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[1] A new publicly available daily gridded precipitation data set over mainland Portugal is presented. This data set is also combined with a recent Spanish data set to obtain a high resolution (0.2°× 0.2°) Iberian data set, labeled IB02. This data set covers the period from 1950 to 2003 and is based on a dense network, with more than 2000 and 400 quality-controlled stations over Spain and Portugal, respectively. The ordinary kriging method, applied over Portugal for consistency with the Spanish data set, performs slightly better than simpler interpolation techniques tested over Portugal. Additionally, this paper evaluates four global gridded data sets: two based on rain gauges (Climate Research Unit (CRU) and Global Precipitation Climate Center (GPCC)) and two European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses (ERA-40 and ERA-Interim), comparing them with the IB02 data set. The main features of the spatial distribution of IB02 mean annual precipitation are reasonably captured by the global data sets, despite their dry biases, mostly in mountainous regions. The four data sets perform better in western Iberia and are able to identify the major drought spells at the Iberian scale. Despite these similarities, GPCC outperforms CRU and ERA-Interim is superior to ERA-40 with respect to several aspects, such as annual cycle and drought detection. The performance of CRU is similar to that of ERA-Interim. The frequency of wet days is overestimated by reanalyses, mainly by ERA-Interim, while heavy precipitation events are underestimated, mostly by ERA-40. At 5 day scales, ECMWF reanalyses reveal difficulties in predicting the magnitude of precipitation, despite their greater ability to estimate the peak locations.Citation: Belo-Pereira, M., E. Dutra, and P. Viterbo (2011), Evaluation of global precipitation data sets over the Iberian Peninsula,

The estimation of the background error statistics is a key issue for data assimilation. Their time average is estimated here using an analysis ensemble method. The experiments are performed with the nonstretched version of the Action de Recherche Petite Echelle Grande Echelle global model, in a perfect-model context. The global (spatially averaged) correlation functions are sharper in the ensemble method than in the so-called National Meteorological Center (NMC) method. This is shown to be closely related to the differences in the analysis step representation. The local (spatially varying) variances appear to reflect some effects of the data density and of the atmospheric variability. The resulting geographical contrasts are found to be partly different from those that are visible in the operational variances and in the NMC method. An economical estimate is also introduced to calculate and compare the local correlation length scales. This allows for the diagnosis of some existing heterogeneities and anisotropies. This information can also be useful for the modeling of heterogeneous covariances based, for example, on wavelets. The implementation of the global covariances and of the local variances, which are provided by the ensemble method, appears moreover to have a positive impact on the forecast quality.

A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

ABSTRACT:In this study precipitation from a high resolution WRF climate simulation is presented and evaluated against daily gridded observations in the Iberian Peninsula. The simulation corresponds to a dynamical downscaling of ERA-Interim, in the period 1989-2009, performed with two nested grids, at 27 and 9 km horizontal resolution. The higher resolution simulation indicates a significantly improved representation of Iberian precipitation fields, at all timescales, with emphasis on the representation of variability and of extreme weather statistics. Results compare well with recent studies with other models and/or for other regions, further supporting the use of WRF as a regional climate model.