A comparative assessment of R. M. Young and tipping bucket rain gauges

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius; Gebo, Norman E.

1992-01-01

Rain rates as derived from standard tipping bucket rain gauges have variable integration times corresponding to the interval between bucket tips. For example, the integration time for the Weathertronics rain gauge is given by delta(T) = 15.24/R (min), where R is the rain rate expressed in mm/h and delta(T) is the time between tips expressed in minutes. It is apparent that a rain rate of 1 mm/h has an integration time in excess of 15 minutes. Rain rates larger than 15.24 mm/h will have integration times smaller than 1 minute. The integration time is dictated by the time it takes to fill a small tipping bucket where each tip gives rise to 0.254 mm of rainfall. Hence, a uniform rain rate of 1 mm/h over a 15 minute period will give rise to the same rain rate as 0 mm/h rainfall over the first 14 minutes and 15 mm/h between 14 to 15 minutes from the reference tip. Hence, the rain intensity fluctuations may not be captured with the tipping bucket rain gauge for highly variable rates encompassing lower and higher values over a given integration time. The objective of this effort is to provide an assessment of the features of the R. M. Young capacitive gauge and to compare these features with those of the standard tipping bucket rain gauge. A number of rain rate-time series derived from measurements with approximately co-located gauges are examined.

A new method for automated dynamic calibration of tipping-bucket rain gauges

USGS Publications Warehouse

Humphrey, M.D.; Istok, J.D.; Lee, J.Y.; Hevesi, J.A.; Flint, A.L.

1997-01-01

Existing methods for dynamic calibration of tipping-bucket rain gauges (TBRs) can be time consuming and labor intensive. A new automated dynamic calibration system has been developed to calibrate TBRs with minimal effort. The system consists of a programmable pump, datalogger, digital balance, and computer. Calibration is performed in two steps: 1) pump calibration and 2) rain gauge calibration. Pump calibration ensures precise control of water flow rates delivered to the rain gauge funnel; rain gauge calibration ensures precise conversion of bucket tip times to actual rainfall rates. Calibration of the pump and one rain gauge for 10 selected pump rates typically requires about 8 h. Data files generated during rain gauge calibration are used to compute rainfall intensities and amounts from a record of bucket tip times collected in the field. The system was tested using 5 types of commercial TBRs (15.2-, 20.3-, and 30.5-cm diameters; 0.1-, 0.2-, and 1.0-mm resolutions) and using 14 TBRs of a single type (20.3-cm diameter; 0.1-mm resolution). Ten pump rates ranging from 3 to 154 mL min-1 were used to calibrate the TBRs and represented rainfall rates between 6 and 254 mm h-1 depending on the rain gauge diameter. All pump calibration results were very linear with R2 values greater than 0.99. All rain gauges exhibited large nonlinear underestimation errors (between 5% and 29%) that decreased with increasing rain gauge resolution and increased with increasing rainfall rate, especially for rates greater than 50 mm h-1. Calibration curves of bucket tip time against the reciprocal of the true pump rate for all rain gauges also were linear with R2 values of 0.99. Calibration data for the 14 rain gauges of the same type were very similar, as indicated by slope values that were within 14% of each other and ranged from about 367 to 417 s mm h-1. The developed system can calibrate TBRs efficiently, accurately, and virtually unattended and could be modified for use with other rain gauge designs. The system is now in routine use to calibrate TBRs in a large rainfall collection network at Yucca Mountain, Nevada.

Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

NASA Technical Reports Server (NTRS)

Wang, Jianxin; Fisher, Brad L.; Wolff, David B.

2007-01-01

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.

High resolution radar-rain gauge data merging for urban hydrology: current practice and beyond

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Bailey, Andy; Willems, Patrick; Onof, Christian

2017-04-01

In this work a thorough test is conducted of radar-rain gauge merging techniques at urban scales, under different climatological conditions and rain gauge density scenarios. The aim is to provide guidance regarding the suitability and application of merging methods at urban scales, which is lacking at present. The test is conducted based upon two pilot locations, i.e. the cities of Edinburgh (254 km^2) and Birmingham (431 km^2), for which a total of 96 and 84 tipping bucket rain gauges were respectively available, alongside radar QPEs, dense runoff records and urban drainage models. Three merging techniques, namely Mean Field Bias (MFB) adjustment, kriging with external (KED) and Bayesian (BAY) combination, were selected for testing on grounds of performance and common use. They were initially tested as they were originally formulated and as they are reportedly commonly applied using typically available radar and rain gauge data. Afterwards, they were tested in combination with two special treatments which were identified as having the potential to improve merging applicability for urban hydrology: (1) reduction of temporal sampling errors in radar QPEs through temporal interpolation and (2) singularity-based decomposition of radar QPEs prior to merging. These treatments ultimately aim at improving the consistency between radar and rain gauge records, which has been identified as the chief factor affecting merging performance and is particularly challenging at the fine spatial-temporal resolutions required for urban applications. The main findings of this study are the following: - All merging methods were found to improve the applicability of radar QPEs for urban hydrological applications, but the degree of improvement they provide and the added value of radar information vary for each merging method and are also a function of climatological conditions and rain gauge density scenarios. - Overall, KED displayed the best performance, with BAY being a close second and MFB providing the smallest improvements upon radar QPEs. However, as compared to BAY, KED performance is more sensitive to rain gauge density and to the ability of rain gauges to sample critical features of the rainfall field. By incorporating more information from radar than KED, BAY is less sensitive to rain gauge density and to poor rain gauge predictability and proved able to provide a good representation of convective cells even in cases in which gauges completely missed such structures. - Based on the findings of this study, it is recommended that KED be used when gauge densities are relatively high (of the order of 30 km2 per gauge or higher) and/or when the quality of radar QPEs is known to be very poor, in which case it is desirable to rely more upon rain gauge records. For low rain gauge density situations and QPEs of reasonable quality (as is the case in most of EU), BAY may be a more appropriate choice. MFB should be the last choice; however, it is better than no correction at all. - The two special treatments under consideration successfully improved overall merging performance at the spatial-temporal resolutions required for urban hydrology, with benefits being particularly evident at low rain gauge density conditions.

Urban Rain Gauge Siting Selection Based on Gis-Multicriteria Analysis

NASA Astrophysics Data System (ADS)

Fu, Yanli; Jing, Changfeng; Du, Mingyi

2016-06-01

With the increasingly rapid growth of urbanization and climate change, urban rainfall monitoring as well as urban waterlogging has widely been paid attention. In the light of conventional siting selection methods do not take into consideration of geographic surroundings and spatial-temporal scale for the urban rain gauge site selection, this paper primarily aims at finding the appropriate siting selection rules and methods for rain gauge in urban area. Additionally, for optimization gauge location, a spatial decision support system (DSS) aided by geographical information system (GIS) has been developed. In terms of a series of criteria, the rain gauge optimal site-search problem can be addressed by a multicriteria decision analysis (MCDA). A series of spatial analytical techniques are required for MCDA to identify the prospective sites. With the platform of GIS, using spatial kernel density analysis can reflect the population density; GIS buffer analysis is used to optimize the location with the rain gauge signal transmission character. Experiment results show that the rules and the proposed method are proper for the rain gauge site selection in urban areas, which is significant for the siting selection of urban hydrological facilities and infrastructure, such as water gauge.

Rain rate duration statistics derived from the Mid-Atlantic coast rain gauge network

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius

1993-01-01

A rain gauge network comprised of 10 tipping bucket rain gauges located in the Mid-Atlantic coast of the United States has been in continuous operation since June 1, 1986. Rain rate distributions and estimated slant path fade distributions at 20 GHz and 30 GHz covering the first five year period were derived from the gauge network measurements, and these results were described by Goldhirsh. In this effort, rain rate time duration statistics are presented. The rain duration statistics are of interest for better understanding the physical nature of precipitation and to present a data base which may be used by modelers to convert to slant path fade duration statistics. Such statistics are important for better assessing optimal coding procedures over defined bandwidths.

NARSTO EPA SS BALTIMORE JHU MET DATA

Atmospheric Science Data Center

2018-04-09

... Meteorological Station Instrument:  Temperature Probe Humidity Probe Cup Anemometer Rain Gauge Sonic ...   E arthdata Search Parameters:  Air Temperature Humidity Surface Winds Precipitation Amount Heat Flux ...

Polarimetric Radar Retrievals in Southeast Texas During Hurricane Harvey

NASA Astrophysics Data System (ADS)

Wolff, D. B.; Petersen, W. A.; Tokay, A.; Marks, D. A.; Pippitt, J. L.; Kirstetter, P. E.

2017-12-01

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017 before exiting the state as a tropical storm on September 1, 2017. In its wake, it left a flood of historic proportions, with some areas measuring 60 inches of rain over a five-day period. Although the storm center stayed west of the immediate Houston area training bands of precipitation impacted the Houston area for five full days. The National Weather Service (NWS) WSR88D dual-polarimetric radar (KHGX), located southeast of Houston, maintained operations for the entirety of the event. The Harris County Flood Warning System (HCFWS) had 150 rain gauges deployed in its network and seven NWS Automated Surface Observing Systems (ASOS) rain gauges are also located in the area. In this study, we used the full radar data set to retrieve daily and event-total precipitation estimates within 120 km of the KHGX radar for the period August 25-29, 2017. These estimates were then compared to the HCFWS and ASOS gauges. Three different polarimetric hybrid rainfall retrievals were used: Ciffeli et al. 2011; Bringi et al. 2004; and, Chen et al. 2017. Each of these hybrid retrievals have demonstrated robust performance in the past. However, both daily and event-total comparisons from each of these retrievals compared to those of HCFWS and ASOS rain gauge networks resulted in significant underestimates by the radar retrievals. These radar underestimates are concerning. Sources of error and variance will be investigated to understand the source of radar-gauge disagreement. One current hypothesis is that due to the large number of small drops often found in hurricanes, the differential reflectivity and specific differential phase are relatively small so that the hybrid algorithms use only the reflectivity/rain rate procedure (so called Z-R relationships), and hence rarely invoke the ZDR or KDP procedures. Thus, an alternative Z-R relationship must be invoked to retrieve accurate rain rate estimates.

The depth-dependence of rain noise in the Philippine Sea.

PubMed

Barclay, David R; Buckingham, Michael J

2013-05-01

During the Philippine Sea experiment in May 2009, Deep Sound, a free-falling instrument platform, descended to a depth of 5.1 km and then returned to the surface. Two vertically aligned hydrophones monitored the ambient noise continuously throughout the descent and ascent. A heavy rainstorm passed over the area during the deployment, the noise from which was recorded over a frequency band from 5 Hz to 40 kHz. Eight kilometers from the deployment site, a rain gauge on board the R/V Kilo Moana provided estimates of the rainfall rate. The power spectral density of the rain noise shows two peaks around 5 and 30 kHz, elevated by as much as 20 dB above the background level, even at depths as great as 5 km. Periods of high noise intensity in the acoustic data correlate well with the rainfall rates recovered from the rain gauge. The vertical coherence function of the rain noise has well-defined zeros between 1 and 20 kHz, which are characteristic of a localized source on the sea surface. A curve-fitting procedure yields the vertical directional density function of the noise, which is sharply peaked, accurately tracking the storm as it passed over the sensor station.

Merging gauge and satellite rainfall with specification of associated uncertainty across Australia

NASA Astrophysics Data System (ADS)

Woldemeskel, Fitsum M.; Sivakumar, Bellie; Sharma, Ashish

2013-08-01

Accurate estimation of spatial rainfall is crucial for modelling hydrological systems and planning and management of water resources. While spatial rainfall can be estimated either using rain gauge-based measurements or using satellite-based measurements, such estimates are subject to uncertainties due to various sources of errors in either case, including interpolation and retrieval errors. The purpose of the present study is twofold: (1) to investigate the benefit of merging rain gauge measurements and satellite rainfall data for Australian conditions and (2) to produce a database of retrospective rainfall along with a new uncertainty metric for each grid location at any timestep. The analysis involves four steps: First, a comparison of rain gauge measurements and the Tropical Rainfall Measuring Mission (TRMM) 3B42 data at such rain gauge locations is carried out. Second, gridded monthly rain gauge rainfall is determined using thin plate smoothing splines (TPSS) and modified inverse distance weight (MIDW) method. Third, the gridded rain gauge rainfall is merged with the monthly accumulated TRMM 3B42 using a linearised weighting procedure, the weights at each grid being calculated based on the error variances of each dataset. Finally, cross validation (CV) errors at rain gauge locations and standard errors at gridded locations for each timestep are estimated. The CV error statistics indicate that merging of the two datasets improves the estimation of spatial rainfall, and more so where the rain gauge network is sparse. The provision of spatio-temporal standard errors with the retrospective dataset is particularly useful for subsequent modelling applications where input error knowledge can help reduce the uncertainty associated with modelling outcomes.

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

NASA Technical Reports Server (NTRS)

Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

2005-01-01

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.

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

NASA Technical Reports Server (NTRS)

Bolvin, David T.; Adler, Robert G.; Nelkin, Eric J.; Poutiainen, Jani

2008-01-01

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.

Evaluation and design of a rain gauge network using a statistical optimization method in a severe hydro-geological hazard prone area

NASA Astrophysics Data System (ADS)

Fattoruso, Grazia; Longobardi, Antonia; Pizzuti, Alfredo; Molinara, Mario; Marocco, Claudio; De Vito, Saverio; Tortorella, Francesco; Di Francia, Girolamo

2017-06-01

Rainfall data collection gathered in continuous by a distributed rain gauge network is instrumental to more effective hydro-geological risk forecasting and management services though the input estimated rainfall fields suffer from prediction uncertainty. Optimal rain gauge networks can generate accurate estimated rainfall fields. In this research work, a methodology has been investigated for evaluating an optimal rain gauges network aimed at robust hydrogeological hazard investigations. The rain gauges of the Sarno River basin (Southern Italy) has been evaluated by optimizing a two-objective function that maximizes the estimated accuracy and minimizes the total metering cost through the variance reduction algorithm along with the climatological variogram (time-invariant). This problem has been solved by using an enumerative search algorithm, evaluating the exact Pareto-front by an efficient computational time.

Use of NEXRAD radar-based observations for quality control of in-situ rain gauge measurements

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O.; Leeper, R.

2017-12-01

Rain gauge quality control is an often over looked important step in the archive of historical precipitation estimates. We investigate the possibilities that exist for using ground based radar networks for quality control of rain gauge measurements. This process includes the point to pixel comparisons of the rain gauge measurements with NEXRAD observations. There are two NEXRAD based data sets used for reference; the NCEP stage IV and the NWS MRMS gridded data sets. The NCEP stage IV data set is available at 4km hourly for the period 2002-present and includes the radar-gauge bias adjusted precipitation estimate. The NWS MRMS data set includes several different variables such as reflectivity, radar-only estimates, precipitation flag, and radar-gauge bias adjusted precipitation estimates. The latter product provides for much more information to apply quality control such as identification of precipitation type, identification of storm type and Z-R relation. In addition, some of the variables are available at 5-minute scale. The rain gauge networks that are investigated are the Climate Reference Network (CRN), the Fischer-Porter Hourly Precipitation Database (HPD), and the Hydrometeorological Automated Data System (HADS). The CRN network is available at the 5-minute scale, the HPD network is available at the 15-minute and hourly scale, and HADS is available at the hourly scale. The varying scales present challenges for comparisons. However given the higher resolution radar-based products we identify an optimal combination of rain gauge observations that can be compared to the radar-based information. The quality control process focuses on identifying faulty gauges in direct comparison while a deeper investigation focuses on event-based differences from light rain to extreme storms.

Optical Rain Gauge Performance: Second Workshop on Optical Rain Gauge Measurements

NASA Technical Reports Server (NTRS)

Short, David A. (Editor); Thiele, Otto W. (Editor); Mcphaden, Michael J. (Editor)

1994-01-01

The primary focus of the workshop was on the performance and reliability of STi mini-Optical Rain Gauges in a number of environments, including deployments on ships and buoys in the western equatorial Pacific Ocean during the TOGA/COARE field experiment, deployments on buoys in U.S. coastal waters, and comparisons with other types of rain gauges on the Virginia coast and in Florida. The workshop was attended by 20 investigators, representing 10 different institutions, who gathered to present new results obtained since the first workshop (April 1993), to discuss problems, to consider solutions, and to chart future directions. Post-TOGA/COARE calibration studies were also presented.

A TRMM Rainfall Estimation Method Applicable to Land Areas

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R.; Weinman, J.; Dalu, G.

1999-01-01

Methods developed to estimate rain rate on a footprint scale over land with the satellite-borne multispectral dual-polarization Special Sensor Microwave Imager (SSM/1) radiometer have met with limited success. Variability of surface emissivity on land and beam filling are commonly cited as the weaknesses of these methods. On the contrary, we contend a more significant reason for this lack of success is that the information content of spectral and polarization measurements of the SSM/I is limited. because of significant redundancy. As a result, the complex nature and vertical distribution C, of frozen and melting ice particles of different densities, sizes, and shapes cannot resolved satisfactorily. Extinction in the microwave region due to these complex particles can mask the extinction due to rain drops. Because of these reasons, theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. To illustrate the weakness of these models, as an example we can consider the brightness temperature measurement made by the radiometer in the 85 GHz channel (T85). Models indicate that T85 should be inversely related to the rain rate, because of scattering. However, rain rate derived from 15-minute rain gauges on land indicate that this is not true in a majority of footprints. This is also supported by the ship-borne radar observations of rain in the Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) region over the ocean. Based on these observations. we infer that theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. We do not follow the above path of rain retrieval on a footprint scale. Instead, we depend on the limited ability of the microwave radiometer to detect the presence of rain. This capability is useful to determine the rain area in a mesoscale region. We find in a given rain event that this rain area is closely related to the mesoscale-average rain rate. Based on this observation, in this study we have developed a method to estimate the mesoscale-average rain rate over land utilizing microwave radiometer data. Because of the high degree of geographic and seasonal variability in the nature and intensity of rain, this method requires some tuning with 15-minute rain gauge data on land. After tuning the method, it can be applied to an independent set of rain events that are close in time and space. We find that the mesoscale rain rates retrieved over the period of a month on land with this method shows a correlation of about 0.85 with respect to the surface rain-gauge observations. This mesoscale-average rain rate estimation method can be useful to extend the spatial and temporal coverage of the rainfall data provided by the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite.

Development of a low-budget, remote, solar powered, and self-operating rain gauge for spatial rainfall real time data monitoring in pristine and urban areas

NASA Astrophysics Data System (ADS)

Shafiei Shiva, J.; Chandler, D. G.; Nucera, K. J.; Valinski, N.

2016-12-01

Precipitation is one of the main components of the hydrological cycle and simulations and it is generally stated as an average value for the study area. However, due to high spatial variability of precipitation in some situations, more precise local data is required. In order to acquire the precipitation data, interpolation of neighbor gauged precipitation data is used which is the most affordable technique for a watershed scale study. Moreover, novel spatial rain measurements such as Doppler radars and satellite image processing have been widely used in recent studies. Although, due to impediments in the radar data processing and the effect of the local setting on the accuracy of the interpolated data, the local measurement of the precipitation remains as one of the most reliable approaches in attaining rain data. In this regard, development of a low-budget, remote, solar powered, and self-operating rain gauge for spatial rainfall real time data monitoring for pristine and urban areas has been presented in this research. The proposed rain gauge consists of two main parts: (a) hydraulic instruments and (b) electrical devices. The hydraulic instruments will collect the rain fall and store it in a PVC container which is connected to the high sensitivity pressure transducer systems. These electrical devices will transmit the data via cellphone networks which will be available for further analysis in less than one minute, after processing. The above-mentioned real time rain fall data can be employed in the precipitation measurement and the evaporation estimation. Due to the installed solar panel for battery recharging and designed siphon system for draining cumulative rain, this device is considered as a self-operating rain gauge. At this time, more than ten rain gauges are built and installed in the urban area of Syracuse, NY. Furthermore, these data are also useful for calibration and validation of data obtained by other rain gauging devices and estimation techniques. Moreover, remote data communication challenges in urban area are demonstrated and the solution for these problems have been addressed. Finally, the rainfall data obtained from the presented rain gauge has been compared with other measuring systems.

A High Precision $3.50 Open Source 3D Printed Rain Gauge Calibrator

NASA Astrophysics Data System (ADS)

Lopez Alcala, J. M.; Udell, C.; Selker, J. S.

2017-12-01

Currently available rain gauge calibrators tend to be designed for specific rain gauges, are expensive, employ low-precision water reservoirs, and do not offer the flexibility needed to test the ever more popular small-aperture rain gauges. The objective of this project was to develop and validate a freely downloadable, open-source, 3D printed rain gauge calibrator that can be adjusted for a wide range of gauges. The proposed calibrator provides for applying low, medium, and high intensity flow, and allows the user to modify the design to conform to unique system specifications based on parametric design, which may be modified and printed using CAD software. To overcome the fact that different 3D printers yield different print qualities, we devised a simple post-printing step that controlled critical dimensions to assure robust performance. Specifically, the three orifices of the calibrator are drilled to reach the three target flow rates. Laboratory tests showed that flow rates were consistent between prints, and between trials of each part, while the total applied water was precisely controlled by the use of a volumetric flask as the reservoir.

A UK portrait of wind-induced undercatch in rainfall measurement

NASA Astrophysics Data System (ADS)

Pollock, Michael; Quinn, Paul; O'Donnell, Greg; Colli, Matteo; Dutton, Mark; Black, Andrew; Wilkinson, Mark; Kilsby, Chris; Stagnaro, Mattia; Lanza, Luca; O'Connell, Enda

2017-04-01

Rainfall is vital to life; civilisation depends upon it. Changing local and regional rainfall regimes toward more intense storm events (e.g. in the UK), increases the existing challenge of accurately measuring and modelling rainfall. Data from rain gauges, often considered to provide the most accurate practicable measure of precipitation at a point in space in time, play a critical role. They are used for, inter alia, flood forecasting and flood risk management; radar calibration and numerical weather prediction models; urban planning and drainage; and water resource management and hydrological modelling. Despite the key importance of these measurements, they remain susceptible to fundamental sources of systematic error which are often not considered when rainfall data are used. Inaccuracies in measurements are compounded in modelling applications by producing potentially misleading or incorrect results; it is therefore of great importance to understand and present uncertainty in observations. Standard practice is to mount rain gauges above the ground surface. This configuration obstructs the prevailing wind which causes an acceleration of airflow above the orifice. Precipitation is deflected away from the orifice and lands 'downstream' of the area represented by the gauge measurement, reducing its collection efficiency (CE). This phenomenon is commonly referred to as 'wind-induced undercatch'. The physical shape of a gauge bears a significant impact on its CE. Computational Fluid Dynamics (CFD) simulations are used to investigate how different shapes of precipitation gauge are affected by the wind. CFD modelling is supported by high-resolution field measurements at several exposed 'Hydro-Met' research stations in the UK. These sites are occupied by rain gauges which are scrutinised in the CFD analyses. The reference measurements at all sites are made within a WMO reference pit, where the rain gauge is mounted with its orifice at ground level and surrounded by an appropriate grid structure. 'Undercatch' exhibited within UK storms, not captured by operational gauge networks in the UK, is quantified and presented in this study. Results from CFD modelling and the field studies show that gauge shape and mounting height significantly affect the extent of the undercatch. 'Aerodynamic' gauges following a 'champagne flute' or a 'funnel' profile were demonstrated by both to have significant advantages over conventional gauge shapes, in terms of improving the CE. This study presents the latest analyses, and proposes the possible extent of rainfall underestimation within the UK, with particular reference to its hydrology.

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

Investigation clogging dynamic of permeable pavement systems using embedded sensors

NASA Astrophysics Data System (ADS)

Razzaghmanesh, Mostafa; Borst, Michael

2018-02-01

Permeable pavement is a stormwater control measure commonly selected in both new and retrofit applications. However, there is limited information about the clogging mechanism of these systems that effects the infiltration. A permeable pavement site located at the Seitz Elementary School, on Fort Riley, Kansas was selected for this study. An 80-space parking lot was built behind the school as part of an EPA collaboration with the U.S. Army. The parking lot design includes a permeable interlocking concrete pavement section along the downgradient edge. This study monitored the clogging progress of the pavement section using twelve water content reflectometers and three buried tipping bucket rain gauges. This clogging dynamic investigation was divided into three stages namely pre-clogged, transitional, and clogged. Recorded initial relative water content of all three stages were significantly and negatively correlated to antecedent dry weather periods with stronger correlations during clogged conditions. The peak relative water content correlation with peak rainfall 10-min intensity was significant for the water content reflectometers located on the western edge away from the eastern edge; this correlation was strongest during transition stage. Once clogged, rainfall measurements no longer correlated with the buried tipping bucket rain gauges. Both water content reflectometers and buried tipping bucket rain gauges showed the progress of surface clogging. For every 6 mm of rain, clogging advanced 1 mm across the surface. The results generally support the hypothesis that the clogging progresses from the upgradient to the downgradient edge. The magnitude of the contributing drainage area and rainfall characteristics are effective factors on rate and progression of clogging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com; Yusof, Fadhilah, E-mail: fadhilahy@utm.my; Daud, Zalina Mohd, E-mail: zalina@ic.utm.my

Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during themore » monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.« less

Throughfall in a Puerto Rican lower montane rain forest: A comparison of sampling strategies

Treesearch

F. Holwerda; F.N. Scatena; L.A. Bruijnzeel

2006-01-01

During a one-year period, the variability of throughfall and the standard errors of the means associated with different gauge arrangements were studied in a lower montane rain forest in Puerto Rico. The following gauge arrangements were used: (1) 60 fixed gauges, (2) 30 fixed gauges, and (3) 30 roving gauges. Stemflow was measured on 22 trees of four different species...

The statistical characteristics of rain-generated stalks on water surface

NASA Astrophysics Data System (ADS)

Liu, Xinan; Liu, Ren; Duncan, James H.

2017-11-01

Laboratory measurements of the stalks generated by the impact of raindrops are performed in a 1.22-m-by-1.22-m water pool with a water depth of 0.3 m. Simulated raindrops are generated by an array of 22-gauge hypodermic needles that are attached to the bottom of an open-surface rain tank. The raindrop diameter is about 2.6 mm and the height of the rain tank above the water surface of the pool is varied from 1 m to 4.5 m to provide different impact velocities. A number of parameters, including the diameter, height and initial upward velocity of the center jets (stalks) are measured with a cinematic laser-induced- fluorescence technique. It is found that the maximum potential energy of the stalk and the joint distribution of stalk height and diameter are strongly correlated to the impact velocities of raindrops. Comparisons between the rain experiments and single drop impacts on a quiescent water surface are also shown.

Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

2015-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

Assessment of Bias in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Reanalysis Radar-Only Estimate

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O. P.; Stevens, S. E.; Seo, D. J.; Zhang, J.; Howard, K.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is nearly completed for the period covering from 2001 to 2012. Reanalysis data are available at 1-km and 5-minute resolution. An important step in generating the best possible precipitation data is to assess the bias in the radar-only product. In this work, we use data from a combination of rain gauge networks to assess the bias in the NMQ reanalysis. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network Daily (GHCN-D) are combined for use in the assessment. These rain gauge networks vary in spatial density and temporal resolution. The challenge hence is to optimally utilize them to assess the bias at the finest resolution possible. For initial assessment, we propose to subset the CONUS data in climatologically representative domains, and perform bias assessment using information in the Q2 dataset on precipitation type and phase.

Comparison of Imerg Half Hourly Final GPM data with Rain Gauge for Riyadh City, Kingdom of Saudi Arabia

NASA Astrophysics Data System (ADS)

Tekeli, E.; Dönmez, S.

2016-12-01

Being launched in 1997 with the main goal of measuring moderate to heavy rainfall, TRMM enabled invaluable service to remote sensing and hydrology community with data more than 17 years. Based on TRMM experience, GPM was launched in 2014. GPM with increased radar sensitivity and higher spatial resolutions, is expected to enable better light rain and snowfall detection. In here, light rainfall detection capacity of IMERG Half hourly final GPM (IFHH) product is investigated for Riyadh City in Kingdom of Saudi Arabia. A tipping bucket rain gauge located on the roof of King Saud University Civil Engineering Department provided rainfall measurements in 10 minute intervals from 22 November 2014 till 11 Jun 2015. Obtained rain gauge data indicated 72 light rain (rain rate [rr] ≤2.5mm/h) 5 medium rain (2.5mm/hPreliminary results indicate that IFHH overestimate most of the light rain. For the medium and heavy rain rates, IFHH showed under estimations. As one of the major goals of GPM is accurate light rain detection, similar studies should be continued and databases should be formed.

Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data

NASA Astrophysics Data System (ADS)

Rossi, M.; Luciani, S.; Valigi, D.; Kirschbaum, D.; Brunetti, M. T.; Peruccacci, S.; Guzzetti, F.

2017-05-01

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the "ground" rainfall registered by rain gauges.

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

NASA Technical Reports Server (NTRS)

Rossi, M.; Luciani, S.; Valigi, D.; Kirschbaum, D.; Brunetti, M. T.; Peruccacci, S.; Guzzetti, F.

2017-01-01

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

A Computational Fluid-Dynamics Assessment of the Improved Performance of Aerodynamic Rain Gauges

NASA Astrophysics Data System (ADS)

Colli, Matteo; Pollock, Michael; Stagnaro, Mattia; Lanza, Luca G.; Dutton, Mark; O'Connell, Enda

2018-02-01

The airflow surrounding any catching-type rain gauge when impacted by wind is deformed by the presence of the gauge body, resulting in the acceleration of wind above the orifice of the gauge, which deflects raindrops and snowflakes away from the collector (the wind-induced undercatch). The method of mounting a gauge with the collector at or below the level of the ground, or the use of windshields to mitigate this effect, is often not practicable. The physical shape of a gauge has a significant impact on its collection efficiency. In this study, we show that appropriate "aerodynamic" shapes are able to reduce the deformation of the airflow, which can reduce undercatch. We have employed computational fluid-dynamic simulations to evaluate the time-averaged airflow realized around "aerodynamic" rain gauge shapes when impacted by wind. Terms of comparison are provided by the results obtained for two standard "conventional" rain gauge shapes. The simulations have been run for different wind speeds and are based on a time-averaged Reynolds-Averaged Navier-Stokes model. The shape of the aerodynamic gauges is shown to have a positive impact on the time-averaged airflow patterns observed around the orifice compared to the conventional shapes. Furthermore, the turbulent air velocity fields for the aerodynamic shapes present "recirculating" structures, which may improve the particle-catching capabilities of the gauge collector.

Exploration of a Dynamic Merging Scheme for Precipitation Estimation over a Small Urban Catchment

NASA Astrophysics Data System (ADS)

Al-Azerji, Sherien; Rico-Ramirez, Miguel, ,, Dr.; Han, Dawei, ,, Prof.

2016-04-01

The accuracy of quantitative precipitation estimation is of significant importance for urban areas due to the potentially damaging consequences that can result from pluvial flooding. Improved accuracy could be accomplished by merging rain gauge measurements with weather radar data through different merging methods. Several factors may affect the accuracy of the merged data, and the gauge density used for merging is one of the most important. However, if there are no gauges inside the research area, then a gauge network outside the research area can be used for the merging. Generally speaking, the denser the rain gauge network is, the better the merging results that can be achieved. However, in practice, the rain gauge network around the research area is fixed, and the research question is about the optimal merging area. The hypothesis is that if the merging area is too small, there are fewer gauges for merging and thus the result would be poor. If the merging area is too large, gauges far away from the research area can be included in merging. However, due to their large distances, those gauges far away from the research area provide little relevant information to the study and may even introduce noise in merging. Therefore, an optimal merging area that produces the best merged rainfall estimation in the research area could exist. To test this hypothesis, the distance from the centre of the research area and the number of merging gauges around the research area were gradually increased and merging with a new domain of radar data was then performed. The performance of the new merging scheme was compared with a gridded interpolated rainfall from four experimental rain gauges installed inside the research area for validation. The result of this analysis shows that there is indeed an optimum distance from the centre of research area and consequently an optimum number of rain gauges that produce the best merged rainfall data inside the research area. This study is of important and practical value for estimating rainfall in an urban catchment (when there are no gauges available inside the catchment) by merging weather radar with rain gauge data from outside of the catchment. This has not been reported in any literature before now.

Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models.

PubMed

Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

2013-01-01

When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this time displacement is not present for system measurements the data assimilation scheme might already have updated the model to include the impact from the particular rain cell when the rain data is forced upon the model, which therefore will end up including the same rain twice in the model run. This paper compares forecast accuracy of updated models when using time displaced rain input to that of rain input with constant biases. This is done using a simple time-area model and historic rain series that are either displaced in time or affected with a bias. The results show that for a 10 minute forecast, time displacements of 5 and 10 minutes compare to biases of 60 and 100%, respectively, independent of the catchments time of concentration.

General probability-matched relations between radar reflectivity and rain rate

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Wolff, David B.; Atlas, David

1993-01-01

An improved method for transforming radar-observed reflectivities Ze into rain rate R is presented. The method is based on a formulation of a Ze-R function constrained such that (1) the radar-retrieved pdf of R and all of its moments are identical to those determined from the gauges over a sufficiently large domain, and (2) the fraction of the time that it is raining above a low but still has an accurately measurable rain intensity is identical for both the radar and for simultaneous measurements of collocated gauges on average. Data measured by a 1.65-deg beamwidth C-band radar and 22 gauges located in the vicinity of Darwin, Australia, are used. The resultant Ze-R functions show a strong range dependence, especially for the rain regimes characterized by strong reflectivity gradients and substantial attenuation. The application of these novel Ze-R functions to the radar data produces excellent matches to the gauge measurements without any systematic bias.

Quantifying the quality of precipitation data from different sources

NASA Astrophysics Data System (ADS)

Leijnse, Hidde; Wauben, Wiel; Overeem, Aart; de Haij, Marijn

2015-04-01

There is an increasing demand for high-resolution rainfall data. The current manual and automatic networks of climate and meteorological stations provide high quality rainfall data, but they cannot provide the high spatial and temporal resolution required for many applications. This can only partly be solved by using remotely sensed data. It is therefore necessary to consider third-party data, such as rain gauges operated by amateurs and rainfall intensities from commercial cellular communication links. The quality of such third-party data is highly variable and generally lower than that of dedicated networks. Often, such data quality information is missing for third party data. In order to be able to use data from various sources it is vital that quantitative knowledge of the data quality is available. This holds for all data sources, including the rain gauges in the reference networks of climate and meteorological stations. Data quality information is generally either not available or very limited for third-party data sources. For most dedicated climate meteorological networks, this information is only available for the sensor in laboratory conditions. In many cases, however, a significant part of the measurement errors and uncertainties is determined by the siting and maintenance of the sensor, for which generally only qualitative information is available. Furthermore sensors may have limitations under specific conditions. We aim to quantify data quality for different data sources by performing analyses on collocated data sets. Here we present an intercomparison of two years of precipitation data from six different sources (manual rain gauge, automatic rain gauge, present weather sensor, weather radar, commercial cellular communication links, and Meteosat) at three different locations in the Netherlands. We use auxiliary meteorological data to determine if the quality is influenced by other variables (e.g. the temperature influencing the evaporation from the rain gauge). We use three techniques to compare the data sets: 1) direct comparison; 2) triple collocation (see Stoffelen, 1998); and 3) comparison of statistics. Stoffelen, A. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. Journal of Geophysical Research: Oceans (1978-2012), 103(C4), 7755-7766.

Statistical assessment and hydrological utility of the latest multi-satellite precipitation analysis IMERG in Ganjiang River basin

NASA Astrophysics Data System (ADS)

Li, Na; Tang, Guoqiang; Zhao, Ping; Hong, Yang; Gou, Yabin; Yang, Kai

2017-01-01

This study aims to statistically and hydrologically assess the hydrological utility of the latest Integrated Multi-satellitE Retrievals from Global Precipitation Measurement (IMERG) multi-satellite constellation over the mid-latitude Ganjiang River basin in China. The investigations are conducted at hourly and 0.1° resolutions throughout the rainy season from March 12 to September 30, 2014. Two high-quality quantitative precipitation estimation (QPE) datasets, i.e., a gauge-corrected radar mosaic QPE product (RQPE) and a highly dense network of 1200 rain gauges, are used as the reference. For the implementation of the study, first, we compare IMERG product and RQPE with rain gauge-interpolated data, respectively. The results indicate that both remote sensing products can estimate precipitation fairly well over the basin, while RQPE significantly outperforms IMERG product in almost all the studied cases. The correlation coefficients of RQPE (CC = 0.98 and CC = 0.67) are much higher than those of IMERG product (CC = 0.80 and CC = 0.33) at basin and grid scales, respectively. Then, the hydrological assessment is conducted with the Coupled Routing and Excess Storage (CREST) model under multiple parameterization scenarios, in which the model is calibrated using the rain gauge-interpolated data, RQPE, and IMERG products respectively. During the calibration period (from March 12 to May 31), the simulated streamflow based on rain gauge-interpolated data shows the highest Nash-Sutcliffe coefficient efficiency (NSCE) value (0.92), closely followed by the RQPE (NSCE = 0.84), while IMERG product performs barely acceptable (NSCE = 0.56). During the validation period (from June 1 to September 30), the three rainfall datasets are used to force the CREST model based on all the three calibrated parameter sets (i.e., nine combinations in total). RQPE outperforms rain gauge-interpolated data and IMERG product in all validation scenarios, possibly due to its advantageous capability in capturing high space-time variability of precipitation systems in the humid climate during the validation period. Overall, RQPE and rain gauge-interpolated data exhibit better performance compared with the newly available IMERG product, and RQPE is better than rain gauge-interpolated data to some extent due to the combination of both radar and rain gauge observations. IMERG-forced hourly CREST hydrologic model based on the Gauge- and RQPE-calibrated parameters performs well over Ganjiang River basin. Future studies should promote the hydrological application of RQPE datasets at global and local scales, and continuously improve IMERG algorithms.

Evaluation and correction of uncertainty due to Gaussian approximation in radar - rain gauge merging using kriging with external drift

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2016-12-01

It is widely recognised that merging radar rainfall estimates (RRE) with rain gauge data can improve the RRE and provide areal and temporal coverage that rain gauges cannot offer. Many methods to merge radar and rain gauge data are based on kriging and require an assumption of Gaussianity on the variable of interest. In particular, this work looks at kriging with external drift (KED), because it is an efficient, widely used, and well performing merging method. Rainfall, especially at finer temporal scale, does not have a normal distribution and presents a bi-modal skewed distribution. In some applications a Gaussianity assumption is made, without any correction. In other cases, variables are transformed in order to obtain a distribution closer to Gaussian. This work has two objectives: 1) compare different transformation methods in merging applications; 2) evaluate the uncertainty arising when untransformed rainfall data is used in KED. The comparison of transformation methods is addressed under two points of view. On the one hand, the ability to reproduce the original probability distribution after back-transformation of merged products is evaluated with qq-plots, on the other hand the rainfall estimates are compared with an independent set of rain gauge measurements. The tested methods are 1) no transformation, 2) Box-Cox transformations with parameter equal to λ=0.5 (square root), 3) λ=0.25 (square root - square root), and 4) λ=0.1 (almost logarithmic), 5) normal quantile transformation, and 6) singularity analysis. The uncertainty associated with the use of non-transformed data in KED is evaluated in comparison with the best performing product. The methods are tested on a case study in Northern England, using hourly data from 211 tipping bucket rain gauges from the Environment Agency and radar rainfall data at 1 km/5-min resolutions from the UK Met Office. In addition, 25 independent rain gauges from the UK Met Office were used to assess the merged products.

Assessment of TRMM 3B43 product for drought monitoring in Singapore

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Chua, Vivien P.; Tan, Kok Chooi; Brindha, K.

2017-10-01

Drought is one of the most hazardous natural disasters for human beings and the environment. Using only rain gauge is insufficient to monitor the drought pattern effectively as it impacts large areas. This situation is more critical on small island countries, with limited rain gauges for monitoring drought pattern over the ocean regions. This study aims to assess the capability of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B43 product in monitoring drought in Singapore from 1998 to 2014. The Standardized Precipitation Index (SPI) at various time-scales is used for identifying drought patterns. Results show moderate to good correlations between TMPA- 3B43 and rain gauges in the SPI estimations. Besides that, TMPA-3B43 exhibits a similar temporal drought behavior as the rain gauges. These findings indicate the TMPA 3B43 product as a very useful tool to study drought pattern over Singapore.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartholomew, Mary Jane

To improve the quantitative description of precipitation processes in climate models, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility deploys several types of rain gauges (MET, RAIN, and optical rain gauge [ORG] datastreams) as well as disdrometers (DISD and VDIS datastreams) at the Southern Great Plains (SGP) Site. This handbook deals specifically with the independent analog ORG (i.e., the ORG datastream).

Algorithm for Identifying Erroneous Rain-Gauge Readings

NASA Technical Reports Server (NTRS)

Rickman, Doug

2005-01-01

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

Rainfall Product Evaluation for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Amitai, E.; Wolff, D. B.; Robinson, M.; Silberstein, D. S.; Marks, D. A.; Kulie, M. S.; Fisher, B.; Einaudi, Franco (Technical Monitor)

2000-01-01

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.

Assessment of satellite rainfall products over the Andean plateau

NASA Astrophysics Data System (ADS)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a negative bias becomes positive for GSMaP. TMPA-3B42 Adjusted (Adj) version 7 demonstrates the best overall agreement with gauges in terms of correlation, rain rate distribution and bias. However, PERSIANN-Adj's bias in the southern part of the domain is very low.

Results of APL rain gauge network measurements in mid-Atlantic coast region and comparisons of distributions with CCIR models

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius; Gebo, Norman; Rowland, John

1988-01-01

In this effort are described cumulative rain rate distributions for a network of nine tipping bucket rain gauge systems located in the mid-Atlantic coast region in the vicinity of the NASA Wallops Flight Facility, Wallops Island, Virginia. The rain gauges are situated within a gridded region of dimensions of 47 km east-west by 70 km north-south. Distributions are presented for the individual site measurements and the network average for the year period June 1, 1986 through May 31, 1987. A previous six year average distribution derived from measurements at one of the site locations is also presented. Comparisons are given of the network average, the CCIR (International Radio Consultative Committee) climatic zone, and the CCIR functional model distributions, the latter of which approximates a log normal at the lower rain rate and a gamma function at the higher rates.

Estimating time and spatial distribution of snow water equivalent in the Hakusan area

NASA Astrophysics Data System (ADS)

Tanaka, K.; Matsui, Y.; Touge, Y.

2015-12-01

In the Sousei program, on-going Japanese research program for risk information on climate change, assessing the impact of climate change on water resources is attempted using the integrated water resources model which consists of land surface model, irrigation model, river routing model, reservoir operation model, and crop growth model. Due to climate change, reduction of snowfall amount, reduction of snow cover and change in snowmelt timing, change in river discharge are of increasing concern. So, the evaluation of snow water amount is crucial for assessing the impact of climate change on water resources in Japan. To validate the snow simulation of the land surface model, time and spatial distribution of the snow water equivalent was estimated using the observed surface meteorological data and RAP (Radar Analysis Precipitation) data. Target area is Hakusan. Hakusan means 'white mountain' in Japanese. Water balance of the Tedori River Dam catchment was checked with daily inflow data. Analyzed runoff was generally well for the period from 2010 to 2012. From the result for 2010-2011 winter, maximum snow water equivalent in the headwater area of the Tedori River dam reached more than 2000mm in early April. On the other hand, due to the underestimation of RAP data, analyzed runoff was under estimated from 2006 to 2009. This underestimation is probably not from the lack of land surface model, but from the quality of input precipitation data. In the original RAP, only the rain gauge data of JMA (Japan Meteorological Agency) were used in the analysis. Recently, other rain gauge data of MLIT (Ministry of Land, Infrastructure, Transport and Tourism) and local government have been added in the analysis. So, the quality of the RAP data especially in the mountain region has been greatly improved. "Reanalysis" of the RAP precipitation is strongly recommended using all the available off-line rain gauges information. High quality precipitation data will contribute to validate hydrological model, satellite based precipitation product, GCM output, etc.

Comparison of SWAT Model Water Balance Calibration Using NEXRAD and Surface Rain Gauge Data

USDA-ARS?s Scientific Manuscript database

The value of watershed-scale, water quality models to ecosystem management is increasingly evident as more programs adopt these tools to help assess the effectiveness of different management scenarios on the environment. The USDA-Conservation Effects Assessment Project (CEAP) is one such program whi...

Comparison of Flow Calibration Using NEXRAD and Surface Rain Gauge Data in ArcSWAT

USDA-ARS?s Scientific Manuscript database

The value of watershed-scale, water quality models to ecosystem management is increasingly evident as more programs adopt these tools to help assess the effectiveness of different management scenarios on the environment. The USDA-Conservation Effects Assessment Project (CEAP) is one such program whi...

Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

NASA Astrophysics Data System (ADS)

Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

2017-09-01

The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

NASA Astrophysics Data System (ADS)

Borup, Morten; Grum, Morten; Linde, Jens Jørgen; Mikkelsen, Peter Steen

2016-08-01

Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5-30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10-20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2-3 km away.

Uncertainties in TRMM-Era multisatellite-based tropical rainfall estimates over the Maritime Continent

NASA Astrophysics Data System (ADS)

Rauniyar, S. P.; Protat, A.; Kanamori, H.

2017-05-01

This study investigates the regional and seasonal rainfall rate retrieval uncertainties within nine state-of-the-art satellite-based rainfall products over the Maritime Continent (MC) region. The results show consistently larger differences in mean daily rainfall among products over land, especially over mountains and along coasts, compared to over ocean, by about 20% for low to medium rain rates and 5% for heavy rain rates. However, rainfall differences among the products do not exhibit any seasonal dependency over both surface types (land and ocean) of the MC region. The differences between products largely depends on the rain rate itself, with a factor 2 difference for light rain and 30% for intermediate and high rain rates over ocean. The rain-rate products dominated by microwave measurements showed less spread among themselves over ocean compared to the products dominated by infrared measurements. Conversely, over land, the rain gauge-adjusted post-real-time products dominated by microwave measurements produced the largest spreads, due to the usage of different gauge analyses for the bias corrections. Intercomparisons of rainfall characteristics of these products revealed large discrepancies in detecting the frequency and intensity of rainfall. These satellite products are finally evaluated at subdaily, daily, monthly, intraseasonal, and seasonal temporal scales against high-quality gridded rainfall observations in the Sarawak (Malaysia) region for the 4 year period 2000-2003. No single satellite-based rainfall product clearly outperforms the other products at all temporal scales. General guidelines are provided for selecting a product that could be best suited for a particular application and/or temporal resolution.

On using smoothing spline and residual correction to fuse rain gauge observations and remote sensing data

NASA Astrophysics Data System (ADS)

Huang, Chengcheng; Zheng, Xiaogu; Tait, Andrew; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Li, Tao; Wang, Zhonglei

2014-01-01

Partial thin-plate smoothing spline model is used to construct the trend surface.Correction of the spline estimated trend surface is often necessary in practice.Cressman weight is modified and applied in residual correction.The modified Cressman weight performs better than Cressman weight.A method for estimating the error covariance matrix of gridded field is provided.

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation

NASA Technical Reports Server (NTRS)

Ferriday, James G.; Avery, Susan K.

1994-01-01

A physically based algorithm sensitive to emission and scattering is used to estimate rainfall using the Special Sensor Microwave/Imager (SSM/I). The algorithm is derived from radiative transfer calculations through an atmospheric cloud model specifying vertical distributions of ice and liquid hydrometeors as a function of rain rate. The algorithm is structured in two parts: SSM/I brightness temperatures are screened to detect rainfall and are then used in rain-rate calculation. The screening process distinguishes between nonraining background conditions and emission and scattering associated with hydrometeors. Thermometric temperature and polarization thresholds determined from the radiative transfer calculations are used to detect rain, whereas the rain-rate calculation is based on a linear function fit to a linear combination of channels. Separate calculations for ocean and land account for different background conditions. The rain-rate calculation is constructed to respond to both emission and scattering, reduce extraneous atmospheric and surface effects, and to correct for beam filling. The resulting SSM/I rain-rate estimates are compared to three precipitation radars as well as to a dynamically simulated rainfall event. Global estimates from the SSM/I algorithm are also compared to continental and shipboard measurements over a 4-month period. The algorithm is found to accurately describe both localized instantaneous rainfall events and global monthly patterns over both land and ovean. Over land the 4-month mean difference between SSM/I and the Global Precipitation Climatology Center continental rain gauge database is less than 10%. Over the ocean, the mean difference between SSM/I and the Legates and Willmott global shipboard rain gauge climatology is less than 20%.

Rain gauge calibration and testing

NASA Technical Reports Server (NTRS)

Wilkerson, John

1994-01-01

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.

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Evaluating the catching performance of aerodynamic rain gauges through field comparisons and CFD modelling

NASA Astrophysics Data System (ADS)

Pollock, Michael; Colli, Matteo; Stagnaro, Mattia; Lanza, Luca; Quinn, Paul; Dutton, Mark; O'Donnell, Greg; Wilkinson, Mark; Black, Andrew; O'Connell, Enda

2016-04-01

Accurate rainfall measurement is a fundamental requirement in a broad range of applications including flood risk and water resource management. The most widely used method of measuring rainfall is the rain gauge, which is often also considered to be the most accurate. In the context of hydrological modelling, measurements from rain gauges are interpolated to produce an areal representation, which forms an important input to drive hydrological models and calibrate rainfall radars. In each stage of this process another layer of uncertainty is introduced. The initial measurement errors are propagated through the chain, compounding the overall uncertainty. This study looks at the fundamental source of error, in the rainfall measurement itself; and specifically addresses the largest of these, the systematic 'wind-induced' error. Snowfall is outside the scope. The shape of a precipitation gauge significantly affects its collection efficiency (CE), with respect to a reference measurement. This is due to the airflow around the gauge, which causes a deflection in the trajectories of the raindrops near the gauge orifice. Computational Fluid-Dynamic (CFD) simulations are used to evaluate the time-averaged airflows realized around the EML ARG100, EML SBS500 and EML Kalyx-RG rain gauges, when impacted by wind. These gauges have a similar aerodynamic profile - a shape comparable to that of a champagne flute - and they are used globally. The funnel diameter of each gauge, respectively, is 252mm, 254mm and 127mm. The SBS500 is used by the UK Met Office and the Scottish Environmental Protection Agency. Terms of comparison are provided by the results obtained for standard rain gauge shapes manufactured by Casella and OTT which, respectively, have a uniform and a tapered cylindrical shape. The simulations were executed for five different wind speeds; 2, 5, 7, 10 and 18 ms-1. Results indicate that aerodynamic gauges have a different impact on the time-averaged airflow patterns observed in the vicinity of the collector, compared to the standard gauge shapes. Both the air velocity and the turbulent kinetic energy fields present structures that may improve the interception of particles by the aerodynamic gauge collector. To provide empirical validation, a field-based experimental campaign was undertaken at four UK research stations to compare the results of aerodynamic and conventional gauges, mounted in juxtaposition. The reference measurement is recorded using a rain gauge pit, as specified by the WMO. The results appear to demonstrate how the effect of the wind on rainfall measurements is influenced by the gauge shape and the mounting height. Significant undercatch is observed compared to the reference measurement. Aerodynamic gauges mounted on the ground catch more rainfall than juxtaposed straight-sided gauges, in most instances. This appears to provide some preliminary validation of the CFD model. The indication that an aerodynamic profile improves the gauge catching capability could be confirmed by tracking the hydrometeor trajectories with a Lagrangian method, based on the available set of airflows; and investigating time-dependent aerodynamic features by means of dedicated CFD simulations. Furthermore, wind-tunnel tests could be carried out to provide more robust physical validation of the CFD model.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2014-10-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

NASA Astrophysics Data System (ADS)

Kumar, Brijesh; Patra, Kanhu Charan; Lakshmi, Venkat

2016-07-01

Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June-September or JJAS) from 2005-2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall. The detection of precipitation amount is strongly dependent on the topography. In the plains areas, TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimates the amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capture the high-intensity rain events but does well with low-intensity rain events in both hilly regions as well as the plain region. The continuous variable verification method shows better agreement of TRMM rainfall products with rain gauge data. TRMM fares better in the prediction of probability of occurrence of high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies that TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography.

Improving Radar QPE's in Complex Terrain for Improved Flash Flood Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Cifelli, R.; Streubel, D. P.; Reynolds, D.

2010-12-01

Quantitative Precipitation Estimation (QPE) is extremely challenging in regions of complex terrain due to a combination of issues related to sampling. In particular, radar beams are often blocked or scan above the liquid precipitation zone while rain gauge density is often too low to properly characterize the spatial distribution of precipitation. Due to poor radar coverage, rain gauge networks are used by the National Weather Service (NWS) River Forecast Centers as the principal source for QPE across the western U.S. The California Nevada River Forecast Center (CNRFC) uses point rainfall measurements and historical rainfall runoff relationships to derive river stage forecasts. The point measurements are interpolated to a 4 km grid using Parameter-elevation Regressions on Independent Slopes Model (PRISM) data to develop a gridded 6-hour QPE product (hereafter referred to as RFC QPE). Local forecast offices can utilize the Multi-sensor Precipitation Estimator (MPE) software to improve local QPE’s and thus local flash flood monitoring and prediction. MPE uses radar and rain gauge data to develop a combined QPE product at 1-hour intervals. The rain gauge information is used to bias correct the radar precipitation estimates so that, in situations where the rain gauge density and radar coverage are adequate, MPE can take advantage of the spatial coverage of the radar and the “ground truth” of the rain gauges to provide an accurate QPE. The MPE 1-hour QPE analysis should provide better spatial and temporal resolution for short duration hydrologic events as compared to 6-hour analyses. These hourly QPEs are then used to correct radar derived rain rates used by the Flash Flood Monitoring and Prediction (FFMP) software in forecast offices for issuance of flash flood warnings. Although widely used by forecasters across the eastern U.S., MPE is not used extensively by the NWS in the west. Part of the reason for the lack of use of MPE across the west is that there has been little quantitative evaluation of MPE performance in this region compared to simply using a gage only analysis. In this study, an evaluation of MPE and RFC QPE is performed in a portion of the CNRFC (including the Russian and American River basins) using an independent set of rain gauge data from the Hydrometeorology Testbed (HMT). Data from a precipitation event in January 2010 are used to establish the comparison methodology and for preliminary evaluation. For this multi-day event, it is shown that the RFC QPE shows generally better agreement with the HMT gauges compared to MPE in terms of storm total precipitation. However, the bias in RFC:MPE is shown to vary as a function of terrain and time. Moreover, for a subset of the HMT gauges in Sonoma county, the 1-hour MPE precipitation totals are found to be generally well correlated to the HMT gauge totals with correlation coefficients ranging from 0.6-0.9. For the Sonoma county gauges, the MPE product generally underestimates rainfall compared to HMT, probably as a consequence of low-level, orographically forced precipitation that was not well captured by the MPE radar analysis.

GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

2017-12-01

Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of ground-based sensors is being deployed during the 2017 monsoon season to better understand possible reasons for this discrepancy.

A Student-Centered Field Project Comparing NEXRAD and Rain Gauge Precipitation Values in Mountainous Terrain.

ERIC Educational Resources Information Center

Woltemade, Christopher J.; Stanitski-Martin, Diane

2002-01-01

Undergraduate students compared Next Generation Weather Radar (NEXRAD) estimates of storm total precipitation to measurements from a network of 20 rain gauges. Student researchers gained valuable experience in field data collection, global positioning systems (GPS), geographic information systems (GIS), Internet data access and downloading,…

Assessing satellite-based rainfall estimates in semi-arid watersheds using the USDA-ARS Walnut Gulch gauge network and TRMM-PR

USDA-ARS?s Scientific Manuscript database

The rain gauge network associated with the U.S. Department of Agriculture, Agricultural Research Service Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in-situ measurements and satellite-based instantaneous rain-rate estimat...

Validation of the TRMM Multi Satellite Rainfall Product 3B42 and estimation of scavenging coefficients for (131)I and (137)Cs using TRMM 3B42 rainfall data.

PubMed

Shrivastava, R; Dash, S K; Hegde, M N; Pradeepkumar, K S; Sharma, D N

2014-12-01

The TRMM rainfall product 3B42 is compared with rain gauge observations for Kaiga, India on monthly and seasonal time scales. This comparison is carried out for the years 2004-2007 spanning four monsoon seasons. A good correlation is obtained between the two data sets however; magnitude wise, the cumulative precipitation of the satellite product on monthly and seasonal time scales is deficient by almost 33-40% as compared to the rain gauge data. The satellite product is also compared with APHRODITE's Monsoon Asia data set on the same time scales. This comparison indicates a much better agreement since both these data sets represent an average precipitation over the same area. The scavenging coefficients for (131)I and (137)Cs are estimated using TRMM 3B42, rain gauge and APHRODITE data. The values obtained using TRMM 3B42 rainfall data compare very well with those obtained using rain gauge and APHRODITE data. Copyright © 2014 Elsevier Ltd. All rights reserved.

Validation of the H-SAF precipitation product H03 over Greece using rain gauge data

NASA Astrophysics Data System (ADS)

Feidas, H.; Porcu, F.; Puca, S.; Rinollo, A.; Lagouvardos, C.; Kotroni, V.

2018-01-01

This paper presents an extensive validation of the combined infrared/microwave H-SAF (EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management) precipitation product H03, for a 1-year period, using gauge observations from a relatively dense network of 233 stations over Greece. First, the quality of the interpolated data used to validate the precipitation product is assessed and a quality index is constructed based on parameters such as the density of the station network and the orography. Then, a validation analysis is conducted based on comparisons of satellite (H03) with interpolated rain gauge data to produce continuous and multi-categorical statistics at monthly and annual timescales by taking into account the different geophysical characteristics of the terrain (land, coast, sea, elevation). Finally, the impact of the quality of interpolated data on the validation statistics is examined in terms of different configurations of the interpolation model and the rain gauge network characteristics used in the interpolation. The possibility of using a quality index of the interpolated data as a filter in the validation procedure is also investigated. The continuous validation statistics show yearly root mean squared error (RMSE) and mean absolute error (MAE) corresponding to the 225 and 105 % of the mean rain rate, respectively. Mean error (ME) indicates a slight overall tendency for underestimation of the rain gauge rates, which takes large values for the high rain rates. In general, the H03 algorithm cannot retrieve very well the light (< 1 mm/h) and the convective type (>10 mm/h) precipitation. The poor correlation between satellite and gauge data points to algorithm problems in co-locating precipitation patterns. Seasonal comparison shows that retrieval errors are lower for cold months than in the summer months of the year. The multi-categorical statistics indicate that the H03 algorithm is able to discriminate efficiently the rain from the no rain events although a large number of rain events are missed. The most prominent feature is the very high false alarm ratio (FAR) (more than 70 %), the relatively low probability of detection (POD) (less than 40 %), and the overestimation of the rainy pixels. Although the different geophysical features of the terrain (land, coast, sea, elevation) and the quality of the interpolated data have an effect on the validation statistics, this, in general, is not significant and seems to be more distinct in the categorical than in the continuous statistics.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

Systematic Anomalies in Rainfall Intensity Estimates Over the Continental U.S.

NASA Technical Reports Server (NTRS)

Amitai, Eyal; Petersen, Walter Arthur; Llort, Xavier; Vasiloff, Steve

2010-01-01

Rainfall intensities during extreme events over the continental U.S. are compared for several advanced radar products. These products include: 1) TRMM spaceborne radar (PR) near surface estimates; 2) NOAA Next-Generation Quantitative Precipitation Estimation (QPE) very high-resolution (1 km) radar-only national mosaics (Q2); 3) very high-resolution instantaneous gauge adjusted radar national mosaics, which we have developed by applying gauge correction on the Q2 instantaneous radar-only products; and 4) several independent C-band dual-polarimetric radar-estimated rainfall samples collected with the ARMOR radar in northern Alabama. Though accumulated rainfall amounts are often similar, we find the satellite and the ground radar rain rate pdfs to be quite different. PR pdfs are shifted towards lower rain rates, implying a much larger stratiform/convective rain ratio than do ground radar products. The shift becomes more evident during strong continental convective storms and much less during tropical storms. Resolving the continental/maritime regime behavior and other large discrepancies between the products presents an important challenge. A challenge to improve our understanding of the source of the discrepancies, to determine the uncertainties of the estimates, and to improve remote-sensing estimates of precipitation in general.

A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield

PubMed Central

Ringard, Justine; Seyler, Frederique; Linguet, Laurent

2017-01-01

Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale. PMID:28621723

A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield.

PubMed

Ringard, Justine; Seyler, Frederique; Linguet, Laurent

2017-06-16

Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.

Assessing the accuracy of weather radar to track intense rain cells in the Greater Lyon area, France

NASA Astrophysics Data System (ADS)

Renard, Florent; Chapon, Pierre-Marie; Comby, Jacques

2012-01-01

The Greater Lyon is a dense area located in the Rhône Valley in the south east of France. The conurbation counts 1.3 million inhabitants and the rainfall hazard is a great concern. However, until now, studies on rainfall over the Greater Lyon have only been based on the network of rain gauges, despite the presence of a C-band radar located in the close vicinity. Consequently, the first aim of this study was to investigate the hydrological quality of this radar. This assessment, based on comparison of radar estimations and rain-gauges values concludes that the radar data has overall a good quality since 2006. Given this good accuracy, this study made a next step and investigated the characteristics of intense rain cells that are responsible of the majority of floods in the Greater Lyon area. Improved knowledge on these rainfall cells is important to anticipate dangerous events and to improve the monitoring of the sewage system. This paper discusses the analysis of the ten most intense rainfall events in the 2001-2010 period. Spatial statistics pointed towards straight and linear movements of intense rainfall cells, independently on the ground surface conditions and the topography underneath. The speed of these cells was found nearly constant during a rainfall event, but depend from event to ranges on average from 25 to 66 km/h.

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Assessment of measurement errors and dynamic calibration methods for three different tipping bucket rain gauges

USDA-ARS?s Scientific Manuscript database

Three different models of tipping bucket rain gauges (TBRs), viz. HS-TB3 (Hydrological Services Pty Ltd), ISCO-674 (Isco, Inc.) and TR-525 (Texas Electronics, Inc.), were calibrated in the lab to quantify measurement errors across a range of rainfall intensities (5 mm.h-1 to 250 mm.h-1) and three di...

The NASA GPM Iowa Flood Studies Experiment

NASA Astrophysics Data System (ADS)

Petersen, W. A.; Krajewski, W. F.; Peters-Lidard, C. D.; Rutledge, S. A.; Wolff, D. B.

2013-12-01

The overarching objective of NASA Global Precipitation Measurement Mission (GPM) integrated hydrologic ground validation (GV) is to provide a better understanding of the strengths and limitations of the satellite products, in the context of hydrologic applications. Accordingly, the NASA GPM GV program recently completed the first of several hydrology-oriented field efforts: the Iowa Flood Studies (IFloodS) experiment. IFloodS was conducted in central Iowa during the months of April-June, 2013. IFloodS science objectives focused on: a) The collection of reference multi-parameter radar, rain gauge, disdrometer, soil moisture, and hydrologic network measurements to quantify the physical character and space/time variability of rain (e.g., rates, drop size distributions, processes), land surface- state and hydrologic response; b) Application of the ground reference measurements to assessment of satellite-based rainfall estimation uncertainties; c) Propagation of both ground and satellite rainfall estimation uncertainties in coupled hydrologic prediction models to assess impacts on predictive skill; and d) Evaluation of rainfall properties such as rate and accumulation relative to basin hydrologic characteristics in modeled flood genesis. IFloodS observational objectives were achieved via deployments of the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars (operating in coordinated scanning modes), four University of Iowa X-band dual-polarimetric radars, four Micro Rain Radars, a network of 25 paired rain gauge platforms with attendant soil moisture and temperature probes, a network of six 2D Video and 14 Parsivel disdrometers, and 15 USDA-ARS rain gauge and soil-moisture stations (collaboration with the USDA-ARS and NASA Soil Moisture Active-Passive mission). The aforementioned platforms complemented existing operational WSR-88D S-band polarimetric radar, USGS streamflow, and Iowa Flood Center-affiliated stream monitoring and rainfall measurements. Coincident low-earth orbiter microwave, geostationary infrared, and derived satellite-algorithm rainfall products were also archived during the experiment. Twice daily NASA Unified Weather Research and Forecasting model simulations were conducted to provide weather forecast guidance and a coupled atmospheric/land-surface model simulation benchmark. During the experiment the IFloodS observational domain experienced heavy rainfall (> 250-300 mm) and significant flooding. Deployed observational assets, especially the research radars performed well throughout the experiment, sampling a broad range of precipitation system types including multi-day mixtures of rain and snow, warm-season mesoscale convective systems, and supercell thunderstorms. The variety of regimes and large rain accumulations sampled creates a rich source of data for testing both satellite products and coupled atmospheric, land system, and hydrologic models. In this study we will provide an overview of the IFloodS experiment, datasets, and preliminary observational results.

The extent of wind-induced undercatch in the UK winter storms of 2015

NASA Astrophysics Data System (ADS)

Pollock, Michael; Colli, Matteo; Stagnaro, Mattia; Quinn, Paul; Dutton, Mark; O'Donnell, Greg; Wilkinson, Mark; Black, Andrew; O'Connell, Enda; Lanza, Luca

2016-04-01

The most widely used device for measuring rainfall is the rain gauge, of which the tipping bucket (TBR) is the most prevalent type. Rain gauges are considered by many to be the most accurate method currently available. The data they produce are used in flood-forecasting and flood risk management, water resource management, hydrological modelling and evaluating impacts on climate change; to name but a few. Rain gauges may provide the most accurate measurement of rainfall at a point in space and time, but they are subject to errors - and some gauges are more prone than others. The most significant error is the 'wind-induced undercatch'. This is caused by the gauge itself contributing to an acceleration of the wind speed near the orifice, which disturbs and distorts the airflow. The trajectories of precipitation particles are affected, resulting in an undercatch. Results from Computational Fluid Dynamics (CFD) simulations, presented herein, describe in detail the physical processes contributing to this. High resolution field measurements of rainfall and wind are collected at four field research stations in the UK. Each site is equipped with juxtaposed rain gauges with different funnel profiles, in addition to a WMO reference pit rain gauge measurement. These data describe the rainfall measurement uncertainty. The sites were selected to represent the prevalent rainfall regimes observed in the UK. Two research stations are on the west coast; which is prone to frontal weather systems and storms swept in from the Atlantic, often enhanced by orography. Two are located in the east. Rural lowland and upland areas are represented, both in the west and the east. Urban sites will also have significant undercatch problems but are outside the scope of this study. Data from the four research stations are analysed for the 2015 winter storms which caused devastating flooding in the west of the UK, particularly Cumbria and the Scottish Borders, where two of the sites are located. An assessment of the effect of wind on the rainfall catch during these large storm events is presented for each research station. Based on a reference pit rain gauge, the undercatch for these events is calculated. The difference in rainfall catch between several types of rain gauge mounted at variable heights is also investigated. This work aims to demonstrate the importance of improving the accuracy of rainfall measurements, and to emphasise the need to provide an assessment of the measurement uncertainty. A knowledge gap exists in the understanding of precisely how physical phenomena are contributing to wind-induced undercatch. For instance, a priori, the effect of the wind on the rainfall catch will change depending upon the dimensions of the rain droplets. Rainfall 'type' and rainfall intensity may be able to inform corrections, but rigorous multi-variate statistical analysis of high resolution measurements will be key to the success of these procedures. As the spatio-temporal distribution of rainfall can be highly variable, and each measurement location is different; it is a challenging undertaking to understand and pin down the fundamental processes responsible for the wind-induced undercatch.

A laboratory evaluation of the influence of weighing gauges performance on extreme events statistics

NASA Astrophysics Data System (ADS)

Colli, Matteo; Lanza, Luca

2014-05-01

The effects of inaccurate ground based rainfall measurements on the information derived from rain records is yet not much documented in the literature. La Barbera et al. (2002) investigated the propagation of the systematic mechanic errors of tipping bucket type rain gauges (TBR) into the most common statistics of rainfall extremes, e.g. in the assessment of the return period T (or the related non-exceedance probability) of short-duration/high intensity events. Colli et al. (2012) and Lanza et al. (2012) extended the analysis to a 22-years long precipitation data set obtained from a virtual weighing type gauge (WG). The artificial WG time series was obtained basing on real precipitation data measured at the meteo-station of the University of Genova and modelling the weighing gauge output as a linear dynamic system. This approximation was previously validated with dedicated laboratory experiments and is based on the evidence that the accuracy of WG measurements under real world/time varying rainfall conditions is mainly affected by the dynamic response of the gauge (as revealed during the last WMO Field Intercomparison of Rainfall Intensity Gauges). The investigation is now completed by analyzing actual measurements performed by two common weighing gauges, the OTT Pluvio2 load-cell gauge and the GEONOR T-200 vibrating-wire gauge, since both these instruments demonstrated very good performance under previous constant flow rate calibration efforts. A laboratory dynamic rainfall generation system has been arranged and validated in order to simulate a number of precipitation events with variable reference intensities. Such artificial events were generated basing on real world rainfall intensity (RI) records obtained from the meteo-station of the University of Genova so that the statistical structure of the time series is preserved. The influence of the WG RI measurements accuracy on the associated extreme events statistics is analyzed by comparing the original intensity-duration-frequency (IDF) curves with those obtained from the measuring of the simulated rain events. References: Colli, M., L.G. Lanza, and P. La Barbera, (2012). Weighing gauges measurement errors and the design rainfall for urban scale applications, 9th International Workshop On Precipitation In Urban Areas, 6-9 December, 2012, St. Moritz, Switzerland Lanza, L.G., M. Colli, and P. La Barbera (2012). On the influence of rain gauge performance on extreme events statistics: the case of weighing gauges, EGU General Assembly 2012, April 22th, Wien, Austria La Barbera, P., L.G. Lanza, and L. Stagi, (2002). Influence of systematic mechanical errors of tipping-bucket rain gauges on the statistics of rainfall extremes. Water Sci. Techn., 45(2), 1-9.

Real-Time Tracking of the Extreme Rainfall of Hurricanes Harvey, Irma, and Maria using UCI CHRS's iRain System

NASA Astrophysics Data System (ADS)

Shearer, E. J.; Nguyen, P.; Ombadi, M.; Palacios, T.; Huynh, P.; Furman, D.; Tran, H.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.; Logan, W. S.

2017-12-01

During the 2017 hurricane season, three major hurricanes-Harvey, Irma, and Maria-devastated the Atlantic coast of the US and the Caribbean Islands. Harvey set the record for the rainiest storm in continental US history, Irma was the longest-lived powerful hurricane ever observed, and Maria was the costliest storm in Puerto Rican history. The recorded maximum precipitation totals for these storms were 65, 16, and 20 inches respectively. These events provided the Center for Hydrometeorology and Remote Sensing (CHRS) an opportunity to test its global real-time satellite precipitation observation system, iRain, for extreme storm events. The iRain system has been under development through a collaboration between CHRS at the University of California, Irvine (UCI) and UNESCO's International Hydrological Program (IHP). iRain provides near real-time high resolution (0.04°, approx. 4km) global (60°N - 60°S) satellite precipitation data estimated by the PERSIANN-Cloud Classification System (PERSIANN-CCS) algorithm developed by the scientists at CHRS. The user-interactive and web-accessible iRain system allows users to visualize and download real-time global satellite precipitation estimates and track the development and path of the current 50 largest storms globally from data generated by the PERSIANN-CCS algorithm. iRain continuously proves to be an effective tool for measuring real-time precipitation amounts of extreme storms-especially in locations that do not have extensive rain gauge or radar coverage. Such areas include large portions of the world's oceans and over continents such as Africa and Asia. CHRS also created a mobile app version of the system named "iRain UCI", available for iOS and Android devices. During these storms, real-time rainfall data generated by PERSIANN-CCS was consistently comparable to radar and rain gauge data. This presentation evaluates iRain's efficiency as a tool for extreme precipitation monitoring and provides an evaluation of the PERSIANN-CCS real-time rainfall estimates during Hurricanes Harvey, Irma, and Maria in relation to radar and rain gauge data using continuous (correlation, root mean square error, and bias) and categorical (POD and FAR) indices. These results present the relative skill of PERSIANN-CCS real-time data to radar and rain gauge data.

Improving rainfall estimation from commercial microwave links using METEOSAT SEVIRI cloud cover information

NASA Astrophysics Data System (ADS)

Boose, Yvonne; Doumounia, Ali; Chwala, Christian; Moumouni, Sawadogo; Zougmoré, François; Kunstmann, Harald

2017-04-01

The number of rain gauges is declining worldwide. A recent promising method for alternative precipitation measurements is to derive rain rates from the attenuation of the microwave signal between remote antennas of mobile phone base stations, so called commercial microwave links (CMLs). In European countries, such as Germany, the CML technique can be used as a complementary method to the existing gauge and radar networks improving their products, for example, in mountainous terrain and urban areas. In West African countries, where a dense gauge or radar network is absent, the number of mobile phone users is rapidly increasing and so are the CML networks. Hence, the CML-derived precipitation measurements have high potential for applications such as flood warning and support of agricultural planning in this region. For typical CML bandwidths (10-40 GHz), the relationship of attenuation to rain rate is quasi-linear. However, also humidity, wet antennas or electronic noise can lead to signal interference. To distinguish these fluctuations from actual attenuation due to rain, a temporal wet (rain event occurred)/ dry (no rain event) classification is usually necessary. In dense CML networks this is possible by correlating neighboring CML time series. Another option is to use the correlation between signal time series of different frequencies or bidirectional signals. The CML network in rural areas is typically not dense enough for correlation analysis and often only one polarization and one frequency are available along a CML. In this work we therefore use cloud cover information derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer onboard the geostationary satellite METEOSAT for a wet (pixels along link are cloud covered)/ dry (no cloud along link) classification. We compare results for CMLs in Burkina Faso and Germany, which differ meteorologically (rain rate and duration, droplet size distributions) and technically (CML frequencies, lengths, signal level) and use rain gauge data as ground truth for validation.

Validation of a global satellite rainfall product for real time monitoring of meteorological extremes

NASA Astrophysics Data System (ADS)

Cánovas-García, Fulgencio; García-Galiano, Sandra; Karbalaee, Negar

2017-10-01

The real time monitoring of storms is important for the management and prevention of flood risks. However, in the southeast of Spain, it seems that the density of the rain gauge network may not be sufficient to adequately characterize the rainfall spatial distribution or the high rainfall intensities that are reached during storms. Satellite precipitation products such as PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) could be used to complement the automatic rain gauge networks and so help solve this problem. However, the PERSIANN-CCS product has only recently become available, so its operational validity for areas such as south-eastern Spain is not yet known. In this work, a methodology for the hourly validation of PERSIANN-CCS is presented. We used the rain gauge stations of the SIAM (Sistema de Información Agraria de Murcia) network to study three storms with a very high return period. These storms hit the east and southeast of the Iberian Peninsula and resulted in the loss of human life, major damage to agricultural crops and a strong impact on many different types of infrastructure. The study area is the province of Murcia (Region of Murcia), located in the southeast of the Iberian Peninsula, covering an area of more than 11,000 km2 and with a population of almost 1.5 million. In order to validate the PERSIANN-CCS product for these three storms, contrasts were made with the hyetographs registered by the automatic rain gauges, analyzing statistics such as bias, mean square difference and Pearson's correlation coefficient. Although in some cases the temporal distribution of rainfall was well captured by PERSIANN-CCS, in several rain gauges high intensities were not properly represented. The differences were strongly correlated with the rain gauge precipitation, but not with satellite-obtained rainfall. The main conclusion concerns the need for specific local calibration for the study area if PERSIANN-CCS is to be used as an operational tool for the monitoring of extreme meteorological phenomena.

Measurement accuracy of weighing and tipping-bucket rainfall intensity gauges under dynamic laboratory testing

NASA Astrophysics Data System (ADS)

Colli, M.; Lanza, L. G.; La Barbera, P.; Chan, P. W.

2014-07-01

The contribution of any single uncertainty factor in the resulting performance of infield rain gauge measurements still has to be comprehensively assessed due to the high number of real world error sources involved, such as the intrinsic variability of rainfall intensity (RI), wind effects, wetting losses, the ambient temperature, etc. In recent years the World Meteorological Organization (WMO) addressed these issues by fostering dedicated investigations, which revealed further difficulties in assessing the actual reference rainfall intensity in the field. This work reports on an extensive assessment of the OTT Pluvio2 weighing gauge accuracy when measuring rainfall intensity under laboratory dynamic conditions (time varying reference flow rates). The results obtained from the weighing rain gauge (WG) were also compared with a MTX tipping-bucket rain gauge (TBR) under the same test conditions. Tests were carried out by simulating various artificial precipitation events, with unsteady rainfall intensity, using a suitable dynamic rainfall generator. Real world rainfall data measured by an Ogawa catching-type drop counter at a field test site located within the Hong Kong International Airport (HKIA) were used as a reference for the artificial rain generation system. Results demonstrate that the differences observed between the laboratory and field performance of catching-type gauges are only partially attributable to the weather and operational conditions in the field. The dynamics of real world precipitation events is responsible for a large part of the measurement errors, which can be accurately assessed in the laboratory under controlled environmental conditions. This allows for new testing methodologies and the development of instruments with enhanced performance in the field.

Evaluation and intercomparison of GPM-IMERG and TRMM 3B42 daily precipitation products over Greece

NASA Astrophysics Data System (ADS)

Kazamias, A. P.; Sapountzis, M.; Lagouvardos, K.

2017-09-01

Accurate precipitation data at high temporal and spatial resolutions are needed for numerous applications in hydrology, water resources management and flood risk management. Satellite-based precipitation estimations/products offer a potential alternative source of rainfall data for regions with sparse rain gauge network. The recently launched Global Precipitation Measurement (GPM) mission is the successor of Tropical Rainfall Measuring Mission (TRMM) providing global precipitation estimates at spatial resolution of 0.1 degree x 0.1 degree and half-hourly temporal resolution. This study aims at evaluating the accuracy of the Integrated Multi-satellite Retrievals for GPM (IMERG) near-real-time daily product (GPM-3IMERGDL) against rain gauge observations from a network of stations distributed across Greece for the year 2016. Moreover, the GPM-IMERG product is also compared with its predecessor, the Version-7 near-real-time (3B42RT) daily product of TRMM Multisatellite Precipitation Analysis (TMPA). Several statistical metrics are used to quantitatively evaluate the performance of the satellite-based precipitation estimates against rain gauge observations. In addition, categorical statistical indices are used to assess rain detection capabilities of the two satellite products. The GPM-IMERG daily product shows reasonable agreement (CC=0.60) against rain gauge observations, with the exception of coastal areas in which low correlations are achieved. The GPM-IMERG daily precipitation product tends to overestimate rainfall, especially in complex terrain areas with high annual precipitation. In particular, rainfall estimates in western Greece have a strong positive bias. On the other hand, the TRMM 3B42 product shows low correlation (CC=0.45) against rain gauge observations and slightly underestimates rainfall. This study is a first attempt to evaluate and compare the newly introduced GPM-IMERG and the TRMM 3B42 rainfall products at daily timescale over Greece.

Predicting urban stormwater runoff with quantitative precipitation estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Pastorek, Jaroslav; Fencl, Martin; Stránský, David; Rieckermann, Jörg; Bareš, Vojtěch

2017-04-01

Reliable and representative rainfall data are crucial for urban runoff modelling. However, traditional precipitation measurement devices often fail to provide sufficient information about the spatial variability of rainfall, especially when heavy storm events (determining design of urban stormwater systems) are considered. Commercial microwave links (CMLs), typically very dense in urban areas, allow for indirect precipitation detection with desired spatial and temporal resolution. Fencl et al. (2016) recognised the high bias in quantitative precipitation estimates (QPEs) from CMLs which significantly limits their usability and, in order to reduce the bias, suggested a novel method for adjusting the QPEs to existing rain gauge networks. Studies evaluating the potential of CMLs for rainfall detection so far focused primarily on direct comparison of the QPEs from CMLs to ground observations. In contrast, this investigation evaluates the suitability of these innovative rainfall data for stormwater runoff modelling on a case study of a small ungauged (in long-term perspective) urban catchment in Prague-Letňany, Czech Republic (Fencl et al., 2016). We compare the runoff measured at the outlet from the catchment with the outputs of a rainfall-runoff model operated using (i) CML data adjusted by distant rain gauges, (ii) rainfall data from the distant gauges alone and (iii) data from a single temporary rain gauge located directly in the catchment, as it is common practice in drainage engineering. Uncertainties of the simulated runoff are analysed using the Bayesian method for uncertainty evaluation incorporating a statistical bias description as formulated by Del Giudice et al. (2013). Our results show that adjusted CML data are able to yield reliable runoff modelling results, primarily for rainfall events with convective character. Performance statistics, most significantly the timing of maximal discharge, reach better (less uncertain) values with the adjusted CML data than with the distant rain gauges. When the relative error of the volume discharged during the maximum flow period is concerned, the adjusted CMLs perform even better than the rain gauge in the catchment. This seem to be very promising, especially for urban catchments with sparse rain gauge networks. References: Del Giudice, D., Honti, M., Scheidegger, A., Albert, C., Reichert, P., and Rieckermann, J. 2013. Improving uncertainty estimation in urban hydrological modeling by statistically describing bias. Hydrology and Earth System Sciences 17, 4209-4225. Fencl, M., Dohnal, M., Rieckermann, J., and Bareš, V. 2016. Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016- 397, in review. Acknowledgements to the Czech Science Foundation projects No. 14-22978S and No. 17-16389S.

Disdrometer and Tipping Bucket Rain Gauge Handbook

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartholomew. MJ

2009-12-01

The Distromet disdrometer model RD-80 and NovaLynx tipping bucket rain gauge model 260-2500E-12 are two devices deployed a few meters apart to measure the character and amount of liquid precipitation. The main purpose of the disdrometer is to measure drop size distribution, which it does over 20 size classes from 0.3 mm to 5.4 mm. The data from both instruments can be used to determine rain rate. The disdrometer results can also be used to infer several properties including drop number density, radar reflectivity, liquid water content, and energy flux. Two coefficients, N0 and Λ, from an exponential fit betweenmore » drop diameter and drop number density, are routinely calculated. Data are collected once a minute. The instruments make completely different kinds of measurements. Rain that falls on the disdrometer sensor moves a plunger on a vertical axis. The disdrometer transforms the plunger motion into electrical impulses whose strength is proportional to drop diameter. The rain gauge is the conventional tipping bucket type. Each tip collects an amount equivalent to 0.01 in. of water, and each tip is counted by a data acquisition system anchored by a Campbell CR1000 data logger.« less

Rainfall estimates for hydrological models: Comparing rain gauge, radar and microwave link data as input for the Wageningen Lowland Runoff Simulator (WALRUS)

NASA Astrophysics Data System (ADS)

Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko

2015-04-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Estimation of Rain Intensity Spectra over the Continental US Using Ground Radar-Gauge Measurements

NASA Technical Reports Server (NTRS)

Lin, Xin; Hou, Arthur Y.

2013-01-01

A high-resolution surface rainfall product is used to estimate rain characteristics over the continental US as a function of rain intensity. By defining each data at 4-km horizontal resolutions and 1-h temporal resolutions as an individual precipitating/nonprecipitating sample, statistics of rain occurrence and rain volume including their geographical and seasonal variations are documented. Quantitative estimations are also conducted to evaluate the impact of missing light rain events due to satellite sensors' detection capabilities. It is found that statistics of rain characteristics have large seasonal and geographical variations across the continental US. Although heavy rain events (> 10 mm/hr.) only occupy 2.6% of total rain occurrence, they may contribute to 27% of total rain volume. Light rain events (< 1.0 mm/hr.), occurring much more frequently (65%) than heavy rain events, can also make important contributions (15%) to the total rain volume. For minimum detectable rain rates setting at 0.5 and 0.2 mm/hr which are close to sensitivities of the current and future space-borne precipitation radars, there are about 43% and 11% of total rain occurrence below these thresholds, and they respectively represent 7% and 0.8% of total rain volume. For passive microwave sensors with their rain pixel sizes ranging from 14 to 16 km and the minimum detectable rain rates around 1 mm/hr., the missed light rain events may account for 70% of train occurrence and 16% of rain volume. Statistics of rain characteristics are also examined on domains with different temporal and spatial resolutions. Current issues in estimates of rain characteristics from satellite measurements and model outputs are discussed.

Testing geostatistical methods to combine radar and rain gauges for precipitation mapping in a mountainous region

NASA Astrophysics Data System (ADS)

Erdin, R.; Frei, C.; Sideris, I.; Kuensch, H.-R.

2010-09-01

There is an increasing demand for accurate mapping of precipitation at a spatial resolution of kilometers. Radar and rain gauges - the two main precipitation measurement systems - exhibit complementary strengths and weaknesses. Radar offers high spatial and temporal resolution but lacks accuracy of absolute values, whereas rain gauges provide accurate values at their specific point location but suffer from poor spatial representativeness. Methods of geostatistical mapping have been proposed to combine radar and rain gauge data for quantitative precipitation estimation (QPE). The aim is to combine the respective strengths and compensate for the respective weaknesses of the two observation platforms. Several studies have demonstrated the potential of these methods over topography of moderate complexity, but their performance remains unclear for high-mountain regions where rainfall patterns are complex, the representativeness of rain gauge measurements is limited and radar observations are obstructed. In this study we examine the potential and limitations of two frequently used geostatistical mapping methods for the territory of Switzerland, where the mountain chain of the Alps poses particular challenges to QPE. The two geostatistical methods explored are kriging with external drift (KED) using radar as drift variable and ordinary kriging of radar errors (OKRE). The radar data is a composite from three C-band radars using a constant Z-R relationship, advanced correction processings for visibility, ground clutter and beam shielding and a climatological bias adjustment. The rain gauge data originates from an automatic network with a typical inter-station distance of 25 km. Both combination methods are applied to a set of case examples representing typical rainfall situations in the Alps with their inherent challenges at daily and hourly time resolution. The quality of precipitation estimates is assessed by several skill scores calculated from cross validation errors at gauge locations. These scores assess different characteristics such as bias, distinction between dry and wet areas (HK, SLEEPS), accuracy of values at wet locations (SCATTER) and overall performance (RMSE, MAD). Special attention is paid to the subject of appropriate case-dependent transformation of variables in order to fulfill model assumptions. Our analyses show that geostatistical merging techniques can provide significant added value compared to pure radar and pure rain gauge data - also in mountainous terrain. Yet, the high a-priori quality of the radar product may have been essential for the good performance of methods. The comparison between the two combination methods shows better results in general for KED, the more flexible of the two methods. However, there are features, such as the differentiation between wet and dry areas (HK), and situations, such as small isolated convective cells, where OKRE outperforms KED. Our discussion conveys interesting insights into the potential and limitations of the two analyzed methods and leads to suggestions for further improvements of combination techniques.

Towards combining GPM and MFG observations to monitor near real time heavy precipitation at fine scale over India and nearby oceanic regions

NASA Astrophysics Data System (ADS)

Mishra, Anoop; Rafiq, Mohammd

2017-12-01

This is the first attempt to merge highly accurate precipitation estimates from Global Precipitation Measurement (GPM) with gap free satellite observations from Meteosat to develop a regional rainfall monitoring algorithm to estimate heavy rainfall over India and nearby oceanic regions. Rainfall signature is derived from Meteosat observations and is co-located against rainfall from GPM to establish a relationship between rainfall and signature for various rainy seasons. This relationship can be used to monitor rainfall over India and nearby oceanic regions. Performance of this technique was tested by applying it to monitor heavy precipitation over India. It is reported that our algorithm is able to detect heavy rainfall. It is also reported that present algorithm overestimates rainfall areal spread as compared to rain gauge based rainfall product. This deficiency may arise from various factors including uncertainty caused by use of different sensors from different platforms (difference in viewing geometry from MFG and GPM), poor relationship between warm rain (light rain) and IR brightness temperature, and weak characterization of orographic rain from IR signature. We validated hourly rainfall estimated from the present approach with independent observations from GPM. We also validated daily rainfall from this approach with rain gauge based product from India Meteorological Department (IMD). Present technique shows a Correlation Coefficient (CC) of 0.76, a bias of -2.72 mm, a Root Mean Square Error (RMSE) of 10.82 mm, Probability of Detection (POD) of 0.74, False Alarm Ratio (FAR) of 0.34 and a Skill score of 0.36 with daily rainfall from rain gauge based product of IMD at 0.25° resolution. However, FAR reduces to 0.24 for heavy rainfall events. Validation results with rain gauge observations reveal that present technique outperforms available satellite based rainfall estimates for monitoring heavy rainfall over Indian region.

Rainfall Measurement with a Ground Based Dual Frequency Radar

NASA Technical Reports Server (NTRS)

Takahashi, Nobuhiro; Horie, Hiroaki; Meneghini, Robert

1997-01-01

Dual frequency methods are one of the most useful ways to estimate precise rainfall rates. However, there are some difficulties in applying this method to ground based radars because of the existence of a blind zone and possible error in the radar calibration. Because of these problems, supplemental observations such as rain gauges or satellite link estimates of path integrated attenuation (PIA) are needed. This study shows how to estimate rainfall rate with a ground based dual frequency radar with rain gauge and satellite link data. Applications of this method to stratiform rainfall is also shown. This method is compared with single wavelength method. Data were obtained from a dual frequency (10 GHz and 35 GHz) multiparameter radar radiometer built by the Communications Research Laboratory (CRL), Japan, and located at NASA/GSFC during the spring of 1997. Optical rain gauge (ORG) data and broadcasting satellite signal data near the radar t location were also utilized for the calculation.

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

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Bringi, V. N.; Gatlin, Patrick; Phillips, Dustin; Schwaller, Mathew; Tokay, Ali; Wingo, Mathew; Wolff, David

2010-01-01

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.

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

PubMed

Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

2009-01-01

In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

Developing Methods For Linking Surficial Aquifers With Localized Rainfall Data

NASA Astrophysics Data System (ADS)

Lafrenz, W. B.; van Gaalen, J. F.

2008-12-01

Water level hydrographs of the surficial aquifer can be evaluated to identify both the cause and consequence of water supply development. Rainfall, as a source of direct recharge and as a source of delayed or compounded recharge, is often the largest influence on surficial aquifer water level responses. It is clear that proximity of the rain gauge to the observation well is a factor in the degree of correlation, but in central Florida, USA, rainfall patterns change seasonally, with latitude, and with distance from the coast . Thus, for a location in central Florida, correlation of rain events with observed hydrograph responses depends on both distance and direction from an observation well to a rain gauge. In this study, we examine the use of extreme value analysis as a method of selecting the best rainfall data set for describing a given surficial aquifer monitor well. A surficial aquifer monitor well with a substantial suite of data is compared to a series of rainfall data sets from gauges ranging from meters to tens of kilometers in distance from the monitor well. The gauges vary in a wide range of directions from the monitor well in an attempt to identify both a method for rainfall gauge selection to be associated with the monitor well. Each rainfall gauge is described by a correlation coefficient with respect to the surficial aquifer water level data.

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

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Meyer, Paul J.; Guillory, Anthony R.; Stellman, Keith; Limaye, Ashutosh; Arnold, James E. (Technical Monitor)

2002-01-01

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.

Uncertainties on the definition of critical rainfall patterns for debris-flows triggering. Results from the Rebaixader monitoring site (Central Pyrenees)

NASA Astrophysics Data System (ADS)

Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc

2015-04-01

Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the catchment may be considered useful or not to describe the rainfall depending on the type of rainfall. For widespread rainfalls, further rain gauges can give a reliable measurement, because the spatial correlation decreases slowly with the distance between the rain gauge and the debris-flow initiation area. Contrarily, local storm cells show higher space-time variability and, therefore, representative rainfall measurements are obtained only by the closest rain gauges. In conclusion, the definition of rainfall thresholds is a delicate task. When the rainfall records are coming from gauges that are outside the catchment under consideration, the data should be carefully analysed and crosschecked with radar data (especially for small convective cells).

UC Irvine CHRS iRain - An Integrated System for Global Real-time Precipitation Observation

NASA Astrophysics Data System (ADS)

Tran, H.; Nguyen, P.; Huynh, P.; Palacios, T.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.

2016-12-01

CHRS iRain developed by the Center for Hydrometeorology and Remote Sensing (CHRS), University of California, Irvine is an integrated system for global real-time rainfall observation and visualization using multiple data sources from satellites, radars, gauges, and crowd sourcing. Its backbone is the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System (PERSIANN-CCS, Hong et al. 2004). Apart from using traditional PERSIANN technique (Hsu et al. 1997), the PERSIANN-CCS also applies image processing and pattern recognition techniques, which significantly improve its accuracy as well as its temporal and spatial resolution (in hourly and 4 km x 4 km respectively). Although satellite-based precipitation products are developing fast, they are still relatively new compared with other precipitation observations by traditional measuring methods, such as radar or rain gauges. CHRS iRain also provides hourly precipitation information from NCEP Stage IV multi-sensor (radar + gauges) products and gauges with over 2000 NOAA River Forecast Center stations. On the website, users can retrieve data of the most recent 72 hour precipitation over different spatial regions regarding their own interests such as grid coordinate, rectangle, watershed, basin, political division, and country. CHRS iRain is a useful tool that provides important global rainfall information for water resources management and decision making for natural disasters such as flash floods, urban flooding, and river flooding. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institue for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

A real-time automated quality control of rain gauge data based on multiple sensors

NASA Astrophysics Data System (ADS)

qi, Y.; Zhang, J.

2013-12-01

Precipitation is one of the most important meteorological and hydrological variables. Automated rain gauge networks provide direct measurements of precipitation and have been used for numerous applications such as generating regional and national precipitation maps, calibrating remote sensing data, and validating hydrological and meteorological model predictions. Automated gauge observations are prone to a variety of error sources (instrument malfunction, transmission errors, format changes), and require careful quality controls (QC). Many previous gauge QC techniques were based on neighborhood checks within the gauge network itself and the effectiveness is dependent on gauge densities and precipitation regimes. The current study takes advantage of the multi-sensor data sources in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) system and developes an automated gauge QC scheme based the consistency of radar hourly QPEs and gauge observations. Error characteristics of radar and gauge as a function of the radar sampling geometry, precipitation regimes, and the freezing level height are considered. The new scheme was evaluated by comparing an NMQ national gauge-based precipitation product with independent manual gauge observations. Twelve heavy rainfall events from different seasons and areas of the United States are selected for the evaluation, and the results show that the new NMQ product with QC'ed gauges has a more physically spatial distribution than the old product. And the new product agrees much better statistically with the independent gauges.

Radar-rain-gauge rainfall estimation for hydrological applications in small catchments

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Chiaravalloti, Francesco; Procopio, Antonio

2017-07-01

The accurate evaluation of the precipitation's time-spatial structure is a critical step for rainfall-runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall-runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Travis, James E.

2013-01-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

An Experimental Study of Small-Scale Variability of Raindrop Size Distribution

NASA Technical Reports Server (NTRS)

Tokay, Ali; Bashor, Paul G.

2010-01-01

An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss-Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported5%more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm/h, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.

Comparison Of Quantitative Precipitation Estimates Derived From Rain Gauge And Radar Derived Algorithms For Operational Flash Flood Support.

NASA Astrophysics Data System (ADS)

Streubel, D. P.; Kodama, K.

2014-12-01

To provide continuous flash flood situational awareness and to better differentiate severity of ongoing individual precipitation events, the National Weather Service Research Distributed Hydrologic Model (RDHM) is being implemented over Hawaii and Alaska. In the implementation process of RDHM, three gridded precipitation analyses are used as forcing. The first analysis is a radar only precipitation estimate derived from WSR-88D digital hybrid reflectivity, a Z-R relationship and aggregated into an hourly ¼ HRAP grid. The second analysis is derived from a rain gauge network and interpolated into an hourly ¼ HRAP grid using PRISM climatology. The third analysis is derived from a rain gauge network where rain gauges are assigned static pre-determined weights to derive a uniform mean areal precipitation that is applied over a catchment on a ¼ HRAP grid. To assess the effect of different QPE analyses on the accuracy of RDHM simulations and to potentially identify a preferred analysis for operational use, each QPE was used to force RDHM to simulate stream flow for 20 USGS peak flow events. An evaluation of the RDHM simulations was focused on peak flow magnitude, peak flow timing, and event volume accuracy to be most relevant for operational use. Results showed RDHM simulations based on the observed rain gauge amounts were more accurate in simulating peak flow magnitude and event volume relative to the radar derived analysis. However this result was not consistent for all 20 events nor was it consistent for a few of the rainfall events where an annual peak flow was recorded at more than one USGS gage. Implications of this indicate that a more robust QPE forcing with the inclusion of uncertainty derived from the three analyses may provide a better input for simulating extreme peak flow events.

Syzygies, Pluricanonical Maps, and the Birational Geometry of Varieties of Maximal Albanese Dimension

NASA Astrophysics Data System (ADS)

Tesfagiorgis, Kibrewossen B.

Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products in mountainous regions. The present work develops an approach to seamlessly blend satellite, available radar, climatological and gauge precipitation products to fill gaps in ground-based radar precipitation field. To mix different precipitation products, the error of any of the products relative to each other should be removed. For bias correction, the study uses a new ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar-gauge precipitation product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. In addition to biases, sometimes there is also spatial error between the radar and satellite precipitation estimates; one of them has to be geometrically corrected with reference to the other. A set of corresponding raining points between SPE and radar products are selected to apply linear registration using a regularized least square technique to minimize the dislocation error in SPEs with respect to available radar products. A weighted Successive Correction Method (SCM) is used to make the merging between error corrected satellite and radar precipitation estimates. In addition to SCM, we use a combination of SCM and Bayesian spatial method for merging the rain gauges and climatological precipitation sources with radar and SPEs. We demonstrated the method using two satellite-based, CPC Morphing (CMORPH) and Hydro-Estimator (HE), two radar-gauge based, Stage-II and ST-IV, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over different geographical locations of the United States. Results show that: (a) the method of ensembles helped reduce biases in SPEs significantly; (b) the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements .The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the operational meteorology and hydrology community.

Implication of Intrastorm Rainfall-Canopy Interaction on Interception Performance of Broadleaf Evergreen Shrubs in Urban Setting

NASA Astrophysics Data System (ADS)

Yerk, W.; Montalto, F. A.

2014-12-01

Because of its ability to intercept a portion of rainfall, vegetated canopy has a significant influence on the urban hydrological cycle. In turn, urban watersheds, characterized by large impervious areas, have an enormous and often adverse impact on receiving waters. However, most historical interception research has been dedicated to forest canopies. The goal of our research was to quantify rainfall partitioning by isolated evergreen canopies in an urban setting. Two years of the field experiment involved three exemplars of Cherry Laurel (Prunus laurocerasus'Otto Luyken'.) Each plant had ten rain gauges to measure throughfall with a five second sampling frequency. A number of preventive techniques were introduced to minimize the gauges' errors (e.g., splash-in, splash-out and excessive wetting.) Leaf area index was measured manually. We estimated the canopy storage capacity to be less than 0.5 mm. An on-site automated weather station provided meteorological data. Cumulative interception loss for the periods of August-December 2013 and April-July 2014 was 51%. Phenological change did not show a stable pattern of influence on throughfall depths. Measurements in May and July 2014 showed a high variability of stemflow (2-16%) between rain events. Throughfall and precipitation intensities (mm/hr) expressed strong linear relationships (adjusted coefficient of determination R20.79) for the entire range of observed rainfall intensities. The ratio of throughfall to precipitation intensity was 0.49:1. The observations suggest that reduction of throughfall intensity by the canopy during a rainstorm determines the bulk of interception depth. In contrast, the amount of water stored on the canopy and evaporated between and after rain events contributes minimally to interception. Simulations of potential evaporation based on the Penman-Monteith method revealed a serious underestimation of evaporation from the wet canopy surfaces during the rain events. Mechanisms other than heat balance models of potential evaporation from a still water surface are being discussed in order to explain large intrastorm evaporation from within an isolated canopy.

A Laboratory Study of a Water Surface in Response to Rainfall

NASA Astrophysics Data System (ADS)

Liu, Ren; Liu, Xinan; Duncan, James

2016-11-01

The shape of a water surface in response to the impact of raindrops is studied experimentally in a 1.22-m-by-1.22-m water pool with a water depth of 0.3 m. Simulated raindrops are generated by an array of 22-gauge hypodermic needles that are attached to the bottom of an open-surface water tank. The tank is connected to a 2D translation stage to provide a small-radius horizontal circular or oval motion to the needles, thus avoiding repeated drop impacts at the same location under each needle. The drop diameter is about 2.6 mm and the height of the water tank above the water surface of the pool is varied from 1 m to 4.8 m to provide different impact velocities. The water surface features including stalks, crowns and ring waves are measured with a cinematic laser-induced- fluorescence (LIF) technique. It is found that the average stalk height is strongly correlated to the impact velocities of raindrops and the phase speeds of ring waves inside the rain field are different from that measured outside the rain field.

Terminal Forecast Reference Notebook, Camp Casey, Korea.

DTIC Science & Technology

1981-08-01

AGL) immediately west of the runway. b. The instrument shelter, with psychrometer , is just outside of building T-2651. It is much too close to the...EQUALS 100 FEET A-6 b. The instrument shelter with psychrometer is 60 feet northwest of the weather station. c. The rain gauge, ML-17, is adjacent to... psychrometer , is 180 feet south of the weather station just east of the runway. A-7 X I x x A IA. WEATHER x STATION RAIN GAUGE SHLTOWER SE IN STRUMENT

BOREAS HYD-9 Tipping Bucket Rain Gauge Data

NASA Technical Reports Server (NTRS)

Kouwen, Nick; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Soulis, Ric; Jenkinson, Wayne; Graham, Allyson; Neff, Todd; Smith, David E. (Technical Monitor)

2000-01-01

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).

Climatological Characterization of Three-Dimensional Storm Structure from Operational Radar and Rain Gauge Data.

NASA Astrophysics Data System (ADS)

Steiner, Matthias; Houze, Robert A., Jr.; Yuter, Sandra E.

1995-09-01

Three algorithms extract information on precipitation type, structure, and amount from operational radar and rain gauge data. Tests on one month of data from one site show that the algorithms perform accurately and provide products that characterize the essential features of the precipitation climatology. Input to the algorithms are the operationally executed volume scans of a radar and the data from a surrounding rain gauge network. The algorithms separate the radar echoes into convective and stratiform regions, statistically summarize the vertical structure of the radar echoes, and determine precipitation rates and amounts on high spatial resolution.The convective and stratiform regions are separated on the basis of the intensity and sharpness of the peaks of echo intensity. The peaks indicate the centers of the convective region. Precipitation not identified as convective is stratiform. This method avoids the problem of underestimating the stratiform precipitation. The separation criteria are applied in exactly the same way throughout the observational domain and the product generated by the algorithm can be compared directly to model output. An independent test of the algorithm on data for which high-resolution dual-Doppler observations are available shows that the convective stratiform separation algorithm is consistent with the physical definitions of convective and stratiform precipitation.The vertical structure algorithm presents the frequency distribution of radar reflectivity as a function of height and thus summarizes in a single plot the vertical structure of all the radar echoes observed during a month (or any other time period). Separate plots reveal the essential differences in structure between the convective and stratiform echoes.Tests yield similar results (within less than 10%) for monthly rain statistics regardless of the technique used for estimating the precipitation, as long as the radar reflectivity values are adjusted to agree with monthly rain gauge data. It makes little difference whether the adjustment is by monthly mean rates or percentiles. Further tests show that 1-h sampling is sufficient to obtain an accurate estimate of monthly rain statistics.

A new Grid Product of Tropical Cyclone Precipitation (TCP) for North America from 1930 to 2013

NASA Astrophysics Data System (ADS)

Zhu, L.

2015-12-01

We first developed a new method that collects daily TCP by using historical storm tracks and precipitation observation based on daily rain gauges in both U.S. and Mexico and calibrated it with satellite precipitation observation. We used a parametrized wind field to correct the possible under-estimations of precipitation in rain gauges. Grid interpolation parameters were optimized by testing different historical rain gauge densities and comparing our grid estimation of TCP and the observation from TRMM Multi-satellite Precipitation Analysis (3B42) by for the data available period from 1998 to 2013. The calibrated method was then used for the whole 94 years of TCP estimation. The preliminary result shows that the frequency of TCP events does not have significant change but the TCP intensity has significant increasing trends, especially in certain locations in North Carolina and Yucatan Peninsula in Mexico. This new long term TCP climatology can potentially assist model calibration and disaster prevention/mitigation.

A multi-source precipitation approach to fill gaps over a radar precipitation field

NASA Astrophysics Data System (ADS)

Tesfagiorgis, K. B.; Mahani, S. E.; Khanbilvardi, R.

2012-12-01

Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. The present work develops an approach to seamlessly blend satellite, radar, climatological and gauge precipitation products to fill gaps over ground-based radar precipitation fields. To mix different precipitation products, the bias of any of the products relative to each other should be removed. For bias correction, the study used an ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar rainfall product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. A weighted Successive Correction Method (SCM) is proposed to make the merging between error corrected satellite and radar rainfall estimates. In addition to SCM, we use a Bayesian spatial method for merging the gap free radar with rain gauges, climatological rainfall sources and SPEs. We demonstrate the method using SPE Hydro-Estimator (HE), radar- based Stage-II, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over three different geographical locations of the United States. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the scientific community.

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

NASA Astrophysics Data System (ADS)

Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

2017-12-01

We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

Evaluation of two "integrated" polarimetric Quantitative Precipitation Estimation (QPE) algorithms at C-band

NASA Astrophysics Data System (ADS)

Tabary, Pierre; Boumahmoud, Abdel-Amin; Andrieu, Hervé; Thompson, Robert J.; Illingworth, Anthony J.; Le Bouar, Erwan; Testud, Jacques

2011-08-01

SummaryTwo so-called "integrated" polarimetric rate estimation techniques, ZPHI ( Testud et al., 2000) and ZZDR ( Illingworth and Thompson, 2005), are evaluated using 12 episodes of the year 2005 observed by the French C-band operational Trappes radar, located near Paris. The term "integrated" means that the concentration parameter of the drop size distribution is assumed to be constant over some area and the algorithms retrieve it using the polarimetric variables in that area. The evaluation is carried out in ideal conditions (no partial beam blocking, no ground-clutter contamination, no bright band contamination, a posteriori calibration of the radar variables ZH and ZDR) using hourly rain gauges located at distances less than 60 km from the radar. Also included in the comparison, for the sake of benchmarking, is a conventional Z = 282 R1.66 estimator, with and without attenuation correction and with and without adjustment by rain gauges as currently done operationally at Météo France. Under those ideal conditions, the two polarimetric algorithms, which rely solely on radar data, appear to perform as well if not better, pending on the measurements conditions (attenuation, rain rates, …), than the conventional algorithms, even when the latter take into account rain gauges through the adjustment scheme. ZZDR with attenuation correction is the best estimator for hourly rain gauge accumulations lower than 5 mm h -1 and ZPHI is the best one above that threshold. A perturbation analysis has been conducted to assess the sensitivity of the various estimators with respect to biases on ZH and ZDR, taking into account the typical accuracy and stability that can be reasonably achieved with modern operational radars these days (1 dB on ZH and 0.2 dB on ZDR). A +1 dB positive bias on ZH (radar too hot) results in a +14% overestimation of the rain rate with the conventional estimator used in this study (Z = 282R1.66), a -19% underestimation with ZPHI and a +23% overestimation with ZZDR. Additionally, a +0.2 dB positive bias on ZDR results in a typical rain rate under- estimation of 15% by ZZDR.

A stochastic fractional dynamics model of space-time variability of rain

NASA Astrophysics Data System (ADS)

Kundu, Prasun K.; Travis, James E.

2013-09-01

varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.

Techniques for analyzing and utilizing the rain gauges at the NASA White Sands Test Facility. [Tracking and Data Relay Satellite System ground station

NASA Technical Reports Server (NTRS)

Kalagher, R. J.

1973-01-01

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.

Mountain and Glacier Terrain Study and Related Investigations in the Juneau Icefield Region, Alaska-Canada

DTIC Science & Technology

1975-09-01

sling psychrometers, thermographs or hygrothermographs, rain gauges , and recording wind direction and velocity Indicators. Four stations Included MRI...precluded drilling a hole and the moulins have not been sufficiently exposed In the last two years, it has been essential to extend the survey control into...middle of May (Miller, 1972 b).The character of thermal penetration Is revealed by data from thermistors drilled Into the Ice from the glacier’s surface

Tropical Rainfall Distributions Determined Using TRMM Combined with other Satellite and Raingauge Information

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George J.; Bolvin, David T.; Curtis, Scott; Nelkin, Eric J.

1999-01-01

Abstract A technique is described to use Tropical Rain Measuring Mission (TRMM) combined radar/radiometer information to adjust geosynchronous infrared satellite data (the TRMM Adjusted GOES Precipitation Index, or TRMM AGPI). The AGPI is then merged with rain gauge information (mostly over land; the TRMM merged product) to provide fine- scale (1 deg latitude/longitude) pentad and monthly analyses, respectively. The TRMM merged estimates are 10% higher than those from the Global Precipitation Climatology Project (GPCP) when integrated over the tropical oceans (37 deg N-S) for 1998, with 20% differences noted in the most heavily raining areas. In the dry subtropics the TRMM values are smaller than the GPCP estimates. The TRMM merged-product tropical-mean estimates for 1998 are 3.3 mm/ day over ocean and 3.1 mm/ day over land and ocean combined. Regional differences are noted between the western and eastern Pacific Ocean maxima when TRMM and GPCP are compared. In the eastern Pacific rain maximum the TRMM and GPCP mean values are nearly equal, very different from the other tropical rainy areas where TRMM merged-product estimates are higher. This regional difference may indicate that TRMM is better at taking in to account the vertical structure of the rain systems and the difference in structure between the western and eastern (shallower) Pacific convection. Comparisons of these TRMM merged analysis estimates with surface data sets shows varied results; the bias is near zero when compared to western Pacific Ocean atoll raingauge data, but significantly positive compared to Kwajalein radar estimates (adjusted by rain gauges). Over land the TRMM estimates also show a significant positive bias. The inclusion of gauge information in the final merged product significantly reduces the bias over land, as expected. The monthly precipitation patterns produced by the TRMM merged data process clearly show the evolution of the ENSO tropical precipitation pattern from early 1998 (El Nino) through early 1999 (La Nina) and beyond. The El Nino minus La Nina difference map shows the eastern Pacific maximum, the maritime continent minima and other tropical and mid-latitude features. The differences in the Pacific are very similar to those detected by the GPCP analyses. However, summing the El Nino minus La Nina differences over the global tropical oceans yields divergent answers from TRMM, GPCP and other estimates. This emphasizes the need for additional validation and analysis before it is feasible to understand the relations between global precipitation anomalies and Pacific Ocean ENSO temperature changes.

Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Rudolf, Bruno; Schneider, Udo; Keehn, Peter R.

1995-01-01

The 'satellite-gauge model' (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5 degrees x 2.5 degrees lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40 degrees N - 40 degrees S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brougth in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields. The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions.

The effects of droplet characteristics on the surface features in a rain field

NASA Astrophysics Data System (ADS)

Liu, R.; Brown, H.; Liu, X.; Duncan, J. H.

2013-11-01

The characteristics of the shape of a water surface in response to the impact of simulated raindrops are studied experimentally in a 1.22-m-by-1.22-m water pool with a water depth of 0.3 m. A rain generator consisting of an open-surface water tank with an array of 22-gauge hypodermic needles (typical needle-to-needle spacing of about L0 = 3 . 5 cm) attached to holes in the tank bottom is mounted 2 m above the water pool. The tank is connected to a 2D translation stage to provide a small-radius (

Effective application of optical sensing technology for sustainable liquid level sensing and rainfall measurement

NASA Astrophysics Data System (ADS)

Afzal, Muhammad Hassan Bin

2015-05-01

Rainfall measurement is performed on regular basis to facilitate effectively the weather stations and local inhabitants. Different types of rain gauges are available with different measuring principle for rainfall measurement. In this research work, a novel optical rain sensor is designed, which precisely calculate the rainfall level according to rainfall intensity. This proposed optical rain sensor model introduced in this paper, which is basically designed for remote sensing of rainfall and it designated as R-ORMS (Remote Optical Rainfall Measurement sensor). This sensor is combination of some improved method of tipping bucket rain gauge and most of the optical hydreon rain sensor's principle. This optical sensor can detect the starting time and ending time of rain, rain intensity and rainfall level. An infrared beam from Light Emitting Diode (LED) through powerful convex lens can accurately determines the diameter of each rain drops by total internal reflection principle. Calculations of these accumulative results determine the rain intensity and rainfall level. Accurate rainfall level is determined by internal optical LED based sensor which is embedded in bucket wall. This internal sensor is also following the total internal reflection (TIR) principle and the Fresnel's law. This is an entirely novel design of optical sensing principle based rain sensor and also suitable for remote sensing rainfall level. The performance of this proposed sensor has been comprehensively compared with other sensors with similar attributes and it showed better and sustainable result. Future related works have been proposed at the end of this paper, to provide improved and enhanced performance of proposed novel rain sensor.

Vibration (?) spikes during natural rain events

NASA Technical Reports Server (NTRS)

Short, David A.

1994-01-01

Limited analysis of optical rain gauge (ORG) data from shipboard and ground based sensors has shown the existence of spikes, possibly attributable to sensor vibration, while rain is occurring. An extreme example of this behavior was noted aboard the PRC#5 on the evening of December 24, 1992 as the ship began repositioning during a rain event in the TOGA/COARE IFA. The spikes are readily evident in the one-second resolution data, but may be indistinguishable from natural rain rate fluctuations in subsampled or averaged data. Such spikes result in increased rainfall totals.

Ground validation of DPR precipitation rate over Italy using H-SAF validation methodology

NASA Astrophysics Data System (ADS)

Puca, Silvia; Petracca, Marco; Sebastianelli, Stefano; Vulpiani, Gianfranco

2017-04-01

The H-SAF project (Satellite Application Facility on support to Operational Hydrology and Water Management, funded by EUMETSAT) is aimed at retrieving key hydrological parameters such as precipitation, soil moisture and snow cover. Within the H-SAF consortium, the Product Precipitation Validation Group (PPVG) evaluate the accuracy of instantaneous and accumulated precipitation products with respect to ground radar and rain gauge data adopting the same methodology (using a Unique Common Code) throughout Europe. The adopted validation methodology can be summarized by the following few steps: (1) ground data (radar and rain gauge) quality control; (2) spatial interpolation of rain gauge measurements; (3) up-scaling of radar data to satellite native grid; (4) temporal comparison of satellite and ground-based precipitation products; and (5) production and evaluation of continuous and multi-categorical statistical scores for long time series and case studies. The statistical scores are evaluated taking into account the satellite product native grid. With the recent advent of the GPM era starting in march 2014, more new global precipitation products are available. The validation methodology developed in H-SAF can be easily applicable to different precipitation products. In this work, we have validated instantaneous precipitation data estimated from DPR (Dual-frequency Precipitation Radar) instrument onboard of the GPM-CO (Global Precipitation Measurement Core Observatory) satellite. In particular, we have analyzed the near surface and estimated precipitation fields collected in the 2A-Level for 3 different scans (NS, MS and HS). The Italian radar mosaic managed by the National Department of Civil Protection available operationally every 10 minutes is used as ground reference data. The results obtained highlight the capability of the DPR to identify properly the precipitation areas with higher accuracy in estimating the stratiform precipitation (especially for the HS). An underestimation of the rainfall rate are observed in the retrieval of some convective case studies. The analysis of several (stratiform and convective) events occurred in the Mediterranean area in the last two years highlights the capability of the DPR to observe interesting features of the precipitation clouds and to estimate the ground rain intensity.

Suitability of standard rain-gauge networks for recording maximum intensity of rainstorms. Examples from the Mediterranean area.

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Gariano, Stefano Luigi; Iovine, Giulio; Mondini, Alessandro; Terranova, Oreste

2014-05-01

Heavy rainstorms often cause natural disasters with damage to the built up environment, injures and victims, strongly hampering social and economic development in the Mediterranean area. Accuracy in space and time of rainfall measurements is a pre-requisite for any attempt of hydrological modelling. Unfortunately, except for a few areas subject to experimentation, rain gauge networks are generally inadequate to describe the spatial distribution of the rainfall. Pluviometric data have hence to be integrated by considering other types of sources. Thanks to its characteristics, mainly in terms of spatial and temporal resolution, the METEOSAT of second generation (MSG) allows for an accurate observation of clouds, and then of the rainstorms, over the entire European territory. More in detail, origin and development of clouds associated to extreme events can be monitored, and the peculiar structures of severe convective rainstorms can be characterized. By the way, several studies pointed out correlations among physical parameters obtained from satellite images and rainstorm intensities. In the Mediterranean area, short rainstorm events are usually associated to cumulonimbus that exhibit a high vertical development. Their top may reach the stratosphere, at 12-13 km above the ground, where the the clouds diverge horizontally to form the typical "anvil". Such notable spreading of the anvil testifies a strong divergence, i.e. upwelling of the air, due to convection. Moreover, due to the limited size of the rainstorm cells (generally, in the order of few tens of km), the maximum intensity can only rarely be recorded by traditional rain gauge networks. Hydrological analyses commonly point out wrong return periods estimations, especially for highly localized and spatially variable events. Despite the huge amount of data, available computer power and storage capacity allow to include in a GIS environment all territorial information, including those derived from satellite images and from the rain gauge network. In the present study, examples of application of rainfall data obtained from satellite images and calibrated by means of traditional rain gauge records are discussed, concerning recent catastrophic rainstorms that affected the Italian territory.

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Regimes of Diurnal Variation of Summer Rainfall over Subtropical East Asia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan W.; Lin W.; Yu, R.

2012-05-01

Using hourly rain gauge records and Tropical Rainfall Measuring Mission 3B42 from 1998 to 2006, the authors present an analysis of the diurnal characteristics of summer rainfall over subtropical East Asia. The study shows that there are four different regimes of distinct diurnal variation of rainfall in both the rain gauge and the satellite data. They are located over the Tibetan Plateau with late-afternoon and midnight peaks, in the western China plain with midnight to early-morning peaks, in the eastern China plain with double peaks in late afternoon and early morning, and over the East China Sea with an early-morningmore » peak. No propagation of diurnal phases is found from the land to the ocean across the coastlines. The different diurnal regimes are highly correlated with the inhomogeneous underlying surface, such as the plateau, plain, and ocean, with physical mechanisms consistent with the large-scale 'mountain-valley' and 'land-sea' breezes and convective instability. These diurnal characteristics over subtropical East Asia can be used as diagnostic metrics to evaluate the physical parameterization and hydrological cycle of climate models over East Asia.« less

A Stochastic Fractional Dynamics Model of Rainfall Statistics

NASA Astrophysics Data System (ADS)

Kundu, Prasun; Travis, James

2013-04-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

Using NDVI to measure precipitation in semi-arid landscapes

USGS Publications Warehouse

Birtwhistle, Amy N.; Laituri, Melinda; Bledsoe, Brian; Friedman, Jonathan M.

2016-01-01

Measuring precipitation in semi-arid landscapes is important for understanding the processes related to rainfall and run-off; however, measuring precipitation accurately can often be challenging especially within remote regions where precipitation instruments are scarce. Typically, rain-gauges are sparsely distributed and research comparing rain-gauge and RADAR precipitation estimates reveal that RADAR data are often misleading, especially for monsoon season convective storms. This study investigates an alternative way to map the spatial and temporal variation of precipitation inputs along ephemeral stream channels using Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper imagery. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG), a region covering 3,367 km2 of semiarid landscapes in southwestern Arizona, USA. The change in NDVI from a pre-to post-monsoon season image along ephemeral stream channels explained 73% of the variance in annual monsoonal precipitation totals from a nearby rain-gauge. In addition, large seasonal changes in NDVI along channels were useful in determining when and where flow events have occurred.

Improving precipitation measurement

NASA Astrophysics Data System (ADS)

Strangeways, Ian

2004-09-01

Although rainfall has been measured for centuries scientifically and in isolated brief episodes over millennia for agriculture, it is still not measured adequately even today for climatology, water resources, and other precise applications. This paper outlines the history of raingauges, their errors, and describes the field testing over 3 years of a first guess design for an aerodynamic rain collector proposed by Folland in 1988. Although shown to have aerodynamic advantage over a standard 5 gauge, the new rain collector was found to suffer from outsplash in heavy rain. To study this problem, and to derive general basic design rules for aerodynamic gauges, its performance was investigated in turbulent, real-world conditions rather than in the controlled and simplified environment of a wind tunnel or mathematical model as in the past. To do this, video records were made using thread tracers to indicate the path of the wind, giving new insight into the complex flow of natural wind around and within raingauges. A new design resulted, and 2 years of field testing have shown that the new gauge has good aerodynamic and evaporative characteristics and minimal outsplash, offering the potential for improved precipitation measurement.

An experimental study of the temporal statistics of radio signals scattered by rain

NASA Technical Reports Server (NTRS)

Hubbard, R. W.; Hull, J. A.; Rice, P. L.; Wells, P. I.

1973-01-01

A fixed-beam bistatic CW experiment designed to measure the temporal statistics of the volume reflectivity produced by hydrometeors at several selected altitudes, scattering angles, and at two frequencies (3.6 and 7.8 GHz) is described. Surface rain gauge data, local meteorological data, surveillance S-band radar, and great-circle path propagation measurements were also made to describe the general weather and propagation conditions and to distinguish precipitation scatter signals from those caused by ducting and other nonhydrometeor scatter mechanisms. The data analysis procedures were designed to provide an assessment of a one-year sample of data with a time resolution of one minute. The cumulative distributions of the bistatic signals for all of the rainy minutes during this period are presented for the several path geometries.

Spectral and Polarimetric Imagery Collection Experiment

DTIC Science & Technology

2011-12-01

Also melted snow liquid rate Optical rain gauge Rain rate Possibly snow rate Visibility meter Visibility Smoke, fog, haze Pyranometer Sun and sky...performance of the IR imagery due to thermal effect or possible inversion layer effects. Pyranometers measure total sun and sky radiation. If the direction

Rain Check Application: Mobile tool to monitor rainfall in remote parts of Haiti

NASA Astrophysics Data System (ADS)

Huang, X.; Baird, J.; Chiu, M. T.; Morelli, R.; de Lanerolle, T. R.; Gourley, J. R.

2011-12-01

Rainfall observations performed uniformly and continuously over a period of time are valuable inputs in developing climate models and predicting events such as floods and droughts. Rain-Check is a mobile application developed in Google App Inventor Platform, for android based smart phones, to allow field researchers to monitor various rain gauges distributed though out remote regions of Haiti and send daily readings via SMS messages for further analysis and long term trending. Rainfall rate and quantity interact with many other factors to influence erosion, vegetative cover, groundwater recharge, stream water chemistry and runoff into streams impacting agriculture and livestock. Rainfall observation from various sites is especially significant in Haiti with over 80% of the country is mountainous terrain. Data sets from global models and limited number of ground stations do not capture the fine-scale rainfall patterns necessary to describe local climate. Placement and reading of rain gauges are critical to accurate measurement of rainfall.

Patterns of precipitation: Fine-scale rain dynamics in the South of England

NASA Astrophysics Data System (ADS)

Callaghan, Sarah

2010-05-01

The consensus in the climate change community is that one of the (many) effects of climate change will be that the nature of rain events will change, and in all likelihood, they will become more extreme. Currently, most long-term rain rate data sets are hourly (or longer) rain accumulations, so investigating the rain events that occur for less than 0.01% (52.5 minutes) of a year is not possible. Rain datasets do exist with smaller temporal resolution, but these are either not continuous, or simply have not been in operation long enough to investigate any trends in climate change. The Chilbolton Observatory in the south of England is one of the world's most advanced meteorological radar experimental facilities, and is home to the world's largest fully steerable meteorological radar, the Chilbolton Advanced Meteorological Radar (CAMRa). It also hosts a wide range of meteorological and atmospheric sensing instruments, including cameras, lidars, radiometers and a wide selection of different types of rain gauges. The UK atmospheric science, hydrology and Earth Observation communities use the instruments located at Chilbolton to conduct research in weather, flooding and climate. This often involves observations of meteorological phenomena operating below the current resolution of (forecasting and climate) models and work on their effective parameterisation. The Chilbolton datasets contain a continuous drop counting rain gauge time series at 10 seconds integration time, spanning from January 2001 to the present. Though the length of the time series is not sufficient to confidently identify any effects of climate change, the time resolution is sufficient to investigate the differences in the extreme values of rain events over the nine years of the dataset, characterising the inter-annual and seasonal variability. Changes in the occurrence of different rain events have also been investigated by looking at event and inter-event durations to determine if there is any change in the relative number of stratiform and convective events over the time period. Knowledge of the fine scale variability of rain (both in the spatial and temporal domains) is important for the development of accurate models for small-scale forecasting, as well as models for the implementation and operation of rain affected systems, such as microwave radio communications and flood mitigation. As the rain gauge measurements made at Chilbolton will continue for the foreseeable future, these datasets will become increasingly valuable, as they provide a "ground-truth" that can be compared with the results of climate and other models.

Evaluation of satellite-retrieved extreme precipitation using gauge observations

NASA Astrophysics Data System (ADS)

Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

2012-04-01

Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

Wallops Island natural rain data analysis

NASA Technical Reports Server (NTRS)

Wang, TING-I.

1994-01-01

ScTI has performed a detailed analysis of four optical rain gauge ORG-105 sensors tested by Wallops Island on 8 May 1992. The four ORG's tested were S/N 2236, 2237, 2239, and 2241. Shown is a 30 minute time series of the individual ORG's, the ORG average, and the weighing gauge. The sensors tracked well with rainrates (RR) up to 45 mm/hr for the period. Also shown is a plot of accumulated rainfall over the same period. It can be seen that even though the ORG's tracked well, some ORG's tended to read higher and some read lower during the event.

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

Voronoi Diagrams and Spring Rain

ERIC Educational Resources Information Center

Perham, Arnold E.; Perham, Faustine L.

2011-01-01

The goal of this geometry project is to use Voronoi diagrams, a powerful modeling tool across disciplines, and the integration of technology to analyze spring rainfall from rain gauge data over a region. In their investigation, students use familiar equipment from their mathematical toolbox: triangles and other polygons, circumcenters and…

The influences on radar-based rainfall estimation due to complex terrain

NASA Astrophysics Data System (ADS)

Craciun, Cristian; Stefan, Sabina

2017-04-01

One of the concerns regarding radar-based quantitative precipitation estimation (QPE) is the level of reliability of radar data, on which the forecaster should trust when he must issue warnings regarding weather phenomena that might put human lives and good in danger. The aim of the current study is to evaluate, by objective means, the difference between radar estimated and gauge measured precipitation over an area with complex terrain. Radar data supplied for the study comes from an S-band, single polarization, Doppler weather system, Weather Surveillance Radar 98 Doppler (WSR-98D), that is located in center part of Romania. Gage measurements are supplied by a net of 27 weather stations, located within the coverage area of the radar. The approach consists in a few steps. In the first one the field of reflectivity data is converted into rain rate, using the radar's native Z-R relationship, and the rain rate field is then transformed into rain accumulation over certain time intervals. In the next step were investigated the differences between radar and gauge rainfall accumulations by using four objective functions: mean bias between radar estimations and ground measurements, root mean square factor, and Spearman and Pearson correlations. The results shows that the differences and the correlations between radar-based accumulations and rain gauge amounts have rather local significance than general relevance over the studied area.

A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data

NASA Astrophysics Data System (ADS)

Velasco-Forero, Carlos A.; Sempere-Torres, Daniel; Cassiraga, Eduardo F.; Jaime Gómez-Hernández, J.

2009-07-01

Quantitative estimation of rainfall fields has been a crucial objective from early studies of the hydrological applications of weather radar. Previous studies have suggested that flow estimations are improved when radar and rain gauge data are combined to estimate input rainfall fields. This paper reports new research carried out in this field. Classical approaches for the selection and fitting of a theoretical correlogram (or semivariogram) model (needed to apply geostatistical estimators) are avoided in this study. Instead, a non-parametric technique based on FFT is used to obtain two-dimensional positive-definite correlograms directly from radar observations, dealing with both the natural anisotropy and the temporal variation of the spatial structure of the rainfall in the estimated fields. Because these correlation maps can be automatically obtained at each time step of a given rainfall event, this technique might easily be used in operational (real-time) applications. This paper describes the development of the non-parametric estimator exploiting the advantages of FFT for the automatic computation of correlograms and provides examples of its application on a case study using six rainfall events. This methodology is applied to three different alternatives to incorporate the radar information (as a secondary variable), and a comparison of performances is provided. In particular, their ability to reproduce in estimated rainfall fields (i) the rain gauge observations (in a cross-validation analysis) and (ii) the spatial patterns of radar fields are analyzed. Results seem to indicate that the methodology of kriging with external drift [KED], in combination with the technique of automatically computing 2-D spatial correlograms, provides merged rainfall fields with good agreement with rain gauges and with the most accurate approach to the spatial tendencies observed in the radar rainfall fields, when compared with other alternatives analyzed.

Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2015-12-01

Intensity-Duration-Frequency (IDF) curves are widely used in flood risk management because they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. Weather radars provide distributed rainfall estimates with high spatial and temporal resolutions and overcome the scarce representativeness of point-based rainfall for regions characterized by large gradients in rainfall climatology. This work explores the use of radar quantitative precipitation estimation (QPE) for the identification of IDF curves over a region with steep climatic transitions (Israel) using a unique radar data record (23 yr) and combined physical and empirical adjustment of the radar data. IDF relationships were derived by fitting a generalized extreme value distribution to the annual maximum series for durations of 20 min, 1 h and 4 h. Arid, semi-arid and Mediterranean climates were explored using 14 study cases. IDF curves derived from the study rain gauges were compared to those derived from radar and from nearby rain gauges characterized by similar climatology, taking into account the uncertainty linked with the fitting technique. Radar annual maxima and IDF curves were generally overestimated but in 70% of the cases (60% for a 100 yr return period), they lay within the rain gauge IDF confidence intervals. Overestimation tended to increase with return period, and this effect was enhanced in arid climates. This was mainly associated with radar estimation uncertainty, even if other effects, such as rain gauge temporal resolution, cannot be neglected. Climatological classification remained meaningful for the analysis of rainfall extremes and radar was able to discern climatology from rainfall frequency analysis.

Gauging Through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Storm Water Modeling Implications

NASA Astrophysics Data System (ADS)

Yang, Pan; Ng, Tze Ling

2017-11-01

Accurate rainfall measurement at high spatial and temporal resolutions is critical for the modeling and management of urban storm water. In this study, we conduct computer simulation experiments to test the potential of a crowd-sourcing approach, where smartphones, surveillance cameras, and other devices act as precipitation sensors, as an alternative to the traditional approach of using rain gauges to monitor urban rainfall. The crowd-sourcing approach is promising as it has the potential to provide high-density measurements, albeit with relatively large individual errors. We explore the potential of this approach for urban rainfall monitoring and the subsequent implications for storm water modeling through a series of simulation experiments involving synthetically generated crowd-sourced rainfall data and a storm water model. The results show that even under conservative assumptions, crowd-sourced rainfall data lead to more accurate modeling of storm water flows as compared to rain gauge data. We observe the relative superiority of the crowd-sourcing approach to vary depending on crowd participation rate, measurement accuracy, drainage area, choice of performance statistic, and crowd-sourced observation type. A possible reason for our findings is the differences between the error structures of crowd-sourced and rain gauge rainfall fields resulting from the differences between the errors and densities of the raw measurement data underlying the two field types.

Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

EPA Science Inventory

Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

Cloud-to-ground lightning and surface rainfall in warm-season Florida thunderstorms

USGS Publications Warehouse

Gungle, B.; Krider, E.P.

2006-01-01

Relationships between cloud-to-ground (CG) lightning and surface rainfall have been examined in nine isolated, warm-season thunderstorms on the east coast of central Florida. CG flashes and the associated rain volumes were measured as a function of time in storm-centered reference frames that followed each storm over a network of rain gauges. Values of the storm-average rain volume per CG flash ranged from 0.70 ?? 104 to 6.4 ?? 104 m3/CG flash, with a mean (and standard deviation) of 2.6 ?? 104 ?? 2.1 ?? 104 m3/CG flash. Values of the rain volume concurrent with CG flashes ranged from 0.11 ?? 104 to 4.9 ?? 104 m3/CG flash with a mean of 2.1 ?? 104 ?? 2.0 ?? 104 m3/CG flash. The lag-time between the peak CG flash rate and the peak rainfall rate (using 5 min bins), and the results of a lag correlation analysis, show that surface rainfall tends to follow the lightning (positive lag) by up to 20 min in six storms. In one storm the rainfall preceded the lightning by 5 min, and two storms had nonsignificant lags. Values of the lagged rain volume concurrent with CG flashes ranged from 0.43 ?? 104 to 4.9 ?? 104 m3/CG flash, and the mean was 1.9 ?? 104 ?? 1.7 ?? 104 m3/CG flash. For the five storms that produced 12 or more flashes and had significant lags, a plot of the optimum lag time versus the total number of CG flashes shows a linear trend (R2 = 0.56). The number of storms is limited, but the lag results do indicate that large storms tend to have longer lags. A linear fit to the lagged rain volume vs. the number of concurrent CG flashes has a slope of 1.9 ?? 104 m3/CG flash (R2 = 0.83). We conclude that warm-season Florida thunderstorms produce a roughly constant rain volume per CG flash and that CG lightning can be used to estimate the location and intensity of convective rainfall in that weather regime. Copyright 2006 by the American Geophysical Union.

SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

EPA Science Inventory

One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

BOREAS HYD-9 Belfort Rain Gauge Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Kouwen, Nick; Soulis, Ric; Jenkinson, Wayne; Graham, Allyson; Knapp, David E. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

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).

Evolving Improvements to TRMM Ground Validation Rainfall Estimates

NASA Technical Reports Server (NTRS)

Robinson, M.; Kulie, M. S.; Marks, D. A.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Silberstein, D. S.; Fisher, B. L.; Wang, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. Since the successful 1997 launch of the TRMM satellite, GV rainfall estimates have demonstrated systematic improvements directly related to improved radar and rain gauge data, modified science techniques, and software revisions. Improved rainfall estimates have resulted in higher quality GV rainfall products and subsequently, much improved evaluation products for the satellite-based precipitation estimates from TRMM. This presentation will demonstrate how TRMM GV rainfall products created in a semi-automated, operational environment have evolved and improved through successive generations. Monthly rainfall maps and rainfall accumulation statistics for each primary site will be presented for each stage of GV product development. Contributions from individual product modifications involving radar reflectivity (Ze)-rain rate (R) relationship refinements, improvements in rain gauge bulk-adjustment and data quality control processes, and improved radar and gauge data will be discussed. Finally, it will be demonstrated that as GV rainfall products have improved, rainfall estimation comparisons between GV and satellite have converged, lending confidence to the satellite-derived precipitation measurements from TRMM.

Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China

NASA Astrophysics Data System (ADS)

Shi, Zhao; Wei, Fangqiang; Chandrasekar, Venkatachalam

2018-03-01

Both Ms 8.0 Wenchuan earthquake on 12 May 2008 and Ms 7.0 Lushan earthquake on 20 April 2013 occurred in the province of Sichuan, China. In the earthquake-affected mountainous area, a large amount of loose material caused a high occurrence of debris flow during the rainy season. In order to evaluate the rainfall intensity-duration (I-D) threshold of the debris flow in the earthquake-affected area, and to fill up the observational gaps caused by the relatively scarce and low-altitude deployment of rain gauges in this area, raw data from two S-band China New Generation Doppler Weather Radar (CINRAD) were captured for six rainfall events that triggered 519 debris flows between 2012 and 2014. Due to the challenges of radar quantitative precipitation estimation (QPE) over mountainous areas, a series of improvement measures are considered: a hybrid scan mode, a vertical reflectivity profile (VPR) correction, a mosaic of reflectivity, a merged rainfall-reflectivity (R - Z) relationship for convective and stratiform rainfall, and rainfall bias adjustment with Kalman filter (KF). For validating rainfall accumulation over complex terrains, the study areas are divided into two kinds of regions by the height threshold of 1.5 km from the ground. Three kinds of radar rainfall estimates are compared with rain gauge measurements. It is observed that the normalized mean bias (NMB) is decreased by 39 % and the fitted linear ratio between radar and rain gauge observation reaches at 0.98. Furthermore, the radar-based I-D threshold derived by the frequentist method is I = 10.1D-0.52 and is underestimated by uncorrected raw radar data. In order to verify the impacts on observations due to spatial variation, I-D thresholds are identified from the nearest rain gauge observations and radar observations at the rain gauge locations. It is found that both kinds of observations have similar I-D thresholds and likewise underestimate I-D thresholds due to undershooting at the core of convective rainfall. It is indicated that improvement of spatial resolution and measuring accuracy of radar observation will lead to the improvement of identifying debris flow occurrence, especially for events triggered by the strong small-scale rainfall process in the study area.

Validation of Satellite Precipitation Products Using Local Rain Gauges to Support Water Assessment in Cochabamba, Bolivia

NASA Astrophysics Data System (ADS)

Saavedra, O.

2017-12-01

The metropolitan region of Cochabamba has been struggling for a consistent water supply master plan for years. The limited precipitation intensities and growing water demand have led to severe water conflicts since 2000 when the fight for water had international visibility. A new dam has just placed into operation, located at the mountain range north of the city, which is the hope to fulfill partially water demand in the region. Looking for feasible water sources and projects are essential to fulfill demand. However, the limited monitoring network composed by conventional rain gauges are not enough to come up with the proper aerial precipitation patterns. This study explores the capabilities of GSMaP-GPM satellite products combined with local rain gauge network to obtain an enhanced product with spatial and temporal resolution. A simple methodology based on penalty factors is proposed to adjust GSMaP-GPM intensities on grid-by-grid basis. The distance of an evaluated grid to the surrounding rain gauges was taken into account. The final correcting factors were obtained by iteration, at this particular case of study four iterations were enough to reduce the relative error. A distributed hydrological model was forced with the enhanced precipitation product to simulate the inflow to the new operating dam. Once the model parameters were calibrated and validated, forecast simulations were run. For the short term, the precipitation trend was projected using exponential equation. As for the long term projection, precipitation and temperature from the hadGEM2 and MIROC global circulation model outputs were used where the last one was found in closer agreement of predictions in the past. Overall, we found out that the amount of 1000 l/s for water supply to the region should be possible to fulfill till 2030. Beyond this year, the intake of two neighboring basins should be constructed to increase the stored volume. This is study was found particularly useful to forecast river discharge at sub-basins where no rain gauges are installed. The approach here can be used to assess new feasible water sources around Cochabamba city to come up with a water supply master plan. Finally, we also recommend to implement awareness programs to reduce and reuse water amount of inhabitants in the city to decrease the demand of water in the future.

From evaporating pans to transpiring plants (John Dalton Medal Lecture)

NASA Astrophysics Data System (ADS)

Roderick, Michael

2013-04-01

The name of the original inventor of irrigated agriculture is lost to antiquity. Nevertheless, one can perhaps imagine an inquisitive desert inhabitant noting the greener vegetation along a watercourse and putting two and two together. Once water was being supplied and food was being produced it would be natural to ask a further question: how much water can we put on? No doubt much experience was gained down through the ages, but again, one can readily imagine someone inverting a rain gauge, filling it with water and measuring how fast the water evaporated. The inverted rain gauge measures the demand for water by the atmosphere. We call it the evaporative demand. I do not know if this is what actually happened but it sure makes an interesting start to a talk. Evaporation pans are basically inverted rain gauges. The rain gauge and evaporation pan measure the supply and demand respectively and these instruments are the workhorses of agricultural meteorology. Rain gauges are well known. Evaporation pans are lesser known but are in widespread use and are a key part of several national standardized meteorological networks. Many more pans are used for things like scheduling irrigation on farms or estimating evaporation from lakes. Analysis of the long records now available from standardized networks has revealed an interesting phenomenon, i.e., pan evaporation has increased in some places and decreased in other but when averaged over large numbers of pans there has been a steady decline. These independent reports from, for example, the US, Russia, China, India, Thailand, are replicated in the southern hemisphere in, for example, Australia, New Zealand and South Africa. One often hears the statement that because the earth is expected to warm with increasing greenhouse gas emissions then it follows that water will evaporate faster. The pan evaporation observations show that this widely held expectation is wrong. When expectations disagree with observations, it is the observations that win. That is the basis of science. In this Dalton Medal lecture we first examine pan evaporation observations and show why pan evaporation has declined. Armed with that knowledge we then investigate the consequences for plant water use and how this is directly coupled to the catchment water balance.

State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems.

PubMed

Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R; Madsen, Henrik

2013-01-01

Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.

A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardèche region, France

NASA Astrophysics Data System (ADS)

Nord, Guillaume; Boudevillain, Brice; Berne, Alexis; Branger, Flora; Braud, Isabelle; Dramais, Guillaume; Gérard, Simon; Le Coz, Jérôme; Legoût, Cédric; Molinié, Gilles; Van Baelen, Joel; Vandervaere, Jean-Pierre; Andrieu, Julien; Aubert, Coralie; Calianno, Martin; Delrieu, Guy; Grazioli, Jacopo; Hachani, Sahar; Horner, Ivan; Huza, Jessica; Le Boursicaud, Raphaël; Raupach, Timothy H.; Teuling, Adriaan J.; Uber, Magdalena; Vincendon, Béatrice; Wijbrans, Annette

2017-03-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution ( ˜ km2, ˜ min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km2, 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100 m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Météo-France (including 2 m air temperature, atmospheric pressure, 2 m relative humidity, 10 m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km2) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling. DOI of the referenced dataset: doi:10.6096/MISTRALS-HyMeX.1438.

Quantifying Precipitation Undercatch in a Semi-arid Watershed in Southeastern Arizona

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Keefer, T.; Goodrich, D. C.; Heilman, P.; Smith, J. R.; Radford, C. D.; Kautz, M. A.

2017-12-01

The observed difference in precipitation measured at above ground level (AGL) and ground-surface (PIT) rain gauges is referred to as wind-induced undercatch (U). Quantification of U is important to accurately assess the water balance and eco-hydrologic response of watersheds and for the modeling of precipitation driven processes. U is a well-known phenomenon having been documented for over one hundred years. Neff (1977), among many others, provides historical perspective on the "Jevons" effect, the increase in U with increasing height of the rain gauge above the earth's surface. U is primarily an effect of wind on precipitation whereby wind and precipitation particles interact such that U increases with increasing wind velocity and increases with smaller and lighter particles, liquid and solid. In recent decades much research on U has been undertaken in field, laboratory, and numeric modeling studies in the U.S. and Europe (e.g. Sieck et al. 2007). Much variability of U is exhibited by years, seasons and storm events. The Walnut Gulch Experimental Watershed and Long Term Agro-ecosystem Research (LTAR) site located in southeastern Arizona has been measuring precipitation at a AGL and PIT rain gauge, wind profiles, and drop size distribution for the period 2010-2015. Our results show that the cumulative precipitation difference between AGL and PIT average 6% for the six year period, but vary from 1% to 12% annually and more so seasonally. Although winter (Nov 1 - Mar 31) has greater U expressed as percentage, more than 2/3 of the total U amount occurs in summer (Jun 15-Oct 15), in the same proportion as seasonal precipitation. Regression estimated event U is greater than daily and cumulative, but may be much greater for individual storm events. The undercatch amount is linearly related to storm event intensity, increasing with increasing intensity, but the U percentage is non-linearly related and increases with decreasing intensity. In agreement with previous studies, U percentage is greater for shorter intervals, greater in winter during non-convective events than summer convective events at low intensities, and greater for faster wind speeds. Similar results are found for U amount for winter events and for wind speeds, but U amount is greater for longer intervals.

A method for combining passive microwave and infrared rainfall observations

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1995-01-01

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.

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

NASA Astrophysics Data System (ADS)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and Lake Michigan. The radar observations are processed using Hydro-NEXRAD algorithms in order to produce rainfall estimates with a spatial resolution of 1 km and a temporal resolution of 15 min. The rainfall estimates are bias-corrected on a daily basis using a network of rain gauges. Besides a thorough evaluation of the different challenges in investigating heavy rain as described above the study includes suggestions for frequency analysis methods as well as studies of hydrometeorological features of single events.

Performance of post-processing algorithms for rainfall intensity using measurements from tipping-bucket rain gauges

NASA Astrophysics Data System (ADS)

Stagnaro, Mattia; Colli, Matteo; Lanza, Luca Giovanni; Chan, Pak Wai

2016-11-01

Eight rainfall events recorded from May to September 2013 at Hong Kong International Airport (HKIA) have been selected to investigate the performance of post-processing algorithms used to calculate the rainfall intensity (RI) from tipping-bucket rain gauges (TBRGs). We assumed a drop-counter catching-type gauge as a working reference and compared rainfall intensity measurements with two calibrated TBRGs operated at a time resolution of 1 min. The two TBRGs differ in their internal mechanics, one being a traditional single-layer dual-bucket assembly, while the other has two layers of buckets. The drop-counter gauge operates at a time resolution of 10 s, while the time of tipping is recorded for the two TBRGs. The post-processing algorithms employed for the two TBRGs are based on the assumption that the tip volume is uniformly distributed over the inter-tip period. A series of data of an ideal TBRG is reconstructed using the virtual time of tipping derived from the drop-counter data. From the comparison between the ideal gauge and the measurements from the two real TBRGs, the performances of different post-processing and correction algorithms are statistically evaluated over the set of recorded rain events. The improvement obtained by adopting the inter-tip time algorithm in the calculation of the RI is confirmed. However, by comparing the performance of the real and ideal TBRGs, the beneficial effect of the inter-tip algorithm is shown to be relevant for the mid-low range (6-50 mmh-1) of rainfall intensity values (where the sampling errors prevail), while its role vanishes with increasing RI in the range where the mechanical errors prevail.

A comprehensive evaluation of input data-induced uncertainty in nonpoint source pollution modeling

NASA Astrophysics Data System (ADS)

Chen, L.; Gong, Y.; Shen, Z.

2015-11-01

Watershed models have been used extensively for quantifying nonpoint source (NPS) pollution, but few studies have been conducted on the error-transitivity from different input data sets to NPS modeling. In this paper, the effects of four input data, including rainfall, digital elevation models (DEMs), land use maps, and the amount of fertilizer, on NPS simulation were quantified and compared. A systematic input-induced uncertainty was investigated using watershed model for phosphorus load prediction. Based on the results, the rain gauge density resulted in the largest model uncertainty, followed by DEMs, whereas land use and fertilizer amount exhibited limited impacts. The mean coefficient of variation for errors in single rain gauges-, multiple gauges-, ASTER GDEM-, NFGIS DEM-, land use-, and fertilizer amount information was 0.390, 0.274, 0.186, 0.073, 0.033 and 0.005, respectively. The use of specific input information, such as key gauges, is also highlighted to achieve the required model accuracy. In this sense, these results provide valuable information to other model-based studies for the control of prediction uncertainty.

Korean national QPE technique development: Analysis of current QPE results and future plan

NASA Astrophysics Data System (ADS)

Cha, Joo Wan

2013-04-01

Korea Meteorological Administration(KMA) has developed a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system using eleven radars over the South Korea. The procedure of the RAD-RAR system in real time consists of four steps: 1) the quality control of volumetric reflectivity for each radar, 2) the computation of the every 10-min rain gauge rainfall within each radar, 3) the real time (10 min-updated) rainfall estimation by the Z-R relationship minimizing the difference between the 1.5-km constant altitude plan precipitation indicator and rain gauge rainfall based on Window Probability Matching Method(WPMM) and by the real-time bias correction of RAD-RAR conducted at every 10 minutes for each radar by making the bias, and 4) the composition of the 11-radar estimated rainfall data. In addition, a local gauge correction method applies for RAD-RAR system. Therefore, the correlation coefficient of R2 = 0.81 is obtained between the daily accumulated observed and RAD-RAR estimated rainfall in 2012. We like to develop a new QPE system using the multi-sensor(radar, rain gauge, numerical model output, and lightning) data for newly improving Korean national QPE system. We made the prototype QPE system in 2012 and improve the detail techniques now. In the future, the new high performance QPE system will include a dual polarization radar observation technique for providing more accurate and valuable national QPE data

An evaluation of the uncertainty of extreme events statistics at the WMO/CIMO Lead Centre on precipitation intensity

NASA Astrophysics Data System (ADS)

Colli, M.; Lanza, L. G.; La Barbera, P.

2012-12-01

Improving the quality of point-scale rainfall measurements is a crucial issue fostered in recent years by the WMO Commission for Instruments and Methods of Observation (CIMO) by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries. The WMO/CIMO Lead Centre on Precipitation Intensity (LC) was recently constituted, in a joint effort between the Dep. of Civil, Chemical and Environmental Engineering of the University of Genova and the Italian Air Force Met Service, gathering the considerable asset of data and information achieved by the past infield and laboratory campaigns with the aim of researching novel methodologies for improving the accuracy of rainfall intensity (RI) measurement techniques. Among the ongoing experimental activities carried out by the LC laboratory particular attention is paid to the reliability evaluation of extreme rainfall events statistics , a common tool in the engineering practice for urban and non urban drainage system design, based on real world observations obtained from weighing gauges. Extreme events statistics were proven already to be highly affected by the traditional tipping-bucket rain gauge RI measurement inaccuracy (La Barbera et al., 2002) and the time resolution of the available RI series certainly constitutes another key-factor in the reliability of the derived hyetographs. The present work reports the LC laboratory efforts in assembling a rainfall simulation system to reproduce the inner temporal structure of the rainfall process by means of dedicated calibration and validation tests. This allowed testing of catching type rain gauges under non-steady flow conditions and quantifying, in a first instance, the dynamic behaviour of the investigated instruments. Considerations about the influence of the dynamic response on the uncertainty budget of modern rain gauges is also shown . The analysis proceeds with the laboratory simulation of the annual maximum rainfall events recorded for different durations at the Villa Cambiaso meteo-station (University of Genova) over the last two decades. Results are reported and discussed in a comparative form involving the derived extreme events statistics. REFERENCES La Barbera P., Lanza L.G. and Stagi L. (2002). Influence of systematic mechanical errors of tipping-bucket rain gauges on the statistics of rainfall extremes. Water Sci. Techn., 45(2), 1-9. Colli M., Lanza L.G., and Chan P.W. (2011). Co-located tipping-bucket and optical drop counter RI measurements and a simulated correction algorithm, Atmos. Res., doi:10.1016/j.atmosres.2011.07.018 Colli M., Lanza L.G., La Barbera P. (2012). Weighing gauges measurement errors and the design rainfall for urban scale applications. 9th International workshop on precipitation in urban areas. St.Moritz, Switzerland, 6-9 December 2012 Lanza L.G. and Vuerich E. (2009). The WMO Field Intercomparison of Rain Intensity Gauges. Atmos. Res., 94, 534-543.

Evaluation of X-band polarimetric radar estimation of rainfall and rain drop size distribution parameters in West Africa

NASA Astrophysics Data System (ADS)

Koffi, A. K.; Gosset, M.; Zahiri, E.-P.; Ochou, A. D.; Kacou, M.; Cazenave, F.; Assamoi, P.

2014-06-01

As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH-KDP-ZDR works well whatever the a priori assumption made on the drop shapes. Dm retrieval based on ZDR alone performs well, but if satisfactory ZDR measurements are not available, the combination ZH-KDP provides satisfactory results for both Dm and NW if an appropriate a priori assumption on drop shape is made.

The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

NASA Astrophysics Data System (ADS)

Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

2010-12-01

Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential optimization. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, an OAS spatially variable adjustment with multiplicative factors, ordinary cokriging, and kriging with external drift. In theory, it could be equally applicable to gauge-satellite estimates and other hydrometeorological variables.

Estimating soil moisture exceedance probability from antecedent rainfall

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Kalansky, J.; Stock, J. D.; Collins, B. D.

2016-12-01

The first storms of the rainy season in coastal California, USA, add moisture to soils but rarely trigger landslides. Previous workers proposed that antecedent rainfall, the cumulative seasonal rain from October 1 onwards, had to exceed specific amounts in order to trigger landsliding. Recent monitoring of soil moisture upslope of historic landslides in the San Francisco Bay Area shows that storms can cause positive pressure heads once soil moisture values exceed a threshold of volumetric water content (VWC). We propose that antecedent rainfall could be used to estimate the probability that VWC exceeds this threshold. A major challenge to estimating the probability of exceedance is that rain gauge records are frequently incomplete. We developed a stochastic model to impute (infill) missing hourly precipitation data. This model uses nearest neighbor-based conditional resampling of the gauge record using data from nearby rain gauges. Using co-located VWC measurements, imputed data can be used to estimate the probability that VWC exceeds a specific threshold for a given antecedent rainfall. The stochastic imputation model can also provide an estimate of uncertainty in the exceedance probability curve. Here we demonstrate the method using soil moisture and precipitation data from several sites located throughout Northern California. Results show a significant variability between sites in the sensitivity of VWC exceedance probability to antecedent rainfall.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joe, Paul; Scott, Bill; Doyle, Chris

Abstract—An innovative monitoring network was implemented to support the operational and science programs for the Vancouver 2010 Winter Olympics. It consisted of in situ weather stations on custom-designed platforms. The sensors included an HMP45C for temperature, humidity and pressure, a tipping bucket rain gauge, an acoustic snow depth sensor, a Pluvio 1 precipitation gauge and an anemometer placed at gauge height and at 10 m height. Modifications to commercial automated precipitation gauges were necessary for the heavy snowfall conditions. Advanced or emerging technologies were deployed to support scientific and nowcasting studies into precipitation intensity, typing, visibility and wind. The sensorsmore » included an FD12P visibility and precipitation sensor, a precipitation occurrence sensing system (POSS) present weather sensor, a Hotplate precipitation sensor and a Parsivel disdrometer. Data were collected at 1 min sampling intervals. A Doppler weather radar was deployed in a valley location and provided critical detailed low-level data. An X-band dual-polarized radar was deployed by the National Oceanic and Atmospheric Administration to monitor Vancouver and Cypress Mountain. Three remote sensing stations for vertical profiling were established. At the base of Whistler Mountain, a micro-rain radar, a 22-channel radiometer, a ceilometer, a Parsivel and a POSS were installed. At the base of Cypress Mountain, a micro-rain radar, a ceilometer, a low cost rain sensor (LCR by ATTEX) and a POSS were installed. At Squamish, a wind profiler and a POSS were installed. Weather sensors were mounted on the Whistler Village Gondola and on the Peak to Peak gondola. Sites were established along the Whistler Mountain slope and at other key locations. The combination of sites and instruments formed a comprehensive network to provide observations appropriate for nowcasting in winter complex terrain and investigate precipitation, visibility and wind processes. The contribution provides a detailed description of the network, their sensors, the innovations and some examples.« less

A coupled hydrological-hydraulic flood inundation model calibrated using post-event measurements and integrated uncertainty analysis in a poorly gauged Mediterranean basin

NASA Astrophysics Data System (ADS)

Hdeib, Rouya; Abdallah, Chadi; Moussa, Roger; Colin, Francois

2017-04-01

Developing flood inundation maps of defined exceedance probabilities is required to provide information on the flood hazard and the associated risk. A methodology has been developed to model flood inundation in poorly gauged basins, where reliable information on the hydrological characteristics of floods are uncertain and partially captured by the traditional rain-gauge networks. Flood inundation is performed through coupling a hydrological rainfall-runoff (RR) model (HEC-HMS) with a hydraulic model (HEC-RAS). The RR model is calibrated against the January 2013 flood event in the Awali River basin, Lebanon (300 km2), whose flood peak discharge was estimated by post-event measurements. The resulting flows of the RR model are defined as boundary conditions of the hydraulic model, which is run to generate the corresponding water surface profiles and calibrated against 20 post-event surveyed cross sections after the January-2013 flood event. An uncertainty analysis is performed to assess the results of the models. Consequently, the coupled flood inundation model is simulated with design storms and flood inundation maps are generated of defined exceedance probabilities. The peak discharges estimated by the simulated RR model were in close agreement with the results from different empirical and statistical methods. This methodology can be extended to other poorly gauged basins facing common stage-gauge failure or characterized by floods with a stage exceeding the gauge measurement level, or higher than that defined by the rating curve.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by about 24 %. In addition, the skill of CHIRPS is less affected by variation in elevation in comparison to TAMSAT 3 and ARC 2 products. CHIRPS resulted in average biases of 1.11, 0.99, and 1.00 at lower (< 1000 m a.s.l.), medium (1000 to 2000 m a.s.l.), and higher elevation (> 2000 m a.s.l.), respectively. Overall, the finding of this validation study shows the potentials of the CHIRPS product to be used for various operational applications such as rainfall pattern and variability study in the Upper Blue Nile basin in Ethiopia.

TRMM Applications for Rainfall-Induced Landslide Early Warning

NASA Astrophysics Data System (ADS)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall (snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

NASA Technical Reports Server (NTRS)

Petersen, Walter; Wolff, David; Krajewski, Witek; Gatlin, Patrick

2015-01-01

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

An Experimental Study of the Rainfall Variability Within TRMM/GPM Precipitation Radar and Microwave Sensor Instantaneous Field of View During MC3E

NASA Technical Reports Server (NTRS)

Tokay, Ali; Petersen, Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.

2011-01-01

Dual tipping bucket gauges were operated at 16 sites in support of ground based precipitation measurements during Mid-latitude Continental Convective Clouds Experiment (MC3E). The experiment is conducted in North Central Oklahoma from April 22 through June 6, 2011. The gauge sites were distributed around Atmospheric Radiation Measurement (ARM) Climate Research facility where the minimum and maximum separation distances ranged from 1 to 12 km. This study investigates the rainfall variability by employing the stretched exponential function. It will focus on the quantitative assessment of the partial beam of the experiment area in both convective and stratiform rain. The parameters of the exponential function will also be determined for various events. This study is unique for two reasons. First is the existing gauge setup and the second is the highly convective nature of the events with rain rates well above 100 mm h-1 for 20 minutes. We will compare the findings with previous studies.

An Experimental Study of the Rainfall Variability Within TRMM/GPM Precipitation Radar and Microwave Sensor Instantaneous Field of View During MC3E

NASA Technical Reports Server (NTRS)

Tokay, Ali; Petersen, Walter Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.

2011-01-01

Dual tipping bucket gauges were operated at 16 sites in support of ground based precipitation measurements during Mid-latitude Continental Convective Clouds Experiment (MC3E). The experiment is conducted in North Central Oklahoma from April 22 through June 6, 2011. The gauge sites were distributed around Atmospheric Radiation Measurement (ARM) Climate Research facility where the minimum and maximum separation distances ranged from 1 to 12 km. This study investigates the rainfall variability by employing the stretched exponential function. It will focus on the quantitative assessment of the partial beam of the experiment area in both convective and stratiform rain. The parameters of the exponential function will also be determined for various events. This study is unique for two reasons. First is the existing gauge setup and the second is the highly convective nature of the events with rain rates well above 100 mm/h for 20 minutes. We will compare the findings with previous studies.

Satellite microwave observations of a storm complex: A comparative analysis

NASA Technical Reports Server (NTRS)

Martin, D. W.

1985-01-01

The hypothesis that cold events correspond to a particular stage in a class of thunderstorms was tested. That class is a storms class which updrafts are: (1) strong, broad and moist, and (2) extend well above the freezing level. Condition (1) implies strong mesoscale forcing. Condition (2) implies a tall updraft or a relatively low freezing level. Such storms should have big, intense radar echoes and cold, fast-growing anvils. The thunderstorm events were analyzed by radar, rain gauge and GOES infrared observations. Radar was the starting point for detection and definition of the hypothesized thunderstorms. The radar signature is compared to the signature of the storm in rain gauge observations, satellite infrared images and satellite microwave images.

Bivariate copula in fitting rainfall data

NASA Astrophysics Data System (ADS)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Validation of High Resolution Orbital Precipitation Over Upper Mahanadi River Basin, India

NASA Astrophysics Data System (ADS)

Gautam, A. K.; Pandey, A.

2016-12-01

Precipitation is one of the most important component of hydrologic cycle and used for various applications i.e. hydrological modeling, structure design to water management policy. Satellite based precipitation, radar rainfall and rain-gauge networks are supporting to each other, in relation to their spatial coverage and ability of observing precipitation. In the absence of rainfall data, satellite precipitation products can be used in the developing countries and over complex terrain where precipitation observations are either sparse or not available. However, satellite precipitation estimates are affected by different errors (AghaKouchak, et al., 2012.). Therefore, ground validation of satellite precipitation estimates is essential. In this study, the upper Mahanadi River Basin (A Part of Central India), has been selected for evaluation of the TRMM multi-satellite precipitation analysis (TMPA) and IMERG (Integrated Multi-satellite Retrievals for GPM) satellite Based Precipitation Products for the period of April 2014 - December 2015. The TMPA (3B42V7) and IMERG (late run) precipitation estimates were evaluated using statistical, contingency table and volumetric method for available 112 rain gauge stations in the study area. Results indicated that, both IMERG and TMPA precipitation overestimated the daily precipitation. The results also revealed that IMERG precipitation estimates provide better accuracy than TMPA precipitation estimates for very light rain (0.1-2.5 mm day-1), light rain (2.5-7.5 mm day-1), moderate rain (7.5-35.5 mm day-1), heavy rain (35.5-64.5 mm day-1) and very heavy rain (>64.5 mm day-1). Although, the detection capability of daily TMPA precipitation performed better in heavy rain. The results showed a good correlation (as high as 0.84) and poor correlation (as low as 0.012) with GPM satellite data over the most parts of the study area. The analyses suggest that, there is a need for improvement in precipitation estimation algorithm and accuracy verification against raingauge precipitation measurement to capture the rain events reliably in the study area.

Precipitation characteristics in tropical Africa using satellite and in situ observations

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Ichoku, I.; Huffman, G. J.; Mohr, K. I.

2017-12-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region have not been well-understood, despite their crucial role in regional and global circulation. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) ground-based gauge network to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product based on satellite observations from the Global Precipitation Measurement (GPM) constellation. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TRMM Multi-Satellite Precipitation Analysis (TMPA), and provide higher resolution data, continent-wide comparisons are made between these two products. Due to its improved temporal resolution, IMERG shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

A laboratory assessment of the measurement accuracy of weighing type rainfall intensity gauges

NASA Astrophysics Data System (ADS)

Colli, M.; Chan, P. W.; Lanza, L. G.; La Barbera, P.

2012-04-01

In recent years the WMO Commission for Instruments and Methods of Observation (CIMO) fostered noticeable advancements in the accuracy of precipitation measurement issue by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries (Lanza et al., 2005; Vuerich et al., 2009). Extreme events analysis is proven to be highly affected by the on-site RI measurement accuracy (see e.g. Molini et al., 2004) and the time resolution of the available RI series certainly constitutes another key-factor in constructing hyetographs that are representative of real rain events. The OTT Pluvio2 weighing gauge (WG) and the GEONOR T-200 vibrating-wire precipitation gauge demonstrated very good performance under previous constant flow rate calibration efforts (Lanza et al., 2005). Although WGs do provide better performance than more traditional Tipping Bucket Rain gauges (TBR) under continuous and constant reference intensity, dynamic effects seem to affect the accuracy of WG measurements under real world/time varying rainfall conditions (Vuerich et al., 2009). The most relevant is due to the response time of the acquisition system and the derived systematic delay of the instrument in assessing the exact weight of the bin containing cumulated precipitation. This delay assumes a relevant role in case high resolution rain intensity time series are sought from the instrument, as is the case of many hydrologic and meteo-climatic applications. This work reports the laboratory evaluation of Pluvio2 and T-200 rainfall intensity measurements accuracy. Tests are carried out by simulating different artificial precipitation events, namely non-stationary rainfall intensity, using a highly accurate dynamic rainfall generator. Time series measured by an Ogawa drop counter (DC) at a field test site located within the Hong Kong International Airport (HKIA) were aggregated at a 1-minute scale and used as reference for the artificial rain generation (Colli et al., 2012). The preliminary development and validation of the rainfall simulator for the generation of variable time steps reference intensities is also shown. The generator is characterized by a sufficiently short time response with respect to the expected weighing gauges behavior in order to ensure effective comparison of the measured/reference intensity at very high resolution in time.

Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

PubMed

Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

2017-02-01

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high-resolution climate models and improved understanding of the drivers of extreme rainfall.

A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

NASA Astrophysics Data System (ADS)

Tan, H.; Chandrasekar, V.; Chen, H.

2017-12-01

Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products, which shows great potential of the machine learning concept in radar rainfall estimation.

Quality‐control of an hourly rainfall dataset and climatology of extremes for the UK

PubMed Central

Lewis, Elizabeth; Chan, Steven C.; Fowler, Hayley J.

2016-01-01

ABSTRACT Sub‐daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non‐operation of gauges. Given the prospect of an intensification of short‐duration rainfall in a warming climate, the identification of such errors is essential if sub‐daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near‐complete hourly records for 1992–2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n‐largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north–south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub‐daily rainfall, with convection dominating during summer. The resulting quality‐controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality‐control procedures for sub‐daily data, the validation of the new generation of very high‐resolution climate models and improved understanding of the drivers of extreme rainfall. PMID:28239235

A Deep Neural Network Model for Rainfall Estimation UsingPolarimetric WSR-88DP Radar Observations

NASA Astrophysics Data System (ADS)

Tan, H.; Chandra, C. V.; Chen, H.

2016-12-01

Rainfall estimation based on radar measurements has been an important topic for a few decades. Generally, radar rainfall estimation is conducted through parametric algorisms such as reflectivity-rainfall relation (i.e., Z-R relation). On the other hand, neural networks are developed for ground rainfall estimation based on radar measurements. This nonparametric method, which takes into account of both radar observations and rainfall measurements from ground rain gauges, has been demonstrated successfully for rainfall rate estimation. However, the neural network-based rainfall estimation is limited in practice due to the model complexity and structure, data quality, as well as different rainfall microphysics. Recently, the deep learning approach has been introduced in pattern recognition and machine learning areas. Compared to traditional neural networks, the deep learning based methodologies have larger number of hidden layers and more complex structure for data representation. Through a hierarchical learning process, the high level structured information and knowledge can be extracted automatically from low level features of the data. In this paper, we introduce a novel deep neural network model for rainfall estimation based on ground polarimetric radar measurements .The model is designed to capture the complex abstractions of radar measurements at different levels using multiple layers feature identification and extraction. The abstractions at different levels can be used independently or fused with other data resource such as satellite-based rainfall products and/or topographic data to represent the rain characteristics at certain location. In particular, the WSR-88DP radar and rain gauge data collected in Dallas - Fort Worth Metroplex and Florida are used extensively to train the model, and for demonstration purposes. Quantitative evaluation of the deep neural network based rainfall products will also be presented, which is based on an independent rain gauge network.

Evaluation of the New Version of the Laser-Optical Disdrometer, OTT Parsivel2

NASA Technical Reports Server (NTRS)

Tokay, Ali; Wolff, David B.; Petersen, Walter A.

2014-01-01

A comparative study of raindrop size distribution measurements has been conducted at NASA's Goddard Space Flight Center where the focus was to evaluate the performance of the upgraded laser-optical OTT Particle Size Velocity (Parsivel2; P2) disdrometer. The experimental setup included a collocated pair of tipping-bucket rain gauges, OTT Parsivel (P1) and P2 disdrometers, and Joss-Waldvogel (JW) disdrometers. Excellent agreement between the two collocated rain gauges enabled their use as a relative reference for event rain totals. A comparison of event total showed that the P2 had a 6%absolute bias with respect to the reference gauges, considerably lower than the P1 and JW disdrometers. Good agreement was also evident between the JW and P2 in hourly raindrop spectra for drop diameters between 0.5 and 4 mm. The P2 drop concentrations mostly increased toward small sizes, and the peak concentrations were mostly observed in the first three measurable size bins. The P1, on the other hand, underestimated small drops and overestimated the large drops, particularly in heavy rain rates. From the analysis performed, it appears that the P2 is an improvement over the P1 model for both drop size and rainfall measurements. P2 mean fall velocities follow accepted terminal fall speed relationships at drop sizes less than 1 mm. As a caveat, the P2 had approximately 1ms21 slower mean fall speed with respect to the terminal fall speed near 1 mm, and the difference between the mean measured and terminal fall speeds reduced with increasing drop size. This caveat was recognized as a software bug by the manufacturer and is currently being investigated.

On the use of MODIS and TRMM products to simulate hydrological processes in the La Plata Basin

NASA Astrophysics Data System (ADS)

Saavedra Valeriano, O. C.; Koike, T.; Berbery, E. H.

2009-12-01

La Plata basin is targeted to establish a distributed water-energy balance model using NASA and JAXA satellite products to estimate fluxes like the river discharge at sub-basin scales. The coupled model is called the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM), already tested with success in the Little Washita basin, Oklahoma, and the upper Tone River in Japan. The model demonstrated the ability to reproduce point-scale energy fluxes, CO2 flux, and river discharges. Moreover, the model showed the ability to predict the basin-scale surface soil moisture evolution in a spatially distributed fashion. In the context of the La Plata Basin, the first step was to set-up the water balance component of the distributed hydrological model of the entire basin using available global geographical data sets. The geomorphology of the basin was extracted using 1-km DEM resolution (obtained from EROS, Hydro 1K). The total delineated watershed reached 3.246 millions km2, identifying 145 sub-basins with a computing grid of 10-km. The distribution of land cover, land surface temperature, LAI and FPAR were obtained from MODIS products. In a first instance, the model was forced by gridded rainfall from the Climate Prediction Center (derived from available rain gauges) and satellite precipitation from TRMM 3B42 (NASA & JAXA). The simulated river discharge using both sources of data was compared and the overall low flow and normal peaks were identified. It was found that the extreme peaks tend to be overestimated when using TRMM 3B42. However, TRMM data allows tracking rainfall patterns which might be missed by the sparse distribution of rain gauges over some areas of the basin.

A stationary criterion to identify the duration of efficient rainfalls to trigger shallow landslide

NASA Astrophysics Data System (ADS)

Vessia, G.; Parise, M.

2012-04-01

Even though rainfall is considered a well known trigger of natural slope instability, its effective role in initiating landsliding phenomena cannot be easily distinguished due to many time- and space- variable interactions among several factors (i.e. slope geometry, mechanical and hydraulic characters of superficial layers and the basin, etc.). A common approach to relate rainfall to the onset of shallow landslides is to plot effective rainfall intensity vs duration to draw intensity threshold lines. Since the earliest work by Caine (1980) on this topic, several researchers have tried to establish intensity thresholds by means of deterministic and probabilistic approaches from a number of worldwide and regional rainfall-landslide inventories. With respect to this intensity-duration threshold approach, information about rainfall-induced landslides are generally collected from chronicles or historical landslide time series, whilst no data about the hydraulic and geometric features of soils and rocks involved into the natural slope instability is commonly taken into account. On the contrary, rainfall heights at different time lag (even every 30 min) are available at different stations by rain gauges. As rain gauge measurements are concerned, these can suffer many problems such as temporary saturation, temporary lack of data transmission and anomalous geographical distribution of the rainfall. Recently, satellite data have been employed to quantify the rainfall event related to landslide occurrence but their correlation to the effective rainfall height at a site is not guaranteed yet. So far, rain gauge measures still represent the most used option. Moreover, the physical simplification introduced by such "rainfall based" approach on landslide prediction can be accepted due to the assumption that only shallow landslides are considered for drawing a regional intensity-duration threshold from the considered data. Starting from the above considerations, and within the framework of a nationwide project by CNR-IRPI, under funds from the National Civil Department, the authors propose in this article a new criterion to identify from rain gauge measures the duration of the rainfalls triggering shallow landslides. The new criterion represents an attempt to identify the duration of the "effective rainfall event" responsible for the landslide occurrence, as reported by newspaper clips and/or in real time web newspapers. At this regard, antecedent precipitations are not taken into account, since the model considers only that amount of rainfall that effectively triggers the slope failure. The model analyses the hourly rainfall time series for at least one month before occurrence of the shallow landslide, using a historical landslide archive covering the time range between 2002 and 2011 in the Lazio Region, central Italy. This archive was obtained by a procedure consisting of the following steps: i) critical scrutiny of chronicles, ii) identification of the landslide site, and iii) retrieval of the rainfall data from the nearest rain gauge station within the pluviometric network provided by the National Department of Civil Protection. The proposed method, for each reported landslide, uses the cumulative function of the rainfall heights and rainfall intensity calculated for different time lag. Then, in order to identify the beginning of the effective rainfall event, two conditions have to be satisfied: (1) the difference in rainfall intensity between two adjacent windows must be very low, and (2) the time series of lack of rainfall must be stationary. When these conditions are met, the initial time of the efficient rainfall necessary to trigger the landslide is established. Such criterion is statistically based according to the rainfall time distribution only. No assumption is needed on the probabilistic distributions of time series of rain/not rain. Such approach has been successfully applied to medium-to-long rainfalls, for which rain/not rain datasets are statistically significant. Very short rainfall durations (i.e. a few hours), due to the small number of data, are not suitable to this approach, but, on the other hand, their onset is generally easily recognizable by visual inspection of the height pluviometric trends.

Scale Dependence of Spatiotemporal Intermittence of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Siddani, Ravi K.

2011-01-01

It is a common experience that rainfall is intermittent in space and time. This is reflected by the fact that the statistics of area- and/or time-averaged rain rate is described by a mixed distribution with a nonzero probability of having a sharp value zero. In this paper we have explored the dependence of the probability of zero rain on the averaging space and time scales in large multiyear data sets based on radar and rain gauge observations. A stretched exponential fannula fits the observed scale dependence of the zero-rain probability. The proposed formula makes it apparent that the space-time support of the rain field is not quite a set of measure zero as is sometimes supposed. We also give an ex.planation of the observed behavior in tenus of a simple probabilistic model based on the premise that rainfall process has an intrinsic memory.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2014-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2015-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

NASA Astrophysics Data System (ADS)

Morin, Efrat; Jacoby, Yael; Navon, Shilo; Bet-Halachmi, Erez

2009-07-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Validation was performed for a subsequent 5-year period for the same catchment and then for an entire 10-year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.

Towards flash flood prediction in the dry Dead Sea region utilizing radar rainfall information

NASA Astrophysics Data System (ADS)

Morin, E.; Jacoby, Y.; Navon, S.; Bet-Halachmi, E.

2009-04-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model utilizing radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on five years of data for one of the catchments. Validation was performed for a subsequent five-year period for the same catchment and then for an entire ten year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood-warning model is feasible for catchments in the area studied.

Disdrometer-based C-Band Radar Quantitative Precipitation Estimation (QPE) in a highly complex terrain region in tropical Colombia.

NASA Astrophysics Data System (ADS)

Sepúlveda, J.; Hoyos Ortiz, C. D.

2017-12-01

An adequate quantification of precipitation over land is critical for many societal applications including agriculture, hydroelectricity generation, water supply, and risk management associated with extreme events. The use of rain gauges, a traditional method for precipitation estimation, and an excellent one, to estimate the volume of liquid water during a particular precipitation event, does not allow to fully capture the highly spatial variability of the phenomena which is a requirement for almost all practical applications. On the other hand, the weather radar, an active remote sensing sensor, provides a proxy for rainfall with fine spatial resolution and adequate temporary sampling, however, it does not measure surface precipitation. In order to fully exploit the capabilities of the weather radar, it is necessary to develop quantitative precipitation estimation (QPE) techniques combining radar information with in-situ measurements. Different QPE methodologies are explored and adapted to local observations in a highly complex terrain region in tropical Colombia using a C-Band radar and a relatively dense network of rain gauges and disdrometers. One important result is that the expressions reported in the literature for extratropical locations are not representative of the conditions found in the tropical region studied. In addition to reproducing the state-of-the-art techniques, a new multi-stage methodology based on radar-derived variables and disdrometer data is proposed in order to achieve the best QPE possible. The main motivation for this new methodology is based on the fact that most traditional QPE methods do not directly take into account the different uncertainty sources involved in the process. The main advantage of the multi-stage model compared to traditional models is that it allows assessing and quantifying the uncertainty in the surface rain rate estimation. The sub-hourly rainfall estimations using the multi-stage methodology are realistic compared to observed data in spite of the many sources of uncertainty including the sampling volume, the different physical principles of the sensors, the incomplete understanding of the microphysics of precipitation and, the most important, the rapidly varying droplet size distribution.

Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.

2013-12-01

Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.

The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates

NASA Astrophysics Data System (ADS)

Seyyedi, H.; Anagnostou, E. N.

2011-12-01

This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.

Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data

NASA Astrophysics Data System (ADS)

Sunilkumar, K.; Narayana Rao, T.; Saikranthi, K.; Purnachandra Rao, M.

2015-09-01

This study presents a comprehensive evaluation of five widely used multisatellite precipitation estimates (MPEs) against 1° × 1° gridded rain gauge data set as ground truth over India. One decade observations are used to assess the performance of various MPEs (Climate Prediction Center (CPC)-South Asia data set, CPC Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks, Tropical Rainfall Measuring Mission's Multisatellite Precipitation Analysis (TMPA-3B42), and Global Precipitation Climatology Project). All MPEs have high detection skills of rain with larger probability of detection (POD) and smaller "missing" values. However, the detection sensitivity differs from one product (and also one region) to the other. While the CMORPH has the lowest sensitivity of detecting rain, CPC shows highest sensitivity and often overdetects rain, as evidenced by large POD and false alarm ratio and small missing values. All MPEs show higher rain sensitivity over eastern India than western India. These differential sensitivities are found to alter the biases in rain amount differently. All MPEs show similar spatial patterns of seasonal rain bias and root-mean-square error, but their spatial variability across India is complex and pronounced. The MPEs overestimate the rainfall over the dry regions (northwest and southeast India) and severely underestimate over mountainous regions (west coast and northeast India), whereas the bias is relatively small over the core monsoon zone. Higher occurrence of virga rain due to subcloud evaporation and possible missing of small-scale convective events by gauges over the dry regions are the main reasons for the observed overestimation of rain by MPEs. The decomposed components of total bias show that the major part of overestimation is due to false precipitation. The severe underestimation of rain along the west coast is attributed to the predominant occurrence of shallow rain and underestimation of moderate to heavy rain by MPEs. The decomposed components suggest that the missed precipitation and hit bias are the leading error sources for the total bias along the west coast. All evaluation metrics are found to be nearly equal in two contrasting monsoon seasons (southwest and northeast), indicating that the performance of MPEs does not change with the season, at least over southeast India. Among various MPEs, the performance of TMPA is found to be better than others, as it reproduced most of the spatial variability exhibited by the reference.

Modified DTW for a quantitative estimation of the similarity between rainfall time series

NASA Astrophysics Data System (ADS)

Djallel Dilmi, Mohamed; Barthès, Laurent; Mallet, Cécile; Chazottes, Aymeric

2017-04-01

The Precipitations are due to complex meteorological phenomenon and can be described as intermittent process. The spatial and temporal variability of this phenomenon is significant and covers large scales. To analyze and model this variability and / or structure, several studies use a network of rain gauges providing several time series of precipitation measurements. To compare these different time series, the authors compute for each time series some parameters (PDF, rain peak intensity, occurrence, amount, duration, intensity …). However, and despite the calculation of these parameters, the comparison of the parameters between two series of measurements remains qualitative. Due to the advection processes, when different sensors of an observation network measure precipitation time series identical in terms of intermitency or intensities, there is a time lag between the different measured series. Analyzing and extracting relevant information on physical phenomena from these precipitation time series implies the development of automatic analytical methods capable of comparing two time series of precipitation measured by different sensors or at two different locations and thus quantifying the difference / similarity. The limits of the Euclidean distance to measure the similarity between the time series of precipitation have been well demonstrated and explained (eg the Euclidian distance is indeed very sensitive to the effects of phase shift : between two identical but slightly shifted time series, this distance is not negligible). To quantify and analysis these time lag, the correlation functions are well established, normalized and commonly used to measure the spatial dependences that are required by many applications. However, authors generally observed that there is always a considerable scatter of the inter-rain gauge correlation coefficients obtained from the individual pairs of rain gauges. Because of a substantial dispersion of estimated time lag, the interpretation of this inter-correlation is not straightforward. We propose here to use an improvement of the Euclidian distance which integrates the global complexity of the rainfall series. The Dynamic Time Wrapping (DTW) used in speech recognition allows matching two time series instantly different and provide the most probable time lag. However, the original formulation of the DTW suffers from some limitations. In particular, it is not adequate to the rain intermittency. In this study we present an adaptation of the DTW for the analysis of rainfall time series : we used time series from the "Météo France" rain gauge network observed between January 1st, 2007 and December 31st, 2015 on 25 stations located in the Île de France area. Then we analyze the results (eg. The distance, the relationship between the time lag detected by our methods and others measured parameters like speed and direction of the wind…) to show the ability of the proposed similarity to provide usefull information on the rain structure. The possibility of using this measure of similarity to define a quality indicator of a sensor integrated into an observation network is also envisaged.

Development of a method of robust rain gauge network optimization based on intensity-duration-frequency results

NASA Astrophysics Data System (ADS)

Chebbi, A.; Bargaoui, Z. K.; da Conceição Cunha, M.

2012-12-01

Based on rainfall intensity-duration-frequency (IDF) curves, a robust optimization approach is proposed to identify the best locations to install new rain gauges. The advantage of robust optimization is that the resulting design solutions yield networks which behave acceptably under hydrological variability. Robust optimisation can overcome the problem of selecting representative rainfall events when building the optimization process. This paper reports an original approach based on Montana IDF model parameters. The latter are assumed to be geostatistical variables and their spatial interdependence is taken into account through the adoption of cross-variograms in the kriging process. The problem of optimally locating a fixed number of new monitoring stations based on an existing rain gauge network is addressed. The objective function is based on the mean spatial kriging variance and rainfall variogram structure using a variance-reduction method. Hydrological variability was taken into account by considering and implementing several return periods to define the robust objective function. Variance minimization is performed using a simulated annealing algorithm. In addition, knowledge of the time horizon is needed for the computation of the robust objective function. A short and a long term horizon were studied, and optimal networks are identified for each. The method developed is applied to north Tunisia (area = 21 000 km2). Data inputs for the variogram analysis were IDF curves provided by the hydrological bureau and available for 14 tipping bucket type rain gauges. The recording period was from 1962 to 2001, depending on the station. The study concerns an imaginary network augmentation based on the network configuration in 1973, which is a very significant year in Tunisia because there was an exceptional regional flood event in March 1973. This network consisted of 13 stations and did not meet World Meteorological Organization (WMO) recommendations for the minimum spatial density. So, it is proposed to virtually augment it by 25, 50, 100 and 160% which is the rate that would meet WMO requirements. Results suggest that for a given augmentation robust networks remain stable overall for the two time horizons.

Development of a method of robust rain gauge network optimization based on intensity-duration-frequency results

NASA Astrophysics Data System (ADS)

Chebbi, A.; Bargaoui, Z. K.; da Conceição Cunha, M.

2013-10-01

Based on rainfall intensity-duration-frequency (IDF) curves, fitted in several locations of a given area, a robust optimization approach is proposed to identify the best locations to install new rain gauges. The advantage of robust optimization is that the resulting design solutions yield networks which behave acceptably under hydrological variability. Robust optimization can overcome the problem of selecting representative rainfall events when building the optimization process. This paper reports an original approach based on Montana IDF model parameters. The latter are assumed to be geostatistical variables, and their spatial interdependence is taken into account through the adoption of cross-variograms in the kriging process. The problem of optimally locating a fixed number of new monitoring stations based on an existing rain gauge network is addressed. The objective function is based on the mean spatial kriging variance and rainfall variogram structure using a variance-reduction method. Hydrological variability was taken into account by considering and implementing several return periods to define the robust objective function. Variance minimization is performed using a simulated annealing algorithm. In addition, knowledge of the time horizon is needed for the computation of the robust objective function. A short- and a long-term horizon were studied, and optimal networks are identified for each. The method developed is applied to north Tunisia (area = 21 000 km2). Data inputs for the variogram analysis were IDF curves provided by the hydrological bureau and available for 14 tipping bucket type rain gauges. The recording period was from 1962 to 2001, depending on the station. The study concerns an imaginary network augmentation based on the network configuration in 1973, which is a very significant year in Tunisia because there was an exceptional regional flood event in March 1973. This network consisted of 13 stations and did not meet World Meteorological Organization (WMO) recommendations for the minimum spatial density. Therefore, it is proposed to augment it by 25, 50, 100 and 160% virtually, which is the rate that would meet WMO requirements. Results suggest that for a given augmentation robust networks remain stable overall for the two time horizons.

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

USGS Publications Warehouse

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

Numerical representation of rainfall field in the Yarmouk River Basin

NASA Astrophysics Data System (ADS)

Shentsis, Isabella; Inbar, Nimrod; Magri, Fabien; Rosenthal, Eliyahu

2017-04-01

Rainfall is the decisive factors in evaluating the water balance of river basins and aquifers. Accepted methods rely on interpolation and extrapolation of gauged rain to regular grid with high dependence on the density and regularity of network, considering the relief complexity. We propose an alternative method that makes up to those restrictions by taking into account additional physical features of the rain field. The method applies to areas with (i) complex plain- and mountainous topography, which means inhomogeneity of the rainfall field and (ii) non-uniform distribution of a rain gauge network with partial lack of observations. The rain model is implemented in two steps: 1. Study of the rainfall field, based on the climatic data (mean annual precipitation), its description by the function of elevation and other factors, and estimation of model parameters (normalized coefficients of the Taylor series); 2. Estimation of rainfall in each historical year using the available data (less complete and irregular versus climatic data) as well as the a-priori known parameters (by the basic hypothesis on inter-annual stability of the model parameters). The proposed method was developed by Shentsis (1990) for hydrological forecasting in Central Asia and was later adapted to the Lake Kinneret Basin. Here this model (the first step) is applied to the Yarmouk River Basin. The Yarmouk River is the largest tributary of the Jordan River. Its transboundary basin (6,833 sq. km) extends over Syria (5,257 sq.km), Jordan (1,379 sq. km) and Israel (197 sq. km). Altitude varies from 1800 m (and more) to -235 m asl. The total number of rain stations in use is 36 (17 in Syria, 19 in Jordan). There is evidently lack and non-uniform distribution of a rain gauge network in Syria. The Yarmouk Basin was divided into five regions considering typical relationship between mean annual rain and elevation for each region. Generally, the borders of regions correspond to the common topographic, geomorphologic and climatic division of the basin. Difference between regional curves is comparable with amplitude of rainfall variance within the regions. In general, rainfall increases with altitude and decreases from west to east (south-east). It should be emphasized that (i) Lake Kinneret Basin (2,490 sq. km) was earlier divided into seven "orographic regions" and (ii) the Lake Kinneret Basin and the Yarmouk River Basin are presented by the system of regional curves X = f (Z) as one whole rainfall field in the Upper Jordan River Basin, where the mean annual rain (X) increases with altitude (Z) and decreases from west to east and from north to south. In the Yarmouk Basin there is much less rainfall (344 mm) than in the Lake Kinneret Basin (749 mm), wherein mean annual rain (2,352 MCM versus 1,865 MCM) is shared between Syria, Jordan and Israel as 80%, 15% and 5%, respectively. The provided rainfall data allow more precise estimations of surface water balances and of recharge to the regional aquifers in the Upper Jordan River Basin. The derived rates serve as fundamental input data for numerical modeling of groundwater flow. This method can be applied to other areas at different temporal and spatial scales. The general applicability makes it a very useful tool in several hydrological problems connected with assessment, management and policy-making of water resources, as well as their changes due to climate and anthropogenic factors. Reference: I. Shentsis (1990). Mathematical models for long-term prediction of mountainous river runoff: methods, information and results, Hydrological Sciences Journal, 35:5, 487-500, DOI: 10.1080/02626669009492453

Self-Nowcast Model of extreme precipitation events for operational meteorology

NASA Astrophysics Data System (ADS)

França, G. B.; de Almeida, M. V.; Rosette, A. C.

2015-10-01

Nowadays many social activities require short-term (one to two hours) and local area forecasts of extreme weather. In particular, air traffic systems have been studying how to minimize the impact of meteorological events, such as turbulence, wind shear, ice, and heavy rain, which are related to the presence of convective systems during all flight phases. This paper presents an alternative self-nowcast model, based on neural network techniques, to produce short-term and local-specific forecasts of extreme meteorological events in the area of the landing and take-off region of Galeão, the principal airport in Rio de Janeiro, Brazil. Twelve years of data were used for neural network training and validation. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area, (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport, (3) rain rate data collected from a network of twenty-nine rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was done about the capability of a neural network to produce early warning signs - or as a nowcasting tool - for extreme meteorological events. The self-nowcast model was validated using results from six categorical statistics, indicated in parentheses for forecasts of the first, second, and third hours, respectively, namely: proportion correct (0.98, 0.96, and 0.94), bias (1.37, 1.48, and 1.83), probability of detection (0.84, 0.80, and 0.76), false-alarm ratio (0.38, 0.46, and 0.58), and threat score (0.54, 0.47, and 0.37). Possible sources of error related to the validation procedure are discussed. Two key points have been identified in which there is a possibility of error: i.e., subjectivity on the part of the meteorologist making the observation, and a rain gauge measurement error of about 20 % depending on wind speed. The latter was better demonstrated when lightning data were included in the validation. The validation showed that the proposed model's performance was quite encouraging for the first and second hours.

Some Precipitation Studies over Andhra Pradesh and the Bay of Bengal using TRMM and SSMI data

NASA Astrophysics Data System (ADS)

Rao, S. Ramalingeswara; Krishna, K. Muni; Kumar, Bhanu

2007-07-01

One of the most difficult issues in modeling the global atmosphere and climate by General Circulation Models is the simulation and initialization of precipitation processes and at the same time rainfall is most important meteorological parameter that effects India's economy. An attempt is made in the present study to evaluate diurnal variation of rain rates over the Bay of Bengal (BoB) for the months June through December during 1999-2002. TMI rainfall product of Wentz and Spencer and SSMI data sets were used in this study. Mean hourly rain rates were calculated over the BoB (10°-15° N and 85°-95°E) and discussed; this study highlights that maximum rain rates are observed in the afternoons during summer monsoon seasons. Secondly mean monthly annual cycle of rainfall is prepared using 3B42RT merged rain product and compared with mean monthly India Meteorological Department (IMD) data for the study period over Andhra Pradesh (A.P). Time series of daily variations of 3B42RT precipitation and observed real time rainfall data over A.P. for the study period is validated and the relationship between them is statistically significant at 1% level. Similarly mean monthly data prepared from the daily analysis and compared with the IMD mean monthly rainfall maps. The comparison suggests that even with only available real time data from 3B42RT and rain gauge, it is possible to construct usable large-scale rainfall maps on regular latitude-longitude grids. This analysis, which uses a high resolution and more local rain gauge data, is able to produce realistic details of Indian summer monsoon rainfall over the study period.

Real-Time Rain Rate Evaluation via Satellite Downlink Signal Attenuation Measurement

PubMed Central

Reggiannini, Ruggero; Moretti, Marco; Adirosi, Elisa; Baldini, Luca; Facheris, Luca; Melani, Samantha; Bacci, Giacomo; Petrolino, Antonio; Vaccaro, Attilio

2017-01-01

We present the NEFOCAST project (named by the contraction of “Nefele”, which is the Italian spelling for the mythological cloud nymph Nephele, and “forecast”), funded by the Tuscany Region, about the feasibility of a system for the detection and monitoring of precipitation fields over the regional territory based on the use of a widespread network of new-generation Eutelsat “SmartLNB” (smart low-noise block converter) domestic terminals. Though primarily intended for interactive satellite services, these devices can also be used as weather sensors, as they have the capability of measuring the rain-induced attenuation incurred by the downlink signal and relaying it on an auxiliary return channel. We illustrate the NEFOCAST system architecture, consisting of the network of ground sensor terminals, the space segment, and the service center, which has the task of processing the information relayed by the terminals for generating rain field maps. We discuss a few methods that allow the conversion of a rain attenuation measurement into an instantaneous rainfall rate. Specifically, we discuss an exponential model relating the specific rain attenuation to the rainfall rate, whose coefficients were obtained from extensive experimental data. The above model permits the inferring of the rainfall rate from the total signal attenuation provided by the SmartLNB and from the link geometry knowledge. Some preliminary results obtained from a SmartLNB installed in Pisa are presented and compared with the output of a conventional tipping bucket rain gauge. It is shown that the NEFOCAST sensor is able to track the fast-varying rainfall rate accurately with no delay, as opposed to a conventional gauge. PMID:28805692

A Comparison of Multisensor Precipitation Estimation Methods in Complex Terrain for Flash Flood Warning and Mitigation

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, C. V.; Willie, D.; Reynolds, D.; Campbell, C.; Zhang, Y.; Sukovich, E.

2012-12-01

Investigating the uncertainties and improving the accuracy of quantitative precipitation estimation (QPE) is a critical mission of the National Oceanic and Atmospheric Administration (NOAA). QPE is extremely challenging in regions of complex terrain like the western U.S. because of the sparse coverage of ground-based radar, complex orographic precipitation processes, and the effects of beam blockages (e.g., Westrick et al. 1999). In addition, the rain gauge density in complex terrain is often inadequate to capture spatial variability in the precipitation patterns. The NOAA Hydrometeorology Testbed (HMT) conducts research on precipitation and weather conditions that can lead to flooding, and fosters transition of scientific advances and new tools into forecasting operations (see hmt.noaa.gov). The HMT program consists of a series of demonstration projects in different geographical regions to enhance understanding of region specific processes related to precipitation, including QPE. There are a number of QPE systems that are widely used across NOAA for precipitation estimation (e.g., Cifelli et al. 2011; Chandrasekar et al. 2012). Two of these systems have been installed at the NOAA Earth System Research Laboratory: Multisensor Precipitation Estimator (MPE) and National Mosaic and Multi-sensor QPE (NMQ) developed by NWS and NSSL, respectively. Both provide gridded QPE products that include radar-only, gauge-only and gauge-radar-merged, etc; however, these systems often provide large differences in QPE (in terms of amounts and spatial patterns) due to differences in Z-R selection, vertical profile of reflectivity correction, and gauge interpolation procedures. Determining the appropriate QPE product and quantification of QPE uncertainty is critical for operational applications, including water management decisions and flood warnings. For example, hourly QPE is used to correct radar based rain rates used by the Flash Flood Monitoring and Prediction (FFMP) package in the NWS forecast offices for issuance of flash flood warnings. This study will evaluate the performance of MPE and NMQ QPE products using independent gauges, object identification techniques for spatial verification and impact on surface runoff using a distributed hydrologic model. The effort will consist of baseline evaluations of these QPE systems to determine which combination of algorithm features is appropriate as well as investigate new methods for combining the gage and radar data. The Russian River Basin in California is used to demonstrate the comparison methodology with data collected from several rainfall events in March 2012.

Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast

NASA Astrophysics Data System (ADS)

Jiang, Mengjiao; Feng, Jinqin; Li, Zhanqing; Sun, Ruiyu; Hou, Yu-Tai; Zhu, Yuejian; Wan, Bingcheng; Guo, Jianping; Cribb, Maureen

2017-11-01

Aerosol-cloud interactions (ACIs) have been widely recognized as a factor affecting precipitation. However, they have not been considered in the operational National Centers for Environmental Predictions Global Forecast System model. We evaluated the potential impact of neglecting ACI on the operational rainfall forecast using ground-based and satellite observations and model reanalysis. The Climate Prediction Center unified gauge-based precipitation analysis and the Modern-Era Retrospective analysis for Research and Applications Version 2 aerosol reanalysis were used to evaluate the forecast in three countries for the year 2015. The overestimation of light rain (47.84 %) and underestimation of heavier rain (31.83, 52.94, and 65.74 % for moderate rain, heavy rain, and very heavy rain, respectively) from the model are qualitatively consistent with the potential errors arising from not accounting for ACI, although other factors cannot be totally ruled out. The standard deviation of the forecast bias was significantly correlated with aerosol optical depth in Australia, the US, and China. To gain further insight, we chose the province of Fujian in China to pursue a more insightful investigation using a suite of variables from gauge-based observations of precipitation, visibility, water vapor, convective available potential energy (CAPE), and satellite datasets. Similar forecast biases were found: over-forecasted light rain and under-forecasted heavy rain. Long-term analyses revealed an increasing trend in heavy rain in summer and a decreasing trend in light rain in other seasons, accompanied by a decreasing trend in visibility, no trend in water vapor, and a slight increasing trend in summertime CAPE. More aerosols decreased cloud effective radii for cases where the liquid water path was greater than 100 g m-2. All findings are consistent with the effects of ACI, i.e., where aerosols inhibit the development of shallow liquid clouds and invigorate warm-base mixed-phase clouds (especially in summertime), which in turn affects precipitation. While we cannot establish rigorous causal relations based on the analyses presented in this study, the significant rainfall forecast bias seen in operational weather forecast model simulations warrants consideration in future model improvements.

Relationships between Hg Air-surface exchange, Soil Moisture and Precipitation at a Background Vegetated Site in South-Eastern Australia.

NASA Astrophysics Data System (ADS)

Macsween, K.; Edwards, G. C.

2017-12-01

Despite many decades of research, the controlling mechanisms of mercury (Hg) air-surface exhange are still poorly understood. Particularly in Australian ecosystems where there are few anthropogenic inputs. A clear understanding of these mechanisms is vital for accurate representation in the global Hg models, particularly regarding re-emission. Water is known to have a considerable influence on Hg exchange within a terrestrial ecosystem. Precipitation has been found to cause spikes is Hg emissions during the initial stages of rain event. While, Soil moisture content is known to enhance fluxes between 15 and 30% Volumetric soil water (VSW), above which fluxes become suppressed. Few field experiments exist to verify these dominantly laboratory or controlled experiments. Here we present work looking at Hg fluxes over an 8-month period at a vegetated background site. The aim of this study is to identify how changes to precipitation intensity and duration, coupled with variable soil moisture content may influence Hg flux across seasons. As well as the influence of other meteorological variables. Experimentation was undertaken using aerodynamic gradient micrometeorological flux method, avoiding disruption to the surface, soil moisture probes and rain gauge measurements to monitor alterations to substrate conditions. Meteorological and air chemistry variables were also measured concurrently throughout the duration of the study. During the study period, South-Eastern Australia experienced several intense east coast low storm systems during the Autumn and Spring months and an unusually dry winter. VSW rarely reached above 30% even following the intense rainfall experienced during the east coast lows. The generally dry conditions throughout winter resulted in an initial spike in Hg emissions when rainfall occurred. Fluxes decreased shortly after the rain began but remained slightly elevated. Given the reduced net radiation and cooler temperatures experienced during the winter months soils took several days to dry out, resulting in slightly enhanced fluxes for the days preceding rainfall. It is thought that seasonality of rainfall has a significant impact of Hg air-surface exchange trends, both through increased recovery times once rain has past and through the increased occurrence of major storm events.

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

NASA Astrophysics Data System (ADS)

Beck, H.; Vergopolan, N.; Pan, M.; Levizzani, V.; van Dijk, A.; Weedon, G. P.; Brocca, L.; Huffman, G. J.; Wood, E. F.; William, L.

2017-12-01

We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000-2016. Twelve non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76,086 gauges worldwide. Another ten gauge-corrected ones were evaluated using hydrological modeling, by calibrating the conceptual model HBV against streamflow records for each of 9053 small to medium-sized (<50,000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR), the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed those indirectly incorporating gauge data through other multi-source datasets (PERSIANN-CDR V1R1 and PGF). Our results highlight large differences in estimation accuracy, and hence, the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite- and reanalysis-based P estimates.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Hao; Zhang, Guifu; Zhao, Kun

A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K DP) and to improve rain estimation. Moreover, the hybrid K DP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ hv) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and K DP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K DP estimatormore » over existing methods.« less

Development of one-minute rain-rate and rain-attenuation contour maps for satellite propagation system planning in a subtropical country: South Africa

NASA Astrophysics Data System (ADS)

Ojo, J. S.; Owolawi, P. A.

2014-10-01

Millimeter and microwave system design at higher frequencies require as input a 1-min rain-rate cumulative distribution function for estimating the level of degradation that can be encountered at such frequency bands. Owing to the lack of 1-min rain-rate data in South Africa and the availability of 5-min and hourly rainfall data, we have used rain-rate conversion models and the refined Moupfouma model to convert the available data into 1-min rain-rate statistics. The attenuation caused by these rain rates was predicted using the International Telecommunication Union (ITU) recommendations model. The Kriging interpolation method was used to draw contour maps over different percentages of time for spatial interpolation of rain-rate values into a regular grid in order to obtain a highly consistent and predictable inter-gauge rain-rate variation over South Africa. The present results will be useful for system designers of modern broadband wireless access (BWA) and high-density cell-based Ku/Ka, Q/V band satellite systems, over the desired area of coverage in order to determine the appropriate effective isotropically radiated power (EIRP) and receiver characteristics of this region.

The Study of Rain Specific Attenuation for the Prediction of Satellite Propagation in Malaysia

NASA Astrophysics Data System (ADS)

Mandeep, J. S.; Ng, Y. Y.; Abdullah, H.; Abdullah, M.

2010-06-01

Specific attenuation is the fundamental quantity in the calculation of rain attenuation for terrestrial path and slant paths representing as rain attenuation per unit distance (dB/km). Specific attenuation is an important element in developing the predicted rain attenuation model. This paper deals with the empirical determination of the power law coefficients which allow calculating the specific attenuation in dB/km from the knowledge of the rain rate in mm/h. The main purpose of the paper is to obtain the coefficients of k and α of power law relationship between specific attenuation. Three years (from 1st January 2006 until 31st December 2008) rain gauge and beacon data taken from USM, Nibong Tebal have been used to do the empirical procedure analysis of rain specific attenuation. The data presented are semi-empirical in nature. A year-to-year variation of the coefficients has been indicated and the empirical measured data was compared with ITU-R provided regression coefficient. The result indicated that the USM empirical measured data was significantly vary from ITU-R predicted value. Hence, ITU-R recommendation for regression coefficients of rain specific attenuation is not suitable for predicting rain attenuation at Malaysia.

Observations of Heavy Rainfall in a Post Wildland Fire Area Using X-Band Polarimetric Radar

NASA Astrophysics Data System (ADS)

Cifelli, R.; Matrosov, S. Y.; Gochis, D. J.; Kennedy, P.; Moody, J. A.

2011-12-01

Polarimetric X-band radar systems have been used increasingly over the last decade for rainfall measurements. Since X-band radar systems are generally less costly, more mobile, and have narrower beam widths (for same antenna sizes) than those operating at lower frequencies (e.g., C and S-bands), they can be used for the "gap-filling" purposes for the areas when high resolution rainfall measurements are needed and existing operational radars systems lack adequate coverage and/or resolution for accurate quantitative precipitation estimation (QPE). The main drawback of X-band systems is attenuation of radar signals, which is significantly stronger compared to frequencies used by "traditional" precipitation radars operating at lower frequencies. The use of different correction schemes based on polarimetric data can, to a certain degree, overcome this drawback when attenuation does not cause total signal extinction. This presentation will focus on examining the use of high-resolution data from the NOAA Earth System Research Laboratory (ESRL) mobile X-band dual polarimetric radar for the purpose of estimating precipitation in a post-wildland fire area. The NOAA radar was deployed in the summer of 2011 to examine the impact of gap-fill radar on QPE and the resulting hydrologic response during heavy rain events in the Colorado Front Range in collaboration with colleagues from the National Center for Atmospheric Research (NCAR), Colorado State University (CSU), and the U.S. Geological Survey (USGS). A network of rain gauges installed by NCAR, the Denver Urban Drainage Flood Control District (UDFCD), and the USGS are used to compare with the radar estimates. Supplemental data from NEXRAD and the CSU-CHILL dual polarimetric radar are also used to compare with the NOAA X-band and rain gauges. It will be shown that rainfall rates and accumulations estimated from specific differential phase measurements (KDP) at X-band are in good agreement with the measurements from the gauge network during heavy rain and rain/hail mixture events. The X-band radar measurements also were generally successful in capturing the high spatial variability in convective rainfall, which caused post-fire debris flows.

Observing atmospheric water in storms with the Nimbus 7 scanning multichannel microwave radiometer

NASA Technical Reports Server (NTRS)

Katsaros, K. B.; Lewis, R. M.

1984-01-01

Employing data on integrated atmospheric water vapor, total cloud liquid water and rain rate obtainable from the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR), we study the frontal structure of several mid-latitude cyclones over the North Pacific Ocean as they approach the West Coast of North America in the winter of 1979. The fronts, analyzed with all available independent data, are consistently located at the leading edge of the strongest gradient in integrated water vapor. The cloud liquid water content, which unfortunately has received very little in situ verification, has patterns which are consistent with the structure seen in visible and infrared imagery. The rain distribution is also a good indicator of frontal location and rain amounts are generally within a factor of two of what is observed with rain gauges on the coast. Furthermore, the onset of rain on the coast can often be accurately forecast by simple advection of the SMMR observed rain areas.

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

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius; Krichevsky, Vladimir; Gebo, Norman

1992-01-01

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.

Mesoscale and synoptic scale features of North Pacific weather systems observed with the scanning multichannel microwave radiometer on Nimbus 7

NASA Technical Reports Server (NTRS)

Katsaros, K. B.; Lewis, R. M.

1986-01-01

Employing data on integrated atmospheric water vapor, total cloud liquid water and rain rate obtainable from the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR), the frontal structure of several mid-latitude cyclones over the North Pacific Ocean as they approach the West Coast of North America in the winter of 1979. The fronts, analyzed with all available independent data, are consistently located at the leading edge of the strongest gradient in integrated water vapor. The cloud liquid water content, which unfortunately has received very little in situ verification, has patterns which are consistent with the structure seen in visible and infrared imagery. The rain distribution is also a good indicator of frontal location and rain amounts are generally within a factor of two of what is observed with rain gauges on the coast. Furthermore, the onset of rain on the coast can often be accurately forecast by simple advection of the SMMR observed rain areas.

Reducing bias in rainfall estimates from microwave links by considering variable drop size distribution

NASA Astrophysics Data System (ADS)

Fencl, Martin; Jörg, Rieckermann; Vojtěch, Bareš

2015-04-01

Commercial microwave links (MWL) are point-to-point radio systems which are used in backhaul networks of cellular operators. For several years, they have been suggested as rainfall sensors complementary to rain gauges and weather radars, because, first, they operate at frequencies where rain drops represent significant source of attenuation and, second, cellular networks almost completely cover urban and rural areas. Usually, path-average rain rates along a MWL are retrieved from the rain-induced attenuation of received MWL signals with a simple model based on a power law relationship. The model is often parameterized based on the characteristics of a particular MWL, such as frequency, polarization and the drop size distribution (DSD) along the MWL. As information on the DSD is usually not available in operational conditions, the model parameters are usually considered constant. Unfortunately, this introduces bias into rainfall estimates from MWL. In this investigation, we propose a generic method to eliminate this bias in MWL rainfall estimates. Specifically, we search for attenuation statistics which makes it possible to classify rain events into distinct groups for which same power-law parameters can be used. The theoretical attenuation used in the analysis is calculated from DSD data using T-Matrix method. We test the validity of our approach on observations from a dedicated field experiment in Dübendorf (CH) with a 1.85-km long commercial dual-polarized microwave link transmitting at a frequency of 38 GHz, an autonomous network of 5 optical distrometers and 3 rain gauges distributed along the path of the MWL. The data is recorded at a high temporal resolution of up to 30s. It is further tested on data from an experimental catchment in Prague (CZ), where 14 MWLs, operating at 26, 32 and 38 GHz frequencies, and reference rainfall from three RGs is recorded every minute. Our results suggest that, for our purpose, rain events can be nicely characterized based on only the maximum rain-induced attenuation of an event. Based on our experimental data, optimal results were achieved by classifying the rain events into three distinct groups with different power-law parameters for each group. In general, the classification of rain events based on attenuation data enables to substantially reduce bias in MWL rainfall estimates due to the power-law model. Thus, when using MWLs for rainfall estimation, reference rain events should be first classified and model parameters of a power-law retrieval model should be fitted for each of class separately. However, this at least requires rainfall data in sub-hourly resolution. It seems very promising to further investigate methods to adjust local MWL rainfall estimates to rainfall observations from traditional sensors. Messer, H., Zinevich, A., Alpert, P., 2006: Environmental Monitoring by Wireless Communication Networks. Science 312, 713-713. doi:10.1126/science.1120034 Fencl, M., Rieckermann, J., Sýkora, P., Stránský D. and Bareš V. 2014: Commercial microwave links instead of rain gauges - fiction or reality? Wat. Sci. Tech., in press doi:10.2166/wst.2014.466 Acknowledgements to Czech Science Foundation project No. 14-22978S and Czech Technical University in Prague project No. SGS13/127/OHK1/2T/11.

Intercomparison of spaceborne precipitation radars and its applications in examining precipitation-topography relationships in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, G.; Gao, J.; Long, D.

2017-12-01

Precipitation is one of the most important components in the water and energy cycles. Spaceborne radars are considered the most direct technology for observing precipitation from space since 1998. This study compares and evaluates the only three existing spaceborne precipitation radars, i.e., the Ku-band precipitation radar (TRMM PR), the W-band Cloud Profiling Radar (CloudSat CPR), and the Ku/Ka-band Dual-frequency Precipitation Radar (GPM DPR). In addition, TRMM PR and GPM DPR are evaluated against hourly rain gauge data in Mainland China. The Tibetan Plateau (TP) is known as the Earth's third pole where precipitation is affected profoundly by topography. However, ground gauges are extremely sparse in the TP, and spaceborne radars can provide valuable data with relatively high accuracy. The relationships between precipitation and topography over the TP are investigated using 17-year TRMM PR data and 2-year GPM DPR data, in combination with rain gauge data. Results indicate that: (1) DPR and PR agree with each other and correlate very well with gauges in Mainland China. DPR improves light precipitation detectability significantly compared with PR. However, DPR high sensitivity scans (HS) deviates from DPR normal and matched scans (NS and MS) and PR in the comparison based on global coincident events and rain gauges in China; (2) CPR outperforms the other two radars in terms of light precipitation detection. In terms of global snowfall estimation, DPR and CPR show very different global snowfall distributions originating from different frequencies, retrieval algorithms, and sampling characteristics; and (3) Precipitation generally decreases exponentially with increasing elevation in the TP. The precipitation-topography relationships are regressed using exponential fitting in seventeen river basins in the TP with good coefficients of determination. Due to the short time span of GPM DPR, the relationships based on GPM DPR data are less robust than those derived from TRMM PR data. The Level-3 precipitation products, i.e., GPM IMERG and GSMaP, can reproduce the general pattern on how precipitation varies with elevation but misrepresent some important details.

Gauge Adjusted Global Satellite Mapping of Precipitation (GSMAP_GAUGE)

NASA Astrophysics Data System (ADS)

Mega, T.; Ushio, T.; Yoshida, S.; Kawasaki, Z.; Kubota, T.; Kachi, M.; Aonashi, K.; Shige, S.

2013-12-01

Precipitation is one of the most important parameters on the earth system, and the global distribution of precipitation and its change are essential data for modeling the water cycle, maintaining the ecosystem environment, agricultural production, improvements of the weather forecast precision, flood warning and so on. The GPM (Global Precipitation Measurement) project is led mainly by the United States and Japan, and is now being actively promoted in Europe, France, India, and China with international cooperation. In this project, the microwave radiometers observing microwave emission from rain will be placed on many low-orbit satellites, to reduce the interval to about 3 hours in observation time for each location on the earth. However, the problem of sampling error arises if the global precipitation estimates are less than three hours. Therefore, it is necessary to utilize a gap-filling technique to generate precipitation maps with high temporal resolution, which is quite important for operational uses such as flash flood warning systems. Global Satellite Mapping of Precipitation (GSMaP) project was established by the Japan Science and Technology Agency (JST) in 2002 to produce global precipitation products with high resolution and high precision from not only microwave radiometers but also geostationary infrared radiometers. Currently, the GSMaP_MVK product has been successfully producing fairly good pictures in near real time, and the products shows a comparable score compared with other high-resolution precipitation systems (Ushio et al. 2009 and Kubota et al. 2009). However some evaluations particularly of the operational applications show the tendency of underestimation compared to some ground based observations for the cases showing extremely high precipitation rates. This is partly because the spatial and temporal samplings of the satellite estimates are different from that of the ground based estimates. The microwave imager observes signals from precipitation instantaneously, while the ground based rain gauges collects precipitation particles for one hour at a certain point. This discrepancy can cause the mismatch between the two estimates, and we need to fill the gap of the precipitation estimates between the satellite and rain gauge attributable to the spatial and temporal resolution difference. To that end, the gauge adjusted product named as GSMaP_Gauge has been developed. In this product, the CPC global gauge data analysis by Xie et al. (2007) and Chen et al. (2008) is used for the adjustment of the GSMaP_MVK data. In this presentation, the algorithm concept, examples of the product, and some validation results are presented.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

A Diagnosis of Rainfall over South America during the 1997/98 El Niño Event. Part I: Validation of NCEP-NCAR Reanalysis Rainfall Data.

NASA Astrophysics Data System (ADS)

Brahmananda Rao, V.; Santo, Clóvis E.; Franchito, Sergio H.

2002-03-01

A comparison between the National Centers for Environmental Predictions-National Center for Atmospheric Research (NCEP-NCAR) reanalysis rainfall data and the Agência Nacional de Energia Elétrica (ANEEL) rain gauge data over Brazil is made. It is found that over northeast Brazil, NCEP-NCAR rainfall is overestimated. But over south and southeast Brazil, the correlation between the two datasets is highly significant showing the utility of NCEP-NCAR rainfall data. Over other parts of Brazil the validity of NCEP-NCAR rainfall data is questionable. A detailed comparison between NCEP-NCAR rainfall data over northwest South America and rain gauge data showed that NCEP-NCAR rainfall data are useful despite important differences between the characteristics in the two data sources. NCEP-NCAR reanalysis data seem to have difficulty in correctly reproducing the strength and orientation of the South Atlantic convergence zone.

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States

NASA Astrophysics Data System (ADS)

Hashemi, H.; Nordin, K. M.; Lakshmi, V.; Knight, R. J.

2016-12-01

Precipitation can be quantified using a rain gauge network, or a remotely sensed precipitation product. Ultimately, the choice of dataset depends on the particular application, the catchment size, climate and the time period of study. In a region with a long record and a dense rain gauge network, the elevation-modified ground-based precipitation product, PRISM, has been found to work well. However, in poorly gauged regions the use of remotely sensed precipitation products is an absolute necessity. The Tropical Rainfall Measuring Mission (TRMM) has provided valuable precipitation datasets for hydrometeorological studies over the past two decades (1998-2015). One concern regarding the usage of TRMM data is the accuracy of the precipitation estimates, when compared to those obtained using PRISM. The reason for this concern is that TRMM and PRISM do not always agree and, typically, TRMM underestimates PRISM over the mountainous regions of the United States. In this study, we develop a correction function to improve the accuracy of the TRMM monthly product (TRMM-3B43) by estimating and removing the bias in the satellite data using the ground-based precipitation product, PRISM. We observe a strong relationship between the bias and land surface elevation; TRMM-3B43 tends to underestimate the PRISM product at altitudes greater than 1500 m above mean sea level (m.amsl) in the contiguous United States. A relationship is developed between TRMM-PRISM bias and elevation. The correction function is used to adjust the TRMM monthly precipitation using PRISM and elevation data. The model is calibrated using 25% of the available time period and the remaining 75% of the time period is used for validation. The corrected TRMM-3B43 product is verified for the high elevations over the contiguous United States and two local regions in the mountainous areas of the western United States. The results show a significant improvement in the accuracy of the TRMM product in the high elevations of the contiguous United States.

DAPAGLOCO - A global daily precipitation dataset from satellite and rain-gauge measurements

NASA Astrophysics Data System (ADS)

Spangehl, T.; Danielczok, A.; Dietzsch, F.; Andersson, A.; Schroeder, M.; Fennig, K.; Ziese, M.; Becker, A.

2017-12-01

The BMBF funded project framework MiKlip(Mittelfristige Klimaprognosen) develops a global climate forecast system on decadal time scales for operational applications. Herein, the DAPAGLOCO project (Daily Precipitation Analysis for the validation of Global medium-range Climate predictions Operationalized) provides a global precipitation dataset as a combination of microwave-based satellite measurements over ocean and rain gauge measurements over land on daily scale. The DAPAGLOCO dataset is created for the evaluation of the MiKlip forecast system in the first place. The HOAPS dataset (Hamburg Ocean Atmosphere Parameter and Fluxes from Satellite data) is used for the derivation of precipitation rates over ocean and is extended by the use of measurements from TMI, GMI, and AMSR-E, in addition to measurements from SSM/I and SSMIS. A 1D-Var retrieval scheme is developed to retrieve rain rates from microwave imager data, which also allows for the determination of uncertainty estimates. Over land, the GPCC (Global Precipitation Climatology Center) Full Data Daily product is used. It consists of rain gauge measurements that are interpolated on a regular grid by ordinary Kriging. The currently available dataset is based on a neuronal network approach, consists of 21 years of data from 1988 to 2008 and is currently extended until 2015 using the 1D-Var scheme and with improved sampling. Three different spatial resolved dataset versions are available with 1° and 2.5° global, and 0.5° for Europe. The evaluation of the MiKlip forecast system by DAPAGLOCO is based on ETCCDI (Expert Team on Climate Change and Detection Indices). Hindcasts are used for the index-based comparison between model and observations. These indices allow for the evaluation of precipitation extremes, their spatial and temporal distribution as well as for the duration of dry and wet spells, average precipitation amounts and percentiles on global scale. Besides, an ETCCDI-based climatology of the DAPAGLOCO precipitation dataset has been derived.

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

2002-01-01

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

Comparison of spatial interpolation of rainfall with emphasis on extreme events

NASA Astrophysics Data System (ADS)

Amin, Kanwal; Duan, Zheng; Disse, Markus

2017-04-01

The sparse network of rain-gauges has always motivated the scientists to find more robust ways to include the spatial variability of precipitation. Turning Bands Simulation, External Drift Kriging, Copula and Random Mixing are amongst one of them. Remote sensing Technologies i.e., radar and satellite estimations are widely known to provide a spatial profile of the precipitation, however during extreme events the accuracy of the resulted areal precipitation is still under discussion. The aim is to compare the areal hourly precipitation results of a flood event from RADOLAN (Radar online adjustment) with the gridded rainfall obtained via Turning Bands Simulation (TBM) and Inverse Distance Weighting (IDW) method. The comparison is mainly focused on performing the uncertainty analysis of the areal precipitation through the said simulation and remote sensing technique for the Upper Main Catchment. The comparison of the results obtained from TBM, IDW and RADOLAN show considerably similar results near the rain gauge stations, but the degree of ambiguity elevates with the increasing distance from the gauge stations. Future research will be carried out to compare the forecasted gridded precipitation simulations with the real-time rainfall forecast system (RADVOR) to make the flood evacuation process more robust and efficient.

Validation of Satellite Precipitation (trmm 3B43) in Ecuadorian Coastal Plains, Andean Highlands and Amazonian Rainforest

NASA Astrophysics Data System (ADS)

Ballari, D.; Castro, E.; Campozano, L.

2016-06-01

Precipitation monitoring is of utmost importance for water resource management. However, in regions of complex terrain such as Ecuador, the high spatio-temporal precipitation variability and the scarcity of rain gauges, make difficult to obtain accurate estimations of precipitation. Remotely sensed estimated precipitation, such as the Multi-satellite Precipitation Analysis TRMM, can cope with this problem after a validation process, which must be representative in space and time. In this work we validate monthly estimates from TRMM 3B43 satellite precipitation (0.25° x 0.25° resolution), by using ground data from 14 rain gauges in Ecuador. The stations are located in the 3 most differentiated regions of the country: the Pacific coastal plains, the Andean highlands, and the Amazon rainforest. Time series, between 1998 - 2010, of imagery and rain gauges were compared using statistical error metrics such as bias, root mean square error, and Pearson correlation; and with detection indexes such as probability of detection, equitable threat score, false alarm rate and frequency bias index. The results showed that precipitation seasonality is well represented and TRMM 3B43 acceptably estimates the monthly precipitation in the three regions of the country. According to both, statistical error metrics and detection indexes, the coastal and Amazon regions are better estimated quantitatively than the Andean highlands. Additionally, it was found that there are better estimations for light precipitation rates. The present validation of TRMM 3B43 provides important results to support further studies on calibration and bias correction of precipitation in ungagged watershed basins.

Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, Ji; Chen, Yangbo; Wang, Huanyu; Qin, Jianming; Li, Jie; Chiao, Sen

2017-03-01

Long lead time flood forecasting is very important for large watershed flood mitigation as it provides more time for flood warning and emergency responses. The latest numerical weather forecast model could provide 1-15-day quantitative precipitation forecasting products in grid format, and by coupling this product with a distributed hydrological model could produce long lead time watershed flood forecasting products. This paper studied the feasibility of coupling the Liuxihe model with the Weather Research and Forecasting quantitative precipitation forecast (WRF QPF) for large watershed flood forecasting in southern China. The QPF of WRF products has three lead times, including 24, 48 and 72 h, with the grid resolution being 20 km  × 20 km. The Liuxihe model is set up with freely downloaded terrain property; the model parameters were previously optimized with rain gauge observed precipitation, and re-optimized with the WRF QPF. Results show that the WRF QPF has bias with the rain gauge precipitation, and a post-processing method is proposed to post-process the WRF QPF products, which improves the flood forecasting capability. With model parameter re-optimization, the model's performance improves also. This suggests that the model parameters be optimized with QPF, not the rain gauge precipitation. With the increasing of lead time, the accuracy of the WRF QPF decreases, as does the flood forecasting capability. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to its long lead time and rational results.

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Radar-based rainfall estimation: Improving Z/R relations through comparison of drop size distributions, rainfall rates and radar reflectivity patterns

NASA Astrophysics Data System (ADS)

Neuper, Malte; Ehret, Uwe

2014-05-01

The relation between the measured radar reflectivity factor Z and surface rainfall intensity R - the Z/R relation - is profoundly complex, so that in general one speaks about radar-based quantitative precipitation estimation (QPE) rather than exact measurement. Like in Plato's Allegory of the Cave, what we observe in the end is only the 'shadow' of the true rainfall field through a very small backscatter of an electromagnetic signal emitted by the radar, which we hope has been actually reflected by hydrometeors. The meteorological relevant and valuable Information is gained only indirectly by more or less justified assumptions. One of these assumptions concerns the drop size distribution, through which the rain intensity is finally associated with the measured radar reflectivity factor Z. The real drop size distribution is however subject to large spatial and temporal variability, and consequently so is the true Z/R relation. Better knowledge of the true spatio-temporal Z/R structure therefore has the potential to improve radar-based QPE compared to the common practice of applying a single or a few standard Z/R relations. To this end, we use observations from six laser-optic disdrometers, two vertically pointing micro rain radars, 205 rain gauges, one rawindsonde station and two C-band Doppler radars installed or operated in and near the Attert catchment (Luxembourg). The C-band radars and the rawindsonde station are operated by the Belgian and German Weather Services, the rain gauge data was partly provided by the French, Dutch, Belgian, German Weather Services and the Ministry of Agriculture of Luxembourg and the other equipment was installed as part of the interdisciplinary DFG research project CAOS (Catchment as Organized Systems). With the various data sets correlation analyzes were executed. In order to get a notion on the different appearance of the reflectivity patterns in the radar image, first of all various simple distribution indices (for example the Gini index, Rosenbluth index) were calculated and compared to the synoptic situation in general and the atmospheric stability in special. The indices were then related to the drop size distributions and the rain rate. Special emphasis was laid in an objective distinction between stratiform and convective precipitation and hereby altered droplet size distribution, respectively Z/R relationship. In our presentation we will show how convective and stratiform precipitation becomes manifest in the different distribution indices, which in turn are thought to represent different patterns in the radar image. We also present and discuss the correlation between these distribution indices and the evolution of the drop size distribution and the rain rate and compare a dynamically adopted Z/R relation to the standard Marshall-Palmer Z/R relation.

Technical Note: An operational landslide early warning system at regional scale based on space-time variable rainfall thresholds

NASA Astrophysics Data System (ADS)

Segoni, S.; Battistini, A.; Rossi, G.; Rosi, A.; Lagomarsino, D.; Catani, F.; Moretti, S.; Casagli, N.

2014-10-01

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult and it provides different outputs. Switching among different views, the system is able to focus both on monitoring of real time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a very straightforward view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain-gauges can be displayed and constantly compared with rainfall thresholds. To better account for the high spatial variability of the physical features, which affects the relationship between rainfall and landslides, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of 332 rain gauges, it allows monitoring each alert zone separately and warnings can be issued independently from an alert zone to another. An important feature of the warning system is the use of thresholds that may vary in time adapting at the conditions of the rainfall path recorded by the rain-gauges. Depending on when the starting time of the rainfall event is set, the comparison with the threshold may produce different outcomes. Therefore, a recursive algorithm was developed to check and compare with the thresholds all possible starting times, highlighting the worst scenario and showing in the WebGIS interface at what time and how much the rainfall path has exceeded or will exceed the most critical threshold. Besides forecasting and monitoring the hazard scenario over the whole region with hazard levels differentiated for 25 distinct alert zones, the system can be used to gather, analyze, visualize, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

Near-Millimeter Wave Technology Base Study: Volume I. Propagation and Target/Background Characteristics

DTIC Science & Technology

1979-11-01

diameter test cell used for laser propagation measurements is Path length-84 m to 2.0 km available and has been designed for circulating aerosols or...36- and 110-GHz and found an attenuation ratio of comparison measurements along a 4-km path with rain rate measured near the receiver end. a *02 They...time. Tipping-bucket systems . gauges are reliable, but become increasingly in- accurate at high rates . Flow gauges which The direct field measurement

Synergetic Combination of Radar Information and Gauge Measurements - with the Conflict between Two Types of Data Being Removed via Displacement and Downscaling

NASA Astrophysics Data System (ADS)

Yan, J.; Bardossy, A.

2017-12-01

Rain gauges are the foundation in hydrology to collect rainfall data, however, gauge measurements alone are limited at representing the complete rainfall distribution. On the other hand, the reliability of radar data is often limited because of the errors in the radar signal (e.g. clutter, variation of the vertical reflectivity profile, beam blockage, attenuation, etc). Thus, merging radar information and gauge rainfall measurements is in an area of active research. The merging method proposed here is to use the radar data in its [0, 1] format (p-value). The actual precipitation values come from the gauge measurements. At each measurement location, two types of data are available, the radar p-value and the gauge measurement in mm. It happens very frequently that there exists a contradiction between these two types of data. A very likely reason is the influence of the unknown process between the radar measurement height and the surface onto which the hydrometeors fall. A method for quantification of the impact of the unknown process is proposed to fix the conflict, but only to a certain degree. Another possible source that can explain the discrepancy between these two types of data is discretization, i.e., the spatial variability cannot be identified by coarse discretization. Thus, downscaling is also considered to further remove the conflict. Based on the p-value from the radar data and the precipitation from the gauge measurements, a distribution function can be built up. The ultimate goal is to simulate the precipitation field for nowcasting purpose. The conditions to be fulfilled by the simulated field is as the following: honoring the measurements at the gauge locations; sharing a similar pattern with the radar image; preserving the inherent covariance structure. The simulation approach employed here is random mixing. The study domain is located in Reutlingen, Baden-Wuerttemberg, Germany (Latitude 48.49N, Longitude 9.20E). The radar data are obtained from a C-band radar (Radar Tuerkheim) whereas the gauge measurements come from stations with 1-min time resolution.

The contribution of tropical cyclones to rainfall in Mexico

NASA Astrophysics Data System (ADS)

Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

Hydrological modelling of the Mabengnong catchment in the southeast Tibet with support of short term intensive precipitation observation

NASA Astrophysics Data System (ADS)

Wang, L.; Zhang, F.; Zhang, H.; Scott, C. A.; Zeng, C.; SHI, X.

2017-12-01

Precipitation is one of the crucial inputs for models used to better understand hydrological processes. In high mountain areas, it is a difficult task to obtain a reliable precipitation data set describing the spatial and temporal characteristic due to the limited meteorological observations and high variability of precipitation. This study carries out intensive observation of precipitation in a high mountain catchment in the southeast of the Tibet during July to August 2013. According to the rain gauges set up at different altitudes, it is found that precipitation is greatly influenced by altitude. The observed precipitation is used to depict the precipitation gradient (PG) and hourly distribution (HD), showing that the average duration is around 0.1, 0.8 and 6.0 hours and the average PG is 0.10, 0.28 and 0.26 mm/d/100m for trace, light and moderate rain, respectively. Based on the gridded precipitation derived from the PG and HD and the nearby Linzhi meteorological station at lower altitude, a distributed biosphere hydrological model based on water and energy budgets (WEB-DHM) is applied to simulate the hydrological processes. Beside the observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are also used for model calibration and validation. The resulting runoff, SCA and LST simulations are all reasonable. Sensitivity analyses indicate that runoff is greatly underestimated without considering PG, illustrating that short-term intensive precipitation observation contributes to improving hydrological modelling of poorly gauged high mountain catchments.

Carbon speciation at the air-sea interface during rain

NASA Astrophysics Data System (ADS)

McGillis, Wade; Hsueh, Diana; Takeshita, Yui; Donham, Emily; Markowitz, Michele; Turk, Daniela; Martz, Todd; Price, Nicole; Langdon, Chris; Najjar, Raymond; Herrmann, Maria; Sutton, Adrienne; Loose, Brice; Paine, Julia; Zappa, Christopher

2015-04-01

This investigation demonstrates the surface ocean dilution during rain events on the ocean and quantifies the lowering of surface pCO2 affecting the air-sea exchange of carbon dioxide. Surface salinity was measured during rain events in Puerto Rico, the Florida Keys, East Coast USA, Panama, and the Palmyra Atoll. End-member analysis is used to determine the subsequent surface ocean carbonate speciation. Surface ocean carbonate chemistry was measured during rain events to verify any approximations made. The physical processes during rain (cold, fresh water intrusion and buoyancy, surface waves and shear, microscale mixing) are described. The role of rain on surface mixing, biogeochemistry, and air-sea gas exchange will be discussed.

Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

NASA Astrophysics Data System (ADS)

Apel, H.; Trepat, O. M.; Hung, N. N.; Chinh, D. T.; Merz, B.; Dung, N. V.

2015-08-01

Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

CSU-CHILL Polarimetric Radar Measurements from a Severe Hail Storm in Eastern Colorado.

NASA Astrophysics Data System (ADS)

Hubbert, J.; Bringi, V. N.; Carey, L. D.; Bolen, S.

1998-08-01

Polarimetric radar measurements made by the recently upgraded CSU-CHILL radar system in a severe hailstorm are analyzed permitting for the first time the combined use of Zh, ZDR, linear depolarization ratio (LDR), KDP, and h to infer hydrometeor types. A chase van equipped for manual collection of hail, and instrumented with a rain gauge, intercepted the storm core for 50 min. The period of golfball-sized hail is easily distinguished by high LDR (greater than or equal to 18 dB), negative ZDR (less than or equal to 0.5 dB), and low h (less than or equal to 0.93) values near the surface. Rainfall accumulation over the entire event (about 40 mm) estimated using KDP is in excellent agreement with the rain gauge measurement. Limited dual-Doppler synthesis using the CSU-CHILL and Denver WSR-88D radars permit estimates of the horizontal convergence at altitudes less than 3 km above ground level (AGL) at 1747 and 1812 mountain daylight time (MDT). Locations of peak horizontal convergence at these times are centered on well-defined positive ZDR columns. Vertical sections of multiparameter radar data at 1812 MDT are interpreted in terms of hydrometeor type. In particular, an enhanced LDR `cap' area on top of the the positive ZDR column is interpreted as a region of mixed phase with large drops mixed with partially frozen and frozen hydrometeors. A positive KDP column on the the western fringe of the main updraft is inferred to be the result of drops (1-2 mm) shed by wet hailstones. Swaths of large hail at the surface (inferred from LDR signatures) and positive ZDR at 3.5 km AGL suggest that potential frozen drop embryos are favorably located for growth into large hailstones. Thin section analysis of a sample of the large hailstones shows that 30%-40% have frozen drop embryos.

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

NASA Astrophysics Data System (ADS)

Beck, Hylke E.; Vergopolan, Noemi; Pan, Ming; Levizzani, Vincenzo; van Dijk, Albert I. J. M.; Weedon, Graham P.; Brocca, Luca; Pappenberger, Florian; Huffman, George J.; Wood, Eric F.

2017-12-01

We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000-2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( < 50 000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1). Our results highlight large differences in estimation accuracy, and hence the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite-, and reanalysis-based P estimates.

A Monte-Carlo Bayesian framework for urban rainfall error modelling

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Willems, Patrick; Onof, Christian

2016-04-01

Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made in recent years towards meeting rainfall input requirements for urban hydrology -including increasing use of high spatial resolution radar rainfall estimates in combination with point rain gauge records- rainfall estimates will never be perfect and the true rainfall field is, by definition, unknown [1]. Quantifying the residual errors in rainfall estimates is crucial in order to understand their reliability, as well as the impact that their uncertainty may have in subsequent runoff estimates. The quantification of errors in rainfall estimates has been an active topic of research for decades. However, existing rainfall error models have several shortcomings, including the fact that they are limited to describing errors associated to a single data source (i.e. errors associated to rain gauge measurements or radar QPEs alone) and to a single representative error source (e.g. radar-rain gauge differences, spatial temporal resolution). Moreover, rainfall error models have been mostly developed for and tested at large scales. Studies at urban scales are mostly limited to analyses of propagation of errors in rain gauge records-only through urban drainage models and to tests of model sensitivity to uncertainty arising from unmeasured rainfall variability. Only few radar rainfall error models -originally developed for large scales- have been tested at urban scales [2] and have been shown to fail to well capture small-scale storm dynamics, including storm peaks, which are of utmost important for urban runoff simulations. In this work a Monte-Carlo Bayesian framework for rainfall error modelling at urban scales is introduced, which explicitly accounts for relevant errors (arising from insufficient accuracy and/or resolution) in multiple data sources (in this case radar and rain gauge estimates typically available at present), while at the same time enabling dynamic combination of these data sources (thus not only quantifying uncertainty, but also reducing it). This model generates an ensemble of merged rainfall estimates, which can then be used as input to urban drainage models in order to examine how uncertainties in rainfall estimates propagate to urban runoff estimates. The proposed model is tested using as case study a detailed rainfall and flow dataset, and a carefully verified urban drainage model of a small (~9 km2) pilot catchment in North-East London. The model has shown to well characterise residual errors in rainfall data at urban scales (which remain after the merging), leading to improved runoff estimates. In fact, the majority of measured flow peaks are bounded within the uncertainty area produced by the runoff ensembles generated with the ensemble rainfall inputs. REFERENCES: [1] Ciach, G. J. & Krajewski, W. F. (1999). On the estimation of radar rainfall error variance. Advances in Water Resources, 22 (6), 585-595. [2] Rico-Ramirez, M. A., Liguori, S. & Schellart, A. N. A. (2015). Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.

SUB-PIXEL RAINFALL VARIABILITY AND THE IMPLICATIONS FOR UNCERTAINTIES IN RADAR RAINFALL ESTIMATES

EPA Science Inventory

Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between real rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the disc...

Weather Instruments.

ERIC Educational Resources Information Center

Brantley, L. Reed, Sr.; Demanche, Edna L.; Klemm, E. Barbara; Kyselka, Will; Phillips, Edwin A.; Pottenger, Francis M.; Yamamoto, Karen N.; Young, Donald B.

This booklet presents some activities to measure various weather phenomena. Directions for constructing a weather station are included. Instruments including rain gauges, thermometers, wind vanes, wind speed devices, humidity devices, barometers, atmospheric observations, a dustfall jar, sticky-tape can, detection of gases in the air, and pH of…

Quantity and quality of runoff reduction and recharge enhancement from constructed rain gardens and vegetated retention ponds in Austin, Texas

NASA Astrophysics Data System (ADS)

Eljuri, A. G.; Moffett, K. B.

2013-12-01

Rain gardens and retention ponds are intended to reduce storm water and pollutant runoff to rivers and streams, rain gardens by enhancing infiltration and retention ponds by promoting evaporation. The City of Austin, Texas is actively investing money and time into these storm water management solutions, but there are no data comparing their effectiveness. In particular, comparisons of rain gardens against control plots and new wetland-vegetated retention pond designs against traditional grassy pond designs are lacking. This study quantifies the quantity and quality of storm runoff to and from five sites: three engineered sites, two rain gardens receiving direct runoff from the same residential roof and a planted retention pond receiving municipal parking lot runoff, and two control sites, a mulched residential lawn receiving direct roof runoff and a grassy municipal retention pond receiving parking lot runoff. A locally installed rain gauge monitors precipitation rates and we collect and analyze rainwater chemistry. Each site is instrumented with bottles to collect direct runoff samples and suction lysimeters within and below the root zone, at 10 cm and 40 cm depth, from which to collect soil water. Soil moisture sensors at 5 cm, 25 cm, and 50 cm depth are used to monitor changes in soil moisture profiles over time. Evapotranspiration rates were determined using local meteorological data and stomatal conductance measurements at the sites. Infiltrometer tests, soil characterizations, and vegetation surveys were also conducted at each site. The soil at the rain gardens are highly mixed with pebbles at the top and become a more uniform soil towards the bottom of the root zone. This differs from the control site where the soil is uniform except for the thin layer of wood chips at the surface. The water samples were analyzed for pH, dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and cations (incl. cadmium, iron, zinc, and lead) and anions (incl. ammonia and nitrate). Samples of waters are taken immediately after rain events and soil moisture is taken both immediately after and two days after events. Austin summers experience fewer rainy days than the spring, fall, and winter, but summer storms are usually high-intensity and short-duration, increasing the potential for flooding. Seasonally, rainfall is somewhat more concentrated around May and October. We find that the negligible constituent concentrations of rainfall quickly become enriched in metals and nutrients from contact with impervious surfaces and that the presence of vegetation is critical, both as canopy over the surface, which promotes substantially higher nutrient levels in runoff (e.g., 1.45 ppm ammonia and 1.68 ppm nitrate under an overhanging tree compared to 0.57 ppm and 0.13 ppm not under the tree), and as plantings in the pond and gardens, which promote infiltration. These field data and a GIS study comparing different possible distributions of future rain gardens and vegetated retention ponds across the city provide much needed data and analysis to support decision making regarding these green storm water management solutions in central Texas.

A Hybrid Method to Estimate Specific Differential Phase and Rainfall With Linear Programming and Physics Constraints

DOE PAGES

Huang, Hao; Zhang, Guifu; Zhao, Kun; ...

2016-10-20

A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K DP) and to improve rain estimation. Moreover, the hybrid K DP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ hv) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and K DP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K DP estimatormore » over existing methods.« less

Application of commercial microwave link (CML) derived precipitation data in a hydrology model

NASA Astrophysics Data System (ADS)

Smiatek, Gerhard; Chwala, Christian; Kunstmann, Harald

2017-04-01

In 2016 very local and extremely intensive convective events caused severe flooding in the Alpine space. Despite the large number of monitoring stations most of the rainfall events were not captured accurately by the existing rain gauge network. As the number of traditional precipitation monitoring sites is in general decreasing, novel rain monitoring techniques are gaining attention. One of the new techniques is the rainfall estimation from signal attenuation in commercial microwave link (CML) networks operated by cellular phone companies. In this contribution, we use CML-derived rainfall information to improve the streamflow forecast of the distributed hydrology model WaSiM-ETH in hindcasting and nowcasting modes. Our model domain covers the complex terrain of the Ammer catchment located in the German Alps. The hydrology model is operated with a spatial resolution of 100m and with an hourly time step. We present two alternative methods of rainfall estimation from CMLs and compare the results to data from rain gauges and a weather radar. Finally, we show the impact of the rainfall data sets on the hydrology model initialization and in discharge simulations of the Ammer River for selected episodes in 2015 and 2016. We found that the densification of the observation network by the CML observations leads to a significant improvement of the model performance.

High resolution regional climate simulation of the Hawaiian Islands - Validation of the historical run from 2003 to 2012

NASA Astrophysics Data System (ADS)

Xue, L.; Newman, A. J.; Ikeda, K.; Rasmussen, R.; Clark, M. P.; Monaghan, A. J.

2016-12-01

A high-resolution (a 1.5 km grid spacing domain nested within a 4.5 km grid spacing domain) 10-year regional climate simulation over the entire Hawaiian archipelago is being conducted at the National Center for Atmospheric Research (NCAR) using the Weather Research and Forecasting (WRF) model version 3.7.1. Numerical sensitivity simulations of the Hawaiian Rainband Project (HaRP, a filed experiment from July to August in 1990) showed that the simulated precipitation properties are sensitive to initial and lateral boundary conditions, sea surface temperature (SST), land surface models, vertical resolution and cloud droplet concentration. The validations of model simulated statistics of the trade wind inversion, temperature, wind field, cloud cover, and precipitation over the islands against various observations from soundings, satellites, weather stations and rain gauges during the period from 2003 to 2012 will be presented at the meeting.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

A 47-Year Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges -APHRODITE project-

NASA Astrophysics Data System (ADS)

Yatagai, A. I.; Yasutomi, N.; Hamada, A.; Kamiguchi, K.; Arakawa, O.

2009-12-01

A daily gridded precipitation dataset for 1961-2007 is created by collecting rain gauge observation data across Asia through the activities of the Asian Precipitation--Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) project. We have already released APHRODITE’s daily gridded precipitation (APHRO_V0902) product for 1961-2004 (Yatagai et al., 2009), and our number of valid stations was between 5000 and 12,000, representing 2.3 to 4.5 times the data available through the Global Telecommunication System network, which were used for most daily grid precipitation products. APHRO_V0902 is the only long-term (1961 onward) continental-scale daily product that contains a dense network of daily rain gauge data for Asia including the Himalayas and mountainous areas in the Middle East. The product has already contributed to studies such as the evaluation of Asian water resources, diagnosis of climate change, statistical downscaling, and verification of numerical model simulation and high-resolution precipitation estimates using satellites. We are currently improving quality control (QC) schemes and interpolation algorithms, and make continuous efforts in data collection. In addition, we have undertaken capacity building activities, such as training seminars by inviting researchers/programmers from some Asian meteorological organizations who provided the observation data for us. Furthermore, we feed the errata (QC) information back to the above organizations and/or data centers. The next version of the algorithm will be fixed in December 2009 (APHRO_V0912), and we will update the product up to 2007. Our progress and advantage of the next products will be shown at the AGU fall meeting in 2009.

Are satellite products good proxies for gauge precipitation over Singapore?

NASA Astrophysics Data System (ADS)

Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

2018-05-01

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate model simulated future projections, when information on precipitation extremes need to be reliable as they are highly crucial for adaptation and mitigation.

Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

NASA Technical Reports Server (NTRS)

Xue, Xianwu; Hong, Yang; Limaye, Ashutosh S.; Gourley, Jonathan; Huffman, George J.; Khan, Sadiq Ibrahim; Dorji, Chhimi; Chen, Sheng

2013-01-01

The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

Rainfall measurement from opportunistic use of earth-space link in Ku Band

NASA Astrophysics Data System (ADS)

Barthès, L.; Mallet, C.

2013-02-01

The present study deals with the development of a low cost microwave device devoted to measure average rain rate observed along earth - satellite links. The principle is to use rain atmospheric attenuation along Earth - space links in Ku-band to deduce the path averaged rain rate. These links are characterized by a path length of a few km through the troposphere. Ground based power measurements are carried out by receiving TV channels from different geostationary satellites in Ku-band. The major difficulty in this study is to retrieve rain characteristics among many fluctuations of the received signal which are due to atmospheric scintillations, changes in the composition of the atmosphere (water vapour concentration, cloud water content) or satellite features (variation of the emitted power, satellite motions). In order to perform a feasibility study of such a device, a measurement campaign has been performed for five months near Paris. This paper proposes an algorithm based on an artificial neural network to identify drought and rainy periods and to suppress the variability of the received signal due to no-rain effects. Taking into account the height of the rain layer, rain attenuation is then inverted to obtain path averaged rain rate. Obtained rainfall rates are compared with co-located rain gauges and radar measurements on the whole experiment period, then the most significant rainy events are analyzed.

An independent assessment of the monthly PRISM gridded precipitation product in central Oklahoma

USDA-ARS?s Scientific Manuscript database

The development of climate-informed decision support tools for agricultural management requires long-duration location-specific climatologies due to the extreme spatiotemporal variability of precipitation. The traditional source of precipitation data (rain gauges) are too sparsely located to fill t...

Basic Weather Facts Study Texts for Students.

ERIC Educational Resources Information Center

Ontario Ministry of the Environment, Toronto.

This pamphlet offers information to teachers and students concerning basic facts about weather and how to construct simple weather measurement devices. Directions, necessary materials, procedures, and instructions for use are given for four weather predicting instruments: wind vane, rain gauge, barometer, anemometer. Information is provided on…

Runoff measurements and hydrological modelling for the estimation of rainfall volumes in an Alpine basin

NASA Astrophysics Data System (ADS)

Ranzi, R.; Bacchi, B.; Grossi, G.

2003-01-01

Streamflow data and water levels in reservoirs have been collected at 30 recording sites in the Toce river basin and its surroundings, upstream of Lago Maggiore, one of the target areas of the Mesoscale Alpine Programme (MAP) experiment. These data have been used for two purposes: firstly, the verification of a hydrological model, forced by rain-gauge data and the output of a mesoscale meteorological model, for flood simulation and forecasting; secondly, to solve an inverse problem--to estimate rainfall volumes from the runoff data in mountain areas where the influence of orography and the limits of actual monitoring systems prevent accurate measurement of precipitation. The methods are illustrated for 19-20 September 1999, MAP Intensive Observing Period 2b, an event with a 4-year return period for the Toce river basin. Uncertainties in the estimates of the areal rainfall volumes based on rain-gauge data and via the inverse solution are assessed.

Scattering by Artificial Wind and Rain Roughened Water Surfaces at Oblique Incidences

NASA Technical Reports Server (NTRS)

Craeye, C.; Sobieski, P. W.; Bliven, L. F.

1997-01-01

Rain affects wind retrievals from scatterometric measurements of the sea surface. To depict the additional roughness caused by rain on a wind driven surface, we use a ring-wave spectral model. This enables us to analyse the rain effect on K(u) band scatterometric observations from two laboratory experiments. Calculations based on the small perturbation method provide good simulation of scattering measurements for the rain-only case, whereas for combined wind and rain cases, the boundary perturbation method is appropriate.

Validation of Satellite-based Rainfall Estimates for Severe Storms (Hurricanes & Tornados)

NASA Astrophysics Data System (ADS)

Nourozi, N.; Mahani, S.; Khanbilvardi, R.

2005-12-01

Severe storms such as hurricanes and tornadoes cause devastating damages, almost every year, over a large section of the United States. More accurate forecasting intensity and track of a heavy storm can help to reduce if not to prevent its damages to lives, infrastructure, and economy. Estimating accurate high resolution quantitative precipitation (QPE) from a hurricane, required to improve the forecasting and warning capabilities, is still a challenging problem because of physical characteristics of the hurricane even when it is still over the ocean. Satellite imagery seems to be a valuable source of information for estimating and forecasting heavy precipitation and also flash floods, particularly for over the oceans where the traditional ground-based gauge and radar sources cannot provide any information. To improve the capability of a rainfall retrieval algorithm for estimating QPE of severe storms, its product is evaluated in this study. High (hourly 4km x 4km) resolutions satellite infrared-based rainfall products, from the NESDIS Hydro-Estimator (HE) and also PERSIANN (Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Networks) algorithms, have been tested against NEXRAD stage-IV and rain gauge observations in this project. Three strong hurricanes: Charley (category 4), Jeanne (category 3), and Ivan (category 3) that caused devastating damages over Florida in the summer 2004, have been considered to be investigated. Preliminary results demonstrate that HE tends to underestimate rain rates when NEXRAD shows heavy storm (rain rates greater than 25 mm/hr) and to overestimate when NEXRAD gives low rainfall amounts, but PERSIANN tends to underestimate rain rates, in general.

Comparison of Diurnal Characteristics of GPM-IMERG Precipitation Products with Hourly Rain Gauge Observations and TRMM-TMPA Products over Mainland China

NASA Astrophysics Data System (ADS)

Li, R.; Wang, K.; QI, D.

2017-12-01

The next generation global high resolutions precipitation products, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) provide new insights into the global hydrometeorology studies. Although there are some previous works to evaluate it on daily scale or above, its performance on sub-daily scale is still limited. This study evaluates the diurnal characteristics of the half-hourly IMERG product with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) data and the hourly rain gauge data from approximately 50000 automatic weather station (AWS) in China during 2014-2016. The results show that IMERG can roughly capture the diurnal cycle of precipitation amount with serial correlation for eight sub-regions ranging from 0.63 to 0.97, but less agreed in frequency (from 0.21 to 0.90) and intensity (from -0.22 to 0.83). IMERG can generally capture the nocturnal and early morning peak of amount, frequency and intensity, which it's a known issue unsolved by TMPA, partly due to the better detection of light rain in the morning. However as for the afternoon precipitation, overestimation of amount and frequency and underestimation of intensity still exist in IMERG product, which probably result from the overestimation of light and moderate rain. IMERG shows large bias in late morning (0900-1100 Beijing Time) and mid evening (2000-2200 Beijing Time). All these results highlight the cautions when using the IMERG sub-daily product and indicate the necessity of improved retrieval algorithm in the future.

Midweek Increase in U.S. Summer Rain and Storm Heights, Suggests Air Pollution Invigorates Rainstorms

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Rosenfeld, Daniel; Kim, Kyu-Myong; Yoo, Jung-Moon; Hahnenberger, Maura

2007-01-01

Tropical Rainfall Measuring Mission (TRMM) satellite data show a significant midweek increase in summertime rainfall over the southeast U.S., due to afternoon intensification. TRMM radar data show a significant midweek increase in rain area and in the heights reached by afternoon storms. Weekly variations in model-reanalysis wind patterns over the region and in rain-gauge data are consistent with the satellite data. A midweek decrease of rainfall over the nearby Atlantic is also seen. EPA measurements of particulate concentrations show a midweek peak over much of the U.S. These observations are consistent with the theory that anthropogenic air pollution suppresses cloud-drop coalescence and early rainout during the growth of thunderstorms over land, allowing more water to be carried above the 0 C isotherm, where freezing yields additional latent heat, invigorating the storms--most dramatically evidenced by the shift in the midweek distribution of afternoon-storm heights--and producing large ice hydrometeors. The enhanced convection induces regional convergence, uplifting and an overall increase of rainfall. Compensating downward air motion suppresses convection over the adjacent ocean areas. Pre-TRMM-era data suggest that the weekly cycle only became strong enough to be detectable beginning in the 1980's. Rain-gauge data also suggest that a weekly cycle may have been detectable in the 1940's, but with peak rainfall on Sunday or Monday, possibly explained by the difference in composition of aerosol pollution at that time. This "weekend effect" may thus offer climate researchers an opportunity to study the regional climate-scale impact of aerosols on storm development and monsoon-like circulation.

Data Report: Meteorological and Evapotranspiration Data from Sagebrush and Pinyon Pine/Juniper Communities at Pahute Mesa, Nevada National Security Site, 2011-2012

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasoni, Richard L; Larsen, Jessica D; Lyles, Brad F.

Pahute Mesa is a groundwater recharge area at the Nevada National Security Site. Because underground nuclear testing was conducted at Pahute Mesa, groundwater recharge may transport radionuclides from underground test sites downward to the water table; the amount of groundwater recharge is also an important component of contaminant transport models. To estimate the amount of groundwater recharge at Pahute Mesa, an INFIL3.0 recharge-runoff model is being developed. Two eddy covariance (EC) stations were installed on Pahute Mesa to estimate evapotranspiration (ET) to support the groundwater recharge modeling project. This data report describes the methods that were used to estimate ETmore » and collect meteorological data. Evapotranspiration was estimated for two predominant plant communities on Pahute Mesa; one site was located in a sagebrush plant community, the other site in a pinyon pine/juniper community. Annual ET was estimated to be 310±13.9 mm for the sagebrush site and 347±15.9 mm for the pinyon pine/juniper site (March 26, 2011 to March 26, 2012). Annual precipitation measured with unheated tipping bucket rain gauges was 179 mm at the sagebrush site and 159 mm at the pinyon pine/juniper site. Annual precipitation measured with bulk precipitation gauges was 222 mm at the sagebrush site and 227 mm at the pinyon pine/juniper site (March 21, 2011 to March 28, 2012). A comparison of tipping bucket versus bulk precipitation data showed that total precipitation measured by the tipping bucket rain gauges was 17 to 20 percent lower than the bulk precipitation gauges. These differences were most likely the result of the unheated tipping bucket precipitation gauges not measuring frozen precipitation as accurately as the bulk precipitation gauges. In this one-year study, ET exceeded precipitation at both study sites because estimates of ET included precipitation that fell during the winter of 2010-2011 prior to EC instrumentation and the precipitation gauges started collecting data in March 2011.« less

National Scale Rainfall Map Based on Linearly Interpolated Data from Automated Weather Stations and Rain Gauges

NASA Astrophysics Data System (ADS)

Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay

2014-05-01

In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.

Tree ring-based chronology of hydro-geomorphic processes as a fundament for identification of hydro-meteorological triggers in the Hrubý Jeseník Mountains (Central Europe).

PubMed

Tichavský, Radek; Šilhán, Karel; Tolasz, Radim

2017-02-01

Hydro-geomorphic processes have significantly influenced the recent development of valley floors, river banks and depositional forms in mountain environments, have caused considerable damage to manmade developments and have disrupted forest management. Trees growing along streams are affected by the transported debris mass and provide valuable records of debris flow/flood histories in their tree-ring series. Dendrogeomorphic approaches are currently the most accurate methods for creating a chronology of the debris flow/flood events in forested catchments without any field-monitoring or a stream-gauging station. Comprehensive studies focusing on the detailed chronology of hydro-geomorphic events and analysis of meteorological triggers and weather circulation patterns are still lacking for the studied area. We provide a spatio-temporal reconstruction of hydro-geomorphic events in four catchments of the Hrubý Jeseník Mountains, Czech Republic, with an analysis of their triggering factors using meteorological data from four nearby rain gauges. Increment cores from 794 coniferous trees (Picea abies [L.] Karst.) allowed the identification of 40 hydro-geomorphic events during the period of 1889-2013. Most of the events can be explained by extreme daily rainfalls (≥50mm) occurring in at least one rain gauge. However, in several cases, there was no record of extreme precipitation at rain gauges during the debris flow/flood event year, suggesting extremely localised rainstorms at the mountain summits. We concluded that the localisation, intensity and duration of rainstorms; antecedent moisture conditions; and amount of available sediments all influenced the initiation, spatial distribution and characteristics of hydro-geomorphic events. The most frequent synoptic situations responsible for the extreme rainfalls (1946-2015) were related to the meridional atmospheric circulation pattern. Our results enhance current knowledge of the occurrences and triggers of debris flows/floods in the Central European mountains in transition between temperate oceanic and continental climatic conditions and may prompt further research of these phenomena in the Eastern Sudetes in general. Copyright © 2016 Elsevier B.V. All rights reserved.

Virtual Rain and Stream Gauge Information Service to Support Effective Decision Making in Lower Mekong Countries

NASA Astrophysics Data System (ADS)

Basnayake, S. B.; Jayasinghe, S.; Apirumanekul, C.; Pudashine, J.; Anderson, E.; Cutter, P. G.; Ganz, D.; Towashiraporn, P.

2016-12-01

During 1995-2015, about 47% of all weather related disasters affected 2.3 billion people, and the majority (95%) of them were from Asia. About 89% of the deaths due to storms were reported in lower and middle income courtiers even though they only experienced about 26% of all storms. In most of the developing countries, decision making processes are hampered by sparse hydro-meteorological observation networks. Thus, the virtual rain and stream gauge information service is designed and developed by SERVIR-Mekong of Asian Disaster Preparedness Center (ADPC) to support effective decision making in Cambodia, Lao PDR, Myanmar, Thailand and Vietnam. The information service contains four remotely sensed data streams with regional and country specific sub setting features for easy access in limited internet bandwidths conditions. It provides rainfall data from near real time GPM IMERG (6 hours latency) with 30 minutes and 0.1X0.1 degree resolutions; TRMM daily data of 0.25X0.25 degree resolution from 1998; and CHIRPS daily data of 0.05X0.05 degree resolution since 1981 with the latency of one month. Satellite altimetry-based Jason 2 Interim Geophysical Data Record virtual stream gauge data (water body height) is provided with 12 days latency for 15 identified locations in 5 countries since 2008. To regionalize and further promote uptake of these data, TRMM monthly data has been bias corrected for Myanmar as a pilot study with spatially interpolated 18-year average (1998-2015) observed monthly rainfall data using Standard Deviation (SD) Ratio method. The results encourage to use SD ratio method for monthly bias corrections. Gamma distribution method will be tested for correcting biases of daily rainfall data with the notion that it has some limitations of capturing extreme rainfalls. The virtual rain and stream gauge information service is publically accessible through a web-based user interface hosted at SERVIR-Mekong of ADPC. Usage of the information service by partner agencies is ensured through co-development and capacity building programs. This service helps lower Mekong countries and their relevant organizations effectively use of remotely sensed data for day-to-day operations, contingency and development planning.

Satellite rainfall monitoring over Africa using multi-spectral MSG data in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Grimes, David

2010-05-01

Rainfall monitoring over Africa is crucial for a variety of humanitarian and agricultural purposes, and satellites have been used for some time to provide real-time rainfall estimates over the region. Several recent applications of satellite rainfall estimates, such as flash-flood warning systems and crop-yield models, require accurate rainfall totals at daily timescales or below. Multi-spectral Meteosat Second Generation (MSG) data provide information on cloud properties such as optical depth and cloud particle size and phase. These parameters are all relevant to the probability of rainfall occurring from a cloud and the likely intensity of that rainfall, so the use of MSG data should lead to improved satellite rainfall estimates. An artificial neural network (ANN) using multi-spectral inputs from MSG has been trained to provide daily rainfall estimates over Ethiopia, using daily rain-gauge data for calibration. Although ANN methods have previously been applied to the problem of producing rainfall estimates from multi-spectral satellite data, in general precipitation radar data have been used for calibration. The advantage of using rain-gauge data is that gauges are far more widespread over Africa than radar networks, so this method can be easily transferred and if necessary re-calibrated in different climatological regions of the continent. The ANN estimates have been validated against independent Ethiopian gauge data at a variety of time and space scales. The ANN shows an improvement in accuracy at daily timescale when compared to rainfall estimates from the TAMSAT algorithm, which uses only single channel MSG data.

A Preliminary Analysis of Precipitation Properties and Processes during NASA GPM IFloodS

NASA Technical Reports Server (NTRS)

Carey, Lawrence; Gatlin, Patrick; Petersen, Walt; Wingo, Matt; Lang, Timothy; Wolff, Dave

2014-01-01

The Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) ground measurement campaign, which took place in eastern Iowa from May 1 to June 15, 2013. The goals of the field campaign were to collect detailed measurements of surface precipitation using ground instruments and advanced weather radars while simultaneously collecting data from satellites passing overhead. Data collected by the radars and other ground instruments, such as disdrometers and rain gauges, will be used to characterize precipitation properties throughout the vertical column, including the precipitation type (e.g., rain, graupel, hail, aggregates, ice crystals), precipitation amounts (e.g., rain rate), and the size and shape of raindrops. The impact of physical processes, such as aggregation, melting, breakup and coalescence on the measured liquid and ice precipitation properties will be investigated. These ground observations will ultimately be used to improve rainfall estimates from satellites and in particular the algorithms that interpret raw data for the upcoming GPM mission's Core Observatory satellite, which launches in 2014. The various precipitation data collected will eventually be used as input to flood forecasting models in an effort to improve capabilities and test the utility and limitations of satellite precipitation data for flood forecasting. In this preliminary study, the focus will be on analysis of NASA NPOL (S-band, polarimetric) radar (e.g., radar reflectivity, differential reflectivity, differential phase, correlation coefficient) and NASA 2D Video Disdrometers (2DVDs) measurements. Quality control and processing of the radar and disdrometer data sets will be outlined. In analyzing preliminary cases, particular emphasis will be placed on 1) documenting the evolution of the rain drop size distribution (DSD) as a function of column melting processes and 2) assessing the impact of range on ground-based polarimetric radar estimates of DSD properties.

Using NEXRAD and Rain Gauge Precipitation Data for Hydrologic Calibration of SWAT in a Northeastern Watershed

USDA-ARS?s Scientific Manuscript database

The value of watershed-scale, hydrologic/water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropri...

Silt fences: An economical technique for measuring hillslope soil erosion

Treesearch

Peter R. Robichaud; Robert E. Brown

2002-01-01

Measuring hillslope erosion has historically been a costly, time-consuming practice. An easy to install low-cost technique using silt fences (geotextile fabric) and tipping bucket rain gauges to measure onsite hillslope erosion was developed and tested. Equipment requirements, installation procedures, statistical design, and analysis methods for measuring hillslope...

Proceedings of the Twelfth NASA Propagation Experimenters Meeting (NAPEX 12)

NASA Technical Reports Server (NTRS)

Davarian, Faramaz (Editor)

1988-01-01

The NASA Propagation Experimenters Meeting was convened on June 9 and 10, 1988. Pilot Field Experiments propagation studies, mobile communication systems, signal fading, communication satellites rain gauge network measurements, atmospheric attenuation studies, optical communication through the atmosphere, and digital beacon receivers were among the topics discussed.

LADOTD 24-Hour rainfall frequency maps and I-D-F curves : summary report.

DOT National Transportation Integrated Search

1991-08-01

Maximum annual 24-hour maps and Intensity-Duration-Frequency (I-D-F) curves for return periods of 2, 5, 10, 25, 50 and 100 years were developed using hourly precipitation data. Data from 92 rain gauges for the period of 1948 to 1987 were compiled and...

The Siberian High and precipitation over Cyprus

NASA Astrophysics Data System (ADS)

Lingis, P.; Michaelides, S. C.

2009-04-01

The aim of this study is to find possible teleconnection patterns associated with the Siberian High (SH) and precipitation in Cyprus. In this respect, the study examines the impacts that the SH exerts on local climate in areas far beyond the area of its domination; in particular, the relation of the teleconnection patterns derived from the SH Sea Level Pressure (SLP) characteristics and precipitation over Cyprus are examined. Four indices are used describing the characteristics of the SH (strength and geographical displacement). In an attempt to identify possible relations between precipitation, on the one hand, and the SH indices, on the other hand, a network of 32 rain gauge stations in Cyprus, both coastal and inland, was carefully selected to cover the whole island. Precipitation in Cyprus is mainly the result of baroclinic depressions traveling in the eastern Mediterranean Basin. SH as one of the dominant centers of action in the northern hemisphere, acts as one of the regulators of the preferred paths of these frontal depressions. The overall effect of the SH on these depressions is connected to characteristics and behavior of the SH, such as its intensity and location, as it may act as a blocking system preventing the propagation of migratory depressions eastwards or diverting them towards the North or South. The depressions arriving or forming over the island have a short lifespan and they are not frequent. The mean monthly sea-level pressure (SLP) was obtained from the dataset of the Climatic Research Unit of the University of East Anglia, with horizontal analysis of 5 degree latitude and 10 degree longitude grid. The 5 degree resolution global mean monthly temperature anomaly values taken were also taken from the same source. Monthly total precipitation amounts from 32 rain gauges in Cyprus were obtained from the Cyprus Meteorological Service for the period 1961 - 2000. Finally, use has been made of the reanalysis data at 2.5x2.5 degree resolution of global monthly mean SLP and precipitation rate from the National Centers for Environmental Prediction (NCEP). Principal Component Analysis (PCA) for the gridded SLP dataset for each month was performed. From this analysis, the first four Principal Components (PC) were obtained, explaining for the winter months 89-90% of the total variance and for all months 81- 90%. From the PCA and for each of the four Principal Components (hereafter denoted as PC1, PC2, PC3 and PC4), graphs of the loading distributions and the respective time series resulting from the scores of each PC were constructed. The scores were used as indices for further calculations. Susequently, the correlation coefficients between the PC scores and mean SLP for each month were calculated. The data from the 32 rain gauges were used to calculate the monthly mean precipitation over Cyprus. Extrapolation using distance weighted average algorithm was used to plot the spatial distribution of precipitation of each month over the island. Correlation coefficients were calculated between the four PC indices and the precipitation at each one of the rain gauge stations; these correlation coefficients were subsequently plotted on geographical maps in an attempt to visualize any recognizable patterns. Also, to investigate the overall effect of the four indices (i.e. PC1 to PC4) on precipitation over Cyprus, multiple correlation analysis was employed between these four indices and the total amount of precipitation of each month (the sum of all rain gauges used for each month).

Rainfall estimation from soil moisture data: crash test for SM2RAIN algorithm

NASA Astrophysics Data System (ADS)

Brocca, Luca; Albergel, Clement; Massari, Christian; Ciabatta, Luca; Moramarco, Tommaso; de Rosnay, Patricia

2015-04-01

Soil moisture governs the partitioning of mass and energy fluxes between the land surface and the atmosphere and, hence, it represents a key variable for many applications in hydrology and earth science. In recent years, it was demonstrated that soil moisture observations from ground and satellite sensors contain important information useful for improving rainfall estimation. Indeed, soil moisture data have been used for correcting rainfall estimates from state-of-the-art satellite sensors (e.g. Crow et al., 2011), and also for improving flood prediction through a dual data assimilation approach (e.g. Massari et al., 2014; Chen et al., 2014). Brocca et al. (2013; 2014) developed a simple algorithm, called SM2RAIN, which allows estimating rainfall directly from soil moisture data. SM2RAIN has been applied successfully to in situ and satellite observations. Specifically, by using three satellite soil moisture products from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation) and SMOS (Soil Moisture and Ocean Salinity); it was found that the SM2RAIN-derived rainfall products are as accurate as state-of-the-art products, e.g., the real-time version of the TRMM (Tropical Rainfall Measuring Mission) product. Notwithstanding these promising results, a detailed study investigating the physical basis of the SM2RAIN algorithm, its range of applicability and its limitations on a global scale has still to be carried out. In this study, we carried out a crash test for SM2RAIN algorithm on a global scale by performing a synthetic experiment. Specifically, modelled soil moisture data are obtained from HTESSEL model (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced by ERA-Interim near-surface meteorology. Afterwards, the modelled soil moisture data are used as input into SM2RAIN algorithm for testing weather or not the resulting rainfall estimates are able to reproduce ERA-Interim rainfall data. Correlation, root mean square differences and categorical scores were used to evaluate the goodness of the results. This analysis wants to draw global picture of the performance of SM2RAIN algorithm in absence of errors in soil moisture and rainfall data. First preliminary results over Europe have shown that SM2RAIN performs particularly well over southern Europe (e.g., Spain, Italy and Greece) while its performances diminish by moving towards Northern latitudes (Scandinavia) and over Alps. The results on a global scale will be shown and discussed at the conference session. REFERENCES Brocca, L., Melone, F., Moramarco, T., Wagner, W. (2013). A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters, 40(5), 853-858. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141. Chen F, Crow WT, Ryu D. (2014) Dual forcing and state correction via soil moisture assimilation for improved rainfall-runoff modeling. J Hydrometeor, 15, 1832-1848. Crow, W.T., van den Berg, M.J., Huffman, G.J., Pellarin, T. (2011). Correcting rainfall using satellite-based surface soil moisture retrievals: the soil moisture analysis rainfall tool (SMART). Water Resour Res, 47, W08521. Dee, D. P.,et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteorol. Soc., 137, 553-597 Massari, C., Brocca, L., Moramarco, T., Tramblay, Y., Didon Lescot, J.-F. (2014). Potential of soil moisture observations in flood modelling: estimating initial conditions and correcting rainfall. Advances in Water Resources, 74, 44-53.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2017-12-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2018-01-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH

NASA Astrophysics Data System (ADS)

Wolters, E. L. A.; van den Hurk, B. J. J. M.; Roebeling, R. A.

2011-02-01

This paper describes the evaluation of the KNMI Cloud Physical Properties - Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and cloud-top temperature (CTT) retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR) as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM), using Climate Prediction Center Morphing Technique (CMORPH) rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ~10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/-10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h-1. However, at higher rain rates (5-16 mm h-1) CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair correspondence between CPP-PP and CMORPH was found, which is reflected by high correlation coefficients (~0.7) for both rain rate and rain occurrence frequency. The daytime cycle of rainfall from CPP-PP shows distinctly different patterns for three different regions in West Africa throughout the WAM, with a decrease in dynamical range of rainfall near the Inter Tropical Convergence Zone (ITCZ). The dynamical range as retrieved from CPP-PP is larger than that from CMORPH. It is suggested that this results from both the better spatio-temporal resolution of SEVIRI, as well as from thermal infrared radiances being partly used by CMORPH, which likely smoothes the daytime precipitation signal, especially in case of cold anvils from convective systems. The promising results show that the CPP-PP algorithm, taking advantage of the high spatio-temporal resolution of SEVIRI, is of added value for monitoring daytime precipitation patterns in tropical areas.

High temporal resolution of extreme rainfall rate variability and the acoustic classification of rainfall

NASA Astrophysics Data System (ADS)

Nystuen, Jeffrey A.; Amitai, Eyal

2003-04-01

The underwater sound generated by raindrop splashes on a water surface is loud and unique allowing detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is proportional to the depth of the hydrophone and can be orders of magnitude greater than other in situ rain gauges. This feature allows high temporal resolution of the rainfall measurement. A series of rain events with extremely high rainfall rates, over 100 mm/hr, is examined acoustically. Rapid onset and cessation of rainfall intensity are detected within the convective cells of these storms with maximum 5-s resolution values exceeding 1000 mm/hr. The probability distribution functions (pdf) for rainfall rate occurrence and water volume using the longer temporal resolutions typical of other instruments do not include these extreme values. The variance of sound intensity within different acoustic frequency bands can be used as an aid to classify rainfall type. Objective acoustic classification algorithms are proposed. Within each rainfall classification the relationship between sound intensity and rainfall rate is nearly linear. The reflectivity factor, Z, also has a linear relationship with rainfall rate, R, for each rainfall classification.

Assessment of TRMM Products and Their Influence on Hydrologic Models within the Middle East and North Africa (MENA) Region Using the Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Milewski, A.; El Kadiri, R.; Durham, M. C.

2013-12-01

Satellite remote sensing datasets have been increasingly employed as an ancillary source of essential hydrologic measurements used for the modeling of hydrologic fluxes. Precipitation is one of the most important meteorological forcing parameter in hydrological investigations and land surface modeling, yet it is largely unknown or misused in water budgets and hydrologic models. The Tropical Rainfall Measurement Mission (TRMM) satellite products are widely being used by the scientific community due to the general spatial and temporal paucity of precipitation data in many parts of world and particularly in the Middle East and North Africa (MENA) region. This research utilized a two-fold approach towards understanding the accuracy of satellite-based rainfall and its application in hydrologic models First, we evaluated the uncertainty, accuracy, and precision of various rainfall satellite products (i.e. TRMM 3B42 V6, TRMM 3B42 V7, TRMM 3B42 V7a and TRMM 3B42 RT) in comparison to in situ gauge data from more than 150 rain gauges in Morocco and across the MENA region. Our analyses extend over many parts of the MENA region in order to assess the effect that different climatic regimes and topographic characteristics have on each TRMM product. Secondly, we analyzed and compared the hydrologic fluxes produced from different modeling inputs for several watersheds within the MENA region. SWAT (Soil and Water Assessment Tool) hydrologic models have been developed for the Oum Er Rbia (Morocco), Asyuti (Egypt), and the Sakarya (Turkey) watersheds. SWAT models produced for each watershed include, one model for each of the four satellite TRMM product (STBM-V6, STBM-V7, STBM-V7a, and STBM-RT) and one model for rain gauge based model (RGBM). Findings indicate the best correlation between field-based and satellite-based rainfall measurements is the TRMM V7a (Pearson coefficient: 0.875) product, followed by TRMM V7 (Pearson coefficient: 0.84), then TRMM V6 (Pearson coefficient: 0.805), and finally TRMM RT (Pearson coefficient: 0.715). However, analyses demonstrate that V7a still has an overestimation bias in arid environments (trend line slope: 1.133), and an underestimation bias in both semi-arid environments (trend line slope: 0.5982) and sub humid environments (trend line slope: 0.6800). Results suggest that all versions are consistently better correlated with field gauges in the sub humid environments (V6 Pc: 0.755, V7 Pc: 0.790, V7a Pc: 0.816 and RT Pc: 0728) than the semi-arid environments (V6 Pc: 0.494, V7 Pc: 0.549, V7a Pc: 0.548 and RT Pc: 0.305) and the arid environments (V6 Pc: 0.546, V7 Pc: 0.681, V7a Pc: 0.697 and RT Pc: 0.562). Initial model values for the Oum Er Rbia watershed (area: 48,000 km2, annual precipitation 550 mm/yr.) indicate the satellite TRMM-based models (STBM) underestimated hydrologic variables (precipitation: 19%; runoff: 25%; and recharge 35%) compared to the rain gauge-based model (RGBM). This study demonstrates the accuracy of TRMM precipitation products and shows the opportunities and challenges of their use in data scarce regions of the world.

Effect of heavy rain to the total received power

NASA Technical Reports Server (NTRS)

Iguchi, Toshio

1994-01-01

If the average power at the receiver is substantially reduced by heavy rain, the AGC (automatic gain control) circuit of the rain gauge will try to compensate this reduction by increasing the gain. If this happens, then the pulses created by rain drops are amplified more than they should be and the rainfall rate may be overestimated. If the effective diameter (blocking efficiency) of a particle is 2 mm and if the beam width is 2 cm, each particle will reduce the received power by 10 percent when it crosses the beam. Since the beam is blocked by water drops 75 percent of the total time according to the above calculation, the total received power may be reduced by 7.5 percent. To compensate this reduction to the reference value, the gain of amplifier will be increased by 8.1 percent. This increase of gain will increase all pulse sizes by the same fraction and result in the overestimate of the rainfall rate.

Rain-rate data base development and rain-rate climate analysis

NASA Technical Reports Server (NTRS)

Crane, Robert K.

1993-01-01

The single-year rain-rate distribution data available within the archives of Consultative Committee for International Radio (CCIR) Study Group 5 were compiled into a data base for use in rain-rate climate modeling and for the preparation of predictions of attenuation statistics. The four year set of tip-time sequences provided by J. Goldhirsh for locations near Wallops Island were processed to compile monthly and annual distributions of rain rate and of event durations for intervals above and below preset thresholds. A four-year data set of tropical rain-rate tip-time sequences were acquired from the NASA TRMM program for 30 gauges near Darwin, Australia. They were also processed for inclusion in the CCIR data base and the expanded data base for monthly observations at the University of Oklahoma. The empirical rain-rate distributions (edfs) accepted for inclusion in the CCIR data base were used to estimate parameters for several rain-rate distribution models: the lognormal model, the Crane two-component model, and the three parameter model proposed by Moupfuma. The intent of this segment of the study is to obtain a limited set of parameters that can be mapped globally for use in rain attenuation predictions. If the form of the distribution can be established, then perhaps available climatological data can be used to estimate the parameters rather than requiring years of rain-rate observations to set the parameters. The two-component model provided the best fit to the Wallops Island data but the Moupfuma model provided the best fit to the Darwin data.

Spatial reconstruction of semi-quantitative precipitation fields over Africa during the nineteenth century from documentary evidence and gauge data

NASA Astrophysics Data System (ADS)

Nicholson, Sharon E.; Klotter, Douglas; Dezfuli, Amin K.

2012-07-01

The article presents a newly created precipitation data set for the African continent and describes the methodology used in its creation. It is based on a combination of proxy data and rain gauge records. The data set is semi-quantitative, with a "wetness" index of - 3 to + 3 to describe the quality of the rainy season. It covers the period AD 1801 to 1900 and includes data for 90 geographical regions of the continent. The results underscore a multi-decadal period of aridity early in the nineteenth century.

Dual-polarization characteristics of the radar ocean return in the presence of rain

NASA Technical Reports Server (NTRS)

Meneghini, R.; Kumagai, H.; Kozu, T.

1992-01-01

Experimental data are presented on the polarimetric and dual-wavelength characteristics of the ocean surface in the presence of rain. To explain a portion of the variability observed in scatter plots under rain conditions, a storm model is used that incorporates measured drop size distributions. The fairly large variability indicates that effects of drop size distribution and the presence of partially melted particles can introduce a significant error in the estimate of attenuation. This effect is especially significant in the case of a 10-GHz radar under high rain rates. A surface reference method at this frequency will tend to overestimate the rain attenuation unless melting layer attenuation is properly taken into account. Observations of the cross-polarization return in stratiform rain over an ocean surface show three distinct components. Two of these correspond to aspherical, nonaligned particles in the melting layer seen in the direct and mirror-image returns. The remaining part depends both on the off-nadir depolarization by the surface and on the rain medium. A possible mechanism for this latter effect is the bistatic scattering from the rain to the surface.

Optimizing weather radar observations using an adaptive multiquadric surface fitting algorithm

NASA Astrophysics Data System (ADS)

Martens, Brecht; Cabus, Pieter; De Jongh, Inge; Verhoest, Niko

2013-04-01

Real time forecasting of river flow is an essential tool in operational water management. Such real time modelling systems require well calibrated models which can make use of spatially distributed rainfall observations. Weather radars provide spatial data, however, since radar measurements are sensitive to a large range of error sources, often a discrepancy between radar observations and ground-based measurements, which are mostly considered as ground truth, can be observed. Through merging ground observations with the radar product, often referred to as data merging, one may force the radar observations to better correspond to the ground-based measurements, without losing the spatial information. In this paper, radar images and ground-based measurements of rainfall are merged based on interpolated gauge-adjustment factors (Moore et al., 1998; Cole and Moore, 2008) or scaling factors. Using the following equation, scaling factors (C(xα)) are calculated at each position xα where a gauge measurement (Ig(xα)) is available: Ig(xα)+-? C (xα) = Ir(xα)+ ? (1) where Ir(xα) is the radar-based observation in the pixel overlapping the rain gauge and ? is a constant making sure the scaling factor can be calculated when Ir(xα) is zero. These scaling factors are interpolated on the radar grid, resulting in a unique scaling factor for each pixel. Multiquadric surface fitting is used as an interpolation algorithm (Hardy, 1971): C*(x0) = aTv + a0 (2) where C*(x0) is the prediction at location x0, the vector a (Nx1, with N the number of ground-based measurements used) and the constant a0 parameters describing the surface and v an Nx1 vector containing the (Euclidian) distance between each point xα used in the interpolation and the point x0. The parameters describing the surface are derived by forcing the surface to be an exact interpolator and impose that the sum of the parameters in a should be zero. However, often, the surface is allowed to pass near the observations (i.e. the observed scaling factors C(xα)) on a distance aαK by introducing an offset parameter K, which results in slightly different equations to calculate a and a0. The described technique is currently being used by the Flemish Environmental Agency in an online forecasting system of river discharges within Flanders (Belgium). However, rescaling the radar data using the described algorithm is not always giving rise to an improved weather radar product. Probably one of the main reasons is the parameters K and ? which are implemented as constants. It can be expected that, among others, depending on the characteristics of the rainfall, different values for the parameters should be used. Adaptation of the parameter values is achieved by an online calibration of K and ? at each time step (every 15 minutes), using validated rain gauge measurements as ground truth. Results demonstrate that rescaling radar images using optimized values for K and ? at each time step lead to a significant improvement of the rainfall estimation, which in turn will result in higher quality discharge predictions. Moreover, it is shown that calibrated values for K and ? can be obtained in near-real time. References Cole, S. J., and Moore, R. J. (2008). Hydrological modelling using raingauge- and radar-based estimators of areal rainfall. Journal of Hydrology, 358(3-4), 159-181. Hardy, R.L., (1971) Multiquadric equations of topography and other irregular surfaces, Journal of Geophysical Research, 76(8): 1905-1915. Moore, R. J., Watson, B. C., Jones, D. A. and Black, K. B. (1989). London weather radar local calibration study. Technical report, Institute of Hydrology.

Variability of the recent climate of eastern Africa

NASA Astrophysics Data System (ADS)

Schreck, Carl J., III; Semazzi, Fredrick H. M.

2004-05-01

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of eastern Africa and opposite conditions over the southern sector. This rainfall trend mode eluded detection in previous studies that did not include recent decades of data, because the signal was still relatively weak. The wind projection onto this mode indicates that the primary flow that feeds the positive anomaly region over the northern part of eastern Africa emanates primarily from the rainfall-deficient southern region of eastern Africa and Sudan. Although we do not assign attribution of the trend mode to global warming (in part because of the relatively short period of analysis), the evidence, based on our results and previous studies, strongly suggests a potential connection.

Gauge-adjusted rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Rieckermann, Jörg; Bareš, Vojtěch

2017-01-01

Increasing urbanization makes it more and more important to have accurate stormwater runoff predictions, especially with potentially severe weather and climatic changes on the horizon. Such stormwater predictions in turn require reliable rainfall information. Especially for urban centres, the problem is that the spatial and temporal resolution of rainfall observations should be substantially higher than commonly provided by weather services with their standard rainfall monitoring networks. Commercial microwave links (CMLs) are non-traditional sensors, which have been proposed about a decade ago as a promising solution. CMLs are line-of-sight radio connections widely used by operators of mobile telecommunication networks. They are typically very dense in urban areas and can provide path-integrated rainfall observations at sub-minute resolution. Unfortunately, quantitative precipitation estimates (QPEs) from CMLs are often highly biased due to several epistemic uncertainties, which significantly limit their usability. In this manuscript we therefore suggest a novel method to reduce this bias by adjusting QPEs to existing rain gauges. The method has been specifically designed to produce reliable results even with comparably distant rain gauges or cumulative observations. This eliminates the need to install reference gauges and makes it possible to work with existing information. First, the method is tested on data from a dedicated experiment, where a CML has been specifically set up for rainfall monitoring experiments, as well as operational CMLs from an existing cellular network. Second, we assess the performance for several experimental layouts of ground truth from rain gauges (RGs) with different spatial and temporal resolutions. The results suggest that CMLs adjusted by RGs with a temporal aggregation of up to 1 h (i) provide precise high-resolution QPEs (relative error < 7 %, Nash-Sutcliffe efficiency coefficient > 0.75) and (ii) that the combination of both sensor types clearly outperforms each individual monitoring system. Unfortunately, adjusting CML observations to RGs with longer aggregation intervals of up to 24 h has drawbacks. Although it substantially reduces bias, it unfavourably smoothes out rainfall peaks of high intensities, which is undesirable for stormwater management. A similar, but less severe, effect occurs due to spatial averaging when CMLs are adjusted to remote RGs. Nevertheless, even here, adjusted CMLs perform better than RGs alone. Furthermore, we provide first evidence that the joint use of multiple CMLs together with RGs also reduces bias in their QPEs. In summary, we believe that our adjustment method has great potential to improve the space-time resolution of current urban rainfall monitoring networks. Nevertheless, future work should aim to better understand the reason for the observed systematic error in QPEs from CMLs.

Climatological Processing of Radar Data for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Kulie, Mark; Marks, David; Robinson, Michael; Silberstein, David; Wolff, David; Ferrier, Brad; Amitai, Eyal; Fisher, Brad; Wang, Jian-Xin; Augustine, David;

The impact of a windshield in a tipping bucket rain gauge on the reduction of losses in precipitation measurements during snowfall events

NASA Astrophysics Data System (ADS)

Buisan, Samuel T.; Collado, Jose Luis; Alastrue, Javier

2016-04-01

The amount of snow available controls the ecology and hydrological response of mountainous areas and cold regions and affects economic activities including winter tourism, hydropower generation, floods and water supply. An accurate measurement of snowfall accumulation amount is critical and source of error for a better evaluation and verification of numerical weather forecast, hydrological and climate models. It is well known that the undercatch of solid precipitation resulting from wind-induced updrafts at the gauge orifice is the main factor affecting the quality and accuracy of the amount of snowfall precipitation. This effect can be reduced by the use of different windshields. Overall, Tipping Bucket Rain Gauges (TPBRG) provide a large percentage of the precipitation amount measurements, in all climate regimes, estimated at about 80% of the total of observations by automatic instruments. In the frame of the WMO-SPICE project, we compared at the Formigal-Sarrios station (Spanish Pyrenees, 1800 m a.s.l.) the measured precipitation in two heated TPBRGs, one of them protected with a single alter windshield in order to reduce the wind bias. Results were contrasted with measured precipitation using the SPICE reference gauge (Pluvio2 OTT) in a Double Fence Intercomparison Reference (DFIR). Results reported that shielded reduces undercatch up to 40% when wind speed exceeds 6 m/s. The differences when compared with the reference gauge reached values higher than 70%. The inaccuracy of these measurements showed a significant impact in nowcasting operations and climatology in Spain, especially during some heavy snowfall episodes. Also, hydrological models showed a better agreement with the observed rivers flow when including the precipitation not accounted during these snowfall events. The conclusions of this experiment will be used to take decisions on the suitability of the installation of windshields in stations characterized by a large quantity of snowfalls during the winter season and which are mainly located in Northern Spain

HYDROLOGIC MODELING OF AN EASTERN PENNSYLVANIA WATERSHED WITH NEXRAD AND RAIN GAUGE DATA

EPA Science Inventory

This paper applies the Soil Water Assessment Tool (SWAT) to model the hydrology in the Pocono Creek watershed located in Monroe County, Pa. The calibrated model will be used in a subsequent study to examine the impact of population growth and rapid urbanization in the watershed o...

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Standard Fog Collector Measurements Along the Central and Northern California Coast During the 2014 and 2015 Fog Seasons

NASA Astrophysics Data System (ADS)

Fernandez, D.; Torregrosa, A.; Weiss-Penzias, P. S.; Mairs, A. A.; Wilson, S.; Bowman, M.; Barkley, T.; Gravelle, M.; Oliphant, A. J.

2015-12-01

Since 2014 an extensive network of standard fog collectors has been deployed along the coast of California, from as far south as southern Big Sur (36.1° N) to as far north as Arcata (40.8° N) at over a dozen sites that contain a total of several dozen of the fog collecting devices. This research is being done in conjunction with the Fognet Project that is looking at the levels of monomethyl mercury in fog water. Data collected reveal a fascinating variability in the amount of fog water collected across different scales of distance, elevation, time and location. In addition, a number of different types of mesh have been deployed and co-located to examine the variation in their fog water collecting capability in identical conditions. Mesh variations exhibit smaller variability across mesh type than had previously been expected. This study documents results found thus far across the network and also discusses the quantification of the errors associated with tipping bucket rain gauge measurements of water volumes and thus the importance of tipping bucket rain gauge calibration.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Interception of rainfall and surface runoff in the Brazilian Cerrado

NASA Astrophysics Data System (ADS)

Tarso Oliveira, Paulo; Wendland, Edson; Nearing, Mark; Perea Martins, João

2014-05-01

The Brazilian Cerrado plays a fundamental role in water resources dynamics because it distributes fresh water to the largest basins in Brazil and South America. In recent decades, the native Cerrado vegetation has increasingly been replaced by agricultural crops and pasture. These land cover and land use changes have altered the hydrological processes. Meanwhile, little is known about the components of the water balance in the Brazilian Cerrado, mainly because the experimental field studies in this region are scarce or nonexistent. The objective of this study was to evaluate two hydrological processes under native Cerrado vegetation, the canopy interception (CI) and the surface runoff (R). The Cerrado physiognomy was classified as "cerrado sensu stricto denso" with an absolute density of 15,278 trees ha-1, and a basal area of 11.44 m2 ha-1. We measured the gross rainfall (P) from an automated tipping bucket rain gauge (model TB4) located in a tower with 11 m of height on the Cerrado. Throughfall (TF) was obtained from 15 automated tipping bucket rain gauges (model Davis) spread below the Cerrado vegetation and randomly relocated every month during the wet season. Stemflow (SF) was measured on 12 trees using a plastic hose wrapped around the trees trunks, sealed with neutral silicone sealant, and a bucket to store the water. The canopy interception was computed by the difference between P and the sum of TF and SF. Surface runoff under undisturbed Cerrado was collected in three plots of 100 m2(5 x 20 m) in size and slope steepness of approximately 0.09 m m-1. The experimental study was conducted between January 2012 and November 2013. We found TF of 81.0% of P and SF of 1.6% of P, i.e. the canopy interception was calculated at 17.4% of P. There was a statistically significant correlation (p < 0.05) between gross rainfall and TF, SF, and CI with correlation coefficients r > 0.8. Our results suggest that the rainfall intensity, the characteristics of the trees trunks (crooked and twisted) and stand structure are the main factors that have influenced CI. The average surface runoff under undisturbed Cerrado was less than 1% of the P, and did not have significant correlation (p > 0.05) with P, but had a significant correlation with maximum 30 minute rainfall intensity (I30). This low value for surface runoff indicates that the forest ?oor has a strong influence over surface runoff generation under undisturbed Cerrado. This process is poorly studied; however, we believe this can be a key to understanding the surface runoff generation under undisturbed Cerrado, and in other tropical vegetation, such as the Amazon rainforest.

Bias correction of satellite-based rainfall data

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Solomatine, Dimitri

2015-04-01

Limitation in hydro-meteorological data availability in many catchments limits the possibility of reliable hydrological analyses especially for near-real-time predictions. However, the variety of satellite based and meteorological model products for rainfall provides new opportunities. Often times the accuracy of these rainfall products, when compared to rain gauge measurements, is not impressive. The systematic differences of these rainfall products from gauge observations can be partially compensated by adopting a bias (error) correction. Many of such methods correct the satellite based rainfall data by comparing their mean value to the mean value of rain gauge data. Refined approaches may also first find out a suitable time scale at which different data products are better comparable and then employ a bias correction at that time scale. More elegant methods use quantile-to-quantile bias correction, which however, assumes that the available (often limited) sample size can be useful in comparing probabilities of different rainfall products. Analysis of rainfall data and understanding of the process of its generation reveals that the bias in different rainfall data varies in space and time. The time aspect is sometimes taken into account by considering the seasonality. In this research we have adopted a bias correction approach that takes into account the variation of rainfall in space and time. A clustering based approach is employed in which every new data point (e.g. of Tropical Rainfall Measuring Mission (TRMM)) is first assigned to a specific cluster of that data product and then, by identifying the corresponding cluster of gauge data, the bias correction specific to that cluster is adopted. The presented approach considers the space-time variation of rainfall and as a result the corrected data is more realistic. Keywords: bias correction, rainfall, TRMM, satellite rainfall

Concurrency and climate change signal in Scottish flooding

NASA Astrophysics Data System (ADS)

Harding, A. E.; Butler, A.; Goody, N.; Bertram, D.; Baggaley, N.; Tett, S. F.

2013-12-01

The Scottish Environment Protection Agency maintains a database of river gauging stations and intensity rain-gauges with a 3-hourly resolution that covers the majority of Scotland. Both SEPA and a number of other Scottish agencies are invested in climate change attribution in this data set. SEPA's main interest lies in trend detection and changes in river level (';stage') data throughout Scotland. Emergency response teams are more concerned with the concurrency of multiple flood events that might stretch their ability to respond effectively. Unfortunately, much of the rainfall signal within SEPA's river-gauge data is altered by land use changes, modified by artificial interventions such as reservoirs, compromised by tidal flow, or obscured by measurement issues. Data reduction techniques, indices of extreme rainfall, and hydrology-driven discrimination have been employed to produce a reduced set of flood-relevant information for 24-hour ';flashy' events. Links between this set and North Atlantic circulation have been explored, as have patterns of mutual occurrence across Scotland and location- and seasonally- dependent trends through time. Both frontal systems and summer convective storms have been characterised in terms of subsequent flood-inducing flow regime, their changing behaviour over the last fifty years, and their spatial extent. This is the first stage of an ongoing project that will intelligently expand to take less robust river and rain-gauge stations into account through statistical analysis and hydrological modelling. It is also the first study of its type to analyse a nation-scale dataset of both rainfall and river flow from multiple catchments for flood event concurrency. As rainfall events are expected to intensify across much of Europe, this kind of research is likely to have an increasing degree of relevance for policy-makers. This project demonstrates that productive, policy-relevant and mutually-rewarding partnerships are already underway.

Risk assessment of tropical cyclone rainfall flooding in the Delaware River Basin

NASA Astrophysics Data System (ADS)

Lu, P.; Lin, N.; Smith, J. A.; Emanuel, K.

2016-12-01

Rainfall-induced inland flooding is a leading cause of death, injury, and property damage from tropical cyclones (TCs). In the context of climate change, it has been shown that extreme precipitation from TCs is likely to increase during the 21st century. Assessing the long-term risk of inland flooding associated with landfalling TCs is therefore an important task. Standard risk assessment techniques, which are based on observations from rain gauges and stream gauges, are not broadly applicable to TC induced flooding, since TCs are rare, extreme events with very limited historical observations at any specific location. Also, rain gauges and stream gauges can hardly capture the complex spatial variation of TC rainfall and flooding. Furthermore, the utility of historically based assessments is compromised by climate change. Regional dynamical downscaling models can resolve many features of TC precipitation. In terms of risk assessment, however, it is computationally demanding to run such models to obtain long-term climatology of TC induced flooding. Here we apply a computationally efficient climatological-hydrological method to assess the risk of inland flooding associated with landfalling TCs. It includes: 1) a deterministic TC climatology modeling method to generate large numbers of synthetic TCs with physically correlated characteristics (i.e., track, intensity, size) under observed and projected climates; 2) a simple physics-based tropical cyclone rainfall model which is able to simulate rainfall fields associated with each synthetic storm; 3) a hydrologic modeling system that takes in rainfall fields to simulate flood peaks over an entire drainage basin. We will present results of this method applied to the Delaware River Basin in the mid-Atlantic US.

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff-erosion model in the Mamuaba catchment, Brazil.

PubMed

Marques da Silva, Richarde; Guimarães Santos, Celso Augusto; Carneiro de Lima Silva, Valeriano; Pereira e Silva, Leonardo

2013-11-01

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

Estimation of Surface Runoff in the Jucar River Basin from Rainfall Data and SMOS Soil Moisture

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Gonzalez Robles, Maura; Herrera Daza, Eddy; Khodayar, Samiro; Lopez-Baeza, Ernesto

2013-04-01

Surface runoff is the water that flows after soil is infiltrated to full capacity and excess water from rain, meltwater, or other sources flows over the land. When the soil is saturated and the depression storage filled, and rain continues to fall, the rainfall will immediately produce surface runoff. The Soil Conservation Service Curve Number (SCS-CN) method is widely used for determining the approximate direct runoff volume for a given rainfall event in a particular area. The advantage of the method is its simplicity and widespread inclusion in existing computer models. It was originally developed by the US Department of Agriculture, Soil Conservation Service, and documented in detail in the National Engineering Handbook, Sect. 4: Hydrology (NEH-4) (USDA-SCS, 1985). Although the SCS-CN method was originally developed in the United States and mainly for the evaluation of storm runoff in small agricultural watersheds, it soon evolved well beyond its original objective and was adopted for various land uses and became an integral part of more complex, long-term, simulation models. The basic assumption of the SCS-CN method is that, for a single storm, the ratio of actual soil retention after runoff begins to potential maximum retention is equal to the ratio of direct runoff to available rainfall. This relationship, after algebraic manipulation and inclusion of simplifying assumptions, results in the following equation given in USDA-SCS (1985): (P--0,2S)2 Q = (P + 0,8S) where Q is the average runoff (mm), P the effective precipitation (mm) and S is potential maximum retention (mm) after the rainfall event. The study has been applied to the Jucar River Basin area, East of Spain. A selection of recent significant rainfall events has been made corresponding to the periods around 22nd November, 2011 and 28-29 September and 10 October, 2012, from Jucar River Basin Authority rain gauge data. Potential maximum retention values for each point have been assumed as the first SMOS soil moisture values available at the closest DGG node immediately after saturation produced by the rain. The results are shown as maps of precipitation and soil moisture obtained using a V4 integration method between a linear and nearest neighbour methods. Surface runoff maps are consequently obtained using the SCS-CN equation given earlier. These results have also been compared to COSMO-CLM model simulations for the same periods. It is envisaged to obtain precipitation maps from MSG-SEVIRI data.

Identification of independent storm events: Seasonal and spatial variability of times between storms in Alpine area

NASA Astrophysics Data System (ADS)

Iadanzaa, Carla; Rianna, Maura; Orlando, Dario; Ubertini, Lucio; Napolitano, Francesco

2013-10-01

The aim of the paper is the identification of rain events that trigger landslides through the use of an exponential method to separate stochastic independent events. This activity is carried out within the definition of empirical rainfall thresholds for debris flows and shallow landslides. The study area is the Trento district, which is located in the northeast zone of an Alpine area. The work evaluates the factors that affect the variability in space and time of the critical duration of each rain gauge, defined as the minimum dry period duration that separates two rainy periods that are stochastically independent.

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

Lekula, Moiteela; Lubczynski, Maciek W.; Shemang, Elisha M.; Verhoef, Wouter

2018-06-01

Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFE∼11 km, TRMM-3B42∼27 km, CMOPRH∼27 km and CMORPH∼8 km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFE∼11 km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of "miss" rainfall events and the "miss-bias", as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.

Implication of Intrastorm Rainfall-Canopy Interaction on Interception Performance of Broadleaf Evergreen Shrubs in an Ultra-Urban Setting

NASA Astrophysics Data System (ADS)

Yerk, W.; Montalto, F. A.

2015-12-01

Because of its ability to intercept a portion of rainfall, vegetated canopies can play substantial role in modulating the urban hydrological cycle. However, canopy interception research has historically been focused to forest canopies. The goal of our research is to quantify rainfall partitioning by isolated evergreen shrub canopies in an ultra-urban setting. The three year field experiment involved three exemplars of cherry laurel (Prunus laurocerasus 'Otto Luyken'.) Ten rain gauges positioned under each plant were used to measure throughfall with a sampling frequency of five seconds. A number of specific techniques were implemented to minimize error associated with the gauges, e.g., splash-in, splash-out and excessive wetting. The cumulative throughfall deficit (i.e., gross precipitation minus throughfall within the canopy projected area and minus stemflow) for the periods of August-December 2013, April-December 2014 and April-July 2015 was 39%. Spatial variability of throughfall was large (coefficient of variation up to 1.5.) Stable areas of preferential throughfall flux were observed. Stemflow showed a high variability (1.4 - 24%) between rain events. The relationship between throughfall and precipitation intensity was strongly linear (adjusted coefficient of determination R2 0.79) throughout the entire range of observed rainfall intensities. The overall ratio of throughfall to precipitation intensity was 0.48:1. The observations suggest that reduction of throughfall intensity by the canopy during a rainstorm determines the aggregate interception depth. In contrast, the amount of water stored on the canopy and evaporated between and after rain events contributes minimally to interception loss. Penman-Monteith estimates of wet canopy evaporation cannot account for the throughfall deficit. Lateral displacement of microdrops beyond the canopy projected area is another phenomenon that will be discussed and most recent observations of an extended gauge network will be presented.

A radar-based hydrological model for flash flood prediction in the dry regions of Israel

NASA Astrophysics Data System (ADS)

Ronen, Alon; Peleg, Nadav; Morin, Efrat

2014-05-01

Flash floods are floods which follow shortly after rainfall events, and are among the most destructive natural disasters that strike people and infrastructures in humid and arid regions alike. Using a hydrological model for the prediction of flash floods in gauged and ungauged basins can help mitigate the risk and damage they cause. The sparsity of rain gauges in arid regions requires the use of radar measurements in order to get reliable quantitative precipitation estimations (QPE). While many hydrological models use radar data, only a handful do so in dry climate. This research presents a robust radar-based hydro-meteorological model built specifically for dry climate. Using this model we examine the governing factors of flash floods in the arid and semi-arid regions of Israel in particular and in dry regions in general. The hydrological model built is a semi-distributed, physically-based model, which represents the main hydrological processes in the area, namely infiltration, flow routing and transmission losses. Three infiltration functions were examined - Initial & Constant, SCS-CN and Green&Ampt. The parameters for each function were found by calibration based on 53 flood events in three catchments, and validation was performed using 55 flood events in six catchments. QPE were obtained from a C-band weather radar and adjusted using a weighted multiple regression method based on a rain gauge network. Antecedent moisture conditions were calculated using a daily recharge assessment model (DREAM). We found that the SCS-CN infiltration function performed better than the other two, with reasonable agreement between calculated and measured peak discharge. Effects of storm characteristics were studied using synthetic storms from a high resolution weather generator (HiReS-WG), and showed a strong correlation between storm speed, storm direction and rain depth over desert soils to flood volume and peak discharge.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Evaluation of rainfall structure on hydrograph simulation: Comparison of radar and interpolated methods, a study case in a tropical catchment

NASA Astrophysics Data System (ADS)

Velasquez, N.; Ochoa, A.; Castillo, S.; Hoyos Ortiz, C. D.

2017-12-01

The skill of river discharge simulation using hydrological models strongly depends on the quality and spatio-temporal representativeness of precipitation during storm events. All precipitation measurement strategies have their own strengths and weaknesses that translate into discharge simulation uncertainties. Distributed hydrological models are based on evolving rainfall fields in the same time scale as the hydrological simulation. In general, rainfall measurements from a dense and well maintained rain gauge network provide a very good estimation of the total volume for each rainfall event, however, the spatial structure relies on interpolation strategies introducing considerable uncertainty in the simulation process. On the other hand, rainfall retrievals from radar reflectivity achieve a better spatial structure representation but with higher uncertainty in the surface precipitation intensity and volume depending on the vertical rainfall characteristics and radar scan strategy. To assess the impact of both rainfall measurement methodologies on hydrological simulations, and in particular the effects of the rainfall spatio-temporal variability, a numerical modeling experiment is proposed including the use of a novel QPE (Quantitative Precipitation Estimation) method based on disdrometer data in order to estimate surface rainfall from radar reflectivity. The experiment is based on the simulation of 84 storms, the hydrological simulations are carried out using radar QPE and two different interpolation methods (IDW and TIN), and the assessment of simulated peak flow. Results show significant rainfall differences between radar QPE and the interpolated fields, evidencing a poor representation of storms in the interpolated fields, which tend to miss the precise location of the intense precipitation cores, and to artificially generate rainfall in some areas of the catchment. Regarding streamflow modelling, the potential improvement achieved by using radar QPE depends on the density of the rain gauge network and its distribution relative to the precipitation events. The results for the 84 storms show a better model skill using radar QPE than the interpolated fields. Results using interpolated fields are highly affected by the dominant rainfall type and the basin scale.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) are provided in order to give a detailed picture of the improvements and remaining challenges.

Integrated approach for the assessment and development of groundwater resources in arid lands: Applications in the Quetta Valley, Pakistan

NASA Astrophysics Data System (ADS)

Sagintayev, Zhanay (Jay Sagin)

The lack of adequate field measurements (e.g., precipitation and stream flow) and difficulty in obtaining them often hampers the construction and calibration of rainfall-runoff models over many of the world's watersheds, leaving key elements of the hydrologic cycle unconstrained. I adopted methodologies that rely heavily on readily available remote sensing datasets as viable alternatives and useful tools for assessing, managing, and modeling the water resources of such remote and inadequately gauged regions. The Soil and Water Assessment Tool was selected for continuous (1998--2005) rainfall-runoff modeling of the northeast part of the Pishin Lora basin (NEPL), a politically unstable area that lacks adequate rain gauge and stream flow data. To account for the paucity of rain gauge and stream flow gauge data, input to the model included satellite-based Tropical Rainfall Measuring Mission TRMM precipitation data. Modeled runoff was calibrated against satellite-based observations including: (1) monthly estimates of the water volumes impounded by the Khushdil Khan (latitude 30° 40'N, longitude 67° 40'E) and the Kara Lora (latitude 30° 34'N, longitude 66° 52'E) reservoirs, and (2) inferred wet versus dry conditions in streams across the NEPL throughout this period. Calibrations were also conducted against observed flow reported from the Burj Aziz Khan station at the NEPL outlet (latitude 30°20'N; longitude 66°35'E). Model simulations indicate that (1) average annual precipitation (1998--2005), surface runoff, and net recharge are 1,300 x 106 m3, 148 x 106 m3, and 361 x 106 m3, respectively; (2) within the NEPL watershed, precipitation and runoff are high for the northeast (precipitation: 194 mm/year; runoff: 38 x 106 m 3/year) and northwest (134 mm/year; 26 x 106 m3/y) basins compared to the southern basin (124 mm/year; 8 x 106 m3/year); and (3) construction of delay action dams in the northeast and northwest basins of the NEPL could increase recharge from 361 x 106 m3/year up to 432 x 106 m3/year and achieve sustainable extraction. The adopted methodologies are not a substitute for traditional approaches that require extensive field datasets, but they could provide first-order estimates for rainfall, runoff, and recharge in the arid and semi-arid parts of the world that are inaccessible and/or lack adequate coverage with stream flow and precipitation data.

A study of the threshold method utilizing raingage data

NASA Technical Reports Server (NTRS)

Short, David A.; Wolff, David B.; Rosenfeld, Daniel; Atlas, David

1993-01-01

The threshold method for estimation of area-average rain rate relies on determination of the fractional area where rain rate exceeds a preset level of intensity. Previous studies have shown that the optimal threshold level depends on the climatological rain-rate distribution (RRD). It has also been noted, however, that the climatological RRD may be composed of an aggregate of distributions, one for each of several distinctly different synoptic conditions, each having its own optimal threshold. In this study, the impact of RRD variations on the threshold method is shown in an analysis of 1-min rainrate data from a network of tipping-bucket gauges in Darwin, Australia. Data are analyzed for two distinct regimes: the premonsoon environment, having isolated intense thunderstorms, and the active monsoon rains, having organized convective cell clusters that generate large areas of stratiform rain. It is found that a threshold of 10 mm/h results in the same threshold coefficient for both regimes, suggesting an alternative definition of optimal threshold as that which is least sensitive to distribution variations. The observed behavior of the threshold coefficient is well simulated by assumption of lognormal distributions with different scale parameters and same shape parameters.

Application of a Threshold Method to the TRMM Radar for the Estimation of Space-Time Rain Rate Statistics

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Jones, Jeffrey A.

1997-01-01

One of the TRMM radar products of interest is the monthly-averaged rain rates over 5 x 5 degree cells. Clearly, the most directly way of calculating these and similar statistics is to compute them from the individual estimates made over the instantaneous field of view of the Instrument (4.3 km horizontal resolution). An alternative approach is the use of a threshold method. It has been established that over sufficiently large regions the fractional area above a rain rate threshold and the area-average rain rate are well correlated for particular choices of the threshold [e.g., Kedem et al., 19901]. A straightforward application of this method to the TRMM data would consist of the conversion of the individual reflectivity factors to rain rates followed by a calculation of the fraction of these that exceed a particular threshold. Previous results indicate that for thresholds near or at 5 mm/h, the correlation between this fractional area and the area-average rain rate is high. There are several drawbacks to this approach, however. At the TRMM radar frequency of 13.8 GHz the signal suffers attenuation so that the negative bias of the high resolution rain rate estimates will increase as the path attenuation increases. To establish a quantitative relationship between fractional area and area-average rain rate, an independent means of calculating the area-average rain rate is needed such as an array of rain gauges. This type of calibration procedure, however, is difficult for a spaceborne radar such as TRMM. To estimate a statistic other than the mean of the distribution requires, in general, a different choice of threshold and a different set of tuning parameters.

Scale Dependence of Statistics of Spatially Averaged Rain Rate Seen in TOGA COARE Comparison with Predictions from a Stochastic Model

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, T. L.; Lau, William K. M. (Technical Monitor)

2002-01-01

A characteristic feature of rainfall statistics is that they in general depend on the space and time scales over which rain data are averaged. As a part of an earlier effort to determine the sampling error of satellite rain averages, a space-time model of rainfall statistics was developed to describe the statistics of gridded rain observed in GATE. The model allows one to compute the second moment statistics of space- and time-averaged rain rate which can be fitted to satellite or rain gauge data to determine the four model parameters appearing in the precipitation spectrum - an overall strength parameter, a characteristic length separating the long and short wavelength regimes and a characteristic relaxation time for decay of the autocorrelation of the instantaneous local rain rate and a certain 'fractal' power law exponent. For area-averaged instantaneous rain rate, this exponent governs the power law dependence of these statistics on the averaging length scale $L$ predicted by the model in the limit of small $L$. In particular, the variance of rain rate averaged over an $L \\times L$ area exhibits a power law singularity as $L \\rightarrow 0$. In the present work the model is used to investigate how the statistics of area-averaged rain rate over the tropical Western Pacific measured with ship borne radar during TOGA COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmospheric Response Experiment) and gridded on a 2 km grid depends on the size of the spatial averaging scale. Good agreement is found between the data and predictions from the model over a wide range of averaging length scales.

Spatial-temporal variability of precipitation in Mountainous Regions in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Prat, O. P.; Barros, A. P.

2009-09-01

The purpose of this work is to investigate the mechanisms of mountainous precipitation and specifically to quantify the influence of the topography on the modification of microphysical and dynamical processes of large weather systems or on the onset of localized convective storms. Three measurement campaigns involving the deployment of one (July-August 2008) or two (October-November 2008, and June-July 2009) Micro Rain Radars (MMR) were conducted in the Great Smoky Mountains National Park (GSMNP) in the Southern Appalachians, with the goal to provide microphysical observations. Here we focus on the characterization of the diurnal cycle of rainfall and the yearly repartition of precipitation both from MRR records and from more than 30 rain gauges deployed from mid- to high-elevation along exposed ridges in the vicinity of the MRR deployment sites. A particular attention is paid to the quantification of space-time patterns of orographic enhancements between valley and ridge locations for the MRR deployment sites. The second aspect of this work, concerns a comparison of raingauge and vertically pointing radars (MRR) records with TRMM 2A25 precipitation products. A long term (from 6 months to more than two years and depending on the rain gauge installation) systematic statistical analysis is performed in order to quantify differences between ground based and remotely sensed observations for precipitation events at the time of satellite overpass. The presentation will provide a synthesis of data analysis and sensor intercomparison.

Challenges with space-time rainfall in urban hydrology highlighted with a semi-distributed model using C-band and X-band radar data

NASA Astrophysics Data System (ADS)

da Silva Rocha Paz, Igor; Ichiba, Abdellah; Skouri-Plakali, Ilektra; Lee, Jisun; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2017-04-01

Climate change and global warming are expected to make precipitation events more frequent, more severe and more local. This may have serious consequences for human health, the environment, cultural heritage, economic activities, utilities and public service providers. Then precipitation risk and water management is a key challenge for densely populated urban areas. Applications derived from high (time and space) resolution observation of precipitations are to make our cities more weather-ready. Finer resolution data available from X-band dual radar measurements enhance engineering tools as used for urban planning policies as well as protection (mitigation/adaptation) strategies to tackle climate-change related weather events. For decades engineering tools have been developed to work conveniently either with very local rain gauge networks, or with mainly C-band weather radars that have gradually been set up for space-time remote sensing of precipitation. Most of the time, the C-band weather radars continue to be calibrated by the existing rain gauge networks. Inhomogeneous distributions of rain gauging networks lead to only a partial information on the rainfall fields. In fact, the statistics of measured rainfall is strongly biased by the fractality of the measuring networks. This fractality needs to be properly taken in to account to retrieve the original properties of the rainfall fields, in spite of the radar data calibration. In this presentation, with the help of multifractal analysis, we first demonstrate that the semi-distributed hydrological models statistically reduce the rainfall fields into rainfall measured by a much scarcer network of virtual rain gauges. For this purpose, we use C-band and X-band radar data. The first has a resolution of 1 km in space and 5 min in time and is in fact a product provided by RHEA SAS after treating the Météo-France C-band radar data. The latter is measured by the radar operated at Ecole des Ponts and has a resolution of 250 m in space and 3.4 min in time. The obtained results suggest that a proper rainfall data re-normalisation is needed either when comparing gauged rainfall with the radar data, or when quantifying the impacts of space-time variability within hydrological modelling. Then, we used the semi-distributed hydrological model InfoWorks CS operated by Veolia over the Bièvre catchment (Paris region) with the same two types of rainfall data as inputs. We simulated six events and analysed the hydrographs resulted from simulations with both data types to show the impacts of initially different resolutions of rainfall fields over the same catchment, especially in respect to the small-scale variability not measured by the C-band radar data. These results encourage us not only to argue the use of higher resolution rainfall data, compare to that has been so claimed in the literature, but also to emphasise the important role of nonlinear geophysics' methods in taking reliable decisions.

Tracking rainfall impulses through progressively larger drainage basins in steep forested terrain

Treesearch

R. R. Ziemer; R. M. Rice

1990-01-01

Abstract - The precision of timing devices in modern electronic data loggers makes it possible to study the routing of water through small drainage basins having rapid responses to hydrologic impulses. Storm hyetographs were measured using digital tipping bucket rain gauges and their routing was observed at headwater piezometers located mid-slope, above a swale, and...

Changes in storm peak flows after clearcut logging

Treesearch

Jack Lewis

1997-01-01

Streamflow in a rain-dominated, 473-ha watershed bearing second-growth redwood forest was monitored at 13 locations before and after 50% of the watershed was logged, primarily by clearcutting. Three gauged subwatersheds were maintained as unlogged controls through-out the 11-year study period. The analysis included 526 observations of peak flow from 59 storm events....

Evaporation loss and evaporation/transpiration partitioning from isotope-based monitoring of Canada's provincial and national river networks

NASA Astrophysics Data System (ADS)

Gibson, J. J.; Birks, S. J.; Stadnyk, T.; Delavau, C. J.

2017-12-01

Stable isotopes of water have been measured since the 1990's as part of hydrometric monitoring programs within Canada's Water Survey of Canada gauging network and Alberta's Long-Term River Network. These datasets are being applied for hydrograph separation of streamflow sources, including rain, snow, groundwater, and surface water, as well as for estimation of watershed evaporation losses and evaporation/transpiration partitioning. Here we describe an innovative isotope mass balance approach, discuss benefits and limitations of the method, and present selected results that illustrate important regional trends in the contemporary hydrology of Canada. Overall, isotopes are shown to be useful for constraining water balance variations across regions with low monitoring density. Recommendations for future activities are identified, including regional comparisons with outputs from isotope-capable distributed hydrologic models.

Coastal Observations of Weather Features in Senegal during the AMMA SOP-3 Period

NASA Technical Reports Server (NTRS)

Jenkins, G.; Kucera, P.; Joseph, E.; Fuentes, J.; Gaye, A.; Gerlach, J.; Roux, F.; Viltard, N.; Papazzoni, M.; Protat, A.;

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

NASA Technical Reports Server (NTRS)

Kalu, A.; Emrich, C.; Ventre, J.; Wilson, W.; Acosta, R.

1998-01-01

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.

Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2013-12-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme precipitation events is also provided. Furthermore, this work is part of a broader effort to evaluate long-term multi-sensor QPEs in the perspective of developing Climate Data Records (CDRs) for precipitation.

Rain Rate from IMERG as a Predictor for Salinity Stratification in the Upper Meter of the Ocean during SPURS-2 Rain Events

NASA Astrophysics Data System (ADS)

Thompson, E. J.; Asher, W.; Drushka, K.; Schanze, J. J.; Jessup, A. T.; Clark, D.

2016-12-01

Rain can produce a lens of fresher and generally colder, less dense water at the ocean surface. These stable surface layers concentrate heat, freshwater, and momentum into a thin layer and reduce the exchange of these properties between the surface layer and deeper water, which can impact regional freshwater storage and air-sea fluxes of heat and moisture. Although in situ observations have shown that fresh lenses are common in the presence of rain, attempts to correlate the magnitude and lifetime of the surface freshening with rain rate using field data have not produced a definitive relationship. The reasons for this are most likely that in situ rain rate measurements represent the freshwater flux to the ocean surface at a single point in space and time, whereas the fresh lens is the result of the integrated rainfall over time and space, convoluted with the evolution of the fresh lens. Therefore, it is possible that integrated, upstream rainfall estimates might provide a better correlate for the presence of fresh lenses than in situ measurements at a point. This hindcast study seeks to determine the utility of NASA GPM IMERG satellite measurements of rain relative to in situ collocated rain measurements in predicting the occurrence and duration of 0-1 m freshwater stabilization of the ocean. Vertical gradients of temperature, salinity, and density between the surface and at most a few meters were measured using towed profilers and underway sampling during the 2016 SPURS-2 experiment conducted in the tropical east Pacific Ocean. Local wind speed was also measured and taken into account. These measurements were used to determine whether local or integrated upstream precipitation metrics could better predict the occurrence of rain-generated lenses of fresher water at the ocean surface and whether the strength and duration of rain events was correlated with the observed lifetime of fresh lenses.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Forest - water dynamics in a Mediterranean mountain environment.

NASA Astrophysics Data System (ADS)

Eliades, Marinos; Bruggeman, Adriana; Lange, Manfred; Camera, Corrado; Christou, Andreas

2015-04-01

In semi-arid Mediterranean mountain environments, the soil layer is very shallow or even absent due to the steep slopes. Soil moisture in these environments is limited, but still vegetation thrives. There is limited knowledge about where the vegetation extracts the water from, how much water it uses, and how it interacts with other processes in the hydrological cycle. The main objective of this study is to quantify the water balance components of a Pinus brutia forest at tree level, by measuring the tree transpiration and the redistribution of the water from trees to the soil and the bedrock fractures. The study area is located on a forested hill slope on the outside edge of Peristerona watershed in Cyprus. The site was mapped with the use of a total station and a differentially-corrected GPS, in order to create a high resolution DEM and soil depth map of the area. Soil depth was measured at a 1-m grid around the trees. Biometric measurements were taken from a total of 45 trees. Four trees were selected for monitoring. Six sap flow sensors are installed in the selected trees for measuring transpiration and reverse flows. Two trees have two sensors each to assess the variability. Four volumetric soil moisture sensors are installed around each tree at distances 1 m and 2 m away from the tree trunk. An additional fifth soil moisture sensor is installed in soil depths exceeding 20-cm depth. Four throughfall rain gauges were installed randomly around each tree to compute interception losses. Stemflow is measured by connecting an opened surface plastic tube collar at 1.6 m height around each tree trunk. The trunk surface gaps were filled with silicon glue in order to avoid any stemflow losses. The plastic collar is connected to a sealed surface rain gauge. A weather station monitors all meteorological variables on an hourly basis. Results showed a maximum sap flow volume of 77.9 L/d, from November to January. The sensors also measured a maximum negative flow of 7.9 L/d, indicating reverse flow. Soil moisture ranged between 10 to 37 % at all sensors. Soil moisture contents showed an increase over 100% after rainfall events, but decreased quickly. Also individual sensor peak values were recorded when rainfall was not occurring, indicating soil moisture increase as a result of reverse flow. Interception losses revealed values, ranging from 10% to 50 % of the total rainfall. Stem flow was recorded after intense rain fall events. To our knowledge, this is the first water use quantification study for Pinus brutia trees. The negative sap flow implies that these trees have the ability to harvest water from the air moisture and redistribute it in the ground. Perhaps part of the intercepted water is captured by the tree and thus contributing to the negative sap flow. All the variables will be monitored for two more years to quantify the role of the trees in the water balance of the area.

Miniature Convection Cooled Plug-type Heat Flux Gauges

NASA Technical Reports Server (NTRS)

Liebert, Curt H.

1994-01-01

Tests and analysis of a new miniature plug-type heat flux gauge configuration are described. This gauge can simultaneously measure heat flux on two opposed active surfaces when heat flux levels are equal to or greater than about 0.2 MW/m(sup 2). The performance of this dual active surface gauge was investigated over a wide transient and steady heat flux and temperature range. The tests were performed by radiatively heating the front surface with an argon arc lamp while the back surface was convection cooled with air. Accuracy is about +20 percent. The gauge is responsive to fast heat flux transients and is designed to withstand the high temperature (1300 K), high pressure (15 MPa), erosive and corrosive environments in modern engines. This gauge can be used to measure heat flux on the surfaces of internally cooled apparatus such as turbine blades and combustors used in jet propulsion systems and on the surfaces of hypersonic vehicles. Heat flux measurement accuracy is not compromised when design considerations call for various size gauges to be fabricated into alloys of various shapes and properties. Significant gauge temperature reductions (120 K), which can lead to potential gauge durability improvement, were obtained when the gauges were air-cooled by forced convection.

Precipitation Characteristics in Tropical Africa Using Satellite and In-Situ Observations

NASA Technical Reports Server (NTRS)

Dezfuli, Amin; Ichoku, Charles; Huffman, George; Mohr, Karen

2017-01-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region, despite their crucial role in regional and global circulation, have not been well-understood. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TMPA, and provide higher resolution data, continent-wide comparisons are made between these two products. IMERG, due to its improved temporal resolution, shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

Particle transport patterns of short-distance soil erosion by wind-driven rain, rain and wind

NASA Astrophysics Data System (ADS)

Marzen, Miriam; Iserloh, Thomas; de Lima, João L. M. P.; Ries, Johannes B.

2015-04-01

Short distance erosion of soil surface material is one of the big question marks in soil erosion studies. The exact measurement of short-distance transported soil particles, prior to the occurrence of overland flow, is a challenge to soil erosion science due to the particular requirements of the experimental setup and test procedure. To approach a quantification of amount and distance of each type of transport, we applied an especially developed multiple-gutter system installed inside the Trier Portable Wind and Rainfall Simulator (PWRS). We measured the amount and travel distance of soil particles detached and transported by raindrops (splash), wind-driven rain (splash-saltation and splash-drift) and wind (saltation). The test setup included three different erosion agents (rain/ wind-driven rain/ wind), two substrates (sandy/ loamy), three surface structures (grain roughness/ rills lengthwise/ rills transversal) and three slope angles (0°/+7°/-7°). The results present detailed transport patterns of the three erosion agents under the varying soil and surface conditions up to a distance of 1.6 m. Under the applied rain intensity and wind velocity, wind-driven rain splash generates the highest erosion. The erodibility and travel distance of the two substrates depend on the erosion agent. The total erosion is slightly higher for the slope angle -7° (downslope), but for wind-driven rain splash, the inclination is not a relevant factor. The effect of surface structures (rills) changes with traveling distance. The wind driven rain splash generates a much higher amount of erosion and a further travel distance of the particles due to the combined action of wind and rain. The wind-driven rain factor appears to be much more significant than the other factors. The study highlights the effects of different erosion agents and surface parameters on short-distance particle transport and the powerful impact of wind-driven rain on soil erosion.

Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products

NASA Astrophysics Data System (ADS)

Tang, Guoqiang; Behrangi, Ali; Long, Di; Li, Changming; Hong, Yang

2018-04-01

Rain gauge observations are commonly used to evaluate the quality of satellite precipitation products. However, the inherent difference between point-scale gauge measurements and areal satellite precipitation, i.e. a point of space in time accumulation v.s. a snapshot of time in space aggregation, has an important effect on the accuracy and precision of qualitative and quantitative evaluation results. This study aims to quantify the uncertainty caused by various combinations of spatiotemporal scales (0.1°-0.8° and 1-24 h) of gauge network designs in the densely gauged and relatively flat Ganjiang River basin, South China, in order to evaluate the state-of-the-art satellite precipitation, the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). For comparison with the dense gauge network serving as "ground truth", 500 sparse gauge networks are generated through random combinations of gauge numbers at each set of spatiotemporal scales. Results show that all sparse gauge networks persistently underestimate the performance of IMERG according to most metrics. However, the probability of detection is overestimated because hit and miss events are more likely fewer than the reference numbers derived from dense gauge networks. A nonlinear error function of spatiotemporal scales and the number of gauges in each grid pixel is developed to estimate the errors of using gauges to evaluate satellite precipitation. Coefficients of determination of the fitting are above 0.9 for most metrics. The error function can also be used to estimate the required minimum number of gauges in each grid pixel to meet a predefined error level. This study suggests that the actual quality of satellite precipitation products could be better than conventionally evaluated or expected, and hopefully enables non-subject-matter-expert researchers to have better understanding of the explicit uncertainties when using point-scale gauge observations to evaluate areal products.

Changing patterns of daily precipitation totals at the Coweeta Hydrologic Laboratory, North Carolina, USA

Treesearch

T. P. Burt; C. Ford Miniat; S. H. Laseter; W. T. Swank

2017-01-01

A pattern of increasing frequency and intensity of heavy rainfall over land has been documented for several temperate regions and is associated with climate change. This study examines the changing patterns of daily precipitation at the Coweeta Hydrologic Laboratory, North Carolina, USA, since 1937 for four rain gauges across a range of elevations. We analyse...

A study of rain effects on radar scattering from water waves

NASA Technical Reports Server (NTRS)

Bliven, Larry F.; Giovanangeli, Jean-Paul; Norcross, George

1988-01-01

Results are presented from a laboratory investigation of microwave power return due to rain-generated short waves on a wind wave surface. The wind wave tank, sensor, and data processing methods used in the study are described. The study focuses on the response of a 36-GHz radar system, orientated 30 deg from nadir and pointing upwind, to surface waves generated by various combinations of rain and wind. The results show stronger radar signal levels due to short surface waves generated by rain impacting the wind wave surface, supporting the results of Moore et al. (1979) for a 14-GHz radar.

Identification of anomalous motion of thunderstorms using daily rainfall fields

NASA Astrophysics Data System (ADS)

Moral, Anna del; Llasat, María del Carmen; Rigo, Tomeu

2017-03-01

Most of the adverse weather phenomena in Catalonia (northeast Iberian Peninsula) are caused by convective events, which can produce heavy rains, large hailstones, strong winds, lightning and/or tornadoes. These thunderstorms usually have marked paths. However, their trajectories can vary sharply at any given time, completely changing direction from the path they have previously followed. Furthermore, some thunderstorms split or merge with each other, creating new formations with different behaviour. In order to identify the potentially anomalous movements that some thunderstorms make, this paper presents a two-step methodology using a database with 8 years of daily rainfall fields data for the Catalonia region (2008-2015). First, it classifies daily rainfall fields between days with "no rain", "non-potentially convective rain" and "potentially convective rain", based on daily accumulated precipitation and extension thresholds. Second, it categorises convective structures within rainfall fields and briefly identifies their main features, distinguishing whether there were any anomalous thunderstorm movements in each case. This methodology has been applied to the 2008-2015 period, and the main climatic features of convective and non-convective days were obtained. The methodology can be exported to other regions that do not have the necessary radar-based algorithms to detect convective cells, but where there is a good rain gauge network in place.

Accuracy of tretyakov precipitation gauge: Result of wmo intercomparison

USGS Publications Warehouse

Yang, Daqing; Goodison, Barry E.; Metcalfe, John R.; Golubev, Valentin S.; Elomaa, Esko; Gunther, Thilo; Bates, Roy; Pangburn, Timothy; Hanson, Clayton L.; Emerson, Douglas G.; Copaciu, Voilete; Milkovic, Janja

1995-01-01

The Tretyakov non-recording precipitation gauge has been used historically as the official precipitation measurement instrument in the Russian (formerly the USSR) climatic and hydrological station network and in a number of other European countries. From 1986 to 1993, the accuracy and performance of this gauge were evaluated during the WMO Solid Precipitation Measurement Intercomparison at 11 stations in Canada, the USA, Russia, Germany, Finland, Romania and Croatia. The double fence intercomparison reference (DFIR) was the reference standard used at all the Intercomparison stations in the Intercomparison. The Intercomparison data collected at the different sites are compatible with respect to the catch ratio (measured/DFIR) for the same gauge, when compared using mean wind speed at the height of the gauge orifice during the observation period.The Intercomparison data for the Tretyakov gauge were compiled from measurements made at these WMO intercomparison sites. These data represent a variety of climates, terrains and exposures. The effects of environmental factors, such as wind speed, wind direction, type of precipitation and temperature, on gauge catch ratios were investigated. Wind speed was found to be the most important factor determining the gauge catch and air temperature had a secondary effect when precipitation was classified into snow, mixed and rain. The results of the analysis of gauge catch ratio versus wind speed and temperature on a daily time step are presented for various types of precipitation. Independent checks of the correction equations against the DFIR have been conducted at those Intercomparison stations and a good agreement (difference less than 10%) has been obtained. The use of such adjustment procedures should significantly improve the accuracy and homogeneity of gauge-measured precipitation data over large regions of the former USSR and central Europe.

Soil moisture controlled runoff mechanisms in a small agricultural catchment in Austria.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Szeles, Borbala; Silasari, Rasmiaditya; Hogan, Patrick; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang; Bloeschl, Guenter

2017-04-01

Understanding runoff generation mechanisms is pivotal for improved estimation of floods in small catchments. However, this requires in situ measurements with a high spatial and temporal resolution of different land surface parameters, which are rarely available distributed over the catchment scale and for a long period. The Hydrological Open Air Laboratory (HOAL) is a hydrological observatory which comprises a complex agricultural catchment, covering 66 ha. Due to the agricultural land use and low permeability of the soil part of the catchment was tile drained in the 1940s. The HOAL is equipped with an extensive soil moisture network measuring at 31 locations, 4 rain gauges and 12 stream gauges. By measuring with so many sensors in a complex catchment, the collected data enables the investigation of multiple runoff mechanisms which can be observed simultaneously in different parts of the catchment. The aim of this study is to identify and characterize different runoff mechanisms and the control soil moisture dynamics exert on them. As a first step 72 rainfall events were identified within the period 2014-2015. By analyzing event discharge response, measured at the different stream gauges, and root zone soil moisture, four different runoff mechanisms are identified. The four mechanisms exhibit contrasting soil moisture-discharge relationships. In the presented study we characterize the runoff response types by curve-fitting the discharge response to the soil moisture state. The analysis provides insights in the main runoff processes occurring in agricultural catchments. The results of this study a can be of assistance in other catchments to identify catchment hydrologic response.

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

NASA Astrophysics Data System (ADS)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Rain erosion considerations for launch vehicle insulation systems

NASA Technical Reports Server (NTRS)

Daniels, D. J.; Sieker, W. D.

1977-01-01

In recent years the Delta launch vehicle has incorporated the capability to be launched through rain. This capability was developed to eliminate a design constraint which could result in a costly launch delay. This paper presents the methodology developed to implement rain erosion protection for the insulated exterior vehicle surfaces. The effect of the interaction between insulation material rain erosion resistance, rainstorm models, surface geometry and trajectory variations is examined. It is concluded that rain erosion can significantly impact the performance of launch vehicle insulation systems and should be considered in their design.

Benefits and limitations of using the weather radar for the definition of rainfall thresholds for debris flows. Case study from Catalonia (Spain).

NASA Astrophysics Data System (ADS)

Abancó, C.; Hürlimann, M.; Sempere, D.; Berenguer, M.

2012-04-01

Torrential processes such as debris flows or hyperconcentrated flows are fast movements formed by a mix of water and different amounts of unsorted solid material. They occur in steep torrents and suppose a high risk for the human settlements. Rainfall is the most common triggering factor for debris flows. The rainfall threshold defines the rainfall conditions that, when reached or exceeded, are likely to provoke one or more events. Many different types of empirical rainfall thresholds for landslide triggering have been defined. Direct measurements of rainfall data are normally not available from a point next to or in the surroundings of the initiation area of the landslide. For this reason, most of the thresholds published for debris flows have been established by data measured at the nearest rain gauges (often located several km far from the landslide). Only in very few cases, the rainfall data to analyse the triggering conditions of the debris flows have been obtained by weather (Doppler) radar. Radar devices present certain limitations in mountainous regions due to undesired reboots, but their main advantage is that radar data can be obtained for any point of the territory. The objective of this work was to test the use of the weather radar data for the definition of rainfall thresholds for debris-flow triggering. Thus, rainfall data obtained from 3 to 5 rain gauges and from radar were compared for a dataset of events occurred in Catalonia (Spain). The goal was to determine in which cases the description of the rainfall episode (in particular the maximum intensity) had been more accurate. The analysed dataset consists of: 1) three events occurred in the Rebaixader debris-flow monitoring station (Axial Pyrenees) including two hyperconcentrated flows and one debris flow; 2) one debris-flow event occurred in the Port Ainé ski resort (Axial Pyrenees); 3) one debris-flow event in Montserrat (Mediterranean Coastal range). The comparison of the hyetographs from the different devices showed that the reliability of the radar is higher for short, high intensity storms more than for long lasting, medium intensity ones. Additionally, the best fit corresponds to the situations where the storm nucleus is located near the source area of the debris flow. The results of the comparison between different rain gauges show similar trends. The ones located in the same valley as the debris flow usually show good results, but if there are orographic elements in-between the debris-flow torrent and the rain gauge or the distance is large, the results can imply a great error in the definition of rainfall intensity. Therefore, we can state that the reliability of the use of the weather radar to define rainfall thresholds is strongly depending on the type of the storm and the distance between the source area and the nucleus of the storm.

Ground Validation Assessments of GPM Core Observatory Science Requirements

NASA Astrophysics Data System (ADS)

Petersen, Walt; Huffman, George; Kidd, Chris; Skofronick-Jackson, Gail

2017-04-01

NASA Global Precipitation Measurement (GPM) Mission science requirements define specific measurement error standards for retrieved precipitation parameters such as rain rate, raindrop size distribution, and falling snow detection on instantaneous temporal scales and spatial resolutions ranging from effective instrument fields of view [FOV], to grid scales of 50 km x 50 km. Quantitative evaluation of these requirements intrinsically relies on GPM precipitation retrieval algorithm performance in myriad precipitation regimes (and hence, assumptions related to physics) and on the quality of ground-validation (GV) data being used to assess the satellite products. We will review GPM GV products, their quality, and their application to assessing GPM science requirements, interleaving measurement and precipitation physical considerations applicable to the approaches used. Core GV data products used to assess GPM satellite products include 1) two minute and 30-minute rain gauge bias-adjusted radar rain rate products and precipitation types (rain/snow) adapted/modified from the NOAA/OU multi-radar multi-sensor (MRMS) product over the continental U.S.; 2) Polarimetric radar estimates of rain rate over the ocean collected using the K-Pol radar at Kwajalein Atoll in the Marshall Islands and the Middleton Island WSR-88D radar located in the Gulf of Alaska; and 3) Multi-regime, field campaign and site-specific disdrometer-measured rain/snow size distribution (DSD), phase and fallspeed information used to derive polarimetric radar-based DSD retrievals and snow water equivalent rates (SWER) for comparison to coincident GPM-estimated DSD and precipitation rates/types, respectively. Within the limits of GV-product uncertainty we demonstrate that the GPM Core satellite meets its basic mission science requirements for a variety of precipitation regimes. For the liquid phase, we find that GPM radar-based products are particularly successful in meeting bias and random error requirements associated with retrievals of rain rate and required +/- 0.5 millimeter error bounds for mass-weighted mean drop diameter. Version-04 (V4) GMI GPROF radiometer-based rain rate products exhibit reasonable agreement with GV, but do not completely meet mission science requirements over the continental U.S. for lighter rain rates (e.g., 1 mm/hr) due to excessive random error ( 75%). Importantly, substantial corrections were made to the V4 GPROF algorithm and preliminary analysis of Version 5 (V5) rain products indicates more robust performance relative to GV. For the frozen phase and a modest GPM requirement to "demonstrate detection of snowfall", DPR products do successfully identify snowfall within the sensitivity and beam sampling limits of the DPR instrument ( 12 dBZ lower limit; lowest clutter-free bins). Similarly, the GPROF algorithm successfully "detects" falling snow and delineates it from liquid precipitation. However, the GV approach to computing falling-snow "detection" statistics is intrinsically tied to GPROF Bayesian algorithm-based thresholds of precipitation "detection" and model analysis temperature, and is not sufficiently tied to SWER. Hence we will also discuss ongoing work to establish the lower threshold SWER for "detection" using combined GV radar, gauge and disdrometer-based case studies.

Rainfall measurement from the opportunistic use of an Earth-space link in the Ku band

NASA Astrophysics Data System (ADS)

Barthès, L.; Mallet, C.

2013-08-01

The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth-satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content) or satellite transmission parameters (variations in emitted power, satellite pointing). In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

Rain in the U.S. Midwest

NASA Technical Reports Server (NTRS)

2007-01-01

The powerful storms that moved across the U.S. Midwest during the first week of May 2007 brought wind, hail, tornadoes, and drenching rain. This image shows rainfall totals over parts of Oklahoma, Kansas, and Nebraska between May 1 and May 8, based in part on measurements made by the Tropical Rainfall Measuring Mission (TRMM) satellite. More than 400 millimeters (15.7 inches) of rain fell over some regions, corresponding with locations where the National Weather Service reported severe weather. A wide swath of red and orange (between 240 and 400 millimeters of rain) arcs in a clockwise direction from western Oklahoma, through central Kansas, and into southeastern Nebraska. The reddish-orange bull's-eye over southeastern Louisiana is evidence of the torrential rains that pounded visitors to the annual New Orleans Jazz Festival. South-central Texas' Edward Plateau was soaked with more than 240 millimeters of rain during the period, as well. From May 4 to May 8, the National Weather Service received approximately 683 reports of severe weather, 140 of which were reports of tornadoes, including the massive F5 tornado that devastated the city of Greensburg, Kansas. Beyond the damaging winds and tornadoes, the torrential rain triggered extensive flooding throughout the Central Plains. On the evening of May 7, flood warnings were in effect from South Dakota to southern Texas, and by May 8, the Hydrologic Information Center reported moderate to major flooding at 53 stream gauge sites in South Dakota, Iowa, Kansas, Nebraska, Missouri, and Arkansas. The floods could be as severe as the 1993 flood, one of the costliest floods in U.S. history, reported the Associated Press.

A Possible Explanation for the Z -R Parameter Inconsistency when Comparing Stratiform and Convective Rainfall

NASA Astrophysics Data System (ADS)

Lane, John; Kasparis, Takis; Michaelides, Silas

2016-04-01

The well-known Z -R power law Z = ARb uses two parameters, A and b, in order to relate rainfall rate R to measured weather radar reflectivity Z. A common method used by researchers is to compute Z and R from disdrometer data and then extract the A-bparameter pair from a log-linear line fit to a scatter plot of Z -R pairs. Even though it may seem far more truthful to extract the parameter pair from a fit of radar ZR versus gauge rainfall rate RG, the extreme difference in spatial and temporal sampling volumes between radar and rain gauge creates a slew of problems that can generally only be solved by using rain gauge arrays and long sampling averages. Disdrometer derived A - b parameters are easily obtained and can provide information for the study of stratiform versus convective rainfall. However, an inconsistency appears when comparing averaged A - b pairs from various researchers. Values of b range from 1.26 to 1.51 for both stratiform and convective events. Paradoxically the values of Afall into three groups: 150 to 200 for convective; 200 to 400 for stratiform; and 400 to 500 again for convective. This apparent inconsistency can be explained by computing the A - b pair using the gamma DSD coupled with a modified drop terminal velocity model, v(D) = αDβ - w, where w is a somewhat artificial constant vertical velocity of the air above the disdrometer. This model predicts three regions of A, corresponding to w < 0, w = 0, and w > 0, which approximately matches observed data.

Occult chemical deposition to a Maritime forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vong, R.J.; Kowalski, A.S.

1996-12-31

Studies of chemical fluxes from the atmosphere to vegetated surfaces have suggested that, along with conventional wet and dry processes, an additional chemical input occurs when wind-blown cloud droplets are directly intercepted by vegetation. This cloud water deposition process has been sometimes termed {open_quote}occult deposition{close_quote} because the water fluxes cannot ordinarily be observed using rain gauges. Such occult deposition of cloud water has rarely been measured directly, in part because of the complexity of the governing turbulent transfer process. However, reviews by the National Acidic Precipitation Assessment Program (NAPAP SoS/T-2,6) have suggested that the chemical flux to be forest declinemore » in the eastern USA. This paper presents direct field measurements occult chemical fluxes to a silver fir forest located in complex terrain on the Olympic Peninsula near the coast of Washington State, USA.« less

Rainfall Climatology over Asir Region, Saudi Arabia

NASA Astrophysics Data System (ADS)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

High-resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset

Treesearch

Christopher Daly; Melissa E. Slater; Joshua A. Roberti; Stephanie H. Laseter; Lloyd W. Swift

2017-01-01

A 69-station, densely spaced rain gauge network was maintained over the period 1951–1958 in the Coweeta Hydrologic Laboratory, located in the southern Appalachians in western North Carolina, USA. This unique dataset was used to develop the first digital seasonal and annual precipitation maps for the Coweeta basin, using elevation regression functions and...

Continuous, Wireless Monitoring of Sediment Flux within Streams on Military Installations

DTIC Science & Technology

2013-10-17

2.2.1.3.2 Voltage Regulation ...................................................................................... 14 2.2.1.3.3 Mote and Data...components are: A. PCB board; B. Suspended sediment sensor; C. MDA300; D. Crossbow mote (not in the picture); E. Rain gauge; F. Two solenoid valves...wireless mote (MICA2, Crossbow Technology), a rechargeable battery, and a mounting structure. The exact configuration of the wireless sensor node

Design and Modification of an Installation Method to Stabilize Small Trapezoidal Flumes in Drainage Ditches

Treesearch

Charles A. Harrison; Susan O’Ney

2002-01-01

We developed procedures for installing prefabricated trapezoidal flumes in deep (10 to 12 feet) drainage ditches to monitor hydrologic functions and provide gauge locations for sampling discharge. Flows from the instrumented basins were generally low, but the ditches were occasionally subject to high flows caused by rain events of 2 to 3 inches or more. These high flow...

Subsurface material identification and sensor selection

NASA Astrophysics Data System (ADS)

T, H.; Reghunadh, R.; Ramesh, M. V.

2017-12-01

In India, most of the landslides occur during monsoon season and causes huge loss of life and property. Design of an early warning system for highly landslide prone area will reduce losses to a great extent. The in-situ monitoring systems needs deployment of several sensors inside a borehole for monitoring a particular slope. Amrita Center for Wireless Networks and Applications (AmritaWNA), Amrita University has designed, developed and deployed a Wireless Sensor Network (WSN) for real time landslide monitoring using geotechnical instruments and sensors like rain gauge, moisture sensor, piezometer, strain gauge, tilt meter and geophone inside a Deep Earth Probe (DEP) at different locations. These sensors provide point measurements of the subsurface at a higher accuracy. Every landslide prone terrain is unique with respect to its geology, hydrological conditions, meteorological conditions, velocity of movement etc. The decision of installing different geotechnical instruments in a landslide prone terrain is a crucial step to be considered. Rain gauge, moisture sensor, and piezometer are usually used in clay rich areas to sense the moisture and pore pressure values. Geophone and Crack meter are instruments used in rocky areas to monitor cracks and vibrations associated with a movement. Inclinometer and Strain gauge are usually placed inside a casing and can be used in both rocky and soil areas. In order to place geotechnical instruments and sensors at appropriate places Electrical Resistivity Tomography (ERT) method can be used. Variation in electrical resistivity values indicate the changes in composition, layer thickness, or contaminant levels. The derived true resistivity image can be used for identifying the type of materials present in the subsurface at different depths. We have used this method for identifying the type of materials present in our site at Chandmari (Sikkim). Fig 1 shows the typical resistivity values of a particular area in Chandmari site. The results shows that the area has more clay so the placement of moisture sensor and piezometer are required instead of placing geophone, crack meter etc.

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach.

PubMed

Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

2018-08-01

Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and North Atlantic Oscillation (NAO), indeces. The results revealed that all climatic features except NAO influenced precipitation in Iran during the 1960-2010 period. Copyright © 2018 Elsevier Inc. All rights reserved.

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

NASA Astrophysics Data System (ADS)

El Kenawy, Ahmed M.; Lopez-Moreno, Juan I.; McCabe, Matthew F.; Vicente-Serrano, Sergio M.

2015-10-01

The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5 mm.day- 1, RMSE of 6.4 mm.day- 1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50 mm.day- 1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5-25 mm.day- 1), but show noticeably less skill in producing both light (< 1 mm.day- 1) and heavy rainfall thresholds (more than 50 mm.day- 1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an informative addition to the spatial and temporal coverage of rain gauges in the domain, offering insights into characteristics of average precipitation and their spatial patterns. However, the satellite-based precipitation data should be used cautiously for monitoring extreme precipitation events, particularly over complex terrain. An improvement in precipitation algorithms is still needed to more accurately reproduce high precipitation events in areas of heterogeneous topography over this region.

Return period curves for extreme 5-min rainfall amounts at the Barcelona urban network

NASA Astrophysics Data System (ADS)

Lana, X.; Casas-Castillo, M. C.; Serra, C.; Rodríguez-Solà, R.; Redaño, A.; Burgueño, A.; Martínez, M. D.

2018-03-01

Heavy rainfall episodes are relatively common in the conurbation of Barcelona and neighbouring cities (NE Spain), usually due to storms generated by convective phenomena in summer and eastern and south-eastern advections in autumn. Prevention of local flood episodes and right design of urban drainage have to take into account the rainfall intensity spread instead of a simple evaluation of daily rainfall amounts. The database comes from 5-min rain amounts recorded by tipping buckets in the Barcelona urban network along the years 1994-2009. From these data, extreme 5-min rain amounts are selected applying the peaks-over-threshold method for thresholds derived from both 95% percentile and the mean excess plot. The return period curves are derived from their statistical distribution for every gauge, describing with detail expected extreme 5-min rain amounts across the urban network. These curves are compared with those derived from annual extreme time series. In this way, areas in Barcelona submitted to different levels of flood risk from the point of view of rainfall intensity are detected. Additionally, global time trends on extreme 5-min rain amounts are quantified for the whole network and found as not statistically significant.

Analysis of 35 GHz Cloud Radar polarimetric variables to identify stratiform and convective precipitation.

NASA Astrophysics Data System (ADS)

Fontaine, Emmanuel; Illingworth, Anthony, J.; Stein, Thorwald

2017-04-01

This study is performed using vertical profiles of radar measurements at 35GHz, for the period going from 29th of February to 1rst October 2016, at the Chilbolton observatory in United Kingdom. During this period, more than 40 days with precipitation events are investigated. The investigation uses the synergy of radar reflectivity factors, vertical velocity, Doppler spectrum width, and linear depolarization ratio (LDR) to differentiate between stratiform and convective rain events. The depth of the layer with Doppler spectrum width values greater than 0.5 m s-1 is shown to be a suitable proxy to distinguish between convective and stratiform events. Using LDR to detect the radar bright band, bright band characteristics such as depth of the layer and maximum LDR are shown to vary with the amount of turbulence aloft. Profiles of radar measurements are also compared to rain gauge measurements to study the contribution of convective and stratiform rainfall to total rain duration and amount. To conclude, this study points out differences between convective and stratiform rains and quantifies their contributions over a precipitation event, highlighting that convective and stratiform rainfall should be considered as a continuum rather than a dichotomy.

Assessment of spill flow emissions on the basis of measured precipitation and waste water data

NASA Astrophysics Data System (ADS)

Hochedlinger, Martin; Gruber, Günter; Kainz, Harald

2005-09-01

Combined sewer overflows (CSOs) are substantial contributors to the total emissions into surface water bodies. The emitted pollution results from dry-weather waste water loads, surface runoff pollution and from the remobilisation of sewer deposits and sewer slime during storm events. One possibility to estimate overflow loads is a calculation with load quantification models. Input data for these models are pollution concentrations, e.g. Total Chemical Oxygen Demand (COD tot), Total Suspended Solids (TSS) or Soluble Chemical Oxygen Demand (COD sol), rainfall series and flow measurements for model calibration and validation. It is important for the result of overflow loads to model with reliable input data, otherwise this inevitably leads to bad results. In this paper the correction of precipitation measurements and the sewer online-measurements are presented to satisfy the load quantification model requirements already described. The main focus is on tipping bucket gauge measurements and their corrections. The results evidence the importance of their corrections due the effects on load quantification modelling and show the difference between corrected and not corrected data of storm events with high rain intensities.

9-year distributions of rain intensities measured in Prague and their utilization in telecommunications

NASA Astrophysics Data System (ADS)

Kvicera, V.; Grabner, M.

2012-04-01

Experimental research in the Department of Frequency Engineering of the Czech Metrology Institute (CMI) in Prague, the Czech Republic, is focused on stability of received signals on terrestrial radio and optical communication paths. Hydrometeors (rain, snow, fog, hails) can cause serious attenuation of electromagnetic waves in the frequency bands above 10 GHz and the availability performances of terrestrial radio communication systems are seriously affected by heavy hydrometeors events. The rain intensity data is usually used for the calculations of attenuation due to rain on terrestrial radio links in accordance with either the relevant ITU-R Recommendation or other methods. Therefore, our experimental research is also focused on our own meteorological measurements in the vicinity of experimental radio and optical paths. The heated tipping-bucket rain gauge with the collector area of 500 cm2 and the rain amount per tip of 0.1 mm is used at CMI for the measurements of intensities of hydrometeors. The time of tips is recorded with uncertainty of 1 second. Hydrometeors intensity data obtained from January 2003 to December 2011 (9 years of observation) was statistically processed over the individual years. All the recorded individual hydrometeor events were compared with the concurrent meteorological conditions and were carefully categorized according to the types of individual hydrometeors, i.e. rain, rain with snow, rain with hails, snow, fog, fog with rain, fog with snow, and fog with rain and snow. The obtained cumulative distributions (CDs) of intensities of individual hydrometeors over 9 years of observation will be presented and compared with the CD of intensities of all hydrometeors together. The rain amounts were examined too. The obtained rain amounts for individual years and the average rain amounts for individual months over the 9-year period will be given. The obtained CD of average 1-minute rain intensities for the average year over the 9-year period of observation was used for the calculations of CDs of attenuation due to rain on terrestrial radio paths in accordance with the relevant recommendation of the ITU-R. The examples of the calculated CDs of attenuation due to rain will be presented for radio communication links with different path lengths working in different frequency bands. The obtained CDs can be used for the assessment of availability performances of terrestrial radio communication links in the climatic region where the rain intensities were measured. The examples will be given. Ministry of Education, Youth and Sports of the Czech Republic under the Project No. OC09076 supported the described work.

On the wind-induced undercatch in rainfall measurement using CFD-based simulations

NASA Astrophysics Data System (ADS)

Colli, Matteo; Lanza, Luca

2016-04-01

The reliability of liquid atmospheric precipitation measurements is a basic requirement since rainfall data represent the fundamental input variables of many scientific applications (hydrologic models, weather forecasting data assimilation, climate change studies, calibration of weather radar, etc.). The scientific community and the National Meteorological Services worldwide are facing the issue of improving the accuracy of precipitation measurements, with an increased focus on retrieving the information at a high temporal resolution. The rainfall intensity is indeed fundamental information for the precise quantification of the markedly time-varying behavior of precipitation events. Environmental conditions have a relevant impact on the rain collection/sensing efficiency. Among other effects, wind is recognized as a major source of underestimation since it reduces the collection efficiency of the catching-type gauges (Nespor and Sevruk, 1999), the most common type of instruments used worldwide in the national observation networks. The collection efficiency is usually obtained by comparing the rainfall amounts measured by the gauge with the reference, which was defined by EN-13798 standard (CEN, 2002) as a gauge placed below the ground level inside a pit. A lot of scatter can be observed for a given wind speed, which is mainly caused by comparability issues among the tested gauges. An additional source of uncertainty is the drops size distribution (DSD) of the rain, which varies on an event-by-event basis. The goal of this study is to understand the role of the physical characteristics of precipitation particles on the wind-induced rainfall underestimation observed for catching-type gauges. To address this issue, a detailed analysis of the flow field in the vicinity of the gauge is conducted using time-averaged computational fluid dynamics (CFD) simulations (Colli et al., 2015). Using a Lagrangian model, which accounts for the hydrodynamic behavior of liquid particles in the atmosphere, droplets trajectories are calculated to obtain the collection efficiency associated with different drop size distribution and varying the wind speed. The main benefit of investigating this error by means of CFD simulations is the possibility to single out the prevailing environmental factors from the instrumental performance of the gauges under analysis. The preliminary analysis shows the variations in the catch efficiency due to the horizontal wind speeds and the DSD. Overall, this study contributes to a better understanding of the environmental sources of uncertainty in rainfall measurements. References: Colli, M., R. Rasmussen, J. M. Theriault, L. G. Lanza, C. B. Baker & J. Kochendorfer (2015) An Improved Trajectory Model to Evaluate the Collection Performance of Snow Gauges. Journal of Applied Meteorology and Climatology, 54, 1826-1836 Nespor, V. and Sevruk, B. (1999). Estimation of wind-induced error of rainfall gauge measurements using a numerical simulation. J. Atmos. Ocean. Tech, 16(4), 450-464. CEN (2002). EN 13798:2002 Hydrometry - Specification for a reference raingauge pit. European Committee for Standardization.

Assessment of Precipitation Trends over Europe by Comparing ERA-20C with a New Homogenized Observational GPCC Dataset

NASA Astrophysics Data System (ADS)

Rustemeier, E.; Ziese, M.; Meyer-Christoffer, A.; Finger, P.; Schneider, U.; Becker, A.

2015-12-01

Reliable data is essential for robust climate analysis. The ERA-20C reanalysis was developed during the projects ERA-CLIM and ERA-CLIM2. These projects focus on multi-decadal reanalyses of the global climate system. To ensure data quality and provide end users with information about uncertainties in these products, the 4th work package of ERA_CLIM2 deals with the quality assessment of the products including quality control and error estimation.In doing so, the monthly totals of the ERA-20C reanalysis are compared to two corresponding Global Precipitation Climatology Centre (GPCC) products; the Full Data Reanalysis Version 7 and the new HOMogenized PRecipitation Analysis of European in-situ data (HOMPRA Europe).ERA-20C reanalysis was produced based on ECMWFs IFS version Cy38r1 with a spatial resolution of about 125 km. It covers the time period 1900 to 2010. Only surface observations are assimilated namely marine winds and pressure. This allows the comparison with independent, not assimilated data. The GPCC Full Data Reanalysis Version 7 comprises monthly land-surface precipitation from approximately 75,000 rain-gauges covering the time period 1901-2013. For this paper, the version with 1° resolution is utilized. For trend analysis, a monthly European subset of the ERA-20C reanalysis is investigated spanning the years 1951-2005. The European subset will be compared to a new homogenized GPCC data set HOMPRA Europe. The latter is based on a collective of 5373 homogenized monthly rain gauge time series, carefully chosen from the GPCC archive of precipitation data.For the spatial and temporal evaluation of ERA-20C, global scores on monthly, seasonal and annual time scales are calculated. These include contingency table scores, correlation, along with spatial scores such as the fractional skill score. Unsurprisingly regions with strongest deviations are those of data scarcity, mountainous regions with their luv and lee effects, and monsoon regions. They all exhibit strong biases throughout their series, and severe shifts in the means. The new HOMPRA Europe data set is useful in particular for trend analysis. Therefore it is compared to a monthly European subset of the ERA-20C reanalysis for the same period, i.e. the years 1951-2005, to study the ERA-20C capability in reproducing observed trends across Europe.

The operational platform XTREM for rainfall measurement and monitoring

NASA Astrophysics Data System (ADS)

Mioche, G.; Van Baëlen, J.; Buisson, E.

2012-04-01

Nowadays in the risk management field, new tools to anticipate extremes meteorological events are in development. Over the last 20 years, the occurrence of such types of events has increased and today they represent a serious threat for human activities and health. In particular, local and intense precipitation events cause significant damages on private and public materials and properties and even loss of lives, especially in vulnerable areas such as urban or mountain environments. The XTREM platform (X-band radar and operational plaTform for high REsolution precipitation Monitoring and forecasting) is an operating system designed to monitor, quantify and even forecast rain events with high time and space resolutions. This is also a useful tool for decision support in the environmental risk management domain. The main instrument of XTREM is an X band radar which is able to measure precipitations with high spatial and temporal resolutions (100 m, 1 minute) on local areas, in real time and continuously, in addition to the existing meteorological radars network. This radar is particularly well adapted in urban areas or in complex orography regions (such as mountains). In this communication, the data processing of X band radar data will be first described, then the XTREM platform products will be presented. Concerning the data processing, the first step is to estimate the attenuation due to the hydrometeors. Then the conversion of reflectivity in rain rate R is made with specific Z-R relationships to provide accurate estimates. Thanks to a system of alerts with customizable thresholds, the real time mode will generates useful information to users to anticipate risks linked to strong rainfall, such as an estimation of the rain height and cumulative rain on defined areas. XTREM is also able to integrate a rain gauge network. The user gets the opportunity to compare in real time radar retrievals with rain gauge data, which allows assessing radar retrievals accuracy. XTREM includes also nowcasting/forecasting products, derived from various methods (extrapolation technique, blending with numerical modelling). Furthermore, an analysis mode is available to study in details a specific event. In this mode, more scientific tools are available (various attenuation calculation methods or various Z-R relationships) in order to carry detailed investigation on particular events observed. Finally, the case study of a local and strong precipitation event which took place in Clermont-Ferrand will be presented, showing the products and impact provided by XTREM.

Sources of sulphur in rain collected below a wheat canopy.

PubMed

Raybould, C C; Unsworth, M H; Gregory, P J

1977-05-12

Vegetation plays an important role in the cycle of sulphur between the atmosphere and the soil. We have measured the quantity of sulphur in rain collected below a maturing wheat canopy. This sulphur has three sources: first, the atmosphere, from which falling rain gains SO2 and sulphate; second, leaf surfaces, from which rain washes sulphur which was previously deposited by turbulent transfer ('dry deposition'), and third, leaf tissue, from which rain leaches sulphur. We have now deduced from field and laboratory measurements that leaching supplied nearly 90% of the sulphur gained by rain as it fell through the wheat canopy. Only a small fraction of sulphur which had been dry-deposited on the surface of leaves could be washed off.

Dengue and Chikungunya Vector Control Pocket Guide

DTIC Science & Technology

2014-05-01

mosquito eggs, larvae, or pupae. Examples of such items are tarps, discarded bottles, flower pot saucers, and rain gauges. In areas where there...coconut husks, (4) tires, (5) barrels, (6) water storage tanks, (7) bromeliads and axils of banana trees, (8) obstructed roof gutters, (9) plant pot...regularly Store under roof Fill with sand Throw Away/ Recycle Buckets X X X Flower Pot Saucers X X Roof Gutters X Discarded

Regional-scale analysis of extreme precipitation from short and fragmented records

NASA Astrophysics Data System (ADS)

Libertino, Andrea; Allamano, Paola; Laio, Francesco; Claps, Pierluigi

2018-02-01

Rain gauge is the oldest and most accurate instrument for rainfall measurement, able to provide long series of reliable data. However, rain gauge records are often plagued by gaps, spatio-temporal discontinuities and inhomogeneities that could affect their suitability for a statistical assessment of the characteristics of extreme rainfall. Furthermore, the need to discard the shorter series for obtaining robust estimates leads to ignore a significant amount of information which can be essential, especially when large return periods estimates are sought. This work describes a robust statistical framework for dealing with uneven and fragmented rainfall records on a regional spatial domain. The proposed technique, named "patched kriging" allows one to exploit all the information available from the recorded series, independently of their length, to provide extreme rainfall estimates in ungauged areas. The methodology involves the sequential application of the ordinary kriging equations, producing a homogeneous dataset of synthetic series with uniform lengths. In this way, the errors inherent to any regional statistical estimation can be easily represented in the spatial domain and, possibly, corrected. Furthermore, the homogeneity of the obtained series, provides robustness toward local artefacts during the parameter-estimation phase. The application to a case study in the north-western Italy demonstrates the potential of the methodology and provides a significant base for discussing its advantages over previous techniques.

Understanding processes that generate flash floods in the arid Judean Desert to the Dead Sea - a measurement network

NASA Astrophysics Data System (ADS)

Hennig, Hanna; Rödiger, Tino; Laronne, Jonathan B.; Geyer, Stefan; Merz, Ralf

2016-04-01

Flash floods in (semi-) arid regions are fascinating in their suddenness and can be harmful for humans, infrastructure, industry and tourism. Generated within minutes, an early warning system is essential. A hydrological model is required to quantify flash floods. Current models to predict flash floods are often based on simplified concepts and/or on concepts which were developed for humid regions. To more closely relate such models to local conditions, processes within catchments where flash floods occur require consideration. In this study we present a monitoring approach to decipher different flash flood generating processes in the ephemeral Wadi Arugot on the western side of the Dead Sea. To understand rainfall input a dense rain gauge network was installed. Locations of rain gauges were chosen based on land use, slope and soil cover. The spatiotemporal variation of rain intensity will also be available from radar backscatter. Level pressure sensors located at the outlet of major tributaries have been deployed to analyze in which part of the catchment water is generated. To identify the importance of soil moisture preconditions, two cosmic ray sensors have been deployed. At the outlet of the Arugot water is sampled and level is monitored. To more accurately determine water discharge, water velocity is measured using portable radar velocimetry. A first analysis of flash flood processes will be presented following the FLEX-Topo concept .(Savenije, 2010), where each landscape type is represented using an individual hydrological model according to the processes within the three hydrological response units: plateau, desert and outlet. References: Savenije, H. H. G.: HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)", Hydrol. Earth Syst. Sci., 14, 2681-2692, doi:10.5194/hess-14-2681-2010, 2010.

On the nature of rainfall in dry climate: Space-time patterns of convective rain cells over the Dead Sea region and their relations with synoptic state and flash flood generation

NASA Astrophysics Data System (ADS)

Belachsen, Idit; Marra, Francesco; Peleg, Nadav; Morin, Efrat

2017-04-01

Space-time patterns of rainfall are important climatic characteristics that influence runoff generation and flash flood magnitude. Their derivation requires high-resolution measurements to adequately represent the rainfall distribution, and is best provided by remote sensing tools. This need is further emphasized in dry climate regions, where rainfall is scarce and, often, local and highly variable. Our research is focused on understanding the nature of rainfall events in the dry Dead Sea region (Eastern Mediterranean) by identifying and characterizing the spatial structure and the dynamics of convective storm cores (known as rain cells). To do so, we take advantage of 25 years of corrected and gauge-adjusted weather radar data. A statistical analysis of convective rain-cells spatial and temporal characteristics was performed with respect to synoptic pattern, geographical location, and flash flood generation. Rain cells were extracted from radar data using a cell segmentation method and a tracking algorithm and were divided into rain events. A total of 10,500 rain cells, 2650 cell tracks and 424 rain events were elicited. Rain cell properties, such as mean areal and maximal rain intensity, area, life span, direction and speed, were derived. Rain events were clustered, according to several ERA-Interim atmospheric parameters, and associated with three main synoptic patterns: Cyprus Low, Low to the East of the study region and Active Red Sea Trough. The first two originate from the Mediterranean Sea, while the third is an extension of the African monsoon. On average, the convective rain cells in the region are 90 km2 in size, moving from West to East in 13 ms-1 and living 18 minutes. Several significant differences between rain cells of the various synoptic types were observed. In particular, Active Red Sea Trough rain cells are characterized by higher rain intensities and lower speeds, suggesting a higher flooding potential for small catchments. The north-south negative gradient of mean annual rainfall in the study region was found to be negatively correlated with rain cells intensity and positively correlated with rain cells area. Additional analysis was done for convective rain cells over two nearby catchments located in the central part of the study region, by ascribing some of the rain events to observed flash-flood events. It was found that rain events associated with flash-floods have higher maximal rain cell intensity and lower minimal cell speed than rain events that did not lead to a flash-flood in the watersheds. This information contributes to our understanding of rain patterns over the dry area of the Dead Sea and their connection to flash-floods. The statistical distributions of rain cells properties can be used for high space-time resolution stochastic simulations of rain storms that can serve as an input to hydrological models.

Tropical Rainfall Measuring Mission

NASA Technical Reports Server (NTRS)

1999-01-01

Tropical rainfall affects the lives and economics of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. Tropical forests and the underlying soils are major sources of many of the atmosphere's trace constituents. Together, the forests and the atmosphere act as a water-energy regulating system. Most of the rainfall is returned to the atmosphere through evaporation and transpiration, and the atmospheric trace constituents take part in the recycling process. Hence, the hydrological cycle provides a direct link between tropical rainfall and the global cycles of carbon, nitrogen, and sulfur, all important trace materials for the Earth's system. Because rainfall is such an important component in the interactions between the ocean, atmosphere, land, and the biosphere, accurate measurements of rainfall are crucial to understanding the workings of the Earth-atmosphere system. The large spatial and temporal variability of rainfall systems, however, poses a major challenge to estimating global rainfall. So far, there has been a lack of rain gauge networks, especially over the oceans, which points to satellite measurement as the only means by which global observation of rainfall can be made. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain systems.The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. Goddard Space Flight Center's involvement includes the observatory, four instruments, integration and testing of the observatory, data processing and distribution, and satellite operations. TRMM has a design lifetime of three years. Data generated from TRMM and archived at the GDAAC are useful not only for hydrologists, atmospheric scientists, and climatologists, but also for the health community studying infectious diseases, the ocean research community, and the agricultural community.

Ice detector

NASA Technical Reports Server (NTRS)

Weinstein, Leonard M. (Inventor)

1988-01-01

An ice detector is provided for the determination of the thickness of ice on the outer surface on an object (e.g., aircraft) independently of temperature or the composition of the ice. First capacitive gauge, second capacitive gauge, and temperature gauge are embedded in embedding material located within a hollowed out portion of the outer surface. This embedding material is flush with the outer surface to prevent undesirable drag. The first capacitive gauge, second capacitive gauge, and the temperature gauge are respectively connected to first capacitive measuring circuit, second capacitive measuring circuit, and temperature measuring circuit. The geometry of the first and second capacitive gauges is such that the ratio of the voltage outputs of the first and second capacitance measuring circuits is proportional to the thickness of ice, regardless of ice temperature or composition. This ratio is determined by offset and dividing circuit.

Utility of remote sensing-based surface energy balance models to track water stress in rain-fed switchgrass under dry and wet conditions

USDA-ARS?s Scientific Manuscript database

The ability of remote sensing-based surface energy balance (SEB) models to track water stress in rain-fed switchgrass has not been explored yet. In this paper, the theoretical framework of crop water stress index (CWSI) was utilized to estimate CWSI in rain-fed switchgrass (Panicum virgatum L.) usin...

Variation of rain intensity and drop size distribution with General Weather Patterns (GWL)

NASA Astrophysics Data System (ADS)

Ghada, Wael; Buras, Allan; Lüpke, Marvin; Menzel, Annette

2017-04-01

Short-duration rainfall extremes may cause flash floods in certain catchments (e.g. cities or fast responding watersheds) and pose a great risk to affected communities. In order to predict their occurrence under future climate change scenarios, their link to atmospheric circulation patterns needs to be well understood. We used a comprehensive data set of meteorological data (temperature, rain gauge precipitation) and precipitation spectra measured by a disdrometer (OTT PARSIVEL) between October 2008 and June 2010 at Freising, southern Germany. For the 21 months of the study period, we integrated the disdrometer spectra over intervals of 10 minutes to correspond to the temporal resolution of the weather station data and discarded measurements with air temperatures below 0°C. Daily General Weather Patterns ("Großwetterlagen", GWL) were downloaded from the website of the German Meteorological Service. Out of the 29 GWL, 14 were included in the analysis for which we had at least 12 rain events during our study period. For the definition of a rain event, we tested different lengths of minimum inter-event times and chose 30 min as a good compromise between number and length of resulting events; rain events started when more than 0.001 mm/h (sensitivity of the disdrometer) were recorded. The length of the rain events ranged between 10 min and 28 h (median 130 min) with the maximum rain intensity recorded being 134 mm/h on 24-07-2009. Seasonal differences were identified for rain event average intensities and maximum intensities per event. The influence of GWL on rain properties such as rain intensity and drop size distribution per time step and per event was investigated based on the above mentioned rain event definition. Pairwise Wilcoxon-tests revealed that higher rain intensity and larger drops were associated with the GWL "Low over the British Isles" (TB), whereas low rain intensities and less drops per interval were associated with the GWL "High over Central Europe" (HM). "Trough over Central Europe" (TRM) was linked to smaller drops and "High Scandinavia-Iceland, Trough C. Europe" (HNFZ) had fewer drops per time step when compared to other GWL types. We also investigated the intra-event behavior regarding fluctuations in rain intensity, rain drop counts, and drop size distribution with time. When combined with predictions of circulation patterns, our analysis provides a detailed insight into the characteristics of rain events under different future climate scenarios, but definitively an extended measurement period and more measurement locations are needed for validation.

Estimation of the rain signal in the presence of large surface clutter

NASA Technical Reports Server (NTRS)

Ahamad, Atiq; Moore, Richard K.

1994-01-01

The principal limitation for the use of a spaceborne imaging SAR as a rain radar is the surface-clutter problem. Signals may be estimated in the presence of noise by averaging large numbers of independent samples. This method was applied to obtain an estimate of the rain echo by averaging a set of N(sub c) samples of the clutter in a separate measurement and subtracting the clutter estimate from the combined estimate. The number of samples required for successful estimation (within 10-20%) for off-vertical angles of incidence appears to be prohibitively large. However, by appropriately degrading the resolution in both range and azimuth, the required number of samples can be obtained. For vertical incidence, the number of samples required for successful estimation is reasonable. In estimating the clutter it was assumed that the surface echo is the same outside the rain volume as it is within the rain volume. This may be true for the forest echo, but for convective storms over the ocean the surface echo outside the rain volume is very different from that within. It is suggested that the experiment be performed with vertical incidence over forest to overcome this limitation.

Optical heat flux gauge

DOEpatents

Noel, Bruce W.; Borella, Henry M.; Cates, Michael R.; Turley, W. Dale; MaCarthur, Charles D.; Cala, Gregory C.

1991-01-01

A heat flux gauge comprising first and second thermographic phosphor layers separated by a layer of a thermal insulator. The gauge may be mounted on a surface with the first thermographic phosphor in contact with the surface. A light source is directed at the gauge, causing the phosphors to luminesce. The luminescence produced by the phosphors is collected and its spectra analyzed in order to determine the heat flux on the surface. First and second phosphor layers must be different materials to assure that the spectral lines collected will be distinguishable.

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

Merging of rain gauge and radar data for urban hydrological modelling

NASA Astrophysics Data System (ADS)

Berndt, Christian; Haberlandt, Uwe

2015-04-01

Urban hydrological processes are generally characterised by short response times and therefore rainfall data with a high resolution in space and time are required for their modelling. In many smaller towns, no recordings of rainfall data exist within the urban catchment. Precipitation radar helps to provide extensive rainfall data with a temporal resolution of five minutes, but the rainfall amounts can be highly biased and hence the data should not be used directly as a model input. However, scientists proposed several methods for adjusting radar data to station measurements. This work tries to evaluate rainfall inputs for a hydrological model regarding the following two different applications: Dimensioning of urban drainage systems and analysis of single event flow. The input data used for this analysis can be divided into two groups: Methods, which rely on station data only (Nearest Neighbour Interpolation, Ordinary Kriging), and methods, which incorporate station as well as radar information (Conditional Merging, Bias correction of radar data based on quantile mapping with rain gauge recordings). Additionally, rainfall intensities that were directly obtained from radar reflectivities are used. A model of the urban catchment of the city of Brunswick (Lower Saxony, Germany) is utilised for the evaluation. First results show that radar data cannot help with the dimensioning task of sewer systems since rainfall amounts of convective events are often overestimated. Gauges in catchment proximity can provide more reliable rainfall extremes. Whether radar data can be helpful to simulate single event flow depends strongly on the data quality and thus on the selected event. Ordinary Kriging is often not suitable for the interpolation of rainfall data in urban hydrology. This technique induces a strong smoothing of rainfall fields and therefore a severe underestimation of rainfall intensities for convective events.

Precipitation Estimate Using NEXRAD Ground-Based Radar Images: Validation, Calibration and Spatial Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xuesong

2012-12-17

Precipitation is an important input variable for hydrologic and ecological modeling and analysis. Next Generation Radar (NEXRAD) can provide precipitation products that cover most of the continental United States with a high resolution display of approximately 4 × 4 km2. Two major issues concerning the applications of NEXRAD data are (1) lack of a NEXRAD geo-processing and geo-referencing program and (2) bias correction of NEXRAD estimates. In this chapter, a geographic information system (GIS) based software that can automatically support processing of NEXRAD data for hydrologic and ecological models is presented. Some geostatistical approaches to calibrating NEXRAD data using rainmore » gauge data are introduced, and two case studies on evaluating accuracy of NEXRAD Multisensor Precipitation Estimator (MPE) and calibrating MPE with rain-gauge data are presented. The first case study examines the performance of MPE in mountainous region versus south plains and cold season versus warm season, as well as the effect of sub-grid variability and temporal scale on NEXRAD performance. From the results of the first case study, performance of MPE was found to be influenced by complex terrain, frozen precipitation, sub-grid variability, and temporal scale. Overall, the assessment of MPE indicates the importance of removing bias of the MPE precipitation product before its application, especially in the complex mountainous region. The second case study examines the performance of three MPE calibration methods using rain gauge observations in the Little River Experimental Watershed in Georgia. The comparison results show that no one method can perform better than the others in terms of all evaluation coefficients and for all time steps. For practical estimation of precipitation distribution, implementation of multiple methods to predict spatial precipitation is suggested.« less

SMAP Salinity Artifacts Associated With Presence of Rain

NASA Astrophysics Data System (ADS)

Jacob, M. M.; Santos-Garcia, A.; Jones, L.

2016-02-01

The Soil Moisture Active Passive (SMAP) satellite carries an L-band radiometer, which measures sea surface salinity (SSS) over a swath of 1000 km @ 40 km resolution. SMAP can extend the Aquarius (AQ) salinity data record with improved temporal/spatial sampling. Previous studies [see references] have demonstrated significant differences between satellite and in-situ salinity measurements during rain. In the presence of precipitation, salinity stratification exists near the sea surface, which nullifies the presumption of a well-mixed salinity. In general, these salinity gradients last only a few hours and the upper layer becomes slightly fresher in salinity. This paper describes the Rain Impact Model (RIM) that simulates the effects of rain accumulation on the SSS [Santos-Garcia et al., 2014] applied to SMAP. This model incorporates rainfall information for the previous 24 hours to the measurement sample (in this case SMAP) and uses as initialization the Hybrid Coordinate Ocean Model (HYCOM) data. Given the better resolution of SMAP, the goal of this paper is to continue the analysis previously done with AQ to better understand the effects of the instantaneous and accumulated rain on the salinity measurements. Boutin, J., N. Martin, G. Reverdin, X. Yin, and F. Gaillard (2013), Sea surface freshening inferred from SMOS and ARGO salinity: Impact of rain, Ocean Sci., 9(1), 183-192, doi:10.5194/os-9-183-2013. Santos-Garcia, A., M. Jacob, L. Jones, W. Asher, Y. Hejazin, H. Ebrahimi, and M. Rabolli (2014), Investigation of rain effects on Aquarius Sea Surface Salinity measurements, J. Geophys. Res. Oceans, 119, 7605-7624, doi:10.1002/2014JC010137. Tang, W., S.H Yueh, A. Hayashi, A.G. Fore, W.L. Jones, A. Santos-Garcia, and M.M. Jacob, (2015), Rain-Induced Near Surface Salinity Stratification and Rain Roughness Correction for Aquarius SSS Retrieval, in Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(99), 1-11, doi: 10.1109/JSTARS.2015.2463768.

Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

NASA Astrophysics Data System (ADS)

Caracciolo, Clelia; Prodi, Franco; Uijlenhoet, Remko

2006-11-01

The performances of two couples of disdrometers based on different measuring principles are compared: a classical Joss-Waldvogel disdrometer and a recently developed device, called the Pludix tested in Ferrara, Italy, and Pludix and the two-dimensional video disdrometer (2DVD) tested in Cabauw, The Netherlands. First, the measuring principles of the different instruments are presented and compared. Secondly, the performances of the two pairs of disdrometers are analysed by comparing their rain amounts with nearby tipping bucket rain gauges and the inferred drop size distributions. The most important rainfall integral parameters (e.g. rain rate and radar reflectivity) and drop size distribution parameters are also analysed and compared. The data set for Ferrara comprises 13 rainfall events, with a total of 20 mm of rainfall and a maximum rain rate of 4 mm h - 1 . The data set for Cabauw consists of 9 events, with 25-50 mm of rainfall and a maximum rain rate of 20-40 mm h - 1 . The Pludix tends to underestimate slightly the bulk rainfall variables in less intense events, whereas it tends to overestimate with respect to the other instruments in heavier events. The correspondence of the inferred drop size distributions with those measured by the other disdrometers is reasonable, particularly with the Joss-Waldvogel disdrometer. Considering that the Pludix is still in a calibration and testing phase, the reported results are encouraging. A new signal inversion algorithm, which will allow the detection of rain drops throughout the entire diameter interval between 0.3 and 7.0 mm, is under development.

Flashflood in the South of Brazil: a Tragedy not Detected by the Meteorological Services

NASA Astrophysics Data System (ADS)

Foster, P.

2012-12-01

A heavy rain hit the southern Rio Grande do Sul (Brazil) between the afternoon of the 9th and the morning of March 10, 2011. On March 10, the city of São Lourenço do Sul was hit by a tragic flood that left a trail of destruction, death, mud and losses, both in urban and rural areas. Hundreds of families had to leave their homes. This flood damaged two bridges of the highway BR-116, that connects Pelotas to Porto Alegre. The rain has affected about 60% of the territory of the city, located on the shores of the Lagoa dos Patos, just after the levels from the São Lourenço's River rose by up to three meters in a few hours. We recorded eight deaths due to flooding. According to the report of the Civil Defense, the damage caused by flooding left a balance of eight deaths, and counting the damage to private property, it is estimated that the value reaches $ 400 million, equivalent to a gross domestic product in the city. About 20,000 people were directly affected by the flooding of which 2.5 thousand were left homeless. São Lourenço do Sul came to be isolated due to a crater on the highway BR-116 by the floods. According to farmers measurements made at gauges in their properties, it rained between 300 and 500 mm in eight hours. This is an absurd amount, if the measurements are correct, after all there is no weather station in the area. This situation is extremely absurd and escapes the logic of a prediction, even though she is pessimistic. Any meteorologist, with a minimum of common sense or responsibility, would make a prognostic of 500 millimeters of rain without at least one supporting forecast. I it has never been seen indicating 500 mm of rain in only eight hours in Brazil. Never. For the afternoon and evening of Wednesday, the U.S. GFS model indicated no more than 30 mm for that area. The day before, the model run by the European Centre had suggested rain, but within the common parameters from 50 to 75 millimeters. Another thesis that ran the media is that there were models of higher resolution (the new model from Centro de Previsão de Tempo e Estudos Climáticos - CPTEC/INPE) and could predict the heavy rainfall of São Lourenço. But the model of high resolution (7km) from the Instituto Nacional de Meteorologia (INMET) did not even indicate heavy rain to the area. The event that led to the tragedy of São Lourenço, moreover, was incredibly isolated. In the urban area of the town, it only came to rain heavily when everything was already flooded on the morning of the Thursday. The flood took place within the municipality. It was thus a microscale occurrence. The analysis of satellite images and meteorological models results indicate that the flood was caused by a low pressure system, characterized by clockwise winds in the layers between 1500 and 5000 feet from the surface. This meteorological phenomenon occurred due to the heat associated with the surface moisture from the Atlantic Ocean. In the early afternoon of March 9, the system began to form over the region and progressed rapidly. Around 15:30 hours, the rain began on São Lourenço`s river basin, intensifying in the night toward the city. The analysis shows that in the absence of a flow strong enough to move the clouds toward the ocean, the system remained active on the municipalities of São Lourenço do Sul and Turuçu. As a consequence, the rain over the region was very intense within a few hours.

Improvements In A Laser-Speckle Surface-Strain Gauge

NASA Technical Reports Server (NTRS)

Lant, Christian T.

1996-01-01

Compact optical subsystem incorporates several improvements over optical subsystems of previous versions of laser-speckle surface-strain gauge: faster acquisition of data, faster response to transients, reduced size and weight, lower cost, and less complexity. Principle of operation described previously in "Laser System Measures Two-Dimensional Strain" (LEW-15046), and "Two-Dimensional Laser-Speckle Surface-Strain Gauge" (LEW-15337).

OLYMPEX: A Global Precipitation Mission (GPM) Ground Validation Campaign on the Olympic Peninsula in the Pacific Northwest

NASA Astrophysics Data System (ADS)

McMurdie, L. A.; Houze, R.; Lundquist, J. D.; Mass, C.; Petersen, W. A.; Schwaller, M.

2014-12-01

The Global Precipitation Measurement (GPM) Mission was successfully launched at 1837 UTC 27 February 2014 with the first space-borne Ku/Ka band Dual Frequency Precipitation Radar and a passive microwave radiometer (channels ranging from 10-183 GHz). The primary objective of the Core satellite is to measure rain and snow globally, determine its 3D structure, and act as the calibration satellite for a constellation of GPM passive microwave satellites. In order to assess how remotely sensed precipitation can be applied to a range of data applications, ground validation (GV) field campaigns are crucial. As such, the Olympic Mountains Experiment (OLYMPEX) is planned for November 2015 - February 2016. The Olympic Peninsula in Washington State is an ideal location to conduct a GV campaign. It is situated within an active mid-latitude winter storm track and receives among the highest annual precipitation amounts in North America. In one compact area, the Olympic peninsula ranges from ocean to coast to land to mountains. It contains a permanent snowfield and numerous associated river basins. This unique venue will enable the field campaign to monitor both upstream precipitation characteristics and processes over the ocean and their modification over complex terrain. The scientific goals of the OLYMPEX field campaign include physical validation of satellite algorithms, precipitation mechanisms in complex terrain, hydrological applications, and modeling studies. In order to address these goals, a wide variety of existing and new observations are planned. These include surface observing networks of meteorological stations, rain and snow gauges, surface microphysical measurements, and snowpack surveys. Several radars will be deployed including the NASA S-Band dual-polarimetric and NASA Dual-Frequency Dual-Polarimetric Doppler radars, the Canadian x-band radar, and other mobile radars. Several instrumented aircraft are likely to participate such as the NASA DC-8 and the University of North Dakota Citation. The aircraft measurements will determine upstream thermodynamic and moisture conditions, sample particle types and sizes, and act as a proxy for the satellite itself. The ground-based measurements will test how well the satellite proxy measurements determine the rain and snow over complex terrain.

Data driven analysis of rain events: feature extraction, clustering, microphysical /macro physical relationship

NASA Astrophysics Data System (ADS)

Djallel Dilmi, Mohamed; Mallet, Cécile; Barthes, Laurent; Chazottes, Aymeric

2017-04-01

The study of rain time series records is mainly carried out using rainfall rate or rain accumulation parameters estimated on a fixed integration time (typically 1 min, 1 hour or 1 day). In this study we used the concept of rain event. In fact, the discrete and intermittent natures of rain processes make the definition of some features inadequate when defined on a fixed duration. Long integration times (hour, day) lead to mix rainy and clear air periods in the same sample. Small integration time (seconds, minutes) will lead to noisy data with a great sensibility to detector characteristics. The analysis on the whole rain event instead of individual short duration samples of a fixed duration allows to clarify relationships between features, in particular between macro physical and microphysical ones. This approach allows suppressing the intra-event variability partly due to measurement uncertainties and allows focusing on physical processes. An algorithm based on Genetic Algorithm (GA) and Self Organising Maps (SOM) is developed to obtain a parsimonious characterisation of rain events using a minimal set of variables. The use of self-organizing map (SOM) is justified by the fact that it allows to map a high dimensional data space in a two-dimensional space while preserving as much as possible the initial space topology in an unsupervised way. The obtained SOM allows providing the dependencies between variables and consequently removing redundant variables leading to a minimal subset of only five features (the event duration, the rain rate peak, the rain event depth, the event rain rate standard deviation and the absolute rain rate variation of order 0.5). To confirm relevance of the five selected features the corresponding SOM is analyzed. This analysis shows clearly the existence of relationships between features. It also shows the independence of the inter-event time (IETp) feature or the weak dependence of the Dry percentage in event (Dd%e) feature. This confirms that a rain time series can be considered by an alternation of independent rain event and no rain period. The five selected feature are used to perform a hierarchical clustering of the events. The well-known division between stratiform and convective events appears clearly. This classification into two classes is then refined in 5 fairly homogeneous subclasses. The data driven analysis performed on whole rain events instead of fixed length samples allows identifying strong relationships between macrophysics (based on rain rate) and microphysics (based on raindrops) features. We show that among the 5 identified subclasses some of them have specific microphysics characteristics. Obtaining information on microphysical characteristics of rainfall events from rain gauges measurement suggests many implications in development of the quantitative precipitation estimation (QPE), for the improvement of rain rate retrieval algorithm in remote sensing context.

The mixing of rain with near-surface water

Treesearch

Dennis F. Houk

1976-01-01

Rain experiments were run with various temperature differences between the warm rain and the cool receiving water. The rain intensities were uniform and the raindrop sizes were usually uniform (2.2 mm, 3.6 mm, and 5.5 mm diameter drops). Two drop size distributions were also used.

Potential Improvements for HEC-HMS Automated Parameter Estimation

DTIC Science & Technology

2006-08-01

and is now a graduate student in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana /Champaign. Daniel...divided into 14 nested subwatersheds with a flow measuring flume constructed at each of the subwatershed outlets. The drainage areas above the...boundaries and stream network, and rain and stream gauge locations are shown in Figure 1. The first HEC-HMS model was applied to the 39.8-acre drainage

Torrential Rain in China

NASA Technical Reports Server (NTRS)

2007-01-01

Concentric ovals of red, orange, yellow, and green are draped over southern China, showing rainfall totals for the week of June 4 through June 11, 2007. The rainfall totals are from the Goddard Space Flight Center Multi-satellite Precipitation Analysis, which is based on rainfall measurements taken by the Tropical Rainfall Measuring Mission (TRMM) satellite. Though seasonal rains are not unexpected in the area, the rain that fell during the week was torrential and relentless. As the image shows, a broad stretch of China received up to 200 millimeters (8 inches) of rain, and some areas were inundated with up to 500 millimeters (20 inches). Floods and landslides resulted, destroying crops and forcing some 643,000 people from their homes, reported the Xinhua News Agency on ReliefWeb. As of June 11, 71 people had died and 13 were missing. The most affected area was the southern coast, where rainfall totals are highest in this image. Heavy tropical rains combined with steep mountains make southeastern China prone to devastating landslides. Monitoring landslide-producing conditions typically requires extensive networks of ground-based rain gauges and weather instruments. But many developing countries in high-risk areas lack the resources to maintain such systems; heavy rains and flooding often wash away ground-based instruments. Robert Adler, a senior scientist in the Laboratory for Atmospheres at Goddard Space Flight Center, and Yang Hong, a research scientist at Goddard Earth Sciences Technology Center, are confronting the problem by developing a satellite-based system for predicting landslides. The system relies on TRMM data to predict when rainfall in different areas has reached a landslide-triggering threshold. The system makes data available on the Internet just a few hours after the satellite makes its observations. To read more about the landslide-monitoring system, please read the feature article Satellite Monitors Rains That Trigger Landslides, http://earthobservatory.nasa.gov/Study/LandslideWarning/. TRMM is a joint mission between NASA and the Japanese space agency, JAXA. NASA images produced by Hal Pierce (SSAI/NASA GSFC).

Understanding Flash Flood Generation in the Arid Region of the Dead Sea

NASA Astrophysics Data System (ADS)

Merz, R.; Hennig, H.; Rödiger, T.; Laronne, J. B.

2017-12-01

The arid region of the Dead Sea is prone by flash floods. Such flash floods in (semi-) arid regions are impressive. Generated within minutes, the peak unit discharge can be as high as 25 m³/s km². Floods are the main mechanism supplying water to alluvial aquifers, forming fluvial landscapes including canyons and often causing damage to humans, infrastructure, industry and tourism. Existing hydrological models in this region focus on peak discharges. However, these models are often based on simplified concepts and/or on concepts which were developed for humid regions. To more closely relate such models to local conditions, processes within catchments where floods occur require consideration. Therefore, a measurement network of rain gauges and level loggers to monitor runoff was installed in the beginning of the 2015/16 hydrological season in the tributaries of Wadi Arugot. The Arugot catchment is one of the largest ephemeral Wadis draining to the western shoreline of the Dead Sea at 450 m bsl. Due to the high gradient in elevation, the climate within the basin ranges from semiarid in the Judean Mountains, to hyper-arid near the Dead Sea with respective mean annual rainfall of 650 and 50 mm. The installed rain gauge network in the mountains is more dense compared to the Dead Sea area. Arid to semiarid catchments have different runoff generation processes compared to humid regions due local storm rainfall, low density of vegetation cover as well as patchy and shallow soil. These characteristics limit the contribution of groundwater flow, saturated overland flow and shallow subsurface flow, and therefore Hortonian overland flow is the most important contributor to overland flow. First analyses of the runoff data have shown that the storage capacity in the mountain area is lower compared to the more arid region. This is an evidence of high transmission losses in the coarse gravel wadi bed, therefore having a high permeability. The rain event duration and the amount of rain could not be determined as the only factors which lead to the generation of runoff events.

Potential Applications of Remote Sensing Precipitation Data on Urban Stormwater Modeling

NASA Astrophysics Data System (ADS)

Maggioni, V.; Tarantola, R.; Ferreira, C.

2014-12-01

Although stormwater modeling is widely used to plan, manage and operate stormwater systems in the urban environment, accuracy in model development and calibration is still problematic. Precipitation is the major forcing of stormwater modeling and one of the most important variables for accurate representation of the water cycle in urban areas. However, rainfall data availability in both temporal and spatial adequate scales is scarce. Here we investigate the potential to apply satellite precipitation products to small-scale urban watersheds with a focus on real-time data for operational use and historical data for model calibration and planning. We present a study case in Northern Virginia, part of the Washington, D.C. metropolitan region. We compare several rainfall datasets from satellites, radar and rain gauges during 2002-2008, using two multi-satellite precipitation products. The first one is the NASA TRMM TMPA at daily/0.25° time/space resolution, which is available in two forms: 3B42-Real Time and 3B42-Version 7, where the latter is a post-processed product, corrected with ground-based observations. The second one is the NOAA CMORPH at 3hrs/0.25° time/space resolution. The NOAA Climate Prediction Center (CPC) data and NCEP Stage IV radar-based product are used as reference datasets for TMPA and CMORPH, respectively. Statistical analyses are conducted to compare these datasets: correlation coefficient, RMSE, bias, probability of correct no-rain detection and of false alarm were computed with a focus on Fairfax, VA county. Preliminary results show that the TMPA products outperform CMORPH, when compared to rain gauges and radar data over the county. Moreover, no appreciable difference is detected between TMPA-V7 and TMPA-RT, which demonstrates that real-time data could be used over the urban watershed with results that are comparable to the adjusted product. Analyses are undergoing to investigate higher temporal resolution and to include a comparison with the Fairfax county rain gages data. Future work will also evaluate the impacts of different precipitation datasets on stormwater runoff for Fairfax county, using the EPA-SWMM5 storm water model.

Numerical Study of the Role of Microphysical Latent Heating and Surface Heat Fluxes in a Severe Precipitation Event in the Warm Sector over Southern China

NASA Astrophysics Data System (ADS)

Yin, Jin-Fang; Wang, Dong-Hai; Liang, Zhao-Ming; Liu, Chong-Jian; Zhai, Guo-Qing; Wang, Hong

2018-02-01

Simulations of the severe precipitation event that occurred in the warm sector over southern China on 08 May 2014 are conducted using the Advanced Weather Research and Forecasting (WRF-ARWv3.5.1) model to investigate the roles of microphysical latent heating and surface heat fluxes during the severe precipitation processes. At first, observations from surface rain gauges and ground-based weather radars are used to evaluate the model outputs. Results show that the spatial distribution of 24-h accumulated precipitation is well reproduced, and the temporal and spatial distributions of the simulated radar reflectivity agree well with the observations. Then, several sensitive simulations are performed with the identical model configurations, except for different options in microphysical latent heating and surface heat fluxes. From the results, one of the significant findings is that the latent heating from warm rain microphysical processes heats the atmosphere in the initial phase of the precipitation and thus convective systems start by self-triggering and self-organizing, despite the fact that the environmental conditions are not favorable to the occurrence of precipitation event at the initial phase. In the case of the severe precipitation event over the warm sector, both warm and ice microphysical processes are active with the ice microphysics processes activated almost two hours later. According to the sensitive results, there is a very weak precipitation without heavy rainfall belt when microphysical latent heating is turned off. In terms of this precipitation event, the warm microphysics processes play significant roles on precipitation intensity, while the ice microphysics processes have effects on the spatial distribution of precipitation. Both surface sensible and latent heating have effects on the precipitation intensity and spatial distribution. By comparison, the surface sensible heating has a strong influence on the spatial distribution of precipitation, and the surface latent heating has only a slight impact on the precipitation intensity. The results indicate that microphysical latent heating might be an important factor for severe precipitation forecast in the warm sector over southern China. Surface sensible heating can have considerable influence on the precipitation spatial distribution and should not be neglected in the case of weak large-scale conditions with abundant water vapor in the warm sector.

Quantitative analysis of precipitation over Fukushima to understand the wet deposition process in March 2011

NASA Astrophysics Data System (ADS)

Yatagai, A.; Onda, Y.; Watanabe, A.

2012-04-01

The Great East Japan Earthquake caused a severe accident at the Fukushima-Daiichi nuclear power plant (NPP), leading to the emission of large amounts of radioactive pollutants into the environment. The transport and diffusion of these radioactive pollutants in the atmosphere caused a disaster for residents in and around Fukushima. Studies have sought to understand the transport, diffusion, and deposition process, and to understand the movement of radioactive pollutants through the soil, vegetation, rivers, and groundwater. However, a detailed simulation and understanding of the distribution of radioactive compounds depend on a simulation of precipitation and on the information on the timing of the emission of these radioactive pollutants from the NPP. Past nuclear expansion studies have demonstrated the importance of wet deposition in distributing pollutants. Hence, this study examined the quantitative precipitation pattern in March 2011 using rain-gauge observations and X-band radar data from Fukushima University. We used the AMeDAS rain-gauge network data of 1) the Japan Meteorological Agency (1273 stations in Japan) and 2) the Water Information System (47 stations in Fukushima prefecture) and 3) the rain-gauge data of the Environmental Information Network of NTT Docomo (30 stations in Fukushima) to construct 0.05-degree mesh data using the same method used to create the APHRODITE daily grid precipitation data (Yatagai et al., 2009). Since some AMeDAS data for the coastal region were lost due to the earthquake, the complementary network of 2) and 3) yielded better precipitation estimates. The data clarified that snowfall was observed on the night of Mar 15 into the morning of Mar 16 throughout Fukushima prefecture. This had an important effect on the radioactive contamination pattern in Fukushima prefecture. The precipitation pattern itself does not show one-on-one correspondence with the contamination pattern. While the pollutants transported northeast of the NPP and through north Kanto (about 200 km southwest of Fukushima and, 100 km north of Tokyo) went to the northwest, the timing of the precipitation causing the fallout, i.e., wet-deposition, is important. Although the hourly Radar-AMeDAS 1-km-mesh precipitation data of JMA are available publically, it does not represent the precipitation pattern in Nakadori, in central Fukushima prefecture. Hence, we used 10-minute interval X-band radar, located in north Nakadori to determine the start and detailed horizontal pattern (120-m mesh) of the precipitation. Since 1) and 3) are 10-minute intervals and 2) is hourly data, we are developing hourly gridded data and using 1-3) to verify and quantify the rain rate observed by the Fukushima University X-band data.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Leblois, E.; Onfroy, T.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2014-09-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45 % outside. Another 10 % is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Presenting the Rain-Sea Interaction Facility

NASA Technical Reports Server (NTRS)

Bliven, Larry F.; Elfouhaily, Tonas M.

1993-01-01

The new Rain-Sea Interaction Facility (RSIF) was established at GSFC/WFF and the first finds are presented. The unique feature of this laboratory is the ability to systematically study microwave scattering from a water surface roughened by artificial rain, for which the droplets are at terminal velocity. The fundamental instruments and systems (e.g., the rain simulator, scatterometers, and surface elevation probes) were installed and evaluated during these first experiments - so the majority of the data were obtained with the rain simulator at 1 m above the water tank. From these initial experiments, three new models were proposed: the square-root function for NCS vs. R, the log Gaussian model for ring-wave elevation frequency spectrum, and the Erland probability density distribution for back scattered power. Rain rate is the main input for these models, although the coefficients may be dependent upon other factors (drop-size distribution, fall velocity, radar configuration, etc.). The facility is functional and we foresee collaborative studies with investigators who are engaged in measuring and modeling rain-sea interaction processes.

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

NASA Technical Reports Server (NTRS)

Iacovazzi, Robert A., Jr.; Prabhakara, C.

2002-01-01

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.

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

NASA Technical Reports Server (NTRS)

Iacovazzi, Robert A., Jr.; Prabhakara, C.; Lau, William K. M. (Technical Monitor)

2001-01-01

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.

Quantifying dominance of intra-storm phase of interception process by small isolated canopies

NASA Astrophysics Data System (ADS)

Yerk, Walter; Montalto, Franco

2014-05-01

Precipitation interception by vegetation canopies has long been recognized as a major component of the hydrologic cycle; however, historically most research has been dedicated to closed or sparse canopy forests. The goal of our research was to quantify rainfall partitioning by small isolated canopies in an urban setting. The field experiment involved small forms of four shrub species (Prunus laurocerasus, Cornus sericea, Itea virginica and Hydrangea quercifolia) with crown heights 40 - 80 cm and diameters 35 - 60 cm. Each plant had ten rain gauges to measure throughfall with a sampling frequency of 5 seconds. An on-site automated weather station provided meteorological data. Leaf area index (LAI) was measured by manual counting. We estimated the canopy storage capacities of all four species to be less than 0.5 mm. The obtained data showed statistically significant differences in interception properties among all four species, except between Cornus and Itea. Cumulative interception loss for the period of August-December 2013 was 10% for Cornus, 16% for Itea, 29% for Hydrangea, and 49% for Prunus. The observations revealed a weak relationship between interception abilities and LAI for all four species. Throughfall and precipitation intensities (mm/hr) expressed very strong linear relationship (adjusted coefficients of determination were from 0.80 to 0.95) for the entire range of observed rainfall intensities. For Cornus the ratio of throughfall to precipitation intensity was close to 0.93:1, for Itea it was 0.82:1. The ratios were lesser for Hydrangea (0.65:1), and especially for Prunus (0.48:1). Therefore we show that reduced by the canopy, throughfall intensity results in the bulk of precipitation depth intercepted during the rain events. In contrast, the amount of water stored on the canopy and evaporated between and after rain events contributes minimally to interception. Simulations of potential evaporation based on the Penman-Monteith method showed a large underestimation of evaporation from the wet canopies during the rain events. Approaches other than energy balance models of potential evaporation from a still water surface are being discussed in order to explain large evaporation from within a wet isolated canopy.

Country-wide rainfall maps from cellular communication networks

PubMed Central

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2013-01-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

Implications of Warm Rain in Shallow Cumulus and Congestus Clouds for Large-Scale Circulations

NASA Astrophysics Data System (ADS)

Nuijens, Louise; Emanuel, Kerry; Masunaga, Hirohiko; L'Ecuyer, Tristan

2017-11-01

Space-borne observations reveal that 20-40% of marine convective clouds below the freezing level produce rain. In this paper we speculate what the prevalence of warm rain might imply for convection and large-scale circulations over tropical oceans. We present results using a two-column radiative-convective model of hydrostatic, nonlinear flow on a non-rotating sphere, with parameterized convection and radiation, and review ongoing efforts in high-resolution modeling and observations of warm rain. The model experiments investigate the response of convection and circulation to sea surface temperature (SST) gradients between the columns and to changes in a parameter that controls the conversion of cloud condensate to rain. Convection over the cold ocean collapses to a shallow mode with tops near 850 hPa, but a congestus mode with tops near 600 hPa can develop at small SST differences when warm rain formation is more efficient. Here, interactive radiation and the response of the circulation are crucial: along with congestus a deeper moist layer develops, which leads to less low-level radiative cooling, a smaller buoyancy gradient between the columns, and therefore a weaker circulation and less subsidence over the cold ocean. The congestus mode is accompanied with more surface precipitation in the subsiding column and less surface precipitation in the deep convecting column. For the shallow mode over colder oceans, circulations also weaken with more efficient warm rain formation, but only marginally. Here, more warm rain reduces convective tops and the boundary layer depth—similar to Large-Eddy Simulation (LES) studies—which reduces the integrated buoyancy gradient. Elucidating the impact of warm rain can benefit from large-domain high-resolution simulations and observations. Parameterizations of warm rain may be constrained through collocated cloud and rain profiling from ground, and concurrent changes in convection and rain in subsiding and convecting branches of circulations may be revealed from a collocation of space-borne sensors, including the Global Precipitation Measurement (GPM) and upcoming Aeolus missions.

Assessing various approaches for flash flood forecasting in the Yzeron periurban catchment (150 km2) south-east Lyon, France

NASA Astrophysics Data System (ADS)

Braud, Isabelle; Breil, Pascal; Javelle, Pierre; Pejakovic, Nikola; Guérin, Stéphane

2017-04-01

The Yzeron periurban catchment (150 km2) is prone to flash floods leading to overflow in the downstream part of the catchment. A prevention and management plan has been approved and the set-up of a flood forecasting system is planned. The present study presents a comparison of several solutions for flood forecasting in the catchment. It is based on an extensive data collection (rain gauges, radar/rain gauge reanalyses, discharge and water level data) from this experimental catchment. A set of rainfall-runoff events leading to floods (problematic and non-problematic floods) was extracted and formed the basis for the definition of a first forecasting method. It is based on data analysis and the identification of explaining factors amongst the following: rainfall amount, intensity, antecedent rainfall, initial discharge. Several statistical methods including Factorial Analysis of Mixed Data and Classification and Regression Tree were used for this purpose. They showed that several classes of problematic floods can be identified. The first one is related to wet conditions characterized with high initial discharge and antecedent rainfall. The second class is driven by rainfall amount, initial discharge and rainfall intensity. Thresholds of these variables can be identified to provide a first warning. The second forecasting method assessed in the study is the system that will be operational in France in 2017, based on the AIGA method (Javelle et al., 2016). For this purpose, 18-year discharge simulation using the hydrological model of the AIGA method, forced using radar/rain gauges reanalysis were available at 44 locations within the catchment. The dates for which quantiles of a given return period were overtopped were identified and compared with the list of problematic events. The AIGA method was found relevant in identifying the most problematic events, but the lead time needs further investigation in order to assess the usefulness for population warning. References: Pierre Javelle, Didier Organde, Julie Demargne, Clotilde Saint-Martin, Céline de Saint-Aubin, Léa Garandeau and Bruno Janet (2016). Setting up a French national flash flood warning system for ungauged catchments based on the AIGA method. E3S Web of Conferences 7, 18010 (2016), 3rd European Conference on Flood Risk Management (FLOODrisk 2016), http://dx.doi.org/10.1051/e3sconf/20160718010

Contribution of tropical cyclones to global rainfall

NASA Astrophysics Data System (ADS)

Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

2016-04-01

Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar patterns using the POT approach to identify extremes. The fractional contributions decrease as we move inland from the coast. Moreover, the relationship between TC-induced extreme rainfall and the El Niño-Southern Oscillation is also examined using logistic and Poisson regression. Results indicate that TC-induced extreme rainfall tends to occur more frequently in Australia and along the U.S. East Coast during La Niña, and along eastern Asia and northwestern Pacific islands during El Niño.

Technical Note: An operational landslide early warning system at regional scale based on space-time-variable rainfall thresholds

NASA Astrophysics Data System (ADS)

Segoni, S.; Battistini, A.; Rossi, G.; Rosi, A.; Lagomarsino, D.; Catani, F.; Moretti, S.; Casagli, N.

2015-04-01

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult, and it provides different outputs. When switching among different views, the system is able to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a basic data view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain gauges can be displayed and constantly compared with rainfall thresholds. To better account for the variability of the geomorphological and meteorological settings encountered in Tuscany, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of more than 300 rain gauges, it allows for the monitoring of each alert zone separately so that warnings can be issued independently. An important feature of the warning system is that the visualization of the thresholds in the WebGIS interface may vary in time depending on when the starting time of the rainfall event is set. The starting time of the rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting time for which the rainfall path is closest to or overcomes the threshold. This is considered the most hazardous condition, and it is displayed by the WebGIS interface. The early warning system is used to forecast and monitor the landslide hazard in the whole region, providing specific alert levels for 25 distinct alert zones. In addition, the system can be used to gather, analyze, display, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

Representing radar rainfall uncertainty with ensembles based on a time-variant geostatistical error modelling approach

NASA Astrophysics Data System (ADS)

Cecinati, Francesca; Rico-Ramirez, Miguel Angel; Heuvelink, Gerard B. M.; Han, Dawei

2017-05-01

The application of radar quantitative precipitation estimation (QPE) to hydrology and water quality models can be preferred to interpolated rainfall point measurements because of the wide coverage that radars can provide, together with a good spatio-temporal resolutions. Nonetheless, it is often limited by the proneness of radar QPE to a multitude of errors. Although radar errors have been widely studied and techniques have been developed to correct most of them, residual errors are still intrinsic in radar QPE. An estimation of uncertainty of radar QPE and an assessment of uncertainty propagation in modelling applications is important to quantify the relative importance of the uncertainty associated to radar rainfall input in the overall modelling uncertainty. A suitable tool for this purpose is the generation of radar rainfall ensembles. An ensemble is the representation of the rainfall field and its uncertainty through a collection of possible alternative rainfall fields, produced according to the observed errors, their spatial characteristics, and their probability distribution. The errors are derived from a comparison between radar QPE and ground point measurements. The novelty of the proposed ensemble generator is that it is based on a geostatistical approach that assures a fast and robust generation of synthetic error fields, based on the time-variant characteristics of errors. The method is developed to meet the requirement of operational applications to large datasets. The method is applied to a case study in Northern England, using the UK Met Office NIMROD radar composites at 1 km resolution and at 1 h accumulation on an area of 180 km by 180 km. The errors are estimated using a network of 199 tipping bucket rain gauges from the Environment Agency. 183 of the rain gauges are used for the error modelling, while 16 are kept apart for validation. The validation is done by comparing the radar rainfall ensemble with the values recorded by the validation rain gauges. The validated ensemble is then tested on a hydrological case study, to show the advantage of probabilistic rainfall for uncertainty propagation. The ensemble spread only partially captures the mismatch between the modelled and the observed flow. The residual uncertainty can be attributed to other sources of uncertainty, in particular to model structural uncertainty, parameter identification uncertainty, uncertainty in other inputs, and uncertainty in the observed flow.

Effects of Increased Horizontal Resolution on Simulation of the North American Monsoon in the NCAR CAM3: An Evaluation based on Surface, Satellite, and Reanalysis Data

NASA Astrophysics Data System (ADS)

Collier, J. C.; Zhang, G. J.

2006-05-01

Simulation of the North American monsoon system by the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3) is evaluated in its sensitivity to increasing horizontal resolution. For two resolutions, T42 and T85, rainfall is compared to TRMM satellite-derived and surface gauge-based rainfall rates over the U.S. and northern Mexico as well as rainfall accumulations in gauges of the North American Monsoon Experiment (NAME) Enhanced Rain Gauge Network (NERN) in the Sierra Madre Occidental mountains. Simulated upper-tropospheric mass and wind fields are compared to those from NCEP-NCAR reanalyses. The comparison presented herein demonstrates that tropospheric motions associated with the North American monsoon system are sensitive to increasing the horizontal resolution of the model. An increase in resolution from T42 to T85 results in changes to a region of large-scale mid-tropospheric descent found north and east of the monsoon anticyclone. Relative to its simulation at T42, this region extends farther south and west at T85. Additionally, at T85, the subsidence is stronger. Consistent with the differences in large-scale descent, the T85 simulation of CAM3 is anomalously dry over Texas and northeastern Mexico during the peak monsoon months. Meanwhile, the geographic distribution of rainfall over the Sierra Madre Occidental region of Mexico is more satisfactorily simulated at T85 than at T42 for July and August. Moisture import into this region is greater at T85 than at T42 during these months. A focused study of the Sierra Madre Occidental region in particular shows that, in the regional average sense, the timing of the peak of the monsoon is relatively insensitive to the horizontal resolution of the model, while a phase bias in the diurnal cycle of monsoon-season precipitation is somewhat reduced in the higher-resolution run. At both resolutions, CAM3 poorly simulates the month-to-month evolution of monsoon rainfall over extreme northwestern Mexico and Arizona, though biases are considerably improved at T85.

An Event-based Assessment of Uncertainty in Measurements Between Multiple Precipitation Sensors During the North American Monsoon

NASA Astrophysics Data System (ADS)

Kautz, M. A.; Keefer, T.; Demaria, E. M.; Goodrich, D. C.; Hazenberg, P.; Petersen, W. A.; Wingo, M. T.; Smith, J.

2017-12-01

The USDA - Agricultural Research Service (USDA-ARS) Long-Term Agroecosystem Research network (LTAR) is a partnership between 18 long-term research sites across the United States. As part of the program, LTAR aims to assemble a network of common sensors and measurements of hydrological, meteorological, and biophysical variables to accompany the legacy datasets of individual LTAR sites. Uncertainty remains as to how the common sensor-based measurements will compare to those measured with existing sensors at each site. The USDA-ARS Southwest Watershed Research Center (SWRC) operated Walnut Gulch Experimental Watershed (WGEW) represents the semiarid grazing lands located in southeastern Arizona in the LTAR network. The bimodal precipitation regime of this region is characterized by large-scale frontal precipitation in the winter and isolated, high-intensity, convective thunderstorms in the summer during the North American Monsoon (NAM). SWRC maintains a network of 90 rain gauges across the 150 km2 WGEW and surrounding area, with measurements dating back to the 1950's. The high intensity and isolated nature of the summer storms has historically made it difficult to quantify compared to other regimes in the US. This study assesses the uncertainty of measurement between the common LTAR Belfort All Weather Precipitation Gauge (AEPG 600) and the legacy WGEW weighing-type raingage. Additionally, in a collaboration with NASA Global Precipitation Measurement mission (GPM) and the University of Arizona a dense array of precipitation measuring sensors was installed at WGEW within a 10 meter radius for observation during the NAM, July through October 2017. In addition to two WGEW weighing-type gauges, the array includes: an AEPG 600, a tipping bucket, a weighing-bucket installed with orifice at ground level, an OTT Pluvio2 rain gauge, a Two-Dimensional Video Disdrometer (2DVD), and three OTT Parsivel2 disdrometers. An event-based comparison was made between precipitation sensors using metrics including total depth, peak intensity (1, 15, 30, and 60 minute), event duration, time to peak intensity, and start time of event. These results provide further insight into the uncertainties of measuring point-based precipitation in this unique precipitation regime and representation in large-scale observation networks.

Use of microwave satellite data to study variations in rainfall over the Indian Ocean

NASA Technical Reports Server (NTRS)

Hinton, Barry B.; Martin, David W.; Auvine, Brian; Olson, William S.

1990-01-01

The University of Wisconsin Space Science and Engineering Center mapped rainfall over the Indian Ocean using a newly developed Scanning Multichannel Microwave Radiometer (SMMR) rain-retrieval algorithm. The short-range objective was to characterize the distribution and variability of Indian Ocean rainfall on seasonal and annual scales. In the long-range, the objective is to clarify differences between land and marine regimes of monsoon rain. Researchers developed a semi-empirical algorithm for retrieving Indian Ocean rainfall. Tools for this development have come from radiative transfer and cloud liquid water models. Where possible, ground truth information from available radars was used in development and testing. SMMR rainfalls were also compared with Indian Ocean gauge rainfalls. Final Indian Ocean maps were produced for months, seasons, and years and interpreted in terms of historical analysis over the sub-continent.

HOAPS precipitation validation with ship-borne rain and snow measurements over the Ocean

NASA Astrophysics Data System (ADS)

Bumke, Karl; Schröder, Marc; Fennig, Karsten

2013-04-01

Measuring precipitation over the oceans is still a challenging task. The main reason for a lack of such data can be attributed to the difficulty of measuring precipitation on moving platforms under high wind speeds. The progress in satellite technology has provided the possibility to retrieve global data sets from space, including precipitation. Levizzani et al. (2007) showed that precipitation over the oceans can be derived with sufficient accuracy from passive microwave radiometry. On the other hand, Andersson et al. (2011) pointed out that even state-of-the-art satellite retrievals and reanalysis data sets still disagree on global precipitation with respect to amounts, patterns, variability and temporal behaviour. This creates the need for ship-based precipitation validation data using instruments capable of accurately measuring rain rates even under high wind speed conditions. In the present study we use ship rain gauges (Hasse et al., 1998) and optical disdrometers (Großklaus et al., 1998), the latter is also capable to measure snow (Lempio et al., 2007). Measurements are point-to-area collocated against Hamburg Ocean Atmosphere Parameters and fluxes from Satellite (HOAPS) data (Andersson et al., 2011). The used HOAPS-S data subset contains all retrieved physical parameters at the native SSM/I (Special Sensor Microwave Imager) pixel-level resolution of approximately 50 km for each individual satellite. The algorithm does not discriminate between rain and snowfall. The satellite data is compared to the in situ measurement by the nearest neighbour approach. Therefore, it must be ensured that both observations are related to each other, which can be determined by the decorrelation length. At least a number of 660 precipitation events are at our disposal including 127 snow events. The statistical analysis follows the recommendations given by the World Meteorological Organization (WMO) for dichotomous or binary forecasts (WWRP/WGNE: http://www.cawcr.gov.au/projects/verification/#Methods_for_dichotomous_forecasts). Taking into account that precipitation has to be regarded as a rare event, a better estimate of the performance is the so-called threat score or critical success index (CSI) instead of the proportion correct. The CSI reaches values up to 0.71 for all events and 0.65 taking only snow measurements into account. From accumulated precipitation rates can be concluded that the HOAPS precipitation rates are in a good agreement to measurements. References Andersson, A., Klepp, C., Fennig, K., Bakan, S., Graßl, H. and 495 co-authors. 2011. Evaluation of HOAPS-3 ocean surface freshwater flux components. J. Appl. Meteorol. Climatol. 50, 379-398, doi:10.1175/2010JAMC2341.1. Großklaus, M., Uhlig, K. and Hasse, L. 1998: An optical disdrometer for use in high wind speeds. J. Atmos. Oceanic Technol. 15, 1051-1059. Hasse, L., Großklaus, M., Uhlig, K. and Timm, P. 1998: A ship rain gauge for use under high wind speeds. J. Atmos. Oceanic Technol. 15, 380-386. Lempio, G. E., Bumke, K. and Macke, A., 2007: Measurements of solid precipitation with an optical disdrometer Advances in Space Research, 19 (3). 527-531. Levizzani, V., Bauer, P. and Turk, F. J., 2007: Measuring Precipitation from Space,EURAINSAT and the Future, Advances in Global Change Research, Vol. 28, Springer, 724 p.

Optical heat flux gauge

DOEpatents

Noel, Bruce W.; Borella, Henry M.; Cates, Michael R.; Turley, W. Dale; MacArthur, Charles D.; Cala, Gregory C.

1991-01-01

A heat flux gauge comprising first and second thermographic phosphor layers separated by a layer of a thermal insulator wherein each thermographic layer comprises a plurality of respective thermographic phosphors. The gauge may be mounted on a surface with the first thermographic phosphor in contact with the surface. A light source is directed at the gauge, causing the phosphors to luminesce. The luminescence produced by the phosphors is collected and its spectra analyzed in order to determine the heat flux on the surface. First and second phosphor layers must be different materials to assure that the spectral lines collected will be distinguishable.

Statistical simulation of ensembles of precipitation fields for data assimilation applications

NASA Astrophysics Data System (ADS)

Haese, Barbara; Hörning, Sebastian; Chwala, Christian; Bárdossy, András; Schalge, Bernd; Kunstmann, Harald

2017-04-01

The simulation of the hydrological cycle by models is an indispensable tool for a variety of environmental challenges such as climate prediction, water resources management, or flood forecasting. One of the crucial variables within the hydrological system, and accordingly one of the main drivers for terrestrial hydrological processes, is precipitation. A correct reproduction of the spatio-temporal distribution of precipitation is crucial for the quality and performance of hydrological applications. In our approach we stochastically generate precipitation fields conditioned on various precipitation observations. Rain gauges provide high-quality information for a specific measurement point, but their spatial representativeness is often rare. Microwave links, e. g. from commercial cellular operators, on the other hand can be used to estimate line integrals of near-surface rainfall information. They provide a very dense observational system compared to rain gauges. A further prevalent source of precipitation information are weather radars, which provide rainfall pattern informations. In our approach we derive precipitation fields, which are conditioned on combinations of these different observation types. As method to generate precipitation fields we use the random mixing method. Following this method a precipitation field is received as a linear combination of unconditional spatial random fields, where the spatial dependence structure is described by copulas. The weights of the linear combination are chosen in the way that the observations and the spatial structure of precipitation are reproduced. One main advantage of the random mixing method is the opportunity to consider linear and non-linear constraints. For a demonstration of the method we use virtual observations generated from a virtual reality of the Neckar catchment. These virtual observations mimic advantages and disadvantages of real observations. This virtual data set allows us to evaluate simulated precipitation fields in a very detailed manner as well as to quantify uncertainties which are conveyed by measurement inaccuracies. In a further step we use real observations as a basis for the generation of precipitation fields. The resulting ensembles of precipitation fields are used for example for data assimilation applications or as input data for hydrological models.

Wet canopy evaporation from a Puerto Rican lower montane rain forest: the importance of realistically estimated aerodynamic conductance

Treesearch

F. Holwerda; L.A. Bruijnzeel; F.N. Scatena; H.F. Vugts; A.G.C.A. Meesters

2012-01-01

Rainfall interception (I) was measured in 20 m tall Puerto Rican tropical forest with complex topography for a 1-year period using totalizing throughfall (TF) and stemflow (SF) gauges that were measured every 2–3 days. Measured values were then compared to evaporation under saturated canopy conditions (E) determined with the Penman–Monteith (P–M) equation, using (i)...

Emergent gauge field for a chiral bound state on curved surface

NASA Astrophysics Data System (ADS)

Shi, Zhe-Yu; Zhai, Hui

2017-09-01

Emergent physics is one of the most important concepts in modern physics, and one of the most intriguing examples is the emergent gauge field. Here we show that a gauge field emerges for a chiral bound state formed by two attractively interacting particles on a curved surface. We demonstrate explicitly that the center-of-mass wave function of such a deeply bound state is monopole harmonic instead of spherical harmonic, which means that the bound state experiences a magnetic monopole at the center of the sphere. This emergent gauge field is due to the coupling between the center-of-mass and the relative motion on a curved surface, and our results can be generalized to an arbitrary curved surface. This result establishes an intriguing connection between the space curvature and gauge field, and paves an alternative way to engineer a topological state with space curvature, and may be observed in a cold atom system.

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

PubMed Central

Feng, Zhe; Leung, L. Ruby; Hagos, Samson; Houze, Robert A.; Burleyson, Casey D.; Balaguru, Karthik

2016-01-01

The changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in the central United States are dominated by mesoscale convective systems (MCSs), the largest type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms. PMID:27834368

The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George J.; Chang, Alfred; Ferraro, Ralph; Xie, Ping-Ping; Janowiak, John; Rudolf, Bruno; Schneider, Udo; Curtis, Scott; Bolvin, David

2003-01-01

The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

DOE PAGES

Feng, Zhe; Leung, L. Ruby; Hagos, Samson M.; ...

2016-11-11

Here, the changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in 36 the central U.S. are dominated by mesoscale convective systems (MCSs), the largestmore » type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.« less

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Zhe; Leung, L. Ruby; Hagos, Samson M.

Here, the changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in 36 the central U.S. are dominated by mesoscale convective systems (MCSs), the largestmore » type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.« less

RHydro - Hydrological models and tools to represent and analyze hydrological data in R

NASA Astrophysics Data System (ADS)

Reusser, Dominik; Buytaert, Wouter

2010-05-01

In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. Other scientific disciplines such as mathematics and physics have benefited significantly from such an approach with freely available implementations for many routines. As an example, hydrological libraries could contain: Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data Data consistency checks Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. The design is such, that a definition of import scripts for additional models is sufficient to have access to the full set of evaluation and visualization tools.

Active and passive microwave measurements in Hurricane Allen

NASA Technical Reports Server (NTRS)

Delnore, V. E.; Bahn, G. S.; Grantham, W. L.; Harrington, R. F.; Jones, W. L.

1985-01-01

The NASA Langley Research Center analysis of the airborne microwave remote sensing measurements of Hurricane Allen obtained on August 5 and 8, 1980 is summarized. The instruments were the C-band stepped frequency microwave radiometer and the Ku-band airborne microwave scatterometer. They were carried aboard a NOAA aircraft making storm penetrations at an altitude of 3000 m and are sensitive to rain rate, surface wind speed, and surface wind vector. The wind speed is calculated from the increase in antenna brightness temperature above the estimated calm sea value. The rain rate is obtained from the difference between antenna temperature increases measured at two frequencies, and wind vector is determined from the sea surface normalized radar cross section measured at several azimuths. Comparison wind data were provided from the inertial navigation systems aboard both the C-130 aircraft at 3000 m and a second NOAA aircraft (a P-3) operating between 500 and 1500 m. Comparison rain rate data were obtained with a rain radar aboard the P-3. Evaluation of the surface winds obtained with the two microwave instruments was limited to comparisons with each other and with the flight level winds. Two important conclusions are drawn from these comparisons: (1) the radiometer is accurate when predicting flight level wind speeds and rain; and (2) the scatterometer produces well behaved and consistent wind vectors for the rain free periods.

Global Precipitation Measurement. Report 7; Bridging from TRMM to GPM to 3-Hourly Precipitation Estimates

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Smith, Eric A.; Adams, W. James (Editor)

2002-01-01

Historically, multi-decadal measurements of precipitation from surface-based rain gauges have been available over continents. However oceans remained largely unobserved prior to the beginning of the satellite era. Only after the launch of the first Defense Meteorological Satellite Program (DMSP) satellite in 1987 carrying a well-calibrated and multi-frequency passive microwave radiometer called Special Sensor Microwave/Imager (SSM/I) have systematic and accurate precipitation measurements over oceans become available on a regular basis; see Smith et al. (1994, 1998). Recognizing that satellite-based data are a foremost tool for measuring precipitation, NASA initiated a new research program to measure precipitation from space under its Mission to Planet Earth program in the 1990s. As a result, the Tropical Rainfall Measuring Mission (TRMM), a collaborative mission between NASA and NASDA, was launched in 1997 to measure tropical and subtropical rain. See Simpson et al. (1996) and Kummerow et al. (2000). Motivated by the success of TRMM, and recognizing the need for more comprehensive global precipitation measurements, NASA and NASDA have now planned a new mission, i.e., the Global Precipitation Measurement (GPM) mission. The primary goal of GPM is to extend TRMM's rainfall time series while making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This report addresses four fundamental questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively.

The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2017-02-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data are required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜ 575 km2) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental setup. The sensor performance in the experimental setup and the density of the PWS network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low-intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

Urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2017-04-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data is required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜575 km2}) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental set-up. The sensor performance in the experimental set-up and the density of the PWS-network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS-platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

Rain Impact Model Assessment of Near-Surface Salinity Stratification Following Rainfall

NASA Astrophysics Data System (ADS)

Drushka, K.; Jones, L.; Jacob, M. M.; Asher, W.; Santos-Garcia, A.

2016-12-01

Rainfall over oceans produces a layer of fresher surface water, which can have a significant effect on the exchanges between the surface and the bulk mixed layer and also on satellite/in-situ comparisons. For satellite sea surface salinity (SSS) measurements, the standard is the Hybrid Coordinate Ocean Model (HYCOM), but there is a significant difference between the remote sensing sampling depth of 0.01 m and the typical range of 5-10 m of in-situ instruments. Under normal conditions the upper layer of the ocean is well mixed and there is uniform salinity; however, under rainy conditions, there is a dilution of the near-surface salinity that mixes downward by diffusion and by mechanical mixing (gravity waves/wind speed). This significantly modifies the salinity gradient in the upper 1-2 m of the ocean, but these transient salinity stratifications dissipate in a few hours, and the upper layer becomes well mixed at a slightly fresher salinity. Based upon research conducted within the NASA/CONAE Aquarius/SAC-D mission, a rain impact model (RIM) was developed to estimate the change in SSS due to rainfall near the time of the satellite observation, with the objective to identify the probability of salinity stratification. RIM uses HYCOM (which does not include the short-term rain effects) and a NOAA global rainfall product CMORPH to model changes in the near-surface salinity profile in 0.5 h increments. Based upon SPURS-2 experimental near-surface salinity measurements with rain, this paper introduces a term in the RIM model that accounts for the effect of wind speed in the mechanical mixing, which translates into a dynamic vertical diffusivity; whereby a Generalized Ocean Turbulence Model (GOTM) is used to investigate the response to rain events of the upper few meters of the ocean. The objective is to determine how rain and wind forcing control the thickness, stratification strength, and lifetime of fresh lenses and to quantify the impacts of rain-formed fresh lenses on the fresh bias in satellite retrievals of salinity. Results will be presented of comparisons of RIM measurements at depth of a few meters with measurements from in-situ salinity instruments. Also, analytical results will be shown, which assess the accuracy of RIM salinity profiles under a variety of rain rate, wind/wave conditions.

A Sensitivity Analysis of the Impact of Rain on Regional and Global Sea-Air Fluxes of CO2

PubMed Central

Shutler, J. D.; Land, P. E.; Woolf, D. K.; Quartly, G. D.

2016-01-01

The global oceans are considered a major sink of atmospheric carbon dioxide (CO2). Rain is known to alter the physical and chemical conditions at the sea surface, and thus influence the transfer of CO2 between the ocean and atmosphere. It can influence gas exchange through enhanced gas transfer velocity, the direct export of carbon from the atmosphere to the ocean, by altering the sea skin temperature, and through surface layer dilution. However, to date, very few studies quantifying these effects on global net sea-air fluxes exist. Here, we include terms for the enhanced gas transfer velocity and the direct export of carbon in calculations of the global net sea-air fluxes, using a 7-year time series of monthly global climate quality satellite remote sensing observations, model and in-situ data. The use of a non-linear relationship between the effects of rain and wind significantly reduces the estimated impact of rain-induced surface turbulence on the rate of sea-air gas transfer, when compared to a linear relationship. Nevertheless, globally, the rain enhanced gas transfer and rain induced direct export increase the estimated annual oceanic integrated net sink of CO2 by up to 6%. Regionally, the variations can be larger, with rain increasing the estimated annual net sink in the Pacific Ocean by up to 15% and altering monthly net flux by > ± 50%. Based on these analyses, the impacts of rain should be included in the uncertainty analysis of studies that estimate net sea-air fluxes of CO2 as the rain can have a considerable impact, dependent upon the region and timescale. PMID:27673683

Optical heat flux gauge

DOEpatents

Noel, B.W.; Borella, H.M.; Cates, M.R.; Turley, W.D.; MacArthur, C.D.; Cala, G.C.

1991-04-09

A heat flux gauge is disclosed comprising first and second thermographic phosphor layers separated by a layer of a thermal insulator, wherein each thermographic layer comprises a plurality of respective thermographic sensors in a juxtaposed relationship with respect to each other. The gauge may be mounted on a surface with the first thermographic phosphor in contact with the surface. A light source is directed at the gauge, causing the phosphors to luminesce. The luminescence produced by the phosphors is collected and its spectra analyzed in order to determine the heat flux on the surface. First and second phosphor layers must be different materials to assure that the spectral lines collected will be distinguishable. 9 figures.

Optical heat flux gauge

DOEpatents

Noel, Bruce W.; Borella, Henry M.; Cates, Michael R.; Turley, W. Dale; MacArthur, Charles D.; Cala, Gregory C.

1991-01-01

A heat flux gauge comprising first and second thermographic phosphor layers separated by a layer of a thermal insulator, wherein each thermographic layer comprises a plurality of respective thermographic sensors in a juxtaposed relationship with respect to each other. The gauge may be mounted on a surface with the first thermographic phosphor in contact with the surface. A light source is directed at the gauge, causing the phosphors to luminesce. The luminescence produced by the phosphors is collected and its spectra analyzed in order to determine the heat flux on the surface. First and second phosphor layers must be different materials to assure that the spectral lines collected will be distinguishable.

Observations of C-Band Brightness Temperature and Ocean Surface Wind Speed and Rain Rate in Hurricanes Earl And Karl (2010)

NASA Technical Reports Server (NTRS)

Miller, Timothy; James, Mark; Roberts, Brent J.; Biswax, Sayak; Uhlhorn, Eric; Black, Peter; Linwood Jones, W.; Johnson, Jimmy; Farrar, Spencer; Sahawneh, Saleem

2012-01-01

Ocean surface emission is affected by: a) Sea surface temperature. b) Wind speed (foam fraction). c) Salinity After production of calibrated Tb fields, geophysical fields wind speed and rain rate (or column) are retrieved. HIRAD utilizes NASA Instrument Incubator Technology: a) Provides unique observations of sea surface wind, temp and rain b) Advances understanding & prediction of hurricane intensity c) Expands Stepped Frequency Microwave Radiometer capabilities d) Uses synthetic thinned array and RFI mitigation technology of Lightweight Rain Radiometer (NASA Instrument Incubator) Passive Microwave C-Band Radiometer with Freq: 4, 5, 6 & 6.6 GHz: a) Version 1: H-pol for ocean wind speed, b) Version 2: dual ]pol for ocean wind vectors. Performance Characteristics: a) Earth Incidence angle: 0deg - 60deg, b) Spatial Resolution: 2-5 km, c) Swath: approx.70 km for 20 km altitude. Observational Goals: WS 10 - >85 m/s RR 5 - > 100 mm/hr.

Application of the Nimbus 5 ESMR to rainfall detection over land surfaces

NASA Technical Reports Server (NTRS)

Meneely, J. M.

1975-01-01

The ability of the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) to detect rainfall over land surfaces was evaluated. The ESMR brightness temperatures (Tb sub B) were compared with rainfall reports from climatological stations for a limited number of rain events over portions of the U.S. The greatly varying emissivity of land surfaces precludes detection of actively raining areas. Theoretical calculations using a ten-layer atmospheric model showed this to be an expected result. Detection of rain which had fallen was deemed feasible over certain types of land surfaces by comparing the Tb sub B fields before and after the rain fell. This procedure is reliable only over relatively smooth terrain having a substantial fraction of bare soil, such as exists in major agricultural regions during the dormant or early growing seasons. Soil moisture budgets were computed at selected sites to show how the observed emissivity responded to changes in the moisture content of the upper soil zone.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE PAGES

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin; ...

2017-01-10

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Optical Extinction Measurements of Laser Side-Scatter During Tropical Storm Colin

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip; Michaelides, Silas

2017-01-01

A side-scatter imaging (SSI) technique using a 447 nm, 500 mW laser and a Nikon D80 camera was tested at Kennedy Space Center, Florida during the passing of a rain band associated with Tropical Storm Colin. The June 6, 2016, 22:00 GMT rain event was intense but short-lived owing to the strong west-to-east advection of the rain band. An effort to validate the optical extinction measurement was conducted by setting up a line of three tipping rain gauges along an 80 m east-west path and below the laser beam. Differences between tipping bucket measurements were correlated to the extinction coefficient profile along the lasers path, as determined by the SSI measurement. In order to compare the tipping bucket to the optical extinction data, a Marshall-Palmer DSD model was assumed. Since this was a daytime event, the laser beam was difficult to detect in the camera images, pointing out an important limitation of SSI measurements: the practical limit of DSD density that can be effectively detected and analyzed under daylight conditions using this laser and camera, corresponds to a fairly moderate rainfall rate on the order of 20 mmh (night measurements achieve a much improved sensitivity). The SSI analysis model under test produced promising results, but in order to use the SSI method for routine meteorological studies, improvements to the math model will be required.

Study of 1-min rain rate integration statistic in South Korea

NASA Astrophysics Data System (ADS)

Shrestha, Sujan; Choi, Dong-You

2017-03-01

The design of millimeter wave communication links and the study of propagation impairments at higher frequencies due to a hydrometeor, particularly rain, require the knowledge of 1-min. rainfall rate data. Signal attenuation in space communication results are due to absorption and scattering of radio wave energy. Radio wave attenuation due to rain depends on the relevance of a 1-min. integration time for the rain rate. However, in practice, securing these data over a wide range of areas is difficult. Long term precipitation data are readily available. However, there is a need for a 1-min. rainfall rate in the rain attenuation prediction models for a better estimation of the attenuation. In this paper, we classify and survey the prominent 1-min. rain rate models. Regression analysis was performed for the study of cumulative rainfall data measured experimentally for a decade in nine different regions in South Korea, with 93 different locations, using the experimental 1-min. rainfall accumulation. To visualize the 1-min. rainfall rate applicable for the whole region for 0.01% of the time, we have considered the variation in the rain rate for 40 stations across South Korea. The Kriging interpolation method was used for spatial interpolation of the rain rate values for 0.01% of the time into a regular grid to obtain a highly consistent and predictable rainfall variation. The rain rate exceeded the 1-min. interval that was measured through the rain gauge compared to the rainfall data estimated using the International Telecommunication Union Radio Communication Sector model (ITU-R P.837-6) along with the empirical methods as Segal, Burgueno et al., Chebil and Rahman, logarithmic, exponential and global coefficients, second and third order polynomial fits, and Model 1 for Icheon regions under the regional and average coefficient set. The ITU-R P. 837-6 exhibits a lower relative error percentage of 3.32% and 12.59% in the 5- and 10-min. to 1-min. conversion, whereas the higher error percentages of 24.64%, 46.44% and 58.46% for the 20-, 30- and 60-min. to 1-min., conversion were obtained in the Icheon region. The available experimental rainfall data were sampled on equiprobable rain-rate values where the application of these models to experimentally obtained data exhibits a variable error rate. This paper aims to provide a better survey of various conversion methods to model a 1-min. rain rate applicable to the South Korea regions with a suitable contour plot at 0.01% of the time.

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

The Role of Ecologists in Designing Rain Gardens: Enhancing Nitrate removal Performance

EPA Science Inventory

Rain gardens are vegetated surface depressions designed to receive stormwater runoff from roads, roofs, and parking lots. Stormwater infiltration through rain gardens’ sandy soils is intended to have both water quantity and quality benefits, through stream peak flow reduction and...

The role of ecologists in designing rain gardens: Enhancing nitrate removal performance

EPA Science Inventory

Rain gardens are vegetated surface depressions designed to receive stormwater runoff from roads, roofs, and parking lots. Stormwater infiltration through rain gardens’ sandy soils is intended to have both water quantity and quality benefits, through stream peak flow reduction an...

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

A Multi-Scale Analysis of Tropical Cyclogenesis Within the Critical Layer of Tropical Easterly Waves in the Atlantic and Western North Pacific Sectors

DTIC Science & Technology

2010-09-01

Electra Doppler Radar (ELDORA), dropwindsonde capability, a Doppler wind lidar , and the ability to collect flight-level data] flew aircraft research...ELDORA Electra Doppler Radar ECMWF European Center for Medium-range Weather Prediction Forecasts ER Equatorial Rossby ERA-40 ECMWF Reanalysis Data...2006) use Dual Doppler radar and rain gauge data to evaluate the performance of the TRMM TMI V6 rainfall algorithm. They 23 conclude that: “In

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

Convective climatology over the southwest U.S. and Mexico from passive microwave and infrared data

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Howard, Kenneth W.; Keehn, Peter R.; Maddox, Robert A.; Adler, Robert F.

1992-01-01

Passive microwave data from the Special Sensor Microwave Imager (SSM/I) were used to estimate the amount of rainfall in the June-August season for the regions of the southwest U.S. and Mexico, and the results are compared to rain-gauge observations and to IR climatologies of Maddox et al. (1992), using both the hourly IR data and IR data sampled at the time of the overpass of the SSM/I. A comparison of the microwave climatology with monthly rainfall measured by the climatological gage network over several states of western Mexico resulted in a 0.63 correlation and a large (482 mm) bias, due to sampling and the incongruity of rain gages and satellite estimates. A comparison between the IR and microwave data showed that the IR tended toward higher percentages along the coast compared to the microwave.

Spatial distribution of perchlorate, iodide and thiocyanate in the aquatic environment of Tianjin, China: environmental source analysis.

PubMed

Qin, Xiaolei; Zhang, Tao; Gan, Zhiwei; Sun, Hongwen

2014-09-01

Although China is the largest producer of fireworks (perchlorate-containing products) in the world, the pathways through which perchlorate enters the environment have not been characterized completely in this country. In this study, perchlorate, iodide and thiocyanate were measured in 101 water samples, including waste water, surface water, sea water and paired samples of rain water and surface runoff collected in Tianjin, China. The concentrations of the target anions were generally on the order of rain>surface water≈waste water treatment plant (WWTP) influent>WWTP effluent. High concentrations of perchlorate, iodide and thiocyanate were detected in rain samples, ranging from 0.35 to 27.3 (median: 4.05), 0.51 to 8.33 (2.92), and 1.31 to 107 (5.62) ngmL(-)(1), respectively. Furthermore, the concentrations of the target anions in rain samples were significantly (r=0.596-0.750, p<0.01) positively correlated with the concentrations obtained in the paired surface runoff samples. The anions tested showed a clear spatial distribution, and higher concentrations were observed in the upper reaches of rivers, sea waters near the coast, and rain-surface runoff pairs sampled in urban areas. Our results revealed that precipitation may act as an important source of perchlorate, iodide and thiocyanate in surface water. Moreover, iodide concentrations in the Haihe River and Dagu Drainage Canal showed a good correlation with an ideal marker (acesulfame) of domestic waste water, indicating that input from domestic waste water was an important source of iodide in the surface waters of Tianjin. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rain events decrease boreal peatland net CO2 uptake through reduced light availability.

PubMed

Nijp, Jelmer J; Limpens, Juul; Metselaar, Klaas; Peichl, Matthias; Nilsson, Mats B; van der Zee, Sjoerd E A T M; Berendse, Frank

2015-06-01

Boreal peatlands store large amounts of carbon, reflecting their important role in the global carbon cycle. The short-term exchange and the long-term storage of atmospheric carbon dioxide (CO2 ) in these ecosystems are closely associated with the permanently wet surface conditions and are susceptible to drought. Especially, the single most important peat forming plant genus, Sphagnum, depends heavily on surface wetness for its primary production. Changes in rainfall patterns are expected to affect surface wetness, but how this transient rewetting affects net ecosystem exchange of CO2 (NEE) remains unknown. This study explores how the timing and characteristics of rain events during photosynthetic active periods, that is daytime, affect peatland NEE and whether rain event associated changes in environmental conditions modify this response (e.g. water table, radiation, vapour pressure deficit, temperature). We analysed an 11-year time series of half-hourly eddy covariance and meteorological measurements from Degerö Stormyr, a boreal peatland in northern Sweden. Our results show that daytime rain events systematically decreased the sink strength of peatlands for atmospheric CO2 . The decrease was best explained by rain associated reduction in light, rather than by rain characteristics or drought length. An average daytime growing season rain event reduced net ecosystem CO2 uptake by 0.23-0.54 gC m(-2) . On an annual basis, this reduction of net CO2 uptake corresponds to 24% of the annual net CO2 uptake (NEE) of the study site, equivalent to a 4.4% reduction of gross primary production (GPP) during the growing season. We conclude that reduced light availability associated with rain events is more important in explaining the NEE response to rain events than rain characteristics and changes in water availability. This suggests that peatland CO2 uptake is highly sensitive to changes in cloud cover formation and to altered rainfall regimes, a process hitherto largely ignored. © 2015 John Wiley & Sons Ltd.

Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

NASA Astrophysics Data System (ADS)

Ho, Chung-Ru; Hsu, Po-Chun; Lin, Chen-Chih; Huang, Shih-Jen

2017-10-01

Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

Investigating the Seasonal and Diurnal Evolution of Fog and its Effect on the Hydrometeorological Regime in the Southern Appalachian Mountains Using a Mobile Observing Platform

NASA Astrophysics Data System (ADS)

Wilson, A. M.; Barros, A.

2015-12-01

Accurate, high resolution observations of fog and low clouds in regions of complex terrain are largely unavailable, due to a lack of existing in situ observations and obstacles to satellite observations such as ground clutter. For the past year, a mobile observing platform including a ground-based passive cavity aerosol spectrometer probe (PCASP-X2), an optical disdrometer (PARSIVEL-2), a tipping bucket rain gauge, and a Vaisala weather station, collocated with a Micro Rain Radar, has been recording observations in valley locations in the inner mountain region of the Southern Appalachian Mountains (SAM). In 2014, the SAM hosted a Global Precipitation Mission field campaign (the Integrated Precipitation and Hydrology Experiment), and during this experiment the platform was also collocated at various times with a microwave radiometer, W- and X- band radars, a Pluvio weighing rain gauge, a 2D video disdrometer, among other instruments. These observations will be discussed in the context of previous findings based on observations and model results (stochastic column model and the Advanced Research Weather and Forecasting Model (WRF)). Specifically, in previous work, seeder-feeder processes have been found to govern the enhancement of light rainfall in the SAM through increased coalescence efficiency in stratiform rainfall due to the interactions with low level clouds and topography modulated fog. This presentation will focus on measurements made by the platform and collocated instruments, as well as observations made by fog collectors on ridges, with the aim of developing a process-based understanding of the characteristics of low cloud and fog through describing the diurnal cycle of microphysical and dynamical processes and properties in the region. The overarching goal is to employ observations of the formation and evolution of the "feeder" clouds and fog to further understand the magnitude and function of their contribution to the local hydrometeorological regime.

Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.

2008-12-01

Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor class. Because the relative performance of the rain algorithms depends on the underlying surface terrain, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Relative to GV, AMSR-E and the TMI exhibited the highest correlation and skill over the full dynamic range of observed rain rates at both validation sites. The AMSU sensors, on the other hand, exhibited the lowest correlation and skill, though all sensors performed reasonably well compared to GV. The general tendency was for the microwave sensors to overestimate rain rates below 1 mm/hr where the sampling was highest and to underestimate the high rain rates above 10 mm/hr where the sampling was lowest. Underestimation of the low rain rate regime is attributed to difficulties of detecting and measuring low rain rates, while overestimation over the oceans was attributed largely to saturation of the brightness temperatures at high rain rates. Overall biases depended on the relative differences in the total rainfall at the extremes and the performance of each sensor at the nominal rain rates.

The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

NASA Astrophysics Data System (ADS)

Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

2015-04-01

In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national scale gridded rainfall product. Finally, radar rainfall data provided by the UK Met Office was assimilated, where available, to provide an optimal hourly estimate of rainfall, given the error variance associated with both datasets. This research introduces a sub-daily rainfall product that will be of particular value to hydrological modellers requiring rainfall inputs at higher temporal resolutions than those currently available nationally. Further research will aim to quantify the uncertainties in the rainfall product in order to improve our ability to diagnose and identify structural errors in hydrological modelling of extreme events. Here we present our initial findings.

Coastal and rain-induced wind variability depicted by scatterometers

NASA Astrophysics Data System (ADS)

Portabella, M.; Lin, W.; Stoffelen, A.; Turiel, A.; Verhoef, A.; Verspeek, J.; Ballabrera, J.; Vogelzang, J.

2012-04-01

A detailed knowledge of local wind variability near the shore is very important since it strongly affects the weather and microclimate in coastal regions. Since coastal areas are densely populated and most activity at sea occurs near the shore, sea-surface wind field information is important for a number of applications. In the vicinity of land sea-breeze, wave fetch, katabatic and current effects are more likely than in the open ocean, thus enhancing air-sea interaction. Also very relevant for air-sea interaction are the rain-induced phenomena, such as downbursts and convergence. Relatively cold and dry air is effectively transported to the ocean surface and surface winds are enhanced. In general, both coastal and rain-induced wind variability are poorly resolved by Numerical Weather Prediction (NWP) models. Satellite real aperture radars (i.e., scatterometers) are known to provide accurate mesoscale (25-50 km resolution) sea surface wind field information used in a wide variety of applications. Nowadays, there are two operating scatterometers in orbit, i.e., the C-band Advanced Scatterometer (ASCAT) onboard Metop-A and the Ku-band scatterometer (OSCAT) onboard Oceansat-2. The EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) delivers several ASCAT level 2 wind products with 25 km and 12.5 km Wind Vector Cell (WVC) spacing, including a pre-operational coastal wind product as well as an OSCAT level 2 wind product with 50 km spacing in development status. Rain is known to both attenuate and scatter the microwave signal. In addition, there is a "splashing" effect. The roughness of the sea surface is increased because of splashing due to rain drops. The so-called "rain contamination" is larger for Ku-band scatterometer systems than for C-band systems. Moreover, the associated downdrafts lead to variable wind speeds and directions, further complicating the wind retrieval. The C-band ASCAT high resolution wind processing is validated under rainy conditions, using collocations with the Tropical Rainfall Measuring Mission's (TRMM) Microwave Imager (TMI) rain data, and the tropical moored buoy wind and precipitation data. It turns out that the effect of low and moderate rain appears mainly in increasing the wind variability near the surface and, unlike for Ku-band scatterometers, the rain rate itself does not appear clearly as a limiting factor in ASCAT wind quality. Moreover, the downburst patterns as observed by ASCAT are unique and have large implications for air-sea exchange. At the conference, the main progress in scatterometer wind data processing will be shown.

Dry spell, onset and cessation of the wet season rainfall in the Upper Baro-Akobo Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Kebede, Asfaw; Diekkrüger, Bernd; Edossa, Desalegn C.

2017-08-01

In this study, maximum dry spell length and number of dry spell periods of rainy seasons in the upper Baro-Akobo River basin which is a part of the Nile basin, Western Ethiopia, were investigated to analyse the drought trend. Daily rainfall records of the period 1972-2000 from eight rain gauge stations were used in the analysis, and Mann-Kendall test was used to test trends for significance. Furthermore, the beginning and end of the trend development in the dry spell were also tested using the sequential version of Mann-Kendall test. Results have shown that there is neither clear monotonic trend found in dry spell for the basin nor significant fluctuation in the onset, cession and duration of rainfall in the Baro-Akobo river basin. This sufficiently explains why rain-fed agriculture has suffered little in the western part of Ethiopia. The predictable nature of dry spell pattern may have allowed farmers to adjust to rainfall variability in the basin. Unlike many parts of Ethiopia, the Baro-Akobo basin climate variability is not a limiting factor for rain-fed agriculture productivity which may contribute significantly to national food security.

The Weekend Effect for Precipitation Over Eastern U.S.: Evidence for Midweek Storm Intensification by Pollution

NASA Technical Reports Server (NTRS)

Bell, Thomas

2007-01-01

Every week the U.S. population carries out a climate-change experiment by varying their activities with the day of the week. It is well documented that pollution levels vary on a weekly basis. Particulate aerosol pollution is generally a maximum in the middle of the week and a minimum on weekends. It is also well known that aerosols can affect precipitation, although whether they suppress or enhance storm development depends on many factors. The Tropical Rainfall Measuring Mission (TRMM) satellite has provided evidence that rain statistics change with the day of the week over the southeast U.S. and neighboring waters during the summer months (JJA) of 1998-2005. There is a midweek increase in both rain area and intensity over land, and a midweek decrease over the nearby Atlantic and perhaps the Gulf of Mexico. Statistical tests suggest that the weekly variations are very unlikely to be due to the random behavior of weather. We will discuss the TRMM evidence. Wind data from model reanalysis, rain-gauge data, and TRMM radar data all appear to be consistent with the picture that aerosols are causing summertime storms to grow more vigorously and to produce more rainfall.

Raindrop and flow interactions for interrill erosion with wind-driven rain

USDA-ARS?s Scientific Manuscript database

Wind-driven rain (WDR) experiments were conducted to evaluate interrill component of the Water Erosion Prediction Project (WEPP) model with two-dimensional experimental set-up in wind tunnel. Synchronized wind and rain simulations were applied to soil surfaces on windward and leeward slopes of 7, 15...

Coupling Stable Water Isotopes in Vapor and Precipitation to Raindrop Size Distributions at a Mid-latitude Tall-tower Site to Evaluate the Role of Rain Evaporation in Boundary Layer Moisture Recycling

NASA Astrophysics Data System (ADS)

Kaushik, A.; Noone, D.

2016-12-01

The continental boundary layer moisture balance plays an important role in regulating water and energy exchange between the surface and the atmosphere, yet the mechanisms associated with moistening and drying are both poorly observed and modeled. Stable water isotope ratio measurements can provide insights into air mass origins, convection dynamics and mechanisms dominating atmosphere-land surface water fluxes. Profiles can be exploited to improve estimates of boundary layer moistening associated with evaporation of falling precipitation and contributions from surface evapotranspiration. We present two years of in situ tower-based measurements of isotope ratios of water vapor and precipitation (δD and δ18O) and raindrop size distributions from the Boulder Atmospheric Observatory (BAO) tall-tower site in Erie, Colorado. Isotope vapor measurements were made at 1 Hz with a full cycle from the surface to 300 meters recorded every 80 minutes. At the surface and 300m, water samples were collected during precipitation events and raindrop sizes were measured continuously using Parsivel instruments. We use this unique suite of measurements and, in particular, exploit the differences between the surface and 300m observations to constrain the surface layer hydrological mass balance during and after rain events, and evaluate parameterization choices for rain evaporation and moisture recycling in current isotope-enabled climate models. Aggregate raindrop size measurements showed shifts from populations of smaller raindrops at 300m to larger raindrops at the surface, contrary to what is expected for rain evaporation. Convective storms resulted in more uniform signatures between the surface and 300m, as well as longer isotope equilibration and adjustment time scales, whereas low Dexcess signatures (<9 to negative) during stratiform drizzle events were indicative of a greater degree of rain evaporation. Our observational results suggest that water vapor-rain equilibration is rarely achieved, and modification of the kinetic fractionation factor is necessary to better capture drop-size related isotope changes. This has implications not only for refining current global climate models, but also for interpreting proxy records connected to rainfall signatures that aid in understanding past hydrology.

Evaluation of Improvements to the TRMM Microwave Rain Algorithm

NASA Technical Reports Server (NTRS)

Yang, Song; Olson, Williams S.; Smith, Eric A.; Kummerow, Christian

2002-01-01

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.

Reproducing an extreme flood with uncertain post-event information

NASA Astrophysics Data System (ADS)

Fuentes-Andino, Diana; Beven, Keith; Halldin, Sven; Xu, Chong-Yu; Reynolds, José Eduardo; Di Baldassarre, Giuliano

2017-07-01

Studies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Post-event data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum-Cunge-Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90 % of the observed high-water marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e.g. from radar data or a denser rain-gauge network. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as they become available.

Nuclear Gauges Used in Road Construction | RadTown USA ...

EPA Pesticide Factsheets

2017-08-07

Nuclear gauges use radioactive sources to measure the thickness, density or make-up of a wide variety of materials and surfaces. When properly used, nuclear gauges will not expose the public to radiation. Nuclear gauges must be used safely and disposed of properly.

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

Close-range radar rainfall estimation and error analysis

NASA Astrophysics Data System (ADS)

van de Beek, C. Z.; Leijnse, H.; Hazenberg, P.; Uijlenhoet, R.

2016-08-01

Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are (1) radar calibration, (2) ground clutter, (3) wet-radome attenuation, (4) rain-induced attenuation, (5) vertical variability in rain drop size distribution (DSD), (6) non-uniform beam filling and (7) variations in DSD. This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1-2 km), where (4), (5) and (6) only play a minor role. Other important errors exist, like beam blockage, WLAN interferences and hail contamination and are briefly mentioned, but not considered in the analysis. A 3-day rainfall event (25-27 August 2010) that produced more than 50 mm of precipitation in De Bilt, the Netherlands, is analyzed using radar, rain gauge and disdrometer data. Without any correction, it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet-radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z-R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall-Palmer Z-R relation. Correcting for all of these effects has a large positive impact on the radar-derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5-8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.

High-resolution space-time characterization of convective rain cells: implications on spatial aggregation and temporal sampling operated by coarser resolution instruments

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2017-04-01

Forecasting the occurrence of flash floods and debris flows is fundamental to save lives and protect infrastructures and properties. These natural hazards are generated by high-intensity convective storms, on space-time scales that cannot be properly monitored by conventional instrumentation. Consequently, a number of early-warning systems are nowadays based on remote sensing precipitation observations, e.g. from weather radars or satellites, that proved effective in a wide range of situations. However, the uncertainty affecting rainfall estimates represents an important issue undermining the operational use of early-warning systems. The uncertainty related to remote sensing estimates results from (a) an instrumental component, intrinsic of the measurement operation, and (b) a discretization component, caused by the discretization of the continuous rainfall process. Improved understanding on these sources of uncertainty will provide crucial information to modelers and decision makers. This study aims at advancing knowledge on the (b) discretization component. To do so, we take advantage of an extremely-high resolution X-Band weather radar (60 m, 1 min) recently installed in the Eastern Mediterranean. The instrument monitors a semiarid to arid transition area also covered by an accurate C-Band weather radar and by a relatively sparse rain gauge network ( 1 gauge/ 450 km2). Radar quantitative precipitation estimation includes corrections reducing the errors due to ground echoes, orographic beam blockage and attenuation of the signal in heavy rain. Intense, convection-rich, flooding events recently occurred in the area serve as study cases. We (i) describe with very high detail the spatiotemporal characteristics of the convective cores, and (ii) quantify the uncertainty due to spatial aggregation (spatial discretization) and temporal sampling (temporal discretization) operated by coarser resolution remote sensing instruments. We show that instantaneous rain intensity decreases very steeply with the distance from the core of convection with intensity observed at 1 km (2 km) being 10-40% (1-20%) of the core value. The use of coarser temporal resolutions leads to gaps in the observed rainfall and even relatively high resolutions (5 min) can be affected by the problem. We conclude providing to the final user indications about the effects of the discretization component of estimation uncertainty and suggesting viable ways to decrease them.

Precipitation Discrimination from Satellite Infrared Temperatures over the CCOPE Mesonet Region.

NASA Astrophysics Data System (ADS)

Weiss, Mitchell; Smith, Eric A.

1987-06-01

A quantitative investigation of the relationship between satellite-derived cloud-top temperature parameters and the detection of intense convective rainfall is described. The area of study is that of the Cooperative Convective Precipitation Experiment (CCOPE), which was held near Miles City, Montana during the summer of 1981. Cloud-top temperatures, derived from the GOES-West operational satellite, were used to calculate a variety of parameters for objectively quantifying the convective intensity of a storm. A dense network of rainfall provided verification of surface rainfall. The cloud-top temperature field and surface rainfall data were processed into equally sized grid domains in order to best depict the individual samples of instantaneous precipitation.The technique of statistical discriminant analysis was used to determine which combinations of cloud-top temperature parameters best classify rain versus no-rain occurrence using three different rain-rate cutoffs: 1, 4, and 10 mm h1. Time lags within the 30 min rainfall verification were tested to determine the optimum time delay associated with rainfall reaching the ground.A total of six storm cases were used to develop and test the statistical models. Discrimination of rain events was found to be most accurate when using a 10 mm h1 rain-rate cutoff. Use parameters designated as coldest cloud-top temperature, the spatial mean of coldest cloud-top temperature, and change over time of mean coldest cloud-top temperature were found to be the best classifiers of rainfall in this study. Combining both a 10-min time lag (in terms of surface verification) with a 10 mm h1 rain-rate threshold resulted in classifying over 60% of all rain and no-rain cases correctly.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

A field evaluation of a satellite microwave rainfall sensor network

NASA Astrophysics Data System (ADS)

Caridi, Andrea; Caviglia, Daniele D.; Colli, Matteo; Delucchi, Alessandro; Federici, Bianca; Lanza, Luca G.; Pastorino, Matteo; Randazzo, Andrea; Sguerso, Domenico

2017-04-01

An innovative environmental monitoring system - Smart Rainfall System (SRS) - that estimates rainfall in real-time by means of the analysis of the attenuation of satellite signals (DVB-S in the microwave Ku band) is presented. Such a system consists in a set of peripheral microwave sensors placed on the field of interest, and connected to a central processing and analysis node. It has been developed jointly by the University of Genoa, with its departments DITEN and DICCA and the Genoese SME "Darts Engineering Srl". This work discusses the rainfall intensity measurements accuracy and sensitivity performance of SRS, based on preliminary results from a field comparison experiment at the urban scale. The test-bed is composed by a set of preliminary measurement sites established from Autumn 2016 in the Genoa (Italy) municipality and the data collected from the sensors during a selection of rainfall events is studied. The availability of point-scale rainfall intensity measurements made by traditional tipping-bucket rain gauges and radar areal observations allows a comparative analysis of the SRS performance. The calibration of the reference rain gauges has been carried out at the laboratories of DICCA using a rainfall simulator and the measurements have been processed taking advantage of advanced algorithms to reduce counting errors. The experimental set-up allows a fine tuning of the retrieval algorithm and a full characterization of the accuracy of the rainfall intensity estimates from the microwave signal attenuation as a function of different precipitation regimes.

Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

2017-12-01

The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

Miniature high temperature plug-type heat flux gauges

NASA Technical Reports Server (NTRS)

Liebert, Curt H.

1992-01-01

The objective is to describe continuing efforts to develop methods for measuring surface heat flux, gauge active surface temperature, and heat transfer coefficient quantities. The methodology involves inventing a procedure for fabricating improved plug-type heat flux gauges and also for formulating inverse heat conduction models and calculation procedures. These models and procedures are required for making indirect measurements of these quantities from direct temperature measurements at gauge interior locations. Measurements of these quantities were made in a turbine blade thermal cycling tester (TBT) located at MSFC. The TBT partially simulates the turbopump turbine environment in the Space Shuttle Main Engine. After the TBT test, experiments were performed in an arc lamp to analyze gauge quality.

Observations of near-surface fresh layers during SPURS-2

NASA Astrophysics Data System (ADS)

Drushka, Kyla; E Asher, William; Thompson, Elizabeth; Jessup, Andrew T.; Clark, Dan

2017-04-01

One of the primary objectives of the ongoing SPURS-2 program is to understand the fate of rainfall deposited on the sea surface. Rain produces stable near-surface fresh layers that persist for O(1-10) hours. The depth, strength, and lifetime of surface fresh layers are known to be related to the local rain and wind conditions, but available observational data are too sparse to allow definitive quantification of cause-and-effect relationships. In this paper, the formation and evolution of rain-formed fresh layers are examined using observations of near-surface salinity made during the 2016 SPURS-2 field experiment, which took place in the Intertropical Convergence Zone of the eastern tropical Pacific Ocean in August-September 2016. During 2016 SPURS-2, over 30 rain events were captured with the Surface Salinity Profiler (SSP), a towed platform that measures salinity and temperature at five discrete depths in the upper meter of the ocean. Differences in salinity measured by the SSP at depths of 0.02 m and at 1 m are correlated with local meteorological conditions. The field results show that the salinity difference increases linearly with rain rate, a result that is consistent with calculations done with a one-dimensional ocean turbulence model. The field data also demonstrate that there is an inverse correlation between wind speed and the vertical salinity difference, which is also consistent with numerical models. The implications of these results are discussed in the context of satellite salinity observations and the representation of rainfall events in climate models.

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

NASA Technical Reports Server (NTRS)

Jacob, Maria Marta; Salemirad, Matin; Jones, W. Linwood; Biswas, Sayak; Cecil, Daniel

2015-01-01

The NASA Hurricane and Severe Storm Sentinel (HS3) mission is an aircraft field measurements program using NASA's unmanned Global Hawk aircraft system for remote sensing and in situ observations of Atlantic and Caribbean Sea hurricanes. One of the principal microwave instruments is the Hurricane Imaging Radiometer (HIRAD), which measures surface wind speeds and rain rates. For validation of the HIRAD wind speed measurement in hurricanes, there exists a comprehensive set of comparisons with the Stepped Frequency Microwave Radiometer (SFMR) with in situ GPS dropwindsondes [1]. However, for rain rate measurements, there are only indirect correlations with rain imagery from other HS3 remote sensors (e.g., the dual-frequency Ka- & Ku-band doppler radar, HIWRAP), which is only qualitative in nature. However, this paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when HIRAD flew over an intense tropical squall line that was simultaneously observed by the Tampa NEXRAD meteorological radar (Fig. 1). During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. Using the well-documented NEXRAD Z-R relationship, 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. A preliminary comparison of HIRAD rain rate retrievals (image) for the first pass and the corresponding closest NEXRAD rain image is presented in Fig. 2 & 3. This paper describes the HIRAD instrument, which 1D synthetic-aperture thinned array radiometer (STAR) developed by NASA Marshall Space Flight Center [2]. The rain rate retrieval algorithm, developed by Amarin et al. [3], is based on the maximum likelihood estimation (MLE) technique, which compares the observed Tb's at the HIRAD operating frequencies of 4, 5, 6 and 6.6 GHz with corresponding theoretical Tb values from a forward radiative transfer model (RTM). The optimum solution is the integrated rain rate that minimizes the difference between RTM and observed values. Because the excess Tb from rain comes from the direct upwelling and the indirect reflected downwelling paths through the atmosphere, there are several assumptions made for the 2D rain distribution in the antenna incident plane (crosstrack to flight direction). The opportunity to knowing 2D rain surface truth from NEXRAD at two different altitudes will enable a comprehensive evaluation to be preformed and reported in this paper.

EFFECT OF AN ACID RAIN ENVIRONMENT ON LIMESTONE SURFACES.

USGS Publications Warehouse

Mossotti, Victor G.; Lindsay, James R.; Hochella, Michael F.

1987-01-01

Salem limestone samples were exposed to weathering for 1 y in several urban and one rural environments. Samples exposed in the rural location were chemically indistinguishable from the freshly quarried limestone, whereas all samples collected from urban exposure sites developed gypsum stains on the ground-facing surfaces where the stones were not washed by precipitation. The gas-solid reaction of SO//2 with calcite was selected for detailed consideration. It appears from the model that under arid conditions, the quantity of stain deposited on an unwashed surface is independent of atmospheric SO//2 concentration once the surface has been saturated with gypsum. Under wet conditions, surface sulfation and weight loss are probably dominated by mechanisms involving wet stone. However, if the rain events are frequent and delimited by periods of dryness, the quantity of gypsum produced by a gas-solid reaction mechanism should correlate with both the frequency of rain events and the atmospheric SO//2 level.

Wageningen Urban Rainfall Experiment 2014 (WURex14): Experimental setup and preliminary results

NASA Astrophysics Data System (ADS)

van Leth, Thomas C.; Uijlenhoet, Remko; Overeem, Aart; Leijnse, Hidde; Hazenberg, Pieter; Berne, Alexis

2016-04-01

Microwave links from cellular communication networks have been shown to be able to provide valuable information concerning the space-time variability of rainfall. In particular over urban areas, where network densities are generally high, they have the potential to complement existing dedicated infrastructure to measure rainfall (gauges, radars). In addition, microwave links provide a great opportunity for ground-based rainfall measurement for those land surface areas of the world where gauges and radars are generally lacking. Such information is not only crucial for water management and agriculture, but also for instance for ground validation of space-borne rainfall estimates such as those provided by the GPM (Global Precipitation Measurement) mission. WURex14 is dedicated to address several errors and uncertainties associated with such quantitative precipitation estimates in detail. The core of the experiment is provided by three co-located microwave links installed between two major buildings on the Wageningen University campus, approximately 2 km apart: a 38 GHz commercial microwave link, provided by T-Mobile NL, and 26 GHz and 38 GHz (dual-polarization) research microwave links from RAL. Transmitting and receiving antennas have been attached to masts installed on the roofs of the two buildings, about 30 m above the ground. This setup has been complemented with a Scintec infrared Large-Aperture Scintillometer, installed over the same path, as well as 5 Parsivel optical disdrometers and an automated rain gauge positioned at several locations along the path. Temporal sampling of the received signals was performed at a rate of 20 Hz. The setup is being monitored by time-lapse cameras to assess the state of the antennas as well as the atmosphere. Finally, data is available from the KNMI weather radars and an automated weather station situated just outside Wageningen. The experiment has been active between August 2014 and December 2015. We give a global overview of the preliminary results.

Projections of Declining Surface-Water Availability for the Southwestern United States

NASA Technical Reports Server (NTRS)

Seager, Richard; Ting, Mingfang; Li, Cuihua; Naik, Naomi; Cook, Benjamin; Nakamura, Jennifer; Liu, Haibo

2012-01-01

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1? by 1? one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P - E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, Min; Kollias, Pavlos; Feng, Zhe

The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification ismore » equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.« less

Understanding the formation and evolution of rain-formed fresh lenses at the ocean surface

NASA Astrophysics Data System (ADS)

Drushka, Kyla; Asher, William E.; Ward, Brian; Walesby, Kieran

2016-04-01

Rain falling on the ocean produces a layer of buoyant fresher surface water, or "fresh lens." Fresh lenses can have significant impacts on satellite-in situ salinity comparisons and on exchanges between the surface and the bulk mixed layer. However, because these are small, transient features, relatively few observations of fresh lenses have been made. Here the Generalized Ocean Turbulence Model (GOTM) is used to explore the response of the upper few meters of the ocean to rain events. Comparisons with observations from several platforms demonstrate that GOTM can reproduce the main characteristics of rain-formed fresh lenses. Idealized sensitivity tests show that the near-surface vertical salinity gradient within fresh lenses has a linear dependence on rain rate and an inverse dependence on wind speed. Yearlong simulations forced with satellite rainfall and reanalysis atmospheric parameters demonstrate that the mean salinity difference between 0.01 and 5 m, equivalent to the measurement depths of satellite radiometers and Argo floats, is -0.04 psu when averaged over the 20°S-20°N tropical band. However, when averaged regionally, the mean vertical salinity difference exceeds -0.15 psu in the Indo-Pacific warm pool, in the Pacific and Atlantic intertropical convergence zone, and in the South Pacific convergence zone. In most of these regions, salinities measured by the Aquarius satellite instrument have a fresh bias relative to Argo measurements at 5 m depth. These results demonstrate that the fresh bias in Aquarius salinities in rainy, low-wind regions may be caused by the presence of rain-produced fresh lenses.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations.

PubMed

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations

PubMed Central

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture. PMID:27003834

Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

NASA Astrophysics Data System (ADS)

Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several pollutant typologies. Different rainfall products are tested: 1) Block kriging of a single reliable rain gauge, 2) Block kriging product from a network of 13 rain gauges and, 3) Universal block kriging with 13 rain gauges and KNMI weather radar estimates as a covariate. Different temporal accumulation levels are compared ranging from 10min to 1h. A geostatistical approach is used to allocate the prediction of the rainfall input in each of the urban hydrological units composing the model. The change in model performance is then assessed by contrasting it with dissolved oxygen monitoring data in a series of events.

RCCM2-BATS model over tropical South America: Applications to tropical deforestation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hahmann, A.N.; Dickinson, R.E.

A multiyear simulation of the global climate uses a revised version of the National Center for Atmospheric Research (NCAR) Community Climate Model Version 2 (CCM2) coupled to the Biosphere-Atmosphere Transfer Scheme (BATS). It is compared with global and rain gauge precipitation climatologies to evaluate precipitation fields and European Centre for Medium-Range Forecasts analyses to evaluate the atmospheric circulation. The near-surface climate is compared with data from Amazonian field campaigns. The model simulation of the South American climate agrees closely with the observational record and is much improved from past simulations with previous versions of the NCAR Community Climate model overmore » this portion of the Tropics. The model is then used to study the local and regional response to tropical deforestation over Amazonia. In addition to the standard deforestation forcing, consisting mainly of increased albedo and decreased roughness length, two additional sensitivity experiments were conducted to assess the individual contributions from these forcings to the deforestation changes. The standard deforestation simulation shows slight increases in annually averaged surface temperature (+1{degrees}C) and reductions in annually averaged precipitation and evaporation (-363 and -149 mm yr{sup -1}, respectively). As expected, increases in surface albedo over Amazonia produce a reduction in net downward solar radiation at the surface and consequently a reduction in net surface radiation and surface latent heat flux. The roughness decrease, on the other hand, reduces the surface latent heat fluxes through decreases in the surface drag coefficient. The regional changes in moisture convergence and precipitation during the Amazonian wet season display a shift in the area of maximum precipitation rather than an overall decrease over the deforested area. 45 refs., 16 figs., 4 tabs.« less

Primordial anisotropies in gauged hybrid inflation

NASA Astrophysics Data System (ADS)

Akbar Abolhasani, Ali; Emami, Razieh; Firouzjahi, Hassan

2014-05-01

We study primordial anisotropies generated in the model of gauged hybrid inflation in which the complex waterfall field is charged under a U(1)gauge field. Primordial anisotropies are generated either actively during inflation or from inhomogeneities modulating the surface of end of inflation during waterfall transition. We present a consistent δN mechanism to calculate the anisotropic power spectrum and bispectrum. We show that the primordial anisotropies generated at the surface of end of inflation do not depend on the number of e-folds and therefore do not produce dangerously large anisotropies associated with the IR modes. Furthermore, one can find the parameter space that the anisotropies generated from the surface of end of inflation cancel the anisotropies generated during inflation, therefore relaxing the constrains on model parameters imposed from IR anisotropies. We also show that the gauge field fluctuations induce a red-tilted power spectrum so the averaged power spectrum from the gauge field can change the total power spectrum from blue to red. Therefore, hybrid inflation, once gauged under a U(1) field, can be consistent with the cosmological observations.

Experiment of Rain Retrieval over Land Using Surface Emissivity Map Derived from TRMM TMI and JRA25

NASA Astrophysics Data System (ADS)

Furuzawa, Fumie; Masunaga, Hirohiko; Nakamura, Kenji

2010-05-01

We are developing a data-set of global land surface emissivity calculated from TRMM TMI brightness temperature (TB) and atmospheric profile data of Japanese 25-year Reanalysis Project (JRA-25) for the region identified as no-rain by TRMM PR, assuming zero cloud liquid water beyond 0-C level. For the evaluation, some characteristics of global monthly emissivity maps, for example, dependency of emissivity on each TMI frequency or each local time or seasonal/annual variation are checked. Moreover, these data are classified based on JRA25 land type or soilwetness and compared. Histogram of polarization difference of emissivity is similar to that of TB and mostly reflects the variability of land type or soil wetness, while histogram of vertical emissivity show a small difference. Next, by interpolating this instantaneous dataset with Gaussian function weighting, we derive an emissivity over neighboring rainy region and assess the interpolated emissivity by running radiative transfer model using PR rain profile and comparing with observed TB. Preliminary rain retrieval from the emissivities for some frequencies and TBs is evaluated based on PR rain profile and TMI rain rate. Moreover, another method is tested to estimate surface temperature from two emissivities, based on their statistical relation for each land type. We will show the results for vertical and horizontal emissivities of each frequency.

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

NASA Astrophysics Data System (ADS)

Chen, Fengrui; Gao, Yongqi

2018-01-01

Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation. However, it is not known whether the precipitation trends derived from them are reliable. For the first time, we have evaluated the annual and seasonal precipitation trends from two typical sources of high-resolution satellite-gauge products, TRMM 3B43 and PERSIANN-CDR, using rain gauge observations over China, and they were also compared with those from gauge-only products (0.25° and 0.5° precipitation products, hereafter called CN25 and CN50). The evaluation focused mainly on the magnitude, significance, sign, and relative order of the precipitation trends, and was conducted at gridded and regional scales. The following results were obtained: (1) at the gridded scale, neither satellite-gauge products precisely measure the magnitude of precipitation trends but they do reproduce their sign and relative order; regarding capturing the significance of trends, they exhibit relatively acceptable performance only over regions with a sufficient amount of significant precipitation trends; (2) at the regional scale, both satellite-gauge products generally provide reliable precipitation trends, although they do not reproduce the magnitude of trends in winter precipitation; and (3) overall, CN50 and TRMM 3B43 outperform others in reproducing all four aspects of the precipitation trends. Compared with CN25, PERSIANN-CDR performs better in determining the magnitude of precipitation trends but marginally worse in reproducing their sign and relative order; moreover, both of them are at a level in capturing the significance of precipitation trends.

A Field Study of Pixel-Scale Variability of Raindrop Size Distribution in the MidAtlantic Region

NASA Technical Reports Server (NTRS)

Tokay, Ali; D'adderio, Leo Pio; Wolff, David P.; Petersen, Walter A.

2016-01-01

The spatial variability of parameters of the raindrop size distribution and its derivatives is investigated through a field study where collocated Particle Size and Velocity (Parsivel2) and two-dimensional video disdrometers were operated at six sites at Wallops Flight Facility, Virginia, from December 2013 to March 2014. The three-parameter exponential function was employed to determine the spatial variability across the study domain where the maximum separation distance was 2.3 km. The nugget parameter of the exponential function was set to 0.99 and the correlation distance d0 and shape parameter s0 were retrieved by minimizing the root-mean-square error, after fitting it to the correlations of physical parameters. Fits were very good for almost all 15 physical parameters. The retrieved d0 and s0 were about 4.5 km and 1.1, respectively, for rain rate (RR) when all 12 disdrometers were reporting rainfall with a rain-rate threshold of 0.1 mm h1 for 1-min averages. The d0 decreased noticeably when one or more disdrometers were required to report rain. The d0 was considerably different for a number of parameters (e.g., mass-weighted diameter) but was about the same for the other parameters (e.g., RR) when rainfall threshold was reset to 12 and 18 dBZ for Ka- and Ku-band reflectivity, respectively, following the expected Global Precipitation Measurement missions spaceborne radar minimum detectable signals. The reduction of the database through elimination of a site did not alter d0 as long as the fit was adequate. The correlations of 5-min rain accumulations were lower when disdrometer observations were simulated for a rain gauge at different bucket sizes.

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS): Timely Volunteer Precipitation Measurements to Supplement Existing Hydrometeorological Networks

NASA Astrophysics Data System (ADS)

Reges, H. W.; Doesken, N. J.; Cifelli, R. C.; Turner, J. S.

2005-12-01

The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) is a community-based, education-focused high density network of individual and family volunteers of all ages and backgrounds, who take daily measurements of rain, hail and snow at their homes, schools and businesses. Precipitation is measured using low-cost high capacity 4" diameter plastic rain gauges and Styrofoam wrapped in aluminum foil "hail pads". Thanks to the "low-tech/low-cost" approach, thousands of volunteers can afford to participate, giving the end user a large collection of data points that fill in gaps in many existing networks and data sets. Where feasible, CoCoRaHS is striving to achieve a station density approaching one observation per km-squared providing exceptional detail on cumulative storm precipitation over populated areas. These observations are collected and made available on the CoCoRaHS website: www.cocorahs.org in map and table format. The data are already being used daily by federal, state and community organizations and businesses for many resource management and hydrologic monitoring and predication applications. CoCoRaHS "Intense Rain Reports" and "Hail Reports" are used in "real time" by the National Weather Service in the issuing of flash flood warnings and severe thunderstorm warnings. While only providing once-daily and occasional event reports, CoCoRaHS does provide excellent observational consistency and accuracy including snowfall, depth and water content measurements, as well as the only comprehensive hail data currently being gathered in the U.S. The CoCoRaHS network currently engages over 2,000 volunteer observers in communities across six states, and the network continues to grow.

Acid rain research program. Annual progress report, September 1975--June 1976

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evans, L.S.; Raynor, G.S.

1976-09-01

The aims of the research program are: (a) to observe the minimum threshold dose of simulated acid rain to produce visual and histological effects on plant foliage, (b) approach threshold limits of simulated sulfate acid rain that affect plant growth and reproduction, and (c) to measure chemical and meteorological parameters of incident rain. Acute leaf injury to several plant species resulted from exposure of foliage to simulated sulfate acid rain of pH level 2.3 to 2.9. Only slight injury occurred at 3.1. Scanning electron micrographs showed that injury to upper leaf surfaces occurred mostly at the base of trichomes (leafmore » hairs) and near stomata. An association of lesion development near vascular tissue was also noted. Histologically, lesions are characterized by an initial collapse of the epidermis with eventual lysis and collapse of more internal leaf tissues on the upper leaf surface of pinto beans which complemented detailed descriptions of visual lesion development after daily exposures to simulated rain. Initial experiments with gametophytes of Pteridium aquilinum show that reproduction of this fern species is very sensitive to solutions of pH 5.2 while vegetative development is not affected at pH levels of 2.2. Initial rain samples from the sequential sampler have been obtained. Initial portions of rain events exhibit a pH near 3.0 in some cases. More complete chemical analyses are anticipated.« less

Rain Splash Dispersal of Gibberella zeae Within Wheat Canopies in Ohio.

PubMed

Paul, P A; El-Allaf, S M; Lipps, P E; Madden, L V

2004-12-01

ABSTRACT Rain splash dispersal of Gibberella zeae, causal agent of Fusarium head blight of wheat, was investigated in field studies in Ohio between 2001 and 2003. Samplers placed at 0, 30, and 100 cm above the soil surface were used to collect rain splash in wheat fields with maize residue on the surface and fields with G. zeae-infested maize kernels. Rain splash was collected during separate rain episodes throughout the wheat-growing seasons. Aliquots of splashed rain were transferred to petri dishes containing Komada's selective medium, and G. zeae was identified based on colony and spore morphology. Dispersed spores were measured in CFU/ml. Intensity of splashed rain was highest at 100 cm and ranged from 0.2 to 10.2 mm h(-1), depending on incident rain intensity and sampler height. Spores were recovered from splash samples at all heights in both locations for all sampled rain events. Both macroconidia and ascospores were found based on microscopic examination of random samples of splashed rain. Spore density and spore flux density per rain episode ranged from 0.4 to 40.9 CFU cm(-2) and 0.4 to 84.8 CFU cm(-2) h(-1), respectively. Spore flux density was higher in fields with G. zeae-infested maize kernels than in fields with maize debris, and generally was higher at 0 and 30 cm than at 100 cm at both locations. However, on average, spore flux density was only 30% lower at 100 cm (height of wheat spikes) than at the other heights. The log of spore flux density was linearly related to the log of splashed rain intensity and the log of incident rain intensity. The regression slopes were not significantly affected by year, location, height, and their interactions, but the intercepts were significantly affected by both sampler height and location. Thus, our results show that spores of G. zeae were consistently splash dispersed to spike heights within wheat canopies, and splashed rain intensity and spore flux density could be predicted based on incident rain intensity in order to estimate inoculum dispersal within the wheat canopy.

Inference of precipitation through thermal infrared measurements of soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, P. J.; Atlas, D.

1981-01-01

The physics of microwave radiative transfer is well understood so that causal models can be assembled which relate the observed brightness temperatures to assumed distributions of hydrometeors (both liquid and ice), non-precipitating clouds, water vapor oxygen, and surface conditions. Present models assume a Marshall Palmer size distribution of liquid hydrometers from the surface to the freezing level (near the 0 C isotherm) and a variable thickness of frozen hydrometeors above that with various reasonable distribution of the other relevant constituents. The validity of such models is discussed. All uncertainties in the rain rate retrieval algorithms can be expressed in terms of specific model uncertainties which can be addressed through appropriate measurements. Those factors which must be known to achieve umambiguous results can be identified so that rainfall measuring algorithms can be developed and improved. The emissivity of the underlying surface significantly affects the contrast that may be measured between areas covered by rain and those which are dry. Sensing strategies for measuring rain over the ocean and rain over land are reviewed.

TRMM Data from the Goddard Earth Sciences (GES) DISC DAAC: Tropical Rainfall Measuring Mission (TRMM)

NASA Technical Reports Server (NTRS)

2003-01-01

Tropical rainfall affects the lives and economies of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain systems. The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. Goddard Space Flight Center's involvement includes the observatory, four instruments, integration and testing of the observatory, data processing and distribution, and satellite operations. TRMM has a design lifetime of three years. It is currently in its fifth year of operation. Data generated from TRMM and archived at the GES DAAC are useful not only for hydrologists, atmospheric scientists, and climatologists, but also for the health community studying infectious diseases, the ocean research community, and the agricultural community.

Swarm slide - debris flow disaster induced by extreme rainfall in Hiroshima, August 2014 and lessons learnt in urban designing

NASA Astrophysics Data System (ADS)

Fukuoka, H.; Wang, C.

2015-12-01

Hiroshima city was hit by swarm debris flows along a narrow, and linear-shaped rain band of 2 km x 10 km which appeared in the early morning of August 20, 2014. Most of the flows were induced by shallow slide in the upstream. This disaster claimed 74 death, although this city experienced very similar disaster in 1999, claiming more than 30 residents lives. In the most severely affected debris flow torrent, more than 50 residents were killed. Most of the casualties arose in the wooden, vulnerable houses constructed in front of the exit of torrents. Points and lessons learnt from the disaster are as follows:1. Authors collected two types of sands from the source scar of the initial debris slides which induced debris flows. Tested by the ring shear apparatus under pore-pressure control condition, clear "Sliding surface liquefaction" was confirmed for both samples even under small normal stress, representing the small thickness of the slides. These results shows even instant excess pore pressure could initiate the slides and trigger slide-induced debris flow byundrained loading onto the torrent deposits.2. Apparently long-term land-use change since 1945 affected and raised the vulnerability of the community. Residential area had expanded into hill-slope (mountainous / semi-mountainous area) especially along the torrents. Those communities were developed on the past debris flow fan.3. As the devastated area is very close to downtown of Hiroshima city, it gave large societal impact to the Japanese citizens. After 1999 Hiroshima debris flow disaster, the Landslide disaster reduction law which intends to promote designation of landslide potential risk zones, was adopted in 2000. Immediately after 2014 disaster, national diet approved revision of the bill to promote rapid completion of the designation over the national territory. MLIT (Ministry of Land, Infrastructure, Tranportation and Tourism) decided to install X-band rain radars at more sites to cover whole city zones of the country. However, narrow extreme rain bands or spots which can not be detected effectively, often appear these years. It means more rain gauges conncted to the net should be implemented at upstreams of the communities facing torrent exits and on debris fan.

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

NASA Astrophysics Data System (ADS)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value < 10.34 mm over 5 days) and bias (median value < -14.44 %) during the evaluation period. The validation has been carried out at original resolution (0.25°) over Europe, Australia and five other areas worldwide to test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

Acid Thunder: Acid Rain and Ancient Mesoamerica

ERIC Educational Resources Information Center

Kahl, Jonathan D. W.; Berg, Craig A.

2006-01-01

Much of Mesoamerica's rich cultural heritage is slowly eroding because of acid rain. Just as water dissolves an Alka-Seltzer tablet, acid rain erodes the limestone surfaces of Mexican archaeological sites at a rate of about one-half millimeter per century (Bravo et al. 2003). A half-millimeter may not seem like much, but at this pace, a few…

Mapping the Extent and Magnitude of Sever Flooding Induced by Hurricane IRMA with Multi-Temporal SENTINEL-1 SAR and Insar Observations

NASA Astrophysics Data System (ADS)

Zhang, B.; Wdowinski, S.; Oliver-Cabrera, T.; Koirala, R.; Jo, M. J.; Osmanoglu, B.

2018-04-01

During Hurricane Irma's passage over Florida in September 2017, many sections of the state experienced heavy rain and sequent flooding. In order to drain water out of potential flooding zones and assess property damage, it is important to map the extent and magnitude of the flooded areas at various stages of the storm. We use Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) observations, acquired by Sentinel-1 before, during and after the hurricane passage, which enable us to evaluate surface condition during different stages of the hurricane. This study uses multi-temporal images acquired under dry condition before the hurricane to constrain the background backscattering signature. Flooded areas are detected when the backscattering during the hurricane is statistically significantly different from the average dry conditions. The detected changes can be either an increase or decrease of the backscattering, which depends on the scattering characteristics of the surface. In addition, water level change information in Palmdale, South Florida is extracted from an interferogram with the aid of a local water gauge as the reference. The results of our flooding analysis revealed that the majority of the study area in South Florida was flooded during Hurricane Irma.

Hydrology and hydraulics of Cypress Creek watershed, Texas during Hurricane Harvey and Impact of Potential Mitigation Measures.

NASA Astrophysics Data System (ADS)

El Hassan, A.; Fares, A.; Risch, E.

2017-12-01

Rain resulting from Hurricane Harvey stated to spread into Harris County late in August 25 and continued until August 31 2017. This high intensity rainfall caused catastrophic flooding across the Greater Houston Area and south Texas. The objectives of this study are to use the USACE Gridded Surface Subsurface Hydrologic Analysis model (GSSHA) to: i) simulate the hydrology and hydraulics of Cypress Creek watershed and quantify the impact of hurricane Harvey on it; and ii) test potential mitigation measures, e.g., construction of a third surface reservoir on the flooding and hydrology of this watershed. Cypress Creek watershed area is 733 km2. Simulations were conducted using precipitation from two sources a) the Multisensory Precipitation Estimator radar products (MPE) and Multi-Radar Multi-Sensor (MRMS) system. Streamflow was downloaded from the USGS gauge at the outlet of the watershed. The models performance using both precipitation data was very reasonable. The construction of an 8 m high embankment at the south central part of the watershed resulted in over 22% reduction of the peak flow of the stream and also reduction of the depth of inundation across the east part of the watershed. These and other mitigation scenarios will be further discussed in details during the presentation.

Two-Dimensional Laser-Speckle Surface-Strain Gauge

NASA Technical Reports Server (NTRS)

Barranger, John P.; Lant, Christian

1992-01-01

Extension of Yamaguchi's laser-speckle surface-strain-gauge method yields data on two-dimensional surface strains in times as short as fractions of second. Laser beams probe rough spot on surface of specimen before and after processing. Changes in speckle pattern of laser light reflected from spot indicative of changes in surface strains during processing. Used to monitor strains and changes in strains induced by hot-forming and subsequent cooling of steel.

Simulation of torrential rain as a means for assessment of surface runoff coefficients and calculation of recurrent design events in alpine catchments

NASA Astrophysics Data System (ADS)

Markart, Gerhard; Kohl, Bernhard; Sotier, Bernadette; Klebinder, Klaus; Schauer, Thomas; Bunza, Günther

2010-05-01

Simulation of heavy rain is an established method for studying infiltration characteristics, runoff and erosion behaviour in alpine catchments. Accordingly for characterization and differentiation of various runoff producing areas in alpine catchments transportable spray irrigation installations for large plots have been developed at the BFW, Department of Natural Hazards and Alpine Timberline, in Innsbruck, Austria. One installation has been designed for assessment of surface runoff coefficients under convective torrential rain with applicable precipitation intensities between 30 and 120 mm*h-1 and a plot size between 50 and 100 m2. The second device is used for simulation of persistent rain events (rain intensity about 10 mm*h-1, plot size: 400-1200 m2). Very reasonable results have been achieved during the comparison with spray irrigations from other institutions (e.g. Bavarian Environmental Agency in Munich) in the field. Rain simulations at BFW are mostly combined with comprehensive additional investigations on land-use, vegetation cover, soil physical characteristics, soil humidity, hydrogeology and other features of the test-sites. This allows proper interpretation of the achieved runoff data. At the moment results from more than 280 rain simulations are available from about 25 catchments / regions of the Eastern Alps at the BFW. Results show that the surface runoff coefficient, when runoff is constant at the test site (φconst) increases only slightly between rain intensities from 30 to 120 mm*h-1 (increment is 6%). Therefore φconst shall be used for assessment of runoff behaviour of runoff contributing areas, because it is less dependent form system conditions than φtot. BFW-data have been consolidated with results of the LfU (Bavarian Environmental Agency in Munich) in a data base and formed the basis for the development of a simple code of practice for assessment of surface runoff coefficients in torrential rain. The manual is freely available under: http://bfw.ac.at/rz/bfwcms.web?dok=4342 (in German language). The runoff contributing areas delineated by use of the manual in the field can be compiled in digital surface runoff coefficient maps and surface roughness maps. These maps in Austria form the basis for calculation of recurrent design events by use of precipitation/runoff models (P/R-models) like ZEMOKOST (optimized runtime method after Zeller = ZEller MOdified by KOhl and STepanek) or HEC-HMS. The result is substantial information on runoff disposition in each sub-catchment and hydrographs showing peak runoff and runoff freight. The code of practice for assessment of surface runoff coefficients has become the standard procedure in Austria to derive input parameters for P/R-models in practice. Recent investigations done at the Institute of Geography at the University of Berne show that the code of practice is suitable for application in catchments at the northern edge of the Swiss Alps too.

Geographically distributed environmental sensor system

DOEpatents

French, Patrick; Veatch, Brad; O'Connor, Mike

2006-10-03

The present invention is directed to a sensor network that includes a number of sensor units and a base unit. The base station operates in a network discovery mode (in which network topology information is collected) in a data polling mode (in which sensed information is collected from selected sensory units). Each of the sensor units can include a number of features, including an anemometer, a rain gauge, a compass, a GPS receiver, a barometric pressure sensor, an air temperature sensor, a humidity sensor, a level, and a radiant temperature sensor.

Novel Principle of Contactless Gauge Block Calibration

PubMed Central

Buchta, Zdeněk; Řeřucha, Šimon; Mikel, Břetislav; Čížek, Martin; Lazar, Josef; Číp, Ondřej

2012-01-01

In this paper, a novel principle of contactless gauge block calibration is presented. The principle of contactless gauge block calibration combines low-coherence interferometry and laser interferometry. An experimental setup combines Dowell interferometer and Michelson interferometer to ensure a gauge block length determination with direct traceability to the primary length standard. By monitoring both gauge block sides with a digital camera gauge block 3D surface measurements are possible too. The principle presented is protected by the Czech national patent No. 302948. PMID:22737012

Novel principle of contactless gauge block calibration.

PubMed

Buchta, Zdeněk; Reřucha, Simon; Mikel, Břetislav; Cížek, Martin; Lazar, Josef; Cíp, Ondřej

2012-01-01

In this paper, a novel principle of contactless gauge block calibration is presented. The principle of contactless gauge block calibration combines low-coherence interferometry and laser interferometry. An experimental setup combines Dowell interferometer and Michelson interferometer to ensure a gauge block length determination with direct traceability to the primary length standard. By monitoring both gauge block sides with a digital camera gauge block 3D surface measurements are possible too. The principle presented is protected by the Czech national patent No. 302948.

Carbon fluxes in an acid rain impacted boreal headwater catchment

NASA Astrophysics Data System (ADS)

Marx, Anne; Hintze, Simone; Jankovec, Jakub; Sanda, Martin; Dusek, Jaromir; Vogel, Tomas; van Geldern, Robert; Barth, Johannes A. C.

2016-04-01

Terrestrial carbon export via inland aquatic systems is a key process in the budget of the global carbon cycle. This includes loss of carbon to the atmosphere via gas evasion from rivers or reservoirs as well as carbon fixation in freshwater sediments. Headwater streams are the first endmembers of the transition of carbon between soils, groundwater and surface waters and the atmosphere. In order to quantify these processes the experimental catchment Uhlirska (1.78 km2) located in the northern Czech Republic was studied. Dissolved inorganic, dissolved organic and particulate organic carbon (DIC, DOC, POC) concentrations and isotopes were analyzed in ground-, soil -and stream waters between 2014 and 2015. In addition, carbon dioxide degassing was quantified via a stable isotope modelling approach. Results show a discharge-weighted total carbon export of 31.99 g C m-2 yr-1 of which CO2 degassing accounts 79 %. Carbon isotope ratios (δ13C) of DIC, DOC, and POC (in ‰ VPDB) ranged from -26.6 to -12.4 ‰ from -29.4 to -22.7 ‰ and from -30.6 to -26.6 ‰ respectively. The mean values for DIC are -21.8 ±3.8 ‰ -23.6 ±0.9 ‰ and -19.5 ±3.0 ‰ for soil, shallow ground and surface water compartments. For DOC, these compartments have mean values of -27.1 ±0.3 ‰ -27.0 ±0.8 ‰ and -27.4 ±0.7 ‰Ṁean POC value of shallow groundwaters and surface waters are -28.8 ±0.8 ‰ and -29.3 ±0.5 ‰ respectively. These isotope ranges indicate little turnover of organic material and predominant silicate weathering. The degassing of CO2 caused an enrichment of the δ13C-DIC values of up to 6.8 ‰ between a catchment gauge and the catchment outlet over a distance of 866 m. In addition, the Uhlirska catchment has only negligible natural sources of sulphate, yet SO42- accounts for 21 % of major stream water ions. This is most likely a remainder from acid rain impacts in the area.

Estimating relative sea-level rise and submergence potential at a coastal wetland

USGS Publications Warehouse

Cahoon, Donald R.

2015-01-01

A tide gauge records a combined signal of the vertical change (positive or negative) in the level of both the sea and the land to which the gauge is affixed; or relative sea-level change, which is typically referred to as relative sea-level rise (RSLR). Complicating this situation, coastal wetlands exhibit dynamic surface elevation change (both positive and negative), as revealed by surface elevation table (SET) measurements, that is not recorded at tide gauges. Because the usefulness of RSLR is in the ability to tie the change in sea level to the local topography, it is important that RSLR be calculated at a wetland that reflects these local dynamic surface elevation changes in order to better estimate wetland submergence potential. A rationale is described for calculating wetland RSLR (RSLRwet) by subtracting the SET wetland elevation change from the tide gauge RSLR. The calculation is possible because the SET and tide gauge independently measure vertical land motion in different portions of the substrate. For 89 wetlands where RSLRwet was evaluated, wetland elevation change differed significantly from zero for 80 % of them, indicating that RSLRwet at these wetlands differed from the local tide gauge RSLR. When compared to tide gauge RSLR, about 39 % of wetlands experienced an elevation rate surplus and 58 % an elevation rate deficit (i.e., sea level becoming lower and higher, respectively, relative to the wetland surface). These proportions were consistent across saltmarsh, mangrove, and freshwater wetland types. Comparison of wetland elevation change and RSLR is confounded by high levels of temporal and spatial variability, and would be improved by co-locating tide gauge and SET stations near each other and obtaining long-term records for both.

Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

NASA Astrophysics Data System (ADS)

Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

2017-09-01

In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7 can capture the annual mean of the absolute indices (the number of wet days in which daily precipitation > 10 mm, 20 mm) better than PERSIANN-CDR. The results of daily evaluations show that the similarity of Empirical Cumulative Density Function (ECDF) of satellite products and IRIMO gauges daily precipitation, as well as dry spells with different thresholds in some selected pixels (include at least five gauges), are significant. The results also indicate that ECDFs become more significant when threshold increases. In terms of regional analyses, the higher SNR of the products on monthly (based on the GTCH method) and daily evaluations (significant ECDFs) is mostly consistent.

Combined effects of simulated acid rain and lanthanum chloride on chloroplast structure and functional elements in rice.

PubMed

Hu, Huiqing; Wang, Lihong; Zhou, Qing; Huang, Xiaohua

2016-05-01

Acid rain and rare earth element (REE) pollution exist simultaneously in many agricultural regions. However, how REE pollution and acid rain affect plant growth in combination remains largely unknown. In this study, the combined effects of simulated acid rain and lanthanum chloride (LaCl3) on chloroplast morphology, chloroplast ultrastructure, functional element contents, chlorophyll content, and the net photosynthetic rate (P n) in rice (Oryza sativa) were investigated by simulating acid rain and rare earth pollution. Under the combined treatment of simulated acid rain at pH 4.5 and 0.08 mM LaCl3, the chloroplast membrane was smooth, proteins on this membrane were uniform, chloroplast structure was integrated, and the thylakoids were orderly arranged, and simulated acid rain and LaCl3 exhibited a mild antagonistic effect; the Mg, Ca, Mn contents, the chlorophyll content, and the P n increased under this combined treatment, with a synergistic effect of simulated acid rain and LaCl3. Under other combined treatments of simulated acid rain and LaCl3, the chloroplast membrane surface was uneven, a clear "hole" was observed on the surface of chloroplasts, and the thylakoids were dissolved and loose; and the P n and contents of functional elements (P, Mg, K, Ca, Mn, Fe, Ni, Cu, Zn and Mo) and chlorophyll decreased. Under these combined treatments, simulated acid rain and LaCl3 exhibited a synergistic effect. Based on the above results, a model of the combined effects of simulated acid rain and LaCl3 on plant photosynthesis was established in order to reveal the combined effects on plant photosynthesis, especially on the photosynthetic organelle-chloroplast. Our results would provide some references for further understanding the mechanism of the combined effects of simulated acid rain and LaCl3 on plant photosynthesis.

Assessing Applications of GPM and IMERG Passive Microwave Rain Rates in Modeling and Operational Forecasting

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Le Roy, A.; Smith, M. R.; Case, J.

2016-12-01

In support of NASA's recently launched GPM `core' satellite, the NASA-SPoRT project is leveraging experience in research-to-operations transitions and training to provide feedback on the operational utility of GPM products. Thus far, SPoRT has focused on evaluating the Level 2 GPROF passive microwave and IMERG rain rate estimates. Formal evaluations with end-users have occurred, as well as internal evaluations of the datasets. One set of end users for these products is National Weather Service Forecast Offices (WFOs) and National Weather Service River Forecast Centers (RFCs), comprising forecasters and hydrologists. SPoRT has hosted a series of formal assessments to determine uses and utility of these datasets for NWS operations at specific offices. Forecasters primarily have used Level 2 swath rain rates to observe rainfall in otherwise data-void regions and to confirm model QPF for their nowcasting or short-term forecasting. Hydrologists have been evaluating both the Level 2 rain rates and the IMERG rain rates, including rain rate accumulations derived from IMERG; hydrologists have used these data to supplement gauge data for post-event analysis as well as for longer-term forecasting. Results from specific evaluations will be presented. Another evaluation of the GPM passive microwave rain rates has been in using the data within other products that are currently transitioned to end-users, rather than as stand-alone observations. For example, IMERG Early data is being used as a forcing mechanism in the NASA Land Information System (LIS) for real-time soil moisture product over eastern Africa. IMERG is providing valuable precipitation information to LIS in an otherwise data-void region. Results and caveats will briefly be discussed. A third application of GPM data is using the IMERG Late and Final products for model verification in remote regions where high-quality gridded precipitation fields are not readily available. These datasets can now be used to verify NWP model forecasts over Eastern Africa using the SPoRT-MET scripts verification package, a wrapper around the NCAR Model Evaluation Toolkit (MET) verification software.

Rainfall Estimation over the Nile Basin using an Adapted Version of the SCaMPR Algorithm

NASA Astrophysics Data System (ADS)

Habib, E. H.; Kuligowski, R. J.; Elshamy, M. E.; Ali, M. A.; Haile, A.; Amin, D.; Eldin, A.

2011-12-01

Management of Egypt's Aswan High Dam is critical not only for flood control on the Nile but also for ensuring adequate water supplies for most of Egypt since rainfall is scarce over the vast majority of its land area. However, reservoir inflow is driven by rainfall over Sudan, Ethiopia, Uganda, and several other countries from which routine rain gauge data are sparse. Satellite-derived estimates of rainfall offer a much more detailed and timely set of data to form a basis for decisions on the operation of the dam. A single-channel infrared algorithm is currently in operational use at the Egyptian Nile Forecast Center (NFC). This study reports on the adaptation of a multi-spectral, multi-instrument satellite rainfall estimation algorithm (Self-Calibrating Multivariate Precipitation Retrieval, SCaMPR) for operational application over the Nile Basin. The algorithm uses a set of rainfall predictors from multi-spectral Infrared cloud top observations and self-calibrates them to a set of predictands from Microwave (MW) rain rate estimates. For application over the Nile Basin, the SCaMPR algorithm uses multiple satellite IR channels recently available to NFC from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Microwave rain rates are acquired from multiple sources such as SSM/I, SSMIS, AMSU, AMSR-E, and TMI. The algorithm has two main steps: rain/no-rain separation using discriminant analysis, and rain rate estimation using stepwise linear regression. We test two modes of algorithm calibration: real-time calibration with continuous updates of coefficients with newly coming MW rain rates, and calibration using static coefficients that are derived from IR-MW data from past observations. We also compare the SCaMPR algorithm to other global-scale satellite rainfall algorithms (e.g., 'Tropical Rainfall Measuring Mission (TRMM) and other sources' (TRMM-3B42) product, and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) CMORPH product. The algorithm has several potential future applications such as: improving the performance accuracy of hydrologic forecasting models over the Nile Basin, and utilizing the enhanced rainfall datasets and better-calibrated hydrologic models to assess the impacts of climate change on the region's water availability.

Precipitation Efficiency in the Tropical Deep Convective Regime

NASA Technical Reports Server (NTRS)

Li, Xiaofan; Sui, C.-H.; Lau, K.-M.; Lau, William K. M. (Technical Monitor)

2001-01-01

Precipitation efficiency in the tropical deep convective regime is analyzed based on a 2-D cloud resolving simulation. The cloud resolving model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. Precipitation efficiency may be defined as a ratio of surface rain rate to sum of surface evaporation and moisture convergence (LSPE) or a ratio of surface rain rate to sum of condensation and deposition rates of supersaturated vapor (CMPE). Moisture budget shows that the atmosphere is moistened (dryed) when the LSPE is less (more) than 100 %. The LSPE could be larger than 100 % for strong convection. This indicates that the drying processes should be included in cumulus parameterization to avoid moisture bias. Statistical analysis shows that the sum of the condensation and deposition rates is bout 80 % of the sum of the surface evaporation rate and moisture convergence, which ads to proportional relation between the two efficiencies when both efficiencies are less han 100 %. The CMPE increases with increasing mass-weighted mean temperature and creasing surface rain rate. This suggests that precipitation is more efficient for warm environment and strong convection. Approximate balance of rates among the condensation, deposition, rain, and the raindrop evaporation is used to derive an analytical solution of the CMPE.

Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

NASA Astrophysics Data System (ADS)

Chowdhury, S.; Sharma, A.

2005-12-01

Hydrological model inputs are often derived from measurements at point locations taken at discrete time steps. The nature of uncertainty associated with such inputs is thus a function of the quality and number of measurements available in time. A change in these characteristics (such as a change in the number of rain-gauge inputs used to derive spatially averaged rainfall) results in inhomogeneity in the associated distributional profile. Ignoring such uncertainty can lead to models that aim to simulate based on the observed input variable instead of the true measurement, resulting in a biased representation of the underlying system dynamics as well as an increase in both bias and the predictive uncertainty in simulations. This is especially true of cases where the nature of uncertainty likely in the future is significantly different to that in the past. Possible examples include situations where the accuracy of the catchment averaged rainfall has increased substantially due to an increase in the rain-gauge density, or accuracy of climatic observations (such as sea surface temperatures) increased due to the use of more accurate remote sensing technologies. We introduce here a method to ascertain the true value of parameters in the presence of additive uncertainty in model inputs. This method, known as SIMulation EXtrapolation (SIMEX, [Cook, 1994]) operates on the basis of an empirical relationship between parameters and the level of additive input noise (or uncertainty). The method starts with generating a series of alternate realisations of model inputs by artificially adding white noise in increasing multiples of the known error variance. The alternate realisations lead to alternate sets of parameters that are increasingly biased with respect to the truth due to the increased variability in the inputs. Once several such realisations have been drawn, one is able to formulate an empirical relationship between the parameter values and the level of additive noise present. SIMEX is based on theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. We illustrate the utility of SIMEX in a synthetic rainfall-runoff modelling scenario and an application to study the dependence of uncertain distributed sea surface temperature anomalies with an indicator of the El Nino Southern Oscillation, the Southern Oscillation Index (SOI). The errors in rainfall data and its affect is explored using Sacramento rainfall runoff model. The rainfall uncertainty is assumed to be multiplicative and temporally invariant. The model used to relate the sea surface temperature anomalies (SSTA) to the SOI is assumed to be of a linear form. The nature of uncertainty in the SSTA is additive and varies with time. The SIMEX framework allows assessment of the relationship between the error free inputs and response. Cook, J.R., Stefanski, L. A., Simulation-Extrapolation Estimation in Parametric Measurement Error Models, Journal of the American Statistical Association, 89 (428), 1314-1328, 1994.

Low-Latitude Ethane Rain on Titan

NASA Technical Reports Server (NTRS)

Dalba, Paul A.; Buratti, Bonnie J.; Brown, R. H.; Barnes, J. W.; Baines, K. H.; Sotin, C.; Clark, R. N.; Lawrence, K. J.; Nicholson, P. D.

2012-01-01

Cassini ISS observed multiple widespread changes in surface brightness in Titan's equatorial regions over the past three years. These brightness variations are attributed to rainfall from cloud systems that appear to form seasonally. Determining the composition of this rainfall is an important step in understanding the "methanological" cycle on Titan. I use data from Cassini VIMS to complete a spectroscopic investigation of multiple rain-wetted areas. I compute "before-and-after" spectral ratios of any areas that show either deposition or evaporation of rain. By comparing these spectral ratios to a model of liquid ethane, I find that the rain is most likely composed of liquid ethane. The spectrum of liquid ethane contains multiple absorption features that fall within the 2-micron and 5-micron spectral windows in Titan's atmosphere. I show that these features are visible in the spectra taken of Titan's surface and that they are characteristically different than those in the spectrum of liquid methane. Furthermore, just as ISS saw the surface brightness reverting to its original state after a period of time, I show that VIMS observations of later flybys show the surface composition in different stages of returning to its initial form.

Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

NASA Astrophysics Data System (ADS)

Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Araujo Abdalad, Mariana; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

2018-02-01

The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted.

Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wang, Li; Zhang, Fan; Zhang, Hongbo; Scott, Christopher A.; Zeng, Chen; Shi, Xiaonan

2018-01-01

Precipitation is one of the most critical inputs for models used to improve understanding of hydrological processes. In high mountain areas, it is challenging to generate a reliable precipitation data set capturing the spatial and temporal heterogeneity due to the harsh climate, extreme terrain and the lack of observations. This study conducts intensive observation of precipitation in the Mabengnong catchment in the southeast of the Tibetan Plateau during July to August 2013. Because precipitation is greatly influenced by altitude, the observed data are used to characterize the precipitation gradient (PG) and hourly distribution (HD), showing that the average PG is 0.10, 0.28 and 0.26 mm/d/100 m and the average duration is around 0.1, 0.8 and 5.2 h for trace, light and moderate rain, respectively. A distributed biosphere hydrological model based on water and energy budgets with improved physical process for snow (WEB-DHM-S) is applied to simulate the hydrological processes with gridded precipitation data derived from a lower altitude meteorological station and the PG and HD characterized for the study area. The observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are used for model calibration and validation. Runoff, SCA and LST simulations all show reasonable results. Sensitivity analyses illustrate that runoff is largely underestimated without considering PG, indicating that short-term intensive precipitation observation has the potential to greatly improve hydrological modelling of poorly gauged high mountain catchments.

Investigating the relationship between deforestation and changes in hydrology across the island of Hispaniola

NASA Astrophysics Data System (ADS)

Hakimdavar, R.

2013-05-01

Over recent decades, Haiti and the Dominican Republic have reported changes in reservoir water levels - while some areas have experienced increases others have seen decreasing trends, especially reservoirs located in the Dominican Republic - leading to, among other things, regional flooding and shortages in hydroelectricity output. We investigate whether extensive deforestation, particularly in the western part of Hispaniola - shared by the two nations - is driving these changes by affecting the regional water balance. Due to a lack of available spatiotemporal environmental data, remotely sensed vegetation and precipitation information is used along with estimated evapotranspiration rates to study regional hydro-climatologic fluctuations over three decades. Changes in vegetative cover, precipitation, and evapotranspiration across the island are investigated using 25 years of Normalized Difference Vegetation Index (NDVI) data, historical satellite and gauge precipitation records, and estimated surface temperature and solar radiation. NDVI values are derived from imagery obtained by NOAA's 8 km resolution AVHRR instrument. Monthly precipitation is collected from several different sources, including NASA and NOAA precipitation satellites, as well as local rain gauges. Evapotranspiration is estimated using an energy balance approach. Preliminary results indicate a general decrease in rainfall over the eastern part of the island during the past three decades, with little change observed across the western half. NDVI and precipitation anomalies across the island are not well correlated, suggesting that deforestation is likely not the cause of regional changes in precipitation. The results of this work hold potentially important implications for future land-use and water infrastructure planning for both nations.

Precipitation phase partitioning variability across the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.

2017-12-01

Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.

Improving a spatial rainfall product using a data-mining approach and its effect on the hydrological response of a meso-scale catchment.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.; Demirel, C.

2017-12-01

The spatial representation of rainfall is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the daily grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. The research is focused on the Skjern catchment (1,050 km2 western Jutland), where we can dispose of the complete rain-gauge database from the Danish Hydrological Observatory and compute the distributed hydrological response at the 1-km scale.To give a better estimation of the gridded rainfall input, we start from ground measurements by simulating the missing data with a stochastic data-mining approach, then we compute again the grid interpolation. To maximize the predictive power of the technique, combinations of station time-series that are the most informative to each other are selected on the basis of their correlation and available historical data. Then, the missing data inside these time-series are simulated together using the direct sampling technique (DS) [1, 2]. DS simulates a datum by sampling the historical record of the same stations where a similar data pattern occurs, preserving their complex statistical relation. The simulated data are reinjected in the whole dataset and used as well as conditioning data to progressively fill up the gaps in other stations.The results show that the proposed methodology, tested on the period 1995-2012, can increase the realism of the grid rainfall product by regenerating the missing ground measurements. The hydrological response is analyzed considering the observations at 5 hydrological stations. The presented methodology can be used in many regions to regenerate the missing data using the information contained in the historical record and propagate the uncertainty of the prediction to the hydrological response. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014.

Improving a spatial rainfall product using multiple-point geostatistical simulations and its effect on a national hydrological model.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.

2016-12-01

Rainfall amount is one of the most sensitive inputs to distributed hydrological models. Its spatial representation is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the 10-km-grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network in recent years (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. Consequently, the related hydrological model shows a significantly lower prediction power. To give a better estimation of spatial rainfall at the grid points far from ground measurements, we use the direct sampling technique (DS) [1], belonging to the family of multiple-point geostatistics. DS, already applied to rainfall and spatial variable estimation [2, 3], simulates a grid value by sampling a training data set where a similar data neighborhood occurs. In this way, complex statistical relations are preserved by generating similar spatial patterns to the ones found in the training data set. Using the reliable grid product from the period 1996-2006 as training data set, we first test the technique by simulating part of this data set, then we apply the technique to the grid product of the period 2007-2014, and subsequently analyzing the uncertainty propagation to the hydrological model. We show that DS can improve the reliability of the rainfall product by generating more realistic rainfall patterns, with a significant repercussion on the hydrological model. The reduction of rain gauge networks is a global phenomenon which has huge implications for hydrological model performance and the uncertainty assessment of water resources. Therefore, the presented methodology can potentially be used in many regions where historical records can act as training data. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014. [3] G. Mariethoz et al. (2012), Water Resour. Res., 10.1029/2012WR012115.

Remote Sensing and River Discharge Forecasting for Major Rivers in South Asia (Invited)

NASA Astrophysics Data System (ADS)

Webster, P. J.; Hopson, T. M.; Hirpa, F. A.; Brakenridge, G. R.; De-Groeve, T.; Shrestha, K.; Gebremichael, M.; Restrepo, P. J.

2013-12-01

The South Asia is a flashpoint for natural disasters particularly flooding of the Indus, Ganges, and Brahmaputra has profound societal impacts for the region and globally. The 2007 Brahmaputra floods affecting India and Bangladesh, the 2008 avulsion of the Kosi River in India, the 2010 flooding of the Indus River in Pakistan and the 2013 Uttarakhand exemplify disasters on scales almost inconceivable elsewhere. Their frequent occurrence of floods combined with large and rapidly growing populations, high levels of poverty and low resilience, exacerbate the impact of the hazards. Mitigation of these devastating hazards are compounded by limited flood forecast capability, lack of rain/gauge measuring stations and forecast use within and outside the country, and transboundary data sharing on natural hazards. Here, we demonstrate the utility of remotely-derived hydrologic and weather products in producing skillful flood forecasting information without reliance on vulnerable in situ data sources. Over the last decade a forecast system has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers in Bangldesh was developed (Hopson and Webster 2010). The system utilizes ECMWF weather forecast uncertainty information and ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates, together with the limited near-real-time river stage observations from Bangladesh. This system has been expanded to Pakistan and has successfully forecast the 2010-2012 flooding (Shrestha and Webster 2013). To overcome the in situ hydrological data problem, recent efforts in parallel with the numerical modeling have utilized microwave satellite remote sensing of river widths to generate operational discharge advective-based forecasts for the Ganges and Brahmaputra. More than twenty remotely locations upstream of Bangldesh were used to produce stand-alone river flow nowcasts and forecasts at 1-15 days lead time. showing that satellite-based flow estimates are a useful source of dynamical surface water information in data-scarce regions and that they could be used for model calibration and data assimilation purposes in near-time hydrologic forecast applications (Hirpa et al. 2013). More recent efforts during this year's monsoon season are optimally combining these different independent sources of river forecast information along with archived flood inundation imagery of the Dartmouth Flood Observatory to improve the visualization and overall skill of the ongoing CFAB ensemble weather forecast-based flood forecasting system within the unique context of the ongoing flood forecasting efforts for Bangladesh.

Improved Hurricane Boundary Layer Observations with the Imaging Wind and Rain Airborne Profiler

NASA Technical Reports Server (NTRS)

Esteban-Fernandez, Daniel; Changy, P.; Carswell, J.; Contreras, R.; Chu, T.

2006-01-01

During the NOAA/NESDIS 2005 Hurricane Season (HS2005) and the 2006 Winter Experiment, the University of Massachusetts (UMass) installed two instruments on the NOAA N42RF WP-3D research aircraft: the Imaging Wind and Rain Airborne Profiler (IWRAP) and the Simultaneous Frequency Microwave Radiometer (SFMR). IWRAP is a dual-band (C- and Ku), dual-polarized pencil-beam airborne radar that profiles the volume backscatter and Doppler velocity from rain and that also measures the ocean backscatter response. It simultaneously profiles along four separate incidence angles while conically scanning at 60 RPM. SFMR is a C-band nadir viewing radiometer that measures the emission from the ocean surface and intervening atmosphere simultaneously at six frequencies. It is designed to obtain the surface wind speed and the column average rain rate. Both instruments have previously been flown during the 2002, 2003 and 2004 hurricane seasons. For the HS2005, the IWRAP system was modified to implement a raw data acquisition system. The importance of the raw data system arises when trying to profile the atmosphere all the way down to the surface with a non-nadir looking radar system. With this particular geometry, problems arise mainly from the fact that both rain and ocean provide a return echo coincident in time through the antenna s main lobe. This paper shows how this limitation has been removed and presents initial results demonstrating its new capabilities to derive the atmospheric boundary layer (ABL) wind field within the inner core of hurricanes to much lower altitudes than the ones the original system was capable of, and to analyze the spectral response of the ocean backscatter and the rain under different wind and rain conditions.