Online Resource #2. Historical and future climate scenarios

Climatic Change manuscript-CLIM-D-16-00498: Prediction of Lake Water Temperature, Dissolved Oxygen, and Fish Habitat under Changing Climate.

Authors: Shahram Missaghi; Miki Hondzo; William Herb

Corresponding author: Shahram Missaghi,

Three different types of climateconditions of historical normal (HN, year 2000), future normal(FN), and future extreme (FE) scenarios were selected for the study. The annual Ta average (x axis) of 30 historical years (normal, 1981-2010) were plotted against the average annual P (y axis) with the intersection of the axes representing the same climate normals (Ta = 7.78 °C and P = 0.78 myr-1) as reported by the National Oceanic and Atmospheric Administration (NOAA, 2012) for the study area (Fig. 2a). The distance from each of the 30 points to the center was evaluated to identify the year nearest to the climate normal (center) as a surrogate for HN scenario and to identify the year farthest from the center as an extreme year. To generate future meteorological climate scenarios of FN and FE, we applied the projected mean monthly meteorological change fields to the two base scenarios of HN and extreme year. The change fields method is a hybrid between Global Climate Model (GCM) predicted outputs and the local historical observed metrological data (Smith & Tirpak, 1989) where the differences (or ratio for P) between the GCM outputs of a control period (predicted historical climate) and future period (predicted future normal climate) is applied to the local historical observed metrological data. The set of monthly CFs (e.g. 2040-2069 minus 1961-1990) selected for this study (Table 1) were obtained from International Panel on Climate Change Data Distribution Centre (IPCC DDC, 2012) for the grid point (45° 42’ N; 93° 38’ W) nearest to the study area. The selected CFs were based on the output of the high-resolution Model for Interdisciplinary Research on Climate (MIROC3.2), a coupled general circulation model, appropriate for use in the study area region (Jiang et al., 2012).

The year 2000 with the nearest annual average of Ta and P to climate normals (Ta = 7.78 °C and P = 0.78 myr-1) was designated as the HN scenario for our study (Fig. 2a) and was used as a base year to construct FN scenario. The set of change fields (Table 1) were applied to the meteorological data of the HN scenario to generate the FN scenario. Extreme climate events, defined as those greater than 90th percentiles (Fowler et al., 2007) could have Ta, and P values that may place them in any of the four quadrants in Fig. 2a. We investigated the predicted trend of Ta and P by plotting their bias corrected model (MIROC3.2) historical (1981-2000) and future (2041-2070) annual averages around the climate normals (Fig. 2a). The predicted future Ta and P annual averages were generally in the direction of warmer and wetter annual averages, similar to the results of other investigations (ICAT, 2013). Based on these findings, year 2005 which had the longest distance from the climate normals (Fig. 2b) and also resided in the warmer and wetter quadrant was considered as the historical extreme year (Ta= 9.02 °C; P=0.85 my-1). The year 2005 was then used as a base for thefuture extreme case. The same set of monthly CFs used for developing FN scenario (Table 1) was also applied to the metrological data of the year 2005 to generate the FE scenario. A drawback of using the CFs method is that it relies on the observed and historical statistical relationships and patterns that may not continue to hold true under future scenarios. The CFs method shifts the historical data into predicted future data. An advantage of the CFs method is that it enables estimation of future climate scenarios that include all seven variables (Table 1) needed as model inputs.

Reference

Fowler H., Blenkinsop S. & Tebaldi C. (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology, 27, 1547-1578.

Interagency Climate Adaptation team - ICAT (2010) Adapting to climate change in Minnesota. Preliminary report of the Interagency Climate Adaptation Team.Report No.p-gen4-07, Minnesota Pollution Control Agency.

Jiang L., Fang X., Stefan H.G., Jacobson P.C. & Pereira D.L. (2012) Oxythermal habitat parameters and identifying cisco refuge lakes in Minnesota under future climate scenarios using variable benchmark periods. Ecological Modelling, 232, 14-27.

National Oceanic and Atmospheric Administration (NOAA ) (2012) Climate Monitoring Products, US Temperature and Precipitation - 2000 and 2005. ( 2000, 1.

The Intergovernmental Panel on Climate Change Data Distribution Center (DDC) (17 June 2013) 1/10/2014, 1.

Smith J.B. & Tirpak D.A. (1989) The potential effects of global climate change on the United States: Report to Congress. US Environmental Protection Agency, Office of Policy, Planning, and Evaluation, Office of Research and Development.

Table 1. The set of monthly Change Fields, obtained from the International Panel on Climate Change Data Distribution Centre, that were applied to the meteorological data of the normal climate and the extreme climate year within the climate normal period (1981-2010) in order to create the future normal and future extreme meteorological climate scenarios.

Air temperature
(°C) / Relative Humidity*
% / Cloud Cover*
(0-1) / Atmospheric
Pressure
(pa) / Wind
Speed
(ms-1) / Solar
Radiation
(Wm-2) / Precipitation
(mm d-1)
Jan / 4.21 / -0.47 / -0.07 / -40.53 / 0.16 / 16.53 / 0.57
Feb / 4.61 / -4.07 / -0.09 / 50.14 / 0.22 / 14.15 / 0.06
Mar / 4.47 / -6.94 / -0.06 / 42.03 / 0.34 / 16.13 / 0.10
Apr / 3.54 / -1.47 / -0.02 / 44.09 / 0.16 / 18.64 / 0.33
May / 4.67 / 0.94 / -0.03 / -53.70 / 0.20 / 31.30 / 0.04
Jun / 3.75 / -3.14 / -0.04 / 99.25 / 0.09 / 22.88 / -0.48
Jul / 3.63 / -4.17 / -0.05 / 2.12 / 0.16 / 23.10 / -1.05
Aug / 3.52 / -2.34 / -0.04 / 7.62 / 0.10 / 23.86 / -0.20
Sep / 3.88 / -2.50 / -0.06 / 167.24 / 0.08 / 22.71 / -0.05
Oct / 4.43 / -0.77 / -0.05 / 128.29 / 0.20 / 22.98 / 0.82
Nov / 4.71 / -4.31 / -0.09 / -7.66 / 0.43 / 17.85 / 0.52
Dec / 4.08 / -3.83 / -0.08 / 43.47 / 0.22 / 14.54 / 0.11

*These values were not obtained from International Panel on Climate Change Data Distribution Centre, but calculated by taking the differences between averaged 2040-2069 and averaged 1961-1990 values.

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