scholarly journals AN EVALUATION ON CAPUTURE RATIO OF GOURND RAINGAUGE DATA BY A DEVELOPMENT OF THE 9 M2 HUGE RAIN-GAUGE

2013 ◽  
Vol 69 (4) ◽  
pp. I_307-I_312
Author(s):  
Kosei YAMAGUCHI ◽  
Eiichi NAKAKITA ◽  
Michinobu NONAKA
Keyword(s):  
Rain Gauge ◽  
Raingauge Data

scholarly journals Experiences in using the TRMM data to complement rain gauge data in the Ecuadorian coastal foothills

2012 ◽  
Vol 9 (11) ◽  
pp. 12435-12461 ◽  
Author(s):  
M. Arias-Hidalgo ◽  
B. Bhattacharya ◽  
A. E. Mynett ◽  
A. van Griensven
Keyword(s):  
River Basin ◽  
New Technologies ◽  
Model Performance ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Time Series ◽  
Rain Gauge Data ◽  
Monthly Data ◽  
Coarse Spatial Resolution ◽  
Raingauge Data

Abstract. Nowadays, new technologies are being used to expand the coverage of conventional meteorological datasets. An example of these is the TRMM data as long as one considers the bias, the type of rainfall and the current coarse spatial resolution. Although in the Guayas River Basin (Ecuadorian lowlands) the radar-based precipitation does not match the magnitude of the ground-based rainfall, at least it records somewhat the spatial pattern. The bias remains more or less steady when the temporal resolution increases from yearly to seasonal and monthly data. By means of an empirical disaggregation method, synthetic daily rainfall time series were generated at the satellite measuring spots. These artificial series were incorporated into an existing hydrological model to complement the available raingauge data to assess the model performance. The results were quite comparable with those using only gauge information. Although the model outcomes did not improve remarkably, the contribution of this approach was based on the fact that given a known bias, the satellite data could still be corrected and may resemble the information provided by the raingauges. Therefore, TRMM may supply valuable information in areas scarcely gauged such as the Andean foothills in the Guayas River Basin.

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

2018 ◽  
Vol 6 (6) ◽  
pp. 119
Author(s):  
Mohammad Shohidul Islam ◽  
Sultana Easmin Siddika ◽  
S M Injamamul Haque Masum
Keyword(s):  
Linear Regression ◽  
Correlation Coefficients ◽  
Rain Gauge ◽  
Regression Method ◽  
Linear Regression Method ◽  
Climate Data ◽  
Rainfall Forecasting ◽  
Statistical Parameters ◽  
Time Duration ◽  
Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

COMPARISON BETWEEN RADAR ESTIMATED AND RAIN GAUGE MEASURED PRECIPITATION IN THE MOLDAVIAN PLATEAU

2012 ◽  
Vol 11 (4) ◽  
pp. 723-731 ◽  
Author(s):  
Sorin Burcea ◽  
Sorin Cheval ◽  
Alexandru Dumitrescu ◽  
Bogdan Antonescu ◽  
Aurora Bell ◽  
...  
Keyword(s):  
Rain Gauge

The Importance of Rainfall Distribution in Urban Drainage Operation

1992 ◽  
Vol 23 (2) ◽  
pp. 121-136 ◽  
Author(s):  
Fons Nelen ◽  
Annemarieke Mooijman ◽  
Per Jacobsen
Keyword(s):  
Real Time ◽  
Treatment Plant ◽  
Rain Gauge ◽  
Point Of View ◽  
Rain Event ◽  
Real Time Control ◽  
Rainfall Distribution ◽  
Statistical Point ◽  
Time Control ◽  
Spatially Distributed

A control simulation model, called LOCUS, is used to investigate the effects of spatially distributed rain and the possibilities to benefit from this phenomenon by means of real time control. The study is undertaken for a catchment in Copenhagen, where rainfall is measured with a network of 8 rain gauges. Simulation of a single rain event, which is assumed to be homogeneous, i.e. using one rain gauge for the whole catchment, leads to large over- and underestimates of the systems output variables. Therefore, when analyzing a single event the highest possible degree of rainfall information may be desired. Time-series simulations are performed for both an uncontrolled and a controlled system. It is shown that from a statistical point of view, rainfall distribution is NOT significant concerning the probability of occurrence of an overflow. The main contributing factor to the potential of real time control, concerning minimizing overflows, is to be found in the system itself, i.e. the distribution of available storage and discharge capacity. When other operational objectives are involved, e.g., to minimize peak flows to the treatment plant, rainfall distribution may be an important factor.

The Prediction of Rainfall and the Direction of Rainfall by a Narrow Area Radar Rain Gauge

1993 ◽  
Vol 28 (11-12) ◽  
pp. 79-85
Author(s):  
Shinichi Kondo
Keyword(s):  
Small Area ◽  
Arrival Time ◽  
Rain Gauge ◽  
Rain Gauges ◽  
Sewage Plant ◽  
Future Prediction ◽  
Near Future ◽  
Narrow Area

Narrow area radar rain gauges are currently used for measuring rainfall. These radar gauges can measure rainfall accurately in a small area. In sewage plants it is important to predict stormwater. To calculate predicted stormwater the results of rainfall and a prediction of the near future are necessary. Recently urbanization has made the arrival time of flooding to the sewage plant much shorter. This paper deals with system technologies for the near future prediction of radar rain gauge rainfall. The method of prediction of rainfall, calculation of results and other considerations are described.

Correction and preparation of continuously measured raingauge data: a standard method in North Rhine-Westphalia

1998 ◽  
Vol 37 (11) ◽  
pp. 155-162 ◽  
Author(s):  
B. Maul-Kötter ◽  
Th. Einfalt
Keyword(s):  
Water Balance ◽  
Standard Method ◽  
The State ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Site Specific ◽  
Free Data ◽  
Important Input ◽  
Raingauge Data ◽  
Environmental Agency

Continuous raingauge measurements are an important input variable for detailed rainfall-runoff simulation. In North Rhine-Westphalia, more than 150 continuous raingauges are used for local hydrological design through the use of site specific rainfall runoff models. Requiring gap-free data, the State Environmental Agency developed methods to use a combination of daily measurements and neighbouring continuous measurements for filling periods of lacking data in a given raindata series. The objective of such a method is to obtain plausible data for water balance simulations. For more than 3500 station years the described methodology has been applied.

scholarly journals Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xichuan Liu ◽  
Taichang Gao ◽  
Yuntao Hu ◽  
Xiaojian Shu
Keyword(s):  
Drop Size ◽  
Rain Rate ◽  
Monte Carlo Model ◽  
Rain Gauge ◽  
Sampling Schemes ◽  
Distribution Parameters ◽  
Optimum Sampling ◽  
Simulation Results ◽  
The Impact ◽  
Good Agreement

In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.

scholarly journals Evaluation of gridded rain‐gauge‐based precipitation datasets: Impact of station density, spatial resolution, altitude gradient and climate

2021 ◽  
Author(s):  
Andrés Merino ◽  
Eduardo García‐Ortega ◽  
Andrés Navarro ◽  
Sergio Fernández‐González ◽  
Francisco J. Tapiador ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Rain Gauge ◽  
Altitude Gradient ◽  
Station Density

scholarly journals Assessment of Snowfall Accumulation from Satellite and Reanalysis Products Using SNOTEL Observations in Alaska

2021 ◽  
Vol 13 (15) ◽  
pp. 2922
Author(s):  
Yang Song ◽  
Patrick D. Broxton ◽  
Mohammad Reza Ehsani ◽  
Ali Behrangi
Keyword(s):  
Snow Water Equivalent ◽  
Stage Iv ◽  
Microwave Remote Sensing ◽  
Rain Gauge ◽  
Snow Accumulation ◽  
Correction Factors ◽  
Rainfall Analysis ◽  
Rain Gauges ◽  
Snow Properties ◽  
Precipitation Estimates

The combination of snowfall, snow water equivalent (SWE), and precipitation rate measurements from 39 snow telemetry (SNOTEL) sites in Alaska were used to assess the performance of various precipitation products from satellites, reanalysis, and rain gauges. Observation of precipitation from two water years (2018–2019) of a high-resolution radar/rain gauge data (Stage IV) product was also utilized to give insights into the scaling differences between various products. The outcomes were used to assess two popular methods for rain gauge undercatch correction. It was found that SWE and precipitation measurements at SNOTELs, as well as precipitation estimates based on Stage IV data, are generally consistent and can provide a range within which other products can be assessed. The time-series of snowfall and SWE accumulation suggests that most of the products can capture snowfall events; however, differences exist in their accumulation. Reanalysis products tended to overestimate snow accumulation in the study area, while the current combined passive microwave remote sensing products (i.e., IMERG-HQ) underestimate snowfall accumulation. We found that correction factors applied to rain gauges are effective for improving their undercatch, especially for snowfall. However, no improvement in correlation is seen when correction factors are applied, and rainfall is still estimated better than snowfall. Even though IMERG-HQ has less skill for capturing snowfall than rainfall, analysis using Taylor plots showed that the combined microwave product does have skill for capturing the geographical distribution of snowfall and precipitation accumulation; therefore, bias adjustment might lead to reasonable precipitation estimates. This study demonstrates that other snow properties (e.g., SWE accumulation at the SNOTEL sites) can complement precipitation data to estimate snowfall. In the future, gridded SWE and snow depth data from GlobSnow and Sentinel-1 can be used to assess snowfall and its distribution over broader regions.

Sign in / Sign up

Export Citation Format

Share Document