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At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

NASA NTRS1995

Cloud model-based simulation of spaceborne radar observations

Simulations of observations from potential spaceborne radars are made based on storm structure generated from the three-dimensional (3D) Goddard cumulus ensemble model simulation of an intense overland convective system. Five frequencies of 3, 10, 14, 35, and 95 GHz are discussed, but the Tropical Rainfall Measuring Mission precipitation radar sensor frequency (14 GHz) is the focus of this study. Radar reflectives and their attenuation in various atmospheric conditions are studied in this simulation. With the attenuation from cloud and precipitation in the estimation of reflectivity factor (dBZ), the reflectivities in the lower atmosphere in the convective cores are significantly reduced. With spatial resolution of 4 km X 4 km, attenuation at 14 GHz may cause as large as a 20-dBZ difference between the simulated measurements of the peak, Z(sub mp) and near-surface reflectivity, Z(sub ms) in the most intense convective region. The Z(sub mp) occurs at various altitudes depending on the hydrometeor concentrations and their vertical distribution. Despite the significant attenuation in the intense cores, the presence of the rain maximum is easily detected by using information of Z(sub mp). In the stratiform region, the attenuation is quite limited (usually less than 5 dBZ), and the reduction of reflectivity is mostly related to the actual vertical structure of cloud distribution. Since Z(sub ms) suffers severe attenuation and tends to underestimate surface rainfall intensity in convective regions. Z(sub mp) can be more representative for rainfall retrieval in the lower atmosphere in these regions. In the stratiform region where attenuation is negligible, however, Z(sub mp) tends to overestimate surface rainfall and Z(sub ms) is more appropriate for rainfall retrieval. A hybrid technique using a weight between the two rain intensities is tested and found potentially usefull for future applications. The estimated surface rain-rate map based on this hybrid approach captures many of the details of the cloud model rain field but still slightly underestimates the rain-rate maximum.

Yeh, H.-Y. M.↗

NASA NTRS2017

Lightning Imaging Sensor (LIS) on the International Space Station (ISS): Launch, Installation, Activation and First Results

Mission: Fly a flight-spare LIS (Lightning Imaging Sensor) on ISS to take advantage of unique capabilities provided by the ISS (e.g., high inclination, real time data); Integrate LIS as a hosted payload on the DoD Space Test Program-Houston 5 (STP-H5) mission and launch on a Space X rocket for a minimum 2 year mission. Measurement: NASA and its partners developed and demonstrated effectiveness and value of using space-based lightning observations as a remote sensing tool; LIS measures lightning (amount, rate, radiant energy) with storm scale resolution, millisecond timing, and high detection efficiency, with no land-ocean bias. Benefit: LIS on ISS will extend TRMM (Tropical Rainfall Measuring Mission) time series observations, expand latitudinal coverage, provide real time data to operational users, and enable cross-sensor calibration.

LIS↗

NASA NTRSDate not supplied

Assessing Environmental and Socioeconomic Factors of Urban Flood Vulnerability in Kansas City, Kansas

Pluvial flooding, over-saturated ground, and drainage systems disproportionately impact historically marginalized urban neighborhoods during extreme rainfall events. These communities are impacted by physical and socioeconomic factors that make them vulnerable to flooding events, such as high concentrations of impervious landcover, high precipitation rates, and a combined sewer system framework. Despite known vulnerability to environmental hazards, understanding potential pluvial street-level flooding events are largely unknown. Using the open-source National Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation model, NASA DEVELOP examined neighborhood scale runoff retention and potential economic damages for risk mapping throughout Kansas City, Kansas. The generated outputs aid in identifying vulnerable neighborhoods susceptible to flooding and in need of future intervention. Previous studies have applied this model framework to understand urban flood vulnerability regarding ecosystem services, urban planning, and flood mitigation strategies. We utilized the InVEST outputs to develop indices pertaining to environmental justice factors of race, socioeconomic status, social vulnerability, and health. The findings indicate that historically redlined neighborhoods in Kansas City, Kansas face disproportional impacts from flood events and are subject to greater environmental stressors. This research provides an approach to utilizing an open-source flood vulnerability model to empower neighborhood-scale environmental justice analysis, enhancing the local communities' understanding of present-day impacts of historical environmental injustices.

Hadwynne Gross↗

DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A North Atlantic synthetic tropical cyclone tracks, intensity, and rainfall dataset

Tropical Cyclones (TCs) cause significant socio-economic damages to the US and Caribbean coastal regions annually, making it important to understand TC risk at the local-to-regional scales where their impacts are most prominent. However, the short length of the observed record and the substantial computational expense associated with high-resolution climate models make it difficult to assess TC risk using either approach. To overcome these challenges, we developed a database of synthetic TCs using the Risk Analysis Framework for Tropical Cyclones (RAFT). The database includes 50,000 synthetic TC tracks, along-track intensities and storm-induced precipitation. TC tracks generated in RAFT are in reasonable agreement with observations for spatial distribution of TC tracks and basin-scale distributions of TC translation speeds, lifetime maximum intensities and intensification rates. Also, spatial variations in coastal frequency and precipitation for landfalling TCs are well-reproduced in RAFT. In summary, the synthetic TC database based on RAFT provides a reasonable pathway for robust assessment of TC wind and rainfall risk for the US coastal regions and other areas affected by Atlantic TCs.

Xu, Wenwei↗

NASA NTRS1990

Time scales and variability of area-averaged tropical oceanic rainfall

A statistical analysis of time series of area-averaged rainfall over the oceans has been conducted around the diurnal time scale. The results of this analysis can be applied directly to the problem of establishing the magnitude of expected errors to be incurred in the estimation of monthly area-averaged rain rate from low orbiting satellites. Such statistics as the mean, standard deviation, integral time scale of background red noise, and spectral analyses were performed on time series of the GOES precipitation index taken at 3-hour intervals during the period spanning December 19, 1987 to March 31, 1988 over the central and eastern tropical Pacific. The analyses have been conducted on 2.5 x 2.5 deg and 5 x 5 deg grid boxes, separately. The study shows that rainfall measurements by a sun-synchronous satellite visiting a spot twice per day will include a bias due to the existence of the semidiurnal cycle in the SPCZ ranging from 5 to 10 percentage points. The bias in the ITCZ may be of the order of 5 percentage points.

Shin, Kyung-Sup↗

NASA NTRS2010

Relating Convective and Stratiform Rain to Latent Heating

The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate-high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.58 horizontal resolution, the occurrence of conditional rain rates over 100 mm/day is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations. An improved convective-stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.

Tao, Wei-Kuo↗

NASA NTRS2003

Uniting Space, Ground and Underwater Measurements for Improved Estimates of Rain Rate

Global precipitation is monitored from a variety of platforms including space-borne, ground- and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.

Amitai, E.↗

NASA NTRS2002

Evaluation of Improvements to the TRMM Microwave Rain Algorithm

Improvements made to the Version 5 TRMM passive microwave rain retrieval algorithm (2A-12) are evaluated using independent data. Surface rain rate estimates from the Version 5 TRMM TMI (2A-12), PR (2A-25) and TMI/PR Combined (2B-31) algorithms and ground-based radar estimates for selected coincident subset datasets in 1998 over Melbourne and Kwajalein show varying degrees of agreement. The surface rain rates are then classified into convective and stratiform rain types over ocean, land, and coastal areas for more detailed comparisons to the ground radar measurements. These comparisons lead to a better understanding of the relative performances of the current TRMM rain algorithms. For example, at Melbourne more than 80% of the radar-derived rainfall is classified as convective rain. Convective rain from the TRMM rain algorithms is less than that from ground radar measurements, while TRMM stratiform rain is much greater. Rain area coverage from 2A-12 is also in reasonable agreement with ground radar measurements, with about 25% more over ocean and 25% less over land and coastal areas. Retrieved rain rates from the improved (Version 6) 2A-12 algorithm will be compared to 2A-25, 2B-31, and ground-based radar measurements to evaluate the impact of improvements to 2A-12 in Version 6. An important improvement to the Version 6 2A-12 algorithm is the retrieval of Q1/Q2 (latent heating/drying) profiles in addition to the surface rain rate and hydrometeor profiles. In order to ascertain the credibility of the new products, retrieved Q1/Q2 profiles are compared to independent ground-based estimates. Analyses of dual-Doppler radar data in conjunction with coincident rawinsonde data yield estimates of the vertical distributions of diabatic heating/drying at high horizontal resolution for selected cases over the Kwajalein and LBA field sites. The estimated vertical heating/drying structures appear to be reasonable. Comparisons of Q1/Q2 profiles from Version 6 2A-12 and the ground-based estimates are in progress. Retrieved Q1/Q2 structures will also be compared to MM5 hurricane simulations for selected cases. The results of these intercomparisons will be presented at the conference.

Yang, Song↗

NASA NTRS2005

The Tropical Convective Spectrum: Archetypal Vertical Structures - Part 1

A taxonomy of tropical convective and stratiform vertical structures is constructed through cluster analysis of 3 yr of Tropical Rainfall Measuring Mission (TRMM) "warm-season" (surface temperature greater than 10 C) precipitation radar (PR) vertical profiles, their surface rainfall, and associated radar-based classifiers (convective/ stratiform and brightband existence). Twenty-five archetypal profile types are identified, including nine convective types, eight stratiform types, two mixed types, and six anvil/fragment types (nonprecipitating anvils and sheared deep convective profiles). These profile types are then hierarchically clustered into 10 similar families, which can be further combined, providing an objective and physical reduction of the highly multivariate PR data space that retains vertical structure information. The taxonomy allows for description of any storm or local convective spectrum by the profile types or families. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/ stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types are presented, demonstrating primary rainfall contribution by midlevel glaciated convection (27%) and similar depth decaying/stratiform stages (28%-31%). Profiles of these types exhibit similar 37- and 85-GHz passive microwave brightness temperatures but differ greatly in their frequency of occurrence and mean rain rates, underscoring the importance to passive microwave rain retrieval of convective/stratiform discrimination by other means, such as polarization or texture techniques, or incorporation of lightning observations. Close correspondence is found between deep convective profile frequency and annualized lightning production, and pixel-level lightning occurrence likelihood directly tracks the estimated mean ice water path within profile types.

Precipitation radar↗

NASA NTRS1983

Simultaneous ocean cross-section and rainfall measurements from space with a nadir pointing radar

A modified version of the surface-target-attenuation radar described by Meneghini et al. (1983) is proposed which permits simultaneous measurement of ocean radar cross sections and path-average rain rates using a nadir-pointing satellite-borne microwave radar. The basic concept is explained and illustrated; the equations describing the data reduction are derived; some preliminary numerical computations based on a 7.5-m-diameter 10-kW 1.33-microsec-pulse radar operating at 1.87 cm from an altitude of 500 km are performed; and the major error sources (mismatches between rain scattering volumes and additional multipath contributions) and limitations (nadir pointing) are discussed. It is suggested that the system could provide a nadir calibration for wide-swath observing systems such as scanning microwave radiometers.

Atlas, D.↗

DOE OSTI2021

Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to 9 % K - 1 in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Science & Technology - Other Topics↗

NASA NTRS1992

Space network interoperability panel (SNIP) study

The history and status of the SNIP study conducted by NASA, ESA, and NASDA are reviewed. Particular attention is given to data relay systems development plans; agency load situations; cross support; the top managers agreement about implementation of S-band interoperability and accelerating the K-alpha band high data rate exploration; testing of actual systems; NASA interim architecture for an S-band era system to make NASA spacecraft and TDRSS/TDRS-II compatible with ESA and NASDA systems; tropical rainfall measuring mission support; S-band cross support; and K-alpha band status.

Fahnestock, Dale↗

NASA NTRS1994

A probability distribution model for rain rate

A systematic approach is suggested for modeling the probability distribution of rain rate. Rain rate, conditional on rain and averaged over a region, is modeled as a temporally homogeneous diffusion process with appropiate boundary conditions. The approach requires a drift coefficient-conditional average instantaneous rate of change of rain intensity-as well as a diffusion coefficient-the conditional average magnitude of the rate of growth and decay of rain rate about its drift. Under certain assumptions on the drift and diffusion coefficients compatible with rain rate, a new parametric family-containing the lognormal distribution-is obtained for the continuous part of the stationary limit probability distribution. The family is fitted to tropical rainfall from Darwin and Florida, and it is found that the lognormal distribution provides adequate fits as compared with other members of the family and also with the gamma distribution.

Kedem, Benjamin↗

NASA NTRS2004

Multivariate Statistical Inference of Lightning Occurrence, and Using Lightning Observations

Two classes of multivariate statistical inference using TRMM Lightning Imaging Sensor, Precipitation Radar, and Microwave Imager observation are studied, using nonlinear classification neural networks as inferential tools. The very large and globally representative data sample provided by TRMM allows both training and validation (without overfitting) of neural networks with many degrees of freedom. In the first study, the flashing / or flashing condition of storm complexes is diagnosed using radar, passive microwave and/or environmental observations as neural network inputs. The diagnostic skill of these simple lightning/no-lightning classifiers can be quite high, over land (above 80% Probability of Detection; below 20% False Alarm Rate). In the second, passive microwave and lightning observations are used to diagnose radar reflectivity vertical structure. A priori diagnosis of hydrometeor vertical structure is highly important for improved rainfall retrieval from either orbital radars (e.g., the future Global Precipitation Mission "mothership") or radiometers (e.g., operational SSM/I and future Global Precipitation Mission passive microwave constellation platforms), we explore the incremental benefit to such diagnosis provided by lightning observations.

Boccippio, Dennis↗

DOE OSTI2025

Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE)

A neural network (NN) surrogate of the NASA GISS ModelE atmosphere (version E3) is trained on a perturbed parameter ensemble (PPE) spanning 45 physics parameters and 36 outputs. The NN is leveraged in a Markov Chain Monte Carlo (MCMC) Bayesian parameter inference framework to generate a second posterior constrained ensemble coined a “calibrated physics ensemble,” or CPE. The CPE members are characterized by diverse parameter combinations and are, by definition, close to top-of-atmosphere radiative balance, and must broadly agree with numerous hydrologic, energy cycle and radiative forcing metrics simultaneously. Global observations of numerous cloud, environment, and radiation properties (provided by global satellite products) are crucial for CPE generation. The inference framework explicitly accounts for discrepancies (or biases) in satellite products during CPE generation. We demonstrate that product discrepancies strongly impact calibration of important model parameter settings (e.g., convective plume entrainment rates; fall speed for cloud ice). Structural improvements new to E3 are retained across CPE members (e.g., stratocumulus simulation). Notably, the framework improved the simulation of shallow cumulus and Amazon rainfall while not degrading radiation fields, an upgrade that neither default parameters nor Latin Hypercube parameter searching achieved. Analyses of the initial PPE suggested several parameters were unimportant for output variation. However, many “unimportant” parameters were needed for CPE generation, a result that brings to the forefront how parameter importance should be determined in PPEs. From the CPE, two diverse 45-dimensional parameter configurations are retained to generate radiatively-balanced, auto-tuned atmospheres that were used in two E3 submissions to CMIP6.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Hydrology team

General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.

Ragan, R.↗

NASA NTRS2015

Projections of Rapidly Rising Temperatures over Africa Under Low Mitigation

An analysis of observed trends in African annual-average near-surface temperatures over the last five decades reveals drastic increases, particularly over parts of the subtropics and central tropical Africa. Over these regions, temperatures have been rising at more than twice the global rate of temperature increase. An ensemble of high-resolution downscalings, obtained using a single regional climate model forced with the sea-surface temperatures and sea-ice fields of an ensemble of global circulation model (GCM) simulations, is shown to realistically represent the relatively strong temperature increases observed in subtropical southern and northern Africa. The amplitudes of warming are generally underestimated, however. Further warming is projected to occur during the 21st century, with plausible increases of 4-6 C over the subtropics and 3-5 C over the tropics by the end of the century relative to present-day climate under the A2 (a low mitigation) scenario of the Special Report on Emission Scenarios. High impact climate events such as heat-wave days and high fire-danger days are consistently projected to increase drastically in their frequency of occurrence. General decreases in soil-moisture availability are projected, even for regions where increases in rainfall are plausible, due to enhanced levels of evaporation. The regional downscalings presented here, and recent GCM projections obtained for Africa, indicate that African annual-averaged temperatures may plausibly rise at about 1.5 times the global rate of temperature increase in the subtropics, and at a somewhat lower rate in the tropics. These projected increases although drastic, may be conservative given the model underestimations of observed temperature trends. The relatively strong rate of warming over Africa, in combination with the associated increases in extreme temperature events, may be key factors to consider when interpreting the suitability of global mitigation targets in terms of African climate change and climate change adaptation in Africa.

climate change↗