Control de calidad de siete variables del banco nacional de datos de AEMET

Tomás-Burguera, Miquel; Castañeda, Azucena Jiménez; Rico, M. Yolanda Luna; Morata, A.; Serrano, Sergio Martín Vicente; Hidalgo, José Carlos González; Beguería, Santiago

doi:10.14198/xcongresoaecalicante2016-38

Cited by 13 publications

(8 citation statements)

References 2 publications

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“…process, which consisted of six defined steps (Figure 2): Step 1: (QC) consisted of discarding weather stations without metadata (i.e., latitude, longitude, elevation and recognized identifier), in addition to those located in the Amazon and insular territories, out of the analysed study areas. Step 2: (QC) consisted of data screening using the protocol proposed by Tomás‐Burguera et al . (2016), which removes questionable samples according to Durre et al . (2010).…”

Section: Methodsmentioning

confidence: 99%

Maximum and minimum air temperature lapse rates in the Andean region of Ecuador and Peru

Navarro-Serrano

López‐Moreno

Domínguez‐Castro

et al. 2020

Intl Journal of Climatology

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To know the vertical distribution of air temperature is complex, and this is necessary for different applications. The main explanatory variable of air temperature is elevation above sea level, whose relationship with air temperature is measured by air temperature lapse rates (LRs). LRs can vary considerably spatiotemporally due to a wide spectrum of geographical, environmental, and other atmospheric factors. Our study presents the first comprehensive assessment of spatiotemporal changes of LRs over the Tropical Andes. Our study is focused on the Peruvian and Ecuadorian Andes, divided in two subregions by the parallel 9.5° (i.e., north and south). Maximum and minimum air temperatures were employed from 115 quality checked weather stations, for the period 1994–2011. Maximum (LRmax) and minimum (LRmin) air temperature lapse rates have been calculated for the whole study period. The effects of seasonality, humidity content and ENSO on the variability of LRs have been analysed. Results show that LRs have large spatiotemporal variability, since references values of LRmax range from −3.57 (South, dry season) to −4.77 (North, wet season), and LRmin range from −3.78 (North, dry season) to −4.93°C·km−1 (South, dry season), in function of season and subregion. Results indicate that the ENSO phases contribute significantly to the variability of southern subregion LRs. This study also presents that minimum air temperatures were more unpredictable than maximum air temperatures in terms of error and uncertainty, as a consequence of the larger spatial variability of nocturnal air temperatures, mainly influenced by local topography. In conclusion, this work goes deeper into the need to obtain precise LRs adapted to the study region, and shows that the use of standard LR values can cause significant failures in modelling air temperature in regions of complex terrain, such as the Andes.

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Section: Methodsmentioning

confidence: 99%

Maximum and minimum air temperature lapse rates in the Andean region of Ecuador and Peru

Navarro-Serrano

López‐Moreno

Domínguez‐Castro

et al. 2020

Intl Journal of Climatology

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“…Therefore, we applied the robust quality control procedure described by Tomás‐Burguera et al . (), involving the removal of questionable records according to Durre et al . ().…”

Section: Methodsmentioning

confidence: 99%

Estimation of near‐surface air temperature lapse rates over continental Spain and its mountain areas

Navarro-Serrano

López‐Moreno

Azorín-Molina

et al. 2018

Intl Journal of Climatology

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Although the mean environmental lapse rate (MELR) value (a linear decrease of −6.5 °C/km) is the most widely used, near‐surface (i.e., non‐free atmosphere) air temperature lapse rates (NSLRs; measured at ~1.5 m height) are variable in space and time because of their dependence on topography and meteorological conditions. In this study we conducted the first analysis of the spatial and temporal variability of NSLRs for continental Spain and their relationship to synoptic atmospheric circulation (circulation weather types [CWTs]), focusing on major mountain areas including the Pyrenees, Cantabrian, Central, Baetic, and Iberian ranges. The results showed that the NSLR varied markedly at spatial and seasonal scales and depended on the dominant atmospheric conditions. The median NSLR values were weaker (less negative) than the MELR for the mountain areas (Pyrenees −5.17 °C/km; Cantabrian range −5.22 °C/km; Central range −5.78 °C/km; Baetic range −4.83 °C/km; Iberian range −5.79 °C/km) and for the entire continental Spain (−5.28 °C/km). For the entire continental Spain the steepest NSLR values were found in April (−5.80 °C/km), May (−5.58 °C/km), and October (−5.54 °C/km) because of the dominance of northerly and westerly advections of cold air. The weakest NSLR values were found in July (−4.67 °C/km) and August (−4.78 °C/km) because of the inland heating, and in winter because of the occurrence of thermal inversions. As the use of the MELR involves the assumption of large errors, we propose 1 zonal, 12 monthly, 11 CWTs, and 132 hybrid monthly–CWTs NSLRs for each of the mountain ranges and for the entire continental Spain. More regional studies are urgently needed to accurately assess the NSLR as a function of atmospheric circulation conditions.

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“…The gridded dataset was created based on all daily observational information from the National Spanish Meteorological Service (AEMET) by means of an interpolation scheme of universal kriging using as input the meteorological data measured in the different meteorological stations and the terrain elevation. The climate series were subjected to a homogenization process and a careful quality control (see details in Tomas-Burguera et al [46]). Additional information about the dataset development, interpolation methodology, and validation are available in Vicente-Serrano et al [47].…”

Section: Datamentioning

confidence: 99%

Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

2021

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Flash drought is the result of strong precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED), which triggers a rapid decline in soil moisture and stresses vegetation over short periods of time. However, little is known about the role of precipitation and AED in the development of flash droughts. For this paper, we compared the standardized precipitation index (SPI) based on precipitation, the evaporative demand drought index (EDDI) based on AED, and the standardized evaporation precipitation index (SPEI) based on the differences between precipitation and AED as flash drought indicators for mainland Spain and the Balearic Islands for 1961–2018. The results show large differences in the spatial and temporal patterns of flash droughts between indices. In general, there was a high degree of consistency between the flash drought patterns identified by the SPI and SPEI, with the exception of southern Spain in the summer. The EDDI showed notable spatial and temporal differences from the SPI in winter and summer, while it exhibited great coherence with the SPEI in summer. We also examined the sensitivity of the SPEI to AED in each month of the year to explain its contribution to the possible development of flash droughts. Our findings showed that precipitation is the main driver of flash droughts in Spain, although AED can play a key role in the development of these during periods of low precipitation, especially in the driest areas and in summer.

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Control de calidad de siete variables del banco nacional de datos de AEMET

Cited by 13 publications

References 2 publications

Maximum and minimum air temperature lapse rates in the Andean region of Ecuador and Peru

Maximum and minimum air temperature lapse rates in the Andean region of Ecuador and Peru

Estimation of near‐surface air temperature lapse rates over continental Spain and its mountain areas

Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

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