Comparison of TRMM multi-satellite precipitation analysis (TMPA) estimation with ground-based precipitation data over Maharashtra, India

2019 ◽  
Vol 22 (6) ◽  
pp. 5539-5552
Author(s):  
T. P. Singh ◽  
Vidya Kumbhar ◽  
Sandipan Das ◽  
Mangesh M. Deshpande ◽  
Komal Dhoka
Keyword(s):  
Precipitation Data ◽  
Satellite Precipitation ◽  
Precipitation Analysis

scholarly journals Adjusting Satellite Precipitation Data to Facilitate Hydrologic Modeling

2010 ◽  
Vol 11 (4) ◽  
pp. 966-978 ◽  
Author(s):  
Kenneth J. Tobin ◽  
Marvin E. Bennett
Keyword(s):  
Hydrological Modeling ◽  
Tropical Rainfall Measuring Mission ◽  
Probability Of Detection ◽  
Precipitation Data ◽  
Satellite Precipitation ◽  
Precipitation Product ◽  
San Pedro ◽  
Precipitation Analysis ◽  
San Pedro Basin ◽  
Daily Time

Abstract Significant concern has been expressed regarding the ability of satellite-based precipitation products such as the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 products (version 6) and the U.S. National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center’s (CPC) morphing technique (CMORPH) to accurately capture rainfall values over land. Problems exist in terms of bias, false-alarm rate (FAR), and probability of detection (POD), which vary greatly worldwide and over the conterminous United States (CONUS). This paper directly addresses these concerns by developing a methodology that adjusts existing TMPA products utilizing ground-based precipitation data. The approach is not a simple bias adjustment but a three-step process that transforms a satellite precipitation product. Ground-based precipitation is used to develop a filter eliminating FAR in the authors’ adjusted product. The probability distribution function (PDF) of the satellite-based product is adjusted to the PDF of the ground-based product, minimizing bias. Failure of precipitation detection (POD) is addressed by utilizing a ground-based product during these periods in their adjusted product. This methodology has been successfully applied in the hydrological modeling of the San Pedro basin in Arizona for a 3-yr time series, yielding excellent streamflow simulations at a daily time scale. The approach can be applied to any satellite precipitation product (i.e., TRMM 3B42 version 7) and will provide a useful approach to quantifying precipitation in regions with limited ground-based precipitation monitoring.

scholarly journals From TRMM to GPM: How Reliable Are Satellite-Based Precipitation Data across Nigeria?

2020 ◽  
Vol 12 (23) ◽  
pp. 3964
Author(s):  
Pius Nnamdi Nwachukwu ◽  
Frederic Satge ◽  
Samira El Yacoubi ◽  
Sebastien Pinel ◽  
Marie-Paule Bonnet
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Annual Rainfall ◽  
Precipitation Data ◽  
Time Step ◽  
Satellite Precipitation ◽  
Satellite Retrievals ◽  
Precipitation Analysis ◽  
Global Precipitation Mission ◽  
Global Precipitation

In this study, 16 satellite-based precipitation products (SPPs) comprising satellite, gauge and reanalysis datasets were assessed on a monthly time step using precipitation data from 11 gauge stations across Nigeria within the 2000–2012 period as reference. Despite the ability of some of the SPPs to reproduce the salient north–south pattern of the annual rainfall field, the Kling–Gupta efficiency (KGE) results revealed substantial discrepancies among the SPP estimates. Generally, the SPP reliability varies spatially and temporally, with all SPPs performing better over part of central Nigeria during the dry season. When we compared the real-time and adjusted satellite-based products, the results showed that the adjusted products had a better KGE score. The assessment also showed that the reliability of integrated multi-satellite retrievals for Global Precipitation Mission (IMERG) products was consistent with that of their predecessor Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). Finally, the best overall scores were obtained from multi-source weighted-ensemble precipitation (MSWEP) v.2.2 and IMERG-F v.6. Both products are therefore suggested for further hydrological studies.

scholarly journals Accelerating assimilation development for new observing systems using EFSO

2018 ◽  
Vol 25 (1) ◽  
pp. 129-143 ◽  
Author(s):  
Guo-Yuan Lien ◽  
Daisuke Hotta ◽  
Eugenia Kalnay ◽  
Takemasa Miyoshi ◽  
Tse-Chun Chen
Keyword(s):  
Selection Criteria ◽  
Ensemble Forecast ◽  
Data Selection ◽  
Development Work ◽  
Observation Data ◽  
Precipitation Data ◽  
Trial And Error ◽  
Satellite Precipitation ◽  
Selection Strategies ◽  
Observing Systems

Abstract. To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

scholarly journals Modelación de Crecidas Aluvionales en la Cuenca del Río Copiapó, Chile

2017 ◽  
Vol 21 (2) ◽  
pp. 135 ◽  
Author(s):  
Rodrigo Valdés-Pineda ◽  
Juan B. Valdés ◽  
Pablo García-Chevesich
Keyword(s):  
Mass Movement ◽  
Satellite Precipitation ◽  
Precipitation Analysis ◽  
Del Rio ◽  
Movement Simulation ◽  
Rapid Mass

<p class="Resumen">Los eventos extremos de precipitación intensa que se produjeron entre el 24 y 26 de marzo de 2015 en la región del Desierto de Atacama (26-29°S), en el Norte de Chile, dejaron alrededor de 30 000 damnificados, siendo uno de los eventos de mayores magnitudes de los últimos 50 años, y que tuvo un costo de reconstrucción de alrededor de $1.5 billones de dólares. Los flujos de detritos que se incrementaron durante la crecida inundaron gran parte de las ciudades de Copiapó y Tierra Amarilla. Este manuscrito tiene por objetivo modelar la crecida aluvional de marzo de 2015 en la cuenca del Río Copiapó, específicamente en las localidades de Copiapó y Tierra Amarilla. La modelación se lleva a cabo utilizando el modelo Rapid Mass Movement Simulation (RAMMS) que permite modelar la dinámica de la crecida aluvional en dos dimensiones, utilizando las características topográficas de los dominios de modelación. La calibración del modelo fue llevada a cabo satisfactoriamente utilizando datos de alturas capturados en terreno después de la crecida del año 2015. Un análisis detallado del evento hidrometeorológico es llevado a cabo utilizando imágenes satelitales obtenidas desde Multi-satellite Precipitation Analysis (TMPA), así como datos pluviométricos e hidrográficos disponibles en la cuenca del Río Copiapó. La simulación de la crecida es reproducida con mapas de alturas de inundación asociados a dos escenarios de modelación. Las alturas máximas de inundación son finalmente utilizadas para el desarrollo de mapas de riesgos en ambas localidades. De acuerdo a nuestros resultados, el modelo RAMMS es una herramienta apropiada para modelar crecidas aluvionales y elaborar mapas de riesgos de inundación para mejorar la gestión de riesgos hidrológicos en cuencas áridas y semiáridas de Chile.</p>

scholarly journals Applicability and Hydrologic Substitutability of TMPA Satellite Precipitation Product in the Feilaixia Catchment, China

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1803
Author(s):  
Xiaoli Chen ◽  
Guoru Huang
Keyword(s):  
Assessment Tool ◽  
Swat Model ◽  
Tropical Rainfall Measuring Mission ◽  
Climatic Conditions ◽  
High Latitudes ◽  
Climate Trends ◽  
Runoff Simulation ◽  
Satellite Precipitation ◽  
Precipitation Analysis ◽  
Water Assessment

The assessment of various precipitation products’ performances in extreme climatic conditions has become a topic of interest. However, little attention has been paid to the hydrological substitutability of these products. The objective of this study is to explore the performance of the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) product in the Feilaixia catchment, China. To assess its applicability in extreme consecutive climates, several statistical indices are adopted to evaluate the TMPA performance both qualitatively and quantitatively. The Cox–Stuart test is used to investigate extreme climate trends. The Soil and Water Assessment Tool (SWAT) model is used to test the TMPA hydrological substitutability via three scenarios of runoff simulation. The results demonstrate that the overall TMPA performance is acceptable, except at high-latitudes and locations where the terrain changes greatly. Moreover, the accuracy of the SWAT model is high both in the semi-substitution and full-substitution scenarios. Based on the results, the TMPA product is a useful substitute for the gauged precipitation in obtaining acceptable hydrologic process information in areas where gauged sites are sparse or non-existent. The TMPA product is satisfactory in predicting the runoff process. Overall, it must be used with caution, especially at high latitudes and altitudes.

scholarly journals Application of TRMM Precipitation Data to Evaluate Drought and Its Effects on Water Resources Instability

2019 ◽  
Vol 9 (24) ◽  
pp. 5377
Author(s):  
Ata Amini ◽  
Abdolnabi Abdeh Kolahchi ◽  
Nadhir Al-Ansari ◽  
Mehdi Karami Moghadam ◽  
Thamer Mohammad
Keyword(s):  
Water Resources ◽  
Standardized Precipitation Index ◽  
Remote Sensing Data ◽  
Tropical Rainfall Measuring Mission ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Discharge Data ◽  
Satellite Precipitation ◽  
Discharge Rates ◽  
Trmm Precipitation

The present research was carried out to study drought and its effects upon water resources using remote sensing data. To this end, the tropical rainfall measuring mission (TRMM) satellite precipitation, the synoptic stations, and fountain discharge data were employed. For monitoring of drought in the study area, in Kermanshah province, Iran, the monthly precipitation data of the synoptic stations along with TRMM satellite precipitation datasets were collected and processed in the geographic information system (GIS) environment. Statistical indicators were applied to evaluate the accuracy of TRMM precipitation against the meteorological stations’ data. Standardized precipitation index, SPI, and normalized fountain discharge were used in the monitoring of drought conditions, and fountains discharge, respectively. The fountains were selected so that in addition to enjoying the most discharge rates, they spread along the study area. The evaluation of precipitation data showed that the TRMM precipitation data were of high accuracy. Studies in temporal scale are indicative of the strike of drought in this region to the effect that for most months of the year, frequency and duration in dry periods are much more than in wet periods. As for seasonal scales, apart from winter, the frequency and duration of drought in spring and autumn have been longer than in wet years. Moreover, the duration of these periods was different. A comparison between the results of changes in fountain discharges and drought index in the region has verified that the drought has caused a remarkable decline in the fountain discharges.

scholarly journals Combined Assimilation of Satellite Precipitation and Soil Moisture: A Case Study Using TRMM and SMOS Data

2017 ◽  
Vol 145 (12) ◽  
pp. 4997-5014 ◽  
Author(s):  
Liao-Fan Lin ◽  
Ardeshir M. Ebtehaj ◽  
Alejandro N. Flores ◽  
Satish Bastola ◽  
Rafael L. Bras
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Specific Humidity ◽  
Surface Model ◽  
Precipitation Data ◽  
Near Surface ◽  
Satellite Precipitation ◽  
Soil Moisture Data ◽  
Mean Square Errors

This paper presents a framework that enables simultaneous assimilation of satellite precipitation and soil moisture observations into the coupled Weather Research and Forecasting (WRF) and Noah land surface model through variational approaches. The authors tested the framework by assimilating precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite. The results show that assimilation of both TRMM and SMOS data can effectively improve the forecast skills of precipitation, top 10-cm soil moisture, and 2-m temperature and specific humidity. Within a 2-day time window, impacts of precipitation data assimilation on the forecasts remain relatively constant for forecast lead times greater than 6 h, while the influence of soil moisture data assimilation increases with lead time. The study also demonstrates that the forecast skill of precipitation, soil moisture, and near-surface temperature and humidity are further improved when both the TRMM and SMOS data are assimilated. In particular, the combined data assimilation reduces the prediction biases and root-mean-square errors, respectively, by 57% and 6% (for precipitation); 73% and 27% (for soil moisture); 17% and 9% (for 2-m temperature); and 33% and 11% (for 2-m specific humidity).

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