Weather types and spatial variability of precipitation in the Iberian Peninsula

Abstract

The relationship between circulation weather types (WTs) and the spatial variability of precipitation across the Iberian Peninsula were studied using a high density, quality controlled, homogenized monthly precipitation database with approximately 3000 stations and interpolated to a 10 km grid. The circulation WTs were computed using an objective version of the Lamb classification centered on the Iberian Peninsula. A total of 26 WTs were selected for the period 1948-2003. Daily WTs were grouped to obtain their monthly frequencies, and used as potential independent variables in a linear least-square non-negative regression model with a forward stepwise selection. Results show the impact of each WT on precipitation in the Iberian Peninsula with a spatial resolution which had never been achieved before and additionally were obtained on a monthly scale highlighting the large seasonal cycle observed in each class, and including significantly different patterns in winter and summer. Nevertheless, results confirm that most of the precipitation in the Iberian Peninsula is produced by just a few WTs, with W, SW and C being the most influential. The association between WTs and precipitation is more robust in winter months and for the western IP areas, while it is lower during summer months and for the eastern IP areas. Spatial analysis revealed that precipitation on the Mediterranean coastland is mostly related with easterly flows (NE, E, SE and their hybrid counterparts), while on the Cantabrian coastland. N and NW flows are the most influential WTs. In general, cyclone-related types are the least frequent ones and also the most efficient in generating precipitation; while anticyclone-related types have the highest frequencies, but also the lowest contribution to total monthly rainfall in the Iberian Peninsula.

Circulation weather types and spatial variability of daily precipitation in the Iberian Peninsula

“…Overall, it is interesting to note from Table 2 that the mean annual frequencies of the Directional, Cyclonic, and Anticyclonic WTs are roughly 50, 10, and 40%, respectively. These results are similar with those described in Cortesi et al (2013b), in which the same reanalysis dataset EMSLP was employed, but during a slightly different period (1948-2003 instead of 1950-2003). In addition, new information regarding the monthly means and the WTs sub-totals are grouped into seasons.…”

“…In fact, the modeling approach presents misleading results for the less frequent WTs, implying positive (negative) bias for the wet (dry) WTs. These biases are responsible that the apparent negligible contribution from the drier WTs and exaggerated contribution associated to wetter WTs (compare Table 2 from Cortesi et al, 2013b with present work Table 3). …”

“…However, the use of a high resolution daily dataset implies much more robust results, in particular we have noticed that the monthly approach has serious limitations, namely positive (negative) bias for the wet (dry) WTs, quite often stating that the contribution from drier WTs is negligible or null while the contribution of wetter WTs is overestimated. For comparison see the large number of zero entrances in the individual WTs contribution in Table 2 (Cortesi et al, 2013b) that are not negligible at all in the corresponding analysis in the present work (Table 3). Additionally we have obtained finer spatial detail results of the WT impact in precipitation and novel results related with combined analysis of precipitation indices related to WTs.…”

“…All these indexes (except the WTs Frequency) are first calculated for each individual pixel of the precipitation grid, and then are averaged over the 1673 Iberian pixel (including Balearic Islands). The shift from monthly to daily precipitation allows to compute new rainfall indexes such as the Mean Precipitation of each WT, the Precipitation Intensity and Efficiency that were not studied in the previous work (Cortesi et al, 2013b). In that work a large number of regression models were developed at the monthly scale for each station; however, such approach presents serious limitations, for example the systematical overestimation of precipitation assigned to the WTs that were selected as predictors by the stepwise regression model and vice versa, the wrong attribution of no rainfall amount to the WTs that were not selected as predictors.…”

The influence of circulation weather patterns at different spatial scales on drought variability in the Iberian Peninsula

“…Typically, applications to the Iberian Peninsula concentrate on climatic trends (Paredes et al, 2006;Lorenzo et al, 2008), on drought events (Trigo and DaCamara, 2000;VicenteSerrano and López-Moreno, 2006;Garcia-Herrera et al, 2007), on very wet years (Vicente- Serrano et al, 2011) or to assess the changes in present and future CWTs frequency (Lorenzo et al, 2011). In particular, several authors have applied different methodologies to study the influence of weather-type frequency on precipitation in Iberia using different datasets and periods of study (e.g., Trigo and DaCamara, 2000;Santos et al, 2005;Lorenzo et al, 2008;Cortesi et al, 2013). However, to the best of our knowledge, there is no application for the entire Iberian Peninsula including an analysis of the relationship between the CWT frequencies and the intensity, as well as, the spatial differences of droughts with detailed spatial scales for winter and summer.…”