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Inverse modeling of global and regional energy and water cycle fluxes using Earth observation data

Thomas, C. M., Dong, B. and Haines, K. (2020) Inverse modeling of global and regional energy and water cycle fluxes using Earth observation data. Journal of Climate, 33 (5). pp. 1707-1723. ISSN 1520-0442

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To link to this item DOI: 10.1175/JCLI-D-19-0343.1

Abstract/Summary

The NASA Energy and Water Cycle Study (NEWS) climatology is a self-consistent coupled annual and seasonal cycle solution for radiative, turbulent and water fluxes over the Earth's surface using Earth observation data covering 2000-2009. Here we seek to improve the NEWS solution, particularly over the ocean basins, by considering spatial covariances in the observation errors (some evidence for which is found by comparing five turbulent flux products over the oceans) and by introducing additional horizontal transports from ocean reanalyses as weak constraints. By explicitly representing large error covariances between surface heat flux components over the major ocean basins we retain the flux contrasts present in the original data and infer additional heat losses over the North Atlantic, more consistent with a strong Atlantic overturning. This change does not alter the global flux balance but if only the errors in evaporation and precipitation are correlated then those fluxes experience larger adjustments (e.g. the surface latent heat flux increases to 85 +- 2 Wm). Replacing SeaFlux v1 with J-OFURO v3 ocean fluxes also leads to a considerable increase in the global latent heat loss as well as a larger North Atlantic heat loss. Furthermore, including a weak constraint on the horizontal transports of heat and freshwater from high-resolution ocean reanalyses improves the net fluxes over the North Atlantic, Caribbean and Arctic Oceans, without any impact on the global flux balances. These results suggest that better characterised flux uncertainties can greatly improve the quality of the optimised flux solution.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:87061
Publisher:American Meteorological Society

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