides a spatially continuous, but temporally discrete measurement of plant photosynthesis, and has the potential to be used to estimate GPP at global scale. However, it remains unclear whether the seasonal time series of SIF snapshots taken at a fixed time of the day can be used to infer daily total GPP variation at spatial and seasonal scales. In this study, we first used GPP estimates from 135 eddy covariance flux sites, covering a wide range of geographic locations and biome types, to investigate the relationship between the instantaneous GPP (GPP(sub inst)) and daily GPP (GPP(sub daily)) on the seasonal course for different times of the day. Latitudinal and diurnal patterns were found to correspond to variations in photosynthetically active radiation (PAR) and light use efficiency (LUE), respectively. We then used the Soil-Canopy Observation Photosynthesis and Energy Balance (SCOPE) model and the FluxCom GPP product to investigate the instantaneous and daily SIF-GPP relationships at five flux tower sites along a latitudinal gradient and at a global scale for different biome types. The results showed that daily SIF had a stronger linear correlation with daily GPP than instantaneous SIF at the seasonal scale, with an instantaneous to daily SIF conversion factor following the latitudinal and seasonal pattern driven by PAR. Our study highlights the necessity to take the latitudinal and diurnal factors into consideration for SIF-GPP relationship analyses or for physiological phenology analyses based on SIF.

photosynthesis model↗

NASA NTRS2016

Cluster Observations of Non-Time Continuous Magnetosonic Waves

Equatorial magnetosonic waves are normally observed as temporally continuous sets of emissions lasting from minutes to hours. Recent observations, however, have shown that this is not always the case. Using Cluster data, this study identifies two distinct forms of these non temporally continuous use missions. The first, referred to as rising tone emissions, are characterized by the systematic onset of wave activity at increasing proton gyroharmonic frequencies. Sets of harmonic emissions (emission elements)are observed to occur periodically in the region +/- 10 off the geomagnetic equator. The sweep rate of these emissions maximizes at the geomagnetic equator. In addition, the ellipticity and propagation direction also change systematically as Cluster crosses the geomagnetic equator. It is shown that the observed frequency sweep rate is unlikely to result from the sideband instability related to nonlinear trapping of suprathermal protons in the wave field. The second form of emissions is characterized by the simultaneous onset of activity across a range of harmonic frequencies. These waves are observed at irregular intervals. Their occurrence correlates with changes in the spacecraft potential, a measurement that is used as a proxy for electron density. Thus, these waves appear to be trapped within regions of localized enhancement of the electron density.

Walker, Simon N.↗

NASA NTRS2009

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Riggs, George A.↗

NASA NTRS2008

Ground Facility for Vicarious Calibration of Skyborne Sensors

An automated ground facility, for vicarious radiometric calibration of airborne and spaceborne sensors of visible and infrared light has been established. In the term "vicarious calibration," "vicarious" is used in the sense of "in place of another," signifying "in place of laboratory calibration." Vicarious calibration involves the use of ground truth in the form of measurements by ground-viewing radiometers, a Sun-viewing photometer, and meteorological instruments positioned in a ground target area. The instrumentation at the facility includes a light-emitting-diode spectrometer (LSpec), which consists of eight tripod-mounted, ground-viewing radiometer units containing LEDs biased to operate as photodetectors (instead of light emitters) at their respective wavelengths. The LSpec provides an essentially continuous stream of measurements at eight discrete wavelengths. These are merged with spectral surface-reflectance measurements made on occasional site visits to obtain temporally continuous coverage with high spectral resolution.

Bruegge, Carol↗

NASA NTRS2005

Towards an A-train Aerosol Assimilation System: Assimilation of MODIS Aerosol Optical Thickness Retrievals into a Global Aerosol Transport and Radiation Model

To understand the role of atmospheric aerosols in Earth's climate system we ideally require a global, three-dimensional, and temporally continuous system of measurements. The view of aerosols provided by a single polar-orbiting satellite instrument (e.g., MODIS), while providing the greatest spatial coverage of any measurement system available, can offer only a single relevant observation per day of a particular location. Furthermore, the quantitative interpretation of those observations is subject to considerable uncertainty because of we do not know the aerosol optical properties or vertical profiles well enough. Ground-based and in situ measurements can provide missing detail about aerosol vertical and optical properties, but lack the spatial (and sometimes temporal) coverage desired. Chemical transport models treating the aerosol lifecycle complement this picture by providing three-dimensional, global, and continuous aerosol fields, but suffer from poor constraints on their initial conditions (e.g., the aerosol source, sink, and transformation mechanisms). Here we present a global, three- dimensional aerosol transport model and assimilation system. The model assimilates the MODIS aerosol optical thickness product to constrain its aerosol distributions and burdens. We provide an analysis of the model aerosol distributions as constrained by ground-based sun photometer measurements and aerosol products from other satellite measurements.

Colarco, P.↗

NASA NTRS2023

Soil Moisture and Sea Surface Salinity Derived from Satellite-Borne Sensors

The monitoring of soil moisture and sea surface salinity over the Earth has been profoundly enhanced during the last thirteen years owing to new generation of satellite sensors. L-band radiometry is currently the only technology providing direct measurements of soil moisture, insensitive to surface roughness and distribution of elements in the soil, and the only technology that allows to measure sea surface salinity from space. The SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive) satellite missions resolve global and local variability with a spatial resolution of approximately 43 km, a swath width close to 1000 km, and a sampling time, for each mission, of at least twice every 3 days. These resolutions and samplings can be increased by either merging data from the two sensors, and with complementary informations gathered with other passive or active sensors, or with in situ information at higher spatial resolution. Numerous scientific studies based on the use of this new type of measurement have led to a better understanding and constraint of the processes governing the variability of the water cycle, ocean circulation and the Earth's climate. The continuity of measurements, and the increased spatial and radiometric resolution is critical for fulfilling scientific needs. Future L-band radiometry missions currently being planned in Europe (the Copernicus Imaging Microwave Radiometer), and in China (the Ocean Salinity Mission) should provide better constraint on auxiliary parameters by combining multiple frequencies, but they will not have improved spatial resolution beyond SMOS and SMAP. The temporal continuity with SMOS and SMAP will most likely not be ensured. In parallel, new concepts are being developed to increase spatial resolution of both land and ocean parameters.

J. Boutin↗

NASA NTRS1999

Impact of a Merged Precipitation Data on Global Soil Moisture Variability

Accurate soil moisture information has proved to be important to climate simulations and climate and weather forecasts. However, many difficulties exist that limit our understanding of soil moisture distribution and variability. One of them is the lack of accurate precipitation with appropriate spatial and temporal resolution. Precipitation as an input forcing to the land surface greatly influences soil moisture characteristics and variability. To improve precipitation data quality, an algorithm has been developed to generate a spatially and temporally continuous 3-hourly global precipitation data for the period of 1987 to present. This precipitation product is a combination of the precipitation from Special Sensor Microwave Imager (SSMI) with the Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) employing a Physical-space Statistical Analysis System (PSAS). In this study we investigate the impact of this merged/analyzed precipitation data on the global soil moisture variability using an Off-line Land-surface GEOS Assimilation (OLGA) system. Two OLGA integrations starting from 1987 to 1993 are performed forced with the analyzed and GEOS-1 DAS precipitation respectively. We examine the spatial and temporal characteristics of soil moisture variability in response to the analyzed precipitation. The influence of this merged precipitation on the soil moisture variability and regional hydrological budget is estimated throughout the comparison with the results forced with the GEOS-1 DAS precipitation only. In the OLGA the sut@-grid scale horizontal heterogeneity is explicitly represented on the tile space. This provides a means to assess the role of the surface moisture heterogeneity in the interaction with the surface atmosphere and surface hydrological budget, and to validate OLGA results at tile space with in situ observation. ABRACOS (Anglo-Brazilian Amazonian Climate Observation Study), FIFE (First ISLSCP Field Experiment) I and HAPEX data will be used in the validation.

Yang, Runhua↗

NASA NTRS2014

Using the SPoRT POES/GOES Hybrid Product in OCONUS Forecasting

The SPoRT (Short-term Prediction and Research Transition) Program at the NASA/Marshall Space Flight Center has been providing unique NASA and NOAA data and techniques to partner Weather Forecast Offices (WFOs) for ten years. Data are provided in the Decision Support System used by WFO forecasters: AWIPS. For the last couple of years, SPoRT has been producing the POES/GOES Hybrid. This suite of products combines the strength ofl5- minute animations of GOES imagery - providing temporal continuity, with the higher resolution, relatively random availability, of polar orbiting (POES) imagery data. The product was first introduced with only MODIS data from NASA's Terra and Aqua satellites, but recently the VIIRS instrument onboard the Suomi-NPP satellite was added, providing better high-resolution coverage. These products represent SPoRT's efforts to prepare for higher resolution, higher frequency GOES-R imagery - as well as helping to move VIIRS (JPSS) data into the mainstream of weather forecasting. SPoRT generates 5 products for this dataset: Visible, Longwave Infrared (11 micrometers), Shortwave IR (3.7 micrometers), Water Vapor (6.7 micrometers), and Fog (Difference of 11 micrometer and 3.7 micrometer channels). The Water Vapor hybrid product has a Red-Blue-Green image from MODIS inlaid, since it provides even more qualitative information than water vapor alone. Animated examples of the products will be shown in this presentation. While the resolution at nadir of GOES imagery is nominally Han (4km for IR channels), the inlaid polar orbiter imagery has a resolution of 250m (lkm for IR channels). This has tremendous application in the continental US. However, in high latitudes, since the usefulness of GOES degrades poleward rapidly, the contrast of GOES and POES data is stark. The consistent temporal nature of GOES, even though at a reduced resolution at high latitudes, provides basic situational awareness, but the introduction of polar data is very helpful in seeing the big picture with clarity - even if only briefly. This presentation will offer real situations where these products helped forecasters make better informed decisions quickly. Plans to augment the product further with the addition of data from several A VHRR instruments will be described.

Smith, Matt↗

NASA NTRS1982

Low-level water vapor fields from the VISSR atmospheric sounder (VAS) split window channels at 11 and 12 microns

A series of high-resolution water vapor fields were derived from the 11 and 12 micron channels of the VISSR Atmospheric Sounder (VAS) on GOES-5. The low-level tropospheric moisture content was separated from the surface and atmospheric radiances by using the differential adsorption across the 'split window' along with the average air temperature from imbedded radiosondes. Fields of precipitable water are presented in a time sequence of five false color images taken over the United States at 3-hour intervals. Vivid subsynoptic and mesoscale patterns evolve at 15 km horizontal resolution over the 12-hour observing period. Convective cloud formations develop from several areas of enhanced low-level water vapor, especially where the vertical water vapor gradient relatively strong. Independent verification at radiosonde sites indicates fairly good absolute accuracy, and the spatial and temporal continuity of the water vapor features indicates very good relative accuracy. Residual errors are dominated by radiometer noise and unresolved clouds.

Chesters, D.↗

NASA NTRS1983

The impact of conventional surface data upon VAS regression retrievals in the lower troposphere

Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the twelve VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observed in the improved relative spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.

Lee, T. H.↗

NASA NTRS1983

The impact of conventional surface data upon VAS regression retrievals in the lower troposphere

Lee, T.-H.↗

NASA NTRS1991

Observing system simulation experiments for the laser atmospheric wind sounder using global spectral model

Fundamental to improving the understanding of the total Earth system are increased and improved observations. In the coming decade several spaceborne instrumented platforms will be constructed and implemented. These platforms will, in large, be housing the NASA Earth Observing System (EOS) instrument suite. One of the proposed instruments is a wind profiling system which is currently referred to as the Laser Atmospheric Wind Sounder (LAWS). This instrument will use a CO2 Doppler lidar wind profiler to give wind measurements with a vertical and horizontal resolution which has yet to be seen globally. The LAWS instrument is now a candidate for launch on a NASA EOS-B platform and is fundamental to increasing our understanding of Earth system science. The LAWS data sets will form an integral component of the temporally continuous data base needed for research of the coupled climate systems. This instrument's observations will aid in giving an improved description of the atmospheric circulation, including the transports of energy, momentum, moisture, trace gases, and aerosols. Also, the wind data will be assimilated and used as the initial state for many global forecast models at various operational centers. Results of system simulation experiments are discussed, and future experiments are described.

Rohaly, Gregg↗

NASA NTRS1992

Aerosols and polar stratospheric clouds measurements during the EASOE campaign

Preliminary results of observations performed using two different lidar systems during the EASOE (European Arctic Stratospheric Ozone Experiment), which has taken place in the winter of 1991-1992 in the northern hemisphere lattitude regions, are presented. The first system is a ground based multiwavelength lidar intended to perform measurements of the ozone vertical distribution in the 5 km to 40 km altitude range. It was located in Sodankyla (67 degrees N, 27 degrees E) as part of the ELSA experiment. The objectives of the ELSA cooperative project is to study the relation between polar stratospheric cloud events and ozone depletion with high vertical resolution and temporal continuity, and the evolution of the ozone distribution in relation to the position of the polar vortex. The second system is an airborne backscatter lidar (Leandre) which allows for the study of the 3-D structure and the optical properties of polar stratospheric clouds. The Leandre instrument is a dual-polarization lidar system, emitting at 532 nm, which allows for the determination of the type of clouds observed, according to the usual classification of polar stratospheric clouds. More than 60 hours of flight were performed in Dec. 1991, and Jan. and Feb. 1992 in Kiruna, Sweden. The operation of the Leandre instrument has led to the observation of the short scale variability of the Pinatubo volcanic cloud in the high latitude regions and to several episodes of polar stratospheric clouds. Preliminary analysis of the data is presented.

Haner, D.↗

NASA NTRS1993

A technique for deriving column-integrated water content using VAS split-window data

An algorithm is examined that uses VISSR Atmospheric Sounder (VAS) 11- and 12-micron (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically based and derives its first-guess information from radiosonde data. The procedure is applied first to a test case data set and then to the 19 June 1986 study day from the Cooperative Huntsville Meteorological Experiment (COHMEX). Ground truth data for verifying results from the technique include IWC from National Weather Service and COHMEX radiosondes, the Multispectral Atmospheric Mapping Sensor (MAMS), and a special set of VAS soundings (12 channel) using an independent retrieval method. Results from the test case show reasonable accuracy with the rms errors as low as +/- 3.8 mm. On the 19 June case study day IWC analyses depict reasonable gradients and exhibit good spatial and temporal continuity. Furthermore, they provide insight into preferred regions for cumulus cloud and thunderstorm formation. On the average, a mean absolute retrieval error of 2.4 mm (an 8.1 percent error) and a rms error of +/- 2.9 mm are obtained on the case study day. These results compare favorably with those from existing VAS IWC techniques. Overall, the findings indicate that the technique has excellent potential to depict mesoscale moisture variations.

Guillory, Anthony R.↗

NASA NTRS2000

Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.

Hart, William D.↗

NASA NTRS2005

Global Retrieval of Aerosol Properties over Desert and Semi-Desert Regions from SeaWiFS and MODIS

Mineral aerosols (dust) play an important role in both climate forcing and oceanic productivity throughout the entire year. Due to the relatively short lifetime (a few hours to about a week), the distributions of these airborne dust particles vary extensively in both space and time. Consequently, satellite observations are needed over both source and sink regions for continuous temporal and spatial sampling of dust properties. However, despite their importance, the high spatial resolution satellite measurements of dust near its source have been lacking. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, sinre the stirfare reflectance nver land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments.

Hsu, Nai-Yung↗

NASA NTRS2005

Global Retrieval of Aerosol Properties from Sources to Sinks By MODIS

Mineral dust and smoke aerosols play an important role in both climate forcing and oceanic productivity throughout the entire year. Due to the relatively short lifetime (a few hours to about a week), the distributions of these airborne particles vary extensively in both space and time. Consequently, satellite observations are needed over both source and sink regions for continuous temporal and spatial sampling of dust and smoke properties. However, despite their importance, the high spatial resolution satellite measurements of these aerosols near their sources have been lacking, In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as MODIS and SeaWiFS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over land, including desert and semi-desert regions. The comparisons show reasonable agreements between these two. Our results show that the dust plumes lifted from the deserts near India/Pakistan border, and over Afghanistan, and the Arabian Peninsula are often observed by MODIS to be transported along the Indo-Gangetic Basin and mixed with the fine mode pollution particles generated by anthropogenic activities in this region, particularly during the pre-monsoon season (April-May). These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments.

Hsu, N. Christina↗