Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals

Increasingly uncertain hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite modern forecasts are skillful over...

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Main Authors: M. Giuliani, A. Castelletti, P. Block
Other Authors: Giuliani, M., Castelletti, A., Block, P.
Format: Conference Object
Language:unknown
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/11311/1061764
https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/269277
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spelling ftpolimilanoiris:oai:re.public.polimi.it:11311/1061764 2024-01-07T09:45:15+01:00 Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals M. Giuliani A. Castelletti P. Block Giuliani, M. Castelletti, A. Block, P. 2017 http://hdl.handle.net/11311/1061764 https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/269277 unknown ispartofbook:American Geophysical Union (AGU) Fall Meeting Abstracts AGU Fall Meeting 2017 http://hdl.handle.net/11311/1061764 https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/269277 info:eu-repo/semantics/conferenceObject 2017 ftpolimilanoiris 2023-12-13T17:54:23Z Increasingly uncertain hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite modern forecasts are skillful over short lead time (from hours to days), predictability generally tends to decrease on longer lead times. Global climate teleconnection, such as El Niño Southern Oscillation (ENSO), may contribute in extending forecast lead times. However, ENSO teleconnection is well defined in some locations, such as Western USA and Australia, while there is no consensus on how it can be detected and used in other regions, particularly in Europe, Africa, and Asia. In this work, we generalize the Niño Index Phase Analysis (NIPA) framework by contributing the Multi Variate Niño Index Phase Analysis (MV-NIPA), which allows capturing the state of multiple large-scale climate signals (i.e. ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Indian Ocean Dipole) to forecast hydroclimatic variables on a seasonal time scale. Specifically, our approach distinguishes the different phases of the considered climate signals and, for each phase, identifies relevant anomalies in Sea Surface Temperature (SST) that influence the local hydrologic conditions. The potential of the MV-NIPA framework is demonstrated through an application to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Numerical results show high correlations between seasonal SST values and one season-ahead precipitation in the Lake Como basin. The skill of the resulting MV-NIPA forecast outperforms the one of ECMWF products. This information represents a valuable contribution to partially anticipate the summer water availability, especially during drought events, ultimately supporting the improvement of the Lake Como operations. Conference Object North Atlantic North Atlantic oscillation RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano Pacific Indian Nipa ENVELOPE(14.813,14.813,68.567,68.567)
institution Open Polar
collection RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano
op_collection_id ftpolimilanoiris
language unknown
description Increasingly uncertain hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite modern forecasts are skillful over short lead time (from hours to days), predictability generally tends to decrease on longer lead times. Global climate teleconnection, such as El Niño Southern Oscillation (ENSO), may contribute in extending forecast lead times. However, ENSO teleconnection is well defined in some locations, such as Western USA and Australia, while there is no consensus on how it can be detected and used in other regions, particularly in Europe, Africa, and Asia. In this work, we generalize the Niño Index Phase Analysis (NIPA) framework by contributing the Multi Variate Niño Index Phase Analysis (MV-NIPA), which allows capturing the state of multiple large-scale climate signals (i.e. ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Indian Ocean Dipole) to forecast hydroclimatic variables on a seasonal time scale. Specifically, our approach distinguishes the different phases of the considered climate signals and, for each phase, identifies relevant anomalies in Sea Surface Temperature (SST) that influence the local hydrologic conditions. The potential of the MV-NIPA framework is demonstrated through an application to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Numerical results show high correlations between seasonal SST values and one season-ahead precipitation in the Lake Como basin. The skill of the resulting MV-NIPA forecast outperforms the one of ECMWF products. This information represents a valuable contribution to partially anticipate the summer water availability, especially during drought events, ultimately supporting the improvement of the Lake Como operations.
author2 Giuliani, M.
Castelletti, A.
Block, P.
format Conference Object
author M. Giuliani
A. Castelletti
P. Block
spellingShingle M. Giuliani
A. Castelletti
P. Block
Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
author_facet M. Giuliani
A. Castelletti
P. Block
author_sort M. Giuliani
title Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
title_short Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
title_full Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
title_fullStr Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
title_full_unstemmed Improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
title_sort improving seasonal forecasts of hydroclimatic variables through the state of multiple large-scale climate signals
publishDate 2017
url http://hdl.handle.net/11311/1061764
https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/269277
long_lat ENVELOPE(14.813,14.813,68.567,68.567)
geographic Pacific
Indian
Nipa
geographic_facet Pacific
Indian
Nipa
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_relation ispartofbook:American Geophysical Union (AGU) Fall Meeting Abstracts
AGU Fall Meeting 2017
http://hdl.handle.net/11311/1061764
https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/269277
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