1. ESA UNCLASSIFIED – For Official Use Campaign results and preparations for the Candidate Core Explorer mission CoReH 2 O Michael Kern, Dirk Schüttemeyer, Andrea Perrera, Malcolm Davidson - Many thanks to MAG, study teams and experimenter teams - Grenoble, France 02/04/2013

2. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 2 ESA UNCLASSIFIED – For Official Use Outline Summary of objectives of CoReH2O Scientific preparations and activities in Phase A Campaigns in preparation of CoReH2O Earth Explorer 7 selection outcome Questions

3. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 3 ESA UNCLASSIFIED – For Official Use Summary of Mission Goals Measurements of snow water equivalent, snow extent and snow accumulation over glaciers with high resolution, high accuracy and temporal revisit Objectives: Quantify amount and variability of freshwater stored in snow packs (land and snow accumulation over glaciers) Evaluate and reduce uncertainty of snow water storage and budgets Validate and improve hydrological processes in NWP models Validate snow and ice processes in global climate models CoReH2O addresses snow and ice processes in the global climate system and water cycle © ESA/AOES Medialab

4. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 4 ESA UNCLASSIFIED – For Official Use Observational requirements Secondary parameters Spatial scale * Regional/Global Sampling (days) Accuracy * (rms) Snow water equivalent 200 m / 500 m3-15 3 cm for SWE  30 cm, 10% for SWE > 30 cm Snow extent 200 m / 500 m3-155% area Glacier snow accumulation 200 m / 500 m≤1510% of maximum * Reference: IGOS Cryosphere Theme Report Melting snow area, snow depth Snow Diagenetic facies, glacial lakes Glaciers Ice area; freeze up and melt onset date Lake/river ice Snow on ice; thin ice type and thickness Sea ice Primary parameters

5. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 5 ESA UNCLASSIFIED – For Official Use Measurement principle – radar backscatter Backscatter contributions: Volume, surface, and interaction terms. Observed backscatter coefficient ° : Main parameters for snow backscatter: Dry snow Snow water equivalent Grain size Soil background signal Wet snow Liquid water content (radar signal does not penetrate) Snow cover is a sintered medium. For backscatter modelling the scattering efficiency is parameterized by effective grain size. Flin & Brzoska, 2008

6. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 6 ESA UNCLASSIFIED – For Official Use Mission Overview USER SEGMENT Climate modelling research centres Hydrology/cryosphere research centres Operational users LAUNCHER Vega PSLV CoReH 2 O Mission Elements SUBJECT & REQUIREMENTS Global observation of snow and ice Dual-frequency, dual polarisation Radar MISSION PROFILE & ORBITS Two phases, two orbits 666/645 km reference altitudes Local time 06h00, 3/15 days cycles Payload Data Ground Segment Payload Data Acquisition Station (X-band) Processing and archiving elements Mission planning and monitoring elements GROUND SEGMENT Flight Operations Segment ESA Kiruna TT&C Station (S-Band) Flight Operation Control Centre (ESOC ) SPACE SEGMENT Single spacecraft X/Ku-band SAR payload LEO platform 1200 kg, 3500 W, 5 years lifetime ParameterMissions requirement Mission phases2 phases – 2 & 3 years long resp. Repeat cycles3 days and 15 days resp. CoverageSnow and ice areas, 85% in phase 2 Timeliness24 h Carrier frequency9.6 GHz (X) and 17.2 GHz (Ku) Polarisations VV and VH Incidence angle30 0 – 45 0 (access range) Spatial resolution≤ 50 m x 50 m (≥ 4 looks, ENL) Swath width≥ 100 km Noise equivalent sigma0 X-band: ≤ -23 dB (VV), ≤ -27 dB (VH) Ku-band: ≤ -20 dB (VV), ≤ -25 dB (VH) Radiometric stability≤ 0.5 dB Absolute radiometric bias≤ 1 dB

7. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 7 ESA UNCLASSIFIED – For Official Use Overview of CoReH2O Phase A Science Activities Development to snow retrieval algorithms for CoReH2O Algorithms for estimating snow grain size for CoReH2O retrievals Synergy of CoReH2O SAR and passive microwave data to retrieve snow and ice parameters CoReH2O Snow data assimilation study Development of sea ice and lake and river ice retrieval algorithms for CoReH2O Algorithms for snow and land ice retrieval using SAR data Example of a cost function in the baseline retrieval algorithm Passive microwave & active microwave remote - contrast of scale S1+ CoReH2O On-going Finalised On-going

8. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 8 ESA UNCLASSIFIED – For Official Use Classification of methods Spatial variability in the vertical direction captured by Class A-C methods. Future campaigns to apply Class A and B methods at different locations to capture horizontal spatial variability. ©WSL

9. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 9 ESA UNCLASSIFIED – For Official Use Algorithms for estimating snow grain size for CoReH2O retrievals Baseline retrieval algorithm was developed that solves for SWE and (effective) grain size Uses a (semi-emipircal, single- layer) radiative transfer model with reduced number of free parameters for iteration Uses a-priori information (SWE, grain size) provided by physical snow models driven by numerical meteorological analysis or forecast data to constrain the inversion. © UE-EEO A-priori accuracy needs: 50% for SWE and 15% for effective grain size

10. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 10 ESA UNCLASSIFIED – For Official Use Campaigns covering main snow regimes Churchill, Canada, Tundra (Near-)Coincident Ku-band and X-band scatterometers and airborne SARs used including very detailed in- situ measurements Sodankylä, Finland, Taiga Innsbruck, Austria, Alpine Fraser, Colorado, USA Alpine/Tundra/ Taiga/Prairie Inuvik, Canada, Tundra Kuparuk, Alaska, Tundra

11. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 11 ESA UNCLASSIFIED – For Official Use CASIX campaign (2010-2011) Acquiring ground-based scatterometer backscatter responses (X-band + Ku-band) and sensitivities to five different land cover types: tundra, fen/bog, forest, lake ice, first year sea ice @ Churchill, Manitoba, Canada Snow temperature Ground in-situ measurements included: magnaprobe measurements (snow depth), SWE, ice thickness, ice cores, snow depth, snow stratigraphy, soil sampling, soil surface roughness, …. ° (dB) at Ku-band (17.2 GHz) and X-band (9.6 GHz),  = 39°, versus SWE in snow pits @ Tundra site TundraFenForestLakeSea ice Traditional snow grain size Snow pit ©UW

12. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 12 ESA UNCLASSIFIED – For Official Use NOSREX campaigns (2009-2013) Intensive Observation Site Measurement towers for instrument installation (5 m, 8m, 30m) In vicinity of meteorological observations Manual snow cover measurements on site Automatic sensors for SWE, snow depth, soil moisture, soil and snow temperature profiles. Accurate characterisation of snow stratigraphy with measurements of near-infrared (NIR) photography, high-resolution penetrometry and casted snow samples. Detailed measurements by means of SnowScat for snow stratigraphy L to W band radiometers Snow pits Near-continuous X to Ku band scatterometer measurements for 4 winters (SnowScat developed by Gamma Remote Sensing) Automatic sensors (Temperature, bulk SWE, SD) Photo: webcam on 30 m tower Test field ©FMI

13. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 13 ESA UNCLASSIFIED – For Official Use SnowSAR acquisitions (2011, 2011/2012) SnowSAR flights in March 2011 and winter 2011/2012 over NOSREX area (every 15 days to mimic CoReH2O’s temporal sampling in the second mission phase) ca. 70 km2 between Sodankylä and lake Orajärvi covering Taiga, bogs, Tundra and sea ice sites 23 flight lines, 8 Km long, 400 m apart; 2 additional flight lines, covering the main in situ data sites from a different look angle 1 mission entirely dedicated to calibration; 14 corner reflectors (co- and cross-pol) on the field extensive in-situ snow (depth and SWE) course measurements to compare to airborne data ©MetaSensing TundraSea iceTaiga Corner reflectors for calibration Snow course measurements Measurements with SnowSAR

14. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 14 ESA UNCLASSIFIED – For Official Use First SWE retrievals using SnowSAR data SnowSAR SWE retrieval in line with ground measurements; Average accumulation 7 to 26 February 2012: retrieved= 37 mm / in-situ= 41 mm Example of CoReH 2 O Phase 2 data sequence (~15 day repeat) ©ENVE O SWE - Snow Accumulation Map SnowSAR σ 0 difference February 26 – 7, 2012 CoReH 2 O Retrieval ©ENVEO©FMI

15. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 15 ESA UNCLASSIFIED – For Official Use Trail Valley Creek Experiment (2012-2013) The primary objectives of this campaign are to evaluate SWE retrievals from SnowSAR measurements using a detailed suite of ground measurements and to assess the impact of these observations on distributed hydrological models used operationally at Environment Canada SnowSAR flights (13.+14. March 2013 & April 2013) at Trail Valley Creek watershed near Inuvik, Northwest Territories, Canada including tundra/forest transition areas, tundra sites and open canopy/northern boreal forest In-situ ground measurements include transects of georeferenced snow depth using Magnaprobes, transects of bulk SWE and density from snow courses, traditional snowpits and NIR photography for stratigraphy, ground-based LiDAR, sled-based ground penetrating radar, passive microwave radiometers, correlation length from snow micropenetrometer 12 corner reflectors used for calibration Snow trenches as seen from the Cessna-208 Arctic landscape (tundra, open canopy/forest transition areas) Corner reflectors for calibration Ground-based lidar to perform scans of volumetric estimates of snow drifts

16. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 16 ESA UNCLASSIFIED – For Official Use AlpSAR (2012-2013) Primary objective is to acquire backscatter data for snow in mid-latitude regions and on glaciers. This includes effects of different types of background target, SWE retrievals for deep snow, snow accumulation on glaciers, effects of topography, segmentation for dry snow, wet snow, and the mapping of diagenetic facies on glaciers Three elevation/test areas covered near Innsbruck, Austria with SnowSAR: Leutasch (1100-1200 m a.s.l.), mosly flat terrain, surface types: grassland, agricultural fields, forests Rotmoostal/Obergurgl (2200 m a.s.l.), level terrain and slopes at different inclination angles, surface types: alpine tundra, alpine grassland, dwarf shrubs, bog Mittelbergferner (2900-3200 m a.s.l.), mountain glacier, glacier zones: ice zones, percolation zone Installation of IETR GB SAR at Leutasch and Rotmoos for 3D imaging (tomography) SnowSAR flights in November 2012, January 2013 and March 2013 Example of SnowSAR images at Ku-band, VH-pol ©MetaSensing

17. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 17 ESA UNCLASSIFIED – For Official Use Access to ESA Campaign Data All ESA campaign datasets formatted and documented are available through the ESA EOPI Portal Data inventory includes final reports with full description of campaign activity and analyses Access to datasets is provided through Category 1 mechanism (short proposal incl. identification of desired datasets) Data archive continuously increase in number and variety of campaign datasets Currently 43 campaign datasets available http://eopi.esa.int

18. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 18 ESA UNCLASSIFIED – For Official Use Outlook with regard to campaigns: planning of Arctic campaign in 2014 Objective a.Compare Cryosat-2 engineering and ice thickness measurements with airborne reference b.Location over sea ice in Arctic Beaufort, Canada c.Time frame: March/April 2014 d.ESA/NASA collaboration (augment measurements and enhance science return) e.Potentially X-band+Ku-band SAR deployment, detailed insitu-data would be desired Experiment details a.Experimenter meeting planned before summer Radar altimeter + Laser scanner EM Bird ice thickness Field support

19. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 19 ESA UNCLASSIFIED – For Official Use User Consultation Meeting Mission Assessment Groups / Phase 0 Reports for Assessment ESAC Recommendation / PB-EO Selection Step 2: Mission Assessment (Phase 0)  Spring 2007 - 2008  Autumn 2008  20-21 January 2009  February 2009 6 Mission Advisory Groups / Phase A Reports for Mission Selection User Consultation Meeting ESAC Recommendation / PB-EO Selection Step 3: Mission Feasibility (Phase A)  2010-2011 3 BIOMASS CoReH 2 O PREMIER  2013 Implementation Step 4: Implementation (Phases B, C/D, E1)  2013-2018 BIOMASS is recommended; selection in May @ PB-EO Call for Ideas ESAC Recommendation / PB-EO Selection  March - July 2005  May 2006 24 Step 1: Call and selection ESA’s 7 th Earth Explorer Mission Selection Process and Outcome

20. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 20 ESA UNCLASSIFIED – For Official Use Questions for discussion Which snow pack structure instrumentation is available? What is the “best” field sampling strategy (temporal, spatial (horizontal, vertical))? What are the available methods to investigate and retrieve snow structural properties from field instrumentation and how do they compare? How to link field observations of snow pack structure to (available) models? How to model snow grain growth, snow layering? How to use and link field snow information to remote-sensing data (active/passive microwave data retrieved snow properties, keywords: correlation length, effective grain size)? ©WSL

21. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 21 ESA UNCLASSIFIED – For Official Use Thank you

22. ESA Presentation | Michael Kern | Grenoble, France | 02/04/2013 | Slide 22 ESA UNCLASSIFIED – For Official Use Selection criteria 1.Relevance to the ESA Research Objectives for Earth Observation 2.Need, Usefulness and Excellence 3.Uniqueness and Complementarity 4.Degree of Innovation and Contribution to the Advancement of the European Earth Observation Capabilities 5.Feasibility and Level of Maturity 6.Timeliness 7.Programmatics