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**Some programs are limited. Please read solicitations carefully and consult your Office of Research for specifics, such as limited applications through your university and internal application deadlines.**

The CYGNSS mission was originally conceived to support improved sampling of ocean surface winds in tropical cyclones, by reducing the revisit time and lowering the sensitivity to precipitation relative to previous satellite-based wind observations, such as those from scatterometers. This ROSES element seeks to expand the utility of the CYGNSS measurements by demonstrating other scientific uses and end-user applications of the mission’s science data products; successful proposers will become members of the Competed CYGNSS Science Team.

This program element has eligibility requirements involving the type of data that may (and must) be used in the proposed activities and there are special requirements on current CYGNSS science team members and proposers from federal agencies other than NASA. All proposers are strongly encouraged to carefully read Section 4 Eligibility and Evaluation Criteria.

Selected examples of research foci that are relevant to this call are provided in Section 3. Please note that this is not an exclusive list. As the amount of funding available for this opportunity is limited, it is unlikely that the set of proposals selected for funding will address all of the example areas listed in Section 3.

Proposals to develop retrieval methods based upon CYGNSS bistatic radar measurements must include:
- An assessment of retrieval uncertainty and the associated error budget; and
- Plans for the development of an algorithm theoretical basis document (ATBD) and an associated algorithm specification document to support the production of new Level 2 science data products (ATBD examples are provided at https://eospso.gsfc.nasa.gov/content/algorithm-theoretical-basis-documents);
Proposals relating to atmospheric and/or oceanographic scientific studies or applications must clearly address the unique contributions made possible by the improved spatial and temporal sampling of the CYGNSS constellation.

3. Example Research Areas
3.1 Quantitative Data Products and/or Analyses Focusing on Surface Wind and/or Air-Sea Interactions
This includes the development of expanded, new, or alternative atmospheric or surface products from the CYGNSS data (such as ocean surface vector wind estimates). Atmospheric or oceanographic studies related to these new products will also be considered. Even though the study of tropical cyclones is the focus of the original CYGNSS mission proposal, NASA will consider additional meritorious studies.

3.2 Physical Oceanography via Altimetry
The CYGNSS Level 1 measurements of scattering cross section also include metadata related to the timing of the signal propagation from the GPS transmitter to the Earth’s surface, and from the surface to the CYGNSS receiver. This timing information permits a modified type of ocean surface altimetry. The vertical accuracy of such an approach is significantly coarser than that of conventional satellite radar altimeters, but the temporal sampling and spatial coverage from the CYGNSS constellation are significantly better. The ability of such a bistatic radar to operate as an altimeter and map the sea surface height (SSH) of the ocean has also been demonstrated experimentally [Clarizia et al., 2016]. The improvement in spatial and temporal sampling properties provided by a CYGNSS-like constellation of altimeters is expected to enable investigations of mesoscale oceanic eddies [Ruffini et al., 2004]. Proposals to develop SSH retrieval methods applicable to the CYGNSS bistatic radar measurements are solicited. Proposals that carry out scientific investigations enabled by the improved spatial and temporal sampling of SSH using CYGNSS-derived altimetric data are also of interest.

3.3 Storm surge
Most numerical weather prediction and storm surge models use ocean surface wind data assimilation schemes developed to accommodate the sampling properties of wide swath, low-Earth orbiting instruments such as scatterometers. The sampling properties of the CYGNSS constellation are significantly different than those provided by these traditional low-Earth orbiting wind-measuring instruments. Data assimilation schemes adapted to, and optimized for, the unique spatial and temporal sampling characteristics of the CYGNSS constellation data are expected to be required in order to maximize the impact of CYGNSS data. In particular, storm surge modeling proposals which make best use of the unique spatial and temporal sampling properties of the CYGNSS ocean surface wind speed science data products are of interest.

3.4 Land Process Studies, Soil Moisture and Freeze/Thaw Ground and airborne field campaigns have demonstrated the sensitivity of GPS-based bistatic radar measurements to sub-surface soil moisture [Katzberg et al., 2006]. More recently, spaceborne measurements by the TechDemoSat mission have also demonstrated sensitivity to soil moisture [Chew et al., 2016]. Significant differences between CYGNSS and previous soil moisture-sensing spaceborne missions include CYGNSS’s high temporal sampling rate and the constellation’s ability to resolve the complete diurnal cycle. Proposals that develop soil moisture retrieval methods applicable to the CYGNSS bistatic radar measurements are of interest. The ability to sense the changes in the Earth's permafrost and the freeze/thaw patterns of seasonally frozen land are critical to understanding the Earth's climate system. The transition of the dielectric properties of the underlying soil from freeze to thaw state has been examined theoretically and demonstrated experimentally using GPS-based bistatic radar measurements [Cardellach et al., 2011]. Proposals that develop freeze/thaw detection methods applicable to the CYGNSS bistatic radar measurements are of interest.

Deadline: Notice of intent due September 8, 2017. Proposal due November 8, 2017

Announcement: https://nspires.nasaprs.com/external/solicitations/summary!init.do?solId=%7b97AB0C24-FCB6-C017-8CC4-A7BFECA08874%7d&path=open