An evaluation of high-resolution multisatellite rainfall products over the Indian monsoon region

Prakash, Satya; Sathiyamoorthy, V.; Mahesh, C.; Gairola, R. M.

doi:10.1080/01431161.2014.894661

Cited by 88 publications

(61 citation statements)

References 59 publications

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“…Several statistical indices (continuous evaluation indices and categorical indices) were adhered for investigation of accuracy (of TMPA precipitation products) in terms of consistency and discrepancy [25,31]. Consistency shows the propinquity or similarity between rain gauge and TMPA-based precipitation estimates, whereas the discrepancy refers to the difference or the ratio between the observed (gauge-based) and estimated (satellite-based) precipitation estimates [32].…”

Section: Methods For Accuracy Assessmentmentioning

confidence: 99%

Evaluation and Comparison of TRMM Multi-Satellite Precipitation Products With Reference to Rain Gauge Observations in Hunza River Basin, Karakoram Range, Northern Pakistan

et al. 2017

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Abstract:The performance evaluation of satellite-based precipitation products at local and regional scales is crucial for modification in satellite-based precipitation retrieval algorithms, as well as for the provision of guidance during the selection of substitute precipitation data. This study evaluated the performances of three Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products (3B42V6, 3B42RT and 3B42V7) with a reference to rain gauge observations in the Hunza River basin, northern Pakistan. Multi-spatial (pixel and basin) and temporal (daily, monthly, seasonal and annual) resolutions were considered for performance evaluation of TMPA products. Results revealed that the spatial pattern of observed precipitation over the basin was adequately captured by 3B42V7 but misplaced by 3B42V6 and 3B42RT. All TMPA products were unable to capture the intense precipitation events. On the daily time scale, the performance of TMPA products was very poor over both spatial scales. 3B42V6 underestimated the precipitation (31.25% and 44.27% on pixel and basin scales, respectively). By contrast, 3B42RT significantly overestimated the precipitation (47.91% and 38.62% on pixel and basin scales, respectively), while 3B42V7 showed overestimation (17.30%) on pixel scale and slight underestimation (6.24%) on the basin scale. On the seasonal scale, TMPA products showed significant biases with observed precipitation data. We found that the TMPA products performed relatively better on monthly and annual time scales and overall performance of 3B42V7 product was better than that of 3B42V6 and 3B42RT. The bias in 3B42V7 was improved by 85.90% compared with 3B42V6 and by 116.16% compared with 3B42RT. Thus, it is concluded that the TMPA products were unreliable to capture the intense precipitation events and retain high errors on daily and seasonal scales. Therefore, caution should be considered while using these precipitation estimates as a substitute data in hydrology, meteorology and climatology studies in Hunza River basin. However, due to the reasonable performance of monthly and annual 3B42V7 estimates, these can be used as an acceptable substitute for applications in the region.

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Section: Methods For Accuracy Assessmentmentioning

confidence: 99%

Evaluation and Comparison of TRMM Multi-Satellite Precipitation Products With Reference to Rain Gauge Observations in Hunza River Basin, Karakoram Range, Northern Pakistan

et al. 2017

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“…1, several evaluation studies exist in the literature focusing on the assessment of seasonal rainfall over India (Uma et al, 2013;Prakash et al, 2014;Sunilkumar et al, 2015), but none of them dealt with high-resolution (temporal) measurements. This aspect has been studied in detail in this section, in which the focus is primarily on the validation of high-resolution MPEs using a variety of metrics and statistical distributions and also on the diurnal cycle of rainfall.…”

Section: Validation Of High-resolution Mpesmentioning

confidence: 99%

“…It is, therefore, highly essential to perform validation independently at finer temporal scales over different climatic regions. As mentioned above, the evaluation of MPEs for monthly and seasonal monsoon precipitation was done to some extent over India (Rahman et al, 2009;Uma et al, 2013;Prakash et al, 2014;Sunilkumar et al, 2015). However, a detailed study on the validation of MPEs at shorter timescales (sub-daily and daily) does not exist due to the lack of suitable measurements.…”

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confidence: 99%

“…Therefore, validation of high-resolution MPEs and quantification of their errors are essential before utilizing them further for operational or research applications. Thus far, a great deal of effort has been put into evaluating the MPEs in different climatic conditions (GlobalAdler et al (2001); Turk et al (2008); Australia, United States of America (USA) and northwestern Europe - Ebert et al (2007); Africa and South America - Dinku et al (2010); India - Prakash et al (2014); Sunilkumar et al (2015); IranGhajarnia et al (2015); China -Chen et al (2015), and references therein) and seasons (Tian et al, 2007;Kidd et al, 2012;Sunilkumar et al, 2015). Though several studies exist on the evaluation of monthly to seasonal rainfall in the literature, only a few studies focused on validating the rainfall at daily and sub-daily scales (Sapiano and Arkin, 2009;Sohn et al, 2010;Habib et al, 2012;Kidd et al, 2012;Mehran and AghaKouchak, 2014).…”

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confidence: 99%

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Assessment of small-scale variability of rainfall and multi-satellite precipitation estimates using measurements from a dense rain gauge network in Southeast India

Sunilkumar

Rao

Satheeshkumar

2016

Hydrol. Earth Syst. Sci.

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Abstract. This paper describes the establishment of a dense rain gauge network and small-scale variability in rain events (both in space and time) over a complex hilly terrain in Southeast India. Three years of high-resolution gauge measurements are used to validate 3-hourly rainfall and subdaily variations of four widely used multi-satellite precipitation estimates (MPEs). The network, established as part of the Megha-Tropiques validation program, consists of 36 rain gauges arranged in a near-square grid area of 50 km × 50 km with an intergauge distance of 6-12 km. Morphological features of rainfall in two principal rainy seasons (southwest monsoon, SWM, and northeast monsoon, NEM) show marked differences. The NEM rainfall exhibits significant spatial variability and most of the rainfall is associated with large-scale/long-lived systems (during wet spells), whereas the contribution from small-scale/short-lived systems is considerable during the SWM. Rain events with longer duration and copious rainfall are seen mostly in the western quadrants (a quadrant is 1/4 of the study region) in the SWM and northern quadrants in the NEM, indicating complex spatial variability within the study region. The diurnal cycle also exhibits large spatial and seasonal variability with larger diurnal amplitudes at all the gauge locations (except for 1) during the SWM and smaller and insignificant diurnal amplitudes at many gauge locations during the NEM. On average, the diurnal amplitudes are a factor of 2 larger in the SWM than in the NEM. The 24 h harmonic explains about 70 % of total variance in the SWM and only ∼ 30 % in the NEM. During the SWM, the rainfall peak is observed between 20:00 and 02:00 IST (Indian Standard Time) and is attributed to the propagating systems from the west coast during active monsoon spells. Correlograms with different temporal integrations of rainfall data (1, 3, 12, 24 h) show an increase in the spatial correlation with temporal integration, but the correlation remains nearly the same after 12 h of integration in both monsoon seasons. The 1 h resolution data show the steepest reduction in correlation with intergauge distance and the correlation becomes insignificant after ∼ 30 km in both monsoon seasons.Validation of high-resolution rainfall estimates from various MPEs against the gauge rainfall data indicates that all MPEs underestimate the light and heavy rain. The MPEs exhibit good detection skills of rain at both 3 and 24 h resolutions; however, considerable improvement is observed at 24 h resolution. Among the different MPEs investigated, the Climate Prediction Centre morphing technique (CMORPH) performs better at 3-hourly resolution in both monsoons. The performance of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) is much better at daily resolution than at 3-hourly, as evidenced by better statistical metrics than the other MPEs. All MPEs captured the basic shape of the diurnal cycle and the amplitude quite well, but failed to reproduce the weak/insign...

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“…Some selected examples of such studies are as follows: Nile Basin (Habib et al 2012); Iran (Katiraie-Boroujerdy et al 2013;Moazami et al 2013); Yangtze River Basin (Li et al 2013); Ganjiang River Basin, China (Hu et al 2013); and India (Prakash et al 2014). Some few other studies use a single environmental factor, mostly elevation (Dinku et al 2008;Dinku et al 2009;Hu et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

Rahmawati

Lubczynski

2017

Theor Appl Climatol

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Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH 25 , CMORPH 8 , TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH 25 , CMORPH 8 , and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH 25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH 25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day −1 rain events. Lastly, the CMORPH 25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH 8 .

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An evaluation of high-resolution multisatellite rainfall products over the Indian monsoon region

Cited by 88 publications

References 59 publications

Evaluation and Comparison of TRMM Multi-Satellite Precipitation Products With Reference to Rain Gauge Observations in Hunza River Basin, Karakoram Range, Northern Pakistan

Evaluation and Comparison of TRMM Multi-Satellite Precipitation Products With Reference to Rain Gauge Observations in Hunza River Basin, Karakoram Range, Northern Pakistan

Assessment of small-scale variability of rainfall and multi-satellite precipitation estimates using measurements from a dense rain gauge network in Southeast India

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

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