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Brown, S. (18-Jan-17). An update on air-sea temperature dependence – which has been hypothesized to be the cause of seasonal biases observed at high latitudes in Aquarius data, – is provided. Version 4.5 (V4.5) data have been analyzed to see if the air-sea dependence observed in Version 4.2 and earlier products was an artifact of the O2 absorption model. Measured versus expected antenna temperature (TA) and winds are compared with air-sea temperature differences (dT) for vertically- and horizontally-polarized data. Results indicate that air-sea temperature difference dependence could be incorporated into Aquarius emissivity corrections (model function) or as a look-up table for delta impacts. Brown, S. (17-Jan-17). This presentation includes outputs of various analyses of Aquarius antenna temperature (TA) versus expected (TAexp) for vertical (V) and horizontal (H) polarizations. Deltas (d) between these are presented by month. In addition, monthly third Stokes (Q) maps and associated statistical data are included. Misra, S. (17-Jan-17). This study has been conducted to ensure that Aquarius radiometers did not introduce long-term variation in salinity retrievals. Radiometer performance has been validated independent from the Hybrid Coordinate Ocean Model (HYCOM) using a ground-based source and double-difference methodology. Microwave emissions over Antarctica has proven to be an excellent relative calibration source at the frequency of Aquarius radiometers (L-band). The study concludes that all channel trends are within +/- 0.1 K over the life of the mission. Lagerloef, G., and Kao, H. (17-Jan-17). Aquarius sea surface salinity (SSS) retrievals are compared with co-located Argo buoy data using three processing versions: 4.0, 4.5.0, and 4.5.1. The first sets of maps show SSS differences over the globe (combined, ascending orbits only, and descending orbits only). Histograms, time-series graphs, and daily global averaged standard deviations of of combined data are then separated by the three Aquarius beams for each processing version. One set of time-series graphs show the daily median of global ascending minus descending for each beam, followed by median data binned into latitude bands. The final histograms show differences between Aquarius, in-situ buoy, and Hybrid Coordinate Ocean Model (HYCOM) data. Meissner, T., Went, F., and Manaster, A. (17-Jan-17). Five proposed changes to the Aquarius geophysical model function (GMF) for Version 5 (V5) are outlined, some of which have been already been incorporated into evaluation processing version and others brand new. These changes include using sea surface temperature data (SST) from the Canadian Meteorological Centre, reflected galaxy data from SMAP, updated galaxy symmetrization (i.e., to 50% of current), oxygen (O2) absorption based on Liebe et al., and adjusting SST dependence of wind-induced emissivity. The final slide outlines the proposed actions towards V5. Lagerloef, G., and Carey, D. (17-Jan-17). Empirical orthogonal function (EOF) analysis of Aquarius data has been performed to determine radiometer drifts without reference to the Hybrid Coordinate Ocean Model (HYCOM). This study focused on decomposition of two evaluation datasets (V4.2.0 and V4.2.1) using vertically-polarized Channel 1 (1V) data for the entire Aquarius mission. Based on these preliminary results, the next step is to re-analyze data using ocean provinces (North Pacific, North Atlantic, etc.) Brown, S. (17-Jan-17). The meeting kicked off with an overview of its focus and format. A summary of the previous in-person Cal/Val Meeting (March 2016), including “marching orders,” set the stage for key issues to tackle before the final release (Version 5) of Aquarius salinity data processing. The presentation concludes with a list of meeting objectives. Lagerloef, G. (17-Jan-17). Aquarius Principal Investigator, Gary Lagerloef, provided his perspective on the open issues facing the Aquarius Cal/Val team under the general categories of latitude bias (in salinity data), sensor calibration, and geophysical errors. He suggested separating sensor drift from geophysical model errors and possibly revisiting radar calibration over the entire Aquarius mission. Dinnat, E., and Le Vine, D. (17-Jan-17). Aquarius cold sky calibration (CSC) maneuvers were performed to determine global biases over time for the various Aquarius channels (i.e., 1, 2, 3 for vertical and horizontal polarizations). Improvement is shown from historic processing to the most recent published version (4.0) and current evaluation version (4.5.1). These data have been used to assess temporal instrument drift such as “wiggles,” along with hardware temperature fluctuations over time. Manaster, A., Meissner, T., and Wentz, F. (17-Jan-17). Two reference salinity models – Hybrid Coordinate Ocean Model (HYCOM) and Forecast Ocean Assimilation Model (FOAM) – were compared with Argo buoy data, considered to be the “truth” for this study. The purpose of this study is assessing the accuracy of the Aquarius-derived dataset, which presently uses HYCOM as its reference salinity. One outcome may be replacing HYCOM with Argo as the Aquarius reference salinity in some regions, if not globally. Lang, R., Zhou, Y., Dinnat, E., and Le Vine, D. (18-Jan-17). Seawater dielectric constant measurements (32 data points) have been used to determine the “GW” model function, based on varying temperature and salinity. This is compared with previous model functions, Klein-Swift and Meissner-Wentz over temperature ranges from 0 to 35 degrees C and salinity values of 30, 33, 35, and 38. Each of these is also compared with Argo buoy data whose SSS sampling SSS is mainly from 34 to 36. Future work will make more measurements in this range to improve the GW model function’s accuracy. Lee, T. (17-Jan-17). Presentation focuses on comparing various processing versions of Level-3 Aquarius sea surface salinity (SSS) products with monthly gridded maps of Argo buoy data from Scripps Institution of Oceanography (SIO). Analyses include: (1) Time-mean SSS differences; (2) Zonally-averaged and time-mean SSS; (3) Averages based on Argo latitudinal coverage; (4) Latitude-time plots of zonally averaged SSS with and without time mean; (5) Comparison of standard deviations at various spatial scales; and (6) Temporal standard deviations at various spatial scales. The study concludes that Version 4.5 has the smallest time-mean global, latitudinal, and regional biases while Version 4.0 has the smallest seasonal anomaly biases. Brown, S. (17-Jan-17). Presentation provides details on various Aquarius data processing releases over time. Version 1.3 was the first (August 2012) while Version 4 (July 2015) was the most recent public release. Each had ever-improving salinity retrievals with updates to antenna patterns, ocean roughness corrections, masks (e.g., RFI, land), and corrections for instrument drift and galaxy reflection off the ocean surface. Recent processing versions (i.e., 4.1 through 4.5) are also described; details of these are being evaluated by the Cal/Val team to determine which items should be included in the final release (Version 5). Hong, L., Gales, J., and Carey, D. (17-Jan-17). To assess specific components of Aquarius data processing, a series of evaluation products were developed from May 2015 through December 2016 (V4.1, V4.2, etc.). Major components include instrument corrections (i.e., “wiggles”), updated sea surface temperature source, galactic symmetrization, Rain Impact Model (RIM), along with new galaxy and oxygen models. An overview of these evaluation versions is presented, including analyses of their effects on salinity retrievals (i.e., time series graphs and maps). Dinnat, E., and Brucker, L. (18-Jan-17). The objective of this work is to provide improved sea ice fractions for the Level-2 Aquarius product. Data acquired near Antarctica using NOAA ice fractions show scattered and highly non-linear relationships with Aquarius brightness temperatures (Tb). Using the AMSR-2 Bootstrap Algorithm (ABA) largely reduces scattering and shows strong linearity with Aquarius Tb. Data plots from both hemispheres show good results with ABA; however, there are some issues related to multiyear ice in the northern hemisphere. The next step is empirical correction of Aquarius Tb for ice contamination to improve coastal sea surface salinity retrievals. Dinnat, E., Soldo, Y., and Le Vine, D. (18-Jan-17). Presentation outlines approaches for land correction in Aquarius data, including using improved land emissivity model in simulator and empirical brightness temperature model-derived L-band measurements. New land corrections have been evaluated using co-located Aquarius and Argo buoy sea surface salinity (SSS). Results are presented for the Mediterranean Sea, including data from the Aquarius/SMAP overlap period. Mapped along-track SSS in the Mediterranean and statistical analyses show improvement with the new land correction, including fewer anomalously low SSS values near coasts and better correlation with Argo data. Jacob, M., Santos-Garcia, A., and Jones, L. (18-Jan-17). Presentation provides an outline of the RIM variables that will be produced for Version 5 of Aquarius data processing, including rain impact variables, other rain parameters (i.e., instantaneous rain rate, rain accumulation over previous 24 hours, and beam fill fraction), and flagging. Data analysis shows that RIM correlates well with Aquarius; however, data were presented to help evaluate whether the current 24-hour time duration window should be reduced (e.g., to 3, 6, 12, or 18 hours). Preliminary results suggest that the difference between RIM 24-hour data and 12- or 18-hour data is less than 0.01 psu. Future analysis will focus on wind speed impacts. Soldo, Y., de Matthaeis, P., and Le Vine, D. (18-Jan-17). Presentation provides an overview of the current Radio Frequency Interference (RFI) flagging in Aquarius data. RFI flags are based on fixed thresholds, defined as the highest antenna temperatures (Ta) that are expected from natural emissions. It is important to note that reaching these thresholds result in flags only, not removal of data from Aquarius datasets. Meissner, T., Wentz, F., and Lee, T. (18-Jan-17). This presentation gives an overview of Remote Sensing Systems’ (RSS) SMAP salinity processing (Version 2.0). These data are batch processed each month and also available through the Physical Oceanography Distributed Active Archive Center. Details on Level 2C, 3, Release Notes, and updates from Version 1.0 are provided. Maps depict the following: antenna temperature (TA) bias for ascending minus descending orbits; TA measured minus expected; Zonal/temporal biases; reflector temperature; and land correction. Data have been validated by comparing with Argo monthly (1 degree by 1 degree) maps from Scripps Institution of Oceanography. Overall, Version 2.0 is an improvement over Version 1.0 with much reduced seasonal biases. Melnichenko, O., and Hacker, P. (17-Jan-17). The presentation begins with a series of analyses focused on regional and/or seasonal biases in Aquarius sea surface salinity (SSS). Various processing versions of Aquarius SSS data (e.g., V4.5.0 and V4.5.1) are compared with Argo buoy data from the Asia-Pacific Data-Research Center (APDRC). Analyses include: (1) Box analysis of regions in the Pacific and Atlantic; (2) Three-year mean global data; (3) Latitude-time distributions of weekly data (zonally averaged and time-varying); and (4) Amplitude of annual and semi-annual cycles in the bias field. The talk concludes with comparisons between Aquarius and SMAP-derived SSS data. Schanze, J. (17-Jan-17). The “Salinity Snake,” which measures salinity at 1-2 cm depth, was field tested during the first Salinity Processes in the Upper-ocean Regional Study (SPURS I) campaign in the North Atlantic (Sep. 2012). The improved snake was used in the SPURS II field program in the tropical western Pacific (summer 2016). This presentation provides eight examples of freshwater lenses sampled during SPURS II under various environmental conditions (e.g., wind speeds, precipitation rates, layered and mixed seawater). Thus far, 50 freshwater lenses have been identified and half of these occured in the absence of recorded precipitation. One conclusion is that low surface salinity is heavily dependent on surface mixing. Dinnat, E., and Le Vine, D. (18-Jan-17). The objective of this analysis is to use observed Aquarius antenna temperatures (Ta obs) and simulations (sims) to apply empirical linear adjustments to brightness temperature (Tb) data. These adjustments would be checked against instrumented land-based reference sites that were covered by Aquarius beams: Little River was covered by beam 2; and Little Washita was covered by beam 3. Graphs of measured versus modeled Ta (vertical polarization) for ocean data and ~30 Aquarius cold sky (CS) calibrations have been used to calculate slope and offset values. The adjusted calibration was checked using bias and scattering of land data. de Matthaeis, P., Soldo, Y., and Le Vine, D. (18-Jan-17). An overview of completed updates to the Aquarius Radio Frequency Interference (RFI) algorithm is provided along with potential new improvements (e.g., additional RFI flags based on higher-order statistics and turning of parameters to reduce missed detection and/or false alarm rate). Undetected low-level RFI is an unresolved issue and its effect on salinity retrievals is not yet quantified. An statistical analysis of measurements in low-RFI and RFI-free regions has been conducted, including a case study in the North Atlantic Ocean whose RFI environment changed dramatically after adjustment of radar frequencies in Northern Canadian (Oct 2013). Preliminary results indicate that the Aquarius RFI filter may miss low-level RFI but further studies are needed. Soldo, Y., Le Vine, D., Dinnat, E., Gales, J., and Hong, L. (18-Jan-17). Changes to the Aquarius land model fall into three general categories: (1) Discontinuities (e.g., Faraday angle, soil moisture near coasts, frozen soils, ice); (2) Consistency with SMAP (e.g., land cover classification, dielectric mixing, vegetation opacity, single-scattering albedo, roughness parameters, soil attributes, and ancillary data); and (3) Bug fixes. Data are presented for measured versus expected antenna temperature (Ta), comparing the old and new land models. The goal for planned land corrections is to use the measured brightness temperature (TB) in conjunction with a forward land model.