Abstract
We employ a Lagrangian based moisture back trajectory method on an ensemble of four reanalysis datasets to provide a comprehensive understanding of moisture sources over the Mediterranean land region (30° N–49.5° N and 9.75° W–61.5° E) at seasonal timescales for 1980–2013 period. Using a source region between 10° S–71.35° N along the latitude and 80° W–84.88° E along the longitude that is subdivided into ten complimentary sub-regions, our analyses is able to backtrack up to > 90% of seasonal precipitation at each grid point within the target region. Our results indicate a significant role of moisture advected from the North Atlantic and Mediterranean Sea, and locally recycled moisture over the target region in shaping the spatial organization of seasonal precipitation. However, a clear east–west contrast is witnessed in determining the relative importance of each of these major moisture sources where the North Atlantic dictates the moisture supply over the western Mediterranean while moisture from Mediterranean Sea and local recycling play a key role over the eastern Mediterranean. Our analyses also demonstrate a major footprint of the North Atlantic Oscillation (NAO) on precipitation variability over the Mediterranean land as dynamic and thermodynamic anomalies during the negative phase of NAO match with those during wet years and vice versa. The findings reported here are generally consistent across the four reanalysis datasets. Overall, this study establishes the relative roles of adjacent and far-off oceanic and terrestrial evaporative sources over the Mediterranean land and should help in understanding the drivers of precipitation variability and change at varying timescales.
| Original language | English |
|---|---|
| Pages (from-to) | 4109-4127 |
| Number of pages | 19 |
| Journal | Climate Dynamics |
| Volume | 54 |
| Issue number | 9-10 |
| DOIs | |
| State | Published - May 1 2020 |
Funding
We thank two anonymous reviewers for their helpful feedback. This study was funded by the Regional and Global Climate Modeling Program within the Office of Science of the US Department of Energy (DOE), research Grant 116Y136 by the Scientific and Technological Research Council of Turkey (TUBITAK), and research Grant 40248 by the Scientific Research Projects Coordination Unit of Istanbul Technical University (ITU). MA was supported by the National Climate-Computing Research Center which is located within the National Center for Computational Sciences at the Oak Ridge National Laboratory (ORNL) and supported under a Strategic Partnership Project, 2316-T849-08, between DOE and NOAA. UT was supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement no. 1852977. Support for data analysis is provided by the Oak Ridge Leadership Computing Facility at the ORNL. This manuscript has been co-authored by employees of Oak Ridge National Laboratory, managed by UT Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan). We thank two anonymous reviewers for their helpful feedback. This study was funded by the Regional and Global Climate Modeling Program within the Office of Science of the US Department of Energy (DOE), research Grant 116Y136 by the Scientific and Technological Research Council of Turkey (TUBITAK), and research Grant 40248 by the Scientific Research Projects Coordination Unit of Istanbul Technical University (ITU). MA was supported by the National Climate-Computing Research Center which is located within the National Center for Computational Sciences at the Oak Ridge National Laboratory (ORNL) and supported under a Strategic Partnership Project, 2316-T849-08, between DOE and NOAA. UT was supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement no. 1852977. Support for data analysis is provided by the Oak Ridge Leadership Computing Facility at the ORNL. This manuscript has been co-authored by employees of Oak Ridge National Laboratory, managed by UT Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( https://energy.gov/downloads/doe-public-access-plan ).
| Funders | Funder number |
|---|---|
| DOE Public Access Plan | |
| National Climate-Computing Research Center | |
| United States Government | |
| National Science Foundation | 1852977 |
| U.S. Department of Energy | 116Y136 |
| National Oceanic and Atmospheric Administration | |
| National Center for Atmospheric Research | |
| Oak Ridge National Laboratory | 2316-T849-08 |
| UT-Battelle | DE-AC05-00OR22725 |
| Türkiye Bilimsel ve Teknolojik Araştirma Kurumu | 40248 |
| Istanbul Teknik Üniversitesi |