Meetings: Salinity Continuity Processing Workshop

April 29-30, 2019
Santa Rosa, CA USA
NASA Physical Oceanography Program hosted the Ocean Salinity Science Team and Salinity Continuity Processing Workshop at Remote Sensing Systems. The primary objectives were to review recent work on sea surface salinity products and their applications, and to discuss improvements in SMAP satellite SSS retrieval.
Documents: 31
Misra, S., Bosch-Lluis, J., Latham, B., Felten, C., Ogut, M., Brown, S., Lee, T., and Yueh, S. [30-Apr-19]. A 2018 field experiment was conducted in the Arctic to test the sensitivity of wide-band spectroradiometry (i.e., CubeRRT) to sea surface salinity in cold waters. Measurement and calibration challenges were encountered due to foam, waves, mixed ice, radiofrequency interference (RFI), and galactic reflection. Lessons learned will be applied to future work.
Wentz., F., Meissner, T., and Manaster, A. [29-Apr-19]. Issues with land contamination in Version 3 Remote Sensing Systems (RSS) processing – for both 70-km and 40-km products – are presented, followed by solutions to be applied in upcoming Version 4 data.
Chmelewski, M., Brown, J., Bingham, F., and Chkrebtii, O. [30-Apr-19]. SPURS-1 central mooring data are statistically analyzed to create a curve of overall distribution of annual rainfall as a function of rain rate. When compared with exponential curves from other regions, there was a consistent finding that greater than 50% of each buoy's cumulative annual rain occurs during fewer than 8% of rain events.
Menezes, V.V. [29-Apr-19]. Evaluation of four years of SMAP data (Remote Sensing Systems, RSS, Version 3 @ 70 km and 40 km; JPL Version 4.2) against Argo float measurements in the North Indian Ocean and Bay of Bengal. Conclusions include a fresh bias for RSS, salty bias for JPL, and better performance in the Arabian Sea than Bay of Bengal.
Dinnat, E. and Le Vine, D.M. [30-Apr-19]. Sea surface salinity (SSS) products are compared to in-situ Argo data over two "eras": Aquarius (Sep 2011 to May 2015) and SMAP (Apr 2015 to Jun 2018). Results show very good performance for SMAP Remote Sensing Systems Version 3; however, some issues remain in Southern Ocean retrievals, uncertainties in the dielectric constant and atmospheric models, and contamination from land and ice.
Lee, T. [29-Apr-19]. Monthly Level 3 (i.e., gridded) SMAP data are evaluated globally at three spatial scales with respect to gridded Argo data: 1x1 degree, 3x3 degrees, and 10x10 degrees. Statistical analysis of nearly four years of data from Remote Sensing Systems (Version 3 @ 70 km) and JPL (Version 4.2) show that SMAP Level 3 data approaches the accuracy of Aquarius Version 5 data.
Brown, S., Misra, S., Lee, T., and Yueh, S. [30-Apr-19]. Sea surface salinity was not included as an allocated "Flight Program Element" in the 2017 Decadal Survey and thus falls into the category of "competed programs" cost capped at $150M. Several options are presented to spark discussion on maintaining salinity continuity in the future.
Sun, J., Vecchi, G., Liao, E., Resplandy, L., and Soden, B. [30-Apr-19]. Conditions associated with Tropical Cyclone Hudhud (2014) are examined in the Bay of Bengal including sea surface salinity (SSS) and temperature (SST), rainfall, wind, and radiation. Model and satellite data are used to compute mixed layer depth, leading to the conclusion that SST increased during low SSS, which provided favorable ocean conditions for storm intensification.
Melnichenko, O. and Hacker, P. [30-Apr-19]. Analysis of Remote Sensing Systems (RSS) Level 3 (i.e., gridded) sea surface salinity products @ 40 km and @ 70 km are presented over various regions. Also, optimally interpolated (OI) along-track RSS Level-2C non-resampled SMAP sea surface salinity data are presented from the Gulf of Mexico. The OI technique provides an opportunity to resolve features closer to coasts without noise issues found in the RSS 40 km product.
Fournier, S., Lee, T., Tang, W., Steele, M., and Yueh, S. [29-Apr-19]. Six sea surface salinity products (SMOS, Aquarius, and SMAP) over the Arctic are compared from 2011-2015 and 2015-2017. Overall, they show good agreement with in-situ observations but there are some differences in terms of ice masks and impact of ice concentration.
Grodsky, S.A., Reul, N., Vandermark, D., and Bentamy, A. [30-Apr-19]. Shifts in the intertropical convergence zone (ITCZ) in the Atlantic Ocean result in intra-seasonal oscillations in rainfall. Sea surface salinity (SSS) and temperature, precipitation, and wind data are analyzed to understand the ocean's response to rainfall variations. Results indicate that SSS oscillations are detectable by SMAP and distinguishable from signals due to tropical instability waves.
Fore, A., Yueh, S., Tang, W., and Hayashi, A. [29-Apr-19]. Details on land corrections in JPL processing are presented. Challenges associated with sea ice correction (e.g., variation in position) lead to the conclusion that more work is needed.
Le Vine, D.M., and Dinnat, E. [30-Apr-19]. Issues associated with matching up satellite data with in-situ data are examined including differences in spatial resolution, accuracy, and frequency. Three options are considered: closest point of approach sampling (CPA), CPA with averaging, and "All-in-Box" (i.e., all samples in a time-space box). Aquarius sea surface salinity (SSS) data are used to evaluate the three options using various time and space scenarios. A draft proposal for Pi-MEP is also included.
Soldo, Y., Dinnat, E., and Le Vine, D.M. [29-Apr-19]. Idea to use actual SMAP measurements over land to compute land correction; however, brightness temperature needs to be estimated for angles other than 40 degrees.
Lindstrom, E. and Vinogradova, N. [29-Apr-19]. Overview of NASA Physical Oceanography and Salinity Continuity Programs are discussed along with upcoming activities and opportunities.
Vandermark, D., Feng, H., Grodsky, S., Reul, N., Wilkin, J., Hunter, E., and Levin, J. [29-Apr-19]. The Northwest Atlantic shelf (i.e., off the New England coast) has salinity assets such as long-term moorings, gliders, thermosalinographs (TSG), gliders, and data-assimilating models. These can be used to understand and complement satellite-derived salinity retrievals in terms of ocean processes and calibration/validation.
Kao, H-Y., Carey, D., Schanze, J., and Lagerloef, G.S.E. [30-Apr-19]. Update on SVDS includes details on flexible match-up tools for the OSST Cal/Val team and the best match-up for the general public and Pi-MEP. Global validation statistics for each version of SMAP data is presented (i.e., Version 2 @ 70 km, Version 3.3 @ 40 km and @ 70 km). The approach criteria for – and examples of – Aquarius and SMAP match-ups are presented including search radius, time window, and smoothing method. Next steps include regional validation case studies (SPURS-1, SPURS-2) and "Salinity Snake" validation.
Tsontos, V., Vazquez, J., and Jiang, Y. [29-Apr-19]. Release of in-situ datasets (Saildrone, SPURS2), new web-based tools for field campaign support, and other announcements are shared. Summary of the status of salinity archival/distribution support under NASA's Salinity Continuity Program, including both satellite sea surface salinity and field campaign datasets.
Tang, W., Yueh, S., Fore, A., and Hayashi, A. [29-Apr-19]. The lack of in-situ data in the Arctic Ocean motivates development of a sea ice correction algorithm using SMAP and Aquarius data. Three regions are highlighted to distinguish signatures of multi-year and first-year sea ice.
Lagerloef, G., Kao, H-Y., and Carey, D. [29-Apr-19]. Update of triple-point analysis efforts being conducted on salinity measurements. The three systems evaluated include Aquarius, in-situ data, and the HYCOM model. Future work will include a more extensive study of Aquarius Level 2 data over a longer time period.
Meissner, T. [29-Apr-19]. SMAP's antenna is emissive and thus more difficult to model than Aquarius. Data from ocean and Amazon targets demonstrates that the SMAP pre-launch antenna thermal reflector model needs empirical adjustment.
Lindsley, R., Manaster, A., Meissner, T., and Wentz., F. [29-Apr-19]. Solar contamination one of many corrections applied to SMAP sea surface salinity retrievals. Presentation gives details on revised sun glint quality control flag, which increases coverage while rejecting data with solar contamination.
Zhou, Y., Lang, R., Dinnat, E., and Le Vine, D.M. [29-Apr-19]. Update on newest dielectric measurements: 30, 34, 35, 36 PSU at various temperatures including subzero temperatures.
Schanze, J.J., Kao, H-Y., Carey, D., and Lagerloef, G.S.E. [30-Apr-19]. The "Salinity Snake" instrument was developed to sample undisturbed seawater in situ from a 13-meter boom. Thus far, it has collected about 40,000 km of very-near surface salinity data, which is used to assess satellite sub-footprint variability. In addition, data from various instruments (Argo floats, moorings, drifters, etc.) has prompted several recommendations on match-up approaches between satellites and in-situ sensors (e.g., search radius, temporal windows).
deCharon, A. [29-Apr-19]. Updates to the "NASA Salinity" website and examples of communication materials are presented to spark discussion of OSST outreach support.
Bingham, F., D'Addezio, J., and Ulfsax, K. [30-Apr-19]. A high-resolution global model (i.e., MITgcm) is used to quantify the sub-footprint variability (SFV) embedded in satellite-based estimates of sea surface salinity. SFV is computed on a 2x2 degree evaluation grid using weighted standard deviation. Analysis of seven latitudes/longitudes, including a location in the SPURS-2 region, show that SFV is large in western boundary currents, frontal regions, river outflows, etc.
Meissner, T., Wentz., F., and Manaster, A. [29-Apr-19]. Latest Remote Sensing Systems (RSS) processing of SMAP salinity data release (Version 3) is outlined along with a preview of Version 4. Details of V3 are provided including rain impact, comparisons with SMAP Version 2, Argo, and Aquarius Version 5 data.
Hormann, V., Centurioni, L., Maximenko, N., and Chao, Y. [30-Apr-19]. Langragian drifters are used to investigate the effect of large-scale circulation on the development, location, and variability of the salinity minimum in the SPURS-2 region. Drifters show variability in near-surface salinity and temperature with saltier and colder water towards the middle of the Pacific. SMAP sea surface salinity data show an overall positive (i.e., fresh) bias when compared with drifter data in the SPURS-2 region.
Fore, A., Yueh, S., Tang, W., and Hayashi, A. [29-Apr-19]. Latest JPL processing of SMAP salinity data release (Version 4.2) is outlined. Details are provided on three-stage brightness temperature calibration, gridding, and data availability (including near-real-time).
Brown, S. and Misra, S. [29-Apr-19]. SMAP's radiometer and processing algorithms are identical to Aquarius. However, SMAP's scanning antenna looks at angles well beyond those of Aquarius, which had three fixed-angle horns. To reconcile differences between SMAP and Aquarius, data are limited to 254.65° (i.e., Horn 2). Comparison of monthly data suggests some geometric dependent bias in processing.
Vazquez, J., Gomez-Valdes, J., Bouali, M., Gentemann, C., and Tang, W. [30-Apr-19]. Data from a solar-powered, unmanned surface vehicle, Saildrone, is compared to SMAP sea surface salinity (SSS) data during Apr-Jun 2018. The JPL SSS product shows overall positive biases while the Remote Sensing Systems (RSS) product @ 40 km and @ 70 km shows negative biases. Signal-to-noise ratios for SSS data were fairly low, possibly due to land contamination. SSS coherence data are consistent with coastal upwelling scales while spectral slopes are consistent with mesoscale to sub-mesoscale variability.