Browsing Artificial Intelligence for the Earth Systems by Issue Date
Now showing items 1-20 of 170
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Improvements to the Land Surface Air Temperature Reconstruction in NOAAGlobalTemp: An Artificial Neural Network Approach
(American Meteorological Society, 2022)NOAA global surface temperature (NOAAGlobalTemp) is NOAA’s operational global surface temperature product, which has been widely used in Earth’s climate assessment and monitoring. To improve the spatial interpolation of ... -
Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm
(American Meteorological Society, 2022)Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these ... -
Can We Integrate Spatial Verification Methods into Neural Network Loss Functions for Atmospheric Science?
(American Meteorological Society, 2022)In the last decade, much work in atmospheric science has focused on spatial verification (SV) methods for gridded prediction, which overcome serious disadvantages of pixelwise verification. However, neural networks (NN) ... -
This Looks Like That There: Interpretable Neural Networks for Image Tasks When Location Matters
(American Meteorological Society, 2022)We develop and demonstrate a new interpretable deep learning model specifically designed for image analysis in Earth system science applications. The neural network is designed to be inherently interpretable, rather than ... -
Archetypal Analysis of Geophysical Data Illustrated by Sea Surface Temperature
(American Meteorological Society, 2022)The ability to find and recognize patterns in high-dimensional geophysical data is fundamental to climate science and critical for meaningful interpretation of weather and climate processes. Archetypal analysis (AA) is one ... -
Detection of Bow Echoes in Kilometer-Scale Forecasts Using a Convolutional Neural Network
(American Meteorological Society, 2022)Bow echoes (BEs) are bow-shaped lines of convective cells that are often associated with swaths of damaging straight-line winds and small tornadoes. This paper describes a convolutional neural network (CNN) able to detect ... -
On Variability due to Local Minima and K-Fold Cross Validation
(American Meteorological Society, 2022)Resampling methods such as cross validation or bootstrap are often employed to estimate the uncertainty in a loss function due to sampling variability, usually for the purpose of model selection. In models that require ... -
Editorial
(American Meteorological Society, 2022) -
Accurate and Clear Quantitative Precipitation Nowcasting Based on a Deep Learning Model with Consecutive Attention and Rain-Map Discrimination
(American Meteorological Society, 2022)Deep learning models are developed for high-resolution quantitative precipitation nowcasting (QPN) in Taiwan up to 3 h ahead. Many recent works aim to accurately predict relatively rare high-rainfall events with the help ... -
Investigating the Fidelity of Explainable Artificial Intelligence Methods for Applications of Convolutional Neural Networks in Geoscience
(American Meteorological Society, 2022)Convolutional neural networks (CNNs) have recently attracted great attention in geoscience because of their ability to capture nonlinear system behavior and extract predictive spatiotemporal patterns. Given their black-box ... -
Challenges and Benchmark Datasets for Machine Learning in the Atmospheric Sciences: Definition, Status, and Outlook
(American Meteorological Society, 2022)Benchmark datasets and benchmark problems have been a key aspect for the success of modern machine learning applications in many scientific domains. Consequently, an active discussion about benchmarks for applications of ... -
Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks
(American Meteorological Society, 2022)Near-surface wind is difficult to estimate using global numerical weather and climate models, because airflow is strongly modified by underlying topography, especially that of a country such as Switzerland. In this article, ... -
Global Mesoscale Ocean Variability from Multiyear Altimetry: An Analysis of the Influencing Factors
(American Meteorological Society, 2022)Sea surface slope (SSS) responds to oceanic processes and other environmental parameters. This study aims to identify the parameters that influence SSS variability. We use SSS calculated from multiyear satellite altimeter ... -
Machine Learning Crop Yield Models Based on Meteorological Features and Comparison with a Process-Based Model
(American Meteorological Society, 2022)A major challenge for food security worldwide is the large interannual variability of crop yield, and climate change is expected to further exacerbate this volatility. Accurate prediction of the crop response to climate ... -
The Pairwise Similarity Partitioning Algorithm: A Method for Unsupervised Partitioning of Geoscientific and Other Datasets Using Arbitrary Similarity Metrics
(American Meteorological Society, 2022)A simple yet flexible and robust algorithm is described for fully partitioning an arbitrary dataset into compact, nonoverlapping groups or classes, sorted by size, based entirely on a pairwise similarity matrix and a ... -
Application of Deep Learning to Understanding ENSO Dynamics
(American Meteorological Society, 2022)Many deep learning technologies have been applied to the Earth sciences. Nonetheless, the difficulty in interpreting deep learning results still prevents their applications to studies on climate dynamics. Here, we applied ... -
Hybrid Neural Network Models for Postprocessing Medium-Range Forecasts of Tropical Cyclone Tracks over the Western North Pacific
(American Meteorological Society, 2022)Tropical cyclone (TC) track forecasts derived from dynamical models inherit their errors. In this study, a neural network (NN) algorithm was proposed for postprocessing TC tracks predicted by the Global Ensemble Forecast ... -
Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps
(American Meteorological Society, 2022)An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations ... -
Understanding Predictability of Daily Southeast U.S. Precipitation Using Explainable Machine Learning
(American Meteorological Society, 2022)We investigate the predictability of the sign of daily southeastern U.S. (SEUS) precipitation anomalies associated with simultaneous predictors of large-scale climate variability using machine learning models. Models using ... -
Adaptive Blending of Probabilistic Precipitation Forecasts with Emphasis on Calibration and Temporal Forecast Consistency
(American Meteorological Society, 2022)A wealth of forecasting models is available for operational weather forecasting. Their strengths often depend on the lead time considered, which generates the need for a seamless combination of different forecast methods. ...