1 Nature 2012 Vol: 491(7424):435-438. DOI: 10.1038/nature11575

Little change in global drought over the past 60 years

Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming. Previous assessments of historic changes in drought over the late twentieth and early twenty-first centuries indicate that this may already be happening globally. In particular, calculations of the Palmer Drought Severity Index (PDSI) show a decrease in moisture globally since the 1970s with a commensurate increase in the area in drought that is attributed, in part, to global warming. The simplicity of the PDSI, which is calculated from a simple water-balance model forced by monthly precipitation and temperature data, makes it an attractive tool in large-scale drought assessments, but may give biased results in the context of climate change. Here we show that the previously reported increase in global drought is overestimated because the PDSI uses a simplified model of potential evaporation that responds only to changes in temperature and thus responds incorrectly to global warming in recent decades. More realistic calculations, based on the underlying physical principles that take into account changes in available energy, humidity and wind speed, suggest that there has been little change in drought over the past 60 years. The results have implications for how we interpret the impact of global warming on the hydrological cycle and its extremes, and may help to explain why palaeoclimate drought reconstructions based on tree-ring data diverge from the PDSI-based drought record in recent years.

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Figures
Figure 1: Global average time series of the PDSI and area in drought. a, PDSI_Th (blue line) and PDSI_PM (red line). b, Area in drought (PDSI <−3.0) for the PDSI_Th (blue line) and PDSI_PM (red line). The shading represents the range derived from uncertainties in precipitation (PDSI_Th and PDSI_PM) and net radiation (PDSI_PM only). Uncertainty in precipitation is estimated by forcing the PDSI_Th and PDSI_PM by four alternative global precipitation data sets. Uncertainty from net radiation is estimated by forcing the PDSI_PM with a hybrid empirical–satellite data set31 and an empirical estimate. The other near-surface meteorological data are from a hybrid reanalysis–observational data set31. The thick lines are the mean values of the different PDSI data sets. The time series are averaged over global land areas excluding Greenland, Antarctica and desert regions with a mean annual precipitation of less than 0.5 mm d−1. Figure 2: Trends in the PDSI and PE. a, c, e, Non-parametric trends for 1950–2008 in annual average PDSI (averaged over the results using the four precipitation data sets and, for the PDSI_PM, also over the two net radiation data sets) from the PDSI_Th (a) and the PDSI_PM (c), and their difference (e). b, d, f, Non-parametric trends for 1950–2008 in annual average PE from the Thornthwaite equation (b) and the PM equations (d), and their difference (f). Values are not shown for Greenland, Antarctica and desert regions with a mean annual precipitation of less than 0.5 mm d−1. Statistically significant trends at the 95% level are indicated by hatching. The difference in trends in e and f and its statistical significance are calculated from the time series of differences between the two data sets.
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References
  1. Sheffield, J.; Wood, E. F. Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations Clim. Dyn. 13, 79-105 (2008) .
    • . . . Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming1, 2, 3 . . .
    • . . . The perceived abundance of drought in the 2000s, such as long-term events in the western United States, southeast Australia and northeast China, and the recent short-term but severe events in Russia and the central United States, hint that climate change may be a forcing factor and this is only likely to get worse, given projected climate warming and precipitation changes for the twenty-first century1, 2 . . .
  2. Dai, A. Drought under global warming: a review Wiley Interdisc. Rev. Clim. Change 2, 45-65 (2010) .
    • . . . Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming1, 2, 3 . . .
    • . . . The perceived abundance of drought in the 2000s, such as long-term events in the western United States, southeast Australia and northeast China, and the recent short-term but severe events in Russia and the central United States, hint that climate change may be a forcing factor and this is only likely to get worse, given projected climate warming and precipitation changes for the twenty-first century1, 2 . . .
    • . . . It is used pervasively for operational monitoring and increasingly in studies of climate change2, 16 . . .
  3. Seneviratne, S. I.; Field, C. B. , 109-230 (2012) .
    • . . . Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming1, 2, 3 . . .
    • . . . The AR4 summary has been substantially revised, however, in the recent IPCC Special Report on Extremes3 that notes the over-reliance on the PDSI and possible overestimation of the increase in regional and global drought. . . .
    • . . . However, the PDSI has several shortcomings because of its simplicity3, 17, 18, including the treatment of potential evaporation (PE, the evaporative demand of the atmosphere), which is calculated from temperature data by using the empirical Thornthwaite equation7 . . .
  4. Dai, A.; Trenberth, K. E.; Qian, T. A global data set of Palmer Drought Severity Index for 1870–2002: relationship with soil moisture and effects of surface warming J. Hydrometeorol. 5, 1117-1130 (2004) .
    • . . . In particular, calculations of the Palmer Drought Severity Index (PDSI) show a decrease in moisture globally since the 1970s with a commensurate increase in the area in drought that is attributed, in part, to global warming4, 5 . . .
    • . . . The AR4 drew heavily from historic analyses of the PDSI, which shows an increase in drought in the last few decades, regionally5, 14 and globally4, that is commensurate with the increase in global temperatures . . .
    • . . . At continental to global scales its simplicity makes it an attractive choice for reconstructing drought records4, 33, for which it has also been shown to be a proxy for soil moisture4 . . .
    • . . . It has been used to analyse continental-scale to global-scale, long-term variability in drought by several studies (see, for example, refs 4, 34, 35) . . .
  5. Briffa, K. R. van der Schrier, G. & Jones, P. D. Wet and dry summers in Europe since 1750: evidence of increasing drought Int. J. Climatol. 29, 1894-1905 (2009) .
    • . . . In particular, calculations of the Palmer Drought Severity Index (PDSI) show a decrease in moisture globally since the 1970s with a commensurate increase in the area in drought that is attributed, in part, to global warming4, 5 . . .
    • . . . Many studies have attributed the severity and length of recent droughts to global warming5, 12 . . .
    • . . . The AR4 drew heavily from historic analyses of the PDSI, which shows an increase in drought in the last few decades, regionally5, 14 and globally4, that is commensurate with the increase in global temperatures . . .
    • . . . Several regional studies5, 12 have suggested that higher temperatures than normal were the cause for increased drought in recent years through increased evaporation . . .
  6. Roderick, M. L.; Hobbins, M. T.; Farquhar, G. D. Pan evaporation trends and the terrestrial water balance II. Energy balance and interpretation Geog. Compass 3, 761-780 (2009) .
    • . . . The simplicity of the PDSI, which is calculated from a simple water-balance model forced by monthly precipitation and temperature data, makes it an attractive tool in large-scale drought assessments, but may give biased results in the context of climate change6 . . .
    • . . . However, numerous studies based on observations and detailed physical modelling have shown regional declines in evaporative demand over past decades as a result of various combinations of declining radiation, vapour-pressure deficit and/or wind speed6, despite generally increasing regional temperatures. . . .
    • . . . Nevertheless, the regions of decreasing PE trends estimated with the PM model are generally in agreement with the abundance of evidence of decreasing pan evaporation for many regions6, which has been attributed to global dimming, decreases in wind speed and in some places decreasing vapour-pressure deficit20 (see Supplementary Information for further discussion) . . .
    • . . . Despite the long-standing consensus that the underlying science for temperature-based estimates of PE is flawed, compounded by the results of this and other studies6, 21, 22 that the flaws are manifested in errors in the estimations of the impact of warming on drought and hydrology in general, the reasons for the long and continued use of the PDSI_Th for climate studies in essentially its original form are a curiosity . . .
  7. Thornthwaite, C. W. An approach toward a rational classification of climate Geogr. Rev. 38, 55-94 (1948) .
    • . . . Here we show that the previously reported increase in global drought is overestimated because the PDSI uses a simplified model of potential evaporation7 that responds only to changes in temperature and thus responds incorrectly to global warming in recent decades . . .
    • . . . However, the PDSI has several shortcomings because of its simplicity3, 17, 18, including the treatment of potential evaporation (PE, the evaporative demand of the atmosphere), which is calculated from temperature data by using the empirical Thornthwaite equation7 . . .
    • . . . PE is modelled in the PDSI by using the temperature-only-based Thornthwaite method. Thornthwaite7 correlated mean monthly temperature with PE, as determined from the water balance for valleys in the eastern USA, where sufficient moisture was available to maintain active transpiration . . .
  8. Penman, H. L. Natural evaporation from open water, bare soil, and grass Proc. R. Soc. Lond. A 193, 120-145 (1948) .
    • . . . More realistic calculations, based on the underlying physical principles8 that take into account changes in available energy, humidity and wind speed, suggest that there has been little change in drought over the past 60 years . . .
    • . . . It has been well established that evaporation is a function of more than just temperature, and the correct physics includes radiative and aerodynamic controls on evaporative demand8, 19, 20, 21 . . .
  9. Fang, K. Y. Drought variations in the eastern part of northwest China over the past two centuries: evidence from tree rings Clim. Res. 38, 129-135 (2009) .
    • . . . The results have implications for how we interpret the impact of global warming on the hydrological cycle and its extremes, and may help to explain why palaeoclimate drought reconstructions based on tree-ring data diverge from the PDSI-based drought record in recent years9, 10. . . .
    • . . . For some regions, the tree-ring data, which reflect real variations in climatic and non-climatic factors (such as disturbances), diverge from the instrumental-based PDSI_Th in recent decades when warming has been most rapid (see, for example, refs 9, 10) . . .
  10. de Grandpré, L. Seasonal shift in the climate responses of Pinus sibirica, Pinus sylvestris, and Larix sibirica trees from semi-arid, north-central Mongolia Can. J. For. Res. 41, 1242-1255 (2011) .
    • . . . The results have implications for how we interpret the impact of global warming on the hydrological cycle and its extremes, and may help to explain why palaeoclimate drought reconstructions based on tree-ring data diverge from the PDSI-based drought record in recent years9, 10. . . .
    • . . . For some regions, the tree-ring data, which reflect real variations in climatic and non-climatic factors (such as disturbances), diverge from the instrumental-based PDSI_Th in recent decades when warming has been most rapid (see, for example, refs 9, 10) . . .
  11. Sternberg, T. Regional drought has a global impact Nature 472, 169 (2011) .
    • . . . Drought is a major natural hazard that can have devastating impacts on regional agriculture, water resources and the environment, with far-reaching impacts in an increasingly globalized world11 . . .
  12. Cai, W.; Cowan, T.; Briggs, P.; Raupach, M. Rising temperature depletes soil moisture and exacerbates severe drought conditions across southeast Australia Geophys. Res. Lett. 36, L21709 (2009) .
    • . . . Many studies have attributed the severity and length of recent droughts to global warming5, 12 . . .
    • . . . Several regional studies5, 12 have suggested that higher temperatures than normal were the cause for increased drought in recent years through increased evaporation . . .
  13. Solomon, S. , (2007) .
    • . . . Increased drying linked with higher temperatures and decreased precipitation has contributed to changes in drought”13 . . .
    • . . . When used in the PDSI model, which derives soil moisture from the balance between precipitation, evaporation and runoff, the increase in PE drives an increase in drought globally13 in addition to the impact of any changes in precipitation . . .
  14. Wang, J.; Chen, F.; Jin, L.; Bai, H. Characteristics of the dry/wet trend over arid central Asia over the past 100 years Clim. Res. 41, 51-59 (2010) .
    • . . . The AR4 drew heavily from historic analyses of the PDSI, which shows an increase in drought in the last few decades, regionally5, 14 and globally4, that is commensurate with the increase in global temperatures . . .
  15. Palmer, W. C. Meteorological Drought , (1965) .
    • . . . The PDSI was developed originally as an agricultural monitoring tool in the United States in the 1960s15 that helped in allocating aid to stricken farmers . . .
    • . . . Historically, the PDSI15 has been the tool of choice when monitoring and analysing drought occurrence, especially in the United States, where it is one component of the US National Drought Monitor32 . . .
  16. Zhao, M.; Running, S. W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009 Science 329, 940-943 (2010) .
    • . . . It is used pervasively for operational monitoring and increasingly in studies of climate change2, 16 . . .
  17. Alley, W. M. The Palmer Drought Severity Index: limitations and assumptions J. Clim. Appl. Meteorol. 23, 1100-1109 (1984) .
    • . . . However, the PDSI has several shortcomings because of its simplicity3, 17, 18, including the treatment of potential evaporation (PE, the evaporative demand of the atmosphere), which is calculated from temperature data by using the empirical Thornthwaite equation7 . . .
    • . . . Despite this legacy, the PDSI has been shown to be unsuitable for widespread application and suffers from simplifications in its physical basis and soil hydrology17, 37 . . .
  18. Wells, N.; Goddard, S.; Hayes, M. J. A self-calibrating Palmer drought severity index J. Clim. 17, 2335-2351 (2004) .
    • . . . However, the PDSI has several shortcomings because of its simplicity3, 17, 18, including the treatment of potential evaporation (PE, the evaporative demand of the atmosphere), which is calculated from temperature data by using the empirical Thornthwaite equation7 . . .
    • . . . Some of the shortcomings have been addressed by a self-calibrating version18 that removes the spatial inconsistencies. . . .
    • . . . We quantify drought with the original and self-calibrating version of the PDSI model18, which uses the Thornthwaite algorithm (PDSI_Th), and a modified version (PDSI_PM) that uses the PM formulation for PE. . . .
  19. Shuttleworth, W. J.; Maidment, D. R. Handbook of Hydrology , 4.1-4.53 (1993) .
    • . . . It has been well established that evaporation is a function of more than just temperature, and the correct physics includes radiative and aerodynamic controls on evaporative demand8, 19, 20, 21 . . .
    • . . . We use the Thornthwaite algorithm and a physically based estimate based on the currently accepted Penman–Monteith (PM) equation19, 23 forced by our global meteorological data set and a set of alternative precipitation and net radiation data sets (see Methods) . . .
    • . . . ET collapses to PE when the stomatal resistance is zero; the recommended form of the equation19, given as the sum of the radiative and aerodynamic components, is . . .
  20. Roderick, M. L.; Rotstayn, L. D.; Farquhar, G. D.; Hobbins, M. T. On the attribution of changing pan evaporation Geophys. Res. Lett. 34, L17403 (2007) .
    • . . . It has been well established that evaporation is a function of more than just temperature, and the correct physics includes radiative and aerodynamic controls on evaporative demand8, 19, 20, 21 . . .
    • . . . Nevertheless, the regions of decreasing PE trends estimated with the PM model are generally in agreement with the abundance of evidence of decreasing pan evaporation for many regions6, which has been attributed to global dimming, decreases in wind speed and in some places decreasing vapour-pressure deficit20 (see Supplementary Information for further discussion) . . .
  21. Donohue, R. J.; McVicar, T. R.; Roderick, M. L. Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate J. Hydrol. (Amst.) 386, 186-197 (2010) .
    • . . . It has been well established that evaporation is a function of more than just temperature, and the correct physics includes radiative and aerodynamic controls on evaporative demand8, 19, 20, 21 . . .
    • . . . Despite the long-standing consensus that the underlying science for temperature-based estimates of PE is flawed, compounded by the results of this and other studies6, 21, 22 that the flaws are manifested in errors in the estimations of the impact of warming on drought and hydrology in general, the reasons for the long and continued use of the PDSI_Th for climate studies in essentially its original form are a curiosity . . .
    • . . . Of concern is if the perceived influence of warming on drought as quantified by empirical approaches is extrapolated into the future and predictions of the impacts of climate change are likely to be overestimated21, 22, 30 . . .
  22. Shaw, S.; Riha, S. J. Assessing temperature-based PET equations under a changing climate in temperate, deciduous forests Hydrol. Process. 25, 1466-1478 (2011) .
    • . . . Temperature-based PE methods apparently perform relatively well in climatological applications because air temperature is correlated with net radiation and humidity at weekly, monthly and subannual timescales22 . . .
    • . . . Despite the long-standing consensus that the underlying science for temperature-based estimates of PE is flawed, compounded by the results of this and other studies6, 21, 22 that the flaws are manifested in errors in the estimations of the impact of warming on drought and hydrology in general, the reasons for the long and continued use of the PDSI_Th for climate studies in essentially its original form are a curiosity . . .
    • . . . Of concern is if the perceived influence of warming on drought as quantified by empirical approaches is extrapolated into the future and predictions of the impacts of climate change are likely to be overestimated21, 22, 30 . . .
  23. Monteith, J. L. Evaporation and environment Symp. Soc. Exp. Biol. 19, 205-234 (1964) .
    • . . . We use the Thornthwaite algorithm and a physically based estimate based on the currently accepted Penman–Monteith (PM) equation19, 23 forced by our global meteorological data set and a set of alternative precipitation and net radiation data sets (see Methods) . . .
    • . . . The PM approach23 is generally accepted as the most comprehensive algorithm for modelling potential and actual evapotranspiration (given additional estimates of the plant and environmental resistance to atmospheric demand) . . .
  24. Dai, A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008 J. Geophys. Res. 116, D12115 (2011) .
    • . . . Recent studies have claimed that there is little difference between the PDSIs that use the Thornthwaite and PM algorithms (PDSI_Th and PDSI_PM, respectively)24, 25 but this can be attributed to inconsistencies in the forcing data sets and simulation configuration (see Supplementary Information). . . .
  25. van der Schrier, G.; Jones, P. D.; Briffa, K. R. The sensitivity of the PDSI to the Thornthwaite and Penman–Monteith parameterizations for potential evapotranspiration J. Geophys. Res. 116, D03106 (2011) .
    • . . . Recent studies have claimed that there is little difference between the PDSIs that use the Thornthwaite and PM algorithms (PDSI_Th and PDSI_PM, respectively)24, 25 but this can be attributed to inconsistencies in the forcing data sets and simulation configuration (see Supplementary Information). . . .
  26. D’Arrigo, R.; Wilson, R.; Liepert, B.; Cherubini, P. On the ‘Divergence Problem’ in northern forests: a review of the tree-ring evidence and possible causes Global Planet. Change 60, 289-305 (2008) .
    • . . . Similarly, the ‘divergence problem’26 as it relates to reconstructions of temperature from high-latitude and high-elevation tree-ring data may be associated with the assumption that temperature can be used as a surrogate for the controls on growth through variations in evapotranspiration, notwithstanding the competing impacts of other environmental factors (for example, higher concentrations of CO2) . . .
  27. Roderick, M. L.; Farquhar, G. D. Changes in Australian pan evaporation from 1970 to 2002 Int. J. Climatol. 24, 1077-1090 (2004) .
    • . . . It is more plausible that evaporation actually decreases during drought27 because of less precipitation, and that drought drives increases in temperatures because there is less evaporative cooling and thus a higher sensible heat flux warming the air28 . . .
  28. Lockart, N.; Kavetski, D.; Franks, S. W. On the recent warming in the Murray–Darling Basin: land surface interactions misunderstood Geophys. Res. Lett. 36, L24405 (2009) .
    • . . . It is more plausible that evaporation actually decreases during drought27 because of less precipitation, and that drought drives increases in temperatures because there is less evaporative cooling and thus a higher sensible heat flux warming the air28 . . .
  29. Hirschi, M. Observational evidence for soil-moisture impact on hot extremes in southeastern Europe Nature Geosci. 4, 17-21 (2011) .
    • . . . Short-term temperature anomalies are likely to be a response to drought, rather than a factor in forcing drought29 . . .
  30. Milly, P. C. D.; Dunne, K. A. On the hydrologic adjustment of climate-model projections: the potential pitfall of potential evapotranspiration Earth Interact. 15, 1-14 (2011) .
    • . . . Of concern is if the perceived influence of warming on drought as quantified by empirical approaches is extrapolated into the future and predictions of the impacts of climate change are likely to be overestimated21, 22, 30 . . .
  31. Sheffield, J.; Goteti, G.; Wood, E. F. Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling J. Clim. 19, 3088-3111 (2006) .
    • . . . Uncertainty from net radiation is estimated by forcing the PDSI_PM with a hybrid empirical–satellite data set31 and an empirical estimate . . .
    • . . . The global meteorological forcing dataset31 combines reanalysis data and observations to form a global, long-term (1948–2008), 1.0°, 3-hourly data set of precipitation, surface radiation and near-surface meteorology . . .
  32. Svoboda, M. The Drought Monitor Bull. Am. Meteorol. Soc. 83, 1181-1190 (2002) .
    • . . . Historically, the PDSI15 has been the tool of choice when monitoring and analysing drought occurrence, especially in the United States, where it is one component of the US National Drought Monitor32 . . .
  33. Cook, E. R.; Meko, D. M.; Stahle, D. W.; Cleaveland, M. K. Drought reconstructions for the continental United States J. Clim. 12, 1145-1162 (1999) .
    • . . . At continental to global scales its simplicity makes it an attractive choice for reconstructing drought records4, 33, for which it has also been shown to be a proxy for soil moisture4 . . .
  34. van der Schrier, G.; Briffa, K. R.; Osborn, T. J.; Cook, E. R. Summer moisture availability across North America J. Geophys. Res. 111, D11102 (2006) .
    • . . . It has been used to analyse continental-scale to global-scale, long-term variability in drought by several studies (see, for example, refs 4, 34, 35) . . .
  35. McCabe, G. J.; Palecki, M. A. Multidecadal climate variability of global lands and oceans Int. J. Climatol. 26, 849-865 (2006) .
    • . . . It has been used to analyse continental-scale to global-scale, long-term variability in drought by several studies (see, for example, refs 4, 34, 35) . . .
  36. Sheffield, J.; Wood, E. F. Characteristics of global and regional drought, 1950–2000: analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle J. Geophys. Res. 112, D17115 (2007) .
    • . . . The PDSI is generally well correlated with output from more comprehensive hydrological modelling36 but diverges in cooler seasons and high latitudes, and substantially so in drier regions. . . .
  37. Jensen, M. E. Consumptive Use of Water and Irrigation Water Requirements , (1973) .
    • . . . Despite this legacy, the PDSI has been shown to be unsuitable for widespread application and suffers from simplifications in its physical basis and soil hydrology17, 37 . . .
  38. Mu, Q. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data J. Geophys. Res. 112, G01012 (2007) .
    • . . . It forms the basis for the evaporation submodel of many distributed hydrological and land surface models, the latter of which often form the land component of coupled climate models, and has been used as the basis for regional and global retrievals of evapotranspiration based on satellite remotely sensed data (see, for example, refs 38–40) . . .
  39. Cleugh, H. A.; Leuning, R.; Mu, Q.; Running, S. W. Regional evaporation estimates from flux tower and MODIS satellite data Remote Sens. Environ. 106, 285-304 (2007) .
  40. Sheffield, J.; Wood, E. F.; Munoz-Arriola, F. Long-term regional estimates of evapotranspiration for Mexico based on downscaled ISCCP data J. Hydrometeorol. 11, 253-275 (2010) .
  41. Kalnay, E. The NCEP/NCAR 40-Year Reanalysis Project Bull. Am. Meteorol. Soc. 77, 437-471 (1996) .
    • . . . The data set is based on the NCEP/NCAR reanalysis (NNR)41, which provides continuous records of atmospheric and land variables from 1948 to the present . . .
  42. Mitchell, T. D.; Jones, P. D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids Int. J. Climatol. 25, 693-712 (2005) .
    • . . . Precipitation and temperature are scaled to match the Climatic Research Unit (CRU) TS3.0 data set42 on a monthly timescale . . .
    • . . . The data sets are CPC-Prec/L45 (ftp://ftp.cpc.ncep.noaa.gov/precip/50yr/), Global Precipitation Climatology Centre V4 (ref. 46) (GPCC; http://gpcc.dwd.de), Climatic Research Unit TS3.0 (ref. 42) (http://badc.nerc.ac.uk/browse/badc/cru) and Willmott–Matsuura V2.01 (ref. 47) (http://climate.geog.udel.edu/~climate/html_pages/download.html). . . .
  43. Huffman, G. J. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales J. Hydrometeorol. 8, 38-55 (2007) .
    • . . . The diurnal cycle of precipitation is resampled from a statistical model derived from the Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) satellite-based data set43 . . .
  44. Gupta, S. K.; Stackhouse, P. W.; Cox, S. J.; Mikovitz, J. C.; Zhang, T. Surface Radiation Budget Project completes 22-year data set GEWEX News 16, 12-13 (2006) .
    • . . . For 1984–2007, the shortwave and longwave radiation are scaled to match the NASA/GEWEX Surface Radiation Budget (SRB) satellite based data set44 on a monthly timescale . . .
  45. Chen, M.; Xie, P.; Janowiak, J. E.; Arkin, P. A. Global land precipitation: a 50-yr monthly analysis based on gauge observations J. Hydrometeorol. 3, 249-266 (2002) .
    • . . . The data sets are CPC-Prec/L45 (ftp://ftp.cpc.ncep.noaa.gov/precip/50yr/), Global Precipitation Climatology Centre V4 (ref. 46) (GPCC; http://gpcc.dwd.de), Climatic Research Unit TS3.0 (ref. 42) (http://badc.nerc.ac.uk/browse/badc/cru) and Willmott–Matsuura V2.01 (ref. 47) (http://climate.geog.udel.edu/~climate/html_pages/download.html). . . .
  46. Schneider, U.; Fuchs, T.; Meyer-Christoffer, A.; Rudolf, B. Global precipitation analysis products of the GPCC , (2008) .
    • . . . The data sets are CPC-Prec/L45 (ftp://ftp.cpc.ncep.noaa.gov/precip/50yr/), Global Precipitation Climatology Centre V4 (ref. 46) (GPCC; http://gpcc.dwd.de), Climatic Research Unit TS3.0 (ref. 42) (http://badc.nerc.ac.uk/browse/badc/cru) and Willmott–Matsuura V2.01 (ref. 47) (http://climate.geog.udel.edu/~climate/html_pages/download.html). . . .
  47. Willmott, C. J.; Matsuura, K. Terrestrial Air Temperature: 1900–2008 Gridded Monthly Time Series, version 2.01 Link , (2010) .
    • . . . The data sets are CPC-Prec/L45 (ftp://ftp.cpc.ncep.noaa.gov/precip/50yr/), Global Precipitation Climatology Centre V4 (ref. 46) (GPCC; http://gpcc.dwd.de), Climatic Research Unit TS3.0 (ref. 42) (http://badc.nerc.ac.uk/browse/badc/cru) and Willmott–Matsuura V2.01 (ref. 47) (http://climate.geog.udel.edu/~climate/html_pages/download.html). . . .
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