Climate change over the extratropical Southern Hemisphere: The tale from an ensemble of reanalysis datasets
In this study, a set of five reanalysis datasets [ERA-Interim, NCEP-DOE AMIP-II reanalysis (R2), MERRA, the Twentieth Century Reanalysis (20CR), and the CFS Reanalysis (CFSR)] is used to provide a robust estimation of precipitation change in the middle-to-high latitudes of the Southern Hemisphere du...
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
American Meteorological Society
2016
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 10742caa a22011177a 4500 | ||
|---|---|---|---|
| 001 | PAPER-16334 | ||
| 003 | AR-BaUEN | ||
| 005 | 20230518204720.0 | ||
| 008 | 190411s2016 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-84960906441 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Solman, S.A. | |
| 245 | 1 | 0 | |a Climate change over the extratropical Southern Hemisphere: The tale from an ensemble of reanalysis datasets |
| 260 | |b American Meteorological Society |c 2016 | ||
| 270 | 1 | 0 | |m Solman, S.A.; CIMA (CONICET-UBA), Ciudad Universitaria, Pabellón II, 2do piso, C1428EGA, Argentina; email: solman@cima.fcen.uba.ar |
| 506 | |2 openaire |e Política editorial | ||
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| 520 | 3 | |a In this study, a set of five reanalysis datasets [ERA-Interim, NCEP-DOE AMIP-II reanalysis (R2), MERRA, the Twentieth Century Reanalysis (20CR), and the CFS Reanalysis (CFSR)] is used to provide a robust estimation of precipitation change in the middle-to-high latitudes of the Southern Hemisphere during the last three decades. Based on several metrics accounting for the eddy activity and moisture availability, an attempt is also made to identify the dynamical mechanisms triggering these changes during extended summer and winter seasons. To that aim, a weighted reanalysis ensemble is built using the inverse of the variance as weighting factors for each variable. Results showed that the weighted reanalysis ensemble reproduced the observed precipitation changes at high and middle latitudes during the two seasons, as depicted by the GPCP dataset. For the extended summer season, precipitation changes were dynamically consistent with changes in the eddy activity, attributed mostly to ozone depletion. For the extended winter season, the eddy activity and moisture availability both contributed to the precipitation changes, with the increased concentration of greenhouse gases being the main driver of the climate change signal. In addition, output from a five-member ensemble of the high-resolution GFDL CM2.5 for the period 1979-2010 was used in order to explore the capability of the model in reproducing both the observed precipitation change and the underlying dynamical mechanisms. The model was able to capture the rainfall change signal. However, the increased availability of moisture from the lower levels controls the precipitation change during both summer and winter. © 2016 American Meteorological Society. |l eng | |
| 593 | |a Centro de Investigaciones del Mar y la Atmosfera, Facultad de Ciencias Exactas y Naturales, Consejo Nacional de Investigaciones Científicas y Técnicas, Departamento de Ciencias de la Atmosfera y los Oceanos, Universidad de Buenos Aires, Buenos Aires, Argentina | ||
| 593 | |a Atmospheric and Oceanic Science Program, Princeton University, Princeton, NJ, United States | ||
| 690 | 1 | 0 | |a ATM/OCEAN STRUCTURE/PHENOMENA |
| 690 | 1 | 0 | |a CIRCULATION/DYNAMICS |
| 690 | 1 | 0 | |a DATABASES |
| 690 | 1 | 0 | |a EXTRATROPICAL CYCLONES |
| 690 | 1 | 0 | |a LARGE-SCALE MOTIONS |
| 690 | 1 | 0 | |a MODELS AND MODELING |
| 690 | 1 | 0 | |a OBSERVATIONAL TECHNIQUES AND ALGORITHMS |
| 690 | 1 | 0 | |a PRECIPITATION |
| 690 | 1 | 0 | |a REANALYSIS DATA |
| 690 | 1 | 0 | |a TRENDS |
| 690 | 1 | 0 | |a VARIABILITY |
| 690 | 1 | 0 | |a DATABASE SYSTEMS |
| 690 | 1 | 0 | |a GREENHOUSE GASES |
| 690 | 1 | 0 | |a INVERSE PROBLEMS |
| 690 | 1 | 0 | |a MOISTURE |
| 690 | 1 | 0 | |a OZONE LAYER |
| 690 | 1 | 0 | |a PRECIPITATION (CHEMICAL) |
| 690 | 1 | 0 | |a STORMS |
| 690 | 1 | 0 | |a EXTRATROPICAL CYCLONES |
| 690 | 1 | 0 | |a LARGE SCALE MOTION |
| 690 | 1 | 0 | |a REANALYSIS |
| 690 | 1 | 0 | |a TRENDS |
| 690 | 1 | 0 | |a VARIABILITY |
| 690 | 1 | 0 | |a CLIMATE CHANGE |
| 690 | 1 | 0 | |a ALGORITHM |
| 690 | 1 | 0 | |a ATMOSPHERIC MODELING |
| 690 | 1 | 0 | |a CLIMATE CHANGE |
| 690 | 1 | 0 | |a DATA SET |
| 690 | 1 | 0 | |a ENSEMBLE FORECASTING |
| 690 | 1 | 0 | |a PRECIPITATION (CLIMATOLOGY) |
| 690 | 1 | 0 | |a SOUTHERN HEMISPHERE |
| 690 | 1 | 0 | |a TREND ANALYSIS |
| 690 | 1 | 0 | |a TROPICAL CYCLONE |
| 700 | 1 | |a Orlanski, I. | |
| 773 | 0 | |d American Meteorological Society, 2016 |g v. 29 |h pp. 1673-1687 |k n. 5 |p J. Clim. |x 08948755 |w (AR-BaUEN)CENRE-5480 |t Journal of Climate | |
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| 856 | 4 | 0 | |u https://doi.org/10.1175/JCLI-D-15-0588.1 |y DOI |
| 856 | 4 | 0 | |u https://hdl.handle.net/20.500.12110/paper_08948755_v29_n5_p1673_Solman |y Handle |
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