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Numerical methods for the next generation weather and climate models

Abstract

Numerical models for atmospheric dynamics, a central piece in weather and climate forecasting, are going through radical changes in order to become adequate for the next generation supercomputers that demand massively parallel processing.This project aims to study two different lines of numerical schemes for this next generation of models: (i) the development and analysis of numerical schemes for quasi-uniform spherical grids, that avoids scalability problems encountered in traditional models; (ii) the exploration of the time dimension as source of parallelism, with methods that radically change the time integration way of thinking of these models.Recently, we have shown that one of the main methodologies used in this new generation of quasi-uniform grid based models lacks consistency (local truncation error fails to converge to zero with increasing resolution). We propose a scheme that circumvents this issue and we aim to add this new scheme to the National Center for Atmospheric Research (NCAR-USA) Model for Prediction Across Scales (MPAS), envisioning to build a numerically and dynamically consistent version of this model. In parallel, we will study other problems arising with this kind of approach, such as numerical instabilities and ways to optimize locally refined quasi-uniform grids. The usage of quasi-uniform grids extends the utility of atmospheric models with respect to its adequacy to modern computer architectures, however, in the long run, their scalability will still be limited by its domain partition communication pattern. We aim in this project to explore the time dimension as a new source of parallelism. Recently, we developed a massively parallel exponential time integrator method, that we intend to couple with a semi-Lagrangian integrator, for nonlinear advection, and with an iterative parallel-in-time scheme, to build a pioneer parallel-in-time method adequate for atmospheric models.This project will be accomplished mainly with the collaboration of researchers from UK universities (Univ. of Exeter and Imperial College), American research centres (Los Alamos Nat. Lab. and NCAR) and the University of Sao Paulo. (AU)

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Scientific publications (7)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
YU, YONGGANG G.; WANG, NING; MIDDLECOFF, JACQUES; PEIXOTO, PEDRO S.; GOVETT, MARK W. Comparing Numerical Accuracy of Icosahedral A-Grid and C-Grid Schemes in Solving the Shallow-Water Model. MONTHLY WEATHER REVIEW, v. 148, n. 10, p. 4009-4033, OCT 2020. Web of Science Citations: 0.
CANDIDO, DARLAN S.; CLARO, INGRA M.; DE JESUS, JAQUELINE G.; SOUZA, WILLIAM M.; MOREIRA, FILIPE R. R.; DELLICOUR, SIMON; MELLAN, THOMAS A.; DU PLESSIS, LOUIS; PEREIRA, RAFAEL H. M.; SALES, FLAVIA C. S.; MANULI, ERIKA R.; THEZE, JULIEN; ALMEIDA, LUIZ; MENEZES, MARIANE T.; VOLOCH, CAROLINA M.; FUMAGALLI, MARCILIO J.; COLETTI, THAIS M.; SILVA, CAMILA A. M.; RAMUNDO, MARIANA S.; AMORIM, MARIENE R.; HOELTGEBAUM, HENRIQUE H.; MISHRA, SWAPNIL; GILL, MANDEV S.; CARVALHO, LUIZ M.; BUSS, LEWIS F.; PRETE JR, CARLOS A.; ASHWORTH, JORDAN; NAKAYA, I, HELDER; PEIXOTO, PEDRO S.; BRADY, OLIVER J.; NICHOLLS, SAMUEL M.; TANURI, AMILCAR; ROSSI, ATILA D.; BRAGA, V, CARLOS K.; GERBER, ALEXANDRA L.; GUIMARAES, ANA PAULA DE C.; GABURO JR, NELSON; ALENCAR, CECILA SALETE; FERREIRA, ALESSANDRO C. S.; LIMA, CRISTIANO X.; LEVI, JOSE EDUARDO; GRANATO, CELSO; FERREIRA, GIULIA M.; FRANCISCO JR, RONALDO S.; GRANJA, FABIANA; GARCIA, MARCIA T.; MORETTI, MARIA LUIZA; PERROUD JR, MAURICIO W.; CASTINEIRAS, TEREZINHA M. P. P.; LAZARI, CAROLINA S.; HILL, SARAH C.; DE SOUZA SANTOS, ANDREZA ARUSKA; SIMEONI, CAMILA L.; FORATO, JULIA; SPOSITO, ANDREI C.; SCHREIBER, ANGELICA Z.; SANTOS, MAGNUN N. N.; DE SA, CAMILA ZOLINI; SOUZA, RENAN P.; RESENDE-MOREIRA, LUCIANA C.; TEIXEIRA, MAURO M.; HUBNER, JOSY; LEME, PATRICIA A. F.; MOREIRA, RENNAN G.; NOGUEIRA, MAURICIO L.; FERGUSON, NEIL M.; COSTA, SILVIA F.; PROENCA-MODENA, JOSE LUIZ; VASCONCELOS, ANA TEREZA R.; BHATT, SAMIR; LEMEY, PHILIPPE; WU, CHIEH-HSI; RAMBAUT, ANDREW; LOMAN, NICK J.; AGUIAR, RENATO S.; PYBUS, OLIVER G.; SABINO, ESTER C.; FARIA, NUNO RODRIGUES; DISCOVERY, BRAZIL-UK CTR ARBOVIRUS. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science, v. 369, n. 6508, SI, p. 1255+, SEP 4 2020. Web of Science Citations: 1.
DIAS, FABIO L.; ASSUMPCAO, MARCELO; PEIXOTO, PEDRO S.; BIANCHI, MARCELO B.; COLLACO, BRUNO; CALHAU, JACKSON. Using Seismic Noise Levels to Monitor Social Isolation: An Example From Rio de Janeiro, Brazil. Geophysical Research Letters, v. 47, n. 16 AUG 28 2020. Web of Science Citations: 0.
PEIXOTO, PEDRO S.; MARCONDES, DIEGO; PEIXOTO, CLAUDIA; OLIVA, SERGIO M. Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil. PLoS One, v. 15, n. 7 JUL 16 2020. Web of Science Citations: 5.
PEIXOTO, PEDRO S.; SCHREIBER, MARTIN. SEMI-LAGRANGIAN EXPONENTIAL INTEGRATION WITH APPLICATION TO THE ROTATING SHALLOW WATER EQUATIONS. SIAM JOURNAL ON SCIENTIFIC COMPUTING, v. 41, n. 5, p. B903-B928, 2019. Web of Science Citations: 0.
SCHMITT, A.; SCHREIBER, M.; PEIXOTO, P.; SCHAEFER, M. A numerical study of a semi-Lagrangian Parareal method applied to the viscous Burgers equation. COMPUTING AND VISUALIZATION IN SCIENCE, v. 19, n. 1-2, SI, p. 45-57, JUN 2018. Web of Science Citations: 0.
PEIXOTO, PEDRO S.; THUBURN, JOHN; BELL, MICHAEL J. Numerical instabilities of spherical shallow-water models considering small equivalent depths. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, v. 144, n. 710, A, p. 156-171, JAN 2018. Web of Science Citations: 8.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.