Search · four archives
Search · four archives
18 papers · ranked by Valyu relevance
Yichen Zhang, Yixiong Xiao, Congxi Xiao, Jingbo Zhou
High-resolution climate data is crucial for meteorological predictions and for informing decision support across diverse domains. However, the acquisition of such high-resolution climate information is often prohibitively costly, necessitating the development of data-driven meteorological prediction models. These…
Norihiro Oyama, Noriko N. Ishizaki, Satoshi Koide, Hiroaki Yoshida
Super-resolving the coarse outputs of global climate simulations, termed downscaling, is crucial in making political and social decisions on systems requiring long-term climate change projections. Existing fast super-resolution techniques, however, have yet to preserve the spatially correlated nature of climatological…
Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri + 4 more
'Álex Hernández-García' 'Campbell D. Watson' 'Daniela Szwarcman' 'David Rolnick'] The availability of reliable, high-resolution climate and weather data is important to inform long-term decisions on climate adaptation and mitigation and to guide rapid responses to extreme events. Forecasting models are limited by…
Grant Buster, Brandon N. Benton, Deeksha Rastogi, Shih-Chieh Kao + 2 more
'Guilherme Castelao' 'Jordan Eisenman'] The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a…
Karandeep Singh, Chaeyoon Jeong, Naufal Shidqi, Sung Won Park + 3 more
'Arjun Babu Nellikkattil' 'Elke Zeller' 'Meeyoung Cha'] Climate change is one of the most critical challenges that our planet is facing today. Rising global temperatures are already bringing noticeable changes to Earth's weather and climate patterns with an increased frequency of unpredictable and extreme weather…
P. Jyoteeshkumar Reddy, Richard Matear, John Taylor, Marcus Thatcher
The present study explores the potential of super-resolution machine learning (ML) models for precipitation downscaling from 100 to 12.5 km at hourly timescale using the Conformal Cubic Atmospheric Model (CCAM) data over the Australian domain. Two approaches were examined: the perfect approach, which trains the ML…
Jared Streich, Anna Furches, David Kainer, Benjamin J. Garcia + 7 more
We present an exascale approach for producing global scale, high resolution, longitudinally based geoclimate classifications. Using a GPU implementation of the DUO Similarity Metric on the Summit supercomputer, we calculated the pairwise environmental similarity of 156,384,190 vectors of 414,640 encoded elements…
Ehsan Zeraatkar, Salah A. Faroughi, Jelena Tešić
System Models Authors: ['Ehsan Zeraatkar' 'Salah A. Faroughi' 'Jelena Tešić'] Purpose: Earth system models (ESMs) integrate the interactions of the atmosphere, ocean, land, ice, and biosphere to estimate the state of regional and global climate under a wide variety of conditions. The ESMs are highly complex, and thus…
Piper Wolters, Favyen Bastani, Aniruddha Kembhavi
High-resolution satellite and aerial imagery have the potential to change the landscape of environmental and climate monitoring applications. Images from these sensors provide the ability to count individual trees , classify crop types and conditions , map out detailed land use categories and track glacial conditions .…
Charis Lanaras, José M. Bioucas‐Dias, Silvano Galliani, E. Baltsavias + 1 more
'E. Baltsavias' 'Konrad Schindler'] The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance – GSD) bands to 10 m GSD, so as to…
Paula Harder, Luca Schmidt, Francis Pelletier, Nicole Ludwig + 4 more
Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is not computationally feasible. Deep learning-based super-resolution models offer a promising solution to downscale ESM outputs to higher…
Evan H. Girvetz, Chris Zganjar, George T. Raber, Edwin P. Maurer + 3 more
Background Although the message of “global climate change” is catalyzing international action, it is local and regional changes that directly affect people and ecosystems and are of immediate concern to scientists, managers, and policy makers. A major barrier preventing informed climate-change adaptation planning is…
Alon Itzkovitch, Idan Sulami, Ronny Doron Efroni, Moni Shahar + 1 more
1. Microclimates are critical for understanding how organisms interact with their environments, influencing behaviour, physiology, and species distributions. However, traditional physical heat-balance models for predicting ground temperatures in microhabitats often exhibit biases due to unaccounted environmental…
Griffin Mooers, Mike Pritchard, Tom Beucler, Prakhar Srivastava + 4 more
'Harshini Mangipudi' 'Liran Peng' 'Pierre Gentine' 'Stephan Mandt'] Global storm-resolving models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult to quantify objective differences in how GSRMs resolve complex…
Thomas P. Smith, Michael Stemkovski, Austin Koontz, William D. Pearse
In an era of increasingly cross-discipline collaborative science, it is imperative to produce data resources which can be quickly and easily utilised by non-specialists. In particular, climate data often require heavy processing before they can be used for analyses. Here we describe AREAdata, a free-to-use online…
David H. Klinges, Ilya M. D. Maclean, Brett R. Scheffers
Scientists have long categorized the planet’s climate using the Köppen-Geiger (KG) classification to understand climate change impacts, biogeographical realms, agricultural suitability, and conservation. However, global KG maps primarily rely on macroclimate data collected by weather stations, which may not represent…
Harald Zandler, Thomas Senftl, Kim André Vanselow
Global environmental research requires long-term climate data. Yet, meteorological infrastructure is missing in the vast majority of the world’s protected areas. Therefore, gridded products are frequently used as the only available climate data source in peripheral regions. However, associated evaluations are commonly…
Authors not listed
A growth curve is S-shaped and typically contains three phases, namely, the lag phase, the exponential phase, and the saturation phase. Similarly, the time-series data of atmospheric CO2 levels over the past thousand years trend like the lag phase of growth until around 1940 and enter an exponential phase like curve…