Miquel Tomas-Burguera

The Westerly Index as complementary indicator of the North Atlantic oscillation in explaining drought variability across Europe

This paper analyses the influence of different atmospheric circulation indices on the multi-scalar drought variability across Europe by using the Standardized Precipitation Evapotranspiration Index (SPEI). The monthly circulation indices used in this study include the North Atlantic oscillation (NAO), the East Atlantic (EA), the Scandinavian (SCAN) and the East Atlantic–Western Russia (EA–WR) patterns, as well as the recently published Westerly Index (WI), defined as the persistence of westerly winds over the eastern north Atlantic region. The results indicate that European drought variability is better explained by the station-based NAO index and the WI than by any other combination of circulation indices. In northern and central Europe the variability of drought severity for different seasons and time-scales is strongly associated with the WI. On the contrary, the influence of the NAO on southern Europe droughts is stronger than that exerted by the WI. The correlation patterns of the NAO and WI with the SPEI show a spatial complementarity in shaping drought variability across Europe. Lagged correlations of the NAO and WI with the SPEI also indicate enough skill of both indices to anticipate drought severity several months in advance. As long as instrumental series of the NAO and WI are available, their combined use would allow inferring European drought variability for the last two centuries and improve the calibration and interpretation of paleoclimatic proxies associated with drought.

Forest resilience to drought varies across biomes

Forecasted increase drought frequency and severity may drive worldwide declines in forest productivity. Species-level responses to a drier world are likely to be influenced by their functional traits. Here, we analyse forest resilience to drought using an extensive network of tree-ring width data and satellite imagery. We compiled proxies of forest growth and productivity (TRWi, absolutely dated ring-width indices; NDVI, Normalized Difference Vegetation Index) for 11 tree species and 502 forests in Spain corresponding to Mediterranean, temperate, and continental biomes. Four different components of forest resilience to drought were calculated based on TRWi and NDVI data before, during, and after four major droughts (1986, 1994-1995, 1999, and 2005), and pointed out that TRWi data were more sensitive metrics of forest resilience to drought than NDVI data. Resilience was related to both drought severity and forest composition. Evergreen gymnosperms dominating semi-arid Mediterranean forests showed the lowest resistance to drought, but higher recovery than deciduous angiosperms dominating humid temperate forests. Moreover, semi-arid gymnosperm forests presented a negative temporal trend in the resistance to drought, but this pattern was absent in continental and temperate forests. Although gymnosperms in dry Mediterranean forests showed a faster recovery after drought, their recovery potential could be constrained if droughts become more frequent. Conversely, angiosperms and gymnosperms inhabiting temperate and continental sites might have problems to recover after more intense droughts since they resist drought but are less able to recover afterwards.

Recent changes of relative humidity: regional connections with land and ocean processes

We analyzed changes in surface relative humidity (RH) at the global scale from 1979 to 2014 using both observations and the ERA-Interim dataset. We compared the variability and trends in RH with those of land evapotranspiration and ocean evaporation in moisture source areas across a range of selected regions worldwide. The sources of moisture for each particular region were identified by integrating different observational data and model outputs into a Lagrangian approach. The aim was to account for the possible role of changes in air temperature over land, in comparison to sea surface temperature (SST), but also the role of land evapotranspiration and the ocean evaporation on RH variability. The results demonstrate that the patterns of the observed trends in RH at the global scale cannot be linked to a particular individual physical mechanism. Our results also stress that the different hypotheses that may explain the decrease in RH under a global warming scenario could act together to explain recent RH trends. Albeit with uncertainty in establishing a direct causality between RH trends and the different empirical moisture sources, we found that the observed decrease in RH in some regions can be linked to lower water supply from land evapotranspiration. In contrast, the empirical relationships also suggest that RH trends in other target regions are mainly explained by the dynamic and thermodynamic mechanisms related to the moisture supply from the oceanic source regions. Overall, while this work gives insights into the connections between RH trends and oceanic and continental processes at the global scale, further investigation is still desired to assess the contribution of both dynamic and thermodynamic factors to the evolution of RH over continental regions.

Computation of rainfall erosivity from daily precipitation amounts

Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases.

Global Assessment of the Standardized Evapotranspiration Deficit Index (SEDI) for Drought Analysis and Monitoring

The dataset contains one zip file corresponding to the SEDI. The format of the file is netCDF3. The file contains 1440 longitudes, 720 latitudes and 444 times (from January 1980 to December 2016). Projection is Geographic (WGS84). The SEDI is in standardized units. The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL.

Seasonal and annual daily precipitation risk maps for the Andean region of Peru

We develop for the first time maps of annual and seasonal extreme precipitation risk in the Andean region of Peru. For this purpose, we used the complete daily precipitation records existing in Peru. In each meteorological station, we obtained series of events of de-clustered daily intensity, total precipitation duration, total magnitude and dry-spell length. Using a peak-overthreshold approach we fitted the annual and seasonal series of these variables to a GeneralizedPareto distribution, obtained the distribution parameters and validated the performance of different thresholds to obtain reliable estimations of the precipitation probability. The parameters obtained in the different meteorological stations were mapped using a universal krigging approach using the elevation and the distance to the ocean as co-variables. Maps of parameters were validated using a jack-knife approach and maximum expected precipitation intensity, magnitude, duration and dryspell length estimated for a period of 25 and 50 years. The reliability of the spatial methodology was validated comparing observed precipitation and estimated by the spatial modelling in the different stations.