Evaluation of satellite-derived agro-climate variables in the Northern Great Plains of the United States

Lemons, Rebecca; Hewitt, Andrea; Kharel, Gehendra; Kirilenko, Andrei; Zhang, Xiaodong

doi:10.1080/10106049.2011.653408

Cited by 2 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( [19,[40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59]; among others) has far outweighed those studying the accuracy, uncertainty, and validation of TMPA data ( [13,18,24,45,60,61]; among others). Even less research has been conducted on the viability of TMPA rainfall products as an adequate substitute for field gauges in data sparse and arid to semi-arid environments [11,18]; arguably the area most critically in need of satellite rainfall.…”

Section: Introductionmentioning

confidence: 99%

Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

2015

View full text Add to dashboard Cite

TRMM Multi-satellite Precipitation Analysis (TMPA) satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7) against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7) outperforms the previous version (V6), particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission. OPEN ACCESSRemote Sens. 2015, 7 5698

show abstract

Section: Introductionmentioning

confidence: 99%

Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

2015

View full text Add to dashboard Cite

show abstract

Tracking the error sources of spatiotemporal differences in TRMM accuracy using error decomposition method

Wang

Chen

et al. 2018

Hydrology Research

View full text Add to dashboard Cite

Tropical Rainfall Measuring Mission (TRMM) products are widely utilized, but the causes of the differences in their spatiotemporal accuracy require further investigation to improve satellite precipitation estimation. In this study, the spatiotemporal accuracy of TRMM 3B42 V7 data was systematically evaluated using the rain gauge data of the densely gauged Xiangjiang River basin, a humid region in South China. The effects of the precipitation intensity and elevation on different error components derived from the error decomposition method were analysed to reveal the causes of spatiotemporal differences of the data errors. The results showed the following. (1) TRMM performs better in the wet season than in the dry season, and it underestimates precipitation in winter and in high-elevation areas. (2) Precipitation intensity directly influences the occurrence and magnitude of error components. Most of the missed precipitation (precipitation detected only by rain-gauged data) and false precipitation (precipitation detected only by TRMM data) occur in low-intensity precipitation events. Hit events (precipitation detected by both TRMM and rain-gauged data) tend to overestimate low-intensity precipitation and underestimate high-intensity precipitation. Elevation has no direct relation with daily bias, but affects the distribution of occurrence and intensity of precipitation events. (3) Missed precipitation is the main contributing source of error in winter. The negative error increases in high-elevation areas, which is contributed by the larger proportion of high intensity hit precipitation and the missed events. This study is not only beneficial for understanding the effect of topography and climate factors on the accuracy of TRMM precipitation data but also provides a reference for the application and error improvement of satellite precipitation products.

show abstract

Evaluation of satellite-derived agro-climate variables in the Northern Great Plains of the United States

Cited by 2 publications

References 34 publications

Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

Tracking the error sources of spatiotemporal differences in TRMM accuracy using error decomposition method

Contact Info

Product

Resources

About