Search NASA⌕ Search

SEARCH · Search NASA

Results for “METEOROLOGICAL SATELLITES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Kawamoto, K.↗
NASA NTRS1994

Simulating Local and Intercontinental Pollutant Effects of Biomass Burning: Integration of Several Remotely Sensed Datasets

Burning to clear land for crops and to destroy pests is an integral and largely unavoidable part of tropical agriculture. It is easy to note but difficult to quantify using remote sensing. This report describes our efforts to integrate remotely sensed data into our computer model of tropical chemical trace-gas emissions, weather, and reaction chemistry (using the MM5 mesoscale model and our own Global-Regional Atmospheric Chemistry Simulator). The effects of burning over the continents of Africa and South America have been noticed in observations from several satellites. Smoke plumes hundreds of kilometers long may be seen individually, or may merge into a large smoke pall over thousands of kilometers of these continents. These features are related to intense pollution in the much more confined regions with heavy burning. These emissions also translocate nitrogen thousands of kilometers in the tropical ecosystems, with large fixed-nitrogen losses balanced partially by locally intense fertilization downwind, where nitric acid is rained out. At a much larger scale, various satellite measurements have indicated the escape of carbon monoxide and ozone into large filaments which extend across the Tropical and Southern Atlantic Ocean. Our work relates the source emissions, estimated in part from remote sensing, in part from conventional surface reports, to the concentrations of these gases over these intercontinental regions. We will mention work in progress to use meteorological satellite data (AVHRR, GOES, and Meteosat) to estimate the surface temperature and extent and height of clouds, and explain why these uses are so important in our computer simulations of global biogeochemistry. We will compare our simulations and interpretation of remote observations to the international cooperation involving Brazil, South Africa, and the USA in the TRACE-A (Transport and Atmospheric Chemistry near the Equator - Atlantic) and SAFARI (Southern Africa Fire Atmosphere Research Initiative) and remote-sensing /aircraft/ecosystem observational campaigns.

Chatfield, Robert B.↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds

Kawamoto, Kazuaki↗
NASA NTRS2004

A Real-Time Satellite-Based Icing Detection System

Aircraft icing is one of the most dangerous weather conditions for general aviation. Currently, model forecasts and pilot reports (PIREPS) constitute much of the database available to pilots for assessing the icing conditions in a particular area. Such data are often uncertain or sparsely available. Improvements in the temporal and areal coverage of icing diagnoses and prognoses would mark a substantial enhancement of aircraft safety in regions susceptible to heavy supercooled liquid water clouds. The use of 3.9 microns data from meteorological satellite imagers for diagnosing icing conditions has long been recognized (e.g., Ellrod and Nelson, 1996) but to date, no explicit physically based methods have been implemented. Recent advances in cloud detection and cloud property retrievals using operational satellite imagery open the door for real-time objective applications of those satellite datasets for a variety of weather phenomena. Because aircraft icing is related to cloud macro- and microphysical properties (e.g., Cober et al. 1995), it is logical that the cloud properties from satellite data would be useful for diagnosing icing conditions. This paper describes the a prototype realtime system for detecting aircraft icing from space.

Minnis, Patrick↗
NASA NTRS1999

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

Rodgers, Edward↗
NASA NTRS1997

Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-Microwave Satellite Data Sets: October 1978-September 1995 User's Guide

Satellite multichannel passive-microwave sensors have provided global radiance measurements with which to map, monitor, and study the Arctic and Antarctic polar sea ice covers. The data span over 18 years (as of April 1997), starting with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) on NASA's SeaSat A and Nimbus 7 in 1978 and continuing with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI) series beginning in 1987. It is anticipated that the DMSP SSMI series will continue into the 21st century. The SSMI series will be augmented by new, improved sensors to be flown on Japanese and U.S. space platforms. This User's Guide provides a description of a new sea ice concentration data set generated from observations made by three of these multichannel sensors. The data set includes gridded daily ice concentrations (every-other-day for the SMMR data) for both the north and south polar regions from October 26, 1978 through September 30, 1995, with the one exception of a 6-week data gap from December 3, 1987 through January 12, 1988. The data have been placed on two CD-ROMs that include a ReadMeCD file giving the technical details on the file format, file headers, north and south polar grids, ancillary data sets, and directory structure of the CD-ROM. The CD-ROMS will be distributed by the National Snow and Ice Data Center in Boulder, CO.

Sea ice concentration↗
NASA NTRS2013

Survey of DMSP Charging Events During the Period Preceding Cycle 23 Solar Maximum

It has been well established that POLAR orbiting satellites can see mild to severe charging levels during solar minimum conditions (Frooninckx and Sojka, 1992, Anderson and Koons, 1996, Anderson, 2012). However, spacecraft operations during solar maximum cannot be considered safe from auroral charging. Recently, we have seen examples of high level charging during the recent approach to solar maximum. We present here a survey of charging events seen by the Defense Meteorological Satellite Program (DMSP) satellites (F16, F17) during the solstices of 2011 and 2012. In this survey, we summarize the condition necessary for charging to occur in this environment, we describe how the lower than normal maximum conditions are conducive to the environment conditions necessary for charging in the POLAR orbit, and we show examples of the more extreme charging events, sometimes exceeding 1 kV, during this time period. We also show examples of other interesting phenomenological events seen in the DMSP data, but which are not considered surface charging events, and discuss the differences.

Parker, Linda Neergaard↗
NASA NTRS2013

Survey of DMSP Charging During the Period Preceding Cycle 24 Solar Maximum

It has been well established that polar orbiting satellites can see mild to severe charging levels during solar minimum conditions (Frooninckx and Sojka, 1992, Anderson and Koons, 1996, Anderson, 2012). However, spacecraft operations during solar maximum cannot be considered safe from auroral charging. Recently, we have seen examples of high level charging during the recent approach to solar maximum. We present here a survey of charging events seen by the Defense Meteorological Satellite Program (DMSP) satellites (F16, F17) during the solstices of 2011 and 2012. In this survey, we summarize the condition necessary for charging to occur in this environment, we describe how the lower than normal maximum conditions are conducive to the environment conditions necessary for charging in the polar orbit, and we show examples of the more extreme charging events, sometimes exceeding 1 kV, during this time period. We also show examples of other interesting phenomenological events seen in the DMSP data, but which are not considered surface charging events, and discuss the differences.

NeergaardParker, L.↗
NASA NTRS1974

Electrically scanning microwave radiometers

The electrically scanning microwave radiometer (ESMR) developed for and currently used onboard the Nimbus 5 meteorological satellite is described, along with the ESMR developed for the Nimbus F satellite. They serve for synoptic mapping of microwave emissions from the earth's surface, the instrument on Nimbus 5 measuring these emissions at a wavelength of 1.55 cm (19.35 GHz) and the instrument on Nimbus F, at a wavelength of 0.81 cm (37 GHz). Radiative transfer characteristics measured at these wavelengths are sufficiently different from IR measurements to permit derivation and interpretation of unique meteorological, geomorphological, and oceanographic data.

Mix, R. F.↗
NASA NTRS1998

Earth Observing System/Meteorological Satellite (EOS/METSAT). Advanced Microwave Sounding Unit-A (AMSU-A) Contamination Control Plan

This Contamination Control Plan is submitted in response the Contract Document requirements List (CDRL) 007 under contract NAS5-32314 for the Earth Observing System (EOS) Advanced Microwave Sounding Unit A (AMSU-A). In response to the CDRL instructions, this document defines the level of cleanliness and methods/procedures to be followed to achieve adequate cleanliness/contamination control, and defines the required approach to maintain cleanliness/contamination control through shipping, observatory integration, test, and flight. This plan is also applicable to the Meteorological Satellite (METSAT) except where requirements are identified as EOS-specific. This plan is based on two key factors: a. The EOS/METSAT AMSU-A Instruments are not highly contamination sensitive. b. Potential contamination of other EOS Instruments is a key concern as addressed in Section 9/0 of the Performance Assurance Requirements for EOS/METSAT Integrated Programs AMSU-A Instrument (MR) (NASA Specification S-480-79).

Fay, M.↗
NASA NTRS1976

Interactive applications of satellite observations and mesoscale numerical models

The impact of numerical weather prediction (NWP) and satellite meteorology on operational weather forecasting has become overwhelming in the past few years. The paper looks toward the merger of these technologies in making short range 6-18 h forecasts through the use of mesoscale NWP models. A short-range (2-18 h) mesoscale forecast system envisioned for the near future is described that includes four components: hydrodynamic numerical models, large-scale and mesoscale; satellites, polar orbiting for high latitudes and geostationary for low latitudes; mesoclimatology, derived in large part from satellite data; and special-purpose simple models and empirical relations. It is important that the components of the forecast system be developed in parallel rather than in series if the system is to be completed within five years. There is enough evidence to substantiate the revolution in the mesoscale weather prediction in the next five years.

Kreitzberg, C. W.↗
NASA NTRS1982

Methods of editing cloud and atmospheric layer affected pixels from satellite data

Practical methods of computer screening cloud-contaminated pixels from data of various satellite systems are proposed. Examples are given of the location of clouds and representative landscape features in HCMM spectral space of reflectance (VIS) vs emission (IR). Methods of screening out cloud affected HCMM are discussed. The character of subvisible absorbing-emitting atmospheric layers (subvisible cirrus or SCi) in HCMM data is considered and radiosonde soundings are examined in relation to the presence of SCi. The statistical characteristics of multispectral meteorological satellite data in clear and SCi affected areas are discussed. Examples in TIROS-N and NOAA-7 data from several states and Mexico are presented. The VIS-IR cluster screening method for removing clouds is applied to a 262, 144 pixel HCMM scene from south Texas and northeast Mexico. The SCi that remain after cluster screening are sited out by applying a statistically determined IR limit.

Nixon, P. R.↗
NASA NTRS1979

Analytic studies on satellite detection of severe, two-cell tornadoes

From funnel-cloud-length interpretation, the severe tornado is characterized by peak swirl speed relative to the axis of rotation of about 90 m/s. Thermohydrodynamic achievement of the pressure deficit from ambient necessary to sustain such swirls requires that a dry, compressionally heated, non-rotating downdraft of initially tropopause-level air lie within an annulus of rapidly swirling, originally low-level air ascending on a near-moist-adiabatic locus of thermodynamic states. The two-cell structure furnishes an observable parameter possibly accessible to a passively instrumented, geosynchronous meteorological satellite with mesoscale resolution, for early detection of a severe tornado. Accordingly, the low-level turnaround region, in which the surface inflow layer separates to become a free ascending layer and for which inviscid modeling suffices, is examined quantitatively. Preliminary results indicate that swirl overshoot, i.e., swirl speeds in the turnaround region in excess of the maximum achieved in the potential vortex, is modest.

Carrier, G. F.↗
NASA NTRS1993

SSH-2 measurements of cirrus at 18-28 micrometers from the King Air during FIRE 2

In November of 1991, the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II cirrus study took place at Coffeyville, Kansas. The field experiment incorporated instrumentation from surface, aircraft, and satellite to attempt to define the optical, radiative, and microphysical characteristics of these high altitude, predominantly ice clouds. The NCAR King Air research aircraft was outfitted with a variety of radiative and microphysical instrumentation for the FIRE II project. Included for this project was the SSH-2, a 16-channel passive radiometer. The SSH-2 was originally designed as a space-qualified infrared (IR) temperature and water vapor sounder for deployment onboard the Defense Meteorological Satellite Program (DMSP) series of environmental satellites. For this experiment, only those channels associated with the water vapor profiling function have been examined although downwelling radiance measurements were taken at all channels during the project. With supporting information from the aircraft telemetry observations it may be possible to relate these SSH-2 measurements to cloud radiative and microphysical properties. The following sections will describe the spectral characteristics of the instrument, the calibration scheme used to convert the raw measured counts into calibrated radiances, and the case studies that will be covered in this paper. This will be followed by a discussion of the results of this preliminary investigation and a description of future work to be done.

Griffin, Michael K.↗
NASA NTRS1999

Incorporating TRMM and Other High-Quality Estimates into the One-Degree Daily (1DD) Global Precipitation Product

The One-Degree Daily (1DD) precipitation dataset was recently developed for the Global Precipitation Climatology Project (GPCP). The IDD provides a globally-complete, observation-only estimate of precipitation on a daily 1 deg x 1 deg grid for the period 1997 through late 1999 (by the time of the conference). In the latitude band 40 N - 40 S the IDD uses the Threshold-Matched Precipitation Index (TMPI), a GPI-like IR product with the T(sub b) threshold and (single) conditional rain rate determined locally for each month by the frequency of precipitation in the GPROF SSNU product and by the precipitation amount in the GPCP satellite-gauge (SG) combination. Outside 40 N - 40 S the 1DD uses a scaled TOVS precipitation estimate that has adjustments based on the TMPI and the SG. This first-generation 1DD has been in beta test preparatory to release as an official GPCP product. In this paper we discuss further development of the 1DD framework to allow the direct incorporation of TRMM and other high-quality precipitation estimates. First, these data are generally sparse (typically from low-orbit satellites), so a fair amount of work was devoted to data boundaries. Second, these data are not the same as the original 1DD estimates, so we had to give careful consideration to the best scheme for forcing the 1DD to sum to the SG for the month. Finally, the non-sun-synchronous, low-inclination orbit occupied by TRMM creates interesting variations against the sun-synchronous, high-inclination orbits occupied by the Defense Meteorological Satellite Program satellites that carry the SSM/I. Examples will be given of each of the development issues, then comparisons will be made to daily raingauge analyses.

Huffman, George J.↗
NASA NTRS1999

Detecting 1mm/Year Signals in Altimetric Global Sea Level: Effect of Atmospheric Water Vapor and Precipitation

Several research efforts exist to use Topography Experiment (TOPEX)/ Projet d'Observatorie de Surveillance et d'Etudes Integrees de la Dynamique des Oceans (Poseidon) (T/P) to detect changes in global sea level possibly associated with climate change. This requires much better than 1 mm/yr accuracy, something that none of the instruments in T/P [or the European Remote Sensing (ERS-2) satellite, or the U.S. Navy's Geosat Follow-On (GFO) satellite] were designed for. This work focuses on the ability of the T/P microwave radiometer (TMR) to retrieve the path delay due to atmospheric water vapor along the altimeter's path with accuracy in the time changes below 1 mm/yr on global average. In collaboration with Stephen Keihm of JPL and Christopher Ruf of Pennsylvania State University, we compared TMR path delay (PD) estimates with atmospheric precipitable water (PW) from the Special Sensor Microwave Imager (SSMI) aboard the Defense Meteorological Satellite Program (DMSP) series of satellites for 1992-1998 to selected radiosondes, and we also looked at the brightness temperatures measured by TMR in the lowest 1% of the histogram. The conclusion is that TMR had a slow instrumental drift, associated with the 18-GHz channel, which causes an approximate underestimation of water vapor at a rate equivalent to 1.2 mm/yr in path delay between 1992 and 1996; this effect stopped and no drift is detected in 1997. The same study concluded that there is no detectable scale error (one which is proportional to measured vapor) in TMR. In related work, carried out with graduate student Damien Cailliau, we investigated the relative abilities of TMR, SSMI and the UP dual-frequency radar altimeter to detect rain, relative to a climatology of shipborne observations. Rain is a crucial but poorly measured variable in studies of the climate system, and a dedicated mission, Tropical Rainfall Measuring Mission (TRMM), was recently launched to measure it. However, the climatologies built over the past 10 years used passive radiometers, such as SSMI, or infrared observation from National Oceanic and Atmospheric Administration (NOAA) geostationary satellites. We concluded that the dual-frequency altimeter does an excellent job at retrieving rain on scales much smaller than the passive radiometer, and a better job at retrieving total precipitation (rain as well as snow) at high latitudes. This work improves the sea level observations by allowing better flagging of observations contaminated by rain, and more importantly, provides an alternative way to measure rainfall over the oceans.

Zlotnicki, Victor↗
NASA NTRSDate not supplied

Machine learning based noise reduction for satellite products: application to solar-induced fluorescence retrievals using simulated and real data

In the past two decades, global satellite measurements of terrestrial chlorophyll solar-induced fluorescence (SIF) have been used widely for a number of different applications related to physiology, phenology, and productivity of plants. However, SIF retrievals are inherently noisy due to the relatively small SIF spectral signature in comparison with observational noise. In this work, we examine how a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network can be used to reduce noise and other artifacts in satellite level 2 (L2) products. We first apply the approach in a controlled environment in which radiance spectra are simulated with a full atmospheric and surface radiative transfer model for different scenarios including various SIF values that are known. Various levels of noise can be added to the simulated spectra. Resulting noisy and noise-reduced SIF retrievals are compared with the true values to assess performance. We then apply the noise reduction approach to real SIF derived from instruments flying on meteorological satellites. The results are evaluated by comparing SIF retrievals from different platforms with each other and with other independent data sets, showing enhanced capability to capture seasonal and interannual variability in SIF.

Chlorophyll fluorescence↗
NASA NTRS2007

Solutions Network Formulation Report. Reducing Light Pollution in U.S. Coastal Regions Using the High Sensitivity Cameras on the SAC-C and Aquarius/SAC-D Satellites

Light pollution has significant adverse biological effects on humans, animals, and plants and has resulted in the loss of our ability to view the stars and planets of the universe. Over half of the U.S. population resides in coastal regions where it is no longer possible to see the stars and planets in the night sky. Forty percent of the entire U.S. population is never exposed to conditions dark enough for their eyes to convert to night vision capabilities. In coastal regions, urban lights shine far out to sea where they are augmented by the output from fishing boat, cruise ship and oil platform floodlights. The proposed candidate solution suggests using HSCs (high sensitivity cameras) onboard the SAC-C and Aquarius/SAC-D satellites to quantitatively evaluate light pollution at high spatial resolution. New products modeled after pre-existing, radiance-calibrated, global nighttime lights products would be integrated into a modified Garstang model where elevation, mountain screening, Rayleigh scattering, Mie scattering by aerosols, and atmospheric extinction along light paths and curvature of the Earth would be taken into account. Because the spatial resolution of the HSCs on SAC-C and the future Aquarius/SAC-D missions is greater than that provided by the DMSP (Defense Meteorological Satellite Program) OLS (Operational Linescan System) or VIIRS (Visible/Infrared Imager/Radiometer Suite), it may be possible to obtain more precise light intensity data for analytical DSSs and the subsequent reduction in coastal light pollution.

Andrews, Jane C.↗