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Accurate simulations of freshwater lake ice are integral for the study of climatic variability in northern environments. Surface albedo, a component often parameterized in lake ice models, has been shown to affect the timing of ice break-up during the melt season. In situ snow and ice albedo measurements were taken over a partially snow-covered freshwater lake near Churchill, Manitoba for the evaluation of the albedo parameterization of the Canadian Lake Ice Model (CLIMo) and the Moderate Resolution Imaging Spectrometer (MODIS) albedo products (MOD10A1/MYD10A1 and MCD43A3). The albedo simulations using CLIMo were performed with and without snow integrated into the model and evaluated against in situ albedo measurements recorded over clear ice, snow ice and snow-covered ice. The simulated snow albedo from CLIMo for the entire ice growth season evaluated against snow albedo observations had a root mean square error of 0.07, a mean absolute error of 0.06, and a mean bias error (MBE) of −0.01. With snow removed from CLIMo, the albedo parameterization overestimated albedo values measured in the field over snow-free clear ice and snow ice with MBE values of 0.13 and 0.10, respectively. These findings suggest that CLIMo's bare ice albedo parameterization needs to be revised to account for albedo differences between ice types. The evaluation of the MODIS albedo products with in situ snow and ice albedo observations and the comparison of these satellite products with CLIMo's albedo parameterization during the melt period, when in situ radiation measurement stations needed to be removed from the lake-ice surface, are addressed in paper Part II (this issue). Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Albedo products (MOD10A1, MYD10A1, and MCD43A3) from the Moderate Resolution Imaging Spectrometer (MODIS) have the potential to be integrated directly into lake ice models such as the Canadian lake ice model (CLIMo) to improve the simulation of freshwater break-up (ice-off). The high albedo of snow and lake ice has been shown to affect the timing of break-up. Therefore, the surface energy balance parameterization of CLIMo requires accurate estimates of albedo when modelling phenology. MOD10A1, MYD10A1, and MCD43A3 were evaluated against in situ snow and ice albedo observations taken over a partially snow-covered freshwater lake (Malcolm Ramsay Lake) near Churchill, Manitoba, during the ice growth period (15 February 2012 to 25 April 2012). The MODIS albedo products were then compared with the CLIMo's albedo parameterization during the ice break-up period. The MODIS albedo products MOD10A1, MYD10A1, and MCD43A3 retrieved snow and ice albedo with root mean square error values of 0.07, 0.08, and 0.06, respectively, compared with spatially averaged in situ albedo measurements during ice growth. MODIS albedo products compared with CLIMo's melting ice parameterization during the melt season indicate that CLIMo's albedo estimates have a mean difference of at least 0.14 compared with the MODIS retrievals during melt. The quality of the albedo retrievals over lake ice from MODIS and the need for more accurate albedo simulations during the melt season suggest that the assimilation of MODIS albedo products into CLIMo could be beneficial for the determination of break-up (ice-off) dates. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Arctic field studies have indicated that the air temperature, soil moisture and vegetation at a site influence the quantity of snow accumulated, and that snow accumulation can alter growing-season soil moisture and vegetation. Climate change is predicted to bring about warmer air temperatures, greater snow accumulation and northward movements of the shrub and tree lines. Understanding the responses of northern environments to changes in snow and growing-season land surface characteristics requires: (1) insights into the present-day linkages between snow and growing-season land surface characteristics; and (2) the ability to continue to monitor these associations over time across the vast pan- Arctic. The objective of this study was therefore to examine the pan-Arctic (north of 60_ N) linkages between two temporally distinct data products created from AMSR-E satellite passive microwave observations: GlobSnow snow water equivalent (SWE), and NTSG growing-season AMSRE Land Parameters (air temperature, soil moisture and vegetation transmissivity). Due to the complex and interconnected nature of processes determining snow and growing-season land surface characteristics, these associations were analyzed using the modern nonparametric technique of alternating conditional expectations (ACE), as this approach does not impose a predefined analytic form. Findings indicate that regions with lower vegetation transmissivity (more biomass) at the start and end of the growing season tend to accumulate less snow at the start and end of the snow season, possibly due to interception and sublimation. Warmer air temperatures at the start and end of the growing season were associated with diminished snow accumulation at the start and end of the snow season. High latitude sites with warmer mean annual growing-season temperatures tended to accumulate more snow, probably due to the greater availability of water vapor for snow season precipitation at warmer locations. Regions with drier soils preceding snow onset tended to accumulate greater quantities of snow, likely because drier soils freeze faster and more thoroughly than wetter soils. Understanding and continuing to monitor these linkages at the regional scale using the ACE approach can allow insights to be gained into the complex response of Arctic ecosystems to climate-driven shifts in air temperature, vegetation, soil moisture and snow accumulation. [ABSTRACT FROM AUTHOR]

Time series of brightness temperatures (TB) 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). TB 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. [ABSTRACT FROM AUTHOR]

The article presents a study which compares the land surface temperatures (LST) values from MODIS to ground-based near-surface air and ground surface temperature (GST) measurements at herbaceous sites in permafrost zone including Northern Québec, Nunavik and Canada. It reveals that LSTs are in stronger agreement with round-based near-surface air during the snow cover season than in the snow free season. The potential of MODIS LSTs for monitoring surface temperature changes is offered.

Lake surface temperature (LST) and ice phenology were simulated for various points differing in depth on Great Slave Lake and Great Bear Lake, two large lakes located in the Mackenzie River Basin in Canada's Northwest Territories, using the 1-D Freshwater Lake model (FLake) and the Canadian Lake Ice Model (CLIMo) over the 2002-2010 period, forced with data from three weather stations (Yellowknife, Hay River and Deline). LST model results were compared to those derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observing System Terra and Aqua satellite platforms. Simulated ice thickness and freeze-up/break-up dates were also compared to in situ observations. Both models showed a good agreement with daily average MODIS LSTs on an annual basis (0.935 5 relative index of agreement 5 0.984 and 0.94 5 mean bias error 5 4.83). The absence of consideration of snow on lake ice in FLake was found to have a large impact on estimated ice thicknesses (25 cm thicker on average by the end of winter compared to in situ measurements; 9 cm thicker for CLIMo) and break-up dates (6 d earlier in comparison with in situ measurements; 3 d later for CLIMo). The overall agreement between the two models and MODIS LST products during both the open water and ice seasons was good. Remotely sensed data are a promising data source for assimilation into numerical weather prediction models, as they provide the spatial coverage that is not captured by in situ data. [ABSTRACT FROM AUTHOR]

The article presents a study on lake ice in the Arctic region of North America. It mentions that lakes contain a large portion of the surface cover in the continent which form a significant part of the cryosphere. It notes the timing of lake ice break-up or freeze-up which is an effective indicator of climate change and variability. It also points out the cause of ice regime alteration that could lead to changes in the ecosystem such as the disappearance of ice cover and species shifts.

The article reports on the patterns and changes in lake ice in the Arctic in 2013. Topics discussed include the use of lake ice as a sensitive indicator of climate variability and change, the ground-based observations of increasingly later freeze-up and earlier break-up dates, and the increasing air temperature trends.