scholarly journals Radiometric calibration of a non-imaging airborne spectrometer to measure the Greenland ice sheet surface

2019 ◽  
Vol 12 (3) ◽  
pp. 1913-1933
Author(s):  
Christopher J. Crawford ◽  
Jeannette van den Bosch ◽  
Kelly M. Brunt ◽  
Milton G. Hom ◽  
John W. Cooper ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Response ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Spectral Irradiance ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Bare Rock ◽  
Sheet Surface

Abstract. Methods to radiometrically calibrate a non-imaging airborne visible-to-shortwave infrared (VSWIR) spectrometer to measure the Greenland ice sheet surface are presented. Airborne VSWIR measurement performance for bright Greenland ice and dark bare rock/soil targets is compared against the MODerate resolution atmospheric TRANsmission (MODTRAN®) radiative transfer code (version 6.0), and a coincident Landsat 8 Operational Land Imager (OLI) acquisition on 29 July 2015 during an in-flight radiometric calibration experiment. Airborne remote sensing flights were carried out in northwestern Greenland in preparation for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) laser altimeter mission. A total of nine science flights were conducted over the Greenland ice sheet, sea ice, and open-ocean water. The campaign's primary purpose was to correlate green laser pulse penetration into snow and ice with spectroscopic-derived surface properties. An experimental airborne instrument configuration that included a nadir-viewing (looking downward at the surface) non-imaging Analytical Spectral Devices (ASD) Inc. spectrometer that measured upwelling VSWIR (0.35 to 2.5 µm) spectral radiance (Wm-2sr-1µm-1) in the two-color Slope Imaging Multi-polarization Photon-Counting Lidar's (SIMPL) ground instantaneous field of view, and a zenith-viewing (looking upward at the sky) ASD spectrometer that measured VSWIR spectral irradiance (W m−2 nm−1) was flown. National Institute of Standards and Technology (NIST) traceable radiometric calibration procedures for laboratory, in-flight, and field environments are described in detail to achieve a targeted VSWIR measurement requirement of within 5 % to support calibration/validation efforts and remote sensing algorithm development. Our MODTRAN predictions for the 29 July flight line over dark and bright targets indicate that the airborne nadir-viewing spectrometer spectral radiance measurement uncertainty was between 0.6 % and 4.7 % for VSWIR wavelengths (0.4 to 2.0 µm) with atmospheric transmittance greater than 80 %. MODTRAN predictions for Landsat 8 OLI relative spectral response functions suggest that OLI is measuring 6 % to 16 % more top-of-atmosphere (TOA) spectral radiance from the Greenland ice sheet surface than was predicted using apparent reflectance spectra from the nadir-viewing spectrometer. While more investigation is required to convert airborne VSWIR spectral radiance into atmospherically corrected airborne surface reflectance, it is expected that airborne science flight data products will contribute to spectroscopic determination of Greenland ice sheet surface optical properties to improve understanding of their potential influence on ICESat-2 measurements.

scholarly journals Radiometric calibration of a non-imaging airborne spectrometer to measure the Greenland Ice Sheet surface

2018 ◽  
Author(s):  
Christopher J. Crawford ◽  
Jeannette van den Bosch ◽  
Kelly M. Brunt ◽  
Milton G. Hom ◽  
John W. Cooper ◽  
...  
Keyword(s):  
Surface Properties ◽  
Spectral Response ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Spectral Irradiance ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Bare Rock ◽  
Sheet Surface

Abstract. Methods to radiometrically calibrate a non-imaging airborne visible-to-shortwave infrared (VSWIR) spectrometer to measure the Greenland Ice Sheet surface are presented. Airborne VSWIR measurement performance is then benchmarked for bright Greenland ice and dark bare rock/soil targets using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer code (version 6.0), and a coincident Landsat 8 Operational Land Imager (OLI) acquisition on 29 July 2015 during an in-flight radiometric calibration experiment. Airborne remote sensing flights were carried out in northwestern Greenland in preparation for the Ice, Cloud and land Elevation Satellite 2 (ICESat-2) laser altimeter mission. Nine science flights were conducted over the Greenland Ice Sheet, sea ice, and open ocean water. The campaign’s primary purpose was to correlate green laser pulse penetration into snow and ice with spectroscopic derived surface properties. An experimental airborne instrument configuration that included a nadir viewing (downward looking at the surface) non-imaging Analytical Spectral Devices Inc. (ASD) spectrometer that measured at-sensor upwelling VSWIR (0.35 to 2.5 µm) spectral radiance (Watts/m−2/sr−1/nm−1) in the two color Slope Imaging Multi-polarization Photon-Counting Lidar’s (SIMPL) ground Instantaneous Field-of-View, and a zenith viewing (upward looking at the sky) ASD spectrometer that measured at-sensor VSWIR spectral irradiance (Watts/m−2/nm−1) was flown. Rigorous radiometric calibration procedures for laboratory, in-flight, and field environments are described in detail to achieve a targeted at-sensor VSWIR measurement requirement of within 5 % to support calibration/validation (cal/val) efforts and geophysical science algorithm development. Our MODTRAN simulations for the 29 July flight line over dark and bright targets indicate that the nadir viewing airborne VSWIR spectrometer achieved an at-sensor spectral radiance measurement accuracy of between 0.6 and 4.7 % for VSWIR wavelengths (0.4 to 2.0 µm) with atmospheric transmittance greater than 80 %. At-sensor MODTRAN simulations for Landsat 8 OLI relative spectral response functions suggest that OLI is measuring 6 to 16% more at-sensor top-of-atmosphere (TOA) spectral radiance from the Greenland Ice Sheet surface than was observed from the nadir viewing airborne VSWIR spectrometer. While more investigation is required to convert airborne at-sensor VSWIR spectral radiance into atmospherically-corrected airborne surface reflectance, it is expected that airborne science flight data products will contribute to spectroscopic determination of Greenland Ice Sheet surface properties to improve understanding of their potential influence on ICESat-2 measurements.

scholarly journals Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

2021 ◽  
Vol 13 (2) ◽  
pp. 227
Author(s):  
Arthur Elmes ◽  
Charlotte Levy ◽  
Angela Erb ◽  
Dorothy K. Hall ◽  
Ted A. Scambos ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Energy Budget ◽  
Landsat 8 ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Seasonal Snow Cover

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

scholarly journals Greenland ice sheet melt area from MODIS (2000–2014)

2020 ◽  
pp. 57-60
Author(s):  
Robert S. Fausto ◽  
Dirk Van As ◽  
Jens A. Antoft ◽  
Jason E. Box ◽  
William Colgan
Keyword(s):  
Global Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Internet Portal ◽  
Sheet Surface ◽  
Glacier Ice ◽  
Key Driver ◽  
Surface Melt ◽  
Global Sea Level ◽  
Terra Satellite

The Greenland ice sheet is an excellent observatory for global climate change. Meltwater from the 1.8 million km2 large ice sheet infl uences oceanic temperature and salinity, nutrient fl uxes and global sea level (IPCC 2013). Surface refl ectivity is a key driver of surface melt rates (Box et al. 2012). Mapping of diff erent ice-sheet surface types provides a clear indicator of where changes in ice-sheet surface refl ectivity are most prominent. Here, we present an updated version of a surface classifi cation algorithm that utilises NASA’s Moderateresolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite to systematically monitor ice-sheet surface melt (Fausto et al. 2007). Our aim is to determine the areal extent of three surface types over the 2000–2014 period: glacier ice, melting snow (including percolation areas) and dry snow (Cuff ey & Paterson 2010). Monthly 1 km2 resolution surface-type grids can be downloaded via the CryoClim internet portal (www.cryoclim.net). In this report, we briefl y describe the updated classifi cation algorithm, validation of surface types and inter-annual variability in surface types.

scholarly journals Estimation and Validation of Land Surface Temperature by using Remote Sensing & GIS for Chittoor District, Andhra Pradesh

2021 ◽  
Vol 12 (5) ◽  
pp. 607-617
Author(s):  
A. Rajani, Dr. S.Varadarajan
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Andhra Pradesh ◽  
Temperature Data ◽  
Sensor Data ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Thermal Band

Land Surface Temperature (LST) quantification is needed in various applications like temporal analysis, identification of global warming, land use or land cover, water management, soil moisture estimation and natural disasters. The objective of this study is estimation as well as validation of temperature data at 14 Automatic Weather Stations (AWS) in Chittoor District of Andhra Pradesh with LST extracted by using remote sensing as well as Geographic Information System (GIS). Satellite data considered for estimation purpose is LANDSAT 8. Sensor data used for assessment of LST are OLI (Operational Land Imager) and TIR (Thermal Infrared). Thermal band  contains spectral bands of 10 and 11 were considered for evaluating LST independently by using algorithm called Mono Window Algorithm (MWA). Land Surface Emissivity (LSE) is the vital parameter for calculating LST. The LSE estimation requires NDVI (Normalized Difference Vegetation Index) which is computed by using Band 4 (visible Red band) and band 5 (Near-Infra Red band) spectral radiance bands. Thermal band images having wavelength 11.2 µm and 12.5 µm of 30th May, 2015 and 21st October, 2015 were processed for the analysis of LST. Later on validation of estimated LST through in-suite temperature data obtained from 14 AWS stations in Chittoor district was carried out. The end results showed that, the LST retrieved by using proposed method achieved 5 per cent greater correlation coefficient (r) compared to LST retrieved by using existing method which is based on band 10.

scholarly journals Direct measurements of meltwater runoff on the Greenland ice sheet surface

2017 ◽  
Vol 114 (50) ◽  
pp. E10622-E10631 ◽  
Author(s):  
Laurence C. Smith ◽  
Kang Yang ◽  
Lincoln H Pitcher ◽  
Brandon T. Overstreet ◽  
Vena W. Chu ◽  
...  
Keyword(s):  
Sea Level ◽  
Surface Runoff ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Dynamics ◽  
Sheet Surface ◽  
Ice Surface ◽  
Meltwater Runoff ◽  
Direct Measurements ◽  
Peak Discharges

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2moulin-terminating internally drained catchment (IDC) on Greenland’s midelevation (1,207–1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.

scholarly journals Does sea ice influence Greenland ice sheet surface-melt?

2009 ◽  
Vol 4 (2) ◽  
pp. 024011 ◽  
Author(s):  
Asa K Rennermalm ◽  
Laurence C Smith ◽  
Julienne C Stroeve ◽  
Vena W Chu
Keyword(s):  
Sea Ice ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sheet Surface ◽  
Surface Melt

scholarly journals Seasonal changes of ice surface characteristics and productivity in the ablation zone of the Greenland Ice Sheet

2015 ◽  
Vol 9 (2) ◽  
pp. 487-504 ◽  
Author(s):  
D. M. Chandler ◽  
J. D. Alcock ◽  
J. L. Wadham ◽  
S. L. Mackie ◽  
J. Telling
Keyword(s):  
Remote Sensing ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Characteristics ◽  
Biological Processes ◽  
Ablation Zone ◽  
Ice Surface ◽  
Surface Productivity ◽  
Cryoconite Hole

Abstract. Field and remote sensing observations in the ablation zone of the Greenland Ice Sheet have revealed a diverse range of ice surface characteristics, primarily reflecting the variable distribution of fine debris (cryoconite). This debris reduces the surface albedo and is therefore an important control on melt rates and ice sheet mass balance. Meanwhile, studies of ice sheet surface biological processes have found active microbial communities associated with the cryoconite debris, which may themselves modify the cryoconite distribution. Due to the considerable difficulties involved with collecting ground-based observations of the ice surface, our knowledge of the physical and biological surface processes, and their links, remains very limited. Here we present data collected at a field camp established in the ice sheet ablation zone at 67° N, occupied for almost the entire melt season (26 May–10 August 2012), with the aim of gaining a much more detailed understanding of the physical and biological processes occurring on the ice surface. These data sets include quadrat surveys of surface type, measurements of ice surface ablation, and in situ biological oxygen demand incubations to quantify microbial activity. In addition, albedo at the site was retrieved from AVHRR (Advanced Very High Resolution Radiometer) remote sensing data. Observations of the areal coverage of different surface types revealed a rapid change from complete snow cover to the "summer" (summer study period) ice surface of patchy debris ("dirty ice") and cryoconite holes. There was significant correlation between surface albedo, cryoconite hole coverage and surface productivity during the melt season, but microbial activity in "dirty ice" was not correlated with albedo and varied widely throughout the season. While this link suggests the potential for a remote-sensing approach to monitoring cryoconite hole biological processes, very wide seasonal and spatial variability in net surface productivity demonstrates the need for caution when extrapolating point measurements of biological processes to larger temporal or spatial scales.

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