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High‐resolution climate projections are critical to assessing climate risk and developing climate resilience strategies. However, they remain limited in quality, availability, and/or geographic coverage. The Seasonal Trends and Analysis of Residuals empirical statistical downscaling model (STAR‐ESDM) is a computationally‐efficient, flexible approach to generating such projections that can be applied globally using predictands and predictors sourced from weather stations, gridded data sets, satellites, reanalysis, and global or regional climate models. It uses signal processing combined with Fourier filtering and kernel density estimation techniques to decompose and smooth any quasi‐Gaussian time series, gridded or point‐based, into multi‐decadal long‐term means and/or trends; static and dynamic annual cycles; and probability distributions of daily variability. Long‐term predictor trends are bias‐corrected and predictor components used to map predictand components to future conditions. Components are then recombined for each station or grid cell to produce a continuous, high‐resolution bias‐corrected and downscaled time series at the spatial and temporal scale of the predictand time series. Comparing STAR‐ESDM output driven by coarse global climate model simulations with daily temperature and precipitation projections generated by a high‐resolution version of the same global model demonstrates it is capable of accurately reproducing projected changes for all but the most extreme temperature and precipitation values. For most continental areas, biases in 1‐in‐1000 hottest and coldest temperatures are <0.5°C and biases in the 1‐in‐1000 wet day precipitation amounts are <5 mm/day. As climate impacts intensify, STAR‐ESDM represents a significant advance in generating consistent high‐resolution projections to comprehensively assess climate risk and optimize resilience globally. Plain Language Summary: The STAR‐ESDM tool is able to quickly and accurately generate future climate projections for weather stations and high‐resolution grids anywhere in the world. It does this by breaking down global or regional climate model output into different components, from the long‐term trend to the day‐to‐day variability, then merging projected changes with observations. When tested against projections generated by a complex and computationally expensive dynamical global model, STAR‐ESDM produced almost the same output, even for extreme temperature and precipitation values, at a fraction of the computational cost. Moreover, unlike most statistical downscaling models, this method isn't tied to any specific geographic area or predictand and/or predictor data set. It can be applied to any regional or global data set, whether generated by a climate or reanalysis model, derived from satellite observations, recorded at weather stations, and more. As climate impacts escalate, STAR‐ESDM offers a flexible and effective way to generate the high‐resolution climate projections needed to better gauge climate risk and enhance resilience anywhere in the world where reliable observational or quasi‐observational data, including reanalysis or satellites, are available. This is particularly relevant to under‐resourced regions, which are often most vulnerable to climate impacts as well as most lacking in future projections. Key Points: STAR‐ESDM is a rapid, flexible and generalizable approach to bias‐correct and downscale climate model output to any finer‐resolution data setPredictors/predictands can be derived from global or regional models, satellites, reanalysis, gridded observations and weather stationsProjected changes in temperature and precipitation mirror those of a high‐resolution global model at a fraction of the computational cost [ABSTRACT FROM AUTHOR]

In this interview, Katharine Hayhoe discusses the regional dimensions and impacts of climate change on the American South. Topics discussed include Texas and the energy sector, the pandemic, climate dismissives, solution aversion, political polarization, Christian identity and climate change, solutions to the climate crisis, definitions of environmentalism, and conducting productive climate conversations. [ABSTRACT FROM AUTHOR]

We review twentieth century and projected twenty-first century changes in climatic and hydrologic conditions in the northeastern United States and the implications of these changes for forest ecosystems. Climate warming and increases in precipitation and associated changes in snow and hydrologic regimes have been observed over the last century, with the most pronounced changes occurring since 1970. Trends in specific climatic and hydrologic variables differ in their responses spatially (e.g., coastal vs. inland) and temporally (e.g., spring vs. summer). Trends can differ depending on the period of record analyzed, hinting at the role of detach)-scale climatic variation that is superimposed over the longer-term trend. Model predictions indicate that continued increases in temperature and precipitation across the northeastern United States can be expected over the next century. Ongoing increases in growing season length (earlier spring and later autumn) will most likely increase evapotranspiration and frequency of drought. In turn, an increase in the frequency of drought will likely increase the risk of fire and negatively impact forest productivity, maple syrup production, and the intensity of autumn foliage coloration. Climate and hydrologic changes could have profound effects on forest structure, composition, and ecological functioning in response to the changes discussed here and as described in related articles in this issue of the Journal. Nous avons passe en revue les changements dans les conditions climatiques et hydrologiques survenues pendant le 20e siecle et projetees au cours du 21e siecle dans le nord-est des Etats-Unis ainsi que les repercussions de ces changements sur les ecosystemes forestiers. Un rechauffement du climat et une augmentation des precipitations ainsi que des changements dans les regimes nivologique et hydrologique ont ete observes pendant le dernier siecle et les changements les plus prononces sont survenus depuis 1970. Les tendances de variables climatiques et hydrologiques specifiques different dans f espace (p. ex. zone cotiere vs interieur des terres) et dans le temps (p. ex. printemps vs ete) dans leur reponse. Les tendances different selon la periode couverte par les donnees qui sont analysees, un indice du role de la variation du climat a une echelle decennale qui se superpose a la tendance a long terme. Les predictions du modele indiquent qu'on peut s'attendre a des augmentations continues de la temperature et des precipitations partout dans la region au cours du prochain siecle. L'allongement en cours de la saison de croissance (printemps qui arrive plus tot et automne qui arrive plus tard) augmentera l'evapotranspiration et la frequence des secheresses. Des secheresses plus frequentes vont probablement augmenter les risques d'incendie et avoir un impact negatif sur la productivite de la foret, la production de sirop d'erable et l'intensite de la coloration automnale du feuillage. Les changements climatiques et hydrologiques pourraient avoir de serieux effets sur la structure, la composition et le fonctionnement ecologique de la foret en reaction aux hangements discutes dans cet article et decrits dans d'autres articles relies au meme sujet et publies dans ce numero. [Traduit par la Redaction], Introduction and overview of climate and hydrology in the region Introduction At a regional scale, interpretations of the effects of recent climate change and predictions of the potential effects of [...]