Marta Angulo-Martínez

A Multiscalar Global Drought Dataset: The SPEIbase: A New Gridded Product for the Analysis of Drought Variability and Impacts

This work has been supported by the research projects CGL2008-01189/BTE and CGL2006-11619/HID, funded by the Spanish Commission of Science and Technology and FEDER; EUROGEOSS (FP7-ENV-2008-1-226487) and ACQWA (FP7-ENV-2007-1- 212250), funded by the VII Framework Programme of the European Commission; and “Las sequias climaticas en la cuenca del Ebro y su respuesta hidrologica” and “La nieve en el Pirineo aragones: Distribucion espacial y su respuesta a las condiciones climatica,” funded by “Obra Social La Caixa” and the Aragon Government.

The NAO Impact on Droughts in the Mediterranean Region

This chapter shows the influence of the North Atlantic Oscillation (NAO) on droughts in the entire Mediterranean region between 1901 and 2006. The analysis has been based on identification of positive and negative NAO winters and also detection of the anomalies of drought severity by means of the Standardized Precipitation Evapotranspiration Index (SPEI). The analysis is focussed on the winter NAO. Nevertheless, given that the SPEI drought indicator can be obtained at different time-scales, the study shows how the effects of the winter NAO on droughts are propagated for the following months when long time scales are considered. In general, during the positive phases, the negative SPEI averages are recorded in Southern Europe (the Iberian Peninsula, Italy and the Balkans), areas of Turkey and northwest Africa. On the contrary, the SPEI averages are found positive in northeast Africa. The opposite configuration, but with some differences in the spatial patterns and the magnitude of the SPEI averages, is found during the negative NAO years. The findings of this study should be of great applicability in terms of developing early warning systems. The established relationships between NAO phases and drought indices seem appropriate for drought prediction over large areas of the Mediterranean basin.

Use of disdrometer data to evaluate the relationship of rainfall kinetic energy and intensity (KE-I)

Determination of rainfall kinetic energy (KE) is required to calculate erosivity, the ability of rainfall to detach soil particles and initiate erosion. Disdrometers can measure rainfall KE by measuring raindrop size and velocity. In the absence of such devices, KE is usually estimated with empirical equations that derive KE from measured rainfall intensity (I). We evaluated the performance of 14 different KE-I equations to estimate the 1min KE and event total KE, and compared these results with 821 observed rainfall events recorded by an optical disdrometer in the inner Ebro Basin, NE Spain. We also evaluated two sources of bias when using such relationships: bias from use of theoretical raindrop terminal velocities instead of measured values; and bias from time aggregation (recording rainfall intensity every 5, 10, 15, 30, and 60min). Empirical relationships performed well when complete events were considered (R(2)>0.90), but performed poorly for within-event variation (1min resolution). Also, several of the KE-I equations had large systematic biases. When raindrop size is known, estimation of terminal velocities by empirical laws led to overestimates of raindrop velocity and KE. Time aggregation led to large under-estimates of KE, although linear scaling successfully corrected for this bias.

Modeling the spatial distribution of soil properties by generalized least squares regression: Toward a general theory of spatial variates

Assessment of the spatial distribution of soil properties has achieved considerable interest among soil scientists, both for testing hypotheses about soil formation processes and for predicting the properties of soils at nonsampled locations (mapping). In this paper, we provide a discussion of the various approaches to the modeling of spatial variates, and we propose a modeling framework that is able to incorporate the most important effects usually found in spatial variates, including fixed and random spatial effects, spatial trends, and heteroscedasticity. We provide a case study of the analysis of eight soil properties in a mountain catchment in the Spanish Pyrenees. As explanatory covariates, we use several topography parameters, which can be related to the pedogenetic processes active in the area. Several of them proved useful for explaining the variability of soil properties, explaining up to 77% of their variance. We focus on the importance of model selection in order to determine which effects are relevant for modeling each soil parameter. We find that the full model is not necessarily optimal for all the variables tested and that the model should be adapted to the complexity of each individual case. This paper is a contribution to the discussion on the modeling of spatial variates and to the eventual development of a general theory of spatial variates.

Comparison of precipitation measurements by OTT Parsivel 2 and Thies LPM optical disdrometers

Optical disdrometers are present weather sensors with the ability of providing detailed information of precipitation such as rain intensity, radar reflectivity or kinetic energy, together with discrete information on the particle size and fall velocity distribution (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterization of precipitation, being useful in several research fields and applications. In this article the performance of two extensively used optical disdrometers, the most recent version of OTT Parsivel disdrometer and Thies Clima Laser Precipitation Monitor (LPM), is evaluated. During two years four collocated optical disdrometers, two Thies Clima LPM and two OTT Parsivel, collected up to 100,000 minutes of data and up to 30,000 minutes with rain in more than 200 rainfall events, with intensities peaking at 277 mm h−1 in one minute. The analysis of these records show significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw particle size and velocity distri∗Correspondence to: santiago.begueria@csic.es Preprint submitted to Elsevier March 6, 2018 bution (PSVD) estimated by the two sensors. Thies LPM recorded a larger number particles than Parsivel and a higher proportion of small particles than OTT Parsivel, resulting in higher rain rates and totals and differences in radar reflectivity and kinetic energy. These differences increased greatly with rainfall intensity. Posible causes of these differences, and their practical consequences, are discussed in order to help researchers and users in the election of the sensor, pointing out at the same time limitations to be addressed in future studies.

Evaluation of the Relationship Between the NAO and Rainfall Erosivity in NE Spain During the Period 1955–2006

Rainfall erosivity is the ability of precipitation to erode soil. Microerosion processes due to the impact of raindrops on the soil – rainsplash – represent an important mechanism of detachment of soil particles, which might be removed thereafter by surface runoff. The annual and interannual patterns of rainfall erosivity are controlled by the variability of rainfall intensity. This study analyses the interannual variability of daily rainfall erosivity due to precipitation in the NE of Spain during the period 1955–2006, and its connection with the North Atlantic Oscillation (NAO). It was found that the erosive power of rainfall is stronger during the negative phase of NAO and weaker during positive NAO conditions, as are the rainfall amounts. Daily rainfall erosivity series were adjusted to a Generalized Pareto probability distribution for positive and negative NAO phases for assessing the effect of NAO on extreme events. Results showed higher values expected for a given return period in most of the area under negative NAO conditions. These findings would be useful in the implementation of soil conservation strategies.