Modeling extreme meteorological droughts from paleo-climatic
reconstructions: A metastatistical framework
Abstract
Droughts have pervasive societal impacts and remain difficult to
characterize observationally, due to the limited number of droughts
sampled in instrumental records. One approach to improving the
statistical basis of drought occurrence probability estimation is to
extend the observational record using proxy climatic archives, such as
those based on tree-ring information. Additionally, since droughts are
rare and characterized by multiannual durations and inter-arrival times,
it is important to devise and apply statistical techniques that make
full use of all of the available information so as to improve our
ability to quantify the rarest droughts. We extract data from a publicly
available tree-ring based Palmer Drought Severity Index (PDSI) dataset,
the Old World Drought Atlas, for two sites in Italy where long rainfall
and temperature observational time series are leveraged for a meaningful
comparison. Drought events are defined in terms of drought deficit
volumes below a threshold PDSI value, and are studied through the
Metastatistical Extreme Value Distribution (MEVD) to quantify the
occurrence probability of extreme drought events. The estimation
uncertainty associated with a variety of possible assumptions in MEVD
analysis is studied, in specific comparison with the performance
obtained using the traditional Generalized Extreme Value distribution,
through a cross-validation methodology. Results suggest that MEVD-based
formulations are more robust and flexible with respect to traditional
ones. The combination of paleoclimatic data and methodologies capable of
using most of the existing information provide more reliable estimates
of drought recurrence times, which may be used to design more effective
drought risk management plans.