(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.

(Table 1) Normalized difference vegetation index in control and warming plots, Abisco Research Station

Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys. Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone. The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.

Area-averaged mean seasonal cycles of chlorophyll-a concentration, sea surface temperature, alongshore wind stress, westward wind speed and dust component of the aerosol optical depth at 550 nm

Nutrient supply in the area off Northwest Africa is mainly regulated by two processes, coastal upwelling and deposition of Saharan dust. In the present study, both processes were analyzed and evaluated by different methods, including cross-correlation, multiple correlation, and event statistics, using remotely sensed proxies of the period from 2000 to 2008 to investigate their influence on the marine environment. The remotely sensed chlorophyll-a concentration was used as a proxy for the phytoplankton biomass stimulated by nutrient supply into the euphotic zone from deeper water layers and from the atmosphere. Satellite-derived alongshore wind stress and sea-surface temperature were applied as proxies for the strength and reflection of coastal upwelling processes. The westward wind and the dust component of the aerosol optical depth describe the transport direction of atmospheric dust and the atmospheric dust column load. Alongshore wind stress and induced upwelling processes were most significantly responsible for the surface chlorophyll-a variability, accounting for about 24% of the total variance, mainly in the winter and spring due to the strong north-easterly trade winds. The remotely sensed proxies allowed determination of time lags between biological response and its forcing processes. A delay of up to 16 days in the surface chlorophyll-a concentration due to the alongshore wind stress was determined in the northern winter and spring. Although input of atmospheric iron by dust storms can stimulate new phytoplankton production in the study area, only 5% of the surface chlorophyll-a variability could be ascribed to the dust component in the aerosol optical depth. All strong desert storms were identified by an event statistics in the time period from 2000 to 2008. The 57 strong storms were studied in relation to their biological response. Six events were clearly detected in which an increase of chlorophyll-a was caused by Saharan dust input and not by coastal upwelling processes. Time lags of <8 days, 8 days, and 16 days were determined. An increase in surface chlorophyll-a concentration of up to 2.4 mg m**3 after dust storms in which the dust component of the aerosol optical depth was up to 0.9 was observed.

(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.

(Table 1) Ice flux, polynya area and sea-ice drift speed in the Kara Sea during winter (Jan-Apr) 1997-2001

The Shelf Seas of the Arctic are known for their large sea-ice production. This paper presents a comprehensive view of the Kara Sea sea-ice cover from high-resolution numerical modeling and space-borne microwave radiometry. As given by the latter the average polynya area in the Kara Sea takes a value of 21.2 × 10**3 km**2 ± 9.1 × 10**3 km**2 for winters (Jan.-Apr.) 1996/97 to 2000/01, being as high as 32.0 × 10**3 km**2 in 1999/2000 and below 12 × 10**3 km**2 in 1998/99. Day-to-day variations of the Kara Sea polynya area can be as high as 50 × 10**3 km**2. For the seasons 1996/97 to 2000/01 the modeled cumulative winter ice-volume flux out of the Kara Sea varied between 100 km**3/a and 350 km**3/a. Modeled high (low) ice export coincides with a high (low) average and cumulative polynya area, and with a low (high) sea-ice compactness in the Kara Sea from remote sensing data, and with a high (low) sea-ice drift speed across its northern boundary derived from independent model data for the winters 1996/97 to 2000/01.

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.

Circumarctic wetland dataset based on ENVISAT ASAR Global Monitoring Mode with links to geotiff image and NetCDF files (2005-01 to 2011-12)

A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.