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Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction ModelMuch work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves Niño3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.
Document ID
20190032288
Acquisition Source
Goddard Space Flight Center
Document Type
Poster
Authors
Kovach, R.
(Science Systems and Applications, Inc. (SSAI) Lanham, MD, United States)
Hackert, E.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Ballabrera-Poy, J.
Busalacchi, A.J.
Vernieres, G.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
October 25, 2019
Publication Date
September 16, 2019
Subject Category
Oceanography
Geosciences (General)
Report/Patent Number
GSFC-E-DAA-TN73375
Meeting Information
Meeting: OceanObs19
Location: Honolulu, HI
Country: United States
Start Date: September 16, 2019
End Date: September 20, 2019
Sponsors: NASA Goddard Space Flight Center
Funding Number(s)
CONTRACT_GRANT: NNG17HP01C
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Keywords
Ocean
SMAP
ENSO
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