December 12-16, 2016
San Francisco, CA USAhttps://fallmeeting.agu.org/2016/
A collection of presentations and poster abstracts from the American Geophysical Union Fall Meeting, held in San Francisco, California on December 12-16. Presentations and posters in ocean science sessions, including "Ocean Salinity, Water Cycle Variability, and Science Results from Satellite Measurements" are featured.Agenda
Documents: 35Fournier, S., Reager, J.T., Lee, T., Vazquez, J., David, C.H., Gierach, M.M.
[16-Dec-16]. Floods are natural hazards that can have damaging impacts not only on affected land areas but also on the adjacent coastal waters. NASAâs Soil Moisture Active Passive (SMAP) mission provides measurements of both surface soil moisture and sea surface salinity (SSS), offering the opportunity to study the effects of flooding events on both terrestrial and marine environments. Here, we present analysis of a severe flood that occurred in May 2015 in Texas using SMAP observations and ancillary satellite and in situ data that describe the precipitation intensity, the evolving saturation state of the land surface, the flood discharge peak, and the resulting freshwater plume in the Gulf of Mexico. Melnichenko, O., Hacker, P.W., Wentz, F.J., Meissner, T., Maximenko, N.A., and Potemra, J.T.
[07-Nov-17]. To address the need for a consistent, continuous, long-term, high-resolution sea surface salinity (SSS) dataset for ocean research and applications, a trial SSS analysis is produced in the eastern tropical Pacific from multi-satellite observations. The new SSS data record is a synergy of data from two satellite missions. The beginning segment, covering the period from September 2011 to June 2015, utilizes Aquarius SSS data and is based on the optimum interpolation analysis developed at the University of Hawaii. The analysis is produced on a 0.25-degree grid and uses a dedicated bias-correction algorithm to correct the satellite retrievals for large-scale biases with respect to in-situ data. Asher, W., Thompson, E.J., Drushka, K., Jessup, A.T., and Schanze, J.J.
[16-Dec-16]. Salinity stratification in the ocean due to rain affects the spatial and temporal variability of heat, salinity, and momentum in the near-surface layer of the ocean. However, the relative importance of rain in driving surface variability of the ocean is not fully understood because routine observations have not been able to quantify either the spatio-temporal variability of rain or the response of the underlying ocean to rain. Relatively high resolution (10 km, 30 min) NASA GPM IMERG rain rate data, now available over much of the globe, can be used with in situ measurements of temperature and salinity in the upper few meters of the ocean to understand how rainfall patterns over scales of tens to hundreds of kilometers are related to spatial variability in the ocean. In this study, local and integrated upstream satellite-derived rain accumulation are compared to the horizontal variability of vertical gradients of temperature and salinity measured between the surface, 2 m, 3 m, and 5 m during the 2016 SPURS-2 experiment in the eastern Pacific Ocean. Susanto, R.D., Setiawan, A., Zheng, Q., Sulistyo, B., Adi, T.R., Agustiadi, T., Treggono, M., Triyono, T., and Kuswardani, A.
[16-Dec-16]. The seasonal variability of a full lifetime of Aquarius sea surface salinity time series from August 25, 2011 to June 7, 2015 is compared to salinity time series obtained from in situ observations in the Karimata Strait. The Karimata Strait plays dual roles in water exchange between the Pacific and the Indian Ocean. The salinity in the Karimata Strait is strongly affected by seasonal monsoon winds. During the boreal winter monsoon, northwesterly winds draws low salinity water from the South China Sea into the Java Sea and at the same time, the Java Sea receives an influx of the Indian Ocean water via the Sunda Strait. Lee, T.
[16-Dec-16]. Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatio-temporal scales are important to applications, capability assessment, and future mission design. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in October 2015) with two widely used Argo monthly gridded near-surface salinity products. Vinogradova, N.T. and Ponte, R.M.
[16-Dec-16]. To understand the ongoing alteration of the Earthâs water budget, it is essential to assess the variability of its oceanic constituent as this component supplies more than 75% of the evaporated and precipitated water in the global water cycle. Here we examine the change in the ocean water cycle and the ocean's response to such changes over the contemporary, well-observed period spanning the last two decades. In particular, we focus on recent changes in surface salinity and fluxes of freshwater within the atmosphere-ocean-land-ice system. Subrahmanyam, B. and Melzer, B.A.
[16-Dec-16]. Global salinity data from Simple Ocean Data Assimilation (SODA) reanalysis highlights surface and subsurface ocean salinity trends in evaporative-dominated subtropical gyre systems over the period of 1950â2010. The SODA reanalysis provides an assimilated view of interannual and decadal salinity variability in the oceans. Subtropical sea surface salinity trends over the past six decades were analyzed, as salinity can be a potential diagnostic of the acceleration pattern of the global water cycle. Our results indicate an increase in salinity within subtropical gyre systems, although our trend is more conservative than previous estimates. Poague, J. and Stine, A.
[16-Dec-16]. Global warming is expected to intensify the global hydrological cycle, but significant regional differences exist in the predicted response. The proposed zonal mean thermodynamic response is enhanced horizontal moisture transport associated with increased saturation vapor pressure, which in turn drives additional net precipitation in the tropics and at high latitudes and additional net evaporation in the subtropics. Sea surface salinity (SSS) anomalies are forced from above by changes in evaporation minus precipitation (E-P) and thus will respond to changes in the global hydrological cycle, opening the possibility of using historical SSS anomalies to diagnose the response of the hydrological cycle to warming. Ferster, B.S. and Subrahmanyam, B.
[16-Dec-16]. Since the 20th century, the Antarctic climate has been changing and relatively unstable. The Southern Ocean plays a major role in global ocean circulation. Because the Southern Ocean around Antarctica is the only location where the ocean can circulate freely all the way around the globe without continental barriers, it's a huge part of the ocean cycle. The use of salinity remote sensing technology offers spatial and temporal salinity observations than insitu and other conventional observations to better represent the sea surface salinity (SSS) in the Southern Ocean (SO). Using data sets from NASAâs Aquarius/SAC-D and ESAâs Soil Moisture and Ocean Salinity (SMOS), and NASAâs Soil Moisture Active and Passive (SMAP) we have estimated fresh and salt water fluxes. Yu, L.
[16-Dec-16]. Studies of recent years have led to an increasing recognition that the evaporation-minus-precipitation (E-P) flux and SSS are not directly linked but through oceanic processes. Two fundamental characteristics define the complex relationship between SSS and E-P. First, E-P is a mass flux and does not stay locally. For instance, when rain adds to the mass of the water column, it causes a pressure perturbation and fast oceanic responses in terms of gravity waves and barotropic Rossby waves. Secondly, E-P does not have a feedback relationship with SSS. This is in stark contrast to the surface heat flux which serves as both forcing and damping mechanisms for SST. E-P forces SSS anomalies but does not dampen them. As a consequence, SSS anomalies tend to be carried out by oceanic processes and circulate around for a period of time. Here we present the analysis of the ocean dynamical control on E-P generated SSS anomalies in two contrasting regimes. Liu, T. and Schmitt, R.W.
[16-Dec-16]. Moisture transport from the excess of evaporation over precipitation in the global ocean drives terrestrial precipitation patterns. Sea surface salinity (SSS) is sensitive to changes in ocean evaporation and precipitation, and therefore, to changes in the global water cycle. We use the Met Office Hadley Centre EN4.2.0 SSS dataset to search for teleconnections between autumn-lead seasonal salinity signals and winter precipitation over the western United States. Chao, Y., Leiva, J., Farrara, J.D., Zhang, H.
[16-Dec-16]. A real-time California coastal ocean nowcast and forecast system is used to quantify the impact of river discharge on the California coastal ocean circulation and variability. River discharge and freshwater runoff is monitored by an extensive network of stream gages maintained through the U.S. Geological Survey, that offers archived stream flow records as well as real-time datasets. Of all the rivers monitored by the USGS, 25 empty into the Pacific Ocean and contribute a potential source of runoff data. Monthly averages for the current water year yield discharge estimates as high as 6,000 cubic meters per second of additional freshwater input into our present model. Kido, S. and Tozuka, T.
[16-Dec-16]. Sea surface salinity (SSS) in the tropical Indian Ocean undergoes large interannual variations associated with the Indian Ocean Dipole (IOD), but their impacts on the upper-ocean stratification and sea surface temperature (SST) are not fully understood. Here, using a 1-D turbulence closure model, a series of sensitivity experiments with and without salinity anomalies is carried out to quantify their impacts during positive IOD events. Lagerloef, G.S.E.
[16-Dec-16]. To improve knowledge of the ocean surface salinity annual cycle, and its link to global precipitation patterns, remains a key science measurement objective for satellites. The Aquarius satellite data are applied here to address this, and the analysis is not as straightforward as it may seem. Sensor calibration is considered carefully to ensure that seasonality in external calibration data sources do not alias the satellite measurements. For example, quasi-monthly calibration error signals were identified early in the Aquarius mission. Hasson, A.E.A., Boutin, J., Bingham, F., Lee, T., Farrar, J.T., Supply, A., Puy, M., Morrow, R., and Reverdin, G.P.
[16-Dec-16]. Sea Surface Salinity (SSS) is one of the key factors influencing the ocean circulation but is also an important indicator of the hydrologic cycle. Understanding processes associated with various SSS regimes is thus crucial to the knowledge of ocean dynamics and of the connection between the ocean and the water cycle. SSS variability is studied between 2010 and mid-2016 in the tropical Pacific Ocean using various datasets such as observations from the satellite missions Soil Moisture Ocean Salinity (SMOS) and Aquarius SAC/D; in situ measurements from Argo, voluntary ships and dedicated campaigns; and a forced simulation of the Nemo ocean model. Grodsky, S. and Carton, J.
[16-Dec-16]. The leading mode of the Aquarius monthly anomalous sea surface salinity (SSS) is evaluated within the 50S-50N belt, where SSS retrieval accuracy is higher. This mode accounts for about 18% of the variance and resembles a pattern of the ENSO-induced anomalous rainfall. The leading mode of SSS variability deducted from a longer JAMSTEC analysis also accounts for about 17% of the variance and has very similar spatial pattern and almost a perfect correspondence of its temporal principal component to the SOI index. In that sense, the Aquarius SSS variability at low and middle latitudes is representative of SSS variability that may be obtained from longer records. Reagan, J.R., Seidov, D., Boyer, T., Zweng, M.
[16-Dec-16]. Multiple studies have shown that since the mid-20th century near-surface salinity patterns have amplified, with fresh regions becoming fresher and salty regions becoming saltier. This pattern amplification is directly related to an amplification of the global hydrological cycle, with wet regions becoming wetter and dry regions becoming dryer. An amplified hydrological cycle could cause an increase in the number of extreme weather events, with more severe floods and droughts. However, it could also lead to additional freshwater fluxes over the deep water formation regions in the northern North Atlantic which can slow down the Atlantic Meridional Overturning Circulation. With historically unreliable global evaporation and precipitation data, salinity is the main source for tracking changes in the hydrological cycle. Köhler, J., Stammer, D., Serra, N., and Bryan, F.
[16-Dec-16]. Space-borne salinity data in the Indian Ocean are analyzed over the period 2000-2015 based on data from the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautical Space Agency's Aquarius/SAC-D missions. The seasonal variability is the dominant mode of sea surface salinity (SSS) variability in the Indian Ocean, accounting for more than 50% of salinity variance. Through a combined analysis of the satellite and ARGO data, dominant forcing terms for seasonal salinity changes are identified. It is found, that E-P controls seasonal salinity tendency in the western Indian Ocean, where the ITCZ has a strong seasonal cycle. Martins, M.S. and Stammer, D.
[16-Dec-16]. The salinity budget of the upper tropical Pacific Ocean underneath the double Intertropical Convergence Zone (ITCZ) is studied using the Soil Moisture and Ocean Salinity (SMOS) and Aquarius surface salinity observations as well as in situ salinity measurements. Delcroix, T.C., Soviadan, D., Chaigneau, A., and Boutn, J.
[16-Dec-16]. High-resolution ocean model results as well as few sporadic observations collected in different regions indicate that mesoscale eddies imprint distinguishable changes on collocated Sea Surface Salinity (SSS) and/or precipitation (P) distribution. This presentation shows this is indeed the case for the tropical Pacific, by collocating 6 years (2010â2016) of SMOS-derived SSS, TRMM-derived P and AVISO-derived sea level anomalies. The main characteristics of mesoscale eddies are first analyzed in sea-level altimetry maps, and their signature is then determined using concomitant satellite-derived SSS and P data. Jones, L., Jacob, M.M., Asher, W., Drushka, K., and Santos-Garcia, A.
[16-Dec-16]. Rainfall over oceans produces a layer of fresher surface water, which can have a significant effect on the exchanges between the surface and the bulk mixed layer and also on satellite/in-situ comparisons. For satellite sea surface salinity (SSS) measurements, the standard is the Hybrid Coordinate Ocean Model (HYCOM), but there is a significant difference between the remote sensing sampling depth of ~ 0.01 m and the typical range of 5-10 m of in-situ instruments. Under normal conditions the upper layer of the ocean is well mixed and there is uniform salinity; however, under rainy conditions, there is a dilution of the near-surface salinity that mixes downward by diffusion and by mechanical mixing (gravity waves/wind speed). This significantly modifies the salinity gradient in the upper 1-2 m of the ocean, but these transient salinity stratifications dissipate in a few hours, and the upper layer becomes well mixed at a slightly fresher salinity. Thompson, E.J., Asher, W., Drushka, K., Schanze, J., Jessup, A.T., and Clark, D.
[16-Dec-16]. Although in situ observations have shown that fresh lenses are common in the presence of rain, attempts to correlate the magnitude and lifetime of the surface freshening with rain rate using field data have not produced a definitive relationship. The reasons for this are most likely that in situ rain rate measurements represent the freshwater flux to the ocean surface at a single point in space and time, whereas the fresh lens is the result of the integrated rainfall over time and space, convoluted with the evolution of the fresh lens. Therefore, it is possible that integrated, upstream rainfall estimates might provide a better correlate for the presence of fresh lenses than in situ measurements at a point. This hindcast study seeks to determine the utility of NASA GPM IMERG satellite measurements of rain relative to in situ collocated rain measurements in predicting the occurrence and duration of 0-1 m freshwater stabilization of the ocean. Schmitt, R.W., Li, L., and Liu, T.
[16-Dec-16]. We have discovered that sea surface salinity (SSS) is a better seasonal predictor of terrestrial rainfall than sea surface temperature (SST) or the usual pressure modes of atmospheric variability. In many regions, a 3-6 month lead of SSS over rainfall on land can be seen. While some lead is guaranteed due to the simple conservation of water and salt, the robust seasonal lead for SSS in some places is truly remarkable, often besting traditional SST and pressure predictors by a very significant margin. One mechanism for the lead has been identified in the recycling of water on land through soil moisture in regional ocean to land moisture transfers. However, a global search has yielded surprising long-range SSS-rainfall teleconnections. It is suggested that these teleconnections indicate a marked sensitivity of the atmosphere to where rain falls on the ocean. Meissner, T. and Wentz, F.J.
[16-Dec-16]. Our presentation discusses the latest improvements in the salinity retrievals for both Aquarius and SMAP since the last releases. The Aquarius V4.0 was released in June 2015 and the SMAP V 1.0 was released in November 2015. Upcoming releases are planned for SMAP (V 2.0) in August 2016 and for Aquarius (V 5.0) late 2017. Yueh, S.H., Fore, A., Tang, W., and Hayashi, A.
[16-Dec-16]. NASAâs Soil Moisture Active Passive (SMAP) mission was launched in January 2015 to provide global mapping of soil moisture. SMAP has two instruments, a polarimetric radiometer and a multi-polarization synthetic aperture radar. The radar stopped operation on 7 July 2015. Both instruments operate at L-band frequencies and share a single 6-m rotating mesh antenna, producing a fixed incidence angle conical scan at 40â° across a 1000-km swath. We have analyzed all available SMAP and Aquarius data to improve the geophysical model functions, relating the L-band radar and radiometer data to ocean surface wind speed, wind direction, significant wave height and sea surface temperature. Potemra, J.T., Hacker, P.W.. Melnichenko, O., and Maximenko, N.A.
[16-Dec-16]. The straits in Indonesia allow for low-latitude exchange of water between the Pacific and Indian Oceans. Collectively known as the Indonesian Throughflow (ITF), this exchange is thought to occur primarily via the Makassar Strait and downstream via the Lombok Strait, Ombai Strait and Timor Passage. The Sunda Strait, between the islands of Sumatra and Java, is a very narrow (~10 km) and shallow (~20m) gap, but it connects the Java Sea directly to the Indian Ocean. Ruiz-Etcheverry, L., Maximenko, N.A., and Melnichenko, O.
[07-Nov-17]. Marine fronts are narrow boundaries that separate water masses of different properties. These fronts are caused by various forcing and believed to be an important component of the coupled ocean-atmosphere system, particularly in the tropical oceans. In this study, we use sea surface salinity (SSS) observations from Aquarius satellite to investigate the spatial structure and temporal variability of SSS fronts in the tropical Atlantic. Lagerloef, G.S.E. and Kao, H-Y.
[16-Dec-16]. Salinity variations at the ocean surface are key indicators of changes in air-sea water fluxes. The Aquarius mission measured sea surface salinity (SSS) over the global ocean from 25 August 2011 to 7 June 2015 (about 3 years, 9 months), coinciding with the onset of the 2015 El NiÃ±o. This presentation will explore preliminary findings of the SSS seasonal to interannual variability during this time, and the correlations with ENSO indices, surface precipitation and evaporation fluxes. Nonaka, M., Hosoda, S., and Schneider, N.
[16-Dec-16]. With accumulation of salinity observational data by Argo floats, it becomes possible to investigate salinity variability on seasonal to interannual time scales. While we know that there is strong seasonality in sea surface temperature (SST), seasonality in sea surface salinity (SSS) is not known well. Based on gridded Argo and other observational data and atmospheric reanalysis data, we examine global distribution of SSS seasonality using 12-month lagged auto-correlation map. Bingham, F. and Lee, T.
[16-Dec-16]. Using Aquarius Version-4 data, we have investigated the time and space scales of sea surface salinity (SSS) over the global ocean between 60Â°S and 60Â°N. Decorrelation time scales of SSS were found to be divided among less than 80 days (covering 1/2 of ocean area), 80-100 days (1/3) and greater than 100 days (remainder). Once the seasonal cycle is removed, shorter time scales (less than 80 days) dominate. Maes, C., O'Kane, T., and Monselesan, D.P.
[16-Dec-16]. Despite recent advances in satellite sensors, it remains great uncertainty in the large-scale spatial variations of upper ocean salinity across seasonal through interannual to decadal timescales. Consonant with both broad-scale surface warming and the amplification of the global hydrological cycle, observed global multidecadal salinity changes typically have focused on the linear response to anthropogenic forcing, but not on salinity variations due to changes in the static stability and or variability due to the intrinsic ocean or internal climate processes. Here, we examine the static stability and spatiotemporal variability of upper ocean salinity across a hierarchy of models and reanalyses. In particular, we partition the variance into time bands via application of singular spectral analysis, considering sea surface salinity (SSS), the Brunt Vaisala frequency (N2), and ocean salinity stratification (OSS) in terms of the stabilizing effect due to the haline part of N2 over the upper 500m. Busecke, J.J.M., Abernathey, R., and Gordon, A. L.
[16-Dec-16]. Lateral mixing by mesoscale eddies is widely recognized as a crucial mechanism for the global ocean circulation and the associated heat/salt/tracer transports. The Salinity in the Upper Ocean Processes Study (SPURS) confirmed the importance of eddy mixing for the surface salinity fields even in the center of the subtropical gyre of the North Atlantic. We focus on the global salinity maxima due to their role as indicators for global changes in the hydrological cycle as well as providing the source water masses for the shallow overturning circulation. Zhang, Y., Bayler, E.J., and Baker-Yeboah, S.
[16-Dec-16]. The NOAA National Centers for Environmental Information (NCEI), as the US archive for oceanographic data, provides long-term data stewardship of in situ sea-surface salinity (SSS) data, including near-real-time and delayed-mode products. These high quality in situ observations enable monitoring and validating Level-2 satellite data from the European Space Agencyâs (ESA) Soil Moisture â Ocean Salinity (SMOS), the National Aeronautics and Space Agencyâs (NASA) Aquarius mission, and NASAâs Soil Moisture Active-Passive (SMAP) mission. Cabot, F., Anterrieu, E., Kerr, Y.H.
[16-Dec-16]. Since the launch of the SMOS mission in 2009, two other satellites carrying L-band radiometers joined it on orbit. Aquarius was launched in June 2011 and SMAP in January 2015. Unfortunately, Aquarius ceased operation later that year. All 3 instruments have been operating simultaneously between April and June 2015. Although this golden age of L-band on orbit radiometry was short lived, it allowed for sound comparison of the performances of these 3 radiometers. Moreover, its untimely termination emphasizes the need for reliable inter calibration to build long term consistent archives of brightness temperature and higher level products. Supply, A., Boutin, J., Vergely, J-L., Hasson, A.E.A.
[16-Dec-16]. The Soil Moisture and Ocean Salinity (SMOS) satellite mission has been measuring sea surface salinity (SSS) for over 6 years with about 5-day global ocean coverage and a spatial resolution of about 50 km. In rainy regions, at local and short time scales, the spatio-temporal variability of SSS is dominated by rainfall. The relationship between surface freshening and rain rate (RR) has been highlighted in the Pacific intertropical convergence zone (Boutin et al., 2014). In this context, this study investigates the rainfall characteristics that may be inferred from SMOS SSS based on statistical approach.