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.

Robust trends of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks, with links to GeoTIFFs

Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.

Comparisons of observed ice properties and Envisat Advanced Synthetic Aperture Radar (ASAR) data during Nathanial B. Palmer cruise NBP09-01 and Oden cruise OSO08/09

Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images are used to derive C-band HH-polarization normalized radar cross sections (NRCS). These are compared with ice-core analysis and visual ship-based observations of snow and ice properties observed according to the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol during two International Polar Year summer cruises (Oden 2008 and Palmer 2009) in West Antarctica. Thick first-year (TFY) and multi-year (MY) ice were the dominant ice types. The NRCS value ranges between -16.3 ± 1.1 and -7.6 ± 1.0 dB for TFY ice, and is -12.6 ± 1.3 dB for MY ice; for TFY ice, NRCS values increase from ~-15 dB to -9 dB from December/January to mid-February. In situ and ASPeCt observations are not, however, detailed enough to interpret the observed NRCS change over time. Co-located Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) vertically polarized 37 GHz brightness temperatures (TB37V), 7 day and 1 day averages as well as the TB37V difference between ascending and descending AMSR-E overpasses suggest the low NRCS values (-15 dB) are associated with snowmelt being still in progress, while the change towards higher NRCS values (-9dB) is caused by commencement of melt-refreeze cycles after about mid-January.

(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.

(Table 3) Air temperatures, and snow and ice characteristics of fresh and brackish water lakes in the Northwest Territories, Canada

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 80x100 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.

High resolution color reflectance and hematite and goethite record of ODP Hole 184-1143A in the South China Sea

Precipitation has a larger variability than temperature in tropical monsoon regions, thus it is an important climate variable. However, reconstructions of long-term rainfall histories are scarce because of the lack of reliable proxies. Here we document that iron oxide minerals, specifically the ratio of hematite to goethite (Hm/Gt), is a reasonable precipitation proxy. Using diffuse reflectance spectrophotometry, we measured samples from Ocean Drilling Program (ODP) 1143 drilling site (9°21.72'N, 113°17.11'E, 2777 m water depth) for hematite and goethite, whose formation processes are favored by opposing climate conditions. In order to determine the content of hematite and goethite we produced a set of calibration samples by removing the iron oxides to generate the natural matrix to which hematite and goethite in known percentages were added. From these calibration samples we developed a transfer function for determining hematite and goethite concentration from a sample's spectral reflectance. Applying this method to ODP 1143 sediments (top 34 m of a 510 m core with sampling interval of 10 cm) we were able to reconstruct a continuous precipitation history for SE Asia of the past 600 kyr using the Hm/Gt ratio as a proxy of the precipitation variability of Asian monsoon. The reliability of this Hm/Gt proxy is corroborated by its consistency with the stalagmite delta18O data from South China. Comparing long-term Hm/Gt records with the surface temperature gradient of equatorial Pacific Ocean, we found that monsoon precipitation and El Niño are correlated for the last 600 kyr. The development of El Niño-like conditions decreased SE Asia precipitation, whereas precipitation increases in response to La Niña intensification

(Table 1) Mean temperatures in january and july, and total annual snowfall at Great Bear Lake and Great Slave Lake, Canada

The sensitivity of brightness temperature (T(B)) at 6.9, 10.7, and 18.7 GHz from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) observations is investigated over five winter seasons (2002-2007) on Great Bear Lake and Great Slave Lake, Northwest Territories, Canada. The T(B) measurements are compared to ice thicknesses obtained with a previously validated thermodynamic lake ice model. Lake ice thickness is found to explain much of the increase of T(B) at 10.7 and 18.7 GHz. T(B) acquired at 18.7 GHz (V-pol) and 10.7 GHz (H-pol) shows the strongest relation with simulated lake ice thickness over the period of study (R**2 > 0.90). A comparison of the seasonal evolution of T(B) for a cold winter (2003-2004) and a warm winter (2005-2006) reveals that the relationship between T(B) and ice growth is stronger in the cold winter (2003-2004). Overall, this letter shows the high sensitivity of T(B) to ice growth and, thus, the potential of AMSR-E mid-frequency channels to estimate ice thickness on large northern lakes.

Temperature affects the morphology and calcification of Emiliania huxleyi strains

The global warming debate has sparked an unprecedented interest in temperature effects on coccolithophores. The calcification response to temperature changes reported in the literature, however, is ambiguous. The two main sources of this ambiguity are putatively differences in experimental setup and strain-specificity. In this study we therefore compare three strains isolated in the North Pacific under identical experimental conditions. Three strains of Emiliania huxleyi type A were grown under non-limiting nutrient and light conditions, at 10, 15, 20 and 25 ºC. All three strains displayed similar growth rate versus temperature relationships, with an optimum at 20-25 ºC. Elemental production (particulate inorganic carbon (PIC), particulate organic carbon (POC), total particulate nitrogen (TPN)), coccolith mass, coccolith size, and width of the tube elements cycle were positively correlated with temperature over the sub-optimum to optimum temperature range. The correlation between PIC production and coccolith mass/size supports the notion that coccolith mass can be used as a proxy for PIC production in sediment samples. Increasing PIC production was significantly positively correlated with the percentage of incomplete coccoliths in one strain only. Generally, coccoliths were heavier when PIC production was higher. This shows that incompleteness of coccoliths is not due to time shortage at high PIC production. Sub-optimal growth temperatures lead to an increase in the percentage of malformed coccoliths in a strain-specific fashion. Since in total only six strains have been tested thus far, it is presently difficult to say whether sub-optimal temperature is an important factor causing malformations in the field. The most important parameter in biogeochemical terms, the PIC:POC, shows a minimum at optimum growth temperature in all investigated strains. This clarifies the ambiguous picture featuring in the literature, i.e. discrepancies between PIC:POC-temperature relationships reported in different studies using different strains and different experimental setups. In summary, global warming might cause a decline in coccolithophore's PIC contribution to the rain ratio, as well as improved fitness in some genotypes due to less coccolith malformations.

Land Surface Temperature continuous time series from SSM/I passive microwave radiometers, over northern latitudes (Latitudes > 45°N), during summer snow free period (2000-2011), with links to NetCDF files

Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.

Seasonal mean air temperatures and ice phenology characteristics of Great Bear Lake and Great Slave Lake (2002-2009)

Time series of brightness temperatures (T(B)) from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) are examined to determine ice phenology variables on the two largest lakes of northern Canada: Great Bear Lake (GBL) and Great Slave Lake (GSL). T(B) measurements from the 18.7, 23.8, 36.5, and 89.0 GHz channels (H- and V- polarization) are compared to assess their potential for detecting freeze-onset/melt-onset and ice-on/ice-off dates on both lakes. The 18.7 GHz (H-pol) channel is found to be the most suitable for estimating these ice dates as well as the duration of the ice cover and ice-free seasons. A new algorithm is proposed using this channel and applied to map all ice phenology variables on GBL and GSL over seven ice seasons (2002-2009). Analysis of the spatio-temporal patterns of each variable at the pixel level reveals that: (1) both freeze-onset and ice-on dates occur on average about one week earlier on GBL than on GSL (Day of Year (DY) 318 and 333 for GBL; DY 328 and 343 for GSL); (2) the freeze-up process or freeze duration (freeze-onset to ice-on) takes a slightly longer amount of time on GBL than on GSL (about 1 week on average); (3) melt-onset and ice-off dates occur on average one week and approximately four weeks later, respectively, on GBL (DY 143 and 183 for GBL; DY 135 and 157 for GSL); (4) the break-up process or melt duration (melt-onset to ice-off) lasts on average about three weeks longer on GBL; and (5) ice cover duration estimated from each individual pixel is on average about three weeks longer on GBL compared to its more southern counterpart, GSL. A comparison of dates for several ice phenology variables derived from other satellite remote sensing products (e.g. NOAA Interactive Multisensor Snow and Ice Mapping System (IMS), QuikSCAT, and Canadian Ice Service Database) show that, despite its relatively coarse spatial resolution, AMSR-E 18.7 GHz provides a viable means for monitoring of ice phenology on large northern lakes.