While cloud-resolving models can explicitly simulate the details of small-scale storm formation and morphology, these details are often ignored by climate models for lack of computational resources. Here, we explore the potential of generative modeling to cheaply recreate small-scale storms by designing and implementing a Variational Autoencoder (VAE) that performs structural replication, dimensionality reduction, and clustering of high-resolution vertical velocity fields. Trained on ~6*10^6 samples spanning the globe, the VAE successfully reconstructs the spatial structure of convection, performs unsupervised clustering of convective organization regimes, and identifies anomalous storm activity, confirming the potential of generative modeling to power stochastic parameterizations of convection in climate models.
University of California Irvine（加州大学欧文分校）；University of Lausanne（洛桑大学）
Understanding the details of small-scale convection and storm formation is crucial to accurately represent the larger-scale planetary dynamics. Presently, atmospheric scientists run high-resolution, storm-resolving simulations to capture these kilometer-scale weather details. However, because they contain abundant information, these simulations can be overwhelming to analyze using conventional approaches. This paper takes a data-driven approach and jointly embeds spatial arrays of vertical wind velocities, temperatures, and water vapor information as three "channels" of a VAE architecture. Our…
Scientific simulations are often used to gain insight into foundational questions. However, many potentially useful simulation results are difficult to visualize without powerful computers. In this research, we seek to build a surrogate model, using a generative adversarial network, to allow for the visualization of the Earth's Mantle Convection data set on readily accessible hardware. We present our preliminary method and results, and all code is made publicly available. The preliminary results show that a surrogate model of the Earth's Mantle Convection data set can generate useful results. …
École polytechnique fédérale de Lausanne（洛桑联邦理工学院）；Federal Office of Meteorology and Climatology MeteoSwiss（联邦气象和气候学办公室 MeteoSwiss）
Generative adversarial networks (GANs) have been recently adopted for super-resolution, an application closely related to what is referred to as "downscaling" in the atmospheric sciences: improving the spatial resolution of low-resolution images. The ability of conditional GANs to generate an ensemble of solutions for a given input lends itself naturally to stochastic downscaling, but the stochastic nature of GANs is not usually considered in super-resolution applications. Here, we introduce a recurrent, stochastic super-resolution GAN that can generate ensembles of time-evolving high-resoluti…
Multimodal Atmospheric Super-Resolution With Deep Generative Models
Information Sciences and Technology（信息科学与技术系）；The Pennsylvania State University（宾夕法尼亚州立大学）；Environmental Science Division（环境科学部）；Argonne National Laboratory（阿贡国家实验室）；Department of Geography（地理系）
Statistical Downscaling of Daily Precipitation from ERA5 Atmospheric Fields to IMERG over West Africa
Laboratoire d’Océanographie et des Sciences de l’Environnement et du Climat (LOSEC)Université Assane Seck de Ziguinchor（西古尔省阿萨内·塞克大学海洋与环境气候学实验室）；Institut Pierre-Simon Laplace (IPSL), Sorbonne Université, IRD（皮埃尔-西蒙·拉普拉斯研究所，索邦大学，法国国家科学研究中心）
Empirical models, fitted to data from observations, are often used in natural sciences to describe physical behaviour and support discoveries. However, with more complex models, the regression of parameters quickly becomes insufficient, requiring a visual parameter space analysis to understand and optimize the models. In this work, we present a design study for building a model describing atmospheric convection. We present a mixed-initiative approach to visually guided modelling, integrating an interactive visual parameter space analysis with partial automatic parameter optimization. Our appro…
It is shown, using results of direct numerical simulations, laboratory experiments, measurements in the atmospheric boundary layer, satellite infrared radiances data, the planetary-scale surface-air and tropospheric data, that the temperature fluctuations in atmospheric free convection can be well described by the spatio-temporal distributed chaos approach based on the Bolgiano-Obukhov phenomenology. A possibility of analogous consideration of the atmospheric dynamics on other planets (Mars, Jupiter and Saturn) has been briefly discussed using the data obtained with the Phoenix lander and the …
Multi-fluid models have recently been proposed as an approach to improving the representation of convection in weather and climate models. This is an attractive framework as it is fundamentally dynamical, removing some of the assumptions of mass-flux convection schemes which are invalid at current model resolutions. However, it is still not understood how best to close the multi-fluid equations for atmospheric convection. In this paper we develop a simple two-fluid, single-column model with one rising and one falling fluid. No further modelling of sub-filter variability is included. We then ap…
Cloud-aerosol interactions remain a major obstacle to understanding climate and severe weather. Observations suggest that aerosols enhance tropical thunderstorm activity; past research, motivated by the importance of understanding aerosol impacts on clouds, has proposed several mechanisms that could explain that observed link. Here, we show that high-resolution atmospheric simulations can reproduce the observed link between aerosols and convection. However, we also show that previously proposed mechanisms are unable to explain the invigoration. Examining underlying processes reveals that, in o…
Numerical simulations of nonhydrostatic atmospheric flow, based on linearly decoupled semi-implicit or fully-implicit techniques, usually solve linear systems by a pre-conditioned Krylov method without preserving the skew-symmetry of convective operators. We propose to perform atmospheric simulations in such a fully-implicit manner that the difference operators preserve both the skew-symmetry and the tightly nonlinear coupling of the differential operators. We demonstrate that a symmetry-preserving Jacobian-free Newton-Krylov~(JFNK) method mimics a balance between convective transport and turb…
After the sunset, under calm and clear sky conditions, aerosol laden surface air-layer, cools radiatively to the upper atmosphere. Predominant effect of the radiative cooling on the vertical temperature profile extends to several hundred meters from the surface. This results in the development of a stable, nocturnal inversion layer. However, ground surface, owing to its higher thermal inertia, lags in the cooling process. Due to this about a meter thick air layer just above the ground can be (2-6)deg Celsius cooler than the ground. Thus, at the surface an unstable convective layer is present, …
From Flight Logs to Atmospheric Science: Paragliders as Convection Sensors for Identifying Thermal Predictors
Econophysics Lab, Institut Louis Bachelier（经济物理学实验室，路易·巴舍利耶研究所）；LadHyX UMR CNRS 7646, École Polytechnique, Institut Polytechnique de Paris（拉迪赫克斯联合研究实验室（CNRS 7646），巴黎综合理工学院，巴黎理工学院）；Capital Fund Management（资本基金管理公司）
In Earth's current climate, moist convective updraft speeds increase with surface warming. This trend suggests that very vigorous convection might be the norm in extremely hot and humid atmospheres, such as those undergoing a runaway greenhouse transition. However, theoretical and numerical evidence suggests that convection is actually gentle in water vapor-dominated atmospheres, implying that convective vigor may peak at some intermediate humidity level. Here, we perform small-domain convection-resolving simulations of an Earth-like atmosphere over a wide range of surface temperatures and con…
Recent research has suggested that the overall dependence of convection near coasts on large-scale atmospheric conditions is weaker than over the open ocean or inland areas. This is due to the fact that in coastal regions convection is often supported by meso-scale land-sea interactions and the topography of coastal areas. As these effects are not resolved and not included in standard cumulus parametrization schemes, coastal convection is among the most poorly simulated phenomena in global models. To outline a possible parametrization framework for coastal convection we develop an idealized mo…
Cooperative Institute for Research in the Atmosphere (CIRA)（大气研究合作研究所）；National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) / Global Systems Laboratory (GSL)（美国国家海洋和大气管理局地球系统研究实验室/全球系统实验室）；Colorado State University（科罗拉多州立大学）
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) in atmospheric science are almost always trained to optimize pixelwise loss functions, even when ultimately assessed with SV methods. This establishes a disconnect between model verification during vs. after training. To address this issue, we develop spatially enhanced loss functions (SELF) and demonstrate their use for a real-world problem: predicting the occurrence of thunde…
One the major factors determining the development and evolution of atmospheric convection is the sea surface temperature and its variability. Results of this thesis show that state of atmospheric convection impacts the diurnal distribution of thermal energy in the upper ocean. Under calm and clear sky conditions a shallow warm layer of several meters depth develops on the surface of the ocean. This warm layer drives an anomalous flux from the ocean to the atmosphere. A novel Kelvin wave trajectory database based on satellite data is introduced in this study. The investigation of its data shows…
This article discusses the modeling of perturbed potential temperature in an atmospheric boundary layer. We adopt a convection-diffusion model with specified initial and boundary conditions that resulted from simplifying the linearized equation of the standard continuity equation for potential temperature field in the state of weak turbulent fluxes. By implementing the method of separation of variables to the non-steady-state perturbed potential temperature, we obtain a regular Sturm-Liouville problem for the spatial-dependent, vertical distribution component of the perturbed potential tempera…
Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations
Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model
Deutsches Zentrum für Luft- und Raumfahrt（德国航空航天中心）；Faculty of Geosciences and Environment, University of Lausanne（洛桑大学地球科学与环境学院）；Expertise Center for Climate Extremes, University of Lausanne（洛桑大学气候极端研究中心）；University of Bremen, Institute of Environmental Physics (IUP)（不来梅大学环境物理研究所）
Ensemble-based, large-eddy reconstruction of wind turbine inflow in a near-stationary atmospheric boundary layer through generative artificial intelligence
National Renewable Energy Laboratory（国家可再生能源实验室）；Sandia National Laboratories（桑迪亚国家实验室）
Improved Precipitation Variability in the Community Atmosphere Model through Implementation of a Neural-Network Deep Convection Scheme
Columbia University（哥伦比亚大学）；Massachusetts Institute of Technology（麻省理工学院）；U.S. National Science Foundation National Center for Atmospheric Research（美国国家科学基金会国家大气研究中心）；University of Cambridge（剑桥大学）；Stony Brook University（石溪大学）；Google Research（谷歌研究）
Moist convection plays a leading role in the dynamics and energy budget of Earth's tropics and influences the sensitivity of Earth's climate to greenhouse gas increases. Because individual convective cells are much smaller than the gridboxes of 3-dimensional global climate models (GCMs), these models parameterize the effects of an ensemble of moist convective updrafts and downdrafts on the environment. Cumulus parameterization has been a focus of the terrestrial meteorology community for half a century. Only in past decade, however, have GCMs with moist convective physics been applied to other…
