Decrease in Snow Cover over the Aysén River Catchment in Patagonia, Chile

Abstract

The evidence for global warming can be seen in various forms, such as glacier shrinkage, sea ice retreat, sea level rise and air temperature increases. The magnitude of these changes tends to be critical over pristine and extreme biomes. Chilean Patagonia is one of the most pristine and uninhabited regions in the world, home to some of the most important freshwater reservoirs as well as to evergreen forest, lakes and fiords. Furthermore, this region presents a sparse and weak network of ground stations which must be complemented with satellite information to determine trends on biophysical parameters. The main objective of this work is to present the first assessment on snow cover over the Aysén basin in Patagonia-Chile by using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the period 2000-2016. The MOD10A2 product was processed at 500 × 500 m spatial resolution. The time-series analysis consisted in the application of non-parametric tests such as the Mann-Kendall test and Sen's slope for annual and seasonal mean of snow covered area (SCA). Data from ground meteorological network and river discharges were also included in this work to show the trends in air temperature, precipitation and stream flow during the last decades. Results indicate that snow cover shows a decreasing non-significant trend in annual mean SCA with a −20.01 km 2 •year −1 slope, and neither seasonal mean shows statistical significance. The comparison with in situ data shows a seasonal decrease in stream flows and precipitation during summer. The hydrological year 2016 was the year with the most negative standardized joint anomalies in the period. However, the lack of in situ snow-monitoring stations in addition to the persistence of cloud cover over the basin can impact trends, creating some uncertainties in the data. Finally, this work provides an initial analysis of the possible impacts of global warming as seen by snow cover in Chilean Patagonia.

Climate‐driven change in the water sourced by trees in a de‐glaciating proglacial fore‐field, Torres del Paine, Chile

“…Mean temperatures in the European Alps increased more than twice as much as (Brunetti, Lentini, & Maugeri, ; Rebetez & Reinhard, ). This is similar for mountain regions in the southern hemisphere (Perez, Mattar, & Fuster, ). In response to this warming, the global water cycle has changed fundamentally, including a decrease in annual rainfall in certain regions (Jansson, Hock, & Schneider, ).…”

“…parts of the world now regularly undergo droughts that were extremely rare 100 years ago (Griffin & Anchukaitis, 2014). A combination of warming-driven ablation and reduced accumulation has led to the shrinkage of global ice cover (Haeberli, Hoelzle, Paul, & Zemp, 2007;Perez et al, 2018), with a rate of loss of 259 ± 28 Gt year −1 of ice between 2003 and 2009 (Gardner, Moholdt, Cogley, et al, 2013). In most Alpine regions of the world, glaciers are undergoing rapid recession (Dyurgerov & Meier, 2000;Perez et al, 2018).…”

Estimation of Snow Depth over the Qinghai-Tibetan Plateau Based on AMSR-E and MODIS Data

“…The new method shows a better relationship with the in situ observation than the old method, and the bias and RMSE values (−1.3 cm and 4.6 cm) are much lower than those of the old method (4.2 cm and 7.9 cm) ( Table 4). The relative absolute bias (Rabias) and RMSE are calculated for each meteorological station from 2003 to 2010 using Equations (9) and (10), and the results are exhibited in Figure 12. When the observed snow depth (sdo i ) is 0 cm, the Rabias is set as 0 if the estimated snow depth (sde i ) is less than 1 cm and set as 1 if sde i is larger than 1 cm.…”

“…The decrease of 0.0018 for the Although the accuracy of calculated snow depth improved substantially compared with the old method, due to the application of ground emissivity, the RMSE remained very large when the snow depth was greater than 0 cm and less than 10 cm. The RMSEs are 6.3 cm and 6.6 cm for the snow depth range (2)(3)(4)(5), with an average snow depth of 3.7 cm, and a range (5)(6)(7)(8)(9)(10) with an average snow depth of 7.5 cm, respectively (Table 4). The ground emissivity depends on soil characteristics that change temporally, and thus the temporal static ground emissivity may cause errors.…”

How long will an Arctic mountain glacier survive? A case study of Austre Lovénbreen, Svalbard

“…Glaciers, which result from specific climatic conditions, are very sensitive to climate change, and many of them have retreated to varying degrees in a global warming context (e.g., Huss et al 2010;Gardner et al 2011;Małecki 2013;Barnard et al 2014;Zhang et al 2014;Pérez et al 2018). Small mountain glaciers and icecaps have significant roles in climate and sea-level changes at decadal or century scales because of their short response times to climate change (Oerlemans & Fortuin 1992).…”