A study was carried out to parameterize the METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) model for estimating instantaneous values of albedo (shortwave albedo) (α_i), net radiation (R_ni) and soil heat flux (G_i), sensible (H_i) and latent heat (LE_i) over a drip-irrigated Merlot vineyard (location: 35°25′ LS; 71°32′ LW; 125 m.a.s. (l). The experiment was carried out in a plot of 4.25 ha, processing 15 Landsat images, which were acquired from 2006 to 2009. An automatic weather station was placed inside the experimental plot to measure α_i, R_ni and G_i. In the same tower an Eddy Covariance (EC) system was mounted to measure H_i and LE_i. Specific sub-models to estimate G_i, leaf area index (LAI) and aerodynamic roughness length for momentum transfer (z_om) were calibrated for the Merlot vineyard as an improvement to the original METRIC model. Results indicated that LAI, z_om and G_i were estimated using the calibrated functions with errors of 4%, 2% and 17%, while those were computed using the original functions with errors of 58%, 81%, and 5%, respectively. At the time of satellite overpass, comparisons between measured and estimated values indicated that METRIC overestimated α_i in 21% and R_ni in 11%. Also, METRIC using the calibrated functions overestimated H_i and LE_i with errors of 16% and 17%, respectively while it using the original functions overestimated H_i and LE_i with errors of 13% and 15%, respectively. Finally, LE_i was estimated with root mean square error (RMSE) between 43 and 60 W∙m⁻² and mean absolute error (MAE) between 35 and 48 W∙m⁻² for both calibrated and original functions, respectively. These results suggested that biases observed for instantaneous pixel-by-pixel values of R_ni, G_i and other intermediate components of the algorithm were presumably absorbed into the computation of sensible heat flux as a result of the internal self-calibration of METRIC.

Parts of Antarctica were amongst the most rapidly changing regions of the planet during the second half of the Twentieth Century. Even so, today, most of Antarctica remains in the grip of continental ice sheets, with only about 0.2% of its overall area being ice-free. The continent’s terrestrial fauna consists only of invertebrates, with just two native species of insects, the chironomid midgesParochlus steineniiandBelgica antarctica. We integrate ecophysiological information with the development of new high-resolution climatic layers for Antarctica, to better understand how the distribution ofP. steineniimay respond to change over the next century under different IPCC climate change scenarios. We conclude that the species has the potential to expand its distribution to include parts of the west and east coasts of the Antarctic Peninsula and even coastal ice-free areas in parts of continental Antarctica. We proposeP. steineniias an effective native sentinel and indicator species of climate change in the Antarctic.

Urban heat islands (UHIs) can present significant risks to human health. Santiago, Chile has around 7 million residents, concentrated in an average density of 480 people/km². During the last few summer seasons, the highest extreme maximum temperatures in over 100 years have been recorded. Given the projections in temperature increase for this metropolitan region over the next 50 years, the Santiago UHI could have an important impact on the health and stress of the general population. We studied the presence and spatial variability of UHIs in Santiago during the summer seasons from 2005 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery and data from nine meteorological stations. Simple regression models, geographic weighted regression (GWR) models and geostatistical interpolations were used to find nocturnal thermal differences in UHIs of up to 9 °C, as well as increases in the magnitude and extension of the daytime heat island from summer 2014 to 2017. Understanding the behavior of the UHI of Santiago, Chile, is important for urban planners and local decision makers. Additionally, understanding the spatial pattern of the UHI could improve knowledge about how urban areas experience and could mitigate climate change.

Climate variability imposes greater challenges on family farming and especially on rural communities in vulnerable mountainous regions such as the Andes in Latin America. Changes in rainfall patterns and fluctuations in temperatures cause a greater frequency of extreme events, increased pests, and crop diseases, which even lead to food insecurity in communities that depend on self-production for survival. This is why strategies need to be developed to face this new scenario. Two cases of adaptation experiences to the effects of climate variability in rural communities in Chile (Araucanía Region) and Colombia (Cauca Department) were analyzed on this paper. For this, a mixed methodological approach was adopted that included the analysis of climate data, socioeconomic, and productive characterization of the communities, and a characterization of adaptation practices for both cases. The results show various ways of adapting mainly to changes in the availability and access of water for the development of agriculture and for domestic use. Likewise, it is shown that in order to be successful, the measures for facing climate variability must be part of coordinated strategies under a community-based adaptation approach and not developed in isolation.