Capabilities of Satellite-Derived Datasets to Detect Consecutive Indian Monsoon Droughts of 2014 and 2015

Prakash, Satya

doi:10.18520/cs/v114/i11/2362-2368

“…CHIRP estimates precipitation based on infrared Cold Cloud Duration observations while, CHIRPS estimates precipitation also merges multiple data, such as tropical rainfall measuring mission multi-satellite precipitation analysis (TMPA), CMORPH, and global geosynchronous TIR archives, etc 22 . CHIRP/S has shown a good correlation with observations in East Africa 50 , and South Asia 51 . CHIRPS were strongly recommended for agricultural and hydrological research because of their excellent performance.…”

Section: Discussionmentioning

confidence: 58%

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam

Gummadi

¹

,

Dinku²,

Shirsath

³

et al. 2022

Sci Rep

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High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges.

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“…CHIRP estimates precipitation based on infrared Cold Cloud Duration observations while, CHIRPS estimates precipitation also merges multiple data, such as tropical rainfall measuring mission multi-satellite precipitation analysis (TMPA), CMORPH, and global geosynchronous TIR archives, etc 22 . CHIRP/S has shown a good correlation with observations in East Africa 59 , and South Asia 60 . CHIRPS were strongly recommended for agricultural and hydrological research because of their excellent performance.…”

Section: Crop Models Validationmentioning

confidence: 58%

Spatial and Temporal Evaluation of Satellite Rainfall Estimates Over Vietnam

Gummadi

¹

,

Dinku

²

,

Shirsath

³

et al. 2021

Preprint

1

0

View full text Add to dashboard Cite

High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges.

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“…The cloud-free daily LST product -MYD11C1 Collection 6 (Wan et al, 2015) for January 2003 to December 2017 has been considered in this study. Collection 6 LST products showed notable differences from Collection 5 products, particularly over the global arid regions (Prakash et al, 2018). The accuracy of Collection 6 LST products was shown to be better than that of Collection 5 products due to substantial improvement in the retrieval algorithms (Wan, 2014;Duan et al, 2019).…”

Section: Data Usedmentioning

confidence: 99%

“…Land surface temperature (LST), also known as land skin temperature, is one of the crucial parameters for the study of surface energy budget, land surface processes, urban heat islands, and for the retrieval of several atmospheric variables (Li et al, 2013;Norouzi et al, 2015a;Didari et al, 2017;Deilami et al, 2018;Prakash et al, 2018;Susskind et al, 2019). LST also plays a key role in the land surface model data assimilation.…”

Section: Introductionmentioning

confidence: 99%

“…LST measurements from the polar-orbiting satellites are generally used as reference for validating LST derived from the geostationary satellites over in-situ data sparse regions (Singh et al, 2016). LST estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the polar-orbiting Aqua and Terra satellites have been widely used for various applications at global and regional scales (Li et al, 2013;Prakash et al, 2016Prakash et al, , 2018Deilami et al, 2018;Phan and Kappas, 2018;Sharifnezhadazizi et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Land surface temperature variability across India: a remote sensing satellite perspective

Prakash

¹

,

Norouzi

²

2019

Theor Appl Climatol

Self Cite

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Land surface temperature (LST) plays a key role in the surface energy budget computation and land surface process studies. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua and Terra satellites provide comprehensive global LST estimates at a fine spatial resolution. The MODIS products were recently upgraded to Collection 6, and shown to be more accurate than its predecessor Collection 5 products. In this study, LST and its variability have been examined across India from Collection 6 of the Aqua MODIS data at 0.05°s patial resolution for the period of 2003 to 2017. All-India mean LST characteristics show distinctive features as compared to the well-documented mean characteristics of near-surface air temperature. All land cover types except permanent snow & ice, and cold desert areas exhibit bimodal peaks in seasonal variations of daytime LST. The daytime LST over the coldest and high-altitude regions of northern India shows anomalous positive linear relationship with NDVI at a monthly scale. However, monthly domain-mean daytime LST of cropland regions is largely negatively correlated with NDVI as compared to other land cover types. Results reveal that about 17% of the Indian landmass received its hottest LST during 2010 followed by 2016. Linear trend analysis for the 15-year period of mean annual LST shows a decrease in diurnal temperature range over most parts of the country due to rather rapid increase in nighttime LST than daytime LST, similar as changes in near-surface air temperature across the country.

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Capabilities of Satellite-Derived Datasets to Detect Consecutive Indian Monsoon Droughts of 2014 and 2015

Abstract: Processing of the papain precursor. The ionization state of a conserved amino acid motif within the Pro region participates in the regulation of intramolecular processing.

Cited by 9 publications

References 31 publications

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam

Spatial and Temporal Evaluation of Satellite Rainfall Estimates Over Vietnam

Land surface temperature variability across India: a remote sensing satellite perspective

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