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NASA NTRS1994

Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation

A physically based algorithm sensitive to emission and scattering is used to estimate rainfall using the Special Sensor Microwave/Imager (SSM/I). The algorithm is derived from radiative transfer calculations through an atmospheric cloud model specifying vertical distributions of ice and liquid hydrometeors as a function of rain rate. The algorithm is structured in two parts: SSM/I brightness temperatures are screened to detect rainfall and are then used in rain-rate calculation. The screening process distinguishes between nonraining background conditions and emission and scattering associated with hydrometeors. Thermometric temperature and polarization thresholds determined from the radiative transfer calculations are used to detect rain, whereas the rain-rate calculation is based on a linear function fit to a linear combination of channels. Separate calculations for ocean and land account for different background conditions. The rain-rate calculation is constructed to respond to both emission and scattering, reduce extraneous atmospheric and surface effects, and to correct for beam filling. The resulting SSM/I rain-rate estimates are compared to three precipitation radars as well as to a dynamically simulated rainfall event. Global estimates from the SSM/I algorithm are also compared to continental and shipboard measurements over a 4-month period. The algorithm is found to accurately describe both localized instantaneous rainfall events and global monthly patterns over both land and ovean. Over land the 4-month mean difference between SSM/I and the Global Precipitation Climatology Center continental rain gauge database is less than 10%. Over the ocean, the mean difference between SSM/I and the Legates and Willmott global shipboard rain gauge climatology is less than 20%.

Ferriday, James G.↗

NASA NTRS1995

Modeling of Wind Direction Signals in Polarimetric Sea Surface Brightness Temperatures

Sea surface brightness temperatures are the radiometric power measure of blackbody radiation from sea water. This radiation is the electromagnetic waves excited by the random thermal motion of charged particles in the sea water. The energy transmitted through the air- water interface produces a scattering of electromagnetic waves into the atmosphere. Polarimetric microwave emissions are investigated.

ocean wind remote sensing polarimetric microwave r↗

NASA NTRS1998

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

The successful launch of the National Space Development Agency of Japan (NASDA) Ocean Color and Temperature Sensor (OCTS) in August 1996, and the launch of Orbital Science Corporation's (OSC) Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) in August 1997 signaled the beginning of a new era for ocean color research and application. These data may be used to remotely evaluate 1) water quality, 2) transport of sediments and adhered pollutants, 3) primary production, upon which commercial shellfish and finfish populations depend for food, and 4) harmful algal blooms which pose a threat to public health and economies of affected areas. Several US government agencies have recently expressed interest in monitoring U.S. coastal waters using optical remote sensing. This renewed interest is broadly driven by 1) resource management concerns over the impact of coastward shifts in population and land use on the ecosystems of estuaries, wetlands, nearshore benthic environments and fisheries, 2) recognition of the need to understand short time scale global change due to urbanization of sensitive land-margin ecosystems, and 3) national security issues. Satellite ocean color sensors have the potential to furnish data at the appropriate time and space scales to evaluate and resolve these concerns and problems. In this draft technical memorandum, we outline our progress during the first year of our SIMBIOS project to evaluate ocean color bio-optical algorithms and products generated using OCTS and SeaWiFS data in coastal US waters.

Brown, Christopher W.↗

NASA NTRS2005

Analysis of Upper Air, Ground and Remote Sensing Data for the Atlas Field Campaign in San Juan, Puerto Rico

The general climate of the island of Puerto Rico is dominated by the easterly trade winds from the Atlantic Ocean, and during synoptically calm days by the topographic and local land surface characteristics [1]. The urban canopy of the metropolitan area of San Juan, capital city of the Island, may introduce a new microclimate that changes the characteristics of the low atmosphere and interacts with the other microclimates already present in the island. The primitive land cover and land use (LCLU) of the metropolitan area of San Juan was composed by broadleaf trees, moist soils, and very dense vegetation in general. The urban LCLU changes the balance for the mass, momentum and energy between the bottom boundary and the lower atmosphere, creating different climate conditions over urban and rural regions. Some of these differences are low relative humidity and high temperatures observed in urban areas when compared to rural areas. These in turn produces a convective circulation over the urban areas, a phenomenon compared to the sea and land breezes, commonly known as heat islands (UHI). Factors that contribute to the formation of the UHI are anthropogenic heat sources, aerosols from pollutants, fast water canalization due to the presence of buildings and streets, among others. The comparison between urban and rural climates is the most common approach to analyze the UHI. These contrasts are larger in clear and calm conditions and tend to disappear in cloudy and windy weather. The UHI was recognized in the early 1950 s as closed isotherms that separates the city from the general temperature field [2]. The impact of the urban LCLU in San Juan, Puerto Rico, was quantified calculating the difference between historical data sets for the air temperature over an identified urban area and a rural area dT(U-R). The analysis of the climatological data revealed that a UHI exists in the metropolitan area of San Juan, Puerto Rico. The data reveals a permanent urban heat island effect present in the SJMA during the year, which is increasing at a rate of 0.41oC/decade. These findings encouraged the planning and execution of an intense field campaign in February 2004 referred as the ATLAS San Juan mission. The focus of the remaining of this report is the analysis of the data for this field campaign.

Gonzalez-Cruz, Jorge E.↗

NASA NTRS1994

Consistency in long-term observations of oceans and ice from space

Satellite remote sensing has provided powerful tools for constructing long-term records of observations of many of Earth's geophysical processes. Geophysicists studying climage change would like to construct time series of data which are as long, accurate, and consistent as possible. While technological advances continue to improve the quality of observations from space, they also present consistency problems. The scanning multichannel microwave radiometer (SMMR), which operated from October 1978 to August 1987, and the special sensor microwave imager (SSMI), which overlapped with the SMMR for nearly two months in 1987, have provided microwave radiances which have been used to monitor long-term changes in sea ice concentration and snow accumulation, among other things. Inspection has shown, however, that brightness temperatures from the two sensors over the same polar firn-covered scene can differ by as much as 14 K. Calibration corrections for polar firn have been derived; in this paper, we present calculations addressing the physics of the small frequency and viewing angle differences between the SMMR and the SSMI on microwave emission from polar scenes containing free water. We focus here only on surface emission. We use a surface scattering model and study the effects of surface roughness, snow wetness, snow density, and young sea ice concentration. We also compare data from Antarctica with our modeled results. We find that for most scenes, surface roughness dominates over the effects of frequency and viewing angle differences, but that for open long-term times series, data must be calibrated and constructed at the geophysical product level rather than at the level of measured radiances.

Zabel, I. H. H.↗

NASA NTRS2013

Algorithm Development for Predicting Biodiversity Based on Phytoplankton Absorption

Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.

phytoplankton↗

NASA NTRS2016

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗

NASA NTRS1975

The fluorescence of chlorophyll and yellow substances in natural waters: A note on the problems of measurement and the importance of their remote sensing

There are two chromophylls which, if sensed remotely from high altitude, would revolutionize the ability to survey large areas of the world's oceans. The chromophylls of importance are: the photosynthetic pigments of plankton algae and a group of organic materials frequently termed dissolved yellow substances. These are derived from plants and carried into the ocean by fresh water inflow. The attenuation of light by phytoplankton is characterized by two distinctive bands (450, 675 nm) which represent absorption by chloroplastic pigments. Yellow substances are characterized by a strong ultraviolet absorption which tails over into the visible region. It is emphasized that chlorophyll determination could be a unique technique for estimating the extent of eutrophication in coastal waters, and that a high altitude observer equipped with temperature, chlorophyll and yellow substance sensors has the possibility of detecting the magnitude of eutrophication and its sources by using laser induced fluorescent devices.

Yentsch, C. S.↗

NASA NTRS2005

Global monitoring of Sea Surface Salinity with Aquarius

Aquarius is a microwave remote sensing system designed to obtain global maps of the surface salinity field of the oceans from space. It will be flown on the Aquarius/SAC-D mission, a partnership between the USA (NASA) and Argentina (CONAE) with launch scheduled for late in 2008. The objective of Aquarius is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean. This will provide data to address scientific questions associated with ocean circulation and its impact on climate. For example, salinity is needed to understand the large scale thermohaline circulation, driven by buoyancy, which moves large masses of water and heat around the globe. Of the two variables that determine buoyancy (salinity and temperature), temperature is already being monitored. Salinity is the missing variable needed to understand this circulation. Salinity also has an important role in energy exchange between the ocean and atmosphere, for example in the development of fresh water lenses (buoyant water that forms stable layers and insulates water below from the atmosphere) which alter the air-sea coupling. Aquarius is a combination radiometer and scatterometer (radar) operating at L-band (1.413 GHz for the radiometer and 1.26 GHz for the scatterometer). The primary instrument,for measuring salinity is the radiometer which is able to detect salinity because of the modulation salinity produces on the thermal emission from sea water. This change is detectable at the long wavelength end of the microwave spectrum. The scatterometer will provide a correction for surface roughness (waves) which is one of the greatest unknowns in the retrieval. The sensor will be in a sun-synchronous orbit at about 650 km with equatorial crossings of 6am/6pm. The antenna for these two instruments is a 3 meter offset fed reflector with three feeds arranged in pushbroom fashion looking away from the sun toward the shadow side of the orbit to minimize sunglint. The mission goal is to produce maps of the salinity field globally once each month with an accuracy of 0.2 psu and a spatial resolution of 100 km. This will be adequate to address l&ge scale features of the salinity field of the open ocean. The temporal resolution is sufficient to address seasonal changes and a three year mission is planned to-collect sufficient data to look for interannual variation. Aquarius is being developed by NASA as part of the Earth System Science Pathfinder (ESSP) program. The SAC-D mission is being developed by CONAE and will include the space craft and several additional instruments, including visible and infrared cameras and a microwave radiometer to monitor rain and wind velocity over the oceans, and sea ice.

Lagerloef, G. S. E.↗

NASA NTRS2016

High Latitude Dust in the Earth System

Natural dust is often associated with hot, subtropical deserts, but significant dust events have been reported from cold, high latitudes. This review synthesizes current understanding of high-latitude (> or = 50degN and > or = 40degS) dust source geography and dynamics and provides a prospectus for future research on the topic. Although the fundamental processes controlling aeolian dust emissions in high latitudes are essentially the same as in temperate regions, there are additional processes specific to or enhanced in cold regions. These include low temperatures, humidity, strong winds, permafrost and niveo-aeolian processes all of which can affect the efficiency of dust emission and distribution of sediments. Dust deposition at high latitudes can provide nutrients to the marine system, specifically by contributing iron to high-nutrient, low-chlorophyll oceans; it also affects ice albedo and melt rates. There have been no attempts to quantify systematically the expanse, characteristics, or dynamics of high-latitude dust sources. To address this, we identify and compare the main sources and drivers of dust emissions in the Northern (Alaska, Canada, Greenland, and Iceland) and Southern (Antarctica, New Zealand, and Patagonia) Hemispheres. The scarcity of year-round observations and limitations of satellite remote sensing data at high latitudes are discussed. It is estimated that under contemporary conditions high-latitude sources cover >500,000 sq km and contribute at least 80-100 Tg/yr1 of dust to the Earth system (approx. 5% of the global dust budget); both are projected to increase under future climate change scenarios.

albedo↗

NASA NTRS2003

Stray-Light Correction of the Marine Optical Buoy

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Brown, Steven W.↗

NASA NTRS2006

Thermal Band Atmospheric Correction Using Atmospheric Profiles Derived from Global Positioning System Radio Occultation and the Atmospheric Infrared Sounder

This Rapid Prototyping Capability study explores the potential to use atmospheric profiles derived from GPS (Global Positioning System) radio occultation measurements and by AIRS (Atmospheric Infrared Sounder) onboard the Aqua satellite to improve surface temperature retrieval from remotely sensed thermal imagery. This study demonstrates an example of a cross-cutting decision support technology whereby NASA data or models are shown to improve a wide number of observation systems or models. The ability to use one data source to improve others will be critical to the GEOSS (Global Earth Observation System of Systems) where a large number of potentially useful systems will require auxiliary datasets as input for decision support. Atmospheric correction of thermal imagery decouples TOA radiance and separates surface emission from atmospheric emission and absorption. Surface temperature can then be estimated from the surface emission with knowledge of its emissivity. Traditionally, radiosonde sounders or atmospheric models based on radiosonde sounders, such as the NOAA (National Oceanic & Atmospheric Administration) ARL (Air Resources Laboratory) READY (Real-time Environmental Application and Display sYstem), provide the atmospheric profiles required to perform atmospheric correction. Unfortunately, these types of data are too spatially sparse and too infrequently taken. The advent of high accuracy, global coverage, atmospheric data using GPS radio occultation and AIRS may provide a new avenue for filling data input gaps. In this study, AIRS and GPS radio occultation derived atmospheric profiles from the German Aerospace Center CHAMP (CHAllenging Minisatellite Payload), the Argentinean Commission on Space Activities SAC-C (Satellite de Aplicaciones Cientificas-C), and the pair of NASA GRACE (Gravity Recovery and Climate Experiment) satellites are used as input data in atmospheric radiative transport modeling based on the MODTRAN (MODerate resolution atmospheric TRANsmittance) radiative transport software to separate out the atmospheric component of measured top of atmosphere radiance. Simulated water bodies across a variety of MODTRAN model atmospheres including desert, mid-latitude, tropical and sub-artic conditions provide test bed conditions. Atmospherically corrected radiance and surface temperature results were compared to those obtained using traditional radiosonde balloon data and models. In general, differences between the different techniques were less than 2 percent indicating the potential value satellite derived atmospheric profiles have to atmospherically correct thermal imagery.

Pagnutti, Mary↗

NASA NTRSDate not supplied

FORWARD AND INVERSE L-BAND RADIATIVE TRANSFER MODELING OVER THE DRY CHACO, USING SMOS OBSERVATIONS, LAND SURFACE MODELING AND IN SITU DATA

Passive microwave L-band remote sensing is well known for its sensitivity to surface soil moisture over land.The signal is also affected by other dynamic variables such as vegetation and soil salinity. In this research, L-band microwave observations of the Soil Moisture Ocean Salinity (SMOS) mission are used to explore soil surface salinity, moisture and vegetation, in the Argentinean Dry Chaco, an area with possible emerging dryland salinity. A Radiative Transfer Model (RTM) with inclusion of a correction to the soil’s dielectric constant for salinity was used in forward and inverse mode, using either in situ data or Catchment Land Surface Model (CLSM) simulations as RTM input. The forward analysis pointed out shortcomings in the modeled soil moisture and soil surface temperature estimates. The impact of salinity on forward simulations over the Dry Chaco was limited.The RTM inversion using 10 years of SMOS brightness temperature observations resulted in realistic estimates of vegetation and roughness, both with and withouto ptimizing a correction term for the dielectric constant in terms of salinity equivalents. However,the retrieval of the correction term to the dielectric constant was very uncertain and not representative of soil surface salinity, but rather of open water, texture uncertainty or soil moisture bias.

L-band↗

NASA NTRS1982

Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981

The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.

Mcintosh, R.↗

NASA NTRS2003

Global Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 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, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

King, Michael D.↗

NASA NTRS2003

Global Multispectral Cloud Retrievals from MODIS

King, Michael D.↗

NASA NTRS2023

Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products

Coastal upwelling regions are one of the most dynamic areas of the world’s oceans. The California and Baja California Coasts are impacted by both coastal upwelling and the California Current, leading to frontal activity that is captured by gradients in both Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). Satellite data are a great source of spatial data to study fronts. However, biases near coastal areas and coarse resolutions can impair its usefulness in upwelling areas. In this work gradients in SST from NASA Multi-Scale Ultra-High Resolution (MUR) and in two SSS products derived from the Soil Moisture Active Passive (SMAP) NASA mission are compared directly with gradients derived from the Saildrone uncrewed vehicles to validate the gradients as well as to assess their ability to detect known frontal features. The three remotely sensed data sets (MURSST/JPL, SMAP SSS/RSS, SMAP SSS) were co-located with the Saildrone data prior to the calculation of the gradients. Wavelet analysis is used to determine how well the satellite derived SST and SSS products are reproducing the Saildrone derived gradients. Overall results indicate the remote sensing products are reproducing features of known areas of coastal upwelling. Differences between the SST and SSS gradients are mainly associated with the limitations of the microwave derived SSS coverage near land and its reduced spatial resolution. The results are promising for using remote sensing data sets to monitor frontal structure along the California Coast and the application to long term changes in coastal upwelling and dynamics.

Sea Surface Salinity↗

NASA NTRS2001

Remote Sensing, GIS, and Vector-Borne Disease

The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).

Beck, Louisa R.↗