Reducing Stakeholder Vulnerability to Climate Variability in Southern Peru Using Statistically-Based Prediction and Risk Management Tools

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semi-arid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Agricultural operations in southern Peru are particularly vulnerable to drought, and the response to drier than normal conditions in this region can be characterized as reactive and fairly limited due to challenges associated with climate forecasting and administrative capacity. Meteorological droughts in this region here are often triggered during El Niño episodes and have direct hydrologic, economic, and social implications. To reduce the vulnerability faced across several sectors, statistically-based tools are developed to predict drought and provide additional resources to stakeholders. An extensive season-ahead precipitation prediction model is developed and conditioned on ENSO and other large-scale climate mechanisms. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to eleven potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. Extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet/dry days per rainy season may further assist regional stakeholders and policymakers in preparing for drought. An ENSO index-based insurance product is also presented as a demonstration of methodology and application for oca production in Puno of southern Peru. The purpose of this product is to streamline the ability of decision makers to provide financial relief to affected farmers during, and perhaps before, drought; extending the lead time of the index used to trigger payouts produces results of similar skill to a product trained on concurrent conditions. Issues explored include basis risk, initial endowment requirements, product longevity, and the potential crossover from index-based insurance to forecast-based financing. The potential for uptake of such products is real in Peru, and of considerable interest to both regional government and relief agencie