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Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets., , , , , , , , and . CoRR, (2016)Reducing the computational cost of the ECF using a nuFFT: A fast and objective probability density estimation method., , , and . Comput. Stat. Data Anal., (2014)A fast and objective multidimensional kernel density estimation method: fastKDE., , , , and . Comput. Stat. Data Anal., (2016)Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation, , , , , , , and . Climate Dynamics, 56 (9): 3205--3230 (May 1, 2021)Evaluation of hydrologic components of community land model 4 and bias identification., , and . Int. J. Appl. Earth Obs. Geoinformation, (2016)Impact of Desert Dust Radiative Forcing on Sahel Precipitation: Relative Importance of Dust Compared to Sea Surface Temperature Variations, Vegetation Changes, and Greenhouse Gas Warming, , , , , , and . J. Climate, 20 (8): 1445--1467 (Apr 1, 2007)TECA: Petascale Pattern Recognition for Climate Science., , , , , and . CAIP (2), volume 9257 of Lecture Notes in Computer Science, page 426-436. Springer, (2015)Progress in Fast, Accurate Multi-scale Climate Simulations., , , , and . ICCS, volume 51 of Procedia Computer Science, page 2006-2015. Elsevier, (2015)What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?, , and . Environ. Model. Softw., (2016)Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction., , , , , and . CoRR, (2024)