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.     

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.     

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 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.     

Comparison of aerial video and Landsat 7 data over ponded sea ice

The development of melt ponds on Arctic sea ice during spring and summer is of great importance to the Arctic climate system as it accelerates the decay of the sea ice and greatly reduces the albedo. Both melt pond development and its spatial distribution are needed to understand the surface energy balance in summer. Previously, a technique was developed for classifying summer sea ice characteristics, including the amount of open water, white (snow-covered) ice, wet ice, and melt ponds using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) spectral information. In this paper, we refine this technique through the use of airborne video data coincident with Landsat ETM+ imagery obtained over Baffin Bay on June 27, 2000. The video images, having a resolution of about 1.5 m at an aircraft altitude of 1.4 km, are classified into open water, ponded or wet ice, and unponded sea ice. Comparison of the video and Landsat imagery shows that many of the melt ponds are too small to cover an entire Landsat pixel (resolution of 30 m) so that the Landsat classification scheme would underestimate melt pond fraction. Thirteen high-resolution video images are classified to develop a method to calculate fractions of open water, ponded or wet ice, and unponded ice from Landsat 7 data. A comparison between these classified video images and Landsat retrievals yields a correlation coefficient of 0.95 with rms errors of less than 9% for the two ice types and 2% for open water. Comparisons of Landsat and video analyses not used in the development of the algorithm yield correlation coefficients of 0.87 for open water, 0.68 for ponded ice, and 0.78 for unponded ice. The rms differences are 10%, 8%, and 11%, respectively.     

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.     

Analysis of normalized difference and surface temperature observations over southeastern Australia

Abstract

Relations between radiative surface temperature (T_R) and visible and near-infrared reflectances expressed as the normalized difference (ND) from a Landsat Thematic Mapper scene were analysed to study the heat balance of agriculture and native evergreen forests in southeastern Australia. The scene was at 0922 h (local time) during late spring (15 October 1986) with phenology of winter annual species between flowering and grain filling. Factors determining the slope of, and residual scatter about, the T_R)/ND relationships were analysed using a coupled two-layer soil-vegetation model of the surface heat balance. Inverse linear relationships were found between T_R), and ND for agriculture, but not for forests. This was a result of a wide range of ND and T_R) values in agricultural areas caused by wide variations in fractional vegetation cover. The relationships between ND and fractional vegetation cover was not general, thus, when forest and agricultural data were combined, the lower near-infrared reflectance of forests (16-9 per cent) compared with agricultural crops (29-0 per cent) resulted in forest data falling below the regression line for agriculture. From the agricultural relations, 60 to 70 per cent of the variation in T_R) was explained by ND, indicating that fractional vegetation cover was the dominant factor determining T_R). Residual variability of T_R) was attributed to spatial variability in ambient temperature, rates of soil evaporation and variations in stage of phenological development affecting stoma-tal resistance. Energy-balance analysis of the effect of soil water availability on the slope of the _R)‘ND relationship indicated opposite effects depending on whether the reduction in evaporation was from soil or from vegetation. Thus, the generality of using the slope of the T_R)/ND relationship to predict surface resistance to evaporation may be limited. It was concluded that extraction of information contained in T_R) and ND data for regional estimation of evaporation requires the separation of T_R) into soil and vegetation temperatures and an alternative to ND that relates more generally to fractional vegetation cover.     

Can phytoplankton community structure be inferred from satellite-derived sea surface temperature anomalies calculated relative to nitrate depletion temperatures?

Hydrographic data collected in the upper 50 m off La Jolla, CA, USA (31°N, 117°W) between 1970 and 1972 were reanalyzed to examine temporal variability in the local temperature-nitrate relationship and to document how chlorophyll a concentration and phytoplankton community structure covary with the temperature-nitrate relationship. Based on the linear expression y=mx+b, the y-intercepts (b), slopes (m), and x-intercepts (−b/m or nitrate depletion temperature, NDT) of four seasonal (January-March, April-June, July-September, and October-December) temperature-nitrate relationships, obtained from the combined multiyear data set, were statistically different from each other and varied around overall multiyear values of b=72.73 μM, m=−5.33 μM °C⁻¹, and NDT=13.65 °C. Three interannual temperature-nitrate relationships from February to April 1970, 1971, and 1972 also had y-intercepts, slopes, and x-intercepts that were statistically different from each other. Nevertheless, limited variability in direct comparisons among seasonal or interannual regression lines and a 1 °C La Jolla NDT range compared to a 25 °C global NDT range supported the general utility of NDT-based comparisons. A nitrate-normalized temperature axis (T−NDT) was created for the La Jolla data set by subtracting NDT from the recorded water column temperatures (T). Chlorophyll a reached a maximum between 0 and 2 °C on this T-NDT axis that ranged from −4 to 10 °C. Microscope-based determinations of La Jolla centric diatom, pennate diatom and dinoflagellate abundances, and La Jolla chlorophyll a, partitioned in proportion to the numerical abundance of the three groups, both peaked in logical progression along the T-NDT axis. In a separate analysis of high-performance liquid chromatography (HPLC) data from three Atlantic Meridional Transect (AMT) cruises (50°N to 52°S), chlorophyll a peaked below 0 °C and three different phytoplankton classes, nanoflagellates, large eukaryotes and prokaryotes, distributed in logical progression along a sea surface temperature (SST) minus NDT axis. To further generalize these results, a previously reported 1° latitude×1° longitude grid of NDTs for the world ocean was applied to satellite-derived grids of SST for March 1999 through June 2000. The SST−NDT calculation provided a standard nitrate-normalized axis simultaneously applicable to all locations in the world ocean. Sixteen plots of satellite-derived chlorophyll a versus SST−NDT for March 1999 through June 2000 demonstrated the opposing seasonal movements of northern and southern hemisphere chlorophyll a along the SST-NDT axis. Based on the phytoplankton community patterns along the temperature minus NDT in the La Jolla and AMT data sets, this chlorophyll a movement along the SST-NDT axis can be associated with phytoplankton community changes related to location around SST−NDT=0 °C. The SST−NDT index appears to provide a useful tool for interpreting the character of the phytoplankton community structure contributing to satellite-derived chlorophyll a in the world ocean.     

Validation of satellite observed thermal emission with in-situ measurements over an urban surface

The Basel Urban Boundary Layer Experiment (BUBBLE) is a joint European research project under the umbrella of COST (Coopération Européenne dans la domaine de la recherche Scientifique et Technique, COST 715: Meteorology applied to urban pollution problems). Besides very detailed field measurements of the structure and dynamics of the urban boundary layer, a series of satellite data has been analyzed and validated. Satellite data from MODIS, NOAA-AVHRR (14, 15, and 16) and Landsat-ETM were used and recorded during June and July 2002 in parallel to the BUBBLE field campaign. MODIS and NOAA-AVHRR data represent day and nighttime surface radiation temperatures in 930 m and 1100 m grid size. Landsat-ETM offers a unique resolution on 60 m, but with only daytime imagery at about the same time of MODIS overpass is available. This enables the validation of satellite measurements from different sensors with ground measurements at locations with various degrees of spatial homogeneity/heterogeneity (urban/rural land use). Several different algorithms for NOAA-AVHRR data were compared with in-situ measurements. The results show a very high correlation of the long wave emissions measured by the satellite with the in-situ measurements showing an accuracy of ± 3% to 5% on average, even in urban environments.     

Comparison of Envisat radar and airborne laser altimeter measurements over Arctic sea ice

Sea ice thickness is a crucial, but very undersampled cryospheric parameter of fundamental importance for climate modeling. Advances in satellite altimetry have enabled the measurement of sea ice freeboard using satellite microwave altimeters. Unfortunately, validation of these new techniques has suffered from a lack of ground truth measurements. Therefore, an airborne campaign was carried out in March 2006 using laser altimetry and photo imagery to validate sea ice elevation measurements derived from the Envisat/RA-2 microwave altimeter.We present a comparative analysis of Envisat/RA-2 sea ice elevation processing with collocated airborne measurements collected north of the Canadian Archipelago. Consistent overall relationships between block-averaged airborne laser and Envisat elevations are found, over both leads and floes, along the full 1300 km aircraft track. The fine resolution of the airborne laser altimeter data is exploited to evaluate elevation variability within the RA-2 ground footprint. Our analysis shows good agreement between RA-2 derived sea ice elevations and those measured by airborne laser altimetry, particularly over refrozen leads where the overall mean difference is about 1 cm. Notwithstanding this small 1 cm mean difference, we identify a larger elevation uncertainty (of order 10 cm) associated with the uncertain location of dominant radar targets within the particular RA-2 footprint. Sources of measurement uncertainty or ambiguity are identified, and include snow accumulation, tracking noise, and the limited coverage of airborne measurements.