Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France
This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in sur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016-03-01
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| Series: | Climate of the Past |
| Online Access: | http://www.clim-past.net/12/635/2016/cp-12-635-2016.pdf |
| _version_ | 1819211043912548352 |
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| author | L. Caillouet J.-P. Vidal E. Sauquet B. Graff |
| author_facet | L. Caillouet J.-P. Vidal E. Sauquet B. Graff |
| author_sort | L. Caillouet |
| collection | DOAJ |
| description | This work proposes a daily high-resolution probabilistic reconstruction of
precipitation and temperature fields in France over the 1871–2012 period
built on the NOAA Twentieth Century global extended atmospheric reanalysis
(20CR). The objective is to fill in the spatial and temporal data gaps in
surface observations in order to improve our knowledge on the local-scale
climate variability from the late nineteenth century onwards.
<br><br>
The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical
downscaling method, initially developed for quantitative precipitation
forecast, is used here to bridge the scale gap between large-scale 20CR
predictors and local-scale predictands from the Safran high-resolution
near-surface reanalysis, available from 1958 onwards only. SANDHY provides
a daily ensemble of 125 analogue dates over the 1871–2012 period for 608
climatically homogeneous zones paving France. Large precipitation biases in
intermediary seasons are shown to occur in regions with high seasonal
asymmetry like the Mediterranean. Moreover, winter and summer temperatures
are respectively over- and under-estimated over the whole of France.
<br><br>
Two analogue subselection methods are therefore developed with the aim of
keeping the structure of the SANDHY method unchanged while reducing those
seasonal biases. The calendar selection keeps the analogues closest to the
target calendar day. The stepwise selection applies two new analogy
steps based on similarity of the sea surface temperature (SST) and the
large-scale 2 m temperature (<i>T</i>). Comparisons to
the Safran reanalysis over 1959–2007 and to homogenized series over the
whole twentieth century show that biases in the interannual cycle of
precipitation and temperature are reduced with both methods. The stepwise
subselection moreover leads to a large improvement of interannual correlation
and reduction of errors in seasonal temperature time series. When the
calendar subselection is an easily applicable method suitable in
a quantitative precipitation forecast context, the stepwise subselection
method allows for potential season shifts and SST trends and is therefore
better suited for climate reconstructions and climate change studies.
<br><br>
The probabilistic downscaling of 20CR over the period 1871–2012 with the
SANDHY probabilistic downscaling method combined with the stepwise
subselection thus constitutes a perfect framework for assessing the recent
observed meteorological events but also future events projected by climate
change impact studies and putting them in a historical perspective. |
| first_indexed | 2024-12-23T06:20:48Z |
| format | Article |
| id | doaj.art-e156c3f11ceb429884eaf9eb4c4fa994 |
| institution | Directory Open Access Journal |
| issn | 1814-9324 1814-9332 |
| language | English |
| last_indexed | 2024-12-23T06:20:48Z |
| publishDate | 2016-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Climate of the Past |
| spelling | doaj.art-e156c3f11ceb429884eaf9eb4c4fa9942022-12-21T17:57:12ZengCopernicus PublicationsClimate of the Past1814-93241814-93322016-03-0112363566210.5194/cp-12-635-2016Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over FranceL. Caillouet0J.-P. Vidal1E. Sauquet2B. Graff3Irstea, UR HHLY, Hydrology and Hydraulics Research Unit, 5 rue de la Doua – BP32108, 69916 Villeurbanne CEDEX, FranceIrstea, UR HHLY, Hydrology and Hydraulics Research Unit, 5 rue de la Doua – BP32108, 69916 Villeurbanne CEDEX, FranceIrstea, UR HHLY, Hydrology and Hydraulics Research Unit, 5 rue de la Doua – BP32108, 69916 Villeurbanne CEDEX, FranceCompagnie Nationale du Rhône (CNR), 2 rue André Bonin, 69004 Lyon, FranceThis work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. <br><br> The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. <br><br> Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (<i>T</i>). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. <br><br> The probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.http://www.clim-past.net/12/635/2016/cp-12-635-2016.pdf |
| spellingShingle | L. Caillouet J.-P. Vidal E. Sauquet B. Graff Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France Climate of the Past |
| title | Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France |
| title_full | Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France |
| title_fullStr | Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France |
| title_full_unstemmed | Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France |
| title_short | Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France |
| title_sort | probabilistic precipitation and temperature downscaling of the twentieth century reanalysis over france |
| url | http://www.clim-past.net/12/635/2016/cp-12-635-2016.pdf |
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