How well do CMIP5 climate simulations replicate historical trends and patterns of meteorological droughts?

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin; Damberg, Lisa; Phillips, T. J.; Miao, Chiyuan; Hsu, Kuolin; Sorooshian, Soroosh

doi:10.1002/2014wr016318

Cited by 93 publications

(76 citation statements)

References 68 publications

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“…In particular, Nasrollahi et al . () investigated the spatio‐temporal robustness of CMIP5 climate models across the globe, and their results suggest that most CMIP5 models agreed with observed global trends in projecting the extent and severity of future drought conditions.…”

Section: Methodsmentioning

confidence: 97%

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Kang

Sridhar

2017

J American Water Resour Assoc

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Impacts of climate change on the severity and intensity of future droughts can be evaluated based on precipitation and temperature projections, multiple hydrological models, simulated hydrometeorological variables, and various drought indices. The objective of this study was to assess climate change impacts on future drought conditions and water resources in the Chesapeake Bay (CB) watershed. In this study, the Soil and Water Assessment Tool (SWAT) and the Variable Infiltration Capacity model were used to simulate a Modified Palmer Drought Severity Index (MPDSI), a Standardized Soil Moisture index (SSI), a Multivariate Standardized Drought Index (MSDI), along with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for both historical and future periods (f1: 2020-2049, f2: 2050-2079). The results of the SSI suggested that there was a general increase in agricultural droughts in the entire CB watershed because of increases in surface and groundwater flow and evapotranspiration. However, MPDSI and MSDI showed an overall decrease in projected drought occurrences due to the increases in precipitation in the future. The results of this study suggest that it is crucial to use multiple modeling approaches with specific drought indices that combine the effects of both precipitation and temperature changes.(KEY TERMS: drought projection; climate change; drought indices; hydrologic models.) Kang, Hyunwoo and Venkataramana Sridhar, 2018. Assessment of Future Drought Conditions in the Chesapeake Bay Watershed.

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Section: Methodsmentioning

confidence: 97%

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Kang

Sridhar

2017

J American Water Resour Assoc

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“…This result may be attributed to the lack of ground-based observations before 1950 (i.e., most of P1). As suggested in previous studies (i.e., Becker et al, 2013;Vittal et al, 2013;Nasrollahi et al, 2015), the limited availability of data in the early 20th century can result in underestimates of the spatial variabilities of climate variables in global datasets; in the present study, such limited data availability might have contributed to the reduced SPEI variance in P1 in East Asia and West Africa. Based on regional averages, the role of the reference period is not clear; thus, we investigate the spatial patterns of SPEI-12 hereafter.…”

Section: Temporal Patterns Of the Drought Indexmentioning

confidence: 49%

“…For meteorological droughts, the indices include the PDSI (Palmer, 1965), the SPI (McKee et al, 1993) and the SPEI (Vicente-Serrano et al, 2010). As different studies have used different meteorological drought indices (Seneviratne, 2012;Sheffield et al, 2012;Trenberth et al, 2014;Nasrollahi et al, 2015;Touma et al, 2015), this study focuses on the SPEI. Devised by Vicente-Serrano et al (2010), the SPEI has the advantage of considering the effects of temperature variability on drought relative to the SPI (Naumann et al, 2014).…”

Section: Meteorological Drought Indexmentioning

confidence: 99%

“…Wang et al (2011) defined the intensityduration-frequency of droughts with the SPI, standardized runoff index (SRI), standardized soil water index (SSWI) derived from observations and future regional climate change projections in central Illinois. To evaluate how well global climate models simulated observed drying or wetting trends, Nasrollahi et al (2015) applied the Mann-Kendall trend test to SPIs derived from global observational climate data, in this case, the dataset from the Climate Research Unit (CRU), and 41 predictions of global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Similarly, Tan et al (2015) utilized climate data from 22 meteorological stations in Ningxia, a well-known food production area in Northwest China, and performed Mann-Kendall trend tests with the SPI and SPEI.…”

Section: Introductionmentioning

confidence: 99%

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Effects of different reference periods on drought index (SPEI) estimations from 1901 to 2014

Kim

Park

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. This study aims to understand how different reference periods (i.e., calibration periods) of climate data used to estimate drought indices influence regional drought assessments. Specifically, we investigate the influences of different reference periods on historical drought characteristics, such as the trend, frequency, intensity and spatial extent, using the standardized precipitation evapotranspiration index (SPEI) with a 12-month lag (SPEI-12), which was estimated from the datasets of the Climate Research Unit (CRU) and the University of Delaware (UDEL). For the 1901-1957 (P1) and 1958-2014 (P2) estimation periods, three different types of reference periods are used to compute the SPEI: P1 and P2 together, P1 and P2 separately and P1 only. Focusing on East Asia, Europe, the United States and West Africa, we find that the influence of the reference period is significant in East Asia and West Africa, with dominant drying trends from P1 to P2. The reference period influenced the assessment of drought characteristics, particularly the severity and spatial extent, whereas the influence on the frequency was relatively small. Finally, self-calibration, which is the most common practice for indices such as the SPEI, tends to underestimate the drought severity and spatial extent relative to the other approaches used in this study. Although the conclusions drawn in this study are limited by the use of two global datasets, they highlight the need for clarification of the reference period in drought assessments to better understand regional drought characteristics and the associated temporal changes, particularly under climate change scenarios.

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“…A drought may last for weeks, months or even decades and may affect local regions or continents. Therefore, droughts can have devastating impacts on both natural and human systems by affecting the crop yield, infrastructure, industry and tourism (Wilhite, ; Nasrollahi et al ., ; Xu et al ., ). For example, Hoerling et al .…”

Section: Introductionmentioning

confidence: 99%

Evaluating historical drought characteristics simulated in CORDEX East Asia against observations

Kim

2017

Intl Journal of Climatology

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This study aims to understand how well regional climate models (RCMs) reproduce the observed characteristics of droughts based on the standardized precipitation evapotranspiration index (SPEI) over East Asia. While RCMs from CORDEX East Asia have been evaluated in terms of the mean and extreme values of precipitation and air temperature in the literature, their performance based on drought characteristics has not been revealed. Therefore, we investigate the temporal characteristics, such as the trend and stationarity, and other drought measures, such as the drought frequency, duration, severity and spatial extent, to determine how well these factors are captured and how they vary among the different models, including four RCMs, their ensemble mean and a driving general circulation model (GCM). The results are compared to a 26‐year observational dataset (1980 to 2005) from APHRODITE. Based on our analyses of the results, the specific findings are as follows. First, based on Mann–Kendall (MK) trend tests, the SPEI shows decreasing trends over the northern part of the domain and no trends in other regions, and these tendencies are captured by a limited number of RCMs. Notably, these trends were not captured by the ensemble mean of RCMs. Second, based on the Phillips–Perron stationarity test, stationarity is dominant in most regions based on both the observations and the RCMs. Third, the frequency decreases with increasing duration in all regions. This tendency is generally captured in the models to varying extents. Fourth, the drought severity decreases with increasing duration in all cases, as expected. However, the drought severity diverges markedly among the RCMs. Finally, estimates of the spatial extent using the RCMs are generally accurate in wet regions but inaccurate in dry regions. Furthermore, the spatial extents of the droughts diverge among the RCMs, and the models fail to accurately capture drought events with large spatial scales.

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How well do CMIP5 climate simulations replicate historical trends and patterns of meteorological droughts?

Cited by 93 publications

References 68 publications

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Effects of different reference periods on drought index (SPEI) estimations from 1901 to 2014

Evaluating historical drought characteristics simulated in CORDEX East Asia against observations

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