Evolution of snow and ice temperature, thickness and energy balance in Lake Orajärvi, northern Finland

Abstract

A B S T R A C TThe seasonal evolution of snow and ice on Lake Oraja¨rvi, northern Finland, was investigated for three consecutive winter seasons. Material consisting of numerical weather prediction model (HIRLAM) output, weather station observations, manual snow and ice observations, high spatial resolution snow and ice temperatures from ice mass balance buoys (SIMB), and Moderate Resolution Imaging Spectroradiometer (MODIS) lake ice surface temperature observations was gathered. A snow/ice model (HIGHTSI) was applied to simulate the evolution of the snow and ice surface energy balance, temperature profiles and thickness. The weather conditions in early winter were found critical in determining the seasonal evolution of the thickness of lake ice and snow. During the winter season (Nov.ÁApr.), precipitation, longwave radiative flux and air temperature showed large inter-annual variations. The uncertainty in snow/ice model simulations originating from precipitation was investigated. The contribution of snow to ice transformation was vital for the total lake ice thickness. At the seasonal time scale, the ice bottom growth was 50Á70% of the total ice growth. The SIMB is suitable for monitoring snow and ice temperatures and thicknesses. The Mean Bias Error (MBE) between the SIMB and borehole measurements was (0.7 cm for snow thicknesses and 1.7 cm for ice thickness. The temporal evolution of MODIS surface temperature (three seasons) agrees well with SIMB and HIGHTSI results (correlation coefficient, R 00.81). The HIGHTSI surface temperatures were, however, higher (2.88C5MBE53.98C) than the MODIS observations. The development of HIRLAM by increasing its horizontal and vertical resolution and including a lake parameterisation scheme improved the atmospheric forcing for HIGHTSI, especially the relative humidity and solar radiation. Challenges remain in accurate simulation of snowfall events and total precipitation.

Sodankylä manual snow survey program

“…They were also applied in the monitoring of soil processes (Rautiainen et al, 2012), in the retrieval of snow density and ground permittivity from L-band radiometry (Lemmetyinen et al, 2016a) and in the study of seasonally and spatially varying snow cover brightness temperature . Cheng et al (2014) applied lake ice measurements to validate buoy-based measurements of lake snow and ice thicknesses. Moreover, snow pit and lake ice measurements were applied by Kontu et al (2014) to study the effect of snow and ice-covered lakes and wetlands to microwave brightness temperature simulation accuracy.…”

Ice Freeze-up and Break-up Detection of Shallow Lakes in Northern Alaska with Spaceborne SAR

“…In such case, it is feasible to combine observations from both sensors in each pixel during an hour. The MODIS UW-L3 LSWT/LIST product has been evaluated against in situ temperature measurements over Finnish lakes [36,39] as well as one-dimensional lake models over two large Canadian lakes [35].…”

The impact of meteorological conditions on snow and ice thickness in an Arctic lake

“…The model has been further developed and adapted to investigate lake snow and ice (Yang et al, , 2013Semmler et al, 2012;Cheng et al, 2014). The details of model physics for lake ice are summarised in Yang et al (2012) and Cheng et al (2014).…”

“…The formation of lake ice strongly depends on the heat exchange at the iceÁwater interface, on the radiative and turbulent heat fluxes at the ice/snow surface, as well as on precipitation (Yang et al, 2013;Cheng et al, 2014). In freshwater lakes, the water column is well mixed before freezing.…”