Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data

An alternative to dynamical seasonal prediction of European climate is statistical modeling. Statistical modeling is an appealing and computationally effective approach for producing seasonal forecasts by exploiting the physical connections between the predictand variable and the predictors. We asse...

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Main Authors: Pyrina, M., Wagner, S., Zorita, E.
Format: Conference Object
Language:English
Published: 2020
Subjects:
Online Access:https://publications.hereon.de/id/39199
https://publications.hzg.de/id/39199
https://doi.org/10.5194/egusphere-egu2020-4571
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spelling fthzgzmk:oai:publications.hereon.de:39199 2023-06-11T04:14:29+02:00 Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data Pyrina, M. Wagner, S. Zorita, E. 2020 https://publications.hereon.de/id/39199 https://publications.hzg.de/id/39199 https://doi.org/10.5194/egusphere-egu2020-4571 en eng https://dx.doi.org/10.5194/egusphere-egu2020-4571 https://publications.hereon.de/id/39199 https://publications.hzg.de/id/39199 info:eu-repo/semantics/openAccess open_access oa_gold Pyrina, M.; Wagner, S.; Zorita, E.: Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data. In: EGU General Assembly 2020. Virtual, 04.05.2020 - 08.05.2020, 2020. (DOI: /10.5194/egusphere-egu2020-4571) info:eu-repo/semantics/conferenceObject Konferenz/Veranstaltung sonst. (nicht gelad.) Vortrag 2020 fthzgzmk https://doi.org/10.5194/egusphere-egu2020-4571 2023-05-28T23:25:06Z An alternative to dynamical seasonal prediction of European climate is statistical modeling. Statistical modeling is an appealing and computationally effective approach for producing seasonal forecasts by exploiting the physical connections between the predictand variable and the predictors. We assess the seasonal predictability of summer European 2m temperature (T2m) using canonical correlation analysis. Seasonal means of spring Soil Moisture (SM), Sea Level Pressure (SLP) and Sea Surface Temperature (SST) are used as predictors of mean summer T2m. For SSTs, we test the potential predictability of T2m using three different regions. These regions include what we define as: Extratropical North Atlantic (ENA), Tropical North Atlantic (TNA), and North Atlantic (NA). The predictability is explored in the ERA20c reanalysis and in comprehensive Earth System Model (ESM) fields. The results are provided for the European domain on a horizontal grid of 1°x1° degrees. In order to identify the local T2m predictability related to the different predictor variables, we first built Univariate Linear Regression models, one for every predictor. The regression models are calibrated and validated during 1902-1950 and a prediction is provided for the periods 1951-1998, 1951-2004, and 1951-2008, respectively. The resulting correlation maps between the original and the predicted T2m anomalies showed that for the predictor variables SLP, SM, and SSTENA the results of the experiments using ESM data share similar T2m predictability patterns with the results of the experiments using reanalysis data. Most prominent disagreements between the predictability patterns resulting from ESMs and from ERA20c refers to the T2m prediction that utilizes tropical SSTs. SM is identified as the most important predictor for the summer European temperature predictability. The ERA20c data show that the SM predictor field can be used for the T2m prediction over most of our study region west of 15° E and that the ENA SSTs can be used for the prediction over ... Conference Object North Atlantic Hereon Publications (Helmholtz-Zentrum)
institution Open Polar
collection Hereon Publications (Helmholtz-Zentrum)
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language English
description An alternative to dynamical seasonal prediction of European climate is statistical modeling. Statistical modeling is an appealing and computationally effective approach for producing seasonal forecasts by exploiting the physical connections between the predictand variable and the predictors. We assess the seasonal predictability of summer European 2m temperature (T2m) using canonical correlation analysis. Seasonal means of spring Soil Moisture (SM), Sea Level Pressure (SLP) and Sea Surface Temperature (SST) are used as predictors of mean summer T2m. For SSTs, we test the potential predictability of T2m using three different regions. These regions include what we define as: Extratropical North Atlantic (ENA), Tropical North Atlantic (TNA), and North Atlantic (NA). The predictability is explored in the ERA20c reanalysis and in comprehensive Earth System Model (ESM) fields. The results are provided for the European domain on a horizontal grid of 1°x1° degrees. In order to identify the local T2m predictability related to the different predictor variables, we first built Univariate Linear Regression models, one for every predictor. The regression models are calibrated and validated during 1902-1950 and a prediction is provided for the periods 1951-1998, 1951-2004, and 1951-2008, respectively. The resulting correlation maps between the original and the predicted T2m anomalies showed that for the predictor variables SLP, SM, and SSTENA the results of the experiments using ESM data share similar T2m predictability patterns with the results of the experiments using reanalysis data. Most prominent disagreements between the predictability patterns resulting from ESMs and from ERA20c refers to the T2m prediction that utilizes tropical SSTs. SM is identified as the most important predictor for the summer European temperature predictability. The ERA20c data show that the SM predictor field can be used for the T2m prediction over most of our study region west of 15° E and that the ENA SSTs can be used for the prediction over ...
format Conference Object
author Pyrina, M.
Wagner, S.
Zorita, E.
spellingShingle Pyrina, M.
Wagner, S.
Zorita, E.
Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
author_facet Pyrina, M.
Wagner, S.
Zorita, E.
author_sort Pyrina, M.
title Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
title_short Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
title_full Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
title_fullStr Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
title_full_unstemmed Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data
title_sort statistical prediction of 20th century european summer temperatures based on era20c reanalysis data
publishDate 2020
url https://publications.hereon.de/id/39199
https://publications.hzg.de/id/39199
https://doi.org/10.5194/egusphere-egu2020-4571
genre North Atlantic
genre_facet North Atlantic
op_source Pyrina, M.; Wagner, S.; Zorita, E.: Statistical prediction of 20th century European summer temperatures based on ERA20c reanalysis data. In: EGU General Assembly 2020. Virtual, 04.05.2020 - 08.05.2020, 2020. (DOI: /10.5194/egusphere-egu2020-4571)
op_relation https://dx.doi.org/10.5194/egusphere-egu2020-4571
https://publications.hereon.de/id/39199
https://publications.hzg.de/id/39199
op_rights info:eu-repo/semantics/openAccess
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oa_gold
op_doi https://doi.org/10.5194/egusphere-egu2020-4571
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