Evaluation of precipitation products over complex mountainous terrain: A water resources perspective

Ward, Eliot M.; Buytaert, Wouter; Peaver, Louise; Wheater, H. S.

doi:10.1016/j.advwatres.2011.05.007

Cited by 146 publications

(101 citation statements)

References 34 publications

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“…Guo et al, 2015;Blacutt et al, 2015;Ward et al, 2011;Scheel et al, 2011). Here, we further subdivide daily rainfall in five types of events, which are used to classify precipitation based on its daily intensity, ranging from no rain (dry day; < 1 mm d −1 ) to violent rain (> 40 mm d −1 ), as shown in Table 2.…”

Section: Performance Indicesmentioning

confidence: 99%

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Zambrano‐Bigiarini

Nauditt²,

Birkel

et al. 2017

Hydrol. Earth Syst. Sci.

213

153

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Abstract. Accurate representation of the real spatiotemporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate -for the first time -the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25 • grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7 • S) and Central Chile (32.18-36.4 • S), in particular at low-and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all timescales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR, and the real-time PERSIANN-CCS-Adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resource assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

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Section: Performance Indicesmentioning

confidence: 99%

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Zambrano‐Bigiarini

Nauditt²,

Birkel

et al. 2017

Hydrol. Earth Syst. Sci.

213

153

View full text Add to dashboard Cite

show abstract

“…Missing data was checked in order to keep it below a maximum percentage of 20%. Additionally, homogeneity was checked with the RHV4 test, available in the R software, which detects changes in the mean precipitation through time (Wang and Feng, 2004 The Tropical Rainfall Measurement Mission (TRMM) was launched in November of 1997 to cover the tropic regions (Simpson et al, 1988). One of its products is 3B43 version 7 which combines the results of several sensors and control rain gauges.…”

Section: Rain Gauge Control Datamentioning

confidence: 99%

Validation of Satellite Precipitation (Trmm 3b43) in Ecuadorian Coastal Plains, Andean Highlands and Amazonian Rainforest

Ballari

Castro

Campozano

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VIII/4KEY WORDS: TRMM, validation, statistical error metrics, detection indexes, Ecuador, ungagged watershed basins ABSTRACT: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.

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“…by Scheel et al (2011) with focus on the Cuzco and La Paz regions in the central Andes. Ward et al (2011) conducted a similar investigation in the Paute region (> 1684 m a.s.l.) situated in the southern Ecuadorian Andes, and Arias-Hidalgo et al (2013) explored its applicability as input for hydrologic studies on a catchment in the Pacific-Andean region in central Ecuador.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of TRMM 3B42 precipitation estimates and WRF retrospective precipitation simulation over the Pacific–Andean region of Ecuador and Peru

Ochoa

Pineda

Crespo

et al. 2014

Hydrol. Earth Syst. Sci.

101

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Abstract. The Pacific-Andean region in western South America suffers from rainfall data scarcity, as is the case for many regions in the South. An important research question is whether the latest satellite-based and numerical weather prediction (NWP) model outputs capture well the temporal and spatial patterns of rainfall over the region, and hence have the potential to compensate for the data scarcity. Based on an interpolated gauge-based rainfall data set, the performance of the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 and its predecessor V6, and the North Western South America Retrospective Simulation (OA-NOSA30) are evaluated over 21 sub-catchments in the Pacific-Andean region of Ecuador and Peru (PAEP).In general, precipitation estimates from TRMM and OA-NOSA30 capture the seasonal features of precipitation in the study area. Quantitatively, only the southern sub-catchments of Ecuador and northern Peru (3.6-6 • S) are relatively well estimated by both products. The accuracy is considerably less in the northern and central basins of Ecuador (0-3.6 • S). It is shown that the probability of detection (POD) is better for light precipitation (POD decreases from 0.6 for rates less than 5 mm day −1 to 0.2 for rates higher than 20 mm day −1 ). Compared to its predecessor, 3B42 V7 shows modest regionwide improvements in reducing biases. The improvement is specific to the coastal and open ocean sub-catchments. In view of hydrological applications, the correlation of TRMM and OA-NOSA30 estimates with observations increases with time aggregation. The correlation is higher for the monthly time aggregation in comparison with the daily, weekly, and 15-day time scales. Furthermore, it is found that TRMM performs better than OA-NOSA30 in generating the spatial distribution of mean annual precipitation.

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Evaluation of precipitation products over complex mountainous terrain: A water resources perspective

Cited by 146 publications

References 34 publications

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Validation of Satellite Precipitation (Trmm 3b43) in Ecuadorian Coastal Plains, Andean Highlands and Amazonian Rainforest

Evaluation of TRMM 3B42 precipitation estimates and WRF retrospective precipitation simulation over the Pacific–Andean region of Ecuador and Peru

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