Estimation of snow water equivalent over first-year sea ice using AMSR-E and surface observations

A SWE retrieval algorithm developed in-situ using passive microwave surface based radiometer data is applied to the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E). Snow water equivalent is predicted from two pixels located in Canadian Arctic Shelf Exchange Study (CASES) overwintering study area in Franklin Bay, N.W.T., Canada. Results show that the satellite SWE predictions are statistically valid with measured in-situ snow thickness data in both smooth and rough ice environments where predicted values range from 15 to 25 mm. Stronger correlation between measured and predicted data is found over smooth ice with R² value of 0.75 and 0.73 for both pixels respectively. Furthermore, a qualitative study of sea ice roughness using both passive and active microwave satellite data shows that the two pixels are rougher than the surrounding areas, but the SWE predictions do not seem to be affected significantly.     

Retrieval of snow grain size over Greenland from MODIS

This paper presents a new automatic algorithm to derive optical snow grain size at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The snow grains are modeled as fractal rather than spherical particles in order to account for their irregular shape. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived grain size shows a good sensitivity to snow melting and snow precipitation events. Pre-processing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust discrimination of clouds over bright snow and ice. Because in-situ grain size measurements over Greenland were not available at the time of this work, the validation was performed using data of Aoki et al. (Aoki, T., Hori, M., Motoyoshi, H., Tanikawa, T., Hachikubo, A., Sugiura, K., et al. (2007). ADEOS-II/GLI snow/ice products — Part II: Validation results using GLI and MODIS data. Remote Sensing of Environment, 111, 274-290) collected at Barrow (Alaska, USA), and Saroma, Abashiri and Nakashibetsu (Japan) in 2001-2005. The retrievals correlate well with measurements in the range of radii ~ 0.1-1 mm, although retrieved optical diameter may be about a factor of 1.5 lower than the physical measured diameter. As part of validation analysis for Greenland, the derived grain size from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM/I radiometer which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS grain size was compared with predictions of the snow model CROCUS driven by measurements of the automatic weather stations of the Greenland Climate Network. We found that the MODIS value is on average a factor of two smaller than CROCUS grain size. This result agrees with the direct validation analysis indicating that the snow reflectance model may need a “calibration” factor of ~ 1.5 for the retrieved grain size to match the physical snow grain size. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of snow grain size for four permanent sites, the paper presents maps of this important parameter over the Greenland ice sheet for the March-September period of 2004.     

Observed and modelled effects of ice lens formation on passive microwave brightness temperatures over snow covered tundra

Immediately before an April 2007 snow survey and passive microwave radiometer field campaign in the Northwest Territories, Canada, a rain-on-snow event deposited a thin (~ 3 mm) continuous layer of ice on the surface of the snowpack. At eight sites the brightness temperature (T_b) of the undisturbed snow pack was measured with a multi-frequency dual polarization (6.9, 19, 37, and 89 GHz) ground based radiometer system. The ice lens was then carefully removed and the T_bs were measured again. The individual V-pol channels and the 37 V − 19 V difference were largely unaffected by the presence of the ice lens, exhibiting a systematic shift of about 3 K. In comparison, the ice lens had a considerable effect on the H-pol T_b at all frequencies, with a mean difference (ice lens present − ice lens removed) of − 9 K (± 5.3 K) at 6.9 GHz, − 40 K (± 11.3 K) at 19 GHz, − 33 K (± 7.6 K) at 37 GHz, and − 19 K (± 8.0 K) at 89 GHz. The effect of the ice lens on H-pol measurements was also observed with spaceborne data from the Advanced Microwave Scanning Radiometer (AMSR-E) satellite data.Simulations of T_b were produced for each site using a new two layer formulation of the Helsinki University of Technology (HUT) snow emission model. The ice lens was used as the top layer and the underlying snowpack considered as a homogenous second layer. The agreement between observations and simulations was variable, with agreement strongest at 19 GHz. A comparison with simulations produced using the Microwave Emission Model of Layered Snowpacks (MEMLS) suggests HUT model uncertainty is related not to the ice lens, but to difficulties in simulating emission from deep snow. Overall, the observations and simulations suggest H-pol measurements are capable of detecting new ice layers across the tundra snowpack, while V-pol measurements are more appropriate for snow water equivalent (SWE) retrievals due to their relative insensitivity to ice layers.     

Evaluation of the MODIS (MOD10A1) daily snow albedo product over the Greenland ice sheet

This study evaluates the performance of the beta-test MODIS (MOD10A1) daily albedo product using in situ data collected in Greenland during summer 2004. Results indicate the beta-test product tracks the general seasonal variability in albedo but exhibits significant more temporal variability than observed at the stations. This may indicate problems with the cloud detection algorithm, and/or failure of the BRDF model to adequately model the bidirectional reflectance of snow. Comparisons with in situ observations at five automatic weather stations in Greenland indicate an overall RMSE of 0.067 for the Terra instrument and an RMSE of 0.075 on Aqua. The Terra-retrieved-albedo are slightly better correlated with the in situ data than the Aqua retrievals (r = 0.79 versus r = 0.77). Comparisons were also made between the MODIS daily albedo product and the MODIS 16-day albedo product (MOD43B3). Results indicate general correspondence between the two products, with better agreement found using the Terra-retrieved-albedo than the Aqua-retrieved albedo. The reason for the differences in albedo between the Aqua and Terra satellites remains unclear. At the stations examined, both the Terra and Aqua retrievals were made at nearly the same time of the day and therefore the differences in albedo between the satellites cannot be explained by differences in solar illumination. Finally, the albedo derived using MODIS data and the direct estimation algorithm (DEA) was also compared with 2004 Greenland in situ data. Results from this comparison suggest that the DEA performs well as long as the solar zenith angle of the observation is not greater than 70°.     

Comparison of CERES surface radiation fluxes with surface observations over Loess Plateau

Surface energy budget is an important factor in weather and climate processes. To estimate the errors in satellite-retrieved surface radiation budget over the interior of China, instantaneous-footprint surface radiation fluxes from the Terra/Aqua FLASHFlux SSF product are compared with the measurements taken at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) from July 2008 to March 2010. Validation is performed separately for different conditions: clear-sky and cloudy-sky, daytime and nighttime for four seasons. Differences between the FLASHFlux CERES shortwave radiation flux and surface measurements have larger standard deviations in cloudy-sky conditions than in clear-sky conditions, indicating that cloud contamination increases uncertainty in the retrieval algorithm. Upward shortwave radiation flux (USW) is overestimated in cloudy conditions suggesting that the cloud parameters and surface scene type in the retrieval process are not optimal for northwestern China. The CERES downward longwave radiation fluxes (DLW) accurately follow the variation of surface measurements during daytime, but are slightly underestimated during nighttime due to the coarse sounding profile and undetected low clouds at nighttime. The CERES upwelling longwave radiation fluxes (ULW) are strongly underestimated during daytime but are slightly underestimated during nighttime regardless of cloud coverage. This large bias could be caused by an underestimate of surface skin temperature and/or surface emissivity, or spatial inhomogeneity around the site. Generally, except for diurnal ULW, other components of the surface radiative fluxes obtained from CERES SSF datasets are close to meeting the accuracy requirements for climate research.     

Accuracy of airborne laser altimetry over the Greenland ice sheet

During September 1991, April 1992 and June/July 1993, a NASA P–3 aircraft, equipped with a scanning laser altimeter, flew numerous transects of the Greenland ice sheet. The aeroplane location was measured precisely using dilTerential Global Positioning System (GPS) surveying techniques, allowing all altimetry data to be converted into measurements of ice-surface elevation relative to the Earth ellipsoid. Results from flight data indicate that icc-surface elevations can be reliably measured to an accuracy of ～20cm (and possibly to ～s lOcm) over baselines of more than seven hundred kilometres.     

Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI

Arctic vegetation distribution is largely controlled by climate, particularly summer temperatures. Summer temperatures have been increasing in the Arctic and this trend is expected to continue. Arctic vegetation has been shown to change in response to increases in summer temperatures, which in turn affects arctic fauna, human communities and industries. An understanding of the relationship of existing plant communities to temperature is important in order to monitor change effectively. In addition, variation along existing climate gradients can help predict where and how vegetation changes may occur as climate warming continues. In this study we described the spatial relationship between satellite-derived land surface temperature (LST), circumpolar arctic vegetation, and normalized difference vegetation index (NDVI). LST, mapped as summer warmth index (SWI), accurately portrayed temperature gradients due to latitude, elevation and distance from the coast. The SWI maps also reflected NDVI patterns, though NDVI patterns were more complex due to the effects of lakes, different substrates and different-aged glacial surfaces. We found that for the whole Arctic, a 5 °C increase in SWI along the climate gradient corresponded to an increase in NDVI of approximately 0.07. This result supports and is of similar magnitude as temporal studies showing increases of arctic NDVI corresponding to increases in growing season temperatures over the length of the satellite record. The strongest positive relationship between NDVI and SWI occurred in partially vegetated and graminoid vegetation types. Recently deglaciated areas, areas with many water bodies, carbonate soil areas, and high mountains had lower NDVI values than predicted by SWI. Plant growth in these areas was limited by substrate factors as well as temperature, and thus is likely to respond less to climate warming than other areas.     

Evaluation of MODIS land surface temperature with in-situ snow surface temperature from CREST-SAFE

This article presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration Terra and Aqua Earth Observing System satellites using in-situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center – Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January–April) and 2014 (February–April). A total of 314 day-and-night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. CREST-SAFE is a synoptic ground station, located in the cold county of Caribou in Maine, USA, with a distinct advantage over most meteorological stations because it provides automated and continuous LST observations via an Apogee Model SI-111 Infrared Radiometer. This article also attempts to answer the question of whether a single pixel (1 km²) or several spatially averaged pixels should be used for satellite LST validation by increasing the MODIS window size to 5 × 5, 9 × 9, and 25 × 25 windows.

Several trends in the MODIS LST data were observed, including the underestimation of daytime values and night-time values. Results indicate that although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy (about 1°C), both suggesting that MODIS LST retrievals are reliable for similar land-cover classes and atmospheric conditions. Increasing the MODIS window size showed an overestimation of in-situ LST and some improvement in the daytime Terra and night-time Aqua biases, with the highest accuracy achieved with the 5 × 5 window. A comparison between MODIS emissivity from bands 31, 32, and in-situ emissivity showed that emissivity errors (relative error = ?0.30%) were insignificant.     

Evaluation of SMMR satellite-derived snow depth using ground-based measurements

Daily snow depth data for 284 first-order hydromet stations located in the former Soviet Union have been made available for climatological analysis by the U.S.S.R. State Committee for Hydrometeorology. The data are compared with the snow depth product derived from Scanning Multichannel Microwave Radiometer (SMMR) passive microwave brightness temperatures for the year 1980. Results suggest some discrepancies between the two data sources. Anomalies are considered to emanate from a variety of sources. These may include: (a) problems comparing a point measurement to one averaged over a pixel area; (b) an algorithm bias given deep snow conditions; (c) geographical influences such as elevation and forest cover; and (d) presence of depth hoar.     

Comparison of brightness temperatures from SSMI instruments on the DMSP F8 and FII satellites for Antarctica and the Greenland ice sheet

Passive microwave satellite data provide extremely important information about the climate and surface conditions in the often cloudy high latitude regions of the Earth. Available since 1978, multichannel passive microwave data have great potential for long term climate monitoring. In order to ensure consistent data sets for such long term monitoring, the relations between the microwave brightness temperatures from similar sensors on successive satellite platforms must be understood. In this study the 19,22. and 37GHz channels of the Defense Meteorological Satellite Program (DMSP) F8 and F11 Special Sensor Microwave Imager (SSMI) instruments are compared. While the analysis shows that the two data sets are highly correlated with correlation coefficients greater than 0·98. the consistency between the two data sets can be improved by applying small corrections in the order of I deg K. Two sets of regression coefficients are provided for adjusting the F11 data to the F8 baseline.     

Comparison of land surface temperatures derived from satellite observations with ground truth during FIFE

Surface temperatures of the FIFE (First ISLSCP Field Experiment) experimental area derived from thermal infrared radiances recorded from different satellite platforms at different scales were compared with reference observations by means of infrared thermometers at ground stations distributed over the area. FIFE was conducted during late spring, summer and fall over an area of 15 km by 15 km in a hilly tall-grass prairie region in northeastern Kansas. The data available for this purpose were produced by AVHRR and TOVS instruments aboard NOAA-9 and NOAA-10, the TM instrument aboard Landsat-5 and VISSR instrument aboard GOES-7. The scales covered by these instruments span a wide range, namely between hundreds of metres (Landsat TM) and hundreds of kilometres (TOVS). The data are analysed both with and without the application of an atmospheric correction.     

Evaluation of a novel inversion model for surface melt magnitude over the Greenland ice sheet during the 2002 ablation season

This work evaluates the performance of an empirical inversion model for surface liquid water fraction (LWF) or melt magnitude, using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Estimates of melt magnitude were evaluated through quantitative comparison to surface melt occurrence and duration derived from the cross-polarization gradient ratio (XPGR) and diurnal amplitude variation (DAV) passive microwave melt indices over the 2002 melt season. Longer melt durations derived from XPGR tend to correspond to higher LWF amounts at lower elevations, where temperatures are warmer than at higher elevations. DAV indicates melt occurrence at higher elevations, with lower durations in melt corresponding to small amounts of LWF. The LWF inversion model demonstrates that it is sensitive to both high melt duration events within the ablation zone, yet capable of capturing greater spatial variability in melt conditions broadly over the entire sheet.     

Comparison of polar and geostationary satellite infrared observations of sea surface temperatures in the Gulf of Maine

A comparison is made between the polar orbiting (NOAA) and the geostationary (GOES) satellite infrared observations of sea surface temperatures in the Gulf of Maine between 23 May and 6 June 1978. Color image enhancement is used to demonstrate that both satellites are capable of detecting the large-scale surface patterns associated with the Gulf Stream and sea surface temperature fronts in the vicinity of Georges Bank and Nova Scotia. The main difference between the range of surface temperatures detected by the two satellites is due to their different spacial resolution: 1 km for the NOAA and 8 km for the GOES. The equivalent blackbody temperatures recorded by the GOES are 2–3°C lower than those obtained by the NOAA satellite because of a GOES calibration offset. The comparison of the NOAA data with ship observations off Nantucket indicates that, at sea surface temperatures of 6–7°C, the NOAA Satellite and ship observations agree within 1°C. A similar comparison in the Gulf Stream at sea surface temperatures of 23–27°C, indicates that the NOAA measurements are 2–3°C lower than in situ observations. Coastal radiosonde profiles are used to estimate the correction for atmospheric attenuation of the infrared radiation. A comparison of Maul and Sidran (1973) and Weinreb and Neuendorffer (1973) models for attenuation of infrared by atmospheric water vapor shows significant differences. It was not possible to resolve the discrepancy between the models because of measurement uncertainties.     

Applicability of satellite-derived sea-surface temperatures in the Fiji region

We have examined NOAA-5 satellite-derived sea-surface temperature data in the Fiji region for a one-year period starting September 1977. Time series analysis revealed that the satellite data has spatial and temporal resolutions characterized by a coherence time of about 4 days and a coherence length of 850 km. A systematic difference ΔT between ship and satellite readings was found to correlate significantly with the surface temperature itself, with latitude, and with vapor pressure. Several possible models to explain the behavior of ΔT are introduced. We conclude that while surface emissivity variations, incomplete cloud decontamination, and cooling across the air-sea interface may all be contributory factors, the bulk of the discrepancy between ship and satellite readings arises from insufficient corrections being made for atmospheric attenuation. This highlights the difficulty of applying data for which globally averaged corrections have been made to a particular latitude band.     

Validation of the Climate-SAF surface broadband albedo product: Comparisons with in situ observations over Greenland and the ice-covered Arctic Ocean

This paper describes a validation study performed by comparing the Climate-SAF Surface Albedo Product (SAL) to ground truth observations over Greenland and the ice-covered Arctic Ocean. We compare Advanced Very High Resolution Radiometer (AVHRR)-based albedo retrievals to data from the Greenland Climate Network (GCN) weather stations and the floating ice station Tara for polar summer 2007. The AVHRR dataset consists of 2755 overpasses. The overpasses are matched to in situ observations spatially and temporally. The SAL algorithm presented here derives the surface broadband albedo from AVHRR channels 1 and 2 using an atmospheric correction, temporal sampling of an empirical Bidirectional Reflectance Distribution Function (BRDF), and a narrow-to-broadband conversion algorithm. The satellite product contains algorithms for snow, sea ice, vegetation, bare soil, and water albedo. At the Summit and DYE-2 stations on the Greenland ice sheet, instantaneous SAL RMSE is 0.073. The heterogeneous surface conditions at satellite pixel scale over the stations near the Greenland west coast increase RMSE to > 0.12. Over Tara, the instantaneous SAL RMSE is 0.069. The BRDF sampling approach reduces RMSE over the ice sheet to 0.053, and to 0.045 over Tara. Taking into account various sources of uncertainty for both satellite retrievals and in situ observations, we conclude that SAL agrees with in situ observations within their limits of accuracy and spatial representativeness.     

Sea ice small-scale surface roughness estimation based on AMSR-E observations

In this article, the retrieval of a sea ice small-scale surface roughness parameter using a proposed model is investigated at several Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) channels (6.9, 10.7, and 89 GHz) over the Arctic oceans. The AMSR-E 89 GHz observations with a spatial resolution of approximately 6 km?× 4 km, nearly three times the resolution of the currently operational radiometer SSM/I 85 GHz (15 km?× 13 km), are fully exploited to retrieve the total and multiyear (MY) ice concentrations through the utilization of the ARTIST sea ice (ASI) and polarization corrected temperature (PCT) algorithms, respectively. To improve the accuracy of the retrieved ice concentration, a tie-point adaption scheme was used to obtain daily adaptable tie-points for the two ice concentration algorithms. A sea ice small-scale roughness parameter was then calculated with the model proposed by Hong for the above-mentioned three frequencies. At lower frequencies, such as 6.9 and 10.7 GHz, roughness estimates are available for all ice types. However, estimates at 89 GHz are physically illegitimate over the wintertime MY ice cover. The model estimates at the two low frequencies were further studied over a protracted period (2003–2010). The annual time series of the averaged estimate over the Arctic sea ice were found to exhibit a slightly decreasing trend (?2.1 × 10^?3 and??1.9 × 10^?3 cm year^?1 for 6.9 and 10.7 GHz, respectively). Meanwhile, the winter time series showed an increasing trend whereas the summer time series showed a remarkably decreasing trend, which indicates more serious melting activity occurring over the Arctic ice.     

Evaluation and assimilation of various satellite-derived rainfall products over India

Accurate prediction of rainfall from the numerical weather prediction model is one of the major objectives over tropical regions. In this study, four different satellite-derived rainfall products (viz. merged-rainfall product from TRMM (Tropical Rainfall Measuring Mission) 3B42 and IMERG (Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement)), and Indian meteorological satellite INSAT-3D retrieved HEM (Hydro-Estimator Method) and IMSRA (INSAT Multi-Spectral Rainfall Algorithm) rainfall) are assimilated in the Weather Research and Forecasting (WRF) model using variational method. Before assimilation of satellite retrieved rainfall product in the WRF model, selected rainfall products are compared with ground rainfall from India Meteorological Department during Indian summer monsoon (June–September) 2015. Preliminary validation results show root-mean-square-difference (mean difference) of 18.1 (2.1), 21.3 (2.1), 15.4 (?0.72), and 14.4 (0.5) mm day^?1 in IMSRA, HEM, IMERG, and TRMM 3B42 rainfall, respectively. Further, the four-dimensional variational data assimilation method is used daily to assimilate selected rainfall products in the WRF model during the entire month of August 2015. Results suggest that assimilation of satellite rainfall improved the WRF model analyses and subsequent temperature and moisture forecasts. Moreover, rainfall prediction is also improved with the maximum positive impact from TRMM rainfall assimilation followed by IMERG rainfall assimilation. Similar nature of improvements is also seen in rainfall prediction when INSAT-3D retrieved rainfall products (HEM and IMSRA) are used for assimilation.     

Sea ice surface features in Arctic summer 2008: Aerial observations

Eight helicopter flights were conducted, and more than 9000 aerial images were obtained during the Third Chinese National Arctic Research Expedition in 2008 in the Pacific Arctic Sector (PAS). Along the cruise tracks between 77°N and 86°N, area fractions of open water and ice cover varied from 0.96 to 0.12 and from 0.03 to 0.81, respectively, while the melt pond fraction varied between 0 and 0.2. The ice concentrations derived from aerial images and the AMSR-E/ASI products were comparable to each other, especially in the range of 50-90%. However, the satellite-derived data overestimated the aerial observations by 14 ± 9% in areas with large ice concentrations (> 90%), and nearly ignored those with very low ice concentrations (< 20%). In addition, a significantly higher amount of melt ponds was observed in the PAS in the summer of 2008 as compared to five years ago. The areally averaged albedo increased from 0.09 in the marginal ice zone at 77°N to 0.63 in the far north zone at 86°N, where the ice concentration was 90%. The albedo was significantly smaller than those reported in earlier studies in the PAS for the same region because of an overall decrease in ice concentration. Compared with 2007 data, the lower ice concentration in 2008 may yield a smaller total ice-covered area, although the Arctic ice extent in 2008 was slightly larger than the record minimum in 2007.     

Evaluation of the HUT modified snow emission model over lake ice using airborne passive microwave measurements

The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80 × 100 m were used as ground-truth to evaluate the simulations.The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of −8.4 K and −8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (−5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R = −0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (−4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.     

MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland

In situ measurements of snow albedo at five stations along a north-south transect in the dry-snow facies of the interior of Greenland follow the theoretically expected dependence of snow albedo with solar zenith angle (SZA). Greenland Climate Network (GC-Net) measurements from 1997 through 2007 exhibit the trend of modest surface brightening with increasing SZA on both diurnal and seasonal timescales. SZA explains up to 50% of seasonal albedo variability. The two other environmental factors considered, temperature and cloudiness, play much less significant roles in seasonal albedo variability at the five stations studied. Compared to the 10-year record of these GC-Net measurements, the five-year record of MODIS satellite-retrieved snow albedo shows a systematic negative bias for SZA larger than about 55°. Larger bias of MODIS snow albedo exists at more northerly stations. MODIS albedos successfully capture the snow albedo dependence on SZA and have a relatively good agreement with GC-Net measurements for SZA < 55°. The discrepancy of MODIS albedo with in situ albedo and with theory is determined mainly by two related factors, SZA and retrieval quality. While the spatiotemporal structure, especially zonal features, of the MODIS-retrieved albedo may be correct for large SZA, the accuracy deteriorates for SZA > 55° and often becomes physically unrealistic for SZA > 65°. This unphysical behavior biases parameterizations of surface albedo and restricts the range of usefulness of the MODIS albedo products. Seasonal-to-interannual trends in surface brightness in Greenland, and in polar (i.e., large SZA) regions in general, and model simulations of these trends, should be evaluated in light of these limitations.