Advances in L-band microwave satellite radiometry in the past decade, pioneered by ESA's SMOS and NASA's Aquarius and SMAP missions, have demonstrated an unprecedented capability to observe global ...sea surface salinity (SSS) from space. Measurements from these missions are the only means to probe the very-near surface salinity (top cm), providing a unique monitoring capability for the interfacial exchanges of water between the atmosphere and the upper-ocean, and delivering a wealth of information on various salinity processes in the ocean, linkages with the climate and water cycle, including land-sea connections, and providing constraints for ocean prediction models. The satellite SSS data are complimentary to the existing in situ systems such as Argo that provide accurate depiction of large-scale salinity variability in the open ocean but under-sample mesoscale variability, coastal oceans and marginal seas, and energetic regions such as boundary currents and fronts. In particular, salinity remote sensing has proven valuable to systematically monitor the open oceans as well as coastal regions up to approximately 40 km from the coasts. This is critical to addressing societally relevant topics, such as land-sea linkages, coastal-open ocean exchanges, research in the carbon cycle, near-surface mixing, and air-sea exchange of gas and mass. In this paper, we provide a community perspective on the major achievements of satellite SSS for the aforementioned topics, the unique capability of satellite salinity observing system and its complementarity with other platforms, uncertainty characteristics of satellite SSS, and measurement versus sampling errors in relation to in situ salinity measurements. We also discuss the need for technological innovations to improve the accuracy, resolution, and coverage of satellite SSS, and the way forward to both continue and enhance salinity remote sensing as part of the integrated Earth Observing System in order to address societal needs.
The equatorial Pacific and Atlantic Oceans release significant amount of CO2 each year. Not much attention has been paid to evaluating the similarities and differences between these two basins in ...terms of temporal variability. Here we employ a basin‐scale, fully coupled physical‐biogeochemical model to study the spatial and temporal variations in sea surface pCO2 and air‐sea CO2 flux over the period of 1984–2013 in the equatorial Pacific and Atlantic Oceans. The model reproduces the overall spatial and temporal variations in the carbon fields for both basins, including higher values to the south of the equator than to the north, the annual maximum sea surface pCO2 in boreal spring, and the annual peak in sea‐to‐air CO2 flux in boreal fall in the upwelling regions. The equatorial Pacific reveals a large interannual variability in sea surface pCO2, which is associated with the El Niño–Southern Oscillation. As a contrast, there is a strong seasonality but little interannual variability in the carbon fields of the equatorial Atlantic. The former is driven by the variability of dissolved inorganic carbon but the latter by sea surface temperature. Our model estimates an average sea‐to‐air CO2 flux of 0.521 ± 0.204 Pg C yr−1 for the tropical Pacific (18°S–18°N, 150°E–90°W), which is in good agreement with the observation‐based estimate (0.51 ± 0.24 Pg C yr−1). On average, sea‐to‐air CO2 flux is 0.214 ± 0.03 Pg C yr−1 in the tropical Atlantic (10°S–10°N), which compares favorably with observational estimates.
Key Points
Model reproduces the magnitudes and spatial‐temporal patterns of carbon fields
ENSO has significant impacts on the Pacific but not on the Atlantic
The Pacific is a DIC‐driven system, but the Atlantic is an SST‐driven system
The Global Modeling and Assimilation Office (GMAO) has recently released a new version of the Goddard Earth Observing System (GEOS) Subseasonal to Seasonal prediction (S2S) system, GEOS‐S2S‐2, that ...represents a substantial improvement in performance and infrastructure over the previous system. The system is described here in detail, and results are presented from forecasts, climate equillibrium simulations, and data assimilation experiments. The climate or equillibrium state of the atmosphere and ocean showed a substantial reduction in bias relative to GEOS‐S2S‐1. The GEOS‐S2S‐2 coupled reanalysis also showed substantial improvements, attributed to the assimilation of along‐track absolute dynamic topography. The forecast skill on subseasonal scales showed a much improved prediction of the Madden‐Julian Oscillation in GEOS‐S2S‐2, and on a seasonal scale the tropical Pacific forecasts show substantial improvement in the east and comparable skill to GEOS‐S2S‐1 in the central Pacific. GEOS‐S2S‐2 anomaly correlations of both land surface temperature and precipitation were comparable to GEOS‐S2S‐1 and showed substantially reduced root‐mean‐square error of surface temperature. The remaining issues described here are being addressed in the development of GEOS‐S2S Version 3, and with that system GMAO will continue its tradition of maintaining a state‐of‐the‐art seasonal prediction system for use in evaluating the impact on seasonal and decadal forecasts of assimilating newly available satellite observations, as well as evaluating additional sources of predictability in the Earth system through the expanded coupling of the Earth system model and assimilation components.
Key Points
GMAO's New Seasonal Prediction Model and Assimilation shows substantial improvement in forecast skill over the previous version
This study demonstrates the positive impact of including gridded Aquarius and SMAP sea surface salinity (SSS) into initialization of coupled 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 control 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 2018, 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 importance of inclusion of satellite SSS for improving the initialization ENSO coupled forecasts.
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.
Key Points
SSS assimilation improves coupled forecasts
Due to better specification of BLT and MLD
SPCZ and western Pacific SSS most important
El Niño‐Southern Oscillation (ENSO) properties can be modulated by many factors; most previous studies have focused on physical aspects of the climate system in the tropical Pacific. Ocean ...biology‐induced feedback (OBF) onto physics and bio‐climate coupling have been the subject of much recent interest, revealing striking model dependence and even conflicting results. Current satellite data are able to resolve the space‐time structure of oceanic signals both in biology and physics, providing an opportunity for quantifying their relationships. Here we use the biological signature from satellite ocean color data to estimate interannual variability of the attenuation depth of solar radiation (Hp), a field linking ocean biology and physics. We then apply a singular value decomposition (SVD) analysis to interannual Hp and sea surface temperature (SST) anomaly fields to derive an empirical Hp model which is incorporated in a hybrid coupled ocean‐atmosphere model of the tropical Pacific to represent the OBF. It is shown that the OBF can have significant effects on ENSO behaviors, including its amplitude, oscillation periods and seasonal phase locking.
El Niño/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would have great societal benefit. However, one key variable that has yet to be ...fully exploited within coupled forecast systems is accurate estimation of near-surface ocean salinity. Satellite sea surface salinity (SSS), combined with temperature, help to improve the estimates of ocean density changes and associated near-surface mixing. For the first time, we assess the impact of satellite SSS observations for improving near-surface dynamics within ocean reanalyses and how these initializations impact dynamical ENSO forecasts using NASA’s coupled forecast system (GEOS-S2S-2). For all initialization experiments, all available sea level and in situ temperature and salinity observations are assimilated. Separate observing system experiments (OSE) additionally assimilate Aquarius, and SMAP, SMOS, and these datasets combined. We highlight the impact of satellite SSS on ocean reanalyses by comparing experiments with and without the application of SSS assimilation. Next, we compare case studies of coupled forecasts for the big 2015 El Niño, the 2017 La Niña, and the weak El Niño in 2018 that are initialized from GEOS-S2S-2 spring reanalyses that assimilate and withhold along-track SSS. For each of these ENSO-event case studies, assimilation of satellite SSS improves the forecast validation with respect to observed NINO3.4 anomalies (or at least reduces the forecast uncertainty). Satellite SSS assimilation improved characterization of the mixed layer depth leading to more accurate coupled air/sea interaction and better forecasts. These results further underline the value of satellite SSS assimilation into operational forecast systems.
In this paper, a series of observing system simulation experiments (OSSEs) are used to study the design of a proposed array of instrumented moorings in the Indian Ocean (IO) outlined by the IO panel ...of the Climate Variability and Predictability (CLIVAR) Project. Fields of the Ocean Topography Experiment (TOPEX)/Poseidon (T/P) and Jason sea surface height (SSH) and sea surface temperature (SST) are subsampled to simulate dynamic height and SST data from the proposed array. Two different reduced-order versions of the Kalman filter are used to reconstruct the original fields from the simulated observations with the objective of determining the optimal deployment of moored platforms and to address the issue of redundancy and array simplification. The experiments indicate that, in terms of the reconstruction of SSH and SST, the location of the subjectively proposed array compareS favorably with the optimally defined one. The only significant difference between the proposed IO array and the optimal array is the lack of justification for increasing the latitudinal resolution near the equator (i.e., moorings 1.5°S and 1.5°N). An analysis of the redundancy also identifies the equatorial region as the one with the largest amount of redundant information. Thus, in the context of these fields, these results may help define the prioritization of its deployment or redefine the array to extend its latitudinal extent while maintaining the same amount of stations.
The intensity of the 1997 El Niño and the 8°C sudden drop in sea surface temperature (SST) around 0°–130°W during the turn into La Niña in 1998 were a surprise to the scientific community. This ...succession of warm and cold events was observed from start to finish with a comprehensive set of remotely sensed and in situ observations. In this study we employ space‐based observations to demonstrate, for the first time, their maturity in capturing the preconditioning, onset, evolution, and decay of the 1997 El Niño and its transition into the 1998 La Niña. An accumulation of warm water in the west and equatorial wave reflection on the western ocean boundary appeared favorable for the development of El Niño. However, the action of a series of westerly wind bursts from December 1996 to June 1997, notably in March 1997, was instrumental in setting up this huge El Niño. The westerly wind bursts excited equatorial downwelling Kelvin waves and advected the eastern edge of the warm pool eastward, which triggered a distinct warming over the central and eastern parts of the equatorial basin. Once these warmed regions joined, the coupling between the SST and surface winds was fully effective, and El Niño reached its mature phase. By that time much of the warm waters of the western equatorial Pacific was transferred toward the east by surface eastward currents. The demise of El Niño and its turn into La Niña in spring 1998 were due to the arrival in the east of various interrelated phenomena. Upwelling was brought from the west by favorable off‐equatorial wind stress curl and equatorial Kelvin waves generated by easterly winds and wave reflection on the western ocean boundary. Additional upwelling was brought from the east by equatorial Rossby waves generated by westerly winds. These various upwelling signals were added to the general uplifting of the thermocline because of the slow discharge of the upper layer of the equatorial basin by diverging surface currents. A series of equatorial Kelvin and Rossby waves, characterized by upwelling and opposite surface currents, led to the breakup of the warm waters, the surfacing of the thermocline, and the drastic drop in SST in May 1998 around 0°–130°W. With the arrival of cold water in the east the easterly winds expanded from the west, and La Niña turned into a growing mode. This view of the 1997–1998 El Niño–La Niña, afforded from space, enables the testing of various El Niño theories.
Predictions of the 1997–1998 El Niño exhibited a wide range of forecast skill that were dependent, in part, on the wind‐driven initial conditions for the ocean. In this study the results of a reduced ...gravity, primitive equation, sigma coordinate ocean general circulation model are compared and contrasted when forced by several different wind products for the 1997–1998 El Niño/La Niña. The different wind products include atmospheric model winds, satellite wind products, and a subjective analysis of ship and in situ winds. The model results are verified against fields of observed sea level anomalies from TOPEX/Poseidon data, sea surface temperature analyses, and subsurface temperature from the Tropical Atmosphere‐Ocean buoy array. Depending on which validation data type one chooses, different wind products provide the best forcing fields for simulating the observed signal. In general, the model results forced by satellite winds provide the best simulations of the spatial and temporal signal of the observed sea level. This is due to the accuracy of the meridional gradient of the zonal wind stress component that these products provide. Differences in wind forcing also affect subsurface dynamics and thermodynamics. For example, the wind products with the weakest magnitude best reproduce the sea surface temperature (SST) signal in the eastern Pacific. For these products the mixed layer is shallower, and the thermocline is closer to the surface. For such simulations the subsurface thermocline variability influences the variation in SST more than in reality. The products with the greatest wind magnitude have a strong cold bias of >1.5°C in the eastern Pacific because of increased mixing. The satellite winds along with the analysis winds correctly reproduce the depth of the thermocline and the general subsurface temperature structure.
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