scholarly journals A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

2012 ◽  
Vol 25 (14) ◽  
pp. 4785-4798 ◽  
Author(s):  
Dorothy K. Hall ◽  
Josefino C. Comiso ◽  
Nicolo E. DiGirolamo ◽  
Christopher A. Shuman ◽  
Jeffrey R. Key ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Accuracy Assessment ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Quality Data ◽  
Climate Data ◽  
Clear Sky ◽  
Data Record ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Surface Temperature

Abstract The authors have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (IST) algorithm. Daily and monthly quality-controlled MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are presented at 6.25-km spatial resolution on a polar stereographic grid along with metadata to permit detailed accuracy assessment. The ultimate goal is to develop a climate data record (CDR) that starts in 1981 with the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the Visible Infrared Imager Radiometer Suite (VIIRS) era (the first VIIRS instrument was launched in October 2011). Differences in the APP and MODIS cloud masks have thus far precluded merging the APP and MODIS IST records, though this will be revisited after the APP dataset has been reprocessed with an improved cloud mask. IST of Greenland may be used to study temperature and melt trends and may also be used in data assimilation modeling and to calculate ice sheet mass balance. The MODIS IST climate-quality dataset provides a highly consistent and well-characterized record suitable for merging with earlier and future IST data records for climate studies. The complete MODIS IST daily and monthly data record is available online.

scholarly journals Melt probabilities and surface temperature trends on the Greenland ice sheet using a Gaussian mixture model

2021 ◽  
Author(s):  
Daniel Clarkson ◽  
Emma Eastoe ◽  
Amber Leeson
Keyword(s):  
Surface Temperature ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Gaussian Mixture ◽  
Ice Surface ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Surface Temperature ◽  
Model Components

Abstract. The Greenland ice sheet has experienced significant melt over the past six decades, with extreme melt events covering large areas of the ice sheet. Melt events are typically analysed using summary statistics, but the nature and characteristics of the events themselves are less frequently analysed. Our work examines melt events from a statistical perspective by modelling 19 years of Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature data using a Gaussian mixture model. We use a mixture model with separate model components for ice and meltwater temperatures at 1139 locations spaced across the ice sheet. By considering the uncertainty of the ice surface temperature measurements, we use the two categories of model components to define a probability of melt for a given observation rather than using a fixed melt threshold. This probability can then be used to estimate the expected number of melt events at a given location. Furthermore, the model can be used to estimate temperature quantiles at a given location, and analyse temperature and melt trends over time by fitting the model to subsets of time. Fitting the model to data from 2001–2009 and 2010–2019 shows increases in melt probability for significant portions of the ice sheet, as well as the yearly expected maximum temperatures.

scholarly journals Greenland ice sheet surface temperature, melt and mass loss: 2000–06

2008 ◽  
Vol 54 (184) ◽  
pp. 81-93 ◽  
Author(s):  
Dorothy K. Hall ◽  
Richard S. Williams ◽  
Scott B. Luthcke ◽  
Nicolo E. Digirolamo
Keyword(s):  
Surface Temperature ◽  
Mass Loss ◽  
Land Surface ◽  
Large Scale ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Concentration Data ◽  
Air Temperatures ◽  
Surface Melt ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractA daily time series of ‘clear-sky’ surface temperature has been compiled of the Greenland ice sheet (GIS) using 1 km resolution moderate-resolution imaging spectroradiometer (MODIS) land-surface temperature (LST) maps from 2000 to 2006. We also used mass-concentration data from the Gravity Recovery and Climate Experiment (GRACE) to study mass change in relationship to surface melt from 2003 to 2006. The mean LST of the GIS increased during the study period by ∼0.27°C a−1. The increase was especially notable in the northern half of the ice sheet during the winter months. Melt-season length and timing were also studied in each of the six major drainage basins. Rapid (<15 days) and sustained mass loss below 2000 m elevation was triggered in 2004 and 2005 as recorded by GRACE when surface melt begins. Initiation of large-scale surface melt was followed rapidly by mass loss. This indicates that surface meltwater is flowing rapidly to the base of the ice sheet, causing acceleration of outlet glaciers, thus highlighting the metastability of parts of the GIS and the vulnerability of the ice sheet to air-temperature increases. If air temperatures continue to rise over Greenland, increased surface melt will play a large role in ice-sheet mass loss.

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 Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Quantitative Information ◽  
Environmental Data ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Data Record ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

scholarly journals Simulation of the future sea level contribution of Greenland with a new glacial system model

2018 ◽  
Vol 12 (10) ◽  
pp. 3097-3121 ◽  
Author(s):  
Reinhard Calov ◽  
Sebastian Beyer ◽  
Ralf Greve ◽  
Johanna Beckmann ◽  
Matteo Willeit ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
System Model ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. We introduce the coupled model of the Greenland glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dynamics, the model of basal hydrology HYDRO and a parameterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, imposing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961–1990 standard climatology derived from simulations of the regional atmosphere model MAR with ERA reanalysis boundary conditions. For the palaeo-part of the spin-up, we add the temperature anomaly derived from the GRIP ice core to the years 1961–1990 average surface temperature field. For our projections, we apply surface temperature and surface mass balance anomalies derived from RCP 4.5 and RCP 8.5 scenarios created by MAR with boundary conditions from simulations with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Further on, the impact of elevation–surface mass balance feedback, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation–surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we investigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temperature and subglacial discharge are about equally important for the melting of the examined outlet glaciers.

scholarly journals How warm was Greenland during the last interglacial period?

2016 ◽  
Vol 12 (9) ◽  
pp. 1933-1948 ◽  
Author(s):  
Amaelle Landais ◽  
Valérie Masson-Delmotte ◽  
Emilie Capron ◽  
Petra M. Langebroek ◽  
Pepijn Bakker ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Ice Core ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Water Isotopes ◽  
Interglacial Period ◽  
Last Interglacial ◽  
Last Interglacial Period ◽  
Ice Sheet Topography ◽  
North Greenland

Abstract. The last interglacial period (LIG, ∼ 129–116 thousand years ago) provides the most recent case study of multimillennial polar warming above the preindustrial level and a response of the Greenland and Antarctic ice sheets to this warming, as well as a test bed for climate and ice sheet models. Past changes in Greenland ice sheet thickness and surface temperature during this period were recently derived from the North Greenland Eemian Ice Drilling (NEEM) ice core records, northwest Greenland. The NEEM paradox has emerged from an estimated large local warming above the preindustrial level (7.5 ± 1.8 °C at the deposition site 126 kyr ago without correction for any overall ice sheet altitude changes between the LIG and the preindustrial period) based on water isotopes, together with limited local ice thinning, suggesting more resilience of the real Greenland ice sheet than shown in some ice sheet models. Here, we provide an independent assessment of the average LIG Greenland surface warming using ice core air isotopic composition (δ15N) and relationships between accumulation rate and temperature. The LIG surface temperature at the upstream NEEM deposition site without ice sheet altitude correction is estimated to be warmer by +8.5 ± 2.5 °C compared to the preindustrial period. This temperature estimate is consistent with the 7.5 ± 1.8 °C warming initially determined from NEEM water isotopes but at the upper end of the preindustrial period to LIG temperature difference of +5.2 ± 2.3 °C obtained at the NGRIP (North Greenland Ice Core Project) site by the same method. Climate simulations performed with present-day ice sheet topography lead in general to a warming smaller than reconstructed, but sensitivity tests show that larger amplitudes (up to 5 °C) are produced in response to prescribed changes in sea ice extent and ice sheet topography.

scholarly journals Last Interglacial climate and sea-level evolution from a coupled ice sheet–climate model

2016 ◽  
Vol 12 (12) ◽  
pp. 2195-2213 ◽  
Author(s):  
Heiko Goelzer ◽  
Philippe Huybrechts ◽  
Marie-France Loutre ◽  
Thierry Fichefet
Keyword(s):  
Surface Temperature ◽  
Sea Level ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Last Interglacial ◽  
A Minor ◽  
The Antarctic ◽  
The Impact ◽  
And Sea Level

Abstract. As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG,  ∼  130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate–ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet–climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

scholarly journals Adjusting for Desert-Dust-Related Biases in a Climate Data Record of Sea Surface Temperature

2020 ◽  
Vol 12 (16) ◽  
pp. 2554
Author(s):  
Christopher J. Merchant ◽  
Owen Embury
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Dust Aerosol ◽  
Sea Surface ◽  
Climate Data ◽  
Desert Dust ◽  
Data Record ◽  
Climate Data Record

Atmospheric desert-dust aerosol, primarily from north Africa, causes negative biases in remotely sensed climate data records of sea surface temperature (SST). Here, large-scale bias adjustments are deduced and applied to the v2 climate data record of SST from the European Space Agency Climate Change Initiative (CCI). Unlike SST from infrared sensors, SST measured in situ is not prone to desert-dust bias. An in-situ-based SST analysis is combined with column dust mass from the Modern-Era Retrospective analysis for Research and Applications, Version 2 to deduce a monthly, large-scale adjustment to CCI analysis SSTs. Having reduced the dust-related biases, a further correction for some periods of anomalous satellite calibration is also derived. The corrections will increase the usability of the v2 CCI SST record for oceanographic and climate applications, such as understanding the role of Arabian Sea SSTs in the Indian monsoon. The corrections will also pave the way for a v3 climate data record with improved error characteristics with respect to atmospheric dust aerosol.

scholarly journals Satellite-based time-series of sea-surface temperature since 1981 for climate applications

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Christopher J. Merchant ◽  
Owen Embury ◽  
Claire E. Bulgin ◽  
Thomas Block ◽  
Gary K. Corlett ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Ocean Model ◽  
Sea Surface ◽  
Climate Data ◽  
Satellite Measurements ◽  
Data Record ◽  
The Mean ◽  
Climate Data Record

Abstract A climate data record of global sea surface temperature (SST) spanning 1981–2016 has been developed from 4 × 1012 satellite measurements of thermal infra-red radiance. The spatial area represented by pixel SST estimates is between 1 km2 and 45 km2. The mean density of good-quality observations is 13 km−2 yr−1. SST uncertainty is evaluated per datum, the median uncertainty for pixel SSTs being 0.18 K. Multi-annual observational stability relative to drifting buoy measurements is within 0.003 K yr−1 of zero with high confidence, despite maximal independence from in situ SSTs over the latter two decades of the record. Data are provided at native resolution, gridded at 0.05° latitude-longitude resolution (individual sensors), and aggregated and gap-filled on a daily 0.05° grid. Skin SSTs, depth-adjusted SSTs de-aliased with respect to the diurnal cycle, and SST anomalies are provided. Target applications of the dataset include: climate and ocean model evaluation; quantification of marine change and variability (including marine heatwaves); climate and ocean-atmosphere processes; and specific applications in ocean ecology, oceanography and geophysics.

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