Partitioning sources of uncertainty in local climate change projections

S. Fatichi; V. Y. Ivanov; A. Paschalis; P. Molnar; S. Rimkus; J. Kim; P. Burlando; N. Peleg; E. Caporali

Partitioning sources of uncertainty in local climate change projections

S. Fatichi
, V. Y. Ivanov
, A. Paschalis
, P. Molnar
, S. Rimkus
, J. Kim
, P. Burlando
, N. Peleg
, E. Caporali

Department of Civil and Environmental Engineering

Swiss Federal Institute of Technology Zurich
University of Michigan, Ann Arbor
Duke University
SCOR Global P and C
University of Florence

Research output: Contribution to conference › Paper › peer-review

Abstract

Impact studies and practical applications demand for climate change predictions of meteorological forcing at local spatial scales and fine temporal resolutions. Concurrently, climate models are typically more reliable at the global and regional scales, but they may have significant biases at the scales of "human action", e.g., few square kilometres and sub-daily scale. Therefore, there is a demand for advanced techniques that offer the capability of transferring predictions of climate models and relative uncertainty to scales commensurate with practical applications and for higher order statistics.

Original language	English
State	Published - 2015
Event	10th International Workshop on Precipitation in Urban Areas: Rainfall in Urban and Natural Systems, UrbanRain 2015 - Pontresina, Switzerland Duration: 1 Dec 2015 → 5 Dec 2015

Conference

Conference	10th International Workshop on Precipitation in Urban Areas: Rainfall in Urban and Natural Systems, UrbanRain 2015
Country/Territory	Switzerland
City	Pontresina
Period	1/12/15 → 5/12/15

UN SDGs

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

SDG 13 Climate Action

Cite this

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TY - CONF

T1 - Partitioning sources of uncertainty in local climate change projections

AU - Fatichi, S.

AU - Ivanov, V. Y.

AU - Paschalis, A.

AU - Molnar, P.

AU - Rimkus, S.

AU - Kim, J.

AU - Burlando, P.

AU - Peleg, N.

AU - Caporali, E.

PY - 2015

Y1 - 2015

N2 - Impact studies and practical applications demand for climate change predictions of meteorological forcing at local spatial scales and fine temporal resolutions. Concurrently, climate models are typically more reliable at the global and regional scales, but they may have significant biases at the scales of "human action", e.g., few square kilometres and sub-daily scale. Therefore, there is a demand for advanced techniques that offer the capability of transferring predictions of climate models and relative uncertainty to scales commensurate with practical applications and for higher order statistics.

AB - Impact studies and practical applications demand for climate change predictions of meteorological forcing at local spatial scales and fine temporal resolutions. Concurrently, climate models are typically more reliable at the global and regional scales, but they may have significant biases at the scales of "human action", e.g., few square kilometres and sub-daily scale. Therefore, there is a demand for advanced techniques that offer the capability of transferring predictions of climate models and relative uncertainty to scales commensurate with practical applications and for higher order statistics.

UR - https://www.scopus.com/pages/publications/85071004439

M3 - Paper

AN - SCOPUS:85071004439

T2 - 10th International Workshop on Precipitation in Urban Areas: Rainfall in Urban and Natural Systems, UrbanRain 2015

Y2 - 1 December 2015 through 5 December 2015

ER -

Partitioning sources of uncertainty in local climate change projections

Abstract

Conference

UN SDGs

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