NASA Soil Moisture Active Passive Mission Status and Science Highlights

The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational during April 2015. This paper provides a summary of the quality assessment of its baseline soil moisture and freeze/thaw products as well as an overview of new products. The first new product explores the Backus Gilbert optimum interpolation based on the oversampling characteristics of the SMAP radiometer. The second one investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic aperture radar (SAR) data to obtain soil moisture products at about 1 to 3 km resolution. In addition, SMAPs L-band data have been found useful for many scientific applications, including depictions of water cycles, vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.The SMAP soil moisture, freeze/taw state and SSSprovide a synergistic view of water cycle. For example, Fig.7 illustrates the transition of freeze/thaw state, change of soilmoisture near the pole and SSS in the Arctic Ocean fromApril to October in 2015 and 2016. In April, most parts ofAlaska, Canada, and Siberia remained frozen. Melt onsetstarted in May. Alaska, Canada, and a big part of Siberia havebecome thawed at the end of May; some freshwater dischargecould be found near the mouth of Mackenzie in 2016, but notin 2015. The soil moisture appeared to be higher in the Oband Yenisei river basins in Siberia in 2015. As a result,freshwater discharge was more widespread in the Kara Seanear the mouths of both rivers in June 2015 than in 2016. TheNorth America and Siberia have become completely thawedin July. After June, the freshwater discharge from other riversinto the Arctic, indicated by blue, also became visible. Thefreeze-up started in September and the high latitude regionsin North America and Eurasia became frozen. Comparing thespread of freshwater in August 2015 and 2016 suggests thatthere was more discharge from Ob and Yenisei in 2015,which appeared to correspond to a higher soil moisturecontent in the Ob and Yenisei basins. In contrast, Mackenzieappeared to have more discharge in September 2016

SMAP Mission Status, New Products, and Extended-Phase Goals

NASA's Soil Moisture Active Passive (SMAP) Project now has completed its prime-phase (three years) mission and has entered a new five-year extended phase. The global L-band radiometry from SMAP has enabled diverse scientific investigations in water, energy and carbon cycle research, terrestrial ecology and ocean science. These include eliciting the role of soil moisture control on the evaporation regime and vegetation gross primary productivity, observing soil-vegetation continuum water relations, analysis of flood and droughts, climate modeling and weather prediction, detecting ocean high-winds during tropical storms, and observing fresh-water outflow in coastal oceans. This paper highlights the recent enhancements to the SMAP suite of science products (from instrument level-1 to geophysical retrievals level-2 and level-3)

Impact of giant iceberg A68A on the physical conditions of the surface South Atlantic, derived using remote sensing

Giant icebergs release cold, fresh meltwater as they drift, perturbing the physical conditions of the surface ocean. This study uses satellite-derived sea surface salinity and temperature measurements to explore the physical impact of supergiant iceberg A68A between September 2020 and June 2021. During A68A's drift through the Scotia Sea in austral spring, gradual but persistent edge-wasting contributed to a freshening of several psu extending hundreds of kilometers ahead of the iceberg, whilst the cooling signal was more pronounced in the iceberg's wake. The magnitude of the physical perturbation intensified during A68A's breakup near South Georgia. Several large meltwater lenses surrounding the descendant icebergs displayed temperature anomalies of up to −4.5°C, whilst the salinity measurements indicated a surface (skin-depth) anomaly regularly exceeding order −10 psu. The perturbations stretched at times >1,000 km and persisted for >2 months following A68A's melt in April 2021

Quasi-biweekly mode of the Asian summer monsoon revealed in Bay of Bengal surface observations

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 125(12),(2020): e2020JC016271, https://doi.org/10.1029/2020JC016271.Asian summer monsoon has a planetary‐scale, westward propagating “quasi‐biweekly” mode of variability with a 10–25 day period. Six years of moored observations at 18°N, 89.5°E in the north Bay of Bengal (BoB) reveal distinct quasi‐biweekly variability in sea surface salinity (SSS) during summer and autumn, with peak‐to‐peak amplitude of 3–8 psu. This large‐amplitude SSS variability is not due to variations of surface freshwater flux or river runoff. We show from the moored data, satellite SSS, and reanalyses that surface winds associated with the quasi‐biweekly monsoon mode and embedded weather‐scale systems, drive SSS and coastal sea level variability in 2015 summer monsoon. When winds are calm, geostrophic currents associated with mesoscale ocean eddies transport Ganga‐Brahmaputra‐Meghna river water southward to the mooring, salinity falls, and the ocean mixed layer shallows to 1–10 m. During active (cloudy, windy) spells of quasi‐biweekly monsoon mode, directly wind‐forced surface currents carry river water away to the east and north, leading to increased salinity at the moorings, and rise of sea level by 0.1–0.5 m along the eastern and northern boundary of the bay. During July–August 2015, a shallow pool of low‐salinity river water lies in the northeastern bay. The amplitude of a 20‐day oscillation of sea surface temperature (SST) is two times larger within the fresh pool than in the saltier ocean to the west, although surface heat flux is nearly identical in the two regions. This is direct evidence that spatial‐temporal variations of BoB salinity influences sub‐seasonal SST variations, and possibly SST‐mediated monsoon air‐sea interaction.The authors thank the Ministry of Earth Sciences (MoES) institutes NIOT and INCOIS, and the Upper Ocean Processes (UOP) group at WHOI for design, integration, and deployment of moorings in the BoB. The WHOI mooring was deployed from the ORV Sagar Nidhi and recovered from the ORV Sagar Kanya—we thank the officers, crew and science teams on the cruises for their support. Sengupta, Ravichandran and Sukhatme acknowledge MoES and the National Monsoon Mission, Indian Institute of Tropical Meteorology (IITM), Pune, for support; Lucas and Farrar acknowledge the US Office of Naval Research for support of ASIRI through grants N00014‐13‐1‐0489, N0001413‐100453, N0001417‐12880. We thank S. Shivaprasad, Dipanjan Chaudhuri and Jared Buckley for discussion on ocean currents and Ekman flow, and Fabien Durand for discussion on sea level. JSL would like to thank the Divecha Center for Climate Change, IISc., for support. DS acknowledges support from the Department of Science and Technology (DST), New Delhi, under the Indo‐Spanish Programme.2021-05-1

Ocean Vector Wind Measurement Potential from the Global Precipitation Measurement Mission using a Combined Active and Passive Algorithm

Ocean surface vector wind (OVW) is an essential parameter for understanding the physics and dynamics of the ocean-atmosphere system, thereby improving weather forecasting and climate studies. Satellite scatterometers, synthetic aperture radars, and polarimetric microwave radiometers have provided almost global coverage of ocean surface vector wind for the last four decades. Nonetheless, a consistent and uninterrupted long-time data record with the capability of resolving sub-diurnal variability has remained a critical challenge over the years. The Global Precipitation Measurement Mission (GPM) is a satellite mission designed to provide space-based precipitation information on a global scale with complete diurnal sampling. This dissertation presents a combined active and passive retrieval algorithm to investigate the feasibility of ocean surface vector wind measurements from the GPM core satellite by utilizing its Ku- and Ka-band Dual-frequency Precipitation Radar (DPR) and the multi-frequency GPM Microwave Imager (GMI) observations. The unique GPM active and passive geophysical model functions were empirically developed by characterizing the anisotropic nature of ocean backscatter of normalized radar cross-section (δ°) and brightness temperature (TB) at multiple bands. For passive GMF, the modified 2nd Stoke\u27s parameter (linear combination of V and H-pol TBs) was used to mitigate the atmospheric contamination and to enhance the anisotropic wind direction signal superimposed on GMI TBs. The GMFs were combined in a maximum likelihood estimation (MLE) algorithm to infer the OVW. Finally, the retrieval algorithm was validated by comparing OVW retrievals with collocated NASA Advanced Scatterometer (ASCAT) wind vectors. The wind speed and direction retrieval performance statistics are promising and comparable with those of conventional scatterometer and polarimetric radiometer data products. The algorithm demonstrates the capability of the GPM to provide a long-term OVW data record for the entire GPM-TRMM era, which may include unique monthly diurnal OVW statistics

Circulation Changes in the Arctic Ocean and Subarctic Seas and Their Connections to the Global Ocean and Climate

Salinity and freshwater fluxes are important tools for monitoring the amount of freshwater entering and exiting the Arctic Ocean. Satellite-derived salinity provides a way to study surface advective freshwater fluxes; however, sea ice contamination, among others, remains an obstacle in the accuracy and reliability of these measurements. In this study, salinity and surface freshwater fluxes are calculated using NASA’s Soil Moisture Active Passive (SMAP) and the ESA’s Soil Moisture Ocean Salinity (SMOS), Argo, and the European Centre for Medium-Range Weather Forecast’s Ocean Reanalysis version 4 (ORAS4). ORAS4 compares well to Argo in the subarctic seas and is used for comparison to the satellites in the Bering Strait and Barents Sea Opening (BSO). There is agreement between satellites and ORAS4 on average and variability of freshwater fluxes in the Bering Strait, demonstrating the potential satellites have to study these fluxes in lower latitude subarctic regions with high freshwater variability. In the BSO, however, the satellites were not able to capture similar fluxes as ORAS4, indicating the need to improve satellitederived salinity in polar regions. This finding is increasingly important as the Arctic changes and more accurate, widespread data are needed. Satellites and models are used to examine decadal changes in the Arctic Ocean and subarctic seas. Salinity has undergone one of the most significant changes, as there is a juxtaposition of trends, with the Canada Basin freshening, and many other seas undergoing salinification. This is caused by decreasing sea ice, and a shift toward an anticyclonic atmospheric circulation regime over the Arctic, which alters riverine flow, freshwater output, and Beaufort Gyre strength. Increasing ocean temperatures across the Arctic Ocean and most significantly, the subarctic Atlantic region, are also found. This likely contributed to thermal expansion which, in addition to ice sheet loss, has caused increasing sea level anomalies across the Arctic and subarctic regions. The warming and salinification in the subarctic Atlantic and Barents Sea may be due to an increased proportion of Atlantic waters in the region, owing to the shift to a more anticyclonic circulation regime in the late 1990s

Influence of nonseasonal river discharge on sea surface salinity and height

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chandanpurkar, H. A., Lee, T., Wang, X., Zhang, H., Fournier, S., Fenty, I., Fukumori, I., Menemenlis, D., Piecuch, C. G., Reager, J. T., Wang, O., & Worden, J. Influence of nonseasonal river discharge on sea surface salinity and height. Journal of Advances in Modeling Earth Systems, 14(2), (2022): e2021MS002715, https://doi.org/10.1029/2021MS002715.River discharge influences ocean dynamics and biogeochemistry. Due to the lack of a systematic, up-to-date global measurement network for river discharge, global ocean models typically use seasonal discharge climatology as forcing. This compromises the simulated nonseasonal variation (the deviation from seasonal climatology) of the ocean near river plumes and undermines their usefulness for interdisciplinary research. Recently, a reanalysis-based daily varying global discharge data set was developed, providing the first opportunity to quantify nonseasonal discharge effects on global ocean models. Here we use this data set to force a global ocean model for the 1992–2017 period. We contrast this experiment with another experiment (with identical atmospheric forcings) forced by seasonal climatology from the same discharge data set to isolate nonseasonal discharge effects, focusing on sea surface salinity (SSS) and sea surface height (SSH). Near major river mouths, nonseasonal discharge causes standard deviations in SSS (SSH) of 1.3–3 practical salinity unit (1–2.7 cm). The inclusion of nonseasonal discharge results in notable improvement of model SSS against satellite SSS near most of the tropical-to-midlatitude river mouths and minor improvement of model SSH against satellite or in-situ SSH near some of the river mouths. SSH changes associated with nonseasonal discharge can be explained by salinity effects on halosteric height and estimated accurately through the associated SSS changes. A recent theory predicting river discharge impact on SSH is found to perform reasonably well overall but underestimates the impact on SSH around the global ocean and has limited skill when applied to rivers near the equator and in the Arctic Ocean.This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) with support from the Physical Oceanography (PO) and Modeling, Analysis, and Prediction (MAP) Programs. High-end computing resources for the numerical simulation were provided by the NASA Advanced Supercomputing Division at the Ames Research Center

Variability and uncertainty of satellite sea surface salinity in the subpolar North Atlantic (2010-2019)

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Yu, L. Variability and uncertainty of satellite sea surface salinity in the subpolar North Atlantic (2010-2019). Remote Sensing, 12(13), (2020): 2092, doi:10.3390/rs12132092.Satellite remote sensing of sea surface salinity (SSS) in the recent decade (2010–2019) has proven the capability of L-band (1.4 GHz) measurements to resolve SSS spatiotemporal variability in the tropical and subtropical oceans. However, the fidelity of SSS retrievals in cold waters at mid-high latitudes has yet to be established. Here, four SSS products derived from two satellite missions were evaluated in the subpolar North Atlantic Ocean in reference to two in situ gridded products. Harmonic analysis of annual and semiannual cycles in in situ products revealed that seasonal variations of SSS are dominated by an annual cycle, with a maximum in March and a minimum in September. The annual amplitudes are larger (>0.3 practical salinity scale (pss)) in the western basin where surface waters are colder and fresher, and weaker (~0.06 pss) in the eastern basin where surface waters are warmer and saltier. Satellite SSS products have difficulty producing the right annual cycle, particularly in the Labrador/Irminger seas where the SSS seasonality is dictated by the influx of Arctic low-salinity waters along the boundary currents. The study also found that there are basin-scale, time-varying drifts in the decade-long SMOS data records, which need to be corrected before the datasets can be used for studying climate variability of SSSThis research was funded by NASA Ocean Salinity Science Team (OSST) activities through Grant 80NSSC18K1335