scholarly journals Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

2018 ◽  
Vol 10 (12) ◽  
pp. 1879 ◽  
Author(s):  
Véronique Michot ◽  
Daniel Vila ◽  
Damien Arvor ◽  
Thomas Corpetti ◽  
Josyane Ronchail ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial Coverage ◽  
Rainfall Regimes ◽  
Trmm 3B42 ◽  
Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

scholarly journals Mapping the Daily Rainfall over an Ungauged Tropical Micro-Watershed: A Downscaling Algorithm Using GPM Data

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1661 ◽  
Author(s):  
Mohd. Rizaludin Mahmud ◽  
Aina Afifah Mohd Yusof ◽  
Mohd Nadzri Mohd Reba ◽  
Mazlan Hashim
Keyword(s):  
High Resolution ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Precipitation Data ◽  
Rain Gauge Data ◽  
Satellite Precipitation ◽  
Daily Rainfall Data ◽  
Gauge Data

In this study, half-hourly Global Precipitation Mission (GPM) satellite precipitation data were downscaled to produce high-resolution daily rainfall data for tropical coastal micro-watersheds (100–1000 ha) without gauges or with rainfall data conflicts. Currently, daily-scale satellite rainfall downscaling techniques rely on rain gauge data as corrective and controlling factors, making them impractical for ungauged watersheds or watersheds with rainfall data conflicts. Therefore, we used high-resolution local orographic and vertical velocity data as proxies to downscale half-hourly GPM precipitation data (0.1°) to high-resolution daily rainfall data (0.02°). The overall quality of the downscaled product was similar to or better than the quality of the raw GPM data. The downscaled rainfall dataset improved the accuracy of rainfall estimates on the ground, with lower error relative to measured rain gauge data. The average error was reduced from 41 to 27 mm/d and from 16 to 12 mm/d during the wet and dry seasons, respectively. Estimates of localized rainfall patterns were improved from 38% to 73%. The results of this study will be useful for production of high-resolution satellite precipitation data in ungauged tropical micro-watersheds.

scholarly journals Variabilitas Spasial Hujan Tahunan di Wilayah UPT PSDA di Pasuruan, Jawa Timur : Analisis Histogram dan Normal QQ-Plot

2018 ◽  
Vol 11 (1) ◽  
pp. 35-49
Author(s):  
Askin Askin ◽  
Indarto Indarto ◽  
Dimas Ghufron Ash-Shiddiq ◽  
Sri Wahyuningsih
Keyword(s):  
Spatial Variability ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Thematic Map ◽  
Daily Rainfall Data ◽  
Average Annual Rainfall ◽  
Administrative Area ◽  
Main Input

Abstrak. Penelitian ini bertujuan untuk menganalisis variabilitas spasial hujan di wilayah UPT PSDA di Pasuruan. Wilayah studi mencakup kabupaten Probolinggo, kota Probolinggo, Kabupaten Pasuruan dan Kota Pasuruan di Jawa Timur. Data hujan tahunan rerata (Hthn_rrt) dan hujan tahunan maksimal (HthnMaks) dihitung dari kumulatif data hujan harian pada 93 stasiun dan dijadikan sebagai input utama untuk analisis. Panjang periode rekaman data yang digunakan dari tahun 1980 sampai dengan 2015 (35 tahun). Tahap penelitian mencakup: (1) pra-pengolahan data, (2) analisis pendahuluan, (3) analisis menggunakan tool histogram dan voronoi map, (4) interpolasi data dan pembuatan peta tematik. Pra-pengolahan data dilakukan menggunakan excel. Analisis histogram dan QQ-Plot dilakukan untuk melihat variabilitas spasial lebih detail per sub-wilayah. Selanjutnya, metode interpolasi digunakan untuk membuat peta tematik hujan tahunan. Peta tematik menunjukkan hujan tahunan rerata (Hthn_rrt) yang terjadi di wilayah tersebut selama 35 tahun terakhir berkisar antara 1200 sd 2600 mm/tahun. Hujan tahunan maksimal yang terjadi berkisar antara 2100 sd 4500 mm/tahun. Penelitian juga menunjukkan adanya korelasi positif antara lokasi stasiun hujan (elevasi) dengan jumlah hujan tahunan yang diterima. Spatial Variability of Annual Rainfall in The Administrative Area of UPT PSDA at Pasuruan, East Java : Analysis Using Histogram and QQ-Plot Abstract. This research aims to analyze the spatial variability of annual rainfall. Daily rainfall data from 93 rain gauge in the administrative area of UPT PSDA Pasuruan were used as the main input. The average annual rainfall and the maximum annual rainfall obtained from the daily rainfall data. Histograms, and QQ-Plot were used to describe the spatial variability in each sub-regions. Next, interpolation methods is used to create a thematic map of the annual rainfall. The results shows that local spatial variability of rainfall can be visualized more detail for each sub-region by means of histogram and QQ-Plot. The thematic map showed that the distribution of average annual rainfall in the region range from 1,200 mm/year up to 2,600 mm/year. Maximum annual rainfall range between 2,100 mm/year up to 4,500 mm/year. The result also show the positif correlation between the altitude of the rain gauge and local annual rainfall received.

scholarly journals A Step towards Integrating CMORPH Precipitation Estimation with Rain Gauge Measurements

2018 ◽  
Vol 2018 ◽  
pp. 1-24
Author(s):  
Augusto José Pereira Filho ◽  
Felipe Vemado ◽  
Guilherme Vemado ◽  
Fábio Augusto Gomes Vieira Reis ◽  
Lucilia do Carmo Giordano ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Brazilian Coast ◽  
Rainfall Estimation ◽  
Peruvian Andes ◽  
Positive Tendency ◽  
Analysis Scheme ◽  
Areal Rainfall

Accurate daily rainfall estimation is required in several applications such as in hydrology, hydrometeorology, water resources management, geomorphology, civil protection, and agriculture, among others. CMORPH daily rainfall estimations were integrated with rain gauge measurements in Brazil between 2000 and 2015, in order to reduce daily rainfall estimation errors by means of the statistical objective analysis scheme (SOAS). Early comparisons indicated high discrepancies between daily rain gauge rainfall measurements and respective CMORPH areal rainfall accumulation estimates that tended to be reduced with accumulation time span (e.g., yearly accumulation). Current results show CMORPH systematically underestimates daily rainfall accumulation along the coastal areas. The normalized error variance (NEXERVA) is higher in sparsely gauged areas at Brazilian North and Central-West regions. Monthly areal rainfall averages and standard deviation were obtained for eleven Brazilian watersheds. While an overall negative tendency (3 mm·h−1) was estimated, the Amazon watershed presented a long-term positive tendency. Monthly areal mean precipitation and respective spatial standard deviation closely follow a power-law relationship for data-rich watersheds, i.e., with denser rain gauge networks. Daily SOAS rainfall accumulation was also used to calculate the spatial distribution of frequencies of 3-day rainfall episodes greater than 100 mm. Frequencies greater than 3% were identified downwind of the Peruvian Andes, the Bolivian Amazon Basin, and the La Plata Basin, as well as along the Brazilian coast, where landslides are recurrently triggered by precipitation.

scholarly journals Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation

2018 ◽  
Vol 20 (4) ◽  
pp. 784-797 ◽  
Author(s):  
Marija Ivković ◽  
Andrijana Todorović ◽  
Jasna Plavšić
Keyword(s):  
Daily Rainfall ◽  
Flood Forecasting ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Rain Gauges ◽  
Observation Network ◽  
Hourly Rainfall ◽  
Extreme Flood ◽  
Flood Simulations

Abstract Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.

Study on multiple rainfall data applied to debris flow warning in Taiwan

2020 ◽  
Author(s):  
Yi-Chao Zeng ◽  
Chyan-Deng Jan ◽  
Mu-Jung Lin ◽  
Ji-Shang Wang ◽  
Hsiao-Yuan Yin ◽  
...  
Keyword(s):  
Debris Flow ◽  
Observational Data ◽  
Water Conservation ◽  
Spatial Interpolation ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Mountain Area ◽  
Rainfall Condition ◽  
Capture Ratio ◽  
Spatial Coverage

<p>Due to climate change, precipitation characteristics have been significantly variation and rainfall patterns are presented more concentrated, high-intensity and long-duration trend in the past two decades. Catastrophic debris-flow disaster threaten lives and property of residents. For mitigation impact of debris-flow, SWCB (Soil and Water Conservation Bureau, Taiwan) has had a leading role in sponsoring debris-flow research and developing a rainfall-based debris-flow warning model. Early warning criteria for debris-flow triggered are also determined depending on the historical rainfall data, and the observational data of rain-gauge are adopted to issue debris-flow warning. However, application of rain-gauge rainfall data has some disadvantages such as low density in mountain area, observation failure to properly represent actual rainfall condition, and data transmission likely interrupted during heavy rainfall or Typhoon. In order to improve the efficiency of debris-flow warning system, two types of gridded precipitation are analyzed and discussed in this study, which are the spatial interpolation rainfall of rain-gauge and the radar-estimated rainfall (QPESUMS). For comparison the differents of multiple rainfall data mentioned above with rain-guage, the third quartile is firstly applied to calculate the regional representative rainfall from grid cells within warning issued area. The results show that the spatial interpolation rainfall underestimates the rainfall intensity and cumulative rainfall owing to the influence of complex topography. By contrast, the radar-estimated rainfall has the advantage in comprehension of the rainfall spatial variability and provide a more complete spatial coverage. Besides, for assessing the appropriate and feasibility of multiple rainfall data applied to debris flow warning, the disaster–capture ratio has been proposed which is defined as the number of debris-flow hazards after issuing warning divided by total number of debris- flow hazards. According to analyis results of historical disaster records from 2012 to 2016, the disaster–capture ratio are 47.6%, 38.1% and 61.9% as warning issued refer to rain gauge, the spatial interpolation rainfall and the radar-estimated rainfall respectively. By the aforementioned process, we realize that the application of radar-estimated rainfall to debris flow warning is obviously increasing efficiency of debris-flow warning ,and gives assistance for reducing uncertainty of rainfall observational data, especially in mountain area.</p>

scholarly journals On Complex Network Construction of Rain Gauge Stations Considering Nonlinearity of Observed Daily Rainfall Data

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1578 ◽  
Author(s):  
Kyunghun Kim ◽  
Hongjun Joo ◽  
Daegun Han ◽  
Soojun Kim ◽  
Taewoo Lee ◽  
...  
Keyword(s):  
Network Analysis ◽  
Mutual Information ◽  
Complex Network ◽  
Pearson Correlation ◽  
Daily Rainfall ◽  
Analysis Data ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Relationship Of ◽  
Rain Gauge Network

Rainfall data is frequently used as input and analysis data in the field of hydrology. To obtain adequate rainfall data, there should be a rain gauge network that can cover the relevant region. Therefore, it is necessary to analyze and evaluate the adequacy of rain gauge networks. Currently, a complex network analysis is frequently used in network analysis and in the hydrology field, Pearson correlation is used as strength of link in constructing networks. However, Pearson correlation is used for analyzing the linear relationship of data. Therefore, it is now suitable for nonlinear hydrological data (such as rainfall and runoff). Thus, a possible solution to this problem is to apply mutual information that can consider nonlinearity of data. The present study used a method of statistical analysis known as the Brock–Dechert–Scheinkman (BDS) statistics to test the nonlinearity of rainfall data from 55 Automated Synoptic Observing System (ASOS) rain gauge stations in South Korea. Analysis results indicated that all rain gauge stations showed nonlinearity in the data. Complex networks of these rain gauge stations were constructed by applying Pearson correlation and mutual information. Then, they were compared by computing their centrality values. Comparing the centrality rankings according to different thresholds for correlation showed that the network based on mutual information yielded consistent results in the rankings, whereas the network, which based on Pearson correlation exhibited much variability in the results. Thus, it was found that using mutual information is appropriate when constructing a complex network utilizing rainfall data with nonlinear characteristics.

Validation of Satellite Rainfall Estimates over Equatorial East Africa

2021 ◽  
Author(s):  
Simon Ageet ◽  
Andreas Fink ◽  
Marlon Maranan
Keyword(s):  
East Africa ◽  
Extreme Values ◽  
Extreme Event ◽  
Weather Prediction ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Annual Rainfall ◽  
Extreme Rainfall Events ◽  
Satellite Rainfall ◽  
Rainfall Estimates

<p>The sparsity of rain gauge (RG) data over Africa is a known impediment to the assessments of hydro-meteorological risks and of the skill of numerical weather prediction (NWP) models. Satellite rainfall estimates (SREs) have been used as surrogate fields for a long time and are continuously replaced by more advanced algorithms.  Using a unique daily rainfall dataset from 36 stations across equatorial East Africa for the period 2001–2018, this study performs a multi-scale evaluation of gauge-calibrated SREs, namely, Integrated Multi-satellite Retrieval for Global Precipitation Measurement (GPM) (IMERG), Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and Multi-Source Weighted-Ensemble Precipitation (MSWEP). Skills were assessed from daily to annual timescales, for extreme daily precipitation, and for the TMPA and IMERG near real-time (NRT) products. Results show that: 1) the satellite products reproduce the annual rainfall pattern and seasonal rainfall cycle well, despite exhibiting biases of up to 9%; 2) IMERG is the best overall for shorter temporal scales (daily, pentadal and dekadal) while MSWEP and CHIRPS perform best at the monthly and annual timesteps, respectively; 3) the SREs’ performance, especially in MSWEP, shows high spatial variability likely due to the variation of weights assigned during gauge calibration; 4) all the SREs miss between 57% (IMERG NRT)  and 83 (CHIRPS) of daily extreme rainfall events recorded in the RGs; 5) IMERG NRT outperforms all the other products regarding extreme event detection and accuracy; and 6) for assessing return values of daily extreme values, IMERG and MSWEP are satisfactory while the use of CHIRPS cannot be recommended. The study highlights some improvements of IMERG over its predecessor TMPA and the potential of Multi-Source Weighted-Ensembles products such as MSWEP for flood risk assessment and validation of NWP rainfall forecasts over East Africa.</p>

Less rain and rainy days - lessons from 45 years of rainfall data (1971 to 2015) in the Kathmandu Valley, Nepal

2021 ◽  
Author(s):  
Rajaram Prajapati ◽  
Rocky Talchabhadel ◽  
Priya Silwal ◽  
Surabhi Upadhyay ◽  
Brandon Ertis ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Temporal Trends ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Kathmandu Valley ◽  
Light Rain ◽  
Mk Test ◽  
Spatio Temporal ◽  
Rainy Days

Abstract Understanding spatio-temporal variability in rainfall patterns is crucial for evaluating water balances needed for water resources planning and management. This paper investigates spatio-temporal variability in rainfall and assesses the frequency of daily rainfall observations from seven stations in the Kathmandu Valley, Nepal, from 1971–2015. Daily rainfall totals were classified into five classes, namely, A (light rain, daily rainfall < 10 mm in a day), B (between 10–50 mm), C (between 50–100 mm), D (between 100–150 mm) and E (> 150 mm). The relationship between daily rainfall and rainfall frequency of various rainfall rate classes were analysed. Kriging method was used for interpolation in interpreting seasonal and annual rainfall data and spatial maps were generated using QGIS. The Mann-Kendall (MK) test was performed to determine the temporal trends and Theil-Sen’s (TS) slope estimator was used in quantifying the magnitude of trends. Mountain stations showed a decreasing trend in rainfall for all seasons, ranging from − 8.4 mm/year at Sankhu to -21.8 mm/year at Thankot, whereas, a mixed pattern was found on the Valley floor. Mean annual rainfall in the Valley was 1610 mm. Both annual rainfall and the number of rainy days decreased in the Kathmandu Valley over the study period. The study indicated a significant reduction in rainfall after 2000. Since springs and shallow groundwater are the primary sources of water supply for residents in the Kathmandu Valley, it is apparent that decreasing rainfall will have (and is already having) an adverse impact on domestic, industrial, and agricultural water supplies, and the livelihoods of people.

scholarly journals Precipitation and Microphysical Processes Observed by Three Polarimetric X-Band Radars during HOPE

2016 ◽  
Author(s):  
Xinxin Xie ◽  
Raquel Evaristo ◽  
Clemens Simmer ◽  
Jan Handwerker ◽  
Silke Troemel
Keyword(s):  
Daily Rainfall ◽  
Rain Gauge ◽  
The Other ◽  
High Definition ◽  
Rain Gauges ◽  
X Band ◽  
Independent Observations ◽  
Microphysical Processes ◽  
Close Distance ◽  
Good Agreement

Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRR) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Juelich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5×5 km2 region, while another three disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed a very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.

scholarly journals Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE

2016 ◽  
Vol 16 (11) ◽  
pp. 7105-7116 ◽  
Author(s):  
Xinxin Xie ◽  
Raquel Evaristo ◽  
Clemens Simmer ◽  
Jan Handwerker ◽  
Silke Trömel
Keyword(s):  
Daily Rainfall ◽  
Rain Gauge ◽  
The Other ◽  
High Definition ◽  
Rain Gauges ◽  
X Band ◽  
Independent Observations ◽  
Microphysical Processes ◽  
Close Distance ◽  
Good Agreement

Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km  ×  5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.

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