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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.

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NASA NTRS1975

Asynoptic meteorological data assimilation by means of a time coordinate transformation

A possible method for assimilating large quantities of asynoptic data, such as satellite observations, into numerical weather forecasts, is investigated. The method is based on a transformation of the time coordinate to coincide with satellite paths, and a well-posed problem is solved in order to obtain forecasts beyond the time of data acquisition. Simulated barotropic forecasts based on the proposed technique are compared with forecasts derived from the direct insertion of data. Results indicate that only in ideal situations, when asynoptic data are obtained both continuosly and accurately, will the method function well as compared with direct insertion techniques.

Halberstam, I.↗
NASA NTRS1975

SEASAT economic assessment. Volume 2: The SEASAT system description and performance

Results are presented of preliminary trade-off studies of operational SEASAT systems. The trade-off studies were used as the basis for the estimation of costs and net benefits of the operational SEASAT system. Also presented are the preliminary results of simulation studies that were designed to lead to a measure of the impact of SEASAT data through the use of numerical weather forecast models.

Source record↗
NASA NTRS1975

Interactive image processing for meteorological applications at NASA/Goddard Space Flight Center

The meteorological data processing program at the space center is centered on the analysis of geostationary satellite data. Its objectives are to detect and predict severe storms, to improve short range and long range global numerical weather forecasting models, and to develop improved satellite systems. The Image Display and Manipulation System (IDAMS) for earth resources satellite data processing is described, as is the special purpose software package, METPAK, for performing meteorology operations on IDAMS. The Atmospheric and Oceanographic Information Processing System (AOIPS), a dual terminal multiprocessor is also described.

Billingsley, J. B.↗
NASA NTRS1983

Analysis of cloud characteristics derived from archived satellite data

The present investigation is concerned with the differing scientific user community requirements for cloud data and the nature of archived satellite data. It is concluded that information on cloud characteristics and cloud cover is of the utmost importance for at least three scientific research areas, viz. numerical weather forecasting, environmental remote sensing, and climatic monitoring and modelling. However, these three user groups require information at different levels of temporal and spatial resolution, and the nature of the comparison between surface and satellite assessment of cloud cover differs among the three groups. Taking into account the diverse requirements of the scientific community and difficulty of a mutually agreed definition of the cloud parameters, a number of recommendations are made. It is suggested that radiance data, not cloud data, should be archived directly from satellite observations, and that the highest spatial and temporal resolutions available should be retained in the archive.

Hughes, N. A.↗
NASA NTRS1989

The computation of generalized cross-validation functions through householder tridiagonalization with applications to the fitting of interaction spline models

An efficient algorithm for computing the generalized cross-validation function for the general cross-validated regularization/smoothing problem is provided. This algorithm is appropriate for problems where no natural structure is available, and the regularization/smoothing problem is solved (exactly) in a reproducing kernel Hilbert space. It is particularly appropriate for certain multivariate smoothing problems with irregularly spaced data, and certain remote sensing problems, such as those that occur in meteorology, where the sensors are arranged irregularly. The algorithm is applied to the fitting of interaction spline models with irregularly spaced data and two smoothing parameters; favorable timing results are presented. The algorithm may be extended to the computation of certain generalized maximum likelihood (GML) functions. Application of the GML algorithm to a problem in numerical weather forecasting, and to a broad class of hypothesis testing problems, is noted.

Gu, Chong↗
NASA NTRS1990

NASA/MSFC FY90 Global Scale Atmospheric Processes Research Program Review

Research supported by the Global Atmospheric Research Program at the Marshall Space Flight Center on atmospheric remote sensing, meteorology, numerical weather forecasting, satellite data analysis, cloud precipitation, atmospheric circulation, atmospheric models and related topics is discussed.

Leslie, Fred W.↗
NASA NTRS1998

Capacitively Stabilized Etalon Technology for Spaceborne Wind Lidar Application

Global monitoring by satellites is important for many types of environmental studies. Among these, the wind field is the single most important atmospheric state variable required for understanding atmospheric motion and predicting weather. Studies indicate that a global determination of the tropospheric wind field to an accuracy of 1-5 m/sec is critical for improved numerical weather forecasting. This measurement could be carried out with a spaceborne lidar system sensing the Doppler shift of a laser signal backscattered from the atmosphere. Over the past four years we have developed a ground-based Edge Technique lidar system and demonstrated wind measurements through the troposphere with high accuracy (1-6 m/s) and high spatial resolution. Recently, we began the design of a shuttle based wind measurement system for technology demonstration as part of the Zephyr program. In this paper, we present the characteristics of the high spectral resolution etalon filter technology for lidar wind measurement with the Edge Technique. In conclusion, a spacecraft motion compensation method has been discussed. We demonstrated experimentally that the etalon can be tuned to compensate for any satellite induced Doppler shift to an accuracy of better than 0.6 m/s over a time period of 2.5 ms.

Li, Steven X.↗
NASA NTRS2001

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Kakar, Ramesh↗
NASA NTRS2001

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by 1 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5 %) and +/- 5.0 K (+/- 15 %), respectively. At a given tropospheric level, such perturbations can cause a +/- 25 % variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2002

Improving Environmental Prediction Using Rainfall Observations from Space

I discuss the need for accurate rainfall observations to improve our knowledge of the atmospheric state and the ability to provide better numerical weather forecasts. I will give an overview of the recent progress in using rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and shortrange forecasts. In cases of Hurricanes Bonnie and Floyd, results show that assimilation of TRMM and SSM/I rain rates produces initial conditions with better defined tropical storm features that lead to better Hurricane track and quantitative precipitation forecasts. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Hou, Arthur Y.↗
NASA NTRS2002

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2008

Effect of GOES-R Image Navigation and Registration Errors on Atmospheric Motion Vectors

High temporal frequency imagery from geostationary satellites allows for the continuous monitoring of rapidly changing atmospheric constituents such as smoke, dust, water vapor and clouds. The image sequences are often used to quantify the displacement of image features such as water vapor and clouds to produce atmospheric motion vectors (AMVs) which are used as diagnostic tools and also assimilated into numerical weather forecast models. The basic principle behind the determination of AMVs is the calculation of the physical displacement of features from one image (time) to the next. This process assumes that the features being tracked do not change as a function of time, usually requiring the use of short time interval imagery to minimize substantial change in size and shape of the features being tracked. High spatial resolution imagery also is required for reliable feature identification. While these image resolution and temporal sampling requirements often provide major drivers for space-based instrument design requirements, accurate image navigation and registration, INn (between a sequence of images), is also critical to the derivation of useful AMVs. In this paper and poster to be presented at the conference, the image navigation and registration (INR) accuracy expected for the Advanced Baseline Imager (ABI) on the GOES-R series of satellites will be discussed in light of its impact on AMV accuracy. Significant satellite platform and modeling enhancements are planned which should significantly improve INn performance of the GOES-R instruments. Some of these improvements have been demonstrated for the GOES-13 satellite which was launched in summer of 2006. An analysis of GOES-13 INR data, from the special satellite check out period, will be used in the assessment.

Jedlovec, Gary↗
NASA NTRS2011

Hyperspectral Remote Sensing of Atmosphere and Surface Properties

Atmospheric Infrared Sounder (AIRS), Infrared Atmospheric Sounding Interferometer (IASI), and Cross-track Infrared Sounder (CrIS) are all hyper-spectral satellite sensors with thousands of spectral channels. Top of atmospheric radiance spectra measured by these sensors contain high information content on atmospheric, cloud, and surface properties. Exploring high information content contained in these high spectral resolution spectra is a challenging task due to computation e ort involved in modeling thousands of spectral channels. Usually, only very small fractions (4{10 percent) of the available channels are included in physical retrieval systems or numerical weather forecast (NWP) satellite data assimilations. We will describe a method of simultaneously retrieving atmospheric temperature, moisture, cloud, and surface properties using all available spectral channels without sacrificing computational speed. The essence of the method is to convert channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Because the EOFs are orthogonal to each other, about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) developed at NASA Langley Research Center is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. There is no need to perform EOF transformations to convert super channels back to spectral space at each iteration step for a one-dimensional variational retrieval or a NWP data assimilation system. The PCRTM forward model is also capable of calculating radiative contributions due to multiple-layer clouds. The multiple scattering effects of the clouds are efficiently parameterized. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance matrices and a priori information as constraints. One advantage of this approach is that it uses all information content from the hyper-spectral data so that the retrieval is less sensitive to instrument noise and eliminates the need for selecting a sub-set of the channels.

Liu, Xu↗
NASA NTRS2011

Observations During GRIP from HIRAD: Ocean Surface Wind Speed and Rain Rate

HIRAD (Hurricane Imaging Radiometer) flew on the WB-57 during NASA's GRIP (Genesis and Rapid Intensification Processes) campaign in August - September of 2010. HIRAD is a new C-band radiometer using a synthetic thinned array radiometer (STAR) technology to obtain cross-track resolution of approximately 3 degrees, out to approximately 60 degrees to each side of nadir. By obtaining measurements of emissions at 4, 5, 6, and 6.6 GHz, observations of ocean surface wind speed and rain rate can be inferred. This technique has been used for many years by precursor instruments, including the Stepped Frequency Microwave Radiometer (SFMR), which has been flying on the NOAA and USAF hurricane reconnaissance aircraft for several years. The advantage of HIRAD over SFMR is that HIRAD can observe a +/- 60-degree swath, rather than a single footprint at nadir angle. Results from the flights during the GRIP campaign will be shown, including images of brightness temperatures, wind speed, and rain rate. To the extent possible, comparisons will be made with observations from other instruments on the GRIP campaign, for which HIRAD observations are either directly comparable or are complementary. Potential impacts on operational ocean surface wind analyses and on numerical weather forecasts will also be discussed.

Miller, Timothy L.↗
NASA NTRS2005

Contour Error Map Algorithm

The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.

Merceret, Francis↗
NASA NTRS2012

Observations During GRIP from HIRAD: Images of C-Band Brightness Temperatures and Ocean Surface Wind Speed and Rain Rate

HIRAD (Hurricane Imaging Radiometer) flew on the WB-57 during NASA s GRIP (Genesis and Rapid Intensification Processes) campaign in August - September of 2010. HIRAD is a new C-band radiometer using a synthetic thinned array radiometer (STAR) technology to obtain cross-track resolution of approximately 3 degrees, out to approximately 60 degrees to each side of nadir. By obtaining measurements of emissions at 4, 5, 6, and 6.6 GHz, observations of ocean surface wind speed and rain rate can be inferred. This technique has been used for many years by precursor instruments, including the Stepped Frequency Microwave Radiometer (SFMR), which has been flying on the NOAA and USAF hurricane reconnaissance aircraft for several years. The advantage of HIRAD over SFMR is that HIRAD can observe a +/- 60-degree swath, rather than a single footprint at nadir angle. Results from the flights during the GRIP campaign will be shown, including images of brightness temperatures, wind speed, and rain rate. To the extent possible, comparisons will be made with observations from other instruments on the GRIP campaign, for which HIRAD observations are either directly comparable or are complementary. Features such as storm eye and eyewall, location of vortex wind and rain maxima, and indications of dynamical features such as the merging of a weaker outer wind/rain maximum with the main vortex may be seen in the data. Potential impacts on operational ocean surface wind analyses and on numerical weather forecasts will also be discussed.

Miller, Timothy L.↗
NASA NTRS2011

180-GHz Interferometric Imager

A 180-GHz interferometric imager uses compact receiver modules, combined high- and low-gain antennas, and ASIC (application specific integrated circuit) correlator technology, enabling continuous, all-weather observations of water vapor with 25-km resolution and 0.3-K noise in 15 minutes of observation for numerical weather forecasting and tropical storm prediction. The GeoSTAR-II prototype instrument is broken down into four major subsystems: the compact, low-noise receivers; sub-array modules; IF signal distribution; and the digitizer/correlator. Instead of the single row of antennas adopted in GeoSTAR, this version has four rows of antennas on a coarser grid. This dramatically improves the sensitivity in the desired field of view. The GeoSTAR-II instrument is a 48-element, synthetic, thinned aperture radiometer operating at 165-183 GHz. The instrument has compact receivers integrated into tiles of 16 elements in a 4x4 arrangement. These tiles become the building block of larger arrays. The tiles contain signal distribution for bias controls, IF signal, and local oscillator signals. The IF signals are digitized and correlated using an ASIC correlator to minimize power consumption. Previous synthetic aperture imagers have used comparatively large multichip modules, whereas this approach uses chip-scale modules mounted on circuit boards, which are in turn mounted on the distribution manifolds. This minimizes the number of connectors and reduces system mass. The use of ASIC technology in the digitizers and correlators leads to a power reduction close to an order of magnitude.

Kangaslahti, Pekka P.↗
NASA NTRS2012

Observations of C-band Brightness Temperatures and Ocean Surface Wind Speed and Rain Rate from the Hurricane Imaging Radiometer (HIRAD)

HIRAD flew on the WB-57 over Earl and Karl during NASA s GRIP (Genesis and Rapid Intensification Processes) campaign in August - September of 2010. HIRAD is a new Cband radiometer using a synthetic thinned array radiometer (STAR) technology to obtain cross-track resolution of approximately 3 degrees, out to approximately 60 degrees to each side of nadir. (The resulting swath width for a platform at 60,000 feet is roughly 60 km, and resolution for most of the swath is around 2 km.) By obtaining measurements of emissions at 4, 5, 6, and 6.6 GHz, observations of ocean surface wind speed and rain rate can be retrieved. This technique has been used for many years by precursor instruments, including the Stepped Frequency Microwave Radiometer (SFMR), which has been flying on the NOAA and USAF hurricane reconnaissance aircraft for several years to obtain observations within a single footprint at nadir angle. Results from the flights during the GRIP campaign will be shown, including images of brightness temperatures, wind speed, and rain rate. Comparisons will be made with observations from other instruments on the GRIP campaign, for which HIRAD observations are either directly comparable or are complementary. Features such as storm eye and eyewall, location of storm wind and rain maxima, and indications of dynamical features such as the merging of a weaker outer wind/rain maximum with the main vortex may be seen in the data. Potential impacts on operational ocean surface wind analyses and on numerical weather forecasts will also be discussed.

Miller, Timothy L.↗