Atmospheric stilling leads to prolonged thermal stratification in a large shallow polymictic lake

To quantify the effects of recent and potential future decreases in surface wind speeds on lake thermal stratification, we apply the one-dimensional process-based model MyLake to a large, shallow, polymictic lake, Võrtsjärv. The model is validated for a 3-year period and run separately for 28 years using long-term daily atmospheric forcing data from a nearby meteorological station. Model simulations show exceptionally good agreement with observed surface and bottom water temperatures during the 3-year period. Similarly, simulated surface water temperatures for 28 years show remarkably good agreement with long-term in situ water temperatures. Sensitivity analysis demonstrates that decreasing wind speeds has resulted in substantial changes in stratification dynamics since 1982, while increasing air temperatures during the same period had a negligible effect. Atmospheric stilling is a phenomenon observed globally, and in addition to recent increases in surface air temperature, needs to be considered when evaluating the influence of climate change on lake ecosystems

State of the climate in 2013

In 2013, the vast majority of the monitored climate variables reported here maintained trends established in recent decades. ENSO was in a neutral state during the entire year, remaining mostly on the cool side of neutral with modest impacts on regional weather patterns around the world. This follows several years dominated by the effects of either La Niña or El Niño events. According to several independent analyses, 2013 was again among the 10 warmest years on record at the global scale, both at the Earths surface and through the troposphere. Some regions in the Southern Hemisphere had record or near-record high temperatures for the year. Australia observed its hottest year on record, while Argentina and New Zealand reported their second and third hottest years, respectively. In Antarctica, Amundsen-Scott South Pole Station reported its highest annual temperature since records began in 1957. At the opposite pole, the Arctic observed its seventh warmest year since records began in the early 20th century. At 20-m depth, record high temperatures were measured at some permafrost stations on the North Slope of Alaska and in the Brooks Range. In the Northern Hemisphere extratropics, anomalous meridional atmospheric circulation occurred throughout much of the year, leading to marked regional extremes of both temperature and precipitation. Cold temperature anomalies during winter across Eurasia were followed by warm spring temperature anomalies, which were linked to a new record low Eurasian snow cover extent in May. Minimum sea ice extent in the Arctic was the sixth lowest since satellite observations began in 1979. Including 2013, all seven lowest extents on record have occurred in the past seven years. Antarctica, on the other hand, had above-average sea ice extent throughout 2013, with 116 days of new daily high extent records, including a new daily maximum sea ice area of 19.57 million km2 reached on 1 October. ENSO-neutral conditions in the eastern central Pacific Ocean and a negative Pacific decadal oscillation pattern in the North Pacific had the largest impacts on the global sea surface temperature in 2013. The North Pacific reached a historic high temperature in 2013 and on balance the globally-averaged sea surface temperature was among the 10 highest on record. Overall, the salt content in nearsurface ocean waters increased while in intermediate waters it decreased. Global mean sea level continued to rise during 2013, on pace with a trend of 3.2 mm yr-1 over the past two decades. A portion of this trend (0.5 mm yr-1) has been attributed to natural variability associated with the Pacific decadal oscillation as well as to ongoing contributions from the melting of glaciers and ice sheets and ocean warming. Global tropical cyclone frequency during 2013 was slightly above average with a total of 94 storms, although the North Atlantic Basin had its quietest hurricane season since 1994. In the Western North Pacific Basin, Super Typhoon Haiyan, the deadliest tropical cyclone of 2013, had 1-minute sustained winds estimated to be 170 kt (87.5 m s-1) on 7 November, the highest wind speed ever assigned to a tropical cyclone. High storm surge was also associated with Haiyan as it made landfall over the central Philippines, an area where sea level is currently at historic highs, increasing by 200 mm since 1970. In the atmosphere, carbon dioxide, methane, and nitrous oxide all continued to increase in 2013. As in previous years, each of these major greenhouse gases once again reached historic high concentrations. In the Arctic, carbon dioxide and methane increased at the same rate as the global increase. These increases are likely due to export from lower latitudes rather than a consequence of increases in Arctic sources, such as thawing permafrost. At Mauna Loa, Hawaii, for the first time since measurements began in 1958, the daily average mixing ratio of carbon dioxide exceeded 400 ppm on 9 May. The state of these variables, along with dozens of others, and the 2013 climate conditions of regions around the world are discussed in further detail in this 24th edition of the State of the Climate series. © 2014, American Meteorological Society. All rights reserved

Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model

A global constant value of the extinction coefficient (<i>K</i>_d) is usually specified in lake models to parameterize water clarity. This study aimed to improve the performance of the 1-D freshwater lake (FLake) model using satellite-derived <i>K</i>_d for Lake Erie. The CoastColour algorithm was applied to MERIS satellite imagery to estimate <i>K</i>_d. The constant (0.2 m⁻¹) and satellite-derived <i>K</i>_d values as well as radiation fluxes and meteorological station observations were then used to run FLake for a meteorological station on Lake Erie. Results improved compared to using the constant <i>K</i>_d value (0.2 m⁻¹). No significant improvement was found in FLake-simulated lake surface water temperature (LSWT) when <i>K</i>_d variations in time were considered using a monthly average. Therefore, results suggest that a time-independent, lake-specific, and constant satellite-derived <i>K</i>_d value can reproduce LSWT with sufficient accuracy for the Lake Erie station. <br><br>A sensitivity analysis was also performed to assess the impact of various <i>K</i>_d values on the simulation outputs. Results show that FLake is sensitive to variations in <i>K</i>_d to estimate the thermal structure of Lake Erie. Dark waters result in warmer spring and colder fall temperatures compared to clear waters. Dark waters always produce colder mean water column temperature (MWCT) and lake bottom water temperature (LBWT), shallower mixed layer depth (MLD), longer ice cover duration, and thicker ice. The sensitivity of FLake to <i>K</i>_d variations was more pronounced in the simulation of MWCT, LBWT, and MLD. The model was particularly sensitive to <i>K</i>_d values below 0.5 m⁻¹. This is the first study to assess the value of integrating <i>K</i>_d from the satellite-based CoastColour algorithm into the FLake model. Satellite-derived <i>K</i>_d is found to be a useful input parameter for simulations with FLake and possibly other lake models, and it has potential for applicability to other lakes where <i>K</i>_d is not commonly measured.</p

Simulation of surface temperature and ice cover of large northern lakes with 1-D models: a comparison with MODIS satellite data and in situ measurements

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&#x0027;s Northwest Territories, using the 1-D Freshwater Lake model (FLake) and the Canadian Lake Ice Model (CLIMo) over the 2002&#x2013;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&#x2009; &#x2264;&#x200A;&#x2009;relative index of agreement&#x2009;&#x200A;&#x2264;&#x200A;&#x2009;0.984 and 0.94&#x2009;&#x200A;&#x2264;&#x200A;&#x2009;mean bias error&#x2009;&#x200A;&#x2264;&#x200A;&#x2009;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&#x2009;cm thicker on average by the end of winter compared to in situ measurements; 9&#x2009;cm thicker for CLIMo) and break-up dates (6&#x2009;d earlier in comparison with in situ measurements; 3&#x2009;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

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

The seasonal evolution of snow and ice on Lake Orajärvi, 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.–Apr.), 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 50–70% 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=0.81). The HIGHTSI surface temperatures were, however, higher (2.8°C≤MBE≤3.9°C) 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