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Kyle A. Hilburn, Imme Ebert-Uphoff, and Steven D. Miller

efficiency effects related to the production of cloud ice ( Rutledge et al. 2020 ), and also possibly to the unsteady nature of updrafts. Instead spatial variability contains more reliable information content, supplementing missing information at very high optical depths, and is especially useful at night. While there is spatial variability in GLM detection efficiency ( Marchand et al. 2019 ), our CNN is more sensitive to the presence of lightning rather than the magnitude of lightning activity, which

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Andrew E. Mercer, Alexandria D. Grimes, and Kimberly M. Wood

separability at RI onset over these SHIPS-RII predictor results. Table 3. True positive rate, true negative rate, and the J statistic for each RI category. The fourth column is the separation metric J , valid for a k- means cluster analysis using all SHIPS-RII predictors obtained from the Regional and Mesoscale Meteorology Branch at the Cooperative Institute for Research in the Atmosphere. These were used as a baseline to measure improvements in separability relative to SHIPS-RII. Note that the false

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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

connection between SM and crops. Simulating cropland carbon fluxes such as soil organic carbon (SOC) decomposition and soil respiration, which are closely affected by SM. Evaluating the effects of alternative cropping pattern on water and carbon fluxes, which may inform regional and local decision making pertaining to environmental and agricultural policies. c. Limitations and uncertainties The extrapolation of the NN model outside the range of training conditions may be the major uncertainty source of

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Sid-Ahmed Boukabara, Vladimir Krasnopolsky, Jebb Q. Stewart, Eric S. Maddy, Narges Shahroudi, and Ross N. Hoffman

.noaa.gov/big-data-project ). The latency requirement is particularly extreme for short-term forecasting of hazardous weather. Yet, improvements in NWP are driven by computationally intensive advances in all aforementioned areas. Examples of specific improvements for global medium-range NWP will include: enhanced assimilation of satellite measurements, including radiances affected by clouds, precipitation, and surface properties [requiring more complete radiative transfer (RT) models accounting for these effects], and using

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