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of 54
pro vyhledávání: '"Watson, Campbell D"'
Autor:
Soni, Sagar, Dudhane, Akshay, Debary, Hiyam, Fiaz, Mustansar, Munir, Muhammad Akhtar, Danish, Muhammad Sohail, Fraccaro, Paolo, Watson, Campbell D, Klein, Levente J, Khan, Fahad Shahbaz, Khan, Salman
Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and resource management. Existing generic VLMs do not perform well on Remote
Externí odkaz:
http://arxiv.org/abs/2412.15190
Autor:
Yang, Qidong, Hernandez-Garcia, Alex, Harder, Paula, Ramesh, Venkatesh, Sattegeri, Prasanna, Szwarcman, Daniela, Watson, Campbell D., Rolnick, David
Climate simulations are essential in guiding our understanding of climate change and responding to its effects. However, it is computationally expensive to resolve complex climate processes at high spatial resolution. As one way to speed up climate s
Externí odkaz:
http://arxiv.org/abs/2305.14452
Autor:
Nathaniel, Juan, Klein, Levente J., Watson, Campbell D., Nyirjesy, Gabrielle, Albrecht, Conrad M.
The global carbon cycle is a key process to understand how our climate is changing. However, monitoring the dynamics is difficult because a high-resolution robust measurement of key state parameters including the aboveground carbon biomass (AGB) is r
Externí odkaz:
http://arxiv.org/abs/2210.13752
Numerical simulations in climate, chemistry, or astrophysics are computationally too expensive for uncertainty quantification or parameter-exploration at high-resolution. Reduced-order or surrogate models are multiple orders of magnitude faster, but
Externí odkaz:
http://arxiv.org/abs/2207.11417
Autor:
Wong, Ken C. L., Wang, Hongzhi, Vos, Etienne E., Zadrozny, Bianca, Watson, Campbell D., Syeda-Mahmood, Tanveer
Global warming leads to the increase in frequency and intensity of climate extremes that cause tremendous loss of lives and property. Accurate long-range climate prediction allows more time for preparation and disaster risk management for such extrem
Externí odkaz:
http://arxiv.org/abs/2112.05254
Autor:
Nogueira Jr, Alberto Costa, Almeida, João Lucas de Sousa, Auger, Guillaume, Watson, Campbell D.
General circulation models are essential tools in weather and hydrodynamic simulation. They solve discretized, complex physical equations in order to compute evolutionary states of dynamical systems, such as the hydrodynamics of a lake. However, high
Externí odkaz:
http://arxiv.org/abs/2103.10931
Autor:
Zadrozny, Bianca, Watson, Campbell D., Szwarcman, Daniela, Civitarese, Daniel, Oliveira, Dario, Rodrigues, Eduardo, Guevara, Jorge
Extreme weather events have an enormous impact on society and are expected to become more frequent and severe with climate change. In this context, resilience planning becomes crucial for risk mitigation and coping with these extreme events. Machine
Externí odkaz:
http://arxiv.org/abs/2102.04534
Autor:
Vos, Etienne E., Gritzman, Ashley, Makhanya, Sibusisiwe, Mashinini, Thabang, Watson, Campbell D.
A significant challenge in seasonal climate prediction is whether a prediction can beat climatology. We hereby present results from two data-driven models - a convolutional (CNN) and a recurrent (RNN) neural network - that predict 2 m temperature out
Externí odkaz:
http://arxiv.org/abs/2102.00085
In an effort to provide optimal inputs to downstream modeling systems (e.g., a hydrodynamics model that simulates the water circulation of a lake), we hereby strive to enhance resolution of precipitation fields from a weather model by up to 9x. We te
Externí odkaz:
http://arxiv.org/abs/2012.01233
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