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Juan Ignacio López-Moreno published an article in March 2018.
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(2004 - 2018)
(2004 - 2018)
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Article 1 Read 0 Citations Air and wet bulb temperature lapse rates and their impact on snowmaking in a Pyrenean ski resort Published: 09 March 2018
Theoretical and Applied Climatology, doi: 10.1007/s00704-018-2448-y
A set of 17 air temperature and relative humidity sensors were used to analyze the temporal variability of surface air temperature (Tair), wet bulb temperature (Twb), and daily snowmaking hours (SM, number of hours per day with Twb < − 2 °C), lapse rates, and the occurrence of thermal inversions at the Formigal ski resort (Spanish Pyrenees) from December to March during three consecutive ski seasons (2012–2013, 2013–2014, and 2014–2015). The Tair and Twb lapse rates showed strong hourly and daily variability, with both exhibiting almost identical temporal fluctuations. The Twb exhibited average lapse rates that were slightly steeper (− 5.2 °C/km) than those observed for Tair (− 4.9 °C/km). The less steep lapse rates and most thermal inversions were observed in December. Days having less (more) steep Tair and Twb lapse rates were observed under low (high) wind speeds and high (low) relative humidity and air pressure. The temporal dynamics of the SM lapse rates was more complex, as this involved consideration of the average Tair in the ski resort, in addition to the driving factors of the spatio-temporal variability of Twb. Thus, on a number of cold (warm) days, snowmaking was feasible at all elevations at the ski resort, independently of the slopes of the lapse rates. The SM exhibited an average daily lapse rate of 8.2 h/km, with a progressive trend of increase from December to March. Weather types over the Iberian Peninsula tightly control the driving factors of the Tair, Twb, and SM lapse rates (wind speed, relative humidity, and Tair), so the slopes of the lapse rates and the frequency of inversions in relation to elevation for the three variables are very dependent on the occurrence of specific weather types. The less steep lapse rates occurred associated with advections from the southeast, although low lapse rates also occurred during advections from the east and south, and under anticyclonic conditions. The steepest Tair and Twb lapse rates were observed during north and northwest advections, while the steepest rates for SM were observed during days of cyclonic circulation and advections from the northeast.
Article 1 Read 4 Citations Spatial heterogeneity in snow water equivalent induced by forest canopy in a mixed beech–fir stand in the Pyrenees Published: 14 September 2017
Annals of Glaciology, doi: 10.3189/172756408787814951
This paper analyzes the effect of forest canopy on snow water equivalent during two consecutive snow seasons in a mixed beech–fir stand in the Pyrenees. The results confirm that the forest canopy is a dominant influence on snowpack distribution during the accumulation and melting periods. In general, a noticeable decrease in snow water equivalent and an increase in variability among observations are detected with increasing density of the forest canopy. The influence of the forest canopy on melting rates is complex and highly dependent on the dominant climatic conditions. Similar conclusions are reached for both of the snow seasons for which measurements are available, but several differences are also recorded. This study highlights the important influence of climatic conditions observed during the snow season on the relationship between stand characteristics and snowpack dynamics.
Article 2 Reads 2 Citations Using very long-range terrestrial laser scanner to analyze the temporal consistency of the snowpack distribution in a hi... Published: 01 May 2017
Journal of Mountain Science, doi: 10.1007/s11629-016-4086-0
Article 2 Reads 0 Citations Integrating scales and LTER methods to better understand the overall dynamics of a mountain protected space: the Ordesa ... Published: 27 April 2016
Ecosistemas, doi: 10.7818/ecos.2016.25-1.04
Article 1 Read 5 Citations Thinning of the Monte Perdido Glacier in the Spanish Pyrenees since 1981 Published: 17 March 2016
The Cryosphere, doi: 10.5194/tc-10-681-2016
This paper analyzes the evolution of the Monte Perdido Glacier, the third largest glacier in the Pyrenees, from 1981 to the present. We assessed the evolution of the glacier's surface area by analysis of aerial photographs from 1981, 1999, and 2006, and changes in ice volume by geodetic methods with digital elevation models (DEMs) generated from topographic maps (1981 and 1999), airborne lidar (2010) and terrestrial laser scanning (TLS, 2011, 2012, 2013, and 2014) data. We interpreted the changes in the glacier based on climate data from nearby meteorological stations. The results indicate that the degradation of this glacier accelerated after 1999. The rate of ice surface loss was almost three times greater during 1999–2006 than during earlier periods. Moreover, the rate of glacier thinning was 1.85 times faster during 1999–2010 (rate of surface elevation change = −8.98 ± 1.80 m, glacier-wide mass balance = −0.73 ± 0.14 m w.e. yr−1) than during 1981–1999 (rate of surface elevation change = −8.35 ± 2.12 m, glacier-wide mass balance = −0.42 ± 0.10 m w.e. yr−1). From 2011 to 2014, ice thinning continued at a slower rate (rate of surface elevation change = −1.93 ± 0.4 m yr−1, glacier-wide mass balance = −0.58 ± 0.36 m w.e. yr−1). This deceleration in ice thinning compared to the previous 17 years can be attributed, at least in part, to two consecutive anomalously wet winters and cool summers (2012–2013 and 2013–2014), counteracted to some degree by the intense thinning that occurred during the dry and warm 2011–2012 period. However, local climatic changes observed during the study period do not seem sufficient to explain the acceleration of ice thinning of this glacier, because precipitation and air temperature did not exhibit statistically significant trends during the study period. Rather, the accelerated degradation of this glacier in recent years can be explained by a strong disequilibrium between the glacier and the current climate, and likely by other factors affecting the energy balance (e.g., increased albedo in spring) and feedback mechanisms (e.g., heat emitted from recently exposed bedrock and debris covered areas).
Article 1 Read 7 Citations Snowpack variability across various spatio-temporal resolutions Published: 11 June 2014
Hydrological Processes, doi: 10.1002/hyp.10245
High‐resolution snow depth (SD) maps (1 × 1 m) obtained from terrestrial laser scanner measurements in a small catchment (0.55 km2) in the Pyrenees were used to assess small‐scale variability of the snowpack at the catchment and sub‐grid scales. The coefficients of variation are compared for various plot resolutions (5 × 5, 25 × 25, 49 × 49, and 99 × 99 m) and eight different days in two snow seasons (2011–2012 and 2012–2013). We also studied the relation between snow variability at the small scale and SD, topographic variables, small‐scale variability in topographic variables. The results showed that there was marked variability in SD, and it increased with increasing scales. Days of seasonal maximum snow accumulation showed the least small‐scale variability, but this increased sharply with the onset of melting. The coefficient of variation (CV) in snowpack depth showed statistically significant consistency amongst the various spatial resolutions studied, although it declined progressively with increasing difference between the grid sizes being compared. SD best explained the spatial distribution of sub‐grid variability. Topographic variables including slope, wind sheltering, sub‐grid variability in elevation, and potential incoming solar radiation were also significantly correlated with the CV of the snowpack, with the greatest correlation occurring at the 99 × 99 m resolution. At this resolution, stepwise multiple regression models explained more than 70% of the variance, whereas at the 25 × 25 m resolution they explained slightly more than 50%. The results highlight the importance of considering small‐scale variability of the SD for comprehensively representing the distribution of snowpack from available punctual information, and the potential for using SD and other predictors to design optimized surveys for acquiring distributed SD data. Copyright © 2014 John Wiley & Sons, Ltd.