ALBERT

Description: Following the idea that analysis of in-situ information in the salt budget could be used as a surrogate for global “ocean rain gauge”, the annual mean oceanic net freshwater flux (E-P) was estimated from the Argo profiles and the wind stress data on a global scale. The comparison between the independent E-P estimation from Argo and the E-P product sets, including the combination of precipitation from TRMM, GPCP, CMAP and evaporation from OAFlux, GSSTF3 and IFREMER and E-P set from NEWS formed from satellite, generally show similar spatial patterns, particularly on the larg scale. However, there are differences among the different satellite-based E-P estimates and between satellite estimates and independent in-situ estimates. Based on the pattern correlation and the RMSD, the evaporation and precipitation from OAFlux and TRMM agrees best with the E-P estimated from the independent Argo-based estimates.

Description: In this paper, we assess the impact of sea surface salinity (SSS) observations on seasonal variability of tropical dynamics as well as on dynamical El Niño–Southern Oscillation (ENSO) forecasts using a hybrid coupled model (HCM). The HCM is composed of a primitive equation ocean model coupled with a singular value decomposition–based statistical atmospheric model. An Ensemble Reduced Order Kalman Filter (EROKF) is used to assimilate observations to constrain tropical Pacific dynamics and thermodynamics for initialization of the HCM. Rather than trying to produce the best possible operational forecasts, point-wise subsurface temperature (sTz) has been assimilated separately and together with gridded observed sea surface salinity (SSS) from optimal interpolation to more efficiently isolate the impact of SSS. Coupled experiments are then initiated from these EROKF initial conditions and run for 12 months for each month, 1993–2007. The results show that adding SSS to sTz assimilation improves coupled forecasts for 6–12 month lead times. The main benefit of SSS assimilation comes from improvement to the spring predictability barrier (SPB) period. SSS assimilation increases correlation for 6–12 month forecasts by 0.2–0.5 and reduces RMS error by 0.3°C–0.6°C for forecasts initiated between December and March, a period key to long-lead ENSO forecasts. The positive impact of SSS assimilation originates from warm pool and Southern Hemisphere salinity anomalies. Improvements are brought about by fresh anomalies at the equator which increases stability, reduces mixing, and shoals the thermocline which concentrates the wind impact of ENSO coupling. This effect is most pronounced in June–August, helping to explain the improvement in the SPB. In addition, we show that SSS impact on coupled forecasts is more pronounced for the period 1993–2001 than for the period 2002–2007 due to the improved inherent predictability associated with the strong 1997–1998 ENSO. Rather than being the final say for the issue of SSS assimilation, this study should be considered as a necessary first step. Future work is still required to assess issues such as SSS satellite data coverage and the complementary nature of satellite/in situ assimilation. However, these results foreshadow the important positive potential impact that gridded satellite SSS provided by missions such as SMOS and Aquarius/SAC-D will have on coupled model predictions.

Description: Abstract This study demonstrates the positive impact of including gridded Aquarius and SMAP sea surface salinity (SSS) into initialization of intermediate complexity coupled model forecasts for the tropical Indo‐Pacific. An experiment that assimilates conventional ocean observations serves as the control. In a separate experiment, Aquarius and SMAP satellite SSS are additionally assimilated into the coupled model initialization. Analysis of the initialization differences with the control indicates that SSS assimilation causes a freshening and shallowing of the mixed layer depth (MLD) near the equator and enhanced Kelvin wave amplitude. For each month from September 2011 to September 2017, 12 month coupled ENSO forecasts are initialized from both the control and satellite SSS assimilation experiments. The experiment assimilating Aquarius and SMAP SSS significantly outperforms the control relative to observed NINO3.4 sea surface temperature anomalies. This work highlights the potential importance of inclusion of satellite SSS for improving the initialization of operational ENSO coupled forecasts.

Description: We investigate the impact of El Niño - Southern Oscillation (ENSO) on surface radiative fluxes over the tropical Pacific using satellite observations and fluxes derived from selected atmospheric re-analyses. Agreement between the two in this region is important because re-analysis information is frequently used to assess surface energy budget sensitivity to ENSO. We found that during the traditional ENSO, the maximum variance of anomalous incoming solar radiation is located just west of the dateline and coincides with the area of largest anomalous SST gradient. It can reach up to ∼60 W/m 2 and lags behind the Niño3 index by about a month, suggesting a response to anomalous SST gradient. The magnitude of longwave anomaly is only half that large, and varies in phase with the SST anomaly. Similar anomalies were derived from outputs: from the European Centre for Medium-Weather Forecasts Reanalysis Interim (ERA-I), from the Modern Era Retrospective Analysis version 2 (MERRA-2), from the NCEP/NCAR Re-analysis 1 (R1), and from the Japanese JRA55 re-analysis. Among the four re-analyses used, results from ERA-I are the closest to observations. We have also investigated the surface wind divergence/convergence and found that the main factor limiting eastward excursions of convection is the surface wind convergence. Due to the wind divergence pattern normally present over the eastern cold tongue, anomalous convection extends into the eastern equatorial Pacific only during the strongest warm events. Our analysis also considers the El Niño Modoki events, for which the radiation flux patterns are shifted westward following the SST pattern.

Description: Indian Ocean (IO) dynamics impact ENSO predictability by influencing wind and precipitation anomalies in the Pacific. To test if the upstream influence of the IO improves ENSO validation statistics, a combination of forced ocean, atmosphere, and coupled models are utilized. In one experiment, the full tropical Indo-Pacific region atmosphere is forced by observed interannual SST anomalies. In the other, the IO is forced by climatological SST. Differences between these two forced atmospheric model experiments spotlight a much richer wind response pattern in the Pacific than previous studies that used idealized forcing and simple linear atmospheric models. Weak westerlies are found near the equator similar to earlier literature. However, at initialization strong easterlies between 30°S to 10°S and 0°N to 25°N and equatorial convergence of the meridional winds across the entire Pacific are unique findings from this paper. The large-scale equatorial divergence west of the dateline and northeasterly-to-northwesterly cross-equatorial flow converging on the equator east of the dateline in the Pacific are generated from interannual IO SST coupling. In addition, off-equatorial downwelling curl impacts large-scale oceanic waves (i.e. Rossby waves reflect as western boundary Kelvin waves). After 3 months, these downwelling equatorial Kelvin waves propagate across the Pacific and strengthen the NINO3 SST. Eventually Bjerknes feedbacks take hold in the eastern Pacific which allows this warm anomaly to grow. Coupled forecasts for NINO3 SST anomalies for 1993-2014 demonstrate that including interannual IO forcing significantly improves predictions for 3-9 month lead times. This article is protected by copyright. All rights reserved.

Description: This study demonstrates the impact of gridded in situ and Aquarius sea surface salinity (SSS) on coupled forecasts for August 2011 until February 2014. Assimilation of all available subsurface temperature (ASSIM_T z ) is chosen as the baseline and an optimal interpolation of all in situ salinity (ASSIM_T z _SSS IS ) and Aquarius SSS (ASSIM_T z _SSS AQ ) are added in separate assimilation experiments. These three are then used to initialize coupled experiments. Including SSS generally improves NINO3 sea surface temperature anomaly validation. For ASSIM_T z _SSS IS , correlation is improved after 7 months, but the root mean square error is degraded with respect to ASSIM_T z after 5 months. On the other hand, assimilating Aquarius gives significant improvement versus ASSIM_T z for all forecast lead times after 5 months. Analysis of the initialization differences with the baseline indicates that SSS assimilation results in an upwelling Rossby wave near the dateline. In the coupled model, this upwelling signal reflects at the western boundary eventually cooling the NINO3 region. For this period, coupled models tend to erroneously predict NINO3 warming so SSS assimilation corrects this defect. Aquarius is more efficient at cooling the NINO3 region since it is relatively more salty in the eastern Pacific than in situ SSS which leads to increased mixing and upwelling which in turn sets up enhanced west to east SST gradient and intensified Bjerknes coupling. A final experiment that uses subsampled Aquarius at in situ locations infers that high-density spatial sampling of Aquarius is the reason for the superior performance of Aquarius versus in situ SSS.