Articles | Volume 15, issue 10
Geosci. Model Dev., 15, 4193–4223, 2022
https://doi.org/10.5194/gmd-15-4193-2022

Special issue: Joint UK Land Environment Simulator (JULES) – configurations,...

Geosci. Model Dev., 15, 4193–4223, 2022
https://doi.org/10.5194/gmd-15-4193-2022
Model description paper
01 Jun 2022
Model description paper | 01 Jun 2022

The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale

Juan Manuel Castillo et al.

Related authors

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model
Jennifer Saxby, Julia Crook, Simon Peatman, Cathryn Birch, Juliane Schwendike, Maria Valdivieso da Costa, Juan Manuel Castillo Sanchez, Chris Holloway, Nicholas P. Klingaman, Ashis Mitra, and Huw Lewis
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-46,https://doi.org/10.5194/wcd-2021-46, 2021
Preprint withdrawn
Short summary
Evaluating the impact of atmospheric forcing and air–sea coupling on near-coastal regional ocean prediction
Huw W. Lewis, John Siddorn, Juan Manuel Castillo Sanchez, Jon Petch, John M. Edwards, and Tim Smyth
Ocean Sci., 15, 761–778, https://doi.org/10.5194/os-15-761-2019,https://doi.org/10.5194/os-15-761-2019, 2019
Short summary
The UKC3 regional coupled environmental prediction system
Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019,https://doi.org/10.5194/gmd-12-2357-2019, 2019
Short summary
Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019,https://doi.org/10.5194/os-15-669-2019, 2019
Short summary
AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018,https://doi.org/10.5194/gmd-11-681-2018, 2018
Short summary

Related subject area

Atmospheric sciences
Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023,https://doi.org/10.5194/gmd-16-509-2023, 2023
Short summary
Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023,https://doi.org/10.5194/gmd-16-479-2023, 2023
Short summary
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023,https://doi.org/10.5194/gmd-16-251-2023, 2023
Short summary
ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023,https://doi.org/10.5194/gmd-16-47-2023, 2023
Short summary
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023,https://doi.org/10.5194/gmd-16-1-2023, 2023
Short summary

Cited articles

Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamic proceses of the UCLA general circulation model, Methods Comput. Phys., 17, 173–265, 1977. 
Ardhuin, F., Rogers, E., Babanin, A. V., Filipot, J. F., Magne, R., Roland, A., van der Westhuysen, A., Queffeulou, P., Lefevre, J. M., Aouf, L., and Collard, F.: Semiempirical dissipation source functions for ocean waves. Part I: definition, calibration, and validation, J. Phys. Oceanogr., 40, 1917–1941, https://doi.org/10.1175/2010JPO4324.1, 2010. 
Arnold, A. K., Lewis, H. W., Hyder, P., Siddorn, J., and O'Dea, E.: The Sensitivity of British Weather to Ocean Tides, Geophys. Res. Lett., 48, e2020GL090732, https://doi.org/10.1029/2020GL090732, 2021. 
Baki, H., Chinta, S., C Balaji, and Srinivasan, B.: Determining the sensitive parameters of the Weather Research and Forecasting (WRF) model for the simulation of tropical cyclones in the Bay of Bengal using global sensitivity analysis and machine learning, Geosci. Model Dev., 15, 2133–2155, https://doi.org/10.5194/gmd-15-2133-2022, 2022. 
Battjes, J. A. and Janssen, J. P. F. M.: Energy loss and set-up due to breaking of random waves, Proc. 16th Int. Conf. Coastal Eng., 569–587, https://doi.org/10.1061/9780872621909.034, 1978. 
Download
Short summary
A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.