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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]

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 [...]

Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Modeling advances now provide the opportunity of utilizing global general circulation models (GCMs) for projections of extreme temperature and precipitation indicators. We analyze historical and future simulations of ten such indicators as derived from an ensemble of 9 GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4), under a range of emissions scenarios. Our focus is on the consensus from the GCM ensemble, in terms of direction and significance of the changes, at the global average and geographical scale. The climate extremes described by the ten indices range from heat-wave frequency to frost-day occurrence, from dry-spell length to heavy rainfall amounts. Historical trends generally agree with previous observational studies, providing a basic sense of reliability for the GCM simulations. Individual model projections for the 21st century across the three scenarios examined are in agreement in showing greater temperature extremes consistent with a warmer climate. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models and across scenarios, while substantial differences appear in the relative magnitude of the trends under different emissions rates. Depictions of a wetter world and greater precipitation intensity emerge unequivocally in the global averages of most of the precipitation indices. However, consensus and significance are less strong when regional patterns are considered. This analysis provides a first overview of projected changes in climate extremes from the 1PCC-AR4 model ensemble, and has significant implications with regard to climate projections for impact assessments.

An IPCC founder and tenacious advocate for climate action. An IPCC founder and tenacious advocate for climate action., Author(s): Katharine Hayhoe, Donald Wuebbles Author Affiliations: John Houghton (1931-2020) John Houghton (right) at the opening of a weather centre in 1985. [see PDF for image] Credit: PA Archive/PA John [...]

Methane (C[H.sub.4]) is the most abundant organic trace gas in the atmosphere. In the distant past, variations in natural sources o methane were responsible for trends in atmospheric methane levels recorded in ice cores. Since the 1700s, rapidly growing human activities, particularly in the areas of agriculture, fossil fuel use, and waste disposal, have more than doubled methane emissions. Atmospheric methane concentrations have increased by a factor of 2-3 in response to this increase, and continue to rise. These increasing concentrations have raised concern due to their potential effects on atmospheric chemistry and climate Methane is important to both tropospheric and stratospheric chemistry, significantly affecting levels of ozone, water vapor, the hydroxyl radical, and numerous other compounds. In addition, methane is currently the second most important greenhouse gas emitted from human activities. On a per molecule basis, it is much more effective a greenhouse gas than additional C[O.sub.2]. In this review, we examine past trends in the concentration of methane in the atmosphere, the sources and sinks that determine it growth rate, and the factors that will affect its growth rate in the future. We also present current understanding of the effects of methane on atmospheric chemistry, and examine the direct and indirect impacts of atmospheric methane on climate. Keywords: methane; greenhouse gases; atmospheric chemistry; global change

Byline: Claudia Tebaldi (1), Katharine Hayhoe (2,3), Julie M. Arblaster (4,5), Gerald A. Meehl (4) Author Affiliation: (1) Institute for the Study of Society and Environment, National Center for Atmospheric Research (NCAR), PO BOX 3000, Boulder, CO, 80301, USA (2) Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA (3) Department of Geosciences, Texas Tech University, Lubbock, TX, USA (4) Climate and Global Dynamics Division, NCAR, Boulder, CO, USA (5) Bureau of Meteorology Research Centre, Melbourne, Australia Article History: Registration Date: 19/02/2007 Online Date: 15/03/2007 Article note: The online version of the original article can be found at: doi: 10.1007/s10584-006-9051-4.

Evaluating the response of vegetation to climate change is relevant to improving the management of both human and natural systems. Here, we quantify the response of the MODIS-based enhanced vegetation index (EVI) to temperature, precipitation, and large-scale natural variability across the South-Central U.S. for summer (JJA) from 2000 to 2013. We find statistically significant relationships between climate and EVI that vary across the region and are distinct for each land cover type: the mean coefficient of determination (R 2 ) between EVI and climate is greatest for pasture (0.61 ± 0.13) and lowest for forest (0.55 ± 0.14). Among the climate variables, three-month cumulative precipitation has the strongest influence on summer vegetation, particularly in semi-arid west Texas and eastern New Mexico. Summer monthly maximum temperature plays an important role in the eastern half of Texas and Oklahoma, moderated by the influence of both Atlantic and Pacific teleconnection indices over inter-annual time scales. Based on these relationships, we train, cross-validate, and, where statistically significant relationships exist, combine this multivariate predictive model with projected changes in teleconnection indices and statistically-downscaled temperature and precipitation from 16 CMIP5 global climate models to quantify future changes in EVI. As global mean temperature increases, projected EVI decreases, indicative of stressed and dry vegetation, particularly for grasslands as compared to other land types, and in Oklahoma and western, central and Gulf Coast Texas for mid- and end-of-century. These trends have potentially important implications for agriculture and the regional economy, as well as for ecosystems and endemic species that depend on vegetation. [ABSTRACT FROM AUTHOR]