Articles | Volume 12, issue 10
Geosci. Model Dev., 12, 4261–4274, 2019
Geosci. Model Dev., 12, 4261–4274, 2019

Development and technical paper 10 Oct 2019

Development and technical paper | 10 Oct 2019

Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model

Jiali Wang et al.

Related authors

Fast and accurate learned multiresolution dynamical downscaling for precipitation
Jiali Wang, Zhengchun Liu, Ian Foster, Won Chang, Rajkumar Kettimuthu, and V. Rao Kotamarthi
Geosci. Model Dev., 14, 6355–6372,,, 2021
Short summary
A parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United States
Jiali Wang, Cheng Wang, Vishwas Rao, Andrew Orr, Eugene Yan, and Rao Kotamarthi
Geosci. Model Dev., 12, 3523–3539,,, 2019
Short summary

Related subject area

Earth and space science informatics
Copula-based synthetic data augmentation for machine-learning emulators
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215,,, 2021
Short summary
Automated geological map deconstruction for 3D model construction using map2loop 1.0 and map2model 1.0
Mark Jessell, Vitaliy Ogarko, Yohan de Rose, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, and Guillaume Pirot
Geosci. Model Dev., 14, 5063–5092,,, 2021
Short summary
A spatially explicit approach to simulate urban heat mitigation with InVEST (v3.8.0)
Martí Bosch, Maxence Locatelli, Perrine Hamel, Roy P. Remme, Jérôme Chenal, and Stéphane Joost
Geosci. Model Dev., 14, 3521–3537,,, 2021
Short summary
Turbidity maximum zone index: A novel model for remote extraction of turbidity maximum zone in different estuaries
Chongyang Wang, Li Wang, Danni Wang, Dan Li, Chenghu Zhou, Hao Jiang, Qiong Zheng, Shuisen Chen, Yangxiaoyue Liu, Ji Yang, Xia Zhou, and Yong Li
Geosci. Model Dev. Discuss.,,, 2021
Revised manuscript accepted for GMD
Short summary
S-SOM v1.0: a structural self-organizing map algorithm for weather typing
Quang-Van Doan, Hiroyuki Kusaka, Takuto Sato, and Fei Chen
Geosci. Model Dev., 14, 2097–2111,,, 2021
Short summary

Cited articles

Attali, J. G. and Pagès, G.: Approximations of functions by a multilayer perception: A new approach, Neural Networks, 6, 1069–1081, 1997. 
Chen, T. and Chen, H.: Approximation capability to functions of several variables, nonlinear functionals and operators by radial basis function neural networks, Neural Networks, 6, 904–910, 1995a. 
Chen, T. and Chen, H.: Universal approximation to nonlinear operators by neural networks with arbitrary activation function and its application to dynamical systems, Neural Networks, 6, 911–917, 1995b. 
Chevallier, F., Chéruy, F., Scott, N. A., and Chédin, A.: A neural network approach for a fast and accurate computation of longwave radiative budget, J. Appl. Meteorol., 37, 1385–1397, 1998. 
Chevallier, F., Morcrette, J.-J., Chéruy, F., and Scott, N. A.: Use of a neural-network-based longwave radiative transfer scheme in the EMCWF atmospheric model, Q. J. Roy. Meteor. Soc., 126, 761–776, 2000. 
Short summary
Parameterizations are frequently used in models representing physical phenomena and are often the computationally expensive portions of the code. Using model output from simulations performed using a weather model, we train deep neural networks to provide an accurate alternative to a physics-based parameterization. We demonstrate that a domain-aware deep neural network can successfully simulate the entire diurnal cycle of the boundary layer physics and the results are transferable.