US Long-Term Ecological Research Network

Fluxes project at North Temperate Lakes LTER: Hydrology Scenarios Model Output

Abstract
A spatially-explicit simulation model of hydrologic flow-paths was developed by Matthew C. Van de Bogert and collaborators for his PhD project, "Aquatic ecosystem carbon cycling: From individual lakes to the landscape." The model is coupled with an in-lake carbon model and simulates hydrologic flow paths in groundwater, wetlands, lakes, uplands, and streams. The goal of this modeling effort was to compare aquatic carbon cycling in two climate scenarios for the North Highlands Lake District (NHLD) of northern Wisconsin: one based on the current climate and the other based on a scenario with warmer winters where lakes and uplands do not freeze, hereinafter referred to as the "no freeze" scenario. In modeling this "no freeze" scenario the same precipitation and temperature data as the current climate model was used, however temperature inputs were artificially floored at 0 degrees Celsius. While not discussed in his dissertation, Van de Bogert considered two other climate scenarios each using the same precipitation and temperature data as the current climate scenario. These scenarios involved running the model after artificially raising and lowering the current temperature data by 10 degrees Celsius. Thus, four scenarios were considered in this modeling effort, the current climate scenario, the "no freeze" scenario, the +10 degrees scenario, and the -10 degrees scenario. These data are the outputs of the model under the different scenarios and include average monthly temperature, average monthly rainfall, average monthly snowfall, total monthly precipitation, daily evapotranspiration, daily surface runoff, daily groundwater recharge, and daily total runoff. Note that the results of how temperature inputs influence aquatic carbon cycling under these different scenarios is not included in this data set, refer to Van de Bogert (2011) for this information. Documentation: Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156.
Core Areas
Dataset ID
286
Date Range
-
Metadata Provider
Methods
The spatially explicit Lakes, Uplands, Wetlands Integrator (LUWI) model of the NHLD was used to explore the interactions among climate, watershed connections, hydrology and carbon cycling. See Cardille et al. 2007 and Cardille et al. 2009 for details on the LUWI model. See Van de Bogert (2011) for a discussion of how these model outputs are used in conjunction with LUWI to predict the effects on lake carbon cycling under the current and "no freeze" climate scenarios.The climate data used in this modeling effort, precipitation and temperature, were obtained from Minoqua, Wisconsin, USA from 1948-2000. In order to test the effect of a climate without freezing temperatures on lake water and carbon cycling the current climate was modeled in addition to a “no freeze” scenario where a minimum air temperature of 0 degrees Celsius was imposed on the model. Note that Van de Bogert (2011) only focuses on the current and “no freeze” climate scenarios, but these data are representative of four climate scenarios: the current climate (base_minoqua_precip), the scenario where the current climate is artificially floored to zero degrees Celsius (no_below_zero), and the scenarios where the current climate is increased and decreased by 10 degrees Celsius (minus_10_degrees and plus_10_degrees).Furthermore, the temperature and precipitation data that was used for the current climate model runs was broken up into aggregates.The aggregates are the length of the 1948-2000 Minoqua temperature and precipitation data that was used in model runs. A total of seven different aggregates were used for model runs under each of the four climate scenarios. The aggregates include temperature and precipitation data from Minoqua, WI, USA for 1. the complete record from 1948-2000 (1948_2000) 2. the driest year which was 1976 (1976_driest) 3. The wettest year which was 1953 (1953_wettest) 4. the five driest years on record from 1948-2000 (5_driest) 5. the five wettest years on record from 1948-2000 (5_wettest) 6. the five coldest years on record for December, January, and February from 1948-2000 (5_coldest_djf) 7. the five warmest years on record for December, January, and February from 1948-2000 (5_warmest_djf).The volume and timing of precipitation to the region were unchanged between scenarios.Evaporation rates were derived from values obtained from the NTL-LTER study site, Sparkling Lake (46.01, -89.70). Refer to Van de Bogert (2011) for a more complete discussion of model inputs and a discussion of the results of the model output. Documentation: Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156.Cardille, J.A., Carpenter, S.R., Coe, M.T., Foley, J.A., Hanson, P.C., Turner, M.G., Vano, J.A., 2007. Carbon and water cycling in lake-rich landscapes: Landscape connections, lake hydrology, and biogeochemistry. Journal of Geophysical Research-Biogeosciences 112.Cardille, J.A., Carpenter, S.R., Foley, J.A., Hanson, P.C., Turner, M.G., Vano, J.A., 2009. Climate change and lakes: Estimating sensitivities of water and carbon budgets. Journal of Geophysical Research-Biogeosciences 114.
Version Number
20

Additional Daily Meteorological Data for Madison Wisconsin (1884-2010)

Abstract
These data are in addition to "Madison Wisconsin Daily Meteorological Data 1869-current." Additional variables added include: daily cloud cover, wind, solar radiation, vapor pressure, dew point temperature, total atmospheric pressure, and average relative humidity for Madison, Wisconsin. In addition, the adjustment factors which were applied on a given date to calculate the adjusted parameters in "Madison Wisconsin Daily Meteorological Data 1869-current" are also included in these data. Raw data, in English units, were assembled by Douglas Clark - Wisconsin State Climatologist. Data were converted to metric units and adjusted for temporal biases by Dale M. Robertson. For adjustments applied to various parameters see Robertson, 1989 Ph.D. Thesis UW-Madison. Adjusted data represent the BEST estimated daily data and may be raw data. Data collected at Washburn observatory, 8-1-1883 to 9-30-1904. Data collected at North Hall, 10-1-1904 to 12-31-1947 Data collected at Truax Field (Admin BLDG), 1-1-1948 to 12-31-1959. Data collected at Truax Field, center of field, 1-1-1960 to Present. Much of the data after 1990 were obtained in digital form from Ed Hopkins, UW-Meteorology. Data starting in 2002-2005 were obtained from Sullivan at http://www.weather.gov/climate/index.php?wfo=mkx%20 ,then go to CF6 and download monthly data to Madison_sullivan_conversion. Relative humidity data was obtained from 1986 to 1995 from CD's at the State Climatologist's Office. Since Robertson (1989) adjusted all historical data to that collected prior to 1989; no adjustments were applied to the recent data except for wind and estimated vapor pressure. Wind after January 1997, and only wind from the southwest after November 2007, was extended by Dale M. Robertson and Yi-Fang "Yvonne" Hsieh, see methods. Estimated vapor pressure after April 2002 was updated by Yvonne Hsieh, see methods.
Dataset ID
282
Date Range
-
Metadata Provider
Methods
Raw data (in English units) were assembled by Douglas Clark - Wisconsin State Climatologist. Data were converted to metric units and adjusted for temporal biases by Dale M. Robertson. For adjustments applied to various parameters see Robertson, 1989 Ph.D. Thesis UW-Madison. Adjusted data represent the BEST estimated daily data and may be raw data. Data collected at Washburn observatory, 8-1-1883 to 9-30-1904. Data collected at North Hall, 10-1-1904 to 12-31-1947 Data collected at Truax Field (Admin BLDG), 1-1-1948 to 12-31-1959. Data collected at Truax Field (Center of Field), 1-1-1960 to Present. Much of the data after 1990 were obtained in digital form from Ed Hopkins, UW-Meteorology. Data starting in 2002-05 were obtained from Sullivan at <a href="http://www.weather.gov/climate/index.php?wfo=mkx%20">http://www.weather.gov/climate/index.php?wfo=mkx</a> ,then go to CF6 and download monthly data to Madison_sullivan_conversion. Since Robertson (1989) adjusted all historical data to that collected from 1884-1989; no adjustments were applied to the recent data except for (1) wind and (2) estimated vapor pressure:(1) Wind after January 1997, and only wind from the southwest after November 2007, was extended by Dale M. Robertson and Yvonne Hsieh.In 1996, a discontinuity in the wind record was caused by change in observational techniques and sensor locations (Mckee et al. 2000). To address the non-climatic changes in wind speed, data from MSN were carefully compared with those collected from the tower of the Atmospheric and Oceanic Science Building at the University of Wisconsin-Madison, see http://ginsea.aos.wisc.edu/labs/mendota/index.htm. Hourly data from both sites (UMSN,hourly and UAOS,hourly) during 2003&ndash;2010 were used to form a 4&times;12 (four components of wind direction &times; 12 months) matrix (K4,12) of wind correction factors, yielding UAOS,daily= Ki,j&times;UMSN,daily. The comparison results indicated that the MSN weather station reported a higher magnitude in winds out of the east by 5% and lower magnitude in winds out of the west and south by 30% and 10%. The adjusted wind data (=Ki,j&times;UMSN,daily) were therefore employed and used in the model simulation. After adjustments, there was a decrease in wind velocities starting shortly before 1996. Overall the adjusted wind data had a decline in wind velocities of 16% from 1988&ndash;93 to 1994&ndash;2009) compared to a 7% decline at a nearby weather station with no known observational changes (St. Charles, Illinois; 150 km southeast of Lake Mendota). (2) Estimated vapor pressure was updated (after April 2002) by using the equation from DYRESM for estimation of vapor pressure (a function of both air temperature and dew point temperature); where a=7.5, b=237.3, and c=.7858.
Version Number
23
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