The extreme forecast index at the seasonal scale

E. Dutra; M. Diamantakis; I. Tsonevsky; E. Zsoter; F. Wetterhall; T. Stockdale; D. Richardson; F. Pappenberger

doi:10.1002/asl2.448

The extreme forecast index at the seasonal scale

E. Dutra^*
, M. Diamantakis
, I. Tsonevsky
, E. Zsoter
, F. Wetterhall
, T. Stockdale
, D. Richardson
, F. Pappenberger

^*Corresponding author for this work

School of Geographical Sciences

Research output: Contribution to journal › Article (Academic Journal) › peer-review

19 Citations (Scopus)

Abstract

The extreme forecast index (EFI) concept has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasts (S4) of 2-m temperature (T2M) and total precipitation (TP) using a novel semi-analytical technique. Results derived from synthetic data highlight the importance of large ensemble sizes to reduce the EFI calculation uncertainty due to sampling. This new diagnostic complements current diagnostics as exemplified for the 2012 warm summer in south central and eastern Europe. The EFI provides an integrated measure of the difference between a particular seasonal forecast ensemble and the underlying model climate which can be used as an early warning indicator.

Original language	English
Pages (from-to)	256-262
Number of pages	7
Journal	Atmospheric Science Letters
Volume	14
Issue number	4
DOIs	https://doi.org/10.1002/asl2.448
Publication status	Published - 1 Oct 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Extreme forecast index
Predictability
Seasonal forecasts

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10.1002/asl2.448

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title = "The extreme forecast index at the seasonal scale",

abstract = "The extreme forecast index (EFI) concept has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasts (S4) of 2-m temperature (T2M) and total precipitation (TP) using a novel semi-analytical technique. Results derived from synthetic data highlight the importance of large ensemble sizes to reduce the EFI calculation uncertainty due to sampling. This new diagnostic complements current diagnostics as exemplified for the 2012 warm summer in south central and eastern Europe. The EFI provides an integrated measure of the difference between a particular seasonal forecast ensemble and the underlying model climate which can be used as an early warning indicator.",

keywords = "Extreme forecast index, Predictability, Seasonal forecasts",

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T1 - The extreme forecast index at the seasonal scale

AU - Dutra, E.

AU - Diamantakis, M.

AU - Tsonevsky, I.

AU - Zsoter, E.

AU - Wetterhall, F.

AU - Stockdale, T.

AU - Richardson, D.

AU - Pappenberger, F.

PY - 2013/10/1

Y1 - 2013/10/1

N2 - The extreme forecast index (EFI) concept has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasts (S4) of 2-m temperature (T2M) and total precipitation (TP) using a novel semi-analytical technique. Results derived from synthetic data highlight the importance of large ensemble sizes to reduce the EFI calculation uncertainty due to sampling. This new diagnostic complements current diagnostics as exemplified for the 2012 warm summer in south central and eastern Europe. The EFI provides an integrated measure of the difference between a particular seasonal forecast ensemble and the underlying model climate which can be used as an early warning indicator.

AB - The extreme forecast index (EFI) concept has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasts (S4) of 2-m temperature (T2M) and total precipitation (TP) using a novel semi-analytical technique. Results derived from synthetic data highlight the importance of large ensemble sizes to reduce the EFI calculation uncertainty due to sampling. This new diagnostic complements current diagnostics as exemplified for the 2012 warm summer in south central and eastern Europe. The EFI provides an integrated measure of the difference between a particular seasonal forecast ensemble and the underlying model climate which can be used as an early warning indicator.

KW - Extreme forecast index

KW - Predictability

KW - Seasonal forecasts

UR - https://www.scopus.com/pages/publications/84886254796

U2 - 10.1002/asl2.448

DO - 10.1002/asl2.448

M3 - Article (Academic Journal)

AN - SCOPUS:84886254796

SN - 1530-261X

VL - 14

SP - 256

EP - 262

JO - Atmospheric Science Letters

JF - Atmospheric Science Letters

IS - 4

ER -

The extreme forecast index at the seasonal scale

Abstract

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