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Global warming due to human-made gases, mainly CO2, is already 0.8{\deg}C and deleterious climate impacts are growing worldwide. More warming is 'in the pipeline' because Earth is out of energy balance, with absorbed solar energy exceeding planetary heat radiation. Maintaining a climate that resembles the Holocene, the world of stable shorelines in which civilization developed, requires rapidly reducing fossil fuel CO2 emissions. Such a scenario is economically sensible and has multiple benefits for humanity and other species. Yet fossil fuel extraction is expanding, including highly carbon-intensive sources that can push the climate system beyond tipping points such that amplifying feedbacks drive further climate change that is practically out of humanity's control. This situation raises profound moral issues as young people, future generations, and nature, with no possibility of protecting their future well-being, will bear the principal consequences of actions and inactions of today's adults., Comment: 28 pages, 6 figures; version submitted to Proceedings of the National Academy of Sciences

Ice velocities observed in 2005/06 at three GPS stations along the Sermeq Avannarleq flowline, West Greenland, are used to characterize an observed annual velocity cycle. We attempt to reproduce this annual ice velocity cycle using a 1-D ice-flow model with longitudinal stresses coupled to a 1-D hydrology model that governs an empirical basal sliding rule. Seasonal basal sliding velocity is parameterized as a perturbation of prescribed winter sliding velocity that is proportional to the rate of change of glacier water storage. The coupled model reproduces the broad features of the annual basal sliding cycle observed along this flowline, namely a summer speed-up event followed by a fall slowdown event. We also evaluate the hypothesis that the observed annual velocity cycle is due to the annual calving cycle at the terminus. We demonstrate that the ice acceleration due to a catastrophic calving event takes an order of magnitude longer to reach CU/ETH ('Swiss') Camp (46km upstream of the terminus) than is observed. The seasonal acceleration observed at Swiss Camp is therefore unlikely to be the result of velocity perturbations propagated upstream via longitudinal coupling. Instead we interpret this velocity cycle to reflect the local history of glacier water balance.

We apply a novel one-dimensional glacier hydrology model that calculates hydraulic head to the tidewater-terminating Sermeq Avannarleq flowline of the Greenland ice sheet. Within a plausible parameter space, the model achieves a quasi-steady-state annual cycle in which hydraulic head oscillates close to flotation throughout the ablation zone. Flotation is briefly achieved during the summer melt season along a approx.17 km stretch of the approx.50 km of flowline within the ablation zone. Beneath the majority of the flowline, subglacial conduit storage closes (i.e. obtains minimum radius) during the winter and opens (i.e. obtains maximum radius) during the summer. Along certain stretches of the flowline, the model predicts that subglacial conduit storage remains open throughout the year. A calculated mean glacier water residence time of approx.2.2 years implies that significant amounts of water are stored in the glacier throughout the year. We interpret this residence time as being indicative of the timescale over which the glacier hydrologic system is capable of adjusting to external surface meltwater forcings. Based on in situ ice velocity observations, we suggest that the summer speed-up event generally corresponds to conditions of increasing hydraulic head during inefficient subglacial drainage. Conversely, the slowdown during fall generally corresponds to conditions of decreasing hydraulic head during efficient subglacial drainage.

A new instrument is used to study the inner workings of Greenland s glacier mills by riding the currents inside a glacier s moulin. The West Greenland Moulin Explorer instrument was deployed into a tubular shaft to autonomously record temperature, pressure, 3D acceleration, and location. It is built with a slightly positive buoyancy in order to assist in recovery. The unit is made up of several components. A 3-axis MEMS (microelectromechanical systems) accelerometer with 0.001-g resolution forms the base of the unit. A pressure transducer is added that is capable of withstanding 500 psi (=3.4 MPa), and surviving down to -40 C. An Iridium modem sends out data every 10 minutes. The location is traced by a GPS (Global Positioning System) unit. This GPS unit is also used for recovery after the mission. Power is provided by a high-capacity lithium thionyl chloride D-sized battery. The accelerometer is housed inside a cylindrical, foot-long (=30 cm) polyvinyl chloride (PVC) shell sealed at each end with acrylic. The pressure transducer is attached to one of these lids and a MEMS accelerometer to the other, recording 100 samples per second per axis.

A probe was designed to investigate the moulins (melt water drainage channels on an ice cap) and ice-hydrology interaction in the Greenla nd Ice Cap.

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0 degree isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plus or minus 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approximately 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

The magnitude of shortwave and longwave dative fluxes are critical to surface energy balance variations over the Greenland ice sheet, affecting many aspects of its climate, including melt rates, the nature of low-level temperature inversions, the katabatic wind regime and buoyant stability of the atmosphere. Nevertheless, reliable measurements of the radiative fluxes over the ice sheet are few in number, and have been of limited duration and areal distribution (e.g. Ambach, 1960; 1963, Konzelmann et al., 1994, Harding et al., 1995, Van den Broeke, 1996). Hourly GC-Net radiation flux measurements spanning 1995-2001 period have been used to produce a monthly dataset of surface radiation balance components. The measurements are distributed widely across Greenland and incorporate multiple sensors

This document serves as a final report for NASA grant NAG5-8625 to the University of Wisconsin-Madison (UW). The report covers work done at Boston University for the first two years of the project (as NAG5-4903) and the third and final year of the project at the University of Wisconsin (NAG5-8625). In 1999 the third year's funding and tasks were transferred to UW where the Principal Investigator (J. Key) is now stationed. A no-cost extension period of the grant ended on June 15, 2001. This is a group project with the University of Colorado (CU) as the lead institution, where Judith Curry is the Principal Investigator. The overall project is jointly funded by NASA and NSF. The progress reported herein is specific to Boston University and the University of Wisconsin.

Large changes in the sea ice cover have been observed recently. Because of the relevance of such changes to climate change studies it is important that key ice concentration data sets used for evaluating such changes are interpreted properly. High and medium resolution visible and infrared satellite data are used in conjunction with passive microwave data to study the true characteristics of the Antarctic sea ice cover, assess errors in currently available ice concentration products, and evaluate the applications and limitations of the latter in polar process studies. Cloud-free high resolution data provide valuable information about the natural distribution, stage of formation, and composition of the ice cover that enables interpretation of the large spatial and temporal variability of the microwave emissivity of Antarctic sea ice. Comparative analyses of co-registered visible, infrared and microwave data were used to evaluate ice concentrations derived from standard ice algorithms (i.e., Bootstrap and Team) and investigate the 10 to 35% difference in derived values from large areas within the ice pack, especially in the Weddell Sea, Amundsen Sea, and Ross Sea regions. Landsat and OLS data show a predominance of thick consolidated ice in these areas and show good agreement with the Bootstrap Algorithm. While direct measurements were not possible, the lower values from the Team Algorithm results are likely due to layering within the ice and snow and/or surface flooding, which are known to affect the polarization ratio. In predominantly new ice regions, the derived ice concentration from passive microwave data is usually lower than the true percentage because the emissivity of new ice changes with age and thickness and is lower than that of thick ice. However, the product provides a more realistic characterization of the sea ice cover, and are more useful in polar process studies since it allows for the identification of areas of significant divergence and polynya activities. Also, heat and salinity fluxes are proportionately increased in these areas compared to those from the thicker ice areas. A slight positive trend in ice extent and area from 1978 through 2000 is observed consistent with slight continental cooling during the period. However, the confidence in this result is only moderate because the overlap period for key instruments is just one month and the sensitivity to changes in sensor characteristics, calibration and threshold for the ice edge is quite high.

This document serves as a final report for NASA grant NAG5-4903 at Boston University. The report covers the first two years of the three-year project. The third year's funding and tasks have been transferred to the University of Wisconsin-Madison (UW) where the Principal Investigator (J. Key) is now stationed. The new UW grant number is NAG5-8625. Plans for the final project year at UW were detailed in the Request to Transfer document, submitted to NASA in July 1999. This is a group project with the University of Colorado (CU) as the lead institution, where Judith Curry is the Principal Investigator. The overall project is jointly funded by NASA and NSF. The progress reported herein is that specific to Boston University, but no attempt has been made to separate NASA and NSF activities.

Analysis of melt extent on the Greenland ice sheet is updated to span the time period 1979-1999 is examined along with its spatial and temporal variability using passive microwave satellite data. In order to acquire the full record, the issue of continuity between previous passive microwave sensors (SMMR, SSM/I F-8, and SSM/I F-11), and the most recent SSM/I F-13 sensor is addressed. The F-13 Cross-polarized gradient ratio (XPGR) melt-classification threshold is determined to be -0.0154. Results show that for the 21-year record, an increasing melt trend of nearly 1 %/yr is observed, and this trend is driven by conditions on in the western portion of the ice sheet, rather than the east, where melt appears to have decreased slightly. Moreover, the eruption of Mt. Pinatubo in 1991 is likely to have had some impact the melt, but not as much as previously suspected. The 1992 melt anomaly is 1.7 standard deviations from the mean. Finally, the relationship between coastal temperatures and melt extent suggest an increase in surface runoff contribution to sea level of 0.31 mm/yr for a 1 C temperature rise.

This year repeat elevation surveys in the southern half of Greenland were made using the Airborne Topographic Mapper (ATM). The intent of these surveys is to compare present elevations to those measured in 1993 and determine the magnitude and spatial distributions of thickening and thinning rates. In order to effectively interpret any observed changes, it is important to understand the processes that affect these changes. Moreover, because the surveys are made over a brief period (2-4 weeks) during the spring or summer, it is also important to understand the effects of seasonal and interannual elevation variability, in relation to the timing of these surveys. Toward that end we are examining data from weather stations along the coast of Greenland along with data from GC-Net automatic weather stations (AWS's) on the ice sheet. The objectives are to assess: a) the importance of the timing of the flights in relation to natural processes that affect surface heights, namely accumulation and melt, and b) the temperature characteristics of the region in the five years that separated the two sets of surveys (1993-1998), in relation to the past 19 years.

The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

The melt extent of the snow on the Greenland ice sheet is of considerable importance to the ice sheet's mass and energy balance, as well as Arctic and global climates. By comparing passive microwave satellite data to field observations, variations in melt extent have been detected by establishing melt thresholds in the cross-polarized gradient ratio (XPGR). The XPGR, defined as the normalized difference between the 19-GHz horizontal channel and the 37-GHz vertical channel of the Special Sensor Microwave/Imager (SSM/I), exploits the different effects of snow wetness on different frequencies and polarizations and establishes a distinct melt signal. Using this XPGR melt signal, seasonal and interannual variations in snowmelt extent of the ice sheet are studied. The melt is found to be most extensive on the western side of the ice sheet and peaks in late July. Moreover, there is a notable increasing trend in melt area between the years 1979 and 1991 of 4.4% per year, which came to an abrupt halt in 1992 after the eruption of Mt. Pinatubo. A similar trend is observed in the temperatures at six coastal stations. The relationship between the warming trend and increasing melt trend between 1979 and 1991 suggests that a 1 C temperature rise corresponds to an increase in melt area of 73000 sq km, which in general exceeds one standard deviation of the natural melt area variability.

By comparing data from the Special Sensor Microwave Imager (SSM/I) to field data, a melt threshold of the cross-polarized gradient ratio (XPGR), which is a normalized difference between the 19 GHz horizontally-polarized and 37 GHz vertically polarized brightness temperatures, is determined. This threshold, XPGR = -0.025, is used to classify dry and wet snow. The annual areal extent of melt is mapped for the years 1988 through 1991, and inter-annual variations of melt extent are examined. The results show that the melt extent varied from a low of 38.3% of the ice sheet (1990) to a high of 41.7% (1991) during the years 1988-1991.

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.

During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

Satellite data for the estimation of radiative and turbulent heat fluxes is becoming an increasingly important tool in large-scale studies of climate. One parameter needed in the estimation of these fluxes is surface temperature. To our knowledge, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic, an area where the first effects of a changing climate are expected to be seen. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol profiles, the microphysical properties of polar clouds, and the spectral characteristics of the wide variety of surface types found there. We have developed a means to correct for the atmospheric attenuation of satellite-measured clear sky brightness temperatures used in the retrieval of ice surface temperature from the split-window thermal channels of the advanced very high resolution radiometer (AVHRR) sensors on-board three of the NOAA series satellites. These corrections are specified for three different 'seasons' and as a function of satellite viewing angle, and are expected to be applicable to the perennial ice pack in the central Arctic Basin.

The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

In the past six months, work has continued on energy flux sensitivity studies, ice surface temperature retrievals, corrections to Advanced Very High Resolution Radiometer (AVHRR) thermal infrared data, modelling of cloud fraction retrievals, and radiation climatologies. We tentatively conclude that the SSM/I may not provide accurate enough estimates of ice concentration and type to improve our shorter term energy flux estimates. SSM/I derived parameters may still be applicable in longer term climatological flux characterizations. We hold promise for a system coupling observation to a ice deformation model. Such a model may provide information on ice distribution which can be used in energy flux calculations. Considerable variation was found in modelled energy flux estimates when bulk transfer coefficients are modulated by lead fetch. It is still unclear what the optimum formulation is and this will be the subject of further work. Data sets for ice surface temperature retrievals were assembled and preliminary data analysis was started. Finally, construction of a conceptual framework for further modelling of the Arctic radiation flux climatology was started.

The sensitivity of passive microwave sea-ice concentration (SIC) algorithms to the selection of tie points was analyzed. SICs were derived with the NASA Team ice algorithm for global tie points and for locally and seasonally adjusted tie points. The SSM/I SIC was then compared to Landsat-MSS-derived SICs. Preliminary results show a mean difference of SSM/I- and Landsat-derived SICs for 50 x 50 km grid cells of 2.7 percent along the ice edge of the Beaufort Sea during fall with local tie points. The accuracy decreased to 9.7 percent when global tie points were used. During freeze-up in the Beaufort Sea, with grey ice and nilas as dominant ice cover, the mean difference was 4.3 percent for local tie points and 13.9 percent for global tie points. For the spring ice cover in the Bering Sea a mean difference of 4.4 percent for local tie points and 15.7 percent for global tie points was found. This large difference reveals some limitations of the NASA-Team algorithm under freeze-up and spring conditions (thin ice areas).

Ice concentrations derived from passive microwave data from the Special Sensing Microwave Imager (SSM/I), the Landsat MSS, and the AVHRR are compared for the validation of SSM/I-derived sea-ice products. Case studies with data from the Beaufort, Bering, East Greenland, and Weddell Seas are conducted to evaluate the performance of the NASA Team SSM/I algorithm under various sea-ice conditions. The results show that SSM/I ice concentrations are accurate with a mean error of 15 percent using globally derived tie points.