Results 81 to 90 of about 7,051 (218)
AI‐Based Regional Emulation for Kilometer‐Scale Dynamical Downscaling
Abstract An AI‐based Limited‐Area Model (LAM) is developed for dynamical downscaling over the Southern Great Plains and the southeastern United States, with strong generalization abilities under diverse boundary conditions. The model is trained using 0.25° ${}^{\circ}$, 3‐hourly ERA5 as forcings and CONUS404 as targets in 1980–2019, producing 4‐km ...
Yingkai Sha +8 more
wiley +1 more source
Abstract Over the past decades, climate change has emerged as a major threat to global biodiversity, negatively affecting the integrity and functioning of ecosystems and the benefits they provide to people. To mitigate these impacts, it is essential to identify climate refugia that support the persistence of the structure and function of reef ...
Sara M. Melo‐Merino +4 more
wiley +1 more source
To improve the scientific planning of crop cultivation regions, enhance crop quality, mitigate meteorological disaster risks, and optimize the utilization of climatic resources, this study analyzed temperature data from 141 national meteorological ...
Le Zhangyan +12 more
doaj +1 more source
Abstract Ecological niche models (ENMs) are used to assess the abiotic preferences of species by linking their occurrences to the environmental conditions in which they live. We developed a fossil‐informed ENM framework that integrates mid‐Holocene and modern occurrences to test niche stability and reconstruct abiotic niche characteristics for four ...
Claire. M. Williams +3 more
wiley +1 more source
Climate Change, Demand Uncertainty, and Firms' Investments: Evidence from Planned Power Plants
ABSTRACT How does demand uncertainty affect firms' investment decisions? We examine this question in the context of electricity‐producing firms' planned investments in new power plants. We measure uncertainty about future electricity demand using plausibly exogenous variation in temperature projections across scientific climate models. The results show
CHEN LIN +2 more
wiley +1 more source
Solving Stochastic Climate‐Economy Models: A Deep Least‐Squares Monte Carlo Approach
ABSTRACT Stochastic versions of recursive integrated climate‐economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid‐based dynamic programming (e.g., value‐function iteration/projection ...
Aleksandar Arandjelović +4 more
wiley +1 more source
Abstract Coastal El Niño (COA) events follow two evolution pathways, remaining in the far eastern Pacific or expanding into basin‐wide El Niño events. Analyzing 55 CMIP6 models, we show that the two pathways are associated with distinct central and eastern Pacific ocean‐atmosphere conditions, and the simulated frequency of each type is linked to ...
G. A. Rivera Tello, C. Karamperidou
wiley +1 more source
The escalating frequency of climate change-induced droughts poses a severe threat to rainfed maize cultivation in Thailand's upper Nan River Basin (NRB).
Rabin Bastola +3 more
doaj +1 more source
Abstract The North Atlantic Subpolar Gyre (NASG) has warmed much less than the global ocean over recent decades, thereby suggesting a human‐caused slowdown of the Atlantic Meridional Overturning Circulation (AMOC). This North Atlantic “warming hole” is also found in climate projections, yet with a model‐dependent timing, location and intensity. Here we
Hervé Douville +2 more
wiley +1 more source
Systematic Overestimation of Global Peak Runoff Synchronization in CMIP6 Models
Abstract Synchronous flooding across distant regions can amplify socioeconomic impacts. As the hydrological cycle intensifies, flood synchronization appears to be expanding, yet predictive understanding beyond gauged basins remains limited. We analyze the global synchronization of annual peak runoff (a proxy for flooding) using gridded data sets and ...
Yixin Yang +2 more
wiley +1 more source

