Mediterranean Climate: Variability and Trends


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Most significantly, sites in many Mediterranean-climate regions show downward trends in annual precipitation southern California, Spain, Australia, Chile, and Northern Italy ; and most of North America, the Mediterranean basin, and Chile showed downward trends in summer precipitation.


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Variations in annual and summer precipitation likely contribute to the high biodiversity and endemism characteristic of Mediterranean-climate biomes; the data indicate trends toward harsher conditions over the past 40 years. Submitted by Matthew Deitch.

Deitch et al mediterranean climate variability. Sapundjieff 2 andShaneT. Keywords:Mediterraneanclimate;spatialvariability;interannualvariability;MannKendalltrendsanalysis;precipitationseasonality;dryseason 1. Forexample,ecosystemsoftheMediterraneanbiomecommonlyexperiencecoolwetwintersandWater 9 ,;doi AdditionalanalysistoarticulatethespecicclimaticcharacteristicsoftheMediterraneanbiomecanhelpresearcherstobettercharacterizetheextentofdrysummerfacedbyterrestrialandaquaticorganismsadapted PAGE 3 Water 9 , 3of21totheseregions,aswellasthewatermanagementchallengesnecessarytosupporturbanandagriculturaldevelopment.

Methods 2. UsingaveragemonthlyprecipitationandtemperaturedatafromtheyearWorldClimdataset,weidentiedregionswithtemperatedry-summercharacteristicsasthosehaving: 1. InterannualTrendsinAnnualPrecipitation,WinterPrecipitation,andSummerPrecipitation; andVariabilityWeusedtheMannKendallnon-parametrictrendstesttodeterminewhetherannualprecipitation,percentageofwinterprecipitation,andpercentageofsummerprecipitationhavebeenundergoingastatisticallysignicantupwardordownwardtrendateachsiteoverrecentdecades. Results 3. PAGE 10 Water 9 , 10of21 3. Trends 3. Annualprecipitationtrends,sitesdistinguishedbetweenthosewith20and30yearsofrecord,inareaswithadrysummerclimate;signicanceat 0.

Annualvariabilitytrends,sitesdistinguishedbetweenthosewith20and30yearsofrecord,inareaswithadrysummerclimate;signicanceat 0. FWSprecipitationtrends,sitesdistinguishedbetweenthosewith20and30yearsofrecord,inareaswithadrysummerclimate;signicanceat 0.

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FWSvariabilitytrends,sitesdistinguishedbetweenthosewith20and30yearsofrecord,inareaswithadrysummerclimate;signicanceat 0. PAGE 13 Water 9 , 13of21 3. Summerprecipitationtrends,sitesdistinguishedbetweenthosewith20and30yearsofrecord,inareaswithadrysummerclimate;signicanceat 0. The variation of the intermediate layers is attributed to decadal variability.

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The finer spatial resolution of the input data climatology filters out the noise induced by the mesoscale features, but at the same time is such that it smoothes less the large-scale features. The temporal resolution is such that it smoothes the strong seasonal, interannual and decadal variability so that the final product is able to resolve in more detail the climatic variability and identify possible warming trends. The gridded fields cover the geographical region 6. The mesoscale features and other smaller patches are therefore filtered out and the climatologies used for the indices' calculations focus on the variability of the large-scale features.

The influence of the uneven distribution in space where a large number of data points are concentrated in a very small area and within a very short period is controlled by applying different weights and lower than 1 to each of these data points because such points cannot be considered independent in a climatological analysis.

The characteristic length of weighting was set to be equal to 0. Detrending was applied in the observations used for the reference climatologies in order to remove the uneven spatial distributions in time. The input gridded data are listed below. They are stored in netCDF files and are accessible from the Zenodo platform, a research platform where papers, data, software codes or any other object contributing to the reproducibility of scientific results can be uploaded and then cited using a digital object identifier DOI.

Annual climatology reference , obtained by analysing all data regardless of month or season for the whole period from to Annual decadal climatology , obtained by analysing all data regardless of month or season for each of the 57 running decades from — to — Seasonal climatology reference , obtained by analysing all data of the whole period from to falling within each season. Seasonal decadal climatology , obtained by analysing all data falling within each season for each of the 57 running decades from — to — It is important to note that in the used input climatology, each gridded field is accompanied by an error field that allows one to assess the reliability of the input data.

This helps to objectively identify areas with poor data coverage, mask them and exclude them from further processing. In all products, temperature and salinity anomalies have been used. Anomaly is defined as the difference between the value of a grid point and a mean climatological reference. Climate shift is defined as the difference between two successive year averages. It is noted that in the climate shifts presented in this work, the period to contains 3 decades and the period to contains 6 years more because the period from to is treated as a decade.

The user of course can choose between any period and average the decades according to their needs of each study since the available product includes all 57 running decades from where the climates are computed. The thickness of the layers was used as weights for the vertical averaging calculated as half of the distance between adjacent depths.

The following weights were used for the 31 standard depth levels: 2. In the case of the annual fields, 30 weights are used starting from the second value 5. The used weights are available with the netCDF files used for the computation of the indices.


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  • Characterizing Precipitation Variability and Trends in the World's Mediterranean-Climate Areas.

For the estimation of the OHC anomalies the following methodology was used. By multiplying the volume by the T anomalies, by the density of seawater, and by the specific heat, we obtain the OHC anomaly of a specific grid point at each standard depth. By integrating over a depth layer and over all of the analysis area, we obtain the OHC anomaly in Joules for the whole Mediterranean Sea according to the following equation:.

Mediterranean Sea climatic indices: monitoring long-term variability and climate changes

In the current climatologies density and specific heat of seawater are not calculated separately, but it would be possible to derive them from T and S gridded fields. Such calculations will be available in future releases of the indices. A mean basin volume is estimated at 3. The produced climatic indices for the whole Mediterranean Sea 6.

Mediterranean Climate‐Variability and Trends

We outline below some of the capabilities of the new product. The explanation of the long-term variability patterns that are revealed and attribution of possible causes is out of the scope of this work. A short overview of these was given in the introduction to facilitate the viewing of the products for those readers who are not familiar with the Mediterranean complex dynamics. The comparison of two successive year averages of heat and salt content anomalies for the period to can be used for the evaluation of the Mediterranean Sea climate changes. The year periods are averages of three successive decades: the first one refers to the decades — to — and the second to — to — The two year successive periods were selected for consistency with the World Meteorological Organization's recommendation of using as climate normals year periods.

The western Mediterranean surface layer Fig. The surface layer of the eastern Mediterranean Fig. The deep waters are warming almost everywhere except the southern Adriatic, the southern Levantine and the south-western Ionian basin Fig. Regarding salinity, it is important to notice that in the whole western Mediterranean there is a clear OSC increase throughout the whole water column Fig.

Notable salt increases are found at the Shikmona gyre and the south-western Ionian Sea, following the patterns of the heat content. We observe that apart from the strong spatial variability shown in Figs. To get a more detailed insight into the long-term fluctuations we show in Fig.

Mediterranean Climate Variability - Google книги

As reference, the annual climatology of all years was used. The trend for the whole water column Fig. The temperature pattern reveals two main areas of long-term decreasing trends Fig. At the surface Fig. This strong signal can also be traced out at the Alboran Sea and the southern Algerian basin Fig. Also, there are more spatial maskings in the current indices because of the statistical significance of the linear trend. We presented a new product of climatic indices for the Mediterranean Sea oriented to the description and study of the long-term variability and climate change of the area.

References:

So far, the insufficient spatial and temporal coverage of historical in situ data has induced large uncertainties and differences among the used approaches, especially in large basin-scale estimations. Thanks to data repositories such as SeaDataNet, which are improving continuously in terms of abundance, quality and state-of-the-art mapping techniques implemented by the DIVA software tool , we were able to interpolate in an optimal way and produce high-resolution products. These products can fill data gaps and can be used in a more efficient way by many applications, for the study of the past, present and future climate changes.

SeaDataNet infrastructure includes data of more than data providers which are quality controlled, archived in data centres and distributed into the infrastructure by the SeaDataNet participants. The data aggregation and validation are performed by regional experts and in close collaboration with the data originators for ensuring the highest quality of the delivered data sets.

To avoid duplicates, data not belonging to the SeaDataNet consortium are not included in the repository. In the next version of this product, these additional sources will be combined with the SeaDataNet data. Future improvements include the use of density climatological fields instead of a constant value at the OHC estimations.

Another improvement concerns the correction of the historical bathythermograph data, although previous studies indicated that it does not alter the final results. AI created the climatic index product, wrote the first version of the manuscript and prepared the figures. CT prepared Fig. It cannot be guaranteed that the product is free from errors or omissions. Correct and appropriate product interpretation and usage are solely the responsibility of data users. Edited by: Giuseppe M.

Adloff, F. Beckers, J. Durack, P. Fusco, G. Giorgi, F. Gouretski, V. Iona, A. Klein, B. Lascaratos, A.

Levitus, S. Lozier, M. Macias, D. Malanotte-Rizzoli, P.

Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends Mediterranean Climate: Variability and Trends
Mediterranean Climate: Variability and Trends

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