The goal of this table is to record specific climate variables, indices, and/or thresholds that were used in climate adaptation work throughout the Great Lakes region.
Possible topics include: Lake Levels, Human Health, Agriculture, Water Resources, Urban Adaptation, Tribal, Ecosystem, etc...
Metric |
Definition |
Reference |
Topic |
---|---|---|---|
Lake Evaporation |
High lake evaporation (0.4-0.6 inches per day) requires three factors: 1) a large temperature difference between water and air (warm water and cold air), 2) low relative humidity, 3) high wind speed. |
Lenters, J. D., J. B. Anderton, P. Blanken, C. Spence, and A. E. Suyker, 2013: Assessing the Impacts of Climate Variability and Change on Great Lakes Evaporation. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center: http://glisaclimate.org/media/GLISA_Lake_Evaporation.pdf | Lake Levels |
Lake Evaporation | High ice cover were usually followed by cooler summer water temperatures and lower evaporation rates. | Lenters, J. D., J. B. Anderton, P. Blanken, C. Spence, and A. E. Suyker, 2013: Assessing the Impacts of Climate Variability and Change on Great Lakes Evaporation. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center:http://glisaclimate.org/media/GLISA_Lake_Evaporation.pdf | Lake Levels |
Physical controls on lake evaporation | Most of the energy for evaporation comes from solar radiation, but the primary solar input occurs roughly five months prior to the annual peak in evaporation. | Lenters, J. D., J. B. Anderton, P. Blanken, C. Spence, and A. E. Suyker, 2013: Assessing the Impacts of Climate Variability and Change on Great Lakes Evaporation. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center:http://glisaclimate.org/media/GLISA_Lake_Evaporation.pdf | Lake Levels |
Spatial variability of lake evaporation | Highest evaporation rates tend to occur in the nearshore regions of Lake Superior during September and October, particularly along the southern shore.This switches to offshore regions by January and February, when ice cover begins to limit evaporation in nearshore regions. | Lenters, J. D., J. B. Anderton, P. Blanken, C. Spence, and A. E. Suyker, 2013: Assessing the Impacts of Climate Variability and Change on Great Lakes Evaporation. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center:http://glisaclimate.org/media/GLISA_Lake_Evaporation.pdf | Lake Levels |
Temporal variability of lake evaporation | The annual peak in evaporation is found to occur during the months of October, December, and January. | Lenters, J. D., J. B. Anderton, P. Blanken, C. Spence, and A. E. Suyker, 2013: Assessing the Impacts of Climate Variability and Change on Great Lakes Evaporation. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center:http://glisaclimate.org/media/GLISA_Lake_Evaporation.pdf | Lake Levels |
The recruitment to the lake whitefish fishery | In their current habitat space, increased water temperature, increased wind speed, and decreased ice cover are projected to inhibit the success of recruitment to the lake white fish fishery | Lynch, A.J., W.W. Taylor, 2013. Designing a Decision Support System for Harvest Management of Great Lakes Lake Whitefish in a Changing Climate. In: GLISA Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Fishery |
Thermal habitat volume for lake whitefish | The warming trends associated with predicted climate change could increase suitable thermal habitat volume for lake whitefish | Lynch, A.J., W.W. Taylor, 2013. Designing a Decision Support System for Harvest Management of Great Lakes Lake Whitefish in a Changing Climate. In: GLISA Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Fishery |
The recruitment to the lake whitefish fishery | The positive relationship between spring temperatures and recruitment with climate change suggests the potential for increased lake whitefish production in the Great Lakes, if habitat is not limiting and sufficient food resources are available when the larvae hatch. However, the negative relationship between fall temperatures, ice cover, and recruitment may inhibit egg survival and, consequently, lake whitefish production. | Lynch, A.J., W.W. Taylor, 2013. Designing a Decision Support System for Harvest Management of Great Lakes Lake Whitefish in a Changing Climate. In: GLISA Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Fishery |
Useful climate change information for the winter sports industry | average maximum winter temperatures; timing of natural snowfall; and, average minimum winter temperatures. | Nicholls, S., B. Amelung, 2013. Attitudes Towards Climate Change: Attitudes Towards and Observations Regarding Climate Variability and Change: Evidence from Michigan’s Downhill Ski Sector. In: GLISA Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Ski area operation |
Heat waves | The heat waves equivalent to the one that killed over 700 people in Chicago in 1995 are projected to occur about once every three years in the Midwest under the lower emissions scenario, and nearly three times a year under the higher emissions scenario | Olabisi,L.S., R. Levine, L. Cameron, M. Beaulac, R. Wahl, and S. Blythe. 2012: A Modeling Framework for Informing Decision Maker Response to Extreme Heat Events in Michigan Under Climate Change. In: 2011Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Extreme heat events |
Heat events | The duration of heat over a number of days, and in particular the elevation of minimum nighttime temperatures without a recuperative period can push the vulnerable into a health crisis. Adverse health effects include heatstroke, heat illness, and exacerbation of chronic conditions such as asthma and cardiovascular disease | Olabisi,L.S., R. Levine, L. Cameron, M. Beaulac, R. Wahl, and S. Blythe. 2012: A Modeling Framework for Informing Decision Maker Response to Extreme Heat Events in Michigan Under Climate Change. In: 2011Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Health |
“1995-like” heat wave | The 1995 Chicago heat wave. This is characterized by at least 7 consecutive days with maximum daily temperatures greater than 32 °C (90 °F) and nighttime minimum temperatures greater than 21 °C (70 °F), with daytime maximum temperatures over 38 °C (100 °F) and nighttime temperatures that remained above 27 °C (80 °F) for at least two of those days | Hayhoe, K., Sheridan, S., Kalkstein, L., & Greene, S. (2010). Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65-73. | Heat wave and health |
Humidex |
A measure that attempts to combine temperature and humidity. Humidex(degC)=Mean temperature(degC) + 0.5555(6.11E-10) E=exp[5417.753((1/271.16)-(1/dew-point temperature(degC)))] where deg K is degrees kelvin. The Humidex was designed to describe the feeling of hot and humid weather for an average person. |
A.G.Barnett, S.Tong, A.C.A.Clements(2010) What measure of temperature is the best predictor of mortality? Environmental Research 110 (2010) 604–611 | Heat wave and health |
Apparent temperature | An index of human discomfort due to the combined effect of heat and humidity, was calculated using the formula of Apparent temperature(degF) = -2.653 + 0.994 * mean temperature(degF) + 0.0153 *[dew-point temperature(degF)], The aim of apparent temperature is to combine the effects of heat and cold with humidity. A rise in apparent temperature in the warm season was associated with increased all-cause mortality in adults |
Lin, S., Luo, M., Walker, R. J., Liu, X., Hwang, S.-A., & Chinery, R. (2009). Extreme High Temperatures and Hospital Admissions for Respiratory and Cardiovascular Diseases. Epidemiology, 20(5), 738-746. |
Heat wave and health |
Daily maximum and minimum temperature. | The extremes of temperature will exert the most physiological pressure and so could be the most important predictor of mortality. Maximum temperature may also be a good measure of exposure because it often occurs in the middle of the day, which could coincide with a peak time for outdoor activity. Conversely, daily minimum temperatures are likely to occur at night when most people are in bed. | A.G.Barnett, S.Tong, A.C.A.Clements(2010) What measure of temperature is the best predictor of mortality? Environmental Research 110 (2010) 604–611 | Heat wave and health |
Urban heat island | As a result of increased temperatures within the urban locales, the UHI may affect the number of hot days as well as the duration of heat waves, potentially increasing the risk of mortality from heat stress, including respiratory failure and circulatory system failure from heart attack or stroke in urban areas. |
Tan, J., Zheng, Y., Tang, X., Guo, C., Li, L., Song, G., et al. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. Int J Biometeorol, 54(1), 75-84. |
Heat wave and health |
Offensive air mass” | Human health is affected by the interactions from a much larger suite of meteorological conditions that constitute an “offensive air mass” For Chicago, two “oppressive” air mass types, Dry Tropical (DT) and Moist Tropical Plus (MT+), have been primarily associated with increased mortality in the past. In particular, the MT+ air mass is characterized by hot and humid conditions with high overnight temperatures. | Hayhoe, K., Sheridan, S., Kalkstein, L., & Greene, S. (2010). Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65-73. | Heat wave and health |
Heat-related mortality | The derived algorithms relating heat-related mortality in Chicago to meteorological and seasonal factors,based on historical observed weather conditions and mortality rates, are as follows:If day is classified as DT or MT+,MORT=-26.74+4.62DIS+0.777AT,if day is classified as another air mass,MORT=-7.8+0.266AT,where MORT is the mortality in 100000 people,AT is the apparent temperature(C), and DIS is the day's position in a sequence of consecutive days characterized by DT or MT+ air masses.The latter suggests that the longer the offensive air mass persists, the deadlier it becomes. | Hayhoe, K., Sheridan, S., Kalkstein, L., & Greene, S. (2010). Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65-73. | Heat wave and health |
Southerly winds | The moderating effect of the lake was minimized by the southerly winds prevailing during the heat wave, which virtually eliminated the cooling effect of lake breezes. | Hayhoe, K., Sheridan, S., Kalkstein, L., & Greene, S. (2010). Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65-73. | Heat wave and health |
Ground level ozone |
A warmer climate generally means more ground level ozone (a component of smog), which can cause respiratory problems, especially for those who are young, old, or have asthma or allergies |
United States Global Change Research Program (2009). Regional Climate Impacts: Midwest. Washington: USGCRP. |
Heat wave and health |
Heatstroke | The most common cause of death and the most acute illness directly attributable to heat is heatstroke, a condition characterized by a body temperature of 105.0°F (40.6°C) or higher and altered mental status |
The Potential Impacts of Climate Variability and Change on Temperature-Related Morbidity and Mortality in the United States |
Heat wave and health |
Heat-mortality | a meta-analysis of recent mortality studies, finding a 2–5 % increase in all-cause mortality for 1 °C increase during heat exposures | E. P. Petkova & H. Morita & P. L. Kinney (2014) Health Impacts of Heat in a Changing Climate: How Can Emerging Science Inform Urban Adaptation Planning? Curr Epidemiol Rep (2014) 1:67–74 DOI 10.1007/s40471-014-0009-1 | Heat wave and health |
Heat-mortality | The US epidemiological studies show that a 10 °C increase in temperature on the same summer day increased cardiovascular mortality by 1.17 %, and there was an 8.3 % difference comparing the highest level of ozone to the lowest among the 95 cities in the National Morbidity and Mortality Study | Global climate change and public health | Heat wave and health |
Hot days above xx(30, 35,38,40,45) deg C | Number of days with Tmax above xx(30,35,38,40,45) deg C | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | Heat wave and health |
r10mm | Heavy Precipitation Days. Number of days with precipitation >=10mm | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | precipitation |
r20mm | Very Heavy Precipitation Days. Number of days with precipitation >=20mm | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | precipitation |
rx1day | Max 1-Day Precipitation. Highest precipitation amount in a 1-day period | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | precipitation |
rx5day | 5-day maximum precipitation accumulation | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | precipitation |
SDII | Simple daily intensity index[mm/day] | https://www.earthsystemcog.org/projects/downscaling-2013/VariablesIndices | precipitation |
Rkeqj |
Rkeqj=P*(EFjike*IMjike) Rkeqj is the risk index for each infrastructure element of type k in DA q.EFjike is the economic factor for each climate scenario, j, impact category, i, infrastructure type, k, and each infrastructure element, e IMjike is the impact multiplier. |
Elisabeth A. Bowering , Angela M. Peck & Slobodan P. Simonovic (2013): A flood risk assessment to municipal infrastructure due to changing climate part I: methodology, Urban Water Journal, DOI:10.1080/1573062X.2012.758293 | Flood risk |
Rjks |
Rjks =Eks* Skj Rjks risk score for the receptor j related to an impact k and a scenario s; Ek,s exposure score related to the impact k in scenario s, according to specific exposure functions; Sk,j susceptibility of the receptor j to the impact k. |
S. Pasini , S. Torresan , J. Rizzi , A. Zabeo , A. Critto , A. Marcomini, Climate change impact assessment in Veneto and Friuli Plain groundwater. Part II: A spatially resolved regional risk assessment,Science of the Total Environment 440 (2012) 219–235 |
Risk assessment |
Influence of the warmer and shorter winter. (wet snow) |
1. High density, wet snow does not drift as much as light snow so highways and roads might be less impaired by blizzards. 2. Structural loading of roofs and buildings is likely to increase from large snowfalls of heavy, wet snow. 3. A higher frequency of snowmelt during the winter from warmer average temperatures, coupled with an increased frequency of winter precipitation in the form of rain will likely further increase surface and basement flood risks 4. Rain falling on snow or on frozen ground will also have a higher runoff coefficient than rain falling on bare ground in warmer seasons, further complicating the assessment of winter flood risks. 5. Deicing salt applications might need to be increased during wet snowfalls, simply because of the dilution effects of denser and wetter snow. 6. An increase in snowstorm intensity, coupled with a greater frequency of heavy, wet snowfalls, will also likely lead to more frequent power blackouts and more extensive tree damage during the winter season. |
Jaffe, M., M.E. Woloszyn, 2013. Development of an Indicator Suite and Winter Adaptation Measures for the Chicago Climate Action Plan. In: 2011 Project Reports. D. Brown, D. Bidwell, and L. Briley, eds. Available from the Great Lakes Integrated Sciences and Assessments (GLISA) Center. | Winter adaptation |
Impacts of temperature on highway operations and infrastructure. |
1.Increases in very hot days and heat waves (higher high temperatures, increased duration of heat waves) • Increased thermal expansion of bridge joints and paved surfaces, causing possible degradation. 2.Decreases in very cold days • Regional changes in snow and ice removal costs and environmental impacts from salt and chemical use. 3.Later onset of seasonal freeze and earlier onset of seasonal thaw • Changes in seasonal weight restrictions. |
The federal highway administration’s climate change & extreme weather vulnerability assessment framework. December 2012 |
Transportation |
Impacts of precipitation on highway operations and infrastructure |
1.Increases in intense • Increases in weather-related delays and traffic disruptions. 2.Increases in drought conditions • Increased susceptibility to wildfires, causing road closures due to fire threat or reduced visibility. 3.Changes in seasonal precipitation and river flow patterns • Benefits for safety and reduced interruptions if frozen precipitation shifts to rainfall. |
The federal highway administration’s climate change & extreme weather vulnerability assessment framework. December 2012 | Transportation |
Impacts of storm intensity on highway operations and infrastructure |
1.Increases in storm intensity • More frequent and potentially more extensive emergency evacuations. |
The federal highway administration’s climate change & extreme weather vulnerability assessment framework. December 2012 | Transportation |
Impacts of sea level rise on operations and highway infrastructure |
1.Rising sea levels (leading to higher storm surge, increased salinity of rivers and estuaries, flooding) • Amplifies effect of storm surge, causing more frequent interruptions to coastal and low-lying roadway travel due to storm surges. |
The federal highway administration’s climate change & extreme weather vulnerability assessment framework. December 2012 | Transportation |