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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Continuous measurement of nontidal variations of gravity

Records from seven superconducting gravimeters operated at five different locations in California and one in Boulder, CO, are examined after removal of tides and the gravitational attraction of the atmosphere. Fluctuations over periods between a few days and several months were observed at all sites with peak amplitudes of order 10 microgal. By contrast, a 640-day record obtained with one of the instruments in Germany showed peak fluctuations of only 2 microgal. In most of the records the causes of these aperiodic variations were not determined so that they serve to set limits on the vertical motion or displacement of mass at the respective locations. However, at The Geysers geothermal field, much of the gravity variation is correlated with seismic activity, reinjection rate, and rainfall. Measurements of this type were not possible prior to the development of the superconducting device. Consequently, these results provide the first evidence for the existence of gravity variations on the time scale and of the magnitude described here. Vertical crustal motion, motion related to seismic events, and hydrological phenomena can lead to variations on this scale. Unambiguous identification of causal relationships will require either special circumstances such as found at The Geysers or operation of the instruments in pairs.

Goodkind, John M.↗
NASA NTRS1992

Spaceborne Radar Would Measure Rain And Clouds

Report describes conceptual design of spaceborne radar system mapping precipitation and clouds at mid-latitudes to provide data for research on global weather and climate. Radar operates at two frequencies. Lower (35 GHz) provides vertical profiles of rainfall at rates up to 20 mm/h and enables probing of cirrus clouds. Higher (94 GHz) enables detection and quantitative measurements of clouds of all types and provides rain profiles at rates up to 10 mm/h.

Im, Eastwood↗
NASA NTRS1993

Estimating the path-average rainwater content and updraft speed along a microwave link

There is a scarcity of methods for accurately estimating the mass of rainwater rather than its flux. A recently proposed technique uses the difference between the observed rates of attenuation A with increasing distance at 38 and 25 GHz, A(38-25), to estimate the rainwater content W. Unfortunately, this approach is still somewhat sensitive to the form of the drop-size distribution. An alternative proposed here uses the ratio A38/A25 to estimate the mass-weighted average raindrop size Dm. Rainwater content is then estimated from measurements of polarization propagation differential phase shift (Phi-DP) divided by (1-R), where R is the mass-weighted mean axis ratio of the raindrops computed from Dm. This paper investigates these two water-content estimators using results from a numerical simulation of observations along a microwave link. From these calculations, it appears that the combination (R, Phi-DP) produces more accurate estimates of W than does A38-25. In addition, by combining microwave estimates of W and the rate of rainfall in still air with the mass-weighted mean terminal fall speed derived using A38/A25, it is possible to detect the potential influence of vertical air motion on the raingage-microwave rainfall comparisons.

Jameson, Arthur R.↗
NASA NTRS1994

SSM/I Rainfall Volume Correlated with Deepening Rate in Extratropical Cyclones

With the emergence of reasonably robust, physically based rain rate algorithms designed for the Special Sensor Microwave/Imager (SSM/I), a unique opportunity exists to directly observe a physical component which can contribute to or be a signature of cyclone deepening (latent heat release). The emphasis of the research in this paper is to seek systematic differences in rain rate observed by the SSM/I, using the algorithm of Petty in cases of explosive and nonexplosive cyclone deepening.

Petty, Grant W.↗
NASA NTRS2022

Stability of the Dual-Frequency Radar Equations and a New Method Applied to the GPM’s Dual-Frequency Precipitation Radar (DPR) Data

A new algorithm is proposed that estimates two parameters of the particle size distribution (PSD) at each range bin from the Global Precipitation Measurement’s (GPM’s) Dual-frequency Precipitation Radar data. The equation that expresses the relationship of the PSD parameters between adjacent range bins is derived. By including the attenuation effect within the bin in the discretized equation, the new algorithm alleviates the double-solution problem when attenuation within the bin is sufficiently large. The stability of the solutions to the equation depends on the value of the mean diameter D(sub m) and its gradient with respect to range in the case of liquid precipitation. If the critical diameter above which the dual-frequency ratio (DFR) of radar reflectivity factors becomes a monotonically increasing function of D(sub m), the backward processing of the equation provides a stable or moderately diverging solution, unlike the forward processing that often gives unstable solutions. To provide a set of initial conditions without using the surface reference technique (SRT) in the backward processing, an initialization method using the Hitschfeld-Bordan attenuation correction method is proposed and tested. The proposed algorithm may provide a tool for investigating the assumptions used in various algorithms.

GPM↗
NASA NTRSDate not supplied

Medium-Range River Flood Forecasts Using a Long Short-Term Memory Network

River flooding and the impacts are a concern for decision makers throughout the United States. Accurate medium-range forecasts (~3-7 days) are critical for providing advanced outlooks to emergency management officials. Unfortunately, accurately forecasting rainfall-runoff and the subsequent rise and fall within rivers remain a challenge in hydrological modeling. While complex physical modeling systems are the standard for representing the hydrological processes, they are computationally demanding and can require extensive calibration. Further, uncertainties remain in the model parameters and input data. The use of machine learning can reduce some of the computational demand while maintaining high accuracy. Therefore, this project makes use of a Long Short-Term Memory (LSTM) network which explicitly accounts for the time-dependent nature of rainfall-runoff modeling. The developed LSTM was trained to predict river gauge height, or stage height, based on time-lagged input features which include: gauge height to initialize the model, the NASA Short-term Prediction Research and Transition Center’s instance of the Land Information System (SPoRT-LIS) relative soil moisture to describe the rainfall infiltration rate, and 6-hr Multi-Radar Multi-Sensor quantitative precipitation estimate (MRMS QPE). The developed LSTM based system is then used to produce 7-day forecasts with a 6-hr temporal resolution using three different quantitative precipitation forecasts (QPF) from the NWS’s Weather Prediction Center (WPC), the NCEP Global Forecast System (GFS) model and the National Blend of Models (NBM). This trained modeling system has been implemented as an experimental product at over 100 different rivers in collaboration with at multiple National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC) across the eastern half of the United States. The developed LSTM model achieved average Nash-Sutcliffe efficiency (NSE) 0.89 higher than the equivalent medium-range National Water Model ensemble member forecast over a 7-day forecast. In addition to the initial development and evaluation, this project has continued to expand. While the initial model was developed for precipitation dominated basins, expansion of the project has taken it to basins effected by snow melt. This presentation will provide an overview of the project with focus on recent developments on incorporating snow melt processes into the model.

Andrew T. White↗
NASA NTRS1958

A Flight Evaluation and Analysis of the Effect of Icing Conditions on the ZPG-2 Airship

A series of test flights was conducted by the U. S. Navy over a 3- year period to evaluate the effects of icing on the operation of the ZPG-2 airship. In supercooled. clouds, ice formed only on the forward edges of small protuberances and wires and presented no serious hazard to operation. Ice accretions of the glaze type which occurred in conditions described as freezing drizzle adversely affected various components to a somewhat greater extent. The results indicated, a need for protection of certain components such as antennas, propellers, and certain parts of the control system. The tests showed that icing of the large surface of the envelope occurred only in freezing rain or drizzle. Because of the infrequent occurrence of these conditions, the potential maximum severity could not be estimated from the test results. The increases in heaviness caused by icing in freezing rain and drizzle were substantial, but well within the operational capabilities of the airship. In order to estimate the potential operational significance of icing in freezing rain, theoretical calculations were used to estimate: (1) the rate of icing as a function of temperature and rainfall intensity, (2) the climatological probability of occurrence of various combinations of these variables, and (3) the significance of the warming influence of the ocean in alleviating freezing-rain conditions. The results of these calculations suggest that, although very heavy icing rates are possible in combinations of low temperature and high rainfall rate, the occurrence of such conditions is very infrequent in coastal areas and virtually impossible 200 or 300 miles offshore.

Lewis, Willilam↗
NASA NTRS1986

Characteristics of precipitation regimes during the global weather experiment

Rainfall data were used in conjunction with heating rate values obtained from GLA/NASA to describe large scale heating changes and concurrent circulation fluctuations for weekly averages during the Special Observing Period I (January-March 1979) of the Global Weather Experiment. The GLA diabatic heating rates were obtained as residues of the thermodynamic energy equation during the four-dimensional data assimilation cycle (as described by Kalnay and Baker, 1984). In week one, the heating and rainfall rate profiles display a positive anomaly on the West Pacific in both fields. The anomaly appears to propagate eastward into the East Pacific and South America by the fifth week. By the week four, the negative anomaly over the Indian Ocean becomes positive. These heating patterns are reflected on positive divergent anomalies at 200 mb analyzed for the same periods. The stream-function anomalies display anticyclonic circulations over the heating anomalies.

Ahrens, Glen D.↗
NASA NTRS1997

Rainfall Estimation Over Tropical Oceans: Area Average Rain Rate - 1

Multichannel dual polarization microwave radiometer SSM/I observations over oceans do not contain sufficient information to differentiate quantitatively the rain from other hydrometeors on a scale comparable to the radiometer field of view (approx. 30 km). For this reason we have developed a method to retrieve average rain rate over a mesoscale grid box of approx. 300 x 300 sq km area over the TOGA COARE region where simultaneous radiometer and radar observations are available for four months (Nov. 92 to Feb. 93). The rain area in the grid box, inferred from the scattering depression due to hydrometeors in the 85 Ghz brightness temperature, constitutes a key parameter in this method. Then the spectral and polarization information contained in all the channels of the SSM/I is utilized to deduce a second parameter. This is the ratio S/E of scattering index S, and emission index E calculated from the SSM/I data. The rain rate retrieved from this method over the mesoscale area can reproduce the radar observed rain rate with a correlation coefficient of about 0.85. Furthermore monthly total rainfall estimated from this method over that area has an average error of about 15%.

Cuddapah, Prabhakara↗
NASA NTRS1994

A comparison of optical rain gauge and radar data from TOGA/COARE

A comparison between rain gauge data and radar data from the Tropical Oceans Global Atmosphere/Coupled Ocean Atmosphere Response Experiment (TOGA/COARE) was studied. The rain gauge data from an echo that passed over the Xiangyanghong #5 on December 24, 1992 was compared to what the MIT radar saw at this location from the R/V Vickers, 103.4 km to the east. The precipitation measured by the rain gauge peaked at 108 mm/hr 92 seconds into the period before tapering off 11 1/2 minutes later. This sharp gradient was evident in a PPI plot of the radar reflectivities and the percentage area-rainfall for the radar data statistics. The percentage area curve was converted to rain rates using a GATE Z-R and compared to a percentage time curve of rain rates according to the rain gauge. A four minute running average applied to the rain gauge rates improved the comparison of peak rates between the rain gauge and radar. Differences in peaks between rain rates observed by the rain gauge and reflectivities observed by the radar could be due to variations in rainfall rates within a single radar data bin. For example, two measurements of reflectivity such as 37 and 47 dBZ within the same bin would result in a 44 dBZ average. This range in rates from 12 mm/hr to 74 mm/hr is observed in 30 seconds by the rain gauges within the first two minutes of the radar echo passage.

Galusha, Linda↗
NASA NTRS1999

Rainfall Estimates from the TMI and the SSM/I

The Tropical Rainfall Measuring Mission (TRMM), which is a joint Japan-U.S. Earth observing satellite, has been successfully launched from Japan on November 27, 1997. The main purpose of the TRMM is to measure quantitatively rainfall over the tropics for the research of climate and weather. One of three rainfall measuring instruments abroad the TRMM is the high resolution TRMM Microwave Imager (TMI). The TMI instrument is essentially the copy of the SSM/I with a dual-polarized pair of 10.7 GHz channels added to increase the dynamic range of rainfall estimates. In addition, the 21.3 GHz water vapor absorption channel is designed in the TMI as opposed to the 22.235 GHz in the SSM/I to avoid saturation in the tropics. This paper will present instantaneous rain rates estimated from the coincident TMI and SSM/I observations. The algorithm for estimating instantaneous rainfall rates from both sensors is the Goddard Profiling algorithm (Gprof). The Gprof algorithm is a physically based, multichannel rainfall retrieval algorithm, The algorithm is very portable and can be used for various sensors with different channels and resolutions. The comparison of rain rates estimated from TMI and SSM/I on the same rain regions will be performed. The results from the comparison and the insight of tile retrieval algorithm will be given.

Hong, Ye↗
NASA NTRS1997

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an eleven year period. 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 North Pacific Ocean total rainfall during June-November when tropical cyclones are most important. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444 km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are converted to monthly rainfall amounts and then compared to those for non-tropical cyclone systems. The main results of this study indicate that: 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maxima in tropical cyclone rainfall are poleward (5 deg to 10 deg latitude depending on longitude) of the maxima in non-tropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% of the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the ITCZ; and 5) in general, tropical cyclone rainfall is enhanced during the El Nino years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Rodgers, Edward B.↗
DOE OSTI2021

Temporal dynamics of free‐living nitrogen fixation in the switchgrass rhizosphere

Abstract Free‐living nitrogen fixation (FLNF) represents an important terrestrial N source and is gaining interest for its potential to contribute plant available N to bioenergy cropping systems. Switchgrass, a cellulosic bioenergy crop, may be particularly reliant on FLNF when grown on low N systems, like marginal lands. However, the potential contributions of FLNF to switchgrass as well as the controls on this process are not well understood. In this study, we evaluated drivers of FLNF rates and N‐fixing microbial (diazotrophic) community composition in field‐grown switchgrass systems over two growing seasons with high temporal sampling. We found that climate variables are strong drivers of FLNF rates in switchgrass systems, compared to other environmental and biological factors including soil nutrients and diazotrophic community composition. Increased soil moisture availability generally promoted FLNF rates, but extreme rainfall events were detrimental. These climate‐related responses suggest a potential for loss of FLNF‐derived N contributions under projected climate shifts. We found a significant, but weak correlation between diazotrophic community composition and FLNF rates. We also observed a significant shift in the diazotrophic community composition between 2017 and 2018 and similarly measured a significant difference in FLNF rates between growing seasons. Lastly, we found that seasonal FLNF N contributions, based on measurement with high temporal resolution, has the potential to meet up to 80% of switchgrass N demands suggesting that FLNF measurements extrapolated from fewer time points or locations may underestimate these potential N contributions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Bayesian Retrieval of Complete Posterior PDFs of Oceanic Rain Rate From Microwave Observations

This paper presents a new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measurements Mission (TRMM) Microwave Imager (TMI) over the ocean, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes Theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance our understanding of theoretical benefits of the Bayesian approach, we have conducted sensitivity analyses based on two synthetic datasets for which the true conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak, due to saturation effects. It is also suggested that the choice of the estimators and the prior information are both crucial to the retrieval. In addition, the performance of our Bayesian algorithm is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.

Chiu, J. Christine↗
DOE OSTI2021

Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot

Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Radar target for remotely sensing hydrological phenomena

An apparatus for remotely measuring and accessing water status relative to snow and glacial melt, surface runoff, rainfall, evaporation, flow rate, and soil moisture is described. A radar target located at a selected location on the surface of the Earth is designed to collect water and render its cross sectional area variable as a function of the height of the water level within the target. The target is remotely monitored by an orbiting or airborne synthetic aperature radar. The target appears as a bright spot embedded within the radar image. The target brightness is indicative of the height of the water level within the ground located target.

Sivertson, W. E., Jr.↗
NASA NTRS1989

Passive microwave retrievals of rainfall and rain system structure

Consideration is given to the development of algorithms for the Tropical Rainfall Measuring Mission to retrieve rain and rain vertical structure from passive microwave radiometry. The self-consistency approach for surface rain rate retrieval of Kummerow et al. (1989) is applied to microwave brightness temperature data from the Cooperative Huntsville Meteorological Experiment (Dodge et al., 1986). Because the algorithm simultaneously retrieves rainfall rate and rain system structure, it is suggested that the algorithm can be used to overcome the problem of the dependence of brightness temperatures on the vertical profile of hydrometeors.

Kummerow, Christian↗
NASA NTRS2000

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Bell, Thomas L.↗