The Global Drought Monitor Portal: The Foundation for a Global Drought Information System

Heim, Richard R.; Brewer, Michael J.

doi:10.1175/2012ei000446.1

Cited by 53 publications

(33 citation statements)

References 13 publications

(15 reference statements)

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“…Several processes affecting the precipitation producing phenomena (or the ultimate cause of meteorological drought) often act over relatively large geographic distances through large‐scale atmospheric motions (e.g., Hadley circulation and Walker circulations, Rossby wave), which are generally forced by SST anomaly, land surface interactions/feedbacks, and natural and anthropogenic changes in radiative forcings (or external factors superimposed on natural climate variability) (Schubert et al, ). These forcing factors provide certain degree of meteorological drought predictability (shown in Figure ) (Heim & Brewer, ; Kingston et al, ; Mueller & Seneviratne, ; Rodríguez‐Fonseca et al, ; Wood et al, ).…”

Section: Drought Mechanism and Predictabilitymentioning

confidence: 99%

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Hao

Singh

Xia

2018

Reviews of Geophysics

429

232

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Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large‐scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high‐quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

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Section: Drought Mechanism and Predictabilitymentioning

confidence: 99%

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Hao

Singh

Xia

2018

Reviews of Geophysics

429

232

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“…Development of a Global Drought Information System was a key recommendation of a World Climate Research Program workshop "Drought Predictability and Prediction in a Changing Climate" held in 2011 (Heim and Brewer, 2012;Pozzi et al, 2013). Though thus far, the implementation of a global seasonal hydrologic prediction system has largely been elusive notwithstanding major strides in the last two decades in the development of large scale hydrologic models (Liang et al, 1994;Mitchell et al, 2004;Wang et al, 2009) and improvement in seasonal climate forecast skill (Goddard et al, 2001(Goddard et al, , 2003Palmer et al, 2004;Saha et al, 2006;Barnston et al, 2010;Yuan et al, 2011).…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

On the sources of global land surface hydrologic predictability

Shukla

Sheffield

Wood

et al. 2013

Hydrol. Earth Syst. Sci.

105

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Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1-6 months) comes from knowledge of initial hydrologic conditions (IHCs) and seasonal climate forecast skill (FS). In this study we quantify the contributions of two primary components of IHCs -soil moisture and snow water content -and FS (of precipitation and temperature) to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two modelbased experiments using the variable infiltration capacity (VIC) macroscale hydrology model, one based on ensemble streamflow prediction (ESP) and another based on Reverse-ESP (Rev-ESP), both for a 47 yr re-forecast period . We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings) and estimate the ratio of root mean square error (RMSE) of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude) regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year.Based on our findings, we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.

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“…The SPEI has been applied extensively in recent climatological and hydrological studies (e.g. Potop 2011, Heim & Brewer 2012, Li et al 2012, Paulo et al 2012, Potop et al 2012, Brázdil et al 2013a, Beguería et al 2014, Yu et al 2014, Potopová et al 2016). …”

Section: Introductionmentioning

confidence: 99%

Drought reconstruction based on grape harvest dates for the Czech Lands, 1499-2012

Možný¹,

Brázdil²,

Dobrovolný³

et al. 2016

Clim. Res.

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The timing of maturity of grapes depends on the weather conditions during the growing season. This study relies on the dependence of harvest dates on the air temperature and dry/wet conditions. Recorded observations show that increases in air temperature and dryness are associated with earlier grape harvests. Documentary data of grape harvests from the Bohemian wine-growing region (mainly northwest of Prague) were combined with mean Standardized Precipitation Evapotranspiration Index (SPEI) series starting in 1841 and ordinary least square regression with subsequent scaling to reconstruct the mean SPEI values for this area for April to August from 1499 to 2012. The reconstructed SPEI series explains 75% of the drought variability since 1841. All dry years that were detected by the reconstructed April−August SPEI values correlate well with years of excellent and good red wine of vintage quality for 1499−1840. A comparison of the reconstructed series with other SPEI reconstructions from the Czech Lands (the recent Czech Republic) based on documentary and instrumental data shows good agreement. The results demonstrate that grape harvest series may be used as a proxy for drought reconstruction in the central European region.

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The Global Drought Monitor Portal: The Foundation for a Global Drought Information System

Abstract: ABSTRACT:The international scientific community has long recognized the need for coordinated drought monitoring and response,

Cited by 53 publications

References 13 publications

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

On the sources of global land surface hydrologic predictability

Drought reconstruction based on grape harvest dates for the Czech Lands, 1499-2012

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