Dry-Season Snow Cover Losses in the Andes (18°-40°S) driven by Changes in Large-Scale Climate Modes

Extreme fire weather in Chile driven by climate change and El Niño-Southern Oscillation (ENSO)

A string of fierce fires broke out in Chile in the austral summer 2023, just six years after the record-breaking 2017 fire season. Favored by extreme weather conditions, fire activity has dramatically risen in recent years in this Andean country. A total of 1.7 million ha. burned during the last decade, tripling figures of the prior decade. Six of the seven most destructive fire seasons on record occurred since 2014. Here, we analyze the progression during the last two decades of the weather conditions associated with increased fire risk in Central Chile (30°-39° S). Fire weather conditions (including high temperatures, low humidity, dryness, and strong winds) increase the potential for wildfires, once ignited, to rapidly spread. We show that the concurrence of El Niño and climate-fueled droughts and heatwaves boost the local fire risk and have decisively contributed to the intense fire activity recently seen in Central Chile. Our results also suggest that the tropical eastern Pacific Ocean variability modulates the seasonal fire weather in the country, driving in turn the interannual fire activity. The signature of the warm anomalies in the Niño 1 + 2 region (0°-10° S, 90° W-80° W) is apparent on the burned area records seen in Central Chile in 2017 and 2023.

Application of a Cloud Removal Algorithm for Snow-Covered Areas from Daily MODIS Imagery over Andes Mountains

Snow cover area is dramatically decreasing across the Los Andes Mountains and the most relevant water reservoir under drought conditions. In this sense, monitoring of snow cover is key to analyzing the hydrologic balance in snowmelt-driven basins. MODIS Snow Cover daily products (MOD10A1 and MYD10A1) allow snow cover to be monitored at regular time intervals and in large areas, although the images often are affected by cloud cover. The main objective of this technical note is to evaluate the application of an algorithm to remove cloud cover in MODIS snow cover imagery in the Chilean Andes mountains. To this end, the northern region of Chile (Pulido river basin) during the period between December 2015 and December 2016 was selected. Results were validated against meteorological data from a ground station. The cloud removal algorithm allowed the overall cloud cover to be reduced from 26.56% to 7.69% in the study area and a snow cover mapping overall accuracy of 86.66% to be obtained. Finally, this work allows new cloud-free snow cover imagery to be produced for long term analysis and hydrologic models, reducing the lack of data and improving the daily regional snow mapping.

Valerianapraecipitis (Caprifoliaceae), a species new to science and endemic to Central Chile

The species Valerianapraecipitis (Caprifoliaceae), new to science and endemic to the Ñuble Region, Central Chile, is formally described. Morphological data support its placement in a new species, clearly different from V.philippiana. A detailed description, insights about its habitat and ecology, distribution map and illustration are provided. A table of comparison is also given with the morphological characters discriminating V.praecipitis from V.philippiana. The species is assessed as Endangered (EN) under the IUCN categories.

Evaluation of MODIS-derived estimates of the albedo over the Atacama Desert using ground-based spectral measurements

Surface albedo is an important forcing parameter that drives the radiative energy budget as it determines the fraction of the downwelling solar irradiance that the surface reflects. Here we report on ground-based measurements of the spectral albedo (350-2200 nm) carried out at 20 sites across a North-South transect of approximately 1300 km in the Atacama Desert, from latitude 18° S to latitude 30° S. These spectral measurements were used to evaluate remote sensing estimates of the albedo derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). We found that the relative mean bias error (RMBE) of MODIS-derived estimates was within ± 5% of ground-based measurements in most of the Atacama Desert (18-27° S). Although the correlation between MODIS-derived estimates and ground-based measurements remained relatively high (R= 0.94), RMBE values were slightly larger in the southernmost part of the desert (27-30° S). Both MODIS-derived data and ground-based measurements show that the albedo at some bright spots in the Atacama Desert may be high enough (up to 0.25 in visible range) for considerably boosting the performance of bifacial photovoltaic technologies (6-12%).

Future snow projections in a small basin of the Western Himalaya

Snow is a crucial component of the hydrological cycle in the Western Himalaya. Water from snowmelt is used in various sectors in downstream regions, thus playing a critical role in securing the livelihoods of millions of people. In this study, we investigated the future evolution of snow cover and snowmelt in the Panjshir catchment of Afghanistan, a sub-basin of the Indus, in the Western Himalaya. We applied a three-step approach to select a few global climate model (GCM) simulations from CMIP5 climate datasets for RCP4.5 and RCP8.5, which showed reasonable performance with ERA5-Land dataset for the chosen historical period (1981-2010). The selected model simulations were then segregated into two groups: those projecting a cold-wet climate and those projecting a warm-dry climate by the end of the 21^st century (2071-2100). These GCMs were downscaled to a higher resolution using empirical statistical downscaling. To simulate the snow processes, we used the distributed cryospheric-hydrological J2000 model. The results indicate that the model captures well the snow cover dynamics for the historical period when compared with the daily MODIS-derived snow cover. The J2000 model was then forced by climate projections from the selected GCMs to quantify future changes in snow cover area, snow storage and snowmelt. While a 10-18% reduction in annual snow cover area is projected in the cold-wet models, a 22-36% reduction is projected in the warm-dry models. Similarly, the snow cover area is projected to decrease in all elevation bands under climate change. At the seasonal scale, across all models and scenarios, the snow cover in the autumn and spring seasons are projected to reduce by as much as 25%, with an increase in winter and spring snowmelt and a decrease in summer snowmelt. The projected changes in the seasonal availability of snowmelt-driven water resources are likely to have direct implications for water-dependent sectors in the region and call for a better understanding of water usage and future adaptation practices.

Hydrological droughts in the southern Andes (40-45°S) from an ensemble experiment using CMIP5 and CMIP6 models

The decrease in freshwater input to the coastal system of the Southern Andes (40-45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040-2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.