Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data

Southern Ocean warming: Increase in basal melting and grounded ice loss

We apply a global finite element sea ice/ice shelf/ocean model (FESOM) to the Antarctic marginal seas to analyze projections of ice shelf basal melting in a warmer climate. The model is forced with the atmospheric output from two climate models: (1) the Hadley Centre Climate Model (HadCM3) and (2) Max Planck Institute’s ECHAM5/MPI-OM. Results from their 20th-century simulations are used to evaluate the modeled present-day ocean state. Sea-ice coverage is largely realistic in both simulations. Modeled ice shelf basal melt rates compare well with observations in both cases, but are consistently smaller for ECHAM5/MPI-OM. Projections for future ice shelf basal melting are computed using atmospheric output for IPCC scenarios E1 and A1B. While trends in sea ice coverage, ocean heat content, and ice shelf basal melting are small in simulations forced with ECHAM5 data, a substantial shift towards a warmer regime is found in experiments forced with HadCM3 output. A strong sensitivity of basal melting to increased ocean temperatures is found for the ice shelves in the Amundsen Sea. For the cold-water ice shelves in the Ross and Weddell Seas,decreasing convection on the continental shelf in the HadCM3 scenarios leads to an erosion of the continental slope front and to warm water of open ocean origin entering the continental shelf. As this water reaches deep into the Filchner-Ronne Ice Shelf (FRIS) cavity, basal melting increases by a factor of three to six compared to the present value of about 100 Gt/yr. Highest melt rates at the deep FRIS grounding line causes a retreat of > 200km, equivalent to an land ice loss of 110 Gt/yr

On the Validation of Satellite-Derived Sea Ice Surface Temperature

The surface temperature of sea ice controls the rate of ice growth and heat exchange between the ocean and the atmosphere. An algorithm for the satellite retrieval of ice surface temperature has recently been published, but due to the lack of validation data has not been extensively tested. In this paper, data from a recent Arctic field experiment is used in an attempt to validate that algorithm. While the procedure is, in principle, straightforward, we demonstrate that validation is complicated by a variety of factors, including incorrectly assumed atmospheric conditions, undetected clouds in the satellite data, spatial and temporal variability in the surface temperature field, and surface and satellite measurement errors. Comparisons between surface temperatures determined from upwelling broadband longwave radiation, spatial measurements of narrow-band radiation, thermocouples buried just below the snow surface, and narrow-band satellite data show differences of 1 to 13 degrees C. The range in these independent measurements indicates the need for specially designed validation experiments utilizing narrow-band radiometers on aircraft to obtain broad spatial coverage.Key words: ice surface temperature, Arctic climate, sea ice, AVHRRLa température de la surface de la glace de mer contrôle le taux de croissance de la glace et les échanges thermiques entre l'océan et l'atmosphère. Un algorithme d'extraction par satellite de la température de la surface de la glace a récemment été publié, mais n'a pu être mis à l'essai sur une grande échelle, en raison du manque de données de validation. On tente, dans cet article, de valider cet algorithme à l'aide de données provenant d'une expérience de terrain menée récemment dans l'Arctique. Si la procédure est, en principe, simple, on démontre que divers facteurs viennent compliquer cette validation, dont une évaluation incorrecte des conditions atmosphériques, la présence de nuages non détectés dans les données obtenues par satellite, une variabilité spatiale et temporelle dans la température de surface de l'aire expérimentale, et des erreurs dans les mesures prises sur le terrain même et par satellite. Des comparaisons entre les températures de surface déterminées à partir du rayonnement ascendant des ondes longues à large bande, des mesures spatiales du rayonnement à bande étroite, des thermocouples placés juste sous la surface de la neige et des données de satellite dans la bande étroite révèlent des différences allant de 1 à 3 °C. La différence qui existe dans ces mesures prises indépendamment montre bien la nécessité de mettre sur pied des expériences de validation conçues à des fins spécifiques, qui utilisent des radiomètres à bande étroite sur les avions en vue d'obtenir une grande couverture spatiale.Mots clés: température de la surface de la glace, climat de l’Arctique, glace de mer, radiomètre perfectionné à très haute résolutio

Analysis of surface structures and thermal distribution of Grenzgletscher ablation area with multispectral and thermal imagery

Due to climate change, glaciers and ice sheets are increasingly melting. Many glaciers in polar and subpolar regions as well the Greenland and Antarctic ice sheet are polythermal. Which arises questions about how a polythermal glacier reacts, when a shift from a polythermal regime to a temperate regime occurs. The largest polythermal glacier in the Alps is the Grenzgletscher, where the ablation zone shows typical surface structures for cold ice. This makes the Grenzgletscher a perfect study site to study a polythermal glacier under warming conditions and then extrapolate the findings to the arctic and subarctic region. The analysis of surface structures and thermal distribution at different locations on in the ablation zone of Grenzgletscher can be interpreted as studies under different climate conditions. By using multispectral and thermal imagery this thesis analyzed the surface of the ablation zone and tries to correlate the findings with the ice temperature. This analysis are important in understanding how a polythermal glacier adapts to warmer climate and what has to be considered in glaciological models

Estimation of CDOM in Inland Waters via Water Bio-Optical Properties Using a Remote Sensing Approach

Monitoring of Colored dissolved organic matter (CDOM) in inland waters provides important information for tracing carbon cycle at the land-water interface and studying aquatic ecosystem. Remote sensing estimation of CDOM in the inland waters offers an alternative approach to field samplings in examining CDOM spatial-temporal dynamics. However, CDOM retrieval is a challenge due to the lack of algorithm for resolving bottom effect in shallow inland waters. Moreover, an effective approach based on multi-spectral, high spatial resolution and global coverage satellite images is in urgent need. To resolve these challenges, shallow water bio-optical properties (SBOP) algorithm was developed to overcome bottom reflectance effect on the total water leaving reflectance in shallow inland water. SBOP algorithm included the bottom reflectance in building underwater light transfer model. It was designed based on the field spectral data from four cruises in Lake Huron. SBOP algorithm had an obviously advantage over previous deep water CDOM algorithm (e.g. QAA-CDOM). In this study, Landsat-8 multi-spectral satellite imagery was selected to derive CDOM spatial-temporal dynamics in lake and river waters. The coastal blue band (443 nm), global coverage and high spatial resolution (30 m) of Landsat-8 images offered suitable data for inland water CDOM mapping. The SBOP algorithm was applied on Landsat-8 images in broad ranges of inland waters with high accuracy (Lake Huron (R2 = 0.87), 14 northeastern freshwater lakes (R2 = 0.80), and 6 large Arctic Rivers (R2 = 0.87)). Both the spatial patterns and seasonal dynamics were derived to study the multiple factors’ impact on terrestrially derived CDOM input to the rivers and lakes, including river discharge, watershed landcover, and temperature. This new satellite approach of CDOM estimation in inland waters provided high accuracy spatial-temporal information for studying land-water carbon cycle and aquatic environment

Detection and classification of sea ice from spaceborne multi-frequency synthetic aperture radar imagery and radar altimetry

The sea ice cover in the Arctic is undergoing drastic changes. Since the start of satellite observations by microwave remote sensing in the late 1970\u27s, the maximum summer sea ice extent has been decreasing and thereby causing a generally thinner and younger sea ice cover. Spaceborne radar remote sensing facilitates the determination of sea ice properties in a changing climate with the high spatio-temporal resolution necessary for a better understanding of the ongoing processes as well as safe navigation and operation in ice infested waters.The work presented in this thesis focuses on the one hand on synergies of multi-frequency spaceborne synthetic aperture radar (SAR) imagery for sea ice classification. On the other hand, the fusion of radar altimetry observations with near-coincidental SAR imagery is investigated for its potential to improve 3-dimensional sea ice information retrieval.Investigations of ice/water classification of C- and L-band SAR imagery with a feed-forward neural network demonstrated the capabilities of both frequencies to outline the sea ice edge with good accuracy. Classification results also indicate that a combination of both frequencies can improve the identification of thin ice areas within the ice pack compared to C-band alone. Incidence angle normalisation has proven to increase class separability of different ice types. Analysis of incidence angle dependence between 19-47\ub0 at co- and cross-polarisation from Sentinel-1 C-band images closed a gap in existing slope estimates at cross-polarisation for multiyear sea ice and confirms values obtained in other regions of the Arctic or with different sensors. Furthermore, it demonstrated that insufficient noise correction of the first subswath at cross-polarisation increased the slope estimates by 0.01 dB/1\ub0 for multiyear ice. The incidence angle dependence of the Sentinel-1 noise floor affected smoother first-year sea ice and made the first subswath unusable for reliable incidence angle estimates in those cases.Radar altimetry can complete the 2-dimensional sea ice picture with thickness information. By comparison of SAR imagery with altimeter waveforms from CryoSat-2, it is demonstrated that waveforms respond well to changes of the sea ice surface in the order of a few hundred metres to a few kilometres. Freeboard estimates do however not always correspond to these changes especially when mixtures of different ice types are found within the footprint. Homogeneous ice floes of about 10 km are necessary for robust averaged freeboard estimates. The results demonstrate that multi-frequency and multi-sensor approaches open up for future improvements of sea ice retrievals from radar remote sensing techniques, but access to in-situ data for training and validation will be critical

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided

An Evaluation of Trend and Anomalies of Arctic Sea Ice Concentration, 1979-2006

As a part of the Cyrosphere ecosystem, Arctic sea ice is one of the focal points when studying Arctic climate change. Arctic sea ice image has been documented by remotely sensed data since the 1970s. By examining these data, some climate patterns can be revealed. In this research, Arctic region is divided into 9 sections to analyze the regional differences of the ice coverage and variability. Data used are bootstrapped 1979 to 2006 SSM/I and SMMR images from NSIDC to perform a time series analysis to examine the sea ice trends and spatial/temporal anomalies detection by conducting a descending sort of sea ice coverage by years in the sub-regional scale. Then, the temporal mixture analysis developed by Piwowar & LeDrew is applied to the data to reveal the variability within each subregion. Fractional images produced by TMA highlight the temporal signature concentration in the entire Arctic region. And the color-mix image derived from TMA highlights and overlaps temporal signatures that have over 80% concentrations from highest to lowest. The color mix image can reveal the spatial distribution of similar temporal characteristics and the evolution of time series in the same area during the 30-year period. Through this analysis, the spatial and temporal variability of Arctic sea ice can be perceived that in the subpolar regions, Arctic sea ice has a higher seasonal pattern which varies a lot each other. The Arctic sea ice extent endures an overall decline trend, which the decline speed increases every ten years. But this trend is not statistically significant in every subregion. The spatial/temporal anomaly analysis reveals several patterns of Arctic sea ice variability. The seasonal variability of Arctic sea ice in the eastern and western side of the Arctic Basin resemble each other in the long term, which may coincide with the North Atlantic Oscillation. In addition, within a subregion, different areas may have significantly different temporal characteristics, such as the Greenland Sea and Seas of Okhotsk. Moreover, the temporal characteristics some areas in the Arctic region have changed through time significantly regarding early melt or late freeze. Hopefully this analysis will provide undiscovered temporal evolution through time and some new insights on the dynamics of the Arctic sea ice cover

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Earth Resources: A continuing bibliography (issue 32)

This bibliography list 580 reports, articles and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis