João Filipe Santos

Spatial and temporal variability of droughts in Portugal

[1] An analysis of droughts in mainland Portugal based on monthly precipitation data, from September 1910 to October 2004, in 144 rain gages distributed uniformly over the country is presented. The drought events were characterized by means of the Standardized Precipitation Index (SPI) applied to different time scales (1, 6, and 12 consecutive months and 6 months from April to September and 12 months from October to September). To assess spatial and temporal patterns of droughts, a principal component analysis (PCA) and K-means clustering (KMC) were applied to the SPI series. In this way, three different and spatially well-defined regions with different temporal evolution of droughts were identified (north, central, and south regions of Portugal). A spectral analysis of the SPI patterns obtained with principal component analysis and clusters analysis, using the fast Fourier transform algorithm (FFT), showed that there is a manifest 3.6-year cycle in the SPI pattern in the south of Portugal and evident 2.4-year and 13.4-year cycles in the north of Portugal. The observation of the drought periods supports the occurrence of more frequent cycles of dry events in the south (droughts from moderate to extreme approximately every 3.6 years) than in the north (droughts from severe to extreme approximately every 13.4 years). These results suggest a much stronger immediate influence of the NAO in the south than in the north of Portugal, although these relations remain a challenging task.

SPI Modes of Drought Spatial and Temporal Variability in Portugal: Comparing Observations, PT02 and GPCC Gridded Datasets

Regional drought modes in Portugal are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on various time scales using the three precipitation datasets covering the period 1950–2003: (i) The observation dataset composed of 193 rain-gauges distributed almost uniformly over the country, (ii) the PT02 high-resolution gridded dataset provided by the Portuguese Meteorological Institute, and (iii) the GPCC dataset with 0.5° spatial resolution. Results suggest that the three datasets well agree in identifying the principal drought modes, i.e. two sub-regions in northern and southern Portugal with independent climate variability. The two sub-regions appear stable when the SPI time scale is varied from 3- to 24-month, and the associated rotated principal component scores (RPCs) do not show any statistically significant linear trend. The degree of similarity between the rotated loadings or REOFs of different SPI time scales for the three used datasets was examined through the congruence coefficients, whose results show a good agreement between the three datasets in capturing the main Portuguese sub-regions. A third spatial mode in central-eastern Portugal was identified for SPI-24 in PT02, with the associated RPC characterized by a statistically significant downward trend. The stability of the identified sub-regions as a function of studied time period was also evaluated applying the same methodologies to a set of three different time windows and it was found that the southern sub-region is very stable but the northern and central-eastern sub-regions are very sensitive to the selected time window.

Trends In Hydrologic Time Series

Nowadays it is often mentioned that the Earth is already suffering from climate change effects: it is no longer a matter of future climate scenarios, but rather frequent abnormal climate occurrences. If changes are already happening then they should be embedded in some of the hydrologic time series, with emphasis on those series more closely related to the weather, such as the rainfall series. In the previous scope several studies were carried out aiming at identifying trends in long Portuguese hydrologic time series and at relating such trends with the climate change issue. Some of the models applied for that purpose, as well as some of the results achieved, are briefly summarized. In general terms the studies showed that for the time being the hydrologic time series do not exhibit the trends that are generally pointed out as typifying the climate change effects.

Estimation of monthly stream flows based on the sequential water budget technique applied to the Thornthwaite potential evapotranspiration

In Portugal mainland, the measurement of stream flows started later then the measurement of the majority of the other hydrologic variables. Also the former measurements were not carried out systematically, thus resulting in stream flow series not only with several faults, but also with reduce length, circumstances that often compromise their utilization either for research or design purposes. Based on the records at sixteen Portuguese climatologic stations it is stressed that the sequential water budget technique applied to the Thornthwaite potential evapotranspiration may provide a stream flow evaluation model having in view the fulfilment but, especially, the extension of monthly flow data. As the number of parameters and the data requirements of the previous technique and model are relatively modest it is possible, by that way, to estimate monthly stream flows even in regions with scarce hydrologic information.

Trends in rainfall and streamflow series: Portuguese case studies

During the history of the Earth, numerous large-scale climate changes occurred, some of them with a cyclic nature. The majority of such changes happened in periods of hundreds, thousands or even millions of years as a result of natural causes, like small variations in Earth’s orbit that change the amount of solar energy received by the planet. However, in recent decades, it has been progressively accepted by the scientifi c community that the emission of greenhouse gases into the atmosphere is the major driving force of the climate change that presumably is occurring since the last century and mainly since the last 50–75 years. However, if there was a change in such a recent and short period, then the time series of the hydrologic variables more directly related to the climate, as the rainfall or the temperature, should denote signs of it, in the form of trends or non-homogeneities. In the previous scope, several studies have been conducted for mainland Portugal aiming at identifying trends in long hydrological time series and at trying to understand those trends from a climate change perspective. Some of the models applied for that purpose, as well as some of the results thus achieved, are briefl y summarized. In general terms, the studies showed that the analyzed time series do not show the trends that are generally pointed out as denoting signs of the climate change, possibly due to their pronounced natural variability and to the insuffi cient length of the recording periods. There was only one exception, the rainfall in March which, in relative terms, denotes a signifi cant decrease over mainland Portugal, such a decrease being however very small when considered in absolute terms.