Multi-Timescale Near-Surface Salinity Variability at the Eastern Edge of the Warm Pool: A Modeling and an OSSE Study in Support of TPOS 2020
PIs: Arun Kumar (NOAA/NCEP/CPC), Avichal Mehra (NOAA/NCEP/EMC) and Meghan Cronin (NOAA/PMEL), Jieshun Zhu (NOAA/NCEP/CPC & UMD/ESSIC), and Dongxiao Zhang (UW/JISAO)
Description
The western Pacific warm pool (WPWP) is characterized by sea surface temperatures (SSTs) warmer than 28–29ºC, sea surface salinities (SSS) fresher than 35psu, enhanced atmospheric deep convections with heavy precipitation of 2–4 m/yr and low wind speed regime. The ocean variability in the WPWP is across a wide range of spatial and temporal scales. In term of time scale, variability ranges from diurnal, intraseasonal, seasonal to interannual and even lower frequency, and is likely controlled by different basin-dependent processes. Our understanding about SSS variability on different time scales in the WPWP is limited compared to SST, partially due to the sparseness of salinity observations.
Our work is a pre-field modeling study in support of advancing the vision of TPOS 2020. The objectives are to (a) explore the multi-timescale near-surface salinity variations in the WPWP by diagnosing model simulations, and (b) to identify possible sampling requirements (and strategies) that may be essential to capture the multi-timescale variability by conducting observing systems simulation experiments (OSSEs).
This project was funded by the NOAA’s Climate Variability and Predictability (CVP) Program as one of its eight modelling projects in support NOAA’s contribution to TPOS2020.
Accomplishments
1) Upper ocean salinity budget analysis with model outputs.
By including some modifications in the NCEP Climate Forecast System, version 2, a more realistic MJO simulation and a better simulation of intraseasonal SSS variability are achieved. Based on the simulation outputs, the mechanisms of the MJO-related SSS variability are further explored by conducting a salinity budget analysis over the mixed layer. The analysis indicates a strong spatial variation in physical processes that dominate the local SSS variability. For example, while the role of surface fluxes dominates in the western Indian basin, oceanic advection plays an important role in the eastern Indian and western Pacific oceans (Fig. 1).
2) An OSSE study for multiple time scale variability: The role of TAO/TRITON vs. Argo.
A series of OSSEs are conducted based on an ocean data assimilation system that is under development at the Joint Center for Satellite Data Assimilation (JCSDA) and the Environmental Modeling Center (EMC)/National Centers for Environmental Prediction (NCEP). The experiments explored the efficacy of TAO/TRITON and Argo observations in TPOS about representing the multiple time scale ocean variability. Diagnostics of the experiments suggest that (1) both TAO/TRITON and especially Argo effectively improve the estimation of mean states and low-frequency (Fig. 2) variations; (2) on the intraseasonal time scale (Fig. 3), Argo has more significant improvements than TAO/TRITON (except for regions close to TAO/TRITON sites); (3) on the high-frequency time scale (Fig. 4), both TAO/TRITON and Argo have evident deficits (although for TAO/TRITON, limited improvements were present close to TAO/TRITON sites).
Lessons Learned
1. Model simulations suggest a strong regional dependency about the role of E-P flux vs. ocean dynamics in the intraseasonal SSS anomalies.
2. OSSE studies suggest the present observational network is inadequate for resolving high frequency variability on a basin wide.
3. TPOS requires higher frequency observations with a basin coverage
Publications
Zhu, J., G. Vernieres, T. Sluka, S. Flampouris, A. Kumar, A. Mehra, M. Cronin, D. Zhang, S. Wills, J. Wang, and W. Wang, 2021: Roles of TAO/TRITON and Argo in tropical Pacific observing system: An OSSE study for multiple time scale variability. (under revision).
Zhu, J., A. Kumar, and W. Wang, 2020: Intraseasonal surface salinity variability and the MJO in a climate model. Geophys. Res. Lett., 47, e2020GL088997. DOI: 10.1029/2020GL088997.
Data
All the model data are archived at NOAA supercomputer Gaea and is available upon request.
Figure 1. Composite MJO lifecycle of upper ocean salinity budget terms in CFSm501 for (a) the western Indian Ocean (57.5-67.5ºE, 5ºS-5ºN), (b) the central Indian Ocean (70-80ºE, 5ºS-5ºN), (c) the eastern Indian Ocean (82.5-92.5ºE, 5ºS-5ºN), and (d) the western Pacific Ocean (155-165ºE, 5ºS-5ºN). Salinity (Sa)_tendency (black), EmP (red), ADVz (green), ADVm (blue), ENT (magenta) and ShCON (aqua) respectively stand for budget terms related to tendency, E-P, zonal advection, meridional advection, vertical entrainment, and stratified shear flow convergence. See Zhu et al. (2020) for more details.
Figure 2. Root mean square differences (RMSD) of low-frequency (a-d) SST (unit: °C) and (e-h) SSS (unit: psu) with respect to Nature Run in (a, e) noDA, (b, f) crtTAO, (c, g) Argo and (d, h) crtTAO+Argo. The green squares in (b, d, f, h) and the small blue dots in (c, d, g, h) indicate where TAO/TRITON buoys and Argo floats are located, respectively..
Figure 3. As in Fig. 2, but for the intraseasonal component.
Figure 4. As in Fig. 2, but for the high-frequency component.