RT Journal Article
T1 Model hierarchies for understanding atmospheric circulation
A1 Maher, Penelope
A1 Gerber, Edwin P.
A1 Medeiros, Brian
A1 Merlis, Timothy M.
A1 Sherwood, Steven
A1 Sheshadri, Aditi
A1 Sobel, Adam H.
A1 Vallis, Geoffrey K.
A1 Voigt, Aiko
A1 Zurita Gotor, Pablo
AB In this review, we highlight the complementary relationship between simple and comprehensive models in addressing key scientific questions to describe Earth's atmospheric circulation. The systematic representation of models in steps, or hierarchies, connects our understanding from idealized systems to comprehensive models and ultimately the observed atmosphere. We define three interconnected principles that can be used to characterize the model hierarchies of the atmosphere. We explore the rich diversity within the governing equations in the dynamical hierarchy, the ability to isolate and understand atmospheric processes in the process hierarchy, and the importance of the physical domain and resolution in the hierarchy of scale. We center our discussion on the large-scale circulation of the atmosphere and its interaction with clouds and convection, focusing on areas where simple models have had a significant impact. Our confidence in climate model projections of the future is based on our efforts to ground the climate predictions in fundamental physical understanding. This understanding is, in part, possible due to the hierarchies of idealized models that afford the simplicity required for understanding complex systems.
PB American Geophysical Union
SN 8755-1209
YR 2019
FD 2019-06
LK https://hdl.handle.net/20.500.14352/13794
UL https://hdl.handle.net/20.500.14352/13794
LA eng
NO © 2019. American Geophysical Union. We wish to acknowledge Dee Burke who created Figure2. We would like to sincerely thank Isaac Held and two anonymous reviewers, whose comments led us to greatly improve earlier versions of this manuscript. We also wish to thank our editors and the editorial staff. We also wish to acknowledge funding agencies who have supported us in writing this review. P. M. and G. K. V. acknowledge the Natural Environment Research Council and Met Office ParaCon project NE/N013123/1. E. P. G. acknowledges support from the U.S. National Science Foundation through grant AGS-1546585. B. M. acknowledges support by the Regional and Global Model Analysis component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological and Environmental Research cooperative agreement DE-FC02-97ER62402, and the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement 1852977. T. M. M. acknowledges Natural Science and Engineering Research Council of Canada grant RGPIN-2014-05416 and a Canada Research Chair. S. S. acknowledges the Australian Research Council grant ARC FL150100035. A. S. acknowledges the Simons Foundation award 354584. A. H. S. acknowledges the National Science Foundation grant AGS-1758603. A. V. acknowledges the German Ministry of Education and Research (BMBF) and FONA: Research for Sustainable Development (www.fona.de) under grant agreement 01LK1509A. P. Z. G. acknowledges the State Research Agency of Spain, grant CGL2015-72259-EXP.
NO Ministerio de Economía y Competitividad (MINECO)
NO Natural Environment Research Council
NO Met Office ParaCon
NO U.S. National Science Foundation
NO Regional and Global Model Analysis component of the Earth
NO Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological
NO Environmental Research
NO the National Center for Atmospheric Research
NO National Science Foundation under Cooperative Agreement
NO Natural Science and Engineering Research Council of Canada
NO Canada Research Chair
NO Australian Research Council
NO State Research Agency of Spain
NO Simons Foundation
NO German Ministry of Education and Research (BMBF)
NO FONA: Research for Sustainable Development (www.fona.de)
DS Docta Complutense
RD 16 abr 2025