Search NASA⌕ Search

SEARCH · Search NASA

Results for “rain gauges”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Techniques for analyzing and utilizing the rain gauges at the NASA White Sands Test Facility

Ten tipping bucket rain gauges have been installed at the NASA WSTF for the purpose of determining rainfall characteristics in this area which may affect the performance of the NASA Tracking and Data Relay Satellite System. A plan is presented for analyzing and utilizing the data which will be obtained during the course of this experiment. Also included is a description of a computer program which has been written to aid in the analysis.

Kalagher, R. J.↗
NASA NTRS2007

Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

This paper describes the cubic spline based operational system for the generation of the TRMM one-minute rain rate product 2A-56 from Tipping Bucket (TB) gauge measurements. Methodological issues associated with applying the cubic spline to the TB gauge rain rate estimation are closely examined. A simulated TB gauge from a Joss-Waldvogel (JW) disdrometer is employed to evaluate effects of time scales and rain event definitions on errors of the rain rate estimation. The comparison between rain rates measured from the JW disdrometer and those estimated from the simulated TB gauge shows good overall agreement; however, the TB gauge suffers sampling problems, resulting in errors in the rain rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When one minute rain rates are averaged to 4-7 minute or longer time scales, the errors dramatically reduce. The rain event duration is very sensitive to the event definition but the event rain total is rather insensitive, provided that the events with less than 1 millimeter rain totals are excluded. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-minute TB rain rates higher and lower than 3 mm per hour, respectively. These errors decrease to 5% and 14% when TB rain rates are used at 7-minute scale. The radar reflectivity-rainrate (Ze-R) distributions drawn from large amount of 7-minute TB rain rates and radar reflectivity data are mostly insensitive to the event definition.

Wang, Jianxin↗
NASA NTRS1992

Rain rate statistics and fade distributions at 20 and 30 GHz derived from a network of rain gauges in the Mid-Atlantic coast over a five year period

A network of ten tipping bucket rain gauges located within a grid 70 km north-south and 47 km east-west in the Mid-Atlantic coast of the United States was used to analyze rain rate and modeled slant path attenuation distributions at 20 and 30 GHz. It was shown that, for realistic fade margins at 20 GHz and above, the variable integration times results are adequate to estimate slant path attenuations using models which require 1 min averages. Crane's Global Model was used to derive fade distributions at 20 and 30 GHz.

Goldhirsh, Julius↗
NASA NTRS1994

Rain gauge calibration and testing

Prior to the Tropical Oceans Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE), 42 Model 100 series optical gauges were tested in the rain simulator facility at Wallops Island before shipment to the field. Baseline measurements at several rain rates were made simultaneously with collector cans, tipping bucket, and a precision weighing gauge and held for post-COARE evaluation with a repeat set of measurements that were to be recorded after the instruments were returned. This was done as a means of detecting any calibration changes that might have occurred while deployed. Although it was known that the artificial rain in the simulator did not contain the required exponential distribution for accurate optical rain gauge rate measurements, use of the facility was necessary because it was the only means available for taking controlled observations with instruments that were received, tested, and shipped out in groups over a period of months. At that point, it was believed that these measurements would be adequately precise for detecting performance changes over time. However, analysis of the data by STI now indicates that this may not be true. Further study of the data will be undertaken to resolve this.

Wilkerson, John↗
NASA NTRS2000

BOREAS HYD-9 Tipping Bucket Rain Gauge Data

The BOREAS HYD-9 team collected several data sets containing precipitation and strearnflow measurements over the BOREAS study areas. This data set contains the measurements from the tipping bucket rain gauges at the BOREAS NSA and SSA. These measurements were submitted in 15-minute and 1-hour intervals. Only the 15-minute interval data set was loaded into the data base tables. Data were collected from the tipping bucket gauges from mid-April until mid-October in 1994, 1995, and 1996. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Kouwen, Nick↗
NASA NTRS2010

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗
NASA NTRS1989

SSM/I radiances correlated with 15 minute rain gauge data

The relationship between rain rate and the 85.5 and 37 GHz brightness temperature (BT) observations of the Special Sensor Microwave Imager (SSM/I) is examined to develop a BT-rain rate relationship for quantitative mapping of global precipitation using SSM/I data. SSM/I observations of a long-lived rain event over the south-central U.S. in 1987 are compared with digitized rain gage data from the National Climate Data Center. The results show that, for the squall line system studied, the rain gage amounts were well correlated with SSM/I polarization corrected 85.5 GHz BT.

Spencer, Roy W.↗
NASA NTRS1992

Rain rate and modeled fade distributions at 20 GHz and 30 GHz derived from five years of network rain gauge measurements

Five years of rain rate and modeled slant path attenuation distributions at 20 GHz and 30 GHz derived from a network of 10 tipping bucket rain gages was examined. The rain gage network is located within a grid 70 km north-south and 47 km east-west in the Mid-Atlantic coast of the United States in the vicinity of Wallops Island, Virginia. Distributions were derived from the variable integration time data and from one minute averages. It was demonstrated that for realistic fade margins, the variable integration time results are adequate to estimate slant path attenuations at frequencies above 20 GHz using models which require one minute averages. An accurate empirical formula was developed to convert the variable integration time rain rates to one minute averages. Fade distributions at 20 GHz and 30 GHz were derived employing Crane's Global model because it was demonstrated to exhibit excellent accuracy with measured COMSTAR fades at 28.56 GHz.

Goldhirsh, Julius↗
NASA NTRS2000

BOREAS HYD-9 Belfort Rain Gauge Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains water content measurements of the moss/humus layer, where it existed. These data were collected along various flight lines in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994. The data are available in tabular ASCII files. The HYD-9 Belfort rain gauge data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS1989

The ground truth analysis of rain gauge data for the TRMM project

As a part of the Tropical Rainfall Measuring Missioin (TRMM) ground truth program to determine the diurnal variability of the area wide rain rates, the rain rate PDFs, and their effect on the area integral algorithm, rain rate data have been collected from a network of gages located in the area near the Cape Canaveral and Kennedy Space Center, in the period beginning in September 1987. In the preliminary statistical analysis, based on the rain rates derived from the eleven gages, the seasonal diurnal rainfall and network averaged rain rates are determined. The analysis was performed in two steps: determination of the hourly and daily rain accumulations and rain rates; and computation of the fraction of hourly and daily rain rates that exceed a particular threshold, and analysis of the hourly and daily rain rate PDFs for the network. The results indicate that there are diurnal and seasonal variations in the components which determine the network rain rate PDFs.

Kowalewsky, Karen J.↗
NASA NTRS1988

Magnetic reversal spurts: Rain gauges for comet showers

Abrupt increases in the rate of magnetic reversals (magnetic reversal spurts) were first studied by many others. They hypothesized that spurts result from increased turbulence in the earth's core dynamo during episodes of intense bolide bombardment of the earth. Mechanisms for creating episodes of intense bombardment of the earth involve gravitational perturbation of the Oort cloud of comets, either by a hidden planet, a solar companion, or massive matter in the galactic plane. Herein, the time variation in reversal rate is analyzed using methods of statistical density estimation. A smooth, continuous estimate of reversal rate is obtained using an adaptive kernel method, in which the kernel width is adjusted as a function of reversal rate. The estimates near the ends of the data series (at 165 my ago and the present) are obtained by extending the data by reflection. The results show that the reversal spurts are not associated demonstrably with extinctions or well-dated impacts. If the spurts do record episodes of intense bombardment of the earth, then the mass extinctions do not, in general, occur at times of impacts. Furthermore, the large impact craters seen are not obviously related to the spurts, suggesting that the craters may have been caused by bolides of a different nature and with a different temporal pattern. However, the most simple explanation seems to be that the spurts do not record comet showers, either because the recording mechanism suggested by Muller and Morris is not effective or because comet showers are not triggered in the ways considered by Hut et al.

Lutz, T. M.↗
NASA NTRS2008

Comparison of GPCP Monthly and Daily Precipitation Estimates with High-Latitude Gauge Observations

It is very important to know how much rain and snow falls around the world for uses that range from crop forecasting to disaster response, drought monitoring to flood forecasting, and weather analysis to climate research. Precipitation is usually measured with rain gauges, but rain gauges don t exist in areas that are sparsely populated, which tends to be a good portion of the globe. To overcome this, meteorologists use satellite data to estimate global precipitation. However, it is difficult to estimate rain and especially snow in cold climates using most current satellites. The satellite sensors are often "confused" by a snowy or frozen surface and therefore cannot distinguish precipitation. One commonly used satellite-based precipitation data set, the Global Precipitation Climatology Project (GPCP) data, overcomes this frozen-surface problem through the innovative use of two sources of satellite data, the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). Though the GPCP estimates are generally considered a very reliable source of precipitation, it has been difficult to assess the quality of these estimates in cold climates due to the lack of gauges. Recently, the Finnish Meteorological Institute (FMI) has provided a 12-year span of high-quality daily rain gauge observations, covering all of Finland, that can be used to compare with the GPCP data to determine how well the satellites estimate cold-climate precipitation. Comparison of the monthly GPCP satellite-based estimates and the FMI gauge observations shows remarkably good agreement, with the GPCP estimates being 6% lower in the amount of precipitation than the FMI observations. Furthermore, the month-to-month correlation between the GPCP and FMI is very high at 0.95 (1.0 is perfect). The daily GPCP estimates replicate the FMI daily occurrences of precipitation with a correlation of 0.55 in the summer and 0.45 in the winter. The winter result indicates the GPCP estimates have skill in "seeing" snowfall, which is the most challenging situation. Thus, the GPCP data set successfully overcomes a current limitation in satellite meteorology, namely the estimation of cold-climate precipitation. The success of the GPCP data set bodes well for future missions, whose instrumentation is specifically designed to give even more information for addressing cold-climate precipitation.

Bolvin, David T.↗
NASA NTRS1998

Narrow Angle Diversity using ACTS Ka-band Signal with Two USAT Ground Stations

Two ultra small aperture terminal (USAT) ground stations, separated by 1.2 km in a narrow angle diversity configuration, received a continuous Ka-band tone sent from Cleveland Link Evaluation Terminal (LET). The signal was transmitted to the USAT ground stations via NASA's Advanced Communications Technology Satellite (ACTS) steerable beam. Received signal power at the two sites was measured and analyzed. A dedicated datalogger at each site recorded time-of-tip data from tipping bucket rain gauges, providing rain amount and instantaneous rain rate. WSR-88D data was also obtained for the collection period. Eleven events with ground-to-satellite slant-path precipitation and resultant signal attenuation were observed during the data collection period. Fade magnitude and duration were compared at the two sites and diversity gain was calculated. These results exceeded standard diversity gain model predictions by several decibels. Rain statistics from tipping bucket data and from radar data were also compared to signal attenuation. The nature of Florida's subtropical rainfall, specifically its impact on signal attenuation at the sites, was addressed.

Kalu, A.↗
NASA NTRS2005

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Gottschalck, Jon↗
NASA NTRS2002

Inter-Comparison of CHARM Data and WSR-88D Storm Integrated Rainfall

A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.

Jedlovec, Gary J.↗
NASA NTRS1995

A method for combining passive microwave and infrared rainfall observations

Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

Kummerow, Christian↗
NASA NTRS2000

Rainfall Product Evaluation for the TRMM Ground Validation Program

Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

Amitai, E.↗