1. A new concept study for a terrestrial snow mass mission at the Canadian Space Agency and Environment Canada Chris Derksen, Stephane Bélair and Anne Walker Environment Canada Mélanie Lapointe, Yves Crevier Canadian Space Agency

2. Outline Background: needs and requirements Science drivers: primary and secondary Overview of the concept review International context

3. Needs Environment Canada has identified high resolution snow water equivalent (SWE) as a priority observational gap which limits the development of enhanced operational environmental monitoring, services, and prediction While a radar-based mission holds potential, SWE retrieval algorithms and forward models require development and validation, and robust first guess model derived information on SWE and snow microstructure are required as retrieval inputs The scope of the concept study is to review and confirm the main operational requirements from users, investigate high level mission concepts, determine Canadian capabilities and technologies, and identify international partnership opportunities

4. Primary objective is complete northern hemisphere coverage every 2 to 3 days, at frequencies sensitive to snow mass, in order to meet land surface modeling requirements within the numerical weather prediction and operational hydrological modeling communities. Frequency selection to maximize sensitivity to SWE over the maximum possible range combined with mitigation of grain size effects. Primary product development would focus on terrestrial snow water equivalent at moderate (~1000 metre) resolution. Building on the heritage of previous missions (i.e. SASS, NSCAT, QuikSCAT) advanced spaceborne radar measurements would also provide suitable measurements to develop products related to: sea ice (type, concentration, extent, motion, melt and freeze onset) land ice (snow accumulation, melt onset, glacier and ice cap/shelf velocity) coastal ocean surface winds The mission concept will be driven by snow mass as the primary requirement, recognizing the potential contribution from spaceborne radar measurements, but is not starting from any pre- determined system concept Data Requirements

5. Snow plays a critical role in climatological, hydrological, and ecological processes across a significant portion of the Northern Hemisphere, represents an essential freshwater resource for human use, and influences a number of hazards (i.e. spring flooding; drought propagation). Specific scientific objectives for moderate resolution (~1 km) terrestrial snow products: 1.Quantify the spatially and temporally dynamic amount of freshwater stored in seasonal snow (monitoring and process studies) 2.Provide observational support for high resolution prediction (via data assimilation) of the land surface for NWP and hydrological modeling (predictions) 3.Diagnose systematic snow mass biases in the land modules of current Earth System Models (projections) How much snow is there? Where, in what ways, and why are snowpacks changing? Primary Science Driver

6. Specific scientific objectives for moderate resolution (~1 km) terrestrial snow products: 1.Quantify the spatially and temporally dynamic amount of freshwater stored in seasonal snow (monitoring and process studies) Accumulated annual snowfall divided by annual runoff over global land regions Barnett et al., Nature, 2005 Observed historical spring SWE and discharge for the Colorado River watershed, and projected streamflow changes from a large ensemble of CanESM2 simulations Fyfe et al., In prep. Snow cover provides a vital freshwater resource over a large fraction of the northern hemisphere This resource is under stress from warming temperatures and shifts in precipitation regimes

7. Specific scientific objectives for moderate resolution (~1 km) terrestrial snow products: 2.Provide observational support for high resolution prediction (via data assimilation) of the land surface for NWP and hydrological modeling (predictions) Error metrics for snow assimilation experiments using the coarse resolution (25 km) GlobSnow product over western Canada Temperature and SWE biases in the Canadian Seasonal to Interannual Prediction System (CanSIPS) Operational NWP requirements: daily coverage, moderate resolution (~1 km), well characterized retrieval uncertainty Operational seasonal prediction requirements: relaxed spatial and temporal resolution requirements

8. Specific scientific objectives for moderate resolution (~1 km) terrestrial snow products: 3.Diagnose systematic snow mass biases in the land modules of current Earth System Models (projections) CMIP5 models do not capture the significant reductions in spring snow cover extent observed during the satellite era Enhanced observations required in support of improvements to model physics and diagnostics June NH snow cover extent from observational snow analyses and CMIPS models (historical + rcp8.5 scenario) Brutel-Vuilmet et al., Cryos., 2012Derksen and Brown, GRL, 2012 March–April NH snow cover extent for historical CMIP5 simulations (colored crosses) and observations (black triangles)

9. Current satellite derived datasets are unable to estimate snow water equivalent (SWE) at the spatial resolution necessary to meet monitoring and modeling requirements. There is a disconnect between current satellite capabilities (25 km resolution) and operational land surface system requirements (1 km resolution). The climatologies for existing gridded SWE products vary by ~ 50% of peak SWE Climatological NH snow mass, 1981-2010 period Mudryk et al., J. Clim, in press Spread among NH snow mass climatologies by region Detrended mean correlation, pairs of daily (NDJFMA) SWE time series (1981-2010) Current Capabilities

10. The failure of QuikScat in 2011 represents an observational gap for many cryosphere parameters, including sea ice type and extent, snow accumulation on ice sheets, and melt onset and duration over land, sea ice, and permanent ice. These observations are required for ongoing determination of variability and change in the cryosphere, and the understanding of the role of the cryosphere in both forcing and responding to the global climate system. Current satellite scatterometer missions, including ASCAT and Rapidscat, provide ocean vector wind measurements at 20 to 30 km spatial resolution, which is insufficient for coastal applications. Using Doppler beam sharpening, 1 to 3 km resolution ocean vector wind retrievals are possible which would address current gaps in monitoring and forecasting near-shore regions. A high resolution capability will also allow the identification and tracking of the eye and motion of cyclones. Secondary Science Drivers

11. QuikSCAT VV (σ 0 in dB) showing trend in decreasing MY ice QuikSCAT Arctic Ocean multiyear ice (MYI) coverage Polyakov et al., 2012 Swan and Long, 2012 200320062009 Secondary Science Drivers: Sea ice type and extent

12. Secondary Science Drivers: Greenland melt and snow accumulation Snow accumulation: in situ measurements and QuikSCAT retrievals Blended MODIS and QuikSCAT surface melt information Hall et al., 2010 Nghiem et al., 2005

13. Secondary Science Drivers: Pan-Arctic melt onset QuikSCAT mean melt onset date (day of year), 2000-2009 Wang et al., 2011 QuikSCAT melt and freeze onset for 2006 Mortin et al., 2012

14. Sidelooking ScanSAR: Single look high res (~50m) 100km swath Cryosphere coverage in 15 days Rotating SAR: Single look res (~250m-500m) 700km swath for high res Cryosphere coverage in 2 days Concept 2 Example Mission Concept Trade Offs

15. Proposed Activities Review mission objectives and product definitions Consult partners to identify science readiness and operational objectives Analysis of experimental datasets in support of algorithm/product development Modeling studies in support of algorithm/product development Payload analysis and trade-off Mission concept design Mission development plan Analysis of alternate options International liaison

16. Scientific evaluation of mission concepts to monitor snow mass and other cryospheric parameters ITT on ESA emits SnowSAR campaign data analysis study (SCADAS) ITT on ESA emits. Release once all campaign data available. Microstructural origin of electromagnetic signatures in microwave remote sensing of snow First progress meeting held SnowLAB campaign, Swiss Alps Start this winter and extend 3 years Snow Product Inter-comparison (SnowPEx) Second workshop in August 2015 Complementary ESA Activities

17. Complementary NASA Activities Ongoing NASA THP projects: snow – radar interactions in tundra environments (PI: Dr. Matthew Sturm, University of Alaska – Fairbanks) and new approaches to backscatter modeling of snow (PI: Dr. Leung Tsang, University of Michigan) Snow Remote Sensing Working Group (3 meetings/workshops since 2013 plus field, modeling, and remote sensing schools) Wideband Instrument for Snow Measurements (WISM; NASA Instrument Incubator) Initial test flights in February 2015 SnowEx

18. Science Steering Committee Chris Derksen/Stephane Belair co-chairs (Environment Canada) Yves Crevier/Melanie Lapointe (CSA) Claude Duguay freshwater ice; CoReH20 MAG (U. Waterloo) Christian Haas sea ice (York University) Stephen Howell sea ice (Environment Canada) Alex Langlois terrestrial snow (U. Sherbrooke) Philip Marsh terrestrial snow (Wilfrid Laurier U) Martin Sharp land ice (U. Alberta) Donald Cline terrestrial snow (NOAA) Simon Yueh ocean vector winds (NASA-JPL) Jouni Pulliainenterrestrial snow; CoReH20 MAG (FMI)

19. Summary A snow mass mission concept study is being prepared, to address a fundamental observational gap which limits the development of enhanced operational environmental monitoring, services, and prediction at Environment Canada The mission is driven by snow mass as the primary requirement and recognizes the potential contribution from spaceborne radar measurements, but is not starting from any pre-determined technological concept Studies have not yet shown the comprehensive validation of radar derived SWE retrievals, nor the successful application of these retrievals to modeling (hydrology; NWP; climate) applications Secondary measurement objectives have been defined but do not drive the payload analysis Identifying international partnership opportunities will be an important component of the study