Dual-frequency altimeter signal from Envisat on the Amery ice-shelf

In Antarctica, radar altimeter measurements are sensitive to dielectric and penetration properties of the sensed medium (snow) such that the spacecraft's altitude can be biased. Since 2002, relatively low frequency radar measurements over the Amery Ice Shelf, east Antarctica, have been acquired using the Envisat dual frequency altimeter at S (3.2 GHz) and Ku (13.6 GHz) bands, which penetrate a few meters into the firn.The altimeter signal is however modified in summer by the presence of snowfilled crevasses. Indeed, the specularity of the snow surfaces in summer makes the altimetric signal sensitive mostly to nadir echoes, that increases the ratio between the crevasse signal and the surrounding ice-shelf signal at nadir. Crevasses are distinguished by differences in backscattering behavior compared with the surrounding ice-shelf signal. Crevasses are characterized by a strong backscatter coefficient at Ku band and anomalies in the S band altitude estimation. These two characteristics make snowfilled crevasses detectable by the dual frequency altimeter of Envisat.We first retrieve the geometric properties of the crevasses using a hyperbolic shape function, created by strong crevasse backscatter in the Ku waveform measurements. From this retrieved crevasse signal and further waveform analysis, we assess the properties of the snow surface and its sub-surface. The crevasse, due to its small size compared to the altimeter footprint, is found to be an excellent target to study snow properties of the ice-shelf.The anomalies in the S band altitude measurements over crevasses can then be explained by the presence of a double echo in the S band waveforms. This echo is attributed to a reflection at the base of the snowbridge, where we see evidence of sub-surface echos in the individual altimeter waveforms. Based on this observation, a methodology is developed to estimate the thickness of the snowbridge. We calculate the penetration depths in the summer snow surface of the Amery at Ku band, that is found to be around 6 m.     

Rapid change of snow surface properties at Vostok, East Antarctica, revealed by altimetry and radiometry

We present results of snow surface properties using the ENVISAT dual frequency altimeter at S (3.2 GHz) and Ku (13.6 GHz) bands and the AMSR-E microwave radiometer at frequencies ranging between 6 and 36 GHz in the Vostok region, East Antarctica. The altimetric time series observed between 2002 and 2008 show variations at 3 different time scales (daily, seasonal and inter-annual), that correlate directly with variations in the snow surface properties. In this study we focus on the analysis of the rapid daily event, occurring on February 14th 2005, that created a jump of the backscatter coefficient of up to 5.3 dB at the S band and 2.5 dB at the Ku band. The ratio of V/H-polarization brightness temperature slowly decreased in December and January 2005, and suddenly increased on February 14th 2005.The origin of this rapid event is investigated using AWS data from Vostok station, altimetric and radiometric data simultaneously. Both snow surface density and roughness are found to vary during this event. This event is shown to be synchronous with strong wind occuring during a period of anomalous wind direction, and the presence of surface hoar. These particular conditions certainly modified the snow surface roughness and thus impacted the altimetric signal. We finally investigate the impact of this event on the calculation of the regional ice-sheet mass-balance using different corrections of height with echo shape variations. It is shown to be negligible only if the full echo shape correction (Legresy et al., 2006) is used.     

A model of satellite radar altimeter return from ice sheets

Abstract

Satellite-borne radar altimetry offers a unique opportunity for measuring the form and mass balance of the polar ice sheets. Changes in ice-sheet mass balance are intimately linked to climatic change and variations in the global mean sea level. However, previous altimeter measurements of ice-sheet topography have been made without the use of a well-validated model of the altimeter return. Here, we present a theoretical model of the return which, supported by both observational and experimental evidence, suggests that over vast areas of the higher altitude regions of the ice-sheets, significant radar penetration of the firn occurs at frequencies commonly used for space altimetry. This implies the need for a previously-neglected correction to height measurements which can be as much as 3-3 m, depending on the retracking method and location. Since the degree of radar penetration may exhibit variability over a range of time-scales, failure to account for the effect could lead to erroneous estimates of surface elevation change. The detection of variability in the degree of penetration is of considerable interest from the point of view of monitoring the processes of accumulation and ablation of snow over the ice-sheet surface, as the return is particularly sensitive to conditions within a few centimetres of the surface. The model has wider applications as it may be used in modified form to simulate altimeter return from all smooth surfaces which exhibit a combination of surface and volume scattering, including deserts and the surfaces of the terrestrial planets and their satellites.     

Synthesis of passive microwave and radar altimeter data for estimating accumulation rates of dry polar snow

In this paper, we compare dry-snow extinction coefficients derived from satellite radar altimeter data with brightness temperature data from passive microwave measurements over a portion of the East Antarctic plateau. The comparison between the extinction coefficients and the brightness temperatures shows a strong negative correlation, where the correlation coefficients ranged from –0·87 to –0·95. The large-scale trend shows that the extinction coefficient of the dry polar snow decreases with increasing surface elevation, while the average brightness temperature increases with surface elevation. Our analysis shows that the observed trends are related to geographical variations in scattering coefficient of snow, which, in turn, are controlled by variations in surface temperature and snow accumulation rate. By combining informa.tion present in the extinction coefficient and brightness temperature datasets, we develop a simple semi-empirical model that can be used to obtain accumulation rate estimates of dry polar snow.     

Review of snow water equivalent retrieval methods using spaceborne passive microwave radiometry

ABSTRACT

The physical properties of a snowpack strongly influence the emissions from the substratum, making snow property retrievals feasible by means of the surface brightness temperature observed by passive microwave sensors. Depending on the spatial resolution observed, time series records of daily snow coverage and critical snowpack properties such as snow depth (SD) and snow water equivalent (SWE) could be helpful in applications ranging from modelling snow variations for water resources management in a catchment to global climatologic studies. However, the challenge of including spaceborne SWE products in operational hydrological and hydroclimate modelling applications is very demanding with limited uptake by these systems, mostly attributed to insufficient SWE estimation accuracy. The root causes of this challenge include the coarse spatial resolution of passive microwave (PM) observations that observe highly aggregated snowpack properties at the spaceborne scale, and inadequacies during the retrieval process caused by uncertainties with the forward emission modelling of snow and challenges to find robust parameterizations of the models. While the spatial resolution problem is largely in the realm of engineering design and constrained by physical restrictions, a better understanding of developed and adopted retrieval methodologies can provide the clarity needed to enhance our knowledge in this field. In this paper, we review snow depth and SWE retrieval methods using PM observations, taking only dry snow retrieval processes into consideration. Snow properties using PM observations can be modelled by purely empirical relations based on underlying physical processes, and SD and SWE can be estimated by regression-based approaches. Snow property retrievals have been refined gradually throughout four decades use of PM observations in tandem with better understanding of physical processes, inclusion of better snowpack parameterizations, improved uncertainty analysis frameworks, and applying better inversion algorithms. Studying available methods, we conclude that snowpack parameterization is key to accurate retrieval. By improving retrieval algorithm architectures to better capture dynamic snowpack evolution processes, SWE estimates are likely to improve. We conclude that this challenge can be addressed by coupling emission models and land surface models or integrating weather-driven snowpack evolution into emission models and performing inversion in a Bayesian framework.     

Inundated wetland dynamics over boreal regions from remote sensing: the use of Topex‐Poseidon dual‐frequency radar altimeter observations

This study presents a first attempt to estimate the extent and seasonality of northern wetlands using radar altimeter satellite observations. The sensitivity of the Topex‐Poseidon dual‐frequency radar altimeter to detect inundation is investigated and compared with passive and active microwave satellite measurements along with a land surface climatology database. The C band backscatter altimeter signal clearly tracks passive microwave emissivity observations of wetlands and is able to detect small flooded areas. Because of the nadir incidence angle, the radar altimeter also shows more capability to detect wetlands than the C band scatterometer. Monthly flooded areas are calculated by estimating flooded pixel fractional coverage using the altimeter C band backscatter magnitude and a linear mixing model with dual‐frequency altimeter backscatter difference, C–Ku, to account for vegetation effects. Because of the Topex‐Poseidon satellite spatial coverage, the results are given only from 40° N to 66° N. This region nevertheless represents more than 30% of world's inundated surfaces during the summer. A direct validation of the inundated extent is unfortunately impossible on a large scale, due to the scarcity of quantitative observations. As a consequence, the results are evaluated by comparison with other existing estimates. Radar altimetry estimates, comprising natural wetlands and river/lakes, indicate a maximum inundated area of 1.86×10⁶ km² for July 1993 and 1994 as compared with 1.31×10⁶ km² from passive microwave technique and ～2.10×10⁶ km² from climatology dataset. The wetland seasonal variability derived from the altimeter and passive microwave techniques agrees well. These promising results could soon be applied to the ENVISAT dual‐frequency radar altimeter that will provide a better survey of global inundated surfaces thanks to its much more complete spatial coverage.     

C波段SAR山区积雪面积提取研究

合成孔径雷达(SAR)不仅具有穿云透雾,全天候观测地表的能力,而且可穿透地表覆盖一定深度获取地表覆盖物内部特征信息。利用2011年10景ENVISAT\|ASAR可变极化模式精细图像(ASA_APP_1P)数据,分析比较了黑河上游祁连山冰沟流域不同时段积雪SAR后向散射特性,应用同期的MODIS积雪面积产品确定研究区积雪的累积和消融背景信息。研究表明:由于融雪期积雪含水量上升,SAR图像后向散射系数相比干雪或无雪图像明显降低,经过分析认为广泛应用的-3 dB阈值会明显低估湿雪覆盖范围,-2 dB阈值更适合该地区湿雪面积参数提取。山区积雪融化过程中低海拔区域积雪融化而高海拔山区积雪仍可能为干雪,在提取湿雪像元的基础上,根据Sigmoid函数阈值获取的像元湿雪百分比及DEM信息来提取干雪像元,最终获取整个流域积雪面积信息。通过与Landsat ETM+图像积雪面积分类结果进行比较,总体精度达到78%。积雪累积和消融背景信息的分析表明:误差主要源于流域东北部与西北部低海拔区域积雪快速消融。     

A ground-based radar backscatter investigation in the percolation zone of the Greenland ice sheet

Satellite radar altimeters and scatterometers deployed over ice sheets experience backscatter from the surface and from within the snowpack, termed surface and volume backscatter respectively. In order to assess the errors in satellite altimeter measurements it is vital to know where the return is originating from in the snowpack. This return can vary spatially and temporally. Seasonal variations in the volume backscatter can be a major complicating factor in the radar return from the percolation zone. Ground-based step-frequency radar was deployed in the percolation zone of the Greenland Ice Sheet at ∼ 1945 m elevation (69 51N, 47 15W). Previous measurements in this area made by scientists from the Byrd Polar Research Centre and the University of Kansas, undertaken prior to summer melt events, have shown the strongest backscatter from ice features at around 1 m depth buried beneath the previous end-of-summer surface. In autumn 2004, radar measurements in the Ku band with bandwidths of 1 and 8 GHz were made alongside detailed stratigraphic observations within a 1 km² site. The radar results revealed no continuous reflecting horizons in the upper 3.5 m of the firn. Shallow cores and snowpits also indicated that there were no spatially continuous stratigraphic horizons across the study site. An average electromagnetic wave velocity of 2.11 ± 0.05 × 10⁸ m s^− 1 was determined for the upper metre of the firn. Surface and volume backscatter at vertical incidence were calculated using a standard model. The contribution of the surface backscatter to the total backscatter was on average 6 dB higher than that of the volume backscatter. However, at the higher 8 GHz bandwidth the strongest return frequently originated not from the surface but from within the upper 30 cm of the snowpack, most probably from thin ice layers. At 1 GHz bandwidth these ice layers were not always resolved; their return merged with the surface return, causing it to broaden, with the peak and leading edge moving down. Modelling using density and thickness measurements from shallow cores and snowpits showed that the backscatter from these shallow, thin ice layers could be stronger than the surface return owing to constructive interference from the top and base of the layers.     

水陆两栖飞机的无线电高度数据处理方法研究

分析了水陆两栖飞机因水上起降和机腹船体构型导致的对无线电高度表数据进行零位基准修正、天线位置修正、负高度显示等特殊的处理要求.提出了零位基准设置的判据,建立了基于坐标变换矩阵,利用姿态角数据对零位基准设置、天线布置偏离零位基准等因素产生的测高误差进行修正的无线电高度数据处理方法,将姿态角的修正从俯仰角扩展到横滚角.应用...     

Monitoring snowmelt across the Arctic forest–tundra ecotone using Synthetic Aperture Radar

Detailed snowpack observations, meteorology, topography and landcover classification were integrated with multi‐temporal SAR data to assess its capability for landscape scale snowmelt mapping at the forest–tundra ecotone. At three sites along an approximately 8° latitudinal gradient in the Fennoscandian mountain range, 16 multi‐temporal spaceborne ERS‐2 synthetic aperture radar (SAR) were used for mapping snowmelt.

Comparison of field measurements and backscatter values demonstrates the difficulty of interpreting observed backscatter response because of complex changes in snow properties on diurnal and seasonal temporal scales. Diurnal and seasonal melt–freeze effects in the snowpack, relative to the timing of ERS‐2 SAR image acquisition, effectively reduce the temporal resolution of such data for snow mapping, even at high latitudes.

The integration of diverse data sources did reveal significant associations between vegetation, topography and snowmelt. Several problems with the application of thresholding for the automatic identification of snowmelt were encountered. These largely related to changes in backscattering from vegetation in the late stages of snowmelt. Due to the impact of environmental heterogeneity in vegetation at the forest–tundra ecotone, we suggest that the potential to map snow cover using single polarization C‐band SAR at the forest–tundra ecotone may be limited to tundra areas.     

A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia.

The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987–1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is − 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient − 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation coefficient decreases to 0.29).     

The relationship between tibetan snow depth,ENSO, river discharge and the monsoons of Bangladesh

Using satellite estimates of snow depth, we examine the interannual variability of the monsoon rains of Bangladesh, an area greatly affected by land surface hydrological processes including Himalayan snowpack size, snowmelt river flooding, and Bay of Bengal storm surge. For the twentieth century, we found Bangladesh monsoon rainfall (BMR) to be uncorrelated with the All‐Indian Monsoon Index. This result is consistent with previous findings for shorter time records. We next used a short 9‐year record of satellite estimates of April snow depth for the Himalayan region and concurrent seasonal El Niño–Southern Oscillation (ENSO) conditions in the equatorial Pacific to develop an empirical model that explains a high percentage of BMR interannual variability. Inclusion of late spring river discharge levels further improves the empirical model representation of BMR for June–September. These results, though with a limited length satellite record, suggest that BMR interannual variability is constrained by concurrent ENSO conditions, spring Himalayan snowpack size and land surface flooding. The same results could not be obtained from analyses using satellite estimates of snow cover. These findings stress the need for development of a quality longer record of satellite estimated snow depth. The twentieth‐century analysis also indicates that BMR should be considered independently of Indian monsoon rainfall.     

Ice sheet survey over Antarctica using satellite altimetry: ERS-2, Envisat,SARAL/AltiKa,the key importance of continuous observations along the same repeat orbit

From September 2002 to October 2010, the Envisat radar altimeter surveyed Greenland and Antarctica ice sheets on a 35 day repeat orbit, providing a unique data set for ice sheet mass balance studies. Up to 85 repeat cycles are available and the whole Envisat data set may be along-track processed in order to provide height variability and trend with a good spatial resolution for the objectives of ice sheet survey.

Soon, a joint Centre National d’Etudes Spatiales/Indian Space Research Organisation mission, SARAL (Satellite with Argos and AltiKa), with the AltiKa payload on board, will be launched on exactly the same orbit (less than 1 km of the nomimal orbit in the across-track direction). This will allow an extension of previous European Remote Sensing (ERS) satellite, ERS-1 and ERS-2, and Envisat missions of the European Space Agency (ESA), in particular from the point of view of ice altimetry. However, AltiKa operates in the Ka band (36.8 GHz), a higher frequency than the classical Ku band (13.6 GHz), leading to important modifications and potential improvements in the interactions between radar wave and snow-pack.

In this paper, a synthesis is presented of all available information relevant to ice altimetry scientific purposes as derived from the Envisat mission: mean and temporal derivatives of the height ? but also of the backscatter and of the two waveform parameters ? snow-pack change corrections, across-track surface slope at 1 km scale, etc. The spatial and temporal variability of ice sheet surface elevation is investigated with the help of the high-resolution Envisat along-track observations. We show that at least 50 repeat cycles are needed to reach the required accuracy for the elevation trend. It is thus advocated as potentially highly beneficial for SARAL/AltiKa as a follow-on mission. Moreover, the novel characteristics of SARAL/AltiKa are promising in improving our understanding of snow penetration impact.     

Hourly simulations of the microwave brightness temperature of seasonal snow in Quebec, Canada, using a coupled snow evolution-emission model

To interpret the snowpack evolution, and in particular to estimate snow water equivalent (SWE), passive microwave remote sensing has proved to be a useful tool given its sensitivity to snow properties. However, the main uncertainties using existing SWE algorithms arise from snow metamorphism which evolves during the winter season, and changes the snow emissivity. To consider the evolution in snow emissivity a coupled snow evolution-emission model can be used to simulate the brightness temperature (T_B) of the snowpack.During a dedicated campaign in the winter season, from November to April, of 2007-2008 two surface-based radiometers operating at 19 GHz and 37 GHz continuously measured the passive microwave radiation emitted through a seasonal snowpack in southern Quebec (Canada). This paper aims at modeling and interpreting this time series of T_B over the whole season, with an hourly step, using a coupled multi-layer snow evolution-emission model. The thermodynamic snow evolution model, referred as to Crocus, was driven by local meteorological measurements. Results from this model provided, in turn, the input variables to run the Microwave Emission Model of Layered Snowpacks (MEMLS) in order to predict T_B at 19 GHz and 37 GHz for both vertical (V) and horizontal (H) polarizations. The accuracy of T_B predicted by the Crocus-MEMLS coupled model was evaluated using continuous measurements from the surface-based radiometers.The weather conditions observed during the winter season were diverse, including several warm periods with melting snow and rain-on-snow events, producing very complex variations in the time series of T_B. To aid our analysis, we identified days with melting snow versus days with dry snow. The Crocus-MEMLS coupled model was able to accurately predict melt events with a success rate of 86%. The residual error was due to an overestimation of the duration of several melt events simulated by Crocus. This problem was explained by 1) a limitation of percolation, and 2) a very long-acting melt of lower layers due to geothermal flux.When the snowpack was completely dry, the global trend of T_B during the season was characterized by a decrease of T_B due to growth in the snow grain size. During most of the season, Crocus-MEMLS correctly predicted the evolution of T_B resulting from temperature gradient metamorphism; the root mean square errors ranged between 2.8 K for the 19 GHz vertical polarization (19V) and 6.9 K for the 37 GHz horizontal polarization (37H). However, during dry periods near the end of the season, the values of T_B were strongly overestimated. This overestimation was mainly due to a limitation of the growth of large snow grains in the wet snowpack simulated by Crocus. This effect was confirmed by estimating snow grain sizes from the observed T_B and the coupled model. The estimated snow grain sizes were larger and more realistic than those initially predicted by the Crocus model.     

Snow optical properties for different particle shapes with application to snow grain size retrieval and MODIS/CERES radiance comparison over Antarctica

We investigated the single scattering optical properties of snow for different ice particle shapes and degrees of microscopic scale roughness. These optical properties were implemented and tested in a coupled atmosphere-snow radiative transfer model. The modeled surface spectral albedo and radiance distribution were compared with surface measurements. The results show that the reflected radiance and irradiance over snow are sensitive to the snow grain size and its vertical profile. When inhomogeneity of the particle size distribution in the vertical is taken into account, the measured spectral albedo can be matched, regardless of the particle shapes. But this is not true for the modeled radiance distribution, which depends a lot on the particle shape. The usual “equivalent spheres” assumption significantly overestimates forward reflected radiances, and underestimates backscattering radiances, around the principal plane. On average, the aggregate shape assumption has the best agreement with the measured radiances to a mean bias within 2%.The snow optical properties with the aggregate assumption were applied to the retrieval of snow grain size over the Antarctic plateau. The retrieved grain sizes of the top layer showed similar and large seasonal variation in all years, but only small year to year variation. Using the retrieved snow grain sizes, the modeled spectral and broadband radiances showed good agreements with MODIS and CERES measurements over the Antarctic plateau. Except for the MODIS 2.13 μm channel, the mean relative model-observation differences are within few percent. The modeled MODIS radiances using measured surface reflectance at Dome C also showed good agreement in visible channels, where radiation is not sensitive to snow grain size and the measured surface bidirectional reflectance is applicable over the Antarctic plateau. But modeled radiances using local, surface-measured reflectance in the near infrared yielded large errors because of the high sensitivity to the snow grain size, which varies spatially and temporally. The CERES broadband shortwave radiance is moderately sensitive to the snow grain size, comparable to the MODIS 0.86 μm channel. The variation of broadband snow reflectance due to the seasonal variation in snow grain size is about 5% in a year over the Antarctic plateau. CERES broadband radiances simulated with grain sizes retrieved using MODIS are about 2% larger than those observed.     

Snow depth inverted by scattering indices of SSM/I channels in a mesh graph

The accuracy of snow depth estimation is affected significantly by the regional surface type. We have developed a theoretical model of vector radiative transfer (VRT) for snowpack/vegetation canopies at SSM/I channels. The vegetation canopy is modelled by a layer of nonspherical particles, and the snowpack is modelled as a layer of dense spherical particles. By numerically solving two coupled VRT equations for multi-layer models of different surface types such as tree/snow, grass/snow and snowpack only, two scattering indices SI1 = T B19v - T B37v and SI2 = T B22v - T B85v are obtained for a variety of snow depths (SD) and ice-grain sizes. These results are combined as a mesh graph in the figure of SI1 versus SI2 . When the SSM/I TB data is observed, its location in the mesh graph can indicate the estimation of SD. Our results compare well with the SSM/I data of the U.S.A. east coast January blizzard, 1996.     

Sea level and surface current variability in the Gulf of St Lawrence from satellite altimetry

Sea level and surface current variability in the Gulf of St Lawrence have been investigated primarily using seven years of TOPEX/Poseidon altimeter data. An orthogonal response analysis is used to derive an annual cycle from 1-s altimetric data along satellite ground tracks, while simultaneously removing aliased residual tides and dynamic signals at alias tide frequencies. An examination of tidal-frequency variability points to the need for a better tide model for detiding altimetric data in order to study shorter (than seasonal) period processes in the Gulf of St Lawrence. Annual sea level amplitudes and phase fields are constructed from the along-track analysis results using a linear interpolation procedure. The altimetric annual harmonic has a magnitude of 2-5 cm in amplitude and is highest in fall. The altimetric sea level results agree well with independent tide-gauge data at coastal stations and can be accounted for mainly by steric height. Geostrophic surface current anomalies derived from the altimetric annual sea level anomalies are then discussed in conjunction with numerical solutions from a regional hydrodynamic model. Interannual sea level change in the Gulf of St Lawrence is also investigated from both altimetry and tide-gauge data, indicating a prominent gulf-wide sea level drop around 1997, with exact timing dependent on location. The interannual sea level variability is thought to be primarily associated with the Labrador Current transport variability (via both the Strait of Belle Isle and Cabot Strait) and the south-north fluctuation of the Gulf Stream position (via Cabot Strait).     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Sea surface wind speed and sea state retrievals from dual-frequency altimeter and its preliminary application in global view of wind-sea and swell distributions

Altimeter radar backscatter intensity, in terms of the normalized radar cross section (NRCS), is known to be modulated by surface wind forcing and the state of wind-sea development. Based on a data set of collocated altimeters (including Topex/Poseidon, Jason-1 and Jason-2) and in situ measurements, different responses to various wind speeds and wave ages (i.e. the state of wind-sea development) were illustrated for altimeter dual-frequency NRCSs (K_u-band at 13.6 Hz and C band at 5.4 Hz), which can facilitate the retrieval of wind speed and wave age parameters. A statistical parametric algorithm was developed to retrieve the two dynamic parameters from the altimeter dual-frequency NRCSs using the neutral network method. The wind-sea significant wave height (SWH) was estimated from wind speed and wave age parameters, which partitions the swell SWH from the altimeter SWH measurement. All newly derived parameters were well validated by comparison against in situ buoy measurements. A preliminary application of the method in examining the swell or wind-sea contributions to global waves was performed; it was found the swell dominance in an open ocean, and the wind-sea dominance in marginal and semi-enclosed seas. The methods would benefit other applications such as studies of air–sea interactions, validation of wave model, determination of swell decay rate and studies of wave climate.