X Ma, X Zhu, Q Xie, J Jin, Y Zhou, Y Luo… - Global change …, 2022 - Wiley Online Library
Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant‐climate interactions. The correct representation of vegetation phenology is important …
Data assimilation (DA) is integrated with machine learning in order to perform entirely data‐ driven online state estimation. To achieve this, recurrent neural networks (RNNs) are …
Artificial intelligence (AI) and machine learning (ML) have become important tools for environmental scientists and engineers, both in research and in applications. Although …
ZM Labe, EA Barnes - Geophysical Research Letters, 2022 - Wiley Online Library
The global mean surface temperature (GMST) record exhibits both interannual to multidecadal variability and a long‐term warming trend due to external climate forcing. To …
S Pawar, O San - Journal of Advances in Modeling Earth …, 2022 - Wiley Online Library
There is a growing interest in developing data‐driven reduced‐order models for atmospheric and oceanic flows that are trained on data obtained either from high‐resolution …
Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy …
A McGovern, A Bostrom, P Davis… - Bulletin of the …, 2022 - journals.ametsoc.org
Abstract We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute …
Quantitative remote sensing is a technique for quantitatively inferring or inverting earth environmental variable from the original remote sensing observations, it is an important step …