SnowEx: a NASA airborne campaign leading to a snow satellite mission SnowEx Organizing Committee: Edward Kim, Charles Gatebe, Dorothy Hall, Matthew Sturm, Noah Molotch, Chris Crawford, DK Kang, Eugenia De Marco, with contributions by many others NASA Headquarters Program Manager: Jared Entin June 14, 2016 Snow Watch Columbus, Ohio

Outline Background Sites Instruments & Aircraft Satellite Mission Concept Summary For more information, see http://snow.nasa.gov 12/3/2018

What is SnowEx? A multi-year airborne snow campaign designed to collect multi-sensor aircraft data and ground truth measurements to enable algorithm development and design a future satellite mission SnowEx is all about challenging the sensing techniques and algorithms…. to learn when, where and how each technique works alone, or in synergy with other techniques, and why 12/3/2018

SnowEx Driving Questions What is the optimum combination of sensing techniques to measure regional (global) SWE? global snow melt/energy balance (where, when, how fast)? The SnowEx experiment design must be developed in the context of a future spaceborne measurement system 12/3/2018

When is SnowEx? Year 1 = 2016/17 fall and winter: campaigns Year 2 = 2017/18 winter: no campaign Year 3 = 2018/19 winter : campaign Year 4 = 2019/20 winter : campaign Year 5 = 2020/21 winter : campaign “Campaign” includes (ideally) Fall -- no-snow background observations with lidar and radar Winter -- dry snow observations with full sensor suite 12/3/2018

Where will SnowEx take place? In Year 1 the experiment will take place in Western Colorado Grand Mesa – meets all four Year 1 requirements Uncompaghre/Senator Beck – good but lacks adequate flat terrain to be the main site Site selection was primarily based on the requirements needed to achieve SnowEx objectives See snow.nasa.gov for a comparison of sites, and for further details on potential sites 12/3/2018

Site Requirements (1) Probability of wet snow is very low (2) Existence of a shallow to deep gradient in snow depths and SWE (3) Snow-covered area with flat terrain that is larger than airborne instrument swath widths (4) Forested stands with variable density and height 12/3/2018

Forest-Cover Gradient 12/3/2018

Advantages/Strengths Remote Sensing techniques for global snow Radar (SAR): senses SWE and melt, high resolution through clouds and darkness Passive MW: senses SWE and melt through clouds and darkness (very long record from satellite data) Lidar: snow depth, accuracy acceptable for deeper snow, SWE (need density), very high resolution, possibly through forest gaps Multispectral: MODIS/VIIRS, fSCA, albedo, grain size, IR, moderate spatial resolution Hyperspectral: fSCA, albedo, surface grain size, moderate/high spatial resolution 12/3/2018

Instruments From the 2016 Seattle iSWGR / SnowEx workshop, the core sensor types for Year 1 are: Lidar Radar (SAR) Passive microwave Passive VIS/IR Radiometer for sensing BRDF 12/3/2018

JPL’s Airborne Snow Observatory (ASO) has been selected by HQ for Year 1 ASO uses a Riegl Q1560 scanning lidar, which captures the surface topography with <10 cm vertical accuracy. Depth is calculated by subtracting a summer “snow-free” dataset from each winter “snow-on” dataset. The accuracy of these data is dependent upon precise knowledge of the aircraft position during the measurements. An integrated Applanix Inertial Measurement Unit (IMU) and GPS provide aircraft attitude and position information, and this information is combined with error corrections from an existing network of GPS base stations at fixed locations near the survey area. This combined use of the IMU for high-speed attitude information, along with the differential GPS solution for absolute position, yields the sub-decimeter aircraft trajectory accuracy necessary for LiDAR snow depth measurements. http://aso.jpl.nasa.gov/ 12/3/2018

ESA’s SnowSAR Twin frequency [9.6 and 17.2 GHz (X- and Ku- bands)] polarimetric Synthetic Aperture Radar High frequencies will allow the study of both the surface and underlying layers of the snowpack because they have different backscattering properties ESA commissioned MetaSensing, a company based in Noordwijk, The Netherlands, to develop and test the SnowSAR instrument 12/3/2018

The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) The AESMIR is a passive microwave airborne imager with 6 microwave bands (6, 10, 18, 23, 36, 89 GHz) with 4-Stokes polarization capability (except at 23 GHz) 18 & 36 GHz, V &H pols are useful for snow; 10 & 89 GHz are of secondary interest for snow Programmable scan modes include conical and cross-track scanning Requires heavy-lift aircraft such as a P-3 aircraft http://science.gsfc.nasa.gov/sci/index.cfm?fuseAction=projects.view&project_id=336 12/3/2018

Passive VIS/IR Cloud Absorption Radiometer (CAR) More info at BRDF capability Multi-spectral: 14 bands (0.34 to 2.29 µm) Mature More info at http://car.gsfc.nasa.gov/ Publication: http://car.gsfc.nasa.gov/publications/pdf/Gatebe_and_King_2016.pdf 12/3/2018

Snow mission concepts Must address global snow Therefore must include multiple sensors (community consensus) Active & passive mw, lidar, multi-spectral VIS/IR Need mature technology and algorithms SCLP and CoReH2O both suffered on radar algorithms Satellite mission must avoid high cost Leverage existing assets (satellite PM and multispectral) But some satellite assets might go away (PM?) International partnering is the key to Leveraging technology and algorithm development investments Spreading costs Some sensors can/should be suborbital E.g., Lidar on aircraft and other sensors on satellites Societal benefits and science return already strong 12/3/2018

Summary SnowEx: a NASA airborne campaign leading to a snow satellite mission Instrument payload designed to determine what combination of sensors provides the optimum results for measuring SWE, BRDF, surface temperature and mass SnowEx Year 1, 2016-17, will be held in Western Colorado – fall and winter campaigns Out years (2018-19, 2019-20 and 2020-21) will likely take place in other locations 12/3/2018