Process-Based Climate Model Development Harnessing Machine Learning: I. A Calibration Tool for Parameterization Improvement

被引:46
作者
Couvreux, Fleur [1 ]
Hourdin, Frederic [2 ]
Williamson, Daniel [3 ,5 ]
Roehrig, Romain [1 ]
Volodina, Victoria [5 ]
Villefranque, Najda [1 ,4 ]
Rio, Catherine [1 ]
Audouin, Olivier [1 ]
Salter, James [3 ,5 ]
Bazile, Eric [1 ]
Brient, Florent [1 ]
Favot, Florence [1 ]
Honnert, Rachel [1 ]
Lefebvre, Marie-Pierre [1 ,2 ]
Madeleine, Jean-Baptiste [2 ]
Rodier, Quentin [1 ]
Xu, Wenzhe [3 ]
机构
[1] Univ Toulouse, CNRS, CNRM, Meteo France, Toulouse, France
[2] Sorbonne Univ, CNRS, LMD IPSL, Paris, France
[3] Exeter Univ, Exeter, Devon, England
[4] Univ Toulouse, CNRS, LAPLACE, Toulouse, France
[5] Alan Turing Inst, London, England
基金
英国工程与自然科学研究理事会;
关键词
calibration; large‐ eddy simulations; physical parameterizations; process‐ oriented model tuning; single‐ column models;
D O I
10.1029/2020MS002217
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The development of parameterizations is a major task in the development of weather and climate models. Model improvement has been slow in the past decades, due to the difficulty of encompassing key physical processes into parameterizations, but also of calibrating or "tuning" the many free parameters involved in their formulation. Machine learning techniques have been recently used for speeding up the development process. While some studies propose to replace parameterizations by data-driven neural networks, we rather advocate that keeping physical parameterizations is key for the reliability of climate projections. In this paper we propose to harness machine learning to improve physical parameterizations. In particular, we use Gaussian process-based methods from uncertainty quantification to calibrate the model free parameters at a process level. To achieve this, we focus on the comparison of single-column simulations and reference large-eddy simulations over multiple boundary-layer cases. Our method returns all values of the free parameters consistent with the references and any structural uncertainties, allowing a reduced domain of acceptable values to be considered when tuning the three-dimensional (3D) global model. This tool allows to disentangle deficiencies due to poor parameter calibration from intrinsic limits rooted in the parameterization formulations. This paper describes the tool and the philosophy of tuning in single-column mode. Part 2 shows how the results from our process-based tuning can help in the 3D global model tuning.
引用
收藏
页数:27
相关论文
共 124 条
[1]   Single-Column Modeling of Convection During the CINDY2011/DYNAMO Field Campaign With the CNRM Climate Model Version 6 [J].
Abdel-Lathif, Ahmat Younous ;
Roehrig, Romain ;
Beau, Isabelle ;
Douville, Herve .
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2018, 10 (03) :578-602
[2]   Efficient History Matching of a High Dimensional Individual-Based HIV Transmission Model [J].
Andrianakis, Loannis ;
McCreesh, Nicky ;
Vernon, Ian ;
McKinley, Trevelyan J. ;
Oakley, Jeremy E. ;
Nsubuga, Rebecca N. ;
Goldstein, Michael ;
White, Richard G. .
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2017, 5 (01) :694-719
[3]  
[Anonymous], CLIMATE CHANGE 2013
[4]   An evaluation of neutral and convective planetary boundary-layer parameterizations relative to large eddy simulations [J].
Ayotte, KW ;
Sullivan, PP ;
Andren, A ;
Doney, SC ;
Holtslag, AAM ;
Large, WG ;
Mcwilliams, JC ;
Moeng, CH ;
Otte, MJ ;
Tribbia, JJ ;
Wyngaard, JC .
BOUNDARY-LAYER METEOROLOGY, 1996, 79 (1-2) :131-175
[5]   Parameter sensitivity analysis for different complexity land surface models using multicriteria methods [J].
Bastidas, L. A. ;
Hogue, T. S. ;
Sorooshian, S. ;
Gupta, H. V. ;
Shuttleworth, W. J. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2006, 111 (D20)
[6]   Objective calibration of regional climate models [J].
Bellprat, O. ;
Kotlarski, S. ;
Luethi, D. ;
Schaer, C. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2012, 117
[7]   Clouds, circulation and climate sensitivity [J].
Bony, Sandrine ;
Stevens, Bjorn ;
Frierson, Dargan M. W. ;
Jakob, Christian ;
Kageyama, Masa ;
Pincus, Robert ;
Shepherd, Theodore G. ;
Sherwood, Steven C. ;
Siebesma, A. Pier ;
Sobel, Adam H. ;
Watanabe, Masahiro ;
Webb, Mark J. .
NATURE GEOSCIENCE, 2015, 8 (04) :261-268
[8]  
BOUGEAULT P, 1989, MON WEATHER REV, V117, P1872, DOI 10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO
[9]  
2
[10]   Macrophysical, Microphysical, and Radiative Properties of Tropical Mesoscale Convective Systems over Their Life Cycle [J].
Bouniol, Dominique ;
Roca, Remy ;
Fiolleau, Thomas ;
Poan, Emmanuel .
JOURNAL OF CLIMATE, 2016, 29 (09) :3353-3371