Why predict climate hazards if we need to understand impacts? Putting humans back into the drought equation
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Why predict climate hazards if we need to understand impacts? Putting humans back into the drought equation M. Enenkel 1,2 & M. E. Brown 3 & J. V. Vogt 4 & J. L. McCarty 5 & A. Reid Bell 6 & D. Guha-Sapir 7 & W. Dorigo 8 & K. Vasilaky 9 & M. Svoboda 10 & R. Bonifacio 11 & M. Anderson 12 & C. Funk 13 & D. Osgood 14 & C. Hain 15 & P. Vinck 1 Received: 17 May 2019 / Accepted: 25 September 2020/ # Springer Nature B.V. 2020
Abstract
Virtually all climate monitoring and forecasting efforts concentrate on hazards rather than on impacts, while the latter are a priority for planning emergency activities and for the evaluation of mitigation strategies. Effective disaster risk management strategies need to consider the prevailing “human terrain” to predict who is at risk and how communities will be affected. There has been little effort to align the spatiotemporal granularity of socioeconomic assessments with the granularity of weather or climate monitoring. The lack of a high-resolution socioeconomic baseline leaves methodical approaches like machine learning virtually untapped for pattern recognition of extreme climate impacts on livelihood conditions. While the request for “better” socioeconomic data is not new, we highlight the need to collect and analyze environmental and socioeconomic data together and discuss novel strategies for coordinated data collection via mobile technologies from a drought risk management perspective. A better temporal, spatial, and contextual understanding of socioeconomic impacts of extreme climate conditions will help to establish complex causal pathways and quantitative proof about climate-attributable livelihood impacts. Such considerations are particularly important in the context of the latest big datadriven initiatives, such as the World Bank’s Famine Action Mechanism (FAM). Keywords Drought . Impact assessment . Disaster resilience . Decision-support . Mobile technologies
* M. Enenkel [email protected] Extended author information available on the last page of the article
Climatic Change
1 Introduction Satellite-derived information has become an indispensable source of information for all phases of disaster risk management. The granularity and availability of satellite data to monitor climate hazards, such as floods and droughts, are increasing, resulting in image updates from intervals of 5 min, in the case of geostationary weather satellites with coarse spatial resolution, to revisit periods from less than one up to several days for very high spatial resolution optical imagery with up to 30-cm spatial resolution. However, climate hazards represent only one part of the disaster risk equation, which defines risk as the product of hazard, exposure, and vulnerability. Without up-to-date information about exposure, socioeconomic conditions, and the related vulnerability of communities at risk, we are facing several major limitations, ranging from weaknesses in the prediction of disaster loss and damage to the evaluation of disaster mitigation strategies. The development of soci
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