Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in Portugal

Abstract

Abstract. Distinction between drought and aridity is crucial to understand water scarcity processes. Drought indices are used for drought identification and drought severity characterisation. The Standardised Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI) are the most known drought indices. In this study, they are compared with the modified PDSI for Mediterranean conditions (MedPDSI) and the Standardised Precipitation Evapotranspiration Index (SPEI). MedPDSI results from the soil water balance of an olive crop, thus real evapotranspiration is considered, while SPEI uses potential (climatic) evapotranspiration. Similarly to the SPI, SPEI can be computed at various time scales. Aiming at understanding possible impacts of climate change, prior to compare the drought indices, a trend analysis relative to precipitation and temperature in 27 weather stations of Portugal was performed for the period 1941 to 2006. A trend for temperature increase was observed for some weather stations and trends for decreasing precipitation in March and increasing in October were also observed for some locations. Comparisons of the SPI and SPEI at 9-and 12-month time scales, the PDSI and Med-PDSI were performed for the same stations and period. SPI and SPEI produce similar results for the same time scales concerning drought occurrence and severity. PDSI and Med-PDSI correlate well between them and the same happened for SPI and SPEI. PDSI and MedPDSI identify more severe droughts than SPI or SPEI and identify drought occurrence earlier than these indices. This behaviour is likely to be related with the fact that a water balance is performed with PDSI and MedPDSI, which better approaches the supplydemand balance.

Stock Volume Dependency of Forest Drought Responses in Yunnan, China

“…To ensure the selected time scale and the corresponding SPEI were truly representative and robust, the average values of R 2 in these regression models, between the SPEI on adjacent time scales and dEVI, were used as references; in other words, sliding windows of three months and five months were used to confirm the average value of R 2 on adjacent time scales. To reduce the interference from miscellaneous data, the average values of SPEI and dEVI in every grade of drought (eight grades) [64] (Table 1), were used as the base data for the linear regression models. The grades in this table are a modified version of those reported by Paulo et al [64], and the proportion of forest grids in each grade to the total number of grids exceeded 5%.…”

“…To reduce the interference from miscellaneous data, the average values of SPEI and dEVI in every grade of drought (eight grades) [64] (Table 1), were used as the base data for the linear regression models. The grades in this table are a modified version of those reported by Paulo et al [64], and the proportion of forest grids in each grade to the total number of grids exceeded 5%.…”

Spatial and temporal variability of precipitation and drought in Portugal

“…It mainly consists of (a) assuming a rainfed olive orchard as a drought reference crop, (b) replacing the potential climatic evapotranspiration (ET) computed with the Thornthwaite method by the reference ET computed with the FAO-PM method (Allen et al, 1998) to estimate the actual evapotranspiration (ETa) of the reference olive orchard, (c) computing ETa with the dual crop coefficient approach, thus, partitioning it into plant transpiration and soil evaporation to make ETa more sensitive to the available soil water, (d) performing a sequential soil water balance that overcomes the limitations of the original Palmer formulation, (e) replacing the climate characteristic used for the standardization of the Palmer moisture anomaly index z by the inverse of the standard deviation of the monthly moisture departures, which are precursors of the z index. The resulting soil water balance components show a better adherence to the vegetation reality than for the original PDSI, e.g., actual ET for the MedPDSI is higher during winter and spring and is generally lower in summer, and the MedPDSI is more sensitive to dry and wet anomalies than the PDSI (Pereira et al, 2007;Paulo et al, 2012;Rosa et al, 2010a).…”

Spatial patterns of European droughts under a moderate emission scenario

“…However, the authors more thoroughly discussed on that in Spinoni et al (2015a, b) and the reader can also find more details on other recent publications, such as Paulo et al (2012); Vicente-Serrano et al (2014); Kingston et al (2015).…”