Abstract

Abstract. The main drawback of the reconstruction of high-resolution distributed global radiation (Rg) time series in mountainous semiarid environments is the common lack of station-based solar radiation registers. This work presents 19 years (2000–2018) of high-spatial-resolution (30 m) daily, monthly, and annual global radiation maps derived using the GIS-based model proposed by Aguilar et al. (2010) in a mountainous area in southern Europe: Sierra Nevada (SN) mountain range (Spain). The model was driven by in situ daily global radiation measurements, from 16 weather stations with historical records in the area; a 30 m digital elevation model; and 240 cloud-free Landsat images. The applicability of the modeling scheme was validated against daily global radiation records at the weather stations. Mean RMSE values of 2.63 MJ m−2 d−1 and best estimations on clear-sky days were obtained. Daily Rg at weather stations revealed greater variations in the maximum values but no clear trends with altitude in any of the statistics. However, at the monthly and annual scales, there is an increase in the high extreme statistics with the altitude of the weather station, especially above 1500 m a.s.l. Monthly Rg maps showed significant spatial differences of up to 200 MJ m−2 per month that clearly followed the terrain configuration. July and December were clearly the months with the highest and lowest values of Rg received, and the highest scatter in the monthly Rg values was found in the spring and fall months. The monthly Rg distribution was highly variable along the study period (2000–2018). Such variability, especially in the wet season (October–May), determined the interannual differences of up to 800 MJ m−2 yr−1 in the incoming global radiation in SN. The time series of the surface global radiation datasets here provided can be used to analyze interannual and seasonal variation characteristics of the global radiation received in SN with high spatial detail (30 m). They can also be used as cross-validation reference data for other global radiation distributed datasets generated in SN with different spatiotemporal interpolation techniques. Daily, monthly, and annual datasets in this study are available at https://doi.org/10.1594/PANGAEA.921012 (Aguilar et al., 2021).

Highlights

  • High-mountain areas in semiarid environments present singular characteristics due to the continuous interaction of alpine conditions in the summits with the surrounding semiarid climate

  • Weather stations are not always equipped to monitor the global radiation or their components, and, they are seldom found in high altitudes, especially over 1500 m a.s.l., which makes it difficult to accurately assess the solar radiation temporal regime and the spatial patterns of solar radiation fields in high-mountain areas

  • A digital elevation model (DEM) with 30 m spatial resolution and 1 m vertical precision was used in this study (Fig. 1)

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Summary

Introduction

High-mountain areas in semiarid environments present singular characteristics due to the continuous interaction of alpine conditions in the summits with the surrounding semiarid climate. M. Liu et al (2012) state that the most difficult issue in solar radiation modeling in data-sparse regions is cloud accounting, due to the rapid spatially and temporally changing weather conditions and the three-dimensional structure of clouds This complexity adds to the heterogeneity resulting from shadowing and reflection due to steep topography (Dubayah, 1992; Batlleìs et al, 2008; Mamassis et al, 2012; Chen et al, 2013; Zhang et al, 2019, 2020). For many studies that could do so, to 2 of the 23 unsolved problems in hydrology (UPH) recently posed by Blöschl et al (2019) in a participatory analytical discussion among the scientific community: UPH 16 “How can we use innovative technologies to measure surface and subsurface properties, states and fluxes at a range of spatial and temporal scales?” and UPH 5 “What causes spatial heterogeneity and homogeneity in runoff, evaporation, subsurface water and material fluxes (carbon and other nutrients, sediments), and in their sensitivity to their controls (e.g., snowfall regime, aridity, reaction coefficients)?”

Study site
Input data
Data quality control
Generation of global radiation maps
Cross validation at weather stations
Results
Daily time series of global radiation in Sierra Nevada
Monthly time series of global radiation in Sierra Nevada
Annual times series of global radiation in Sierra Nevada
Final remarks
Full Text
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