A sensitivity analysis of soil moisture retrieval from the t-w microwave emission model

The potential of the τ-ω model for retrieving the volumetric moisture content of bare and vegetated soil from dual polarisation passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure and consequently its microwave singlescattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the τ-ω model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated.

EOF analysis of three records of sea-ice concentration spanning the last 30 years

Several continuous observational datasets of Artic sea-ice concentration are currently available that cover the period since the advent of routine satellite observations. We report on a comparison of three sea-ice concentration datasets. These are the National Ice Center charts, and two passive microwave radiometer datasets derived using different approaches: the NASA team and Bootstrap algorithms. Empirical orthogonal function (EOF) analyses were employed to compare modes of variability and their consistency between the datasets. The analysis was motivated by the need for a reliable, realistic sea ice climatology for use in climate model simulations, for which both the variability and absolute values of extent and concentration are important. We found that, while there are significant discrepancies in absolute concentrations, the major modes of variability derived from all records were essentially the same.

Global snow mass measurements and the effect of stratigraphic detail on inversion of microwave brightness temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

Spatio-temporal variability of polynya dynamics and ice production in the Laptev Sea between the winters of 1979/80 and 2007/08

Polynyas in the Laptev Sea are examined with respect to recurrence and interannual wintertime ice production.We use a polynya classification method based on passive microwave satellite data to derive daily polynya area from long-term sea-ice concentrations. This provides insight into the spatial and temporal variability of open-water and thin-ice regions on the Laptev Sea Shelf. Using thermal infrared satellite data to derive an empirical thin-ice distribution within the thickness range from 0 to 20 cm, we calculate daily average surface heat loss and the resulting wintertime ice formation within the Laptev Sea polynyas between 1979 and 2008 using reanalysis data supplied by the National Centers for Environmental Prediction, USA, as atmospheric forcing. Results indicate that previous studies significantly overestimate the contribution of polynyas to the ice production in the Laptev Sea. Average wintertime ice production in polynyas amounts to approximately 55 km39 27% and is mostly determined by the polynya area, wind speed and associated large-scale circulation patterns. No trend in ice production could be detected in the period from 1979/80 to 2007/08.

New perspectives on the synoptic and mesoscale structure of Hurricane Catarina

This work explores in detail synoptic and mesoscale features of Hurricane Catarina during its life cycle from a decaying baroclinic wave to a tropical depression that underwent tropical transition (TT) and finally to a Category 2 hurricane at landfall over Santa Catarina State coast, southern Brazil. This unique system caused 11 deaths mostly off the Brazilian coast and an estimated half billion dollars in damage in a matter of a few hours on 28 March 2004. Although the closest meteorological station available was tens of kilometres away from the eye, in situ meteorological measurements provided by a work-team sent to the area where the eye made landfall unequivocally reproduces the tropical signature with category 2 strength, adding to previous analysis where this data was not available. Further analyses are based mostly on remote sensing data available at the time of the event. A classic dipole blocking set synoptic conditions for Hurricane Catarina to develop, dynamically contributing to the low wind shear observed. On the other hand, on its westward transit, large scale subsidence limited its strength and vertical development. Catarina had relatively cool SST conditions, but this was mitigated by favourable air-sea fluxes leading to latent heat release-driven processes during the mature phase. The ocean`s dynamic topography also suggested the presence of nearby warm core rings which may have facilitated the transition and post-transition intensification. Since there were no records of such a system at least in the past 30 years and given that SSTs were generally below 26 degrees C and vertical shear was usually strong, despite all satellite data available, the system was initially classified as an extratropical cyclone. Here we hypothesise that this categorization was based oil inadequate regional scale model outputs which did not account for the importance of the latent heat fluxes over the ocean. Hurricane Catarina represents a dramatic event on weather systems in South America. It has attracted attention worldwide and poses questions as whether or not it is a symptom of global warming. (C) 2009 Elsevier B.V. All rights reserved.

Evaluation of operational SSM/I ice-concentration algorithms

The United States National Ice Center (NIC) provides weekly ice analyses of the Arctic and Antarctic using information from ice reconnaissance, ship reports and high-resolution satellite imagery. In cloud-covered areas and regions lacking imagery, the higher-resolution sources are augmented by ice concentrations derived from Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMII) passive-microwave imagery. However, the SSMII-derived ice concentrations are limited by low resolution and uncertainties in thin-ice regions. Ongoing research at NIC is attempting to improve the utility of these SSMII products for operational sea-ice analyses. The refinements of operational algorithms may also aid future scientific studies. Here we discuss an evaluation of the standard operational ice-concentration algorithm, Cal/Val, with a possible alternative, a modified NASA Team algorithm. The modified algorithm compares favorably with CallVal and is a substantial improvement over the standard NASA Team algorithm in thin-ice regions that are of particular interest to operational activities.

Daily polynya area and ice production in the North Water polynya region

The North Water (NOW) Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada) at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1) sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS)) and (2) thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison with MODIS data (thin-ice thickness < 20 cm) shows that the wintertime polynya area estimates derived by MODIS are about 30 to 40% higher than those derived using the polynya signature simulation method (PSSM) with AMSR-E data. In turn, the difference in polynya area between PSSM and a sea ice concentration (SIC) threshold of 70% is fairly low (approximately 10%) when applied to AMSR-E data. For the coarse-resolution SSM/I-SSMIS data, this difference is much larger, particularly in November and December. Instead of a sea ice concentration threshold, the PSSM method should be used for SSM/I-SSMIS data. Depending on the type of cloud-cover correction, the calculated ice production based on MODIS data reaches an average value of 264.4 ± 65.1 km**3 to 275.7 ± 67.4 km**3 (2002/2003 to 2014/2015) and shows a high interannual variability. Our achieved long-term results underline the major importance of the NOW polynya considering its influence on Arctic ice production and associated atmosphere/ocean processes.

(Table 1) Ice thickness at lake Nam Co, Tibet, during 2008-2009

Lake ice change is one of the sensitive indicators of regional and global climate change. Different sources of data are used in monitoring lake ice phenology nowadays. Visible and Near Infrared bands of imagery (VNIR) are well suited for the observation of freshwater ice change, for example data from AVHRR and MODIS. Active and passive microwave data are also used for the observation of lake ice, e.g., from satellite altimetry and radiometry, backscattering coefficient from QuickSCAT, brightness temperature (Tb) from SSM/I, SMMR, and AMSR-E. Most of the studies are about lake ice cover phenology, while few studies focus on lake ice thickness. For example, Hall et al. using 5 GHz (6 cm) radiometer data showed a good relationship between Tb and ice thickness. Kang et al. found the seasonal evolution of Tb at 10.65 GHz and 18.7 GHz from AMSR-E to be strongly influenced by ice thickness. Many studies on lake ice phenology have been carried out since the 1970s in cold regions, especially in Canada, the USA, Europe, the Arctic, and Antarctica. However, on the Tibetan Plateau, very little research has focused on lake ice-cover change; only a small number of published papers on Qinghai Lake ice observations. The main goal of this study is to investigate the change in lake ice phenology at Nam Co on the Tibetan Plateau using MODIS and AMSR-E data (monitoring the date of freeze onset, the formation of stable ice cover, first appearance of water, and the complete disappearance of ice) during the period 2000-2009.

Onset of south summer snowmelt on Antarctic sea ice between 1988 and 2007

The annual onset of snowmelt on sea ice is essential for climate monitoring since it triggers a decrease in surface albedo that feeds back into a stronger absorption of shortwave radiation - a process known as the snowmelt-albedo feedback - and thus strongly modifies the surface energy balance during summer. Algorithms designed for the detection of snowmelt on Arctic sea ice and based on longterm passive-microwave data revealed the melt season in the Arctic from 1979 to 1998 to be significantly elongated and the onset of melt to be shifted toward earlier dates.

Daily MODIS composites of thin-ice thickness and ice-surface temperatures for the Southern Weddell Sea

Based upon high-resolution thermal-infrared Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with ERA-Interim atmospheric reanalysis data, we derived long-term polynya parameters such as polynya area, thin-ice thickness distribution and ice-production rates from daily cloud-cover corrected thin-ice thickness composites. Our study is based on a thirteen year investigation period (2002-2014) for the austral winter (1 April to 30 September) in the Antarctic Southern Weddell Sea. The focus lies on coastal polynyas which are important hot spots for new-ice formation, bottom-water formation and heat/moisture release into the atmosphere. MODIS has the capability to resolve even very narrow coastal polynyas. Its major disadvantage is the sensor limitation due to cloud cover. We make use of a newly developed and adapted spatial feature reconstruction scheme to account for cloud-covered areas. We find the sea-ice areas in front of Ronne and Brunt Ice Shelf to be the most active with an annual average polynya area of 3018 ± 1298 and 3516 ± 1420 km2 as well as an accumulated volume ice production of 31 ± 13 and 31 ± 12 km**3, respectively. For the remaining four regions, estimates amount to 421 ± 294 km**2 and 4 ± 3 km**3 (Antarctic Peninsula), 1148 ± 432 km**2 and 12 ± 5 km**3 (Iceberg A23A), 901 ± 703 km**2 and 10 ± 8 km**3 (Filchner Ice Shelf) as well as 499 ± 277 km**2 and 5 ± 2 km**3 (Coats Land). Our findings are discussed in comparison to recent studies based on coupled sea-ice/ocean models and passive-microwave satellite imagery, each investigating different parts of the Southern Weddell Sea.

Daily ice production and polynya area in the Laptev Sea region during 1979-2009

Polynyas in the Laptev Sea are examined with respect to recurrence and interannual wintertime ice production.We use a polynya classification method based on passive microwave satellite data to derive daily polynya area from long-term sea-ice concentrations. This provides insight into the spatial and temporal variability of open-water and thin-ice regions on the Laptev Sea Shelf. Using thermal infrared satellite data to derive an empirical thin-ice distribution within the thickness range from 0 to 20 cm, we calculate daily average surface heat loss and the resulting wintertime ice formation within the Laptev Sea polynyas between 1979 and 2008 using reanalysis data supplied by the National Centers for Environmental Prediction, USA, as atmospheric forcing. Results indicate that previous studies significantly overestimate the contribution of polynyas to the ice production in the Laptev Sea. Average wintertime ice production in polynyas amounts to approximately 55 km3 ± 27% and is mostly determined by the polynya area, wind speed and associated large-scale circulation patterns. No trend in ice production could be detected in the period from 1979/80 to 2007/08.