English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We propose a new approach to explain multiday rainfall accumulation over a French Alpine watershed using large-scale atmospheric predictors based on analogy. The classical analogy framework associates a rainfall cumulative distribution function (CDF) with a given atmospheric situation from the precipitation accumulations yielded by the closest situations. The analogy may apply to single-day or multiday sequences of pressure fields. The proposed approach represents a paradigm shift in analogy. It relies on the similarity of the local topology mapping the pressure field sequences, somehow forgetting the pressure fields per se. This topology is summarized by the way the sequences of pressure fields resemble their neighbors (dimensional predictors) and how fast they evolve in time (dynamical predictors). Although some information—and hence predictability—is expected to be lost when compared with classical analogy, this approach provides new insight on the atmospheric features generating rainfall CDFs. We apply both approaches to geopotential heights over western Europe in view of assessing 3-day rainfall accumulations over the Isère River catchment at Grenoble, France. Results show that dimensional predictors are the most skillful features for predicting 3-day rainfall—bringing alone 60% of the predictability of the classical analogy approach—whereas the dynamical predictors are less explicative. These results open new directions of research that the classical analogy approach cannot handle. They show, for instance, that both dry sequences and strong rainfall sequences are associated with singular 500-hPa geopotential shapes acting as local attractors—a way of explaining the change in rainfall CDFs in a changing climate.

Explaining Rainfall Accumulations over Several Days in the French Alps Using Low-Dimensional Atmospheric Predictors Based on Analogy