Seasonal evolution of supraglacial lake volume from ASTER imagery

AbstractWater stored in and released from supraglacial lakes is an important factor when considering the seasonal and long-term evolution of the Greenland ice sheet. Here we use a radiative transfer model to estimate changes in the depth and volume of a supraglacial lake on the surface of Jakobshavn Isbræ, West Greenland, between 2002 and 2005. When compared to estimates of the lake depth determined from airborne lidar observations, we estimate that the root-mean-square departure of the modelled lake depths was 0.3 m during cloud-free conditions. The maximum lake area, depth and volume were 3.4 km2, 9.6 ±1.0 m and (18.6±3.7)×106 m3, respectively. When sequenced according to the number of positive degree-days (PDDs) accumulated prior to each image, we observe that the lake volume evolves in three distinct phases. At the start of the melting season, the rate of filling is slow; after approximately 80 PDDs the rate of filling increases by a factor ∽3, and after approximately 125 PDDs the lake drains rapidly. We estimate that the lake drains at a minimum rate of (2.66±0.53)×106 m3 d–1 over a 6 day period.

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Glacier algae accelerate melt rates on the western Greenland Ice Sheet

10.5194/tc-2019-58 ◽

2019 ◽

Cited By ~ 2

Author(s):

Joseph M. Cook ◽

Andrew J. Tedstone ◽

Christopher Williamson ◽

Jenine McCutcheon ◽

Andrew J. Hodson ◽

...

Keyword(s):

Sea Level ◽

Ice Sheet ◽

Algal Growth ◽

Greenland Ice Sheet ◽

Remote Sensing Data ◽

Radiation Absorption ◽

Radiative Transfer Model ◽

Transfer Model ◽

Active Growth ◽

Ice Surface

Abstract. Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface that increase solar radiation absorption. This biological albedo reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a novel radiative transfer model, supervised classification of UAV and satellite remote sensing data and runoff modelling to calculate biologically-driven ice surface ablation and compare it to the albedo reducing effects of local mineral dust. We demonstrate that algal growth led to an additional 5.5–8.0 Gt of runoff from the western sector of the GrIS in summer 2016, representing 6–9 % of the total. Our analysis confirms the importance of the biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland’s future sea level contribution, especially because both the bare ice zones available for algal colonization and the length of the active growth season are set to expand in the future.

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Polar Stratospheric Clouds detection at Belgrano II Antarctic station from DOAS measurements

10.5194/egusphere-egu21-3054 ◽

2021 ◽

Author(s):

Laura Gómez Martín ◽

Daniel Toledo ◽

Margarita Yela ◽

Cristina Prados-Román ◽

José Antonio Adame ◽

...

Keyword(s):

Radiative Transfer ◽

Color Index ◽

Radiative Transfer Model ◽

Optical Absorption Spectroscopy ◽

Transfer Model ◽

Meteorological Model ◽

Weather Forecasts ◽

Stratospheric Temperature ◽

Stratospheric Clouds

Ground-based zenith DOAS (Differential Optical Absorption Spectroscopy) measurements have been used to detect and estimate the altitude of PSCs over Belgrano II Antarctic station during the polar sunrise seasons of 2018 and 2019. The method used in this work studies the evolution of the color index (CI) during twilights. The CI has been defined here as the ratio of the recorded signal at 520 and 420 nm. In the presence of PSCs, the CI shows a maximum at a given solar zenith angle (SZA). The value of such SZA depends on the altitude of the PSC. By using a spherical Monte Carlo radiative transfer model (RTM), the method has been validated and a function relating the SZA of the CI maximum and the PSC altitude has been calculated. Model simulations also show that PSCs can be detected and their altitude can be estimated even in presence of optically thin tropospheric clouds or aerosols. Our results are in good agreement with the stratospheric temperature evolution obtained through the ERA5 data reanalysis from the global meteorological model ECMWF (European Centre for Medium Range Weather Forecasts) and the PSCs observations from CALIPSO (Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations).The methodology used in this work could also be applied to foreseen and/or historical measurements obtained with ground-based spectrometers such e. g. the DOAS instruments dedicated to trace gas observation in Arctic and Antarctic sites. This would also allow to investigate the presence and long-term evolution of PSCs.Keywords: Polar stratospheric clouds; color index; radiative transfer model; visible spectroscopy.

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Investigating Controls on the Formation and Distribution of Wintertime Storage of Water in Supraglacial Lakes

Frontiers in Earth Science ◽

10.3389/feart.2020.00370 ◽

2020 ◽

Vol 8 ◽

Author(s):

Derrick Julius Lampkin ◽

Lora Koenig ◽

Casey Joseph ◽

Jason Eric Box

Keyword(s):

Ice Sheet ◽

Greenland Ice Sheet ◽

Lake Area ◽

Channel Networks ◽

Supraglacial Lakes ◽

Lake Model ◽

Temporal Occurrence ◽

Atmospheric Factors ◽

And Behavior ◽

Percolation Zone

Supraglacial lakes over the Greenland Ice Sheet can demonstrate multi-model drainage states. Lakes can demonstrate incomplete drainage, where residual melt can become buried under ice and snow and survive throughout the winter. We evaluate atmospheric factors that influence the propensity for the formation of buried lakes over the ice sheet. We examine the spatial and temporal occurrence and behavior of buried lakes over the Jakobshavn Isbrae and Zachariae Isstrøm outlet basins and assess the magnitude of insolation necessary to preserve melt water using a numerical lake model from 2009 to 2012. Buried lakes tend to occur at higher elevations within the ablation zone and those present at elevations > 1000 m tend to reoccur over several seasons. Lakes without buried water are relatively small (∼1 km2), whereas lakes with buried water are larger (∼6–10 km2). Lake area is correlated with the number of seasons sub-surface water persists. Buried lakes are relatively deep and associated with complex supraglacial channel networks. Winter stored water could be a precursor to the formation of supraglacial channels. Simulations of the insulation potential of accumulated snow and ice on the surface of lakes indicate substantial regional differences and inter-annual variability. With the possibility of inland migration of supraglacial lakes, buried lakes could be important in the evolution of ablation/percolation zone hydrology.

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Estimating the volume of Alpine glacial lakes

Earth Surface Dynamics ◽

10.5194/esurf-3-559-2015 ◽

2015 ◽

Vol 3 (4) ◽

pp. 559-575 ◽

Cited By ~ 37

Author(s):

S. J. Cook ◽

D. J. Quincey

Keyword(s):

Glacial Lake ◽

Lake Area ◽

Empirical Relationships ◽

Main Trunk ◽

Data Set ◽

Global Database ◽

Lake Volume ◽

Supraglacial Lakes ◽

Glacial Lake Outburst Flood ◽

Downstream Communities

Abstract. Supraglacial, moraine-dammed and ice-dammed lakes represent a potential glacial lake outburst flood (GLOF) threat to downstream communities in many mountain regions. This has motivated the development of empirical relationships to predict lake volume given a measurement of lake surface area obtained from satellite imagery. Such relationships are based on the notion that lake depth, area and volume scale predictably. We critically evaluate the performance of these existing empirical relationships by examining a global database of glacial lake depths, areas and volumes. Results show that lake area and depth are not always well correlated (r2 = 0.38) and that although lake volume and area are well correlated (r2 = 0.91), and indeed are auto-correlated, there are distinct outliers in the data set. These outliers represent situations where it may not be appropriate to apply existing empirical relationships to predict lake volume and include growing supraglacial lakes, glaciers that recede into basins with complex overdeepened morphologies or that have been deepened by intense erosion and lakes formed where glaciers advance across and block a main trunk valley. We use the compiled data set to develop a conceptual model of how the volumes of supraglacial ponds and lakes, moraine-dammed lakes and ice-dammed lakes should be expected to evolve with increasing area. Although a large amount of bathymetric data exist for moraine-dammed and ice-dammed lakes, we suggest that further measurements of growing supraglacial ponds and lakes are needed to better understand their development.

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Airborne Hyperspectral Imaging for Submerged Archaeological Mapping in Shallow Water Environments

Remote Sensing ◽

10.3390/rs11192237 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2237 ◽

Cited By ~ 5

Author(s):

Alexandre Guyot ◽

Marc Lennon ◽

Nicolas Thomas ◽

Simon Gueguen ◽

Tristan Petit ◽

...

Keyword(s):

Remote Sensing ◽

Shallow Water ◽

Water Column ◽

Sea Level ◽

Hyperspectral Imagery ◽

Airborne Lidar ◽

Radiative Transfer Model ◽

Invasive Technique ◽

Transfer Model ◽

Water Bottom

Nearshore areas around the world contain a wide variety of archeological structures, including prehistoric remains submerged by sea level rise during the Holocene glacial retreat. While natural processes, such as erosion, rising sea level, and exceptional climatic events have always threatened the integrity of this submerged cultural heritage, the importance of protecting them is becoming increasingly critical with the expanding effects of global climate change and human activities. Aerial archaeology, as a non-invasive technique, contributes greatly to documentation of archaeological remains. In an underwater context, the difficulty of crossing the water column to reach the bottom and its potential archaeological information usually requires active remote-sensing technologies such as airborne LiDAR bathymetry or ship-borne acoustic soundings. More recently, airborne hyperspectral passive sensors have shown potential for accessing water-bottom information in shallow water environments. While hyperspectral imagery has been assessed in terrestrial continental archaeological contexts, this study brings new perspectives for documenting submerged archaeological structures using airborne hyperspectral remote sensing. Airborne hyperspectral data were recorded in the Visible Near Infra-Red (VNIR) spectral range (400–1000 nm) over the submerged megalithic site of Er Lannic (Morbihan, France). The method used to process these data included (i) visualization of submerged anomalous features using a minimum noise fraction transform, (ii) automatic detection of these features using Isolation Forest and the Reed–Xiaoli detector and (iii) morphological and spectral analysis of archaeological structures from water-depth and water-bottom reflectance derived from the inversion of a radiative transfer model of the water column. The results, compared to archaeological reference data collected from in-situ archaeological surveys, showed for the first time the potential of airborne hyperspectral imagery for archaeological mapping in complex shallow water environments.

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Inter-Calibration of nine UV sensing instruments over Antarctica and Greenland since 1980: impact on global UV cloud albedo trends

10.5194/egusphere-egu2020-10856 ◽

2020 ◽

Author(s):

Clark Weaver ◽

Gordon Labow ◽

Dong Wu ◽

Pawan K. Bhartia ◽

David Haffner

Keyword(s):

Zenith Angle ◽

Forest Fires ◽

Solar Zenith Angle ◽

Radiative Transfer Model ◽

Transfer Model ◽

Cloud Albedo ◽

Enso Events ◽

Modeling Analysis ◽

Long Term Trend

A suite of NASA/NOAA UV (340nm) sensing satellite instruments, starting with Nimbus-7 SBUV in 1980, provides a global long-term record of cloud trends and cloud response from ENSO events. We present new method to inter-calibrate the radiances of all the SBUV instruments and the Suomi NPP OMPS mapper over both the East Antarctic Plateau and Greenland ice sheets during summer. First, the strong solar zenith angle dependence from the intensities are removed using an empirical approach rather than a radiative transfer model. Then small multiplicative adjustments are made to these solar zenith angle normalized intensities in order to minimize differences when two or more instruments temporally overlap. While the calibrated intensities show a negligible long-term trend over Antarctica, and a statistically insignificant UV albedo trend of -0.05 % per decade over the interior of Greenland, there are small episodic reductions in&#160;intensities which are often seen by multiple instruments. Three of these darkening events are explained by boreal forest fires using trajectory modeling analysis. Other events are caused by surface melting or volcanoes. We estimate a 2-sigma uncertainty&#160;of 0.35% for the calibrated radiances. Finally, we connect the estimated radiance uncertainties, derived from our calibration approach, to the tropical and midlatitude UV cloud albedo trends.

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A LONG TERM FIELD EXPERIMENT FOR RADIATIVE TRANSFER MODEL DEVELOPMENT AND LAND SURFACE PROCESSES REMOTE SENSING

PROCEEDINGS OF HYDRAULIC ENGINEERING ◽

10.2208/prohe.52.13 ◽

2008 ◽

Vol 52 ◽

pp. 13-18

Author(s):

Hui LU ◽

Toshio KOIKE ◽

Hiroyuki TSUTSUI ◽

David Ndegwa KURIA ◽

Tobias GRAF ◽

...

Keyword(s):

Remote Sensing ◽

Radiative Transfer ◽

Field Experiment ◽

Land Surface ◽

Model Development ◽

Surface Processes ◽

Radiative Transfer Model ◽

Transfer Model ◽

Term Field

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Analysis of Long-Term Solar Resource Variability Using NSRDB Version 3

10.5194/ems2021-193 ◽

2021 ◽

Author(s):

Manajit Sengupta ◽

Aron Habte

Keyword(s):

Solar Radiation ◽

Spatial Variability ◽

Temporal Variability ◽

Radiative Transfer Model ◽

Transfer Model ◽

Spatial And Temporal Variability ◽

Cloud Optical Depth ◽

Resource Variability ◽

Solar Resource

Understanding long-term solar resource variability is essential for planning and deployment of solar energy systems. These variabilities occur due to deterministic effects such as sun cycle and nondeterministic such as complex weather patterns. The NREL&#8217;s National Solar Radiation Database (NSRDB) provides long term solar resource data covering 1998- 2019 containing more than 2 million pixels over the Americas and gets updated on an annual basis. This dataset is satellite-based and uses a two-step physical model for it&#8217;s development. In the first step we retrieve cloud properties such as cloud mask, cloud type, cloud optical depth and effective radius. The second step uses a fast radiative transfer model to compute solar radiation. &#160;This dataset is ideal for studying solar resource variability. For this study, NSRDB version 3 which contains data from 1998-2017 on a half hourly and 4x4 km temporal and spatial resolution was used. The study analyzed the spatial and temporal trend of solar resource of global horizontal irradiance (GHI) and direct normal irradiance (DNI) using long-term 20-years NSRDB data. The coefficient of variation (COV) was used to analyze the spatio-temporal interannual and seasonal variabilities. The spatial variability was analyzed by comparing the center pixel to neighboring pixels. The spatial variability result showed higher COV as the number of neighboring pixels increased. Similarly, the temporal variability for the NSRDB domain ranges on average from &#177;10% for GHI and &#177;20% for DNI. Furthermore, the long-term variabilities were also analyzed using the K&#246;ppen-Geiger climate classification. This assisted in the interpretation of the result by reducing the originally large number of pixels into a smaller number of groups. This presentation will provided a unique look at long-term spatial and temporal variability of solar radiation using high-resolution satellite-based datasets.

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Radiance-based Retrieval Bias Mitigation for the MOPITT Instrument: The Version 8 Product

10.5194/amt-2019-41 ◽

2019 ◽

Cited By ~ 1

Author(s):

Merritt N. Deeter ◽

David P. Edwards ◽

Gene L. Francis ◽

John C. Gille ◽

Debbie Mao ◽

...

Keyword(s):

Fossil Fuels ◽

Atmospheric Transport ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Bias Drift ◽

Atmospheric Carbon Monoxide ◽

Nearly Continuous ◽

Retrieval Bias

Abstract. The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument has been making nearly continuous observations of atmospheric carbon monoxide (CO) since 2000. Satellite observations of CO are routinely used to analyze emissions from fossil fuels and biomass burning, and the atmospheric transport of those emissions. Recent enhancements to the MOPITT retrieval algorithm have resulted in the release of the Version 8 (V8) product. V8 products benefit from updated spectroscopic data for water vapor and nitrogen used to develop the operational radiative transfer model and exploit a new method for minimizing retrieval biases through parameterized radiance bias correction. Validation results illustrate clear improvements with respect to long-term bias drift and geographically variable retrieval bias.

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Global distribution of Earth's surface shortwave radiation budget

Atmospheric Chemistry and Physics ◽

10.5194/acp-5-2847-2005 ◽

2005 ◽

Vol 5 (10) ◽

pp. 2847-2867 ◽

Cited By ~ 108

Author(s):

N. Hatzianastassiou ◽

C. Matsoukas ◽

A. Fotiadi ◽

K. G. Pavlakis ◽

E. Drakakis ◽

...

Keyword(s):

Radiative Heating ◽

Surface Radiation ◽

Radiation Budget ◽

Shortwave Radiation ◽

Radiative Transfer Model ◽

Physical Parameters ◽

Transfer Model ◽

Data Set ◽

Global Mean

Abstract. The monthly mean shortwave (SW) radiation budget at the Earth's surface (SRB) was computed on 2.5-degree longitude-latitude resolution for the 17-year period from 1984 to 2000, using a radiative transfer model accounting for the key physical parameters that determine the surface SRB, and long-term climatological data from the International Satellite Cloud Climatology Project (ISCCP-D2). The model input data were supplemented by data from the National Centers for Environmental Prediction - National Center for Atmospheric Research (NCEP-NCAR) and European Center for Medium Range Weather Forecasts (ECMWF) Global Reanalysis projects, and other global data bases such as TIROS Operational Vertical Sounder (TOVS) and Global Aerosol Data Set (GADS). The model surface radiative fluxes were validated against surface measurements from 22 stations of the Baseline Surface Radiation Network (BSRN) covering the years 1992-2000, and from 700 stations of the Global Energy Balance Archive (GEBA), covering the period 1984-2000. The model is in good agreement with BSRN and GEBA, with a negative bias of 14 and 6.5 Wm-2, respectively. The model is able to reproduce interesting features of the seasonal and geographical variation of the surface SW fluxes at global scale. Based on the 17-year average model results, the global mean SW downward surface radiation (DSR) is equal to 171.6 Wm-2, whereas the net downward (or absorbed) surface SW radiation is equal to 149.4 Wm-2, values that correspond to 50.2 and 43.7% of the incoming SW radiation at the top of the Earth's atmosphere. These values involve a long-term surface albedo equal to 12.9%. Significant increasing trends in DSR and net DSR fluxes were found, equal to 4.1 and 3.7 Wm-2, respectively, over the 1984-2000 period (equivalent to 2.4 and 2.2 Wm-2 per decade), indicating an increasing surface solar radiative heating. This surface SW radiative heating is primarily attributed to clouds, especially low-level, and secondarily to other parameters such as total precipitable water. The surface solar heating occurs mainly in the period starting from the early 1990s, in contrast to decreasing trend in DSR through the late 1980s. The computed global mean DSR and net DSR flux anomalies were found to range within ±8 and ±6 Wm-2, respectively, with signals from El Niño and La Niña events, and the Pinatubo eruption, whereas significant positive anomalies have occurred in the period 1992-2000.

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