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WIREs Clim Change
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Drought under global warming: a review

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This article reviews recent literature on drought of the last millennium, followed by an update on global aridity changes from 1950 to 2008. Projected future aridity is presented based on recent studies and our analysis of model simulations. Dry periods lasting for years to decades have occurred many times during the last millennium over, for example, North America, West Africa, and East Asia. These droughts were likely triggered by anomalous tropical sea surface temperatures (SSTs), with La Niña‐like SST anomalies leading to drought in North America, and El‐Niño‐like SSTs causing drought in East China. Over Africa, the southward shift of the warmest SSTs in the Atlantic and warming in the Indian Ocean are responsible for the recent Sahel droughts. Local feedbacks may enhance and prolong drought. Global aridity has increased substantially since the 1970s due to recent drying over Africa, southern Europe, East and South Asia, and eastern Australia. Although El Niño‐Southern Oscillation (ENSO), tropical Atlantic SSTs, and Asian monsoons have played a large role in the recent drying, recent warming has increased atmospheric moisture demand and likely altered atmospheric circulation patterns, both contributing to the drying. Climate models project increased aridity in the 21st century over most of Africa, southern Europe and the Middle East, most of the Americas, Australia, and Southeast Asia. Regions like the United States have avoided prolonged droughts during the last 50 years due to natural climate variations, but might see persistent droughts in the next 20–50 years. Future efforts to predict drought will depend on models' ability to predict tropical SSTs. WIREs Clim Change 2011 2 45–65 DOI: 10.1002/wcc.81

This article is categorized under:

  • Paleoclimates and Current Trends > Detection and Attribution
  • Paleoclimates and Current Trends > Modern Climate Change
  • Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
  • Assessing Impacts of Climate Change > Observed Impacts of Climate Change
Figure 1.

Time series of the tree‐ring reconstructed PDSI (<−1 for drought) averaged over western North America (25°–50°N, 95°–125°W) from 1000 to 2003 AD (Reprinted with permission from Ref 49.)

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Figure 2.

Time series of percentage area (left ordinate) and actual area (right ordinate) over eastern China (22°–40°N, 105°–122°E) in very dry conditions (severe drought or worse) during the last five centuries, created using GIS technique based on the network of the drought/flood index in China of Zhang et al.55 Severe, extreme, and exceptional drought years stand out, with area percentages reaching 20, 30 and 40%, respectively. (Reprinted with permission from Ref 74. Copyright 2007 Springer.)

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Figure 3.

Annual time series averaged over the Sahel (18°W–20°E, 10°N–20°N, land only) for observed precipitation from 1921 to 2008 (black), Palmer Drought Severity Index (PDSI) (red) and CLM3‐simulated top‐1 m soil moisture content (green). The precipitation and soil moisture are shown as normalized anomalies in units of standard deviation (SD).

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Figure 4.

Historical fluctuations in African lake levels since 1800 (higher values for wet periods). Except for Lake Ngami, solid lines indicate modern measurements, short dashed lines indicate historical information, and long dashed lines indicate general trends. (Reprinted with permission from Ref 79. Copyright 2001 Springer.)

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Figure 5.

Trend maps for observed annual (a) surface air temperature (from HadCRUT3: http://www.cru.uea.ac.uk/cru/data/temperature/), (b) precipitation (see text for data sources), and (c) runoff inferred from streamflow records. (Panel c reprinted with permission from Ref 99. Copyright 2002 American Meteorological Society.)

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Figure 6.

(left) Temporal (black) and (right) spatial patterns of the two leading EOFs of monthly PDSI from 1900 to 2008 (normalized by its standard deviation prior to the EOF analysis). Red (blue) areas are dry (wet) for a positive temporal coefficient on the corresponding PC time series [e.g., the red (blue) areas in panel (b) represent a drying (moistening) trend whose temporal pattern is shown in panel (a)]. Variations on <2‐year time scales were filtered out in plotting the left panels (but retained in the EOF analysis). Also shown in panel (c) is the normalized Darwin mean sea‐level pressure anomaly shifted to the right (i.e., lead) by 6 months to obtain a maximum correlation (r = 0.63) with the PC 2 time series. (a) The percentage variance explained by the EOF is shown on the top of the left panels.

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Figure 7.

Maps of annual trends (red = drying) from 1950 to 2008 in PDSI (change per 50 years) with potential evapotranspiration (PE) calculated using the (a) Thornthwaite and (b) Penman‐Monteith (PM) equation, and (c) annual trends in self‐calibrated PDSI with the PM potential evaporation. Also shown (d) is the trend in top‐1 m soil moisture content (mm/50 years) from 948 to 2004 simulated by a land surface model (CLM3) forced by observation‐based atmospheric forcing (see Ref 29 for details).

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Figure 8.

Global land (60°S–75°N) averaged annual time series of top 1 m soil moisture anomaly (mm) simulated by a land surface model (CLM3) forced with observation‐based estimates of monthly temperature, precipitation, and solar radiation with intra‐monthly variations from the NCEP‐NCAR (black) and ERA‐40 (green) reanalysis (see Ref 29 for details), compared with the similarly averaged PDSI time series computed with both observed temperature and precipitation (red solid line for PDSI with Thornthwaite PE and magenta for PDSI with Penman‐Monteith PE) and precipitation only (i.e., no temperature changes, dashed lines). Results for averages over 40°S–40°N land areas are very similar. The SC‐PDSI_pm is similar to the PDSI_pm.

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Figure 9.

Time series of global dry areas (defined locally as the bottom 20 percentiles) as a percentage of the global (60°S–75°N) land area based on the CLM3‐simulated top‐1 m soil moisture content (green), and PDSI calculated with both observed precipitation and temperature and Thornthwaite (red solid line) and Penman‐Monteith (magenta solid line) PE, and with precipitation only (dashed lines). Monthly data were used in the PDSI and PE calculations with variations on <12‐month time scales were filtered out before plotting.

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Figure 10.

Multi‐model mean changes from 1980–1999 to 2080–2099 under the SRES A1B scenario in annual (a) precipitation (mm/day), (b) soil moisture (%), (c) runoff (mm/day), and (d) evaporation (mm/day). The stippling indicates where at least 80% of the models agree on the sign of the mean change. (Reprinted with permission from Ref 114. Copyright 2007 Cambridge University Press.)

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Figure 11.

Mean annual sc‐PDSI_pm for years (a) 1950–1959, (b) 1975–1984, (c) 2000–2009, (d) 2030–2039, (e) 2060–2069, and (f) 2090–2099 calculated using the 22‐model ensemble‐mean surface air temperature, precipitation, humidity, net radiation, and wind speed used in the IPCC AR4 from the 20th century and SRES A1B 21st century simulations.128 Red to pink areas are extremely dry (severe drought) conditions while blue colors indicate wet areas relative to the 1950–1979 mean.

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