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Unmanned Aerial System Nadir Reflectance and MODIS Nadir BRDF

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Unmanned Aerial System Nadir Reflectance and MODIS Nadir BRDF The Cryosphere, 11, 1575–1589, 2017 https://doi.org/10.5194/tc-11-1575-2017 © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License. Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland John Faulkner Burkhart1,2, Arve Kylling3, Crystal B. Schaaf4, Zhuosen Wang5,6, Wiley Bogren7, Rune Storvold8, Stian Solbø8, Christina A. Pedersen9, and Sebastian Gerland9 1Department of Geosciences, University of Oslo, Oslo, Norway 2University of California, Merced, CA, USA 3Norwegian Institute for Air Research, Kjeller, Norway 4School for the Environment, University of Massachusetts Boston, Boston, MA, USA 5NASA Goddard Space Flight Center, Greenbelt, MD, USA 6Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA 7U.S. Geological Survey, Flagstaff, AZ, USA 8Norut-Northern Research Institute, Tromsø, Norway 9Norwegian Polar Institute, Fram Centre, Tromsø, Norway Correspondence to: John Faulkner Burkhart ([email protected]) Received: 12 November 2016 – Discussion started: 15 December 2016 Revised: 17 May 2017 – Accepted: 18 May 2017 – Published: 4 July 2017 Abstract. Albedo is a fundamental parameter in earth sci- data demonstrate potentially large sub-pixel variability of ences, and many analyses utilize the Moderate Resolu- MODIS reflectance products and the potential to explore this tion Imaging Spectroradiometer (MODIS) bidirectional re- variability using the UAS as a platform. It is also found that, flectance distribution function (BRDF)/albedo (MCD43) al- even at the low elevations flown typically by a UAS, re- gorithms. While derivative albedo products have been eval- flectance measurements may be influenced by haze if present uated over Greenland, we present a novel, direct compar- at and/or below the flight altitude of the UAS. This impact ison with nadir surface reflectance collected from an un- could explain some differences between data from the two manned aerial system (UAS). The UAS was flown from platforms and should be considered in any use of airborne Summit, Greenland, on 210 km transects coincident with the platforms. MODIS sensor overpass on board the Aqua and Terra satel- lites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking 1 Introduction spectrometers (300–920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands Albedo, the ratio of reflected to incident energy at the sur- 1, 3, and 4. The data provide a unique opportunity to di- face of the earth, is a fundamental parameter in energy bal- rectly compare UAS nadir reflectance with the MODIS nadir ance computations, and therefore any prediction of climate BRDF-adjusted surface reflectance (NBAR) products. The must account for albedo through a parameterization process data show UAS measurements are slightly higher than the (Henderson-Sellers and Wilson, 1983). Generally climate MODIS NBARs for all bands but agree within their stated models rely on simplified estimations of albedo as single- uncertainties. Differences in variability are observed as ex- value climatological means of broadband albedo that are a pected due to different footprints of the platforms. The UAS function of seasonal changes in surface characteristics and the presence of snow (Curry and Schramm, 2001). For mod- Published by Copernicus Publications on behalf of the European Geosciences Union. 1576 J. F. Burkhart et al.: UAS–MODIS reflectances eling snow and ice melt processes on the earth’s surface, Collection 6 (C6) data, and show a marked improvement of albedo is a critical parameter, providing the most coarse ad- the MODIS C6 retrieval. Prior studies relied predominately justment with respect to available energy to drive melt. Satel- on existing GrIS fixed station data from the Greenland Cli- lite instruments play an important role in providing a charac- mate Network (GC-Net) of automatic weather stations (Box terization of albedo of the surface of earth that is relevant for et al., 2012; Stroeve et al., 2005, 2006, 2013). To our knowl- climate and earth system modeling. edge most investigations have compared ground-based mea- Stroeve et al.(2005) and more recently Stroeve et al. surements of albedo with satellite albedo products. While (2013) have carefully evaluated the Moderate Resolution this is valuable, one must recognize that albedo products are Imaging Spectroradiometer (MODIS) albedo products over developed through a processing chain of models and there- Greenland. Several further studies have evaluated presently fore do not represent a direct measurement, making compar- available satellite products and compared these products with isons complicated. ground-based observations. This recent body of work has Recently, the advent of relatively low-cost unmanned air- been largely spurred by the 2012 melt events on the Green- borne systems (UASs) has created a rush to utilize this novel land Ice Sheet (GrIS). These events, recorded by MODIS platform to provide unique data sets otherwise unobtainable satellite observations, have been linked to albedo feedback without manned flight. Furthermore, UASs provide a unique stemming from thermodynamic processes (Box et al., 2012). niche in the ability to characterize cryospheric surfaces in Dumont et al.(2014), Goelles et al.(2015), and Keegan et al. relatively localized regions at higher resolutions than may be (2014) attribute some of the darkening to deposition of soot possible with traditional aircraft, and they certainly offer the from forest fires, pollution, and dust, while others have linked potential to extend the observational range of a traditional the changes predominately to delivery of warm water vapor ground-based campaign (Bhardwaj et al., 2016). In one of and low-level clouds (Bennartz et al., 2013; Miller et al., the first applications of a UAS for cryospheric characteri- 2015). zation, Hakala et al.(2014) demonstrated the potential for Due to the impact on snow and ice albedo, the Intergovern- BRDF measurements from a simple quadcopter. Immerzeel mental Panel on Climate Change (IPCC) identified black car- et al.(2014) used a UAS to characterize glacial dynamics bon on snow as an important process driving changes in the in the Himalaya, while numerous other have recently ap- cryospheric energy balance with significant associated un- plied structure from motion photogrammetry to several ap- certainty (IPCC, 2013). These findings are based on research plications related to snow and ice surfaces (e.g., Jagt et al., that has focused on the theoretical response of snow to black 2015; Ryan et al., 2015; Rippin et al., 2015). Most recently, carbon deposition (Warren and Wiscombe, 1980; Hansen and Ryan et al.(2017) have attempted to use cameras to measure Nazarenko, 2004). Subsequent studies have shown that small albedo from a UAS on board a fixed-wing platform on the changes in snow albedo globally may have significant im- perimeter of Greenland. pact on the top-of-atmosphere forcing and could be driving a Herein we provide a first-of-a-kind, “apples-to-apples” component of the Arctic warming witnessed today (Flanner evaluation of the accuracy of the MODIS nadir BRDF- et al., 2009). However, presenting a distinct challenge, War- adjusted reflectance (NBAR) retrievals through intercompar- ren(2012) suggests that the changes anticipated from this ison with reflectance observed from a UAS platform over effect are below the present-day measurement capabilities. Greenland. The advent of UASs presents an immense op- Numerous studies have used ground-based measurements portunity to spatially assess the accuracy of satellite sensors, to compare and validate satellite sensor data, a necessary pro- versus simple validation against ground point observations. cess to assess accuracy of the observations, and particularly However, as discussed in this work, there are a host of com- to understand the variability that may be missed by differ- plications that must be considered. We explore those further ent sensor footprint scales. A seminal study is that of Sa- herein. lomonson and Marlatt(1971), who conducted an evaluation In this study, spectral reflectance measurements made of surface reflectance conditions for application to retrievals from a UAS flying in the dry snow region near Summit, from the Medium-Resolution Infrared Radiometer (MRIR) Greenland, are used to evaluate sub-pixel-scale variability instrument aboard the Nimbus II and III satellites. The study of the MODIS NBAR retrievals. The campaign was con- focused on the measurement of bidirectional reflectance dis- ducted in 2010 and provides data for two transects on sep- tribution function (BRDF) over a variety of terrestrial sur- arate days coincident with the near nadir subtrack of the faces. Appreciable anisotropy on all the surfaces was found, MODIS instrument overpasses. Due to the pristine nature leading to the conclusion of the importance of using a BRDF of the snow surface in this area, and the limited influence model for satellite retrievals – a standard application today of aerosols and warm temperatures, albedo and reflectance (Schaaf et al., 2002; Jin, 2003; Román et al., 2009; Ju et al., variability in this region is expected to be less than 10 %, 2010; Wang et al., 2014). and potentially as low as 3 % – within the 5 % stated accu- Wright et al.(2014) intercompare ground-based spectral racy of the MODIS
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