The GPCC Drought Index – a new, combined and gridded global drought index

Ziese, Markus; Schneider, Ulrike; Meyer-Christoffer, Anja; Schamm, Kirstin; Vido, Jaroslav; Finger, Peter; Bissolli, Peter; Pietzsch, Silke; Becker, Andreas

doi:10.5194/essd-6-285-2014

Cited by 52 publications

(26 citation statements)

References 23 publications

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“…GPCC Full Data Monthly Product is the most comprehensive gridded rainfall dataset available today and is based on measurements from over 80,000 stations worldwide. When this study was conducted, the dataset covered a period ranging from January 1891 to December 2016 [11,43]. While GPCC data are available at different spatial resolutions, the data with 0.5 • × 0.5 • spatial resolution were used to be consistent with the resolution of the available temperature data.…”

Section: Datasets and Methodsmentioning

confidence: 99%

Long-Term Drought Trends in Ethiopia with Implications for Dryland Agriculture

Temam

Uddameri

Mohammadi

et al. 2019

Water

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Intraseason and seasonal drought trends in Ethiopia were studied using a suite of drought indicators—standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI) and Z-index for Meher (long-rainy), Bega (dry), and Belg (short-rainy) seasons—to identify drought-causing mechanisms. Trend analysis indicated shifts in late-season Meher precipitation into Bega in the southwest and southcentral portions of Ethiopia. Droughts during Bega (October–January) are largely temperature controlled. Short-term temperature-controlled hydrologic processes exacerbate rainfall deficits during Belg (February–May) and highlight the importance of temperature- and hydrology-induced soil dryness on production of short-season crops such as tef. Droughts during Meher (June–September) are largely driven by precipitation declines arising from the narrowing of the intertropical convergence zone (ITCZ). Increased dryness during Meher has severe consequences on the production of corn and sorghum. PDSI is an aggressive indicator of seasonal droughts suggesting the low natural resilience to combat the effects of slow-acting, moisture-depleting hydrologic processes. The lack of irrigation systems in the nation limits the ability to combat droughts and improve agricultural resilience. There is an urgent need to monitor soil moisture (a key agro-hydrologic variable) to better quantify the impacts of meteorological droughts on agricultural systems in Ethiopia.

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Section: Datasets and Methodsmentioning

confidence: 99%

Long-Term Drought Trends in Ethiopia with Implications for Dryland Agriculture

Temam

Uddameri

Mohammadi

et al. 2019

Water

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“…The GPCC full data reanalysis monthly product is comprised of monthly totals on a regular grid with 0.5° spatial grid spacing. Based on 67200 stations worldwide, GPCC data was regarded with high accuracy383940. Data input for calculating SRI and SSI came from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product.…”

Section: Methodsmentioning

confidence: 99%

Droughts in India from 1981 to 2013 and Implications to Wheat Production

Zhang

Obringer

Wei

et al. 2017

Sci Rep

100

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Understanding drought from multiple perspectives is critical due to its complex interactions with crop production, especially in India. However, most studies only provide singular view of drought and lack the integration with specific crop phenology. In this study, four time series of monthly meteorological, hydrological, soil moisture, and vegetation droughts from 1981 to 2013 were reconstructed for the first time. The wheat growth season (from October to April) was particularly analyzed. In this study, not only the most severe and widespread droughts were identified, but their spatial-temporal distributions were also analyzed alone and concurrently. The relationship and evolutionary process among these four types of droughts were also quantified. The role that the Green Revolution played in drought evolution was also studied. Additionally, the trends of drought duration, frequency, extent, and severity were obtained. Finally, the relationship between crop yield anomalies and all four kinds of drought during the wheat growing season was established. These results provide the knowledge of the most influential drought type, conjunction, spatial-temporal distributions and variations for wheat production in India. This study demonstrates a novel approach to study drought from multiple views and integrate it with crop growth, thus providing valuable guidance for local drought mitigation.

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“…It covers a period ranging from January 1891-December 2016, when this study was conducted. The GPCC Full Data Monthly Product is the most accurate in situ precipitation reanalysis data set of GPCC, and aims to support regional climate monitoring, model validation, climate variability analyses, and water resources assessment studies (e.g., Becker et al [66], Zeise et al [67]). It is also noted to provide representative coverage in Ethiopia [7], and as such, was deemed suitable for this study.…”

Section: Data Compilationmentioning

confidence: 99%

Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia

Tsige

Uddameri

Forghanparast

et al. 2019

Water

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Meteorological drought indicators are commonly used for agricultural drought contingency planning in Ethiopia. Agricultural droughts arise due to soil moisture deficits. While these deficits may be caused by meteorological droughts, the timing and duration of agricultural droughts need not coincide with the onset of meteorological droughts due to soil moisture buffering. Similarly, agricultural droughts can persist, even after the cessation of meteorological droughts, due to delayed hydrologic processes. Understanding the relationship between meteorological and agricultural droughts is therefore crucial. An evaluation framework was developed to compare meteorologicaland agriculture-related drought indicators using a suite of exploratory and confirmatory tools. Receiver operator characteristics (ROC) was used to understand the covariation of meteorological and agricultural droughts. Comparisons were carried out between SPI-2, SPEI-2, and Palmer Z-index to assess intraseasonal droughts, and between SPI-6, SPEI-6, and PDSI for full-season evaluations. SPI was seen to correlate well with selected agriculture-related drought indicators, but did not explain all the variability noted in them. The correlation between meteorological and agricultural droughts exhibited spatial variability which varied across indicators. SPI is better suited to predict non-agricultural drought states than agricultural drought states. Differences between agricultural and meteorological droughts must be accounted for in order to devise better drought-preparedness planning.

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The GPCC Drought Index – a new, combined and gridded global drought index

Cited by 52 publications

References 23 publications

Long-Term Drought Trends in Ethiopia with Implications for Dryland Agriculture

Long-Term Drought Trends in Ethiopia with Implications for Dryland Agriculture

Droughts in India from 1981 to 2013 and Implications to Wheat Production

Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia

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