Georg Heygster

Frost flowers on sea ice as a source of sea salt and their influence on tropospheric halogen chemistry

[1] Frost flowers grow on newly-formed sea ice from a saturated water vapour layer. They provide a large effective surface area and a reservoir of sea salt ions in the liquid phase with triple the ion concentration of sea water. Recently, frost flowers have been recognised as the dominant source of sea salt aerosol in the Antarctic, and it has been speculated that they could be involved in processes causing severe tropospheric ozone depletion events during the polar sunrise. These events can be explained by heterogeneous autocatalytic reactions taking place on salt-laden ice surfaces which exponentially increase the reactive gas phase bromine (‘‘bromine explosion’’). We analyzed tropospheric bromine monoxide (BrO) and the sea ice coverage both measured from satellite sensors. Our model based interpretation shows that young ice regions potentially covered with frost flowers seem to be the source of bromine found in bromine explosion events. INDEX TERMS: 0322 Atmospheric Composition and Structure: Constituent sources and sinks; 1640 Global Change: Remote sensing; 3309 Meteorology and Atmospheric Dynamics: Climatology (1620); 3339 Meteorology and Atmospheric Dynamics: Ocean/atmosphere interactions (0312, 4504); 3360 Meteorology and Atmospheric Dynamics: Remote sensing. Citation: Kaleschke, L., et al. (2004), Frost flowers on sea ice as a source of sea salt and their influence on tropospheric halogen chemistry, Geophys. Res. Lett., 31, L16114, doi:10.1029/ 2004GL020655.

Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice

[1] Measurements of sea ice concentration from the Special Sensor Microwave Imager (SSM/I) using seven different algorithms are compared to ship observations, sea ice divergence estimates from the Radarsat Geophysical Processor System, and ice and water surface type classification of 59 wide-swath synthetic aperture radar (SAR) scenes. The analysis is confined to the high-concentration Arctic sea ice, where the ice cover is near 100%. During winter the results indicate that the variability of the SSM/I concentration estimates is larger than the true variability of ice concentration. Results from a trusted subset of the SAR scenes across the central Arctic allow the separation of the ice concentration uncertainty due to emissivity variations and sensor noise from other error sources during the winter of 2003–2004. Depending on the algorithm, error standard deviations from 2.5 to 5.0% are found with sensor noise between 1.3 and 1.8%. This is in accord with variability estimated from analysis of SSM/I time series. Algorithms, which primarily use 85 GHz information, consistently give the best agreement with both SAR ice concentrations and ship observations. Although the 85 GHz information is more sensitive to atmospheric influences, it was found that the atmospheric contribution is secondary to the influence of the surface emissivity variability. Analysis of the entire SSM/I time series shows that there are significant differences in trend between sea ice extent and area, using different algorithms. This indicates that long-term trends in surface and atmospheric properties, unrelated to sea ice concentration, influence the computed trends.

Exploring Arctic Transpolar Drift During Dramatic Sea Ice Retreat

The Arctic is undergoing significant environmental changes due to climate warming. The most evident signal of this warming is the shrinking and thinning of the ice cover of the Arctic Ocean. If the warming continues, as global climate models predict, the Arctic Ocean will change from a perennially ice-covered to a seasonally ice-free ocean. Estimates as to when this will occur vary from the 2030s to the end of this century. One reason for this huge uncertainty is the lack of systematic observations describing the state, variability, and changes in the Arctic Ocean.

Atmospheric water vapor over Antarctica derived from Special Sensor Microwave/Temperature 2 data

In polar regions, satellite microwave radiometry has not been successful in measuring the total water vapor (TWV) in the atmosphere. The difficulties faced in these regions arise from the very low water vapor burden of the atmosphere and the large and highly variable emissivities of ice surfaces in the microwave frequency range. By exploiting the advantages of the Special Sensor Microwave/Temperature 2 (SSM/T2), a method is developed to retrieve TWV over Antarctica from satellite data. This method shows very low sensitivities to the change of surface emissivity and to the presence of water clouds. However, ice clouds may have considerable effects. Results of radiative transfer model simulation show that they may cause one to underestimate TWV using the proposed method and that the amount of underestimation is proportional to the ice water path of the ice cloud. Validations using radiosonde measurements and numerical model analyzes suggest that SSM/T2 retrievals have a high accuracy (maximum error <10%) as long as TWV is <4.0 kg m−2. Above this value, retrievals show a systematic overestimation. Presumably, this is a result of the seasonal difference between the validation and the training radiosonde data sets. TWV retrievals of 1 years SSM/T2 data show clearly the seasonal variation of water vapor over Antarctica. Throughout the year the mean TWV over West Antarctica is nearly twice as high as that over East Antarctica; the temporal fluctuation of TWV over West Antarctica is also significantly stronger than over East Antarctica. This suggests that precipitation and water vapor transport in West Antarctica are more active than in East Antarctica. Using the same years TWV data, we estimated the mean residence time of atmospheric water vapor over the Antarctica to be merely 3–4 days. This, however, is much shorter than the global mean of 9–10 days.

Spatial resolution improvement of SSM/I data with image restoration techniques

A space variant image restoration algorithm has been developed with the aim of improving the spatial resolution of SSM/I (Special Sensor Microwave/Imager) passive microwave imagery. Due to the conical scanning of the instrument the relative geometry of the data samples changes over the scan. This change is accounted for by using a space variant point-spread-function in the restoration algorithm. Application of this algorithm to a scene from the Weddell Sea results in an image with enhanced ice edge and coast definition. As a result ice concentration estimates near the edge agree more closely with higher resolution (optical) data from AVHRR. >

Polynya Signature Simulation Method polynya area in comparison to AMSR-E 89 GHz sea-ice concentrations in the Ross Sea and off the Adelie Coast, Antarctica, for 2002-05: first results

Abstract The Polynya Signature Simulation Method (PSSM) is applied to Special Sensor Microwave/Imager observations from different Defense Meteorological Satellite Program spacecraft for 2002–05 to analyze the polynya area in the Ross Sea (Ross Ice Shelf polynya (RISP) and Terra Nova Bay polynya (TNBP)) and off the Adélie Coast (Mertz Glacier polynya (MGP)), Antarctica, on a sub-daily scale. The RISP and the MGP exhibit similar average total polynya areas. Major area changes (>10000km2; TNPB: >2000km2) occur over a range of 2–3 to 20 days in all regions. Sub-daily area changes are largest for the MGP (5800km2) and smallest for the TNBP (800km2), underlining the persistence of the forcing of the latter. ARTIST sea-ice (ASI) algorithm concentration maps obtained using 89 GHz Advanced Microwave Scanning Radiometer (AMSR-E) data are compared to PSSM maps, yielding convincing agreement in the average, similarly detailed winter polynya distribution. Average ASI algorithm ice concentrations take values of 25–40% and 65–80% for the PSSM open-water and thin-ice class, respectively. The discrepancy with expected values (0% and 100%) can be explained by the different spatial resolution and frequency used by the methods. A new land mask and a mask to flag icebergs are introduced. Comparison of PSSM maps with thermal ice thickness based on AVHRR infrared temperature and ECMWF ERA-40 data suggests an upper thickness limit for the PSSM thin-ice class of 20–25 cm.

Topographic Mapping of the German Tidal Flats Analyzing SAR Images With the Waterline Method

The waterline method is used to derive the topography of the tidal flats along the German coast by evaluation of synthetic aperture radar (SAR) images. A series of about 70 European Remote Sensing Satellites SAR images of the German Bight taken at different water levels within four years is analyzed to detect the borderline between tidal flats and adjacent water areas using a wavelet-based edge-detection algorithm. After geocoding, the waterlines are combined with the corresponding water levels to represent the topography on an irregularly spaced grid. The water levels are taken from a numerical tide model and corrected with the measured gauge data. Interpolation of these data into a regular grid yields a topographic map of the intertidal zone. While the general practicability of this method has been demonstrated in previous studies for smaller test areas, this paper is the first attempt to generate maps of a large area on a yearly basis.

A combined radiative transfer model for sea ice, open ocean, and atmosphere

A radiative transfer model to compute brightness temperatures in the microwave frequency range for polar regions including sea ice, open ocean, and atmosphere has been developed and applied to sensitivity studies and retrieval algorithm development. The radiative transfer within sea ice is incorporated according to the “many layer strong fluctuation theory” of Stogryn [1986, 1987] and T. Grenfell [Winebrenner et al., 1992]. The reflectivity of the open water is computed with the three-scale model of Schrader [1995]. Both surface models supply the bistatic scattering coefficients, which define the lower boundary for the atmospheric model. The atmospheric model computes the gaseous absorption by the Liebe et al. [1993] model. Scattering by hydrometeors is determined by Mie or Rayleigh theory. Simulated brightness temperatures have been compared with special sensor microwave imager (SSM/I) observations. The comparison exhibits shortcomings of the ice model for 37 GHz. Applying a simple ad hoc correction at this frequency gives consistent comparison results within the range of observational accuracy. The simulated brightness temperatures show the strong influence of clouds and variations of wind speed over the open ocean, which will affect the sea ice retrieval even for an ice-covered ocean. Simulated brightness temperatures have been used to train a neural network algorithm for the total sea ice concentration, which accounts for these effects. Sea ice concentrations sensed from the SSM/I data using the network and the NASA sea ice algorithm show systematic differences in dependence on cloudiness.

Surface Emissivity of Arctic Sea Ice at AMSU Window Frequencies

A method to retrieve the surface emissivity of sea ice at the window channels of the Advanced Microwave Sounding Unit (AMSU) radiometers in the polar region is presented. The instruments are on the new-generation satellites of the U.S. National Oceanic and Atmospheric Administration (NOAA-15, NOAA-16, and NOAA-17). The method assumes hypothetical surfaces with emissivities zero and one and simulates brightness temperatures at the top of the atmosphere using profiles of atmospheric parameters, e.g., from the European Centre for Medium-Range Weather Forecasts (ECMWF) model runs, as input for a radiative transfer model. The retrieval of surface emissivity is done by combining simulated brightness temperatures with the satellite-measured brightness temperature. The AMSU window channels differ in surface penetration depths and, thus, in the surface microphysical parameters that they depend on. Lowest layer air temperatures from ECMWF are used to infer temperatures of emitting layers at different frequencies of sea ice. A complete yearly cycle of monthly average emissivities in two selected regions (first- and multiyear ice) is giving insight into the variation of emissivities in various development stages of sea ice.

Improved Retrieval of Total Water Vapor Over Polar Regions From AMSU-B Microwave Radiometer Data

The polar regions are among those where the least information is available about the current and predicted states of surface and atmosphere. We present advances in a method to retrieve the total water vapor (TWV) of the polar atmosphere from data from spaceborne microwave radiometers such as the Advanced Microwave Sounding Unit B (AMSU-B) on the polar-orbiting satellites of the National Oceanic and Atmospheric Administration (NOAA), NOAA-15, -16, and -17. The starting point of the retrieval is a recently proposed algorithm that uses the three AMSU-B channels centered around the 183-GHz water vapor line and the window channel at 150 GHz, and that can retrieve the TWV with little dependence on the surface emissivity. This works up to TWV values of about 7 kg/m2. We extend the retrievable range toward higher TWV values by including the window channel at 89 GHz. However, now, the algorithm needs information on the surface emissivity, which we have extracted from emissivity measurements over sea ice and open water during the Surface Emissivities in Polar Regions-Polar Experiment campaign. The resulting algorithm can retrieve TWV up to about 15 kg/m2, with reduced accuracy as compared to the original algorithm. It now allows the monitoring of the TWV over the central Arctic sea ice and over Antarctica, and the surrounding sea ice during most of the year with a spatial resolution of about 50 km. Such TWV fields can show details which might be missed out by standard weather model analysis data.