The Potential Benefits of Handling Mixture Statistics via a Bi-Gaussian EnKF: Tests With All-Sky Satellite Infrared Radiances [0.03%]
基于双高斯分布的集合卡尔曼滤波同化卫星全天空红外辐射资料的可能优势研究
Man-Yau Chan,Xingchao Chen,Jeffrey L Anderson
Man-Yau Chan
The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., s...
Toward Eliminating the Decades-Old "Too Zonal and Too Equatorward" Storm-Track Bias in Climate Models [0.03%]
消除气候模式中长期存在的“纬向偏差”和“赤道偏差”的风暴轴偏误
Sebastian Schemm
Sebastian Schemm
Generations of climate models exhibit biases in their representation of North Atlantic storm tracks, which tend to be too far near the equator and too zonal. Additionally, models have difficulties simulating explosive cyclone growth. These ...
Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation [0.03%]
考虑和不考虑降水自聚集情况下的全球变暖引起的降水分布变化特征
Benjamin Fildier,William D Collins,Caroline Muller
Benjamin Fildier
We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium s...
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts [0.03%]
用于降水预报随机降尺度的一种生成式深度学习方法
Lucy Harris,Andrew T T McRae,Matthew Chantry et al.
Lucy Harris et al.
Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables. A major contributing factor to this is that several key processes affecting precipitation distributi...
Assimilation of Remotely Sensed Leaf Area Index Enhances the Estimation of Anthropogenic Irrigation Water Use [0.03%]
遥感叶面积指数同化可提高人为灌溉需水量的估算精度
Wanshu Nie,Sujay V Kumar,Christa D Peters-Lidard et al.
Wanshu Nie et al.
Representation of irrigation in Earth System Models has advanced over the past decade, yet large uncertainties persist in the effective simulation of irrigation practices, particularly over locations where the on-ground practices and climat...
Jan Ackmann,Peter D Dueben,Tim Palmer et al.
Jan Ackmann et al.
Semi-implicit (SI) time-stepping schemes for atmosphere and ocean models require elliptic solvers that work efficiently on modern supercomputers. This paper reports our study of the potential computational savings when using mixed precision...
R K Braghiere,J B Fisher,K Allen et al.
R K Braghiere et al.
Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant product...
Non-Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models [0.03%]
一种变分编码解码器的非线性降维方法在气候模型中理解对流过程
Gunnar Behrens,Tom Beucler,Pierre Gentine et al.
Gunnar Behrens et al.
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resu...
Fluid Simulations Accelerated With 16 Bits: Approaching 4x Speedup on A64FX by Squeezing ShallowWaters.jl Into Float16 [0.03%]
基于A64FX的浅水方程组流体模拟加速：16位浮点运算实现近4倍速度提升
Milan Klöwer,Sam Hatfield,Matteo Croci et al.
Milan Klöwer et al.
Most Earth-system simulations run on conventional central processing units in 64-bit double precision floating-point numbers Float64, although the need for high-precision calculations in the presence of large uncertainties has been question...
Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth From Dense Satellite and Sparse In Situ Observations [0.03%]
基于密集卫星观测和稀疏船载观测的海洋混合层深度的概率机器学习估计方法研究
Dallas Foster,David John Gagne nd,Daniel B Whitt
Dallas Foster
The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean pred...