Article
Mathematics, Applied
Manuel Santos Gutierrez, Valerio Lucarini, Mickael D. Chekroun, Michael Ghil
Summary: This study establishes a strong connection between data-driven and theoretical approaches to achieving efficient and accurate parameterizations for model reduction. Through perturbation expansions, a general stochastic parameterization of weakly coupled dynamical systems is derived, and it is shown that truncation of expansions is not necessary when coupling is additive. Additionally, the study simplifies unwieldy integrodifferential equations into a multilevel Markovian model and establishes an intuitive connection with a generalized Langevin equation. This research supports the physical basis and robustness of the empirical model reduction (EMR) methodology while highlighting the practical relevance of the perturbative expansion used for deriving the parameterizations.
Article
Engineering, Electrical & Electronic
David Kraljic
Summary: The increased share of renewable energy sources in power grids results in larger deviations in grid frequency and poses challenges for control and modeling. This paper focuses on the grid frequency of the power system in Great Britain, which serves as a template for future power grids due to its high proportion of renewables and exhibits unique statistical properties such as long-term correlations, periodicity, bi-modality, and heavy tails in frequency distribution. By modifying the swing equation and noise statistics, the authors successfully reproduce these statistical properties and demonstrate the improved performance of their model compared to a standard swing equation model in realistic frequency response services.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Geosciences, Multidisciplinary
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurelie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clement Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, Rene Schubert, Baylor Fox-Kemper, William K. Dewar, Alan Wallcraft
Summary: With the increase in computational power, higher-resolution ocean models have been developed, but the larger data size poses challenges for data transfer and analysis. A cloud-based analysis framework is proposed to address these challenges, allowing for more efficient and collaborative analysis of model outputs.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Meteorology & Atmospheric Sciences
B. Khouider, B. B. Goswami, R. Phani, A. J. Majda
Summary: Cumulus parameterization in global climate models is based on the quasi-equilibrium assumption, which is not compatible with the organization and dynamical interactions of cloud systems. Recently, novel ideas such as the stochastic multicloud model have emerged to represent the key processes of moist convection-large-scale interaction. By modifying the Zhang-McFarlane parameterization, the stochastic multicloud model introduces a stochastic ensemble of plumes to better simulate organized tropical convection.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Environmental Sciences
Yu Ting Kwok, Edward Yan Yung Ng
Summary: Researchers have made significant progress in understanding urban-induced microclimate through numerical modelling, with advancements in model complexity and urban surface data precision observed in recent years. Most studies focus on urban thermal climate and urbanization effects, with a need for more research on vulnerable cities in developing countries. Collaborative field campaigns, consistent city characterization initiatives, and multi-scale modelling approaches have proven beneficial for urban climate studies. Efforts should be directed towards translating scientific findings into information relevant for human well-being, urban planning, and policymaking.
Article
Geosciences, Multidisciplinary
Niraj Agarwal, R. Justin Small, Frank O. Bryan, Ian Grooms, Philip J. Pegion
Summary: Air-sea flux variability is influenced by both ocean and atmosphere at different spatio-temporal scales. While climate models can accurately capture atmospheric synoptic scales and air-sea turbulent heat flux, they often fail to resolve ocean mesoscales due to resolution limitations. This study introduces a stochastic subgrid-scale parameterization method for ocean density, which enhances the representation of lateral density variations caused by oceanic eddies, and examines its impact on air-sea heat flux variability using a comprehensive coupled climate model. The stochastic parameterization significantly alters sea surface temperature (SST) and latent heat flux (LHF) variability and their co-variability, particularly at scales near the resolution of the ocean model grid, leading to improved consistency with high-resolution satellite observations, especially in the Gulf Stream region.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Geosciences, Multidisciplinary
C. E. J. Watt, H. J. Allison, R. L. Thompson, S. N. Bentley, N. P. Meredith, S. A. Glauert, R. B. Horne, I. J. Rae
Summary: In this study, the impact of temporal variability in diffusion coefficients (D) on changes in electron flux in Earth's outer radiation belt was investigated using stochastic parameterization method. Results show that the evolution and final state of the numerical experiment greatly depend on the variability time scale of D, highlighting the importance of considering temporal variability in radiation belt diffusion.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Review
Physics, Multidisciplinary
Christian L. E. Franzke, Richard Blender, Terence J. O'Kane, Valerio Lembo
Summary: The 2021 Nobel prize for physics was awarded to two climate scientists, Syukuro Manabe and Klaus Hasselmann, and the physicist Giorgio Parisi. While Parisi's work might not seem directly related to climate science, his contributions to complexity science methods have had a significant impact on climate modeling. Hasselmann's stochastic climate models and Manabe's advancements in parameterization have also greatly influenced climate research.
FRONTIERS IN PHYSICS
(2022)
Article
Meteorology & Atmospheric Sciences
V. Kitsios, J. S. Frederiksen, T. J. O'Kane
Summary: Ocean circulation dynamics is a complex system with various interactions between different scales and components, which can be effectively represented and simulated using numerical models. The accuracy of these simulations depends on proper parameterizations, especially for the subgrid interactions. In this study, parameterizations for different classes of subgrid interactions are developed and validated in idealized Antarctic Circumpolar Current flows.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Meteorology & Atmospheric Sciences
Jihoon Shin, Jong-Jin Baik
Summary: A new spectral convection scheme called stochastic UNICON is implemented in a general circulation model and evaluated in comparison with UNICON, with a focus on simulating the Madden-Julian oscillation (MJO). Stochastic UNICON extends UNICON by randomly sampling convective updrafts from a joint probability density function, leading to improved simulation of MJO intensity and propagation patterns. The coherency between MJO-related convection and large-scale circulation is also enhanced, and the simulation of moisture tendencies and convective processes during MJO developing periods is consistently improved.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Meteorology & Atmospheric Sciences
Wenyu Zhou, L. Ruby Leung, Jian Lu
Summary: This study shows that local-scale drizzling bias in atmospheric models can lead to large-scale double-ITCZ bias in coupled models. The double-ITCZ bias consists of hemispherically asymmetric and nearly symmetric components.
JOURNAL OF CLIMATE
(2022)
Article
Environmental Sciences
Andrea Storto, Chunxue Yang
Summary: Advancing the representation of uncertainties in ocean general circulation numerical models is crucial for various applications. The main uncertainty source in these models is the atmospheric forcing. In this study, different approaches to perturb the air-sea fluxes used in atmospheric boundary conditions are formulated and revised. The schemes are implemented and tested in the NEMO4 ocean model, and the results show that they can improve verification skill scores and enhance certain oceanic features. The choice of scheme depends on the specific application.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Meteorology & Atmospheric Sciences
Hideaki Kawai, Kohei Yoshida, Tsuyoshi Koshiro, Seiji Yukimoto
Summary: Parameter tuning is well-known to impact the performance of Global Climate Models. However, other implementation details, such as limits and thresholds of variables, can also significantly affect model performance. These minor-looking treatments sometimes have comparable or even larger impacts than advanced parameterizations based on theory and observation.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Review
Geosciences, Multidisciplinary
Anahi Villalba-Pradas, Francisco J. Tapiador
Summary: Convection plays a crucial role in climate and weather events, making accurate predictions of its time, location, and development essential. Parameterization of convection is necessary in global climate models and Earth system models due to the scale differences. This paper examines the choices made in convection schemes and emphasizes the importance of observations in improving our understanding of convection physics.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Meteorology & Atmospheric Sciences
J. S. Kenigson, A. Adcroft, S. D. Bachman, F. Castruccio, I Grooms, P. Pegion, Z. Stanley
Summary: This study tests a new parameterization method in an ocean model and finds that it has coherent impacts on large-scale ocean circulation and hydrography, especially in the Nordic Seas and Labrador Sea.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Meteorology & Atmospheric Sciences
Sergey Kravtsov, I. Rudeva, Sergey K. Gulev
JOURNAL OF THE ATMOSPHERIC SCIENCES
(2015)
Editorial Material
Multidisciplinary Sciences
S. Kravtsov, M. G. Wyatt, J. A. Curry, A. A. Tsonis
Article
Geosciences, Multidisciplinary
Nikola Jajcay, Jaroslav Hlinka, Sergey Kravtsov, Anastasios A. Tsonis, Milan Palus
GEOPHYSICAL RESEARCH LETTERS
(2016)
Article
Meteorology & Atmospheric Sciences
Sergey Kravtsov, Natalia Tilinina, Yulia Zyulyaeva, Sergey K. Gulev
JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
(2016)
Article
Geosciences, Multidisciplinary
Sergey Kravtsov
GEOPHYSICAL RESEARCH LETTERS
(2017)
Article
Meteorology & Atmospheric Sciences
Sergey Kravtsov, David Callicutt
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2017)
Editorial Material
Meteorology & Atmospheric Sciences
Sergey Kravtsov
JOURNAL OF CLIMATE
(2017)
Article
Multidisciplinary Sciences
Sergey Kravtsov, Paul Roebber, Vytaras Brazauskas
Article
Mechanics
Sergey Kravtsov, Gregory Reznik
Article
Meteorology & Atmospheric Sciences
Sergey Kravtsov
JOURNAL OF CLIMATE
(2020)
Article
Mechanics
Gregory Reznik, Sergey Kravtsov
Summary: Building upon the work of Kravtsov and Reznik [J. Fluid Mech. 909, A23 (2021); KR21], this study investigates the interactions of a localized monopole with a rectilinear, constant-shear flow in a quasi-geostrophic model. The dynamics of the interactions are significantly influenced by the non-invariance of the model with respect to Galilean transformations. The results show that certain configurations are stable while others eventually break down due to the movement of the vortex in the background flow field.
Article
Meteorology & Atmospheric Sciences
Sergey Kravtsov, Paul Roebber, Thomas M. Hamill, James Brown
Summary: This paper utilizes statistical and statistical-dynamical methodologies to select a minimal subset of dates that would provide representative sampling of local precipitation distributions across the contiguous United States. By building a high-dimensional empirical model of temperature and precipitation, the researchers are able to accurately simulate and forecast the observed data.
WEATHER AND FORECASTING
(2022)
Article
Meteorology & Atmospheric Sciences
S. Kravtsov, C. Grimm, S. Gu
NPJ CLIMATE AND ATMOSPHERIC SCIENCE
(2018)
Article
Meteorology & Atmospheric Sciences
Nikola Jajcay, Sergey Kravtsov, George Sugihara, Anastasios A. Tsonis, Milan Palus
NPJ CLIMATE AND ATMOSPHERIC SCIENCE
(2018)
Article
Meteorology & Atmospheric Sciences
Noriyuki Sugiyama, Sergey Kravtsov, Paul Roebber