Editing IPCC:AR6/WGI/Chapter-12 (section)

=== 12.3.1 Heat and Cold ===

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==== 12.3.1.1 Mean Air Temperature ====

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Information about increasing mean annual and seasonal air temperature is relevant in the determination of suitable species range for terrestrial, freshwater and intertidal species ( [[#Thomas--2004|Thomas et al., 2004]] ; [[#Elith--2010|Elith et al., 2010]] ; [[#Hincapie--2013|Hincapie and Caicedo, 2013]] ; [[#Cooper--2014|Cooper, 2014]] ; [[#Krist--2014|Krist et al., 2014]] ; [[#Lindner--2014|Lindner et al., 2014]] ; [[#Saintilan--2014|Saintilan et al., 2014]] ; [[#Lenoir--2015|Lenoir and Svenning, 2015]] ; [[#Myers-Smith--2015|Myers-Smith et al., 2015]] ; [[#Urban--2015|Urban, 2015]] ; [[#Thorne--2017|Thorne et al., 2017]] ). Ocean ecosystems are affected by the ocean temperature CID (described in [[#12.3.6.1|Section 12.3.6.1]] ). Species redistribution and extinction studies also need information about climate velocity, a comparison of the pace of warming to geographical temperature gradients that indicates the rate at which a species would have to move to maintain its climatological temperature ( [[#Thomas--2004|Thomas et al., 2004]] ; [[#Loarie--2009|Loarie et al., 2009]] ; [[#Dobrowski--2013|Dobrowski et al., 2013]] ; [[#Burrows--2014|Burrows et al., 2014]] ; [[#Dobrowski--2016|Dobrowski and Parks, 2016]] ; [[#Sittaro--2017|Sittaro et al., 2017]] ) with some studies incorporating additional variables beyond temperature ( [[#Hamann--2015|Hamann et al., 2015]] ). Many freshwater ecosystems are strongly constrained by stream and lake temperatures ( [[#Scheurer--2009|Scheurer et al., 2009]] ; [[#Comte--2013|Comte and Grenouillet, 2013]] ; [[#Contador--2014|Contador et al., 2014]] ; [[#Knouft--2017|Knouft and Ficklin, 2017]] ). Warmer and more stratified lake temperatures are more conducive to cyanobacteria blooms with implications for ecosystem health and water resource quality ( [[#Whitehead--2009|Whitehead et al., 2009]] ; [[#Moss--2011|Moss et al., 2011]] ; [[#Jones--2014|Jones and Brett, 2014]] ; [[#Chapra--2017|Chapra et al., 2017]] ; [[#Shatwell--2019|Shatwell et al., 2019]] ). Consideration of nighttime and daytime temperature trends also elucidates different biophysical effects on vegetation ( [[#Peng--2013|Peng et al., 2013]] ). Changes in the seasonal timing caused by warming trends are critical to species ranges and ecosystem function ( [[#Pearce-Higgins--2015|Pearce-Higgins et al., 2015]] ; [[#Hughes--2017b|Hughes et al., 2017b]] ), and indices that characterize the onset of spring shed light on plant emergence and development ( [[#Ault--2015|Ault et al., 2015]] ).

Mean air temperature dictates many aspects of crop cultivation, livestock production, agroforestry and output from freshwater aquaculture and fisheries, as well as the potential for food contamination. Mean warming alters suitable cultivation zones for crop species ( [[#Bragança--2016|Bragança et al., 2016]] ; [[#Gendron%20St-Marseille--2019|Gendron St-Marseille et al., 2019]] ; [[#IPCC--2019c|IPCC, 2019c]] ) and tree species ( [[#Hanewinkel--2013|Hanewinkel et al., 2013]] ; [[#Fei--2017|Fei et al., 2017]] ). Crop and ecosystem service productivity often responds directly to mean temperatures, although this is dependent on farming systems ( [[#Bassu--2014|Bassu et al., 2014]] ; [[#Challinor--2014|Challinor et al., 2014]] ; [[#Lobell--2014|Lobell and Tebaldi, 2014]] ; [[#Rosenzweig--2014|Rosenzweig et al., 2014]] ; [[#Asseng--2015|Asseng et al., 2015]] ; [[#Li--2015|Li et al., 2015]] ; [[#Fleisher--2017|Fleisher et al., 2017]] ; [[#Zhao--2017|Zhao et al., 2017]] ; [[#Smith--2019|Smith and Fazil, 2019]] ). Many studies relate plant development (phenology), insect generation cycles and pest outbreaks to growing degree days, an aggregation of daily thermal units above a threshold (e.g., T <sub>mean</sub> &gt;5°C) that accelerates with warmer conditions ( [[#Hof--2016|Hof and Svahlin, 2016]] ; [[#Ruosteenoja--2016|Ruosteenoja et al., 2016]] ; [[#Tripathi--2016|Tripathi et al., 2016]] ). Many plants respond to changes in nighttime temperatures that affect respiration and transpiration rates (Narayanan et al., 2015; X. [[#Chen--2019|]] [[#Chen--2019|Chen et al., 2019]] ), and warming of the soil column is also relevant to determine plant sprouting ( [[#Grotjahn--2021|Grotjahn, 2021]] ). A number of indices have been developed to represent the length of the viable local growing season, including a count of days where T <sub>max</sub> &gt;5°C ( [[#Mueller--2015|Mueller et al., 2015]] ) or the period between a year’s first and last set of five consecutive days with a weighted T <sub>mean</sub> ≥10°C (G. [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|Li et al., 2018]] ). Warmer conditions and altered seasonality modify the range and metabolism of some pollinators, pests, diseases and weeds ( [[#Wolfe--2008|Wolfe et al., 2008]] ; [[#Bebber--2015|Bebber, 2015]] ; [[#Aljaryian--2016|Aljaryian and Kumar, 2016]] ; IPBES, 2016; [[#Ramesh--2017|Ramesh et al., 2017]] ; [[#Deutsch--2018|Deutsch et al., 2018]] ; [[#Nyangiwe--2018|Nyangiwe et al., 2018]] ) and may reduce the effectiveness of winter storage for farmers and caching species ( [[#Sutton--2016|Sutton et al., 2016]] ).

Warming raises accumulated seasonal heat indices used in livestock production, especially when humidity is high ( [[#Key--2014|Key et al., 2014]] ; [[#Lallo--2018|Lallo et al., 2018]] ), determines aquaculture suitability and is important for wild fish species migration ( [[#Tripathi--2016|Tripathi et al., 2016]] ; [[#Brander--2017|Brander et al., 2017]] ). Agricultural planners may also calculate how overall warming trends alter the accumulation of vernalization units or chilling hours for agricultural or horticultural crops (often accumulated temperature deficit below a given daily or hourly threshold; [[#Dennis--2009|Dennis and Peacock, 2009]] ; [[#Luedeling--2012|Luedeling, 2012]] ; [[#Tripathi--2016|Tripathi et al., 2016]] ; [[#Grotjahn--2021|Grotjahn, 2021]] ). Warming in the post-harvest is also important for the determination of spoilage and waste ( [[#Stathers--2013|Stathers et al., 2013]] ) as well as food-borne diseases ( [[#Kovats--2004|Kovats et al., 2004]] ; [[#Mbow--2019|Mbow et al., 2019]] ).

Warming affects road degradation rates ( [[#Chinowsky--2012|Chinowsky and Arndt, 2012]] ; [[#Espinet--2016|Espinet et al., 2016]] ) and warming rates inform designs for long-term energy efficiency of buildings ( [[#Kalvelage--2014|Kalvelage et al., 2014]] ). Mean temperature drives seasonal energy demand, often expressed using winter heating degree days (the accumulated deficit of daily temperatures below a ‘comfortable’ indoor temperature, e.g., 15.5°C) and summer cooling degree days (the accumulated excess of temperature above a ‘comfortable’ level, e.g., 18°C; [[#Spinoni--2015|Spinoni et al., 2015]] ; [[#Arnell--2019|Arnell et al., 2019]] ). Energy resources may also need information on warming trends to determine suitable zones and overall productivity for biofuels and solar panels, the efficiency of which decreases with higher temperatures ( [[#Schaeffer--2012|Schaeffer et al., 2012]] ; [[#Wild--2015|Wild et al., 2015]] ; [[#Solaun--2019|Solaun and Cerdá, 2019]] ).

Health impacts and risk studies compare seasonal temperature conditions to limiting thresholds to understand range shifts and incubation rates for pathogens, disease vectors and zoonotic hosts (e.g., mosquitoes, ticks; [[#Caminade--2012|Caminade et al., 2012]] , 2014; [[#Eisen--2013|Eisen and Moore, 2013]] ; [[#Lima--2016|Lima et al., 2016]] ; [[#Ogden--2017|Ogden, 2017]] ; [[#Monaghan--2018|Monaghan et al., 2018]] ) and warming of surface ocean and lake waters conducive to bacterial outbreaks ( [[#Baker-Austin--2013|Baker-Austin et al., 2013]] ; [[#Jacobs--2015|Jacobs et al., 2015]] ; [[#Vezzulli--2015|Vezzulli et al., 2015]] ). Warmer conditions can also affect tourism ( [[#Kovács--2017|Kovács et al., 2017]] ) and impact human health by lengthening the allergy season and increasing pollen concentration ( [[#Hamaoui-Laguel--2015|Hamaoui-Laguel et al., 2015]] ; [[#Kinney--2015a|Kinney et al., 2015a]] ; [[#Lake--2017|Lake et al., 2017]] ; [[#Upperman--2017|Upperman et al., 2017]] ; [[#Sapkota--2019|Sapkota et al., 2019]] ; [[#Ziska--2019|Ziska et al., 2019]] ).

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==== 12.3.1.2 Extreme Heat ====

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Impacts and risk assessments utilize a large variety of indices and approaches tailored to evaluate heat impacts on human health ( [[#Sanderson--2017|Sanderson et al., 2017]] ; [[#Gao--2018|]] [[#Gao--2018|C. Gao et al., 2018]] ; [[#McGregor--2018|McGregor and Vanos, 2018]] ; [[#Staiger--2019|Staiger et al., 2019]] ; J. [[#Zhu--2019|]] [[#Zhu--2019|Zhu et al., 2019]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ). A mixture of simple and complex heat stress indices often combine extreme temperatures and high humidity to capture human health challenges ( [[#Aström--2013|Aström et al., 2013]] ; [[#Chow--2016|Chow et al., 2016]] ; [[#Dahl--2017a|Dahl et al., 2017a]] ; [[#Im--2017|Im et al., 2017]] ; [[#Coffel--2018|Coffel et al., 2018]] ; J. [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|Li et al., 2018]] ; [[#Vanos--2020|Vanos et al., 2020]] ). Different optimum temperatures and extreme heat thresholds based on local distributions are needed to reflect acclimation of different locations and populations ( [[#Hajat--2014|Hajat et al., 2014]] ; [[#WHO--2014|WHO, 2014]] ; [[#Kinney--2015b|Kinney et al., 2015b]] ; [[#Russo--2015|Russo et al., 2015]] ; [[#Petitti--2016|Petitti et al., 2016]] ; [[#Dosio--2017|Dosio, 2017]] ; [[#Cheng--2018|Cheng et al., 2018]] ; [[#Lay--2018|Lay et al., 2018]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ). Hot and humid heat episodes can be deadly ( [[#Mora--2017|Mora et al., 2017]] ), are associated with elevated hospital intake ( [[#Goldie--2017|Goldie et al., 2017]] ) and lower safety and productivity of outdoor labourers ( [[#Dunne--2013|Dunne et al., 2013]] ; [[#Graff%20Zivin--2014|Graff Zivin and Neidell, 2014]] ; [[#Kjellstrom--2016|Kjellstrom et al., 2016]] ; [[#Pal--2016|Pal and Eltahir, 2016]] ; Y. [[#Zhao--2016|]] [[#Zhao--2016|Zhao et al., 2016]] ; [[#Mora--2017|Mora et al., 2017]] ; [[#Watts--2018|Watts et al., 2018]] ; [[#Orlov--2019|Orlov et al., 2019]] ). Elevated nighttime temperatures prevent the human body from experiencing relief from heat stress ( [[#Zhang--2012|Zhang et al., 2012]] ) and can be tracked over extended periods of sequential day and night heat extremes ( [[#Murage--2017|Murage et al., 2017]] ; [[#Mukherjee--2018|Mukherjee and Mishra, 2018]] ). Extreme heat also exacerbates asthma, respiratory difficulties and response to airborne allergens such as hay fever ( [[#Upperman--2017|Upperman et al., 2017]] ). Extreme heat affects outdoor exercise such as the use of bike-share facilities ( [[#Heaney--2019|Heaney et al., 2019]] ; [[#Vanos--2020|Vanos et al., 2020]] ). Large-scale recreational and sporting events such as marathons and tennis tournaments monitor heat extremes when determining the viability of host cities ( [[#Smith--2016|Smith et al., 2016]] , 2018).

Short-term exposure of crops to temperatures beyond a critical temperature threshold can lead to lower yields and above a limiting temperature threshold, crops may fail altogether ( [[#Schlenker--2009|Schlenker and Roberts, 2009]] ; [[#Lobell--2012|Lobell et al., 2012]] , 2013; [[#Gourdji--2013|Gourdji et al., 2013]] ; [[#Deryng--2014|Deryng et al., 2014]] ; [[#Schauberger--2017|Schauberger et al., 2017]] ; [[#Tesfaye--2017|Tesfaye et al., 2017]] ; [[#Vogel--2019|Vogel et al., 2019]] ). The exact level of these thresholds depends on species, cultivar and farm management ( [[#Hatfield--2015|Hatfield and Prueger, 2015]] ; [[#Hatfield--2015|Hatfield et al., 2015]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Grotjahn--2021|Grotjahn, 2021]] ). The timing of heatwaves is particularly important, as extreme heat is more damaging during critical phenological stages ( [[#Teixeira--2013|Teixeira et al., 2013]] ; [[#Eyshi%20Rezaei--2015|Eyshi Rezaei et al., 2015]] ; [[#Fontana--2015|Fontana et al., 2015]] ; [[#Wang--2017|]] [[#Wang--2017|]] [[#Wang--2017|B. Wang et al., 2017]] ; [[#Mäkinen--2018|Mäkinen et al., 2018]] ). Extreme canopy temperatures, rather than 2 m air temperatures, may be a more robust biophysical indicator of heat impacts on crop production ( [[#Siebert--2017|Siebert et al., 2017]] ). Heat stress indices based upon temperature and humidity determine livestock productivity as well as conception and mortality rates ( [[#Key--2014|Key et al., 2014]] ; [[#Dash--2016|Dash et al., 2016]] ; [[#Pragna--2016|Pragna et al., 2016]] ; [[#Rojas-Downing--2017|Rojas-Downing et al., 2017]] ).

Heat extremes factor in mortality, morbidity and the range of some thermally sensitive ecosystem species ( [[#Smith--2015|Smith and Nagy, 2015]] ; [[#Ratnayake--2019|Ratnayake et al., 2019]] ; [[#Thomsen--2019|Thomsen et al., 2019]] ). Combined heat and drought stress can reduce forest and grassland primary productivity ( [[#Ciais--2005|Ciais et al., 2005]] ; [[#De%20Boeck--2018|De Boeck et al., 2018]] ) and even cause tree mortality at higher extremes ( [[#Teskey--2015|Teskey et al., 2015]] ).

Extreme heat events raise temperatures in buildings and cities already warmed by the urban heat island effect ( [[#Gaffin--2012|Gaffin et al., 2012]] ; [[#Oleson--2018|Oleson et al., 2018]] ; [[#Zhao--2018|Zhao et al., 2018]] ; [[#Mauree--2019|Mauree et al., 2019]] ; Box 10.3) and can induce disruptions in critical infrastructure networks ( [[#Chapman--2013|Chapman et al., 2013]] ). Heat affects transportation infrastructure by warping roads and airport runways ( [[#Chinowsky--2012|Chinowsky and Arndt, 2012]] ) or buckling railways ( [[#Dobney--2010|Dobney et al., 2010]] ; [[#Dépoues--2017|Dépoues, 2017]] ; [[#Chinowsky--2019|Chinowsky et al., 2019]] ), and high temperatures reduce air density leading to aircraft take-off weight restrictions ( [[#Coffel--2017|Coffel et al., 2017]] ; [[#Palko--2017|Palko, 2017]] ; T. [[#Zhou--2018|]] [[#Zhou--2018|Zhou et al., 2018]] ). Heat extremes increase peak cooling demand and challenge transmission and transformer capacity ( [[#Sathaye--2013|Sathaye et al., 2013]] ; [[#Russo--2016|Russo et al., 2016]] ; [[#Craig--2018|Craig et al., 2018]] ; X. [[#Gao--2018|]] [[#Gao--2018|Gao et al., 2018]] ) and may cause transmission lines to sag or fail ( [[#Gupta--2012|Gupta et al., 2012]] ). Thermal and nuclear electricity plants may be challenged when using warmer river waters for cooling or when mixing waste waters back into waterways without causing ecosystem impacts ( [[#Kopytko--2011|Kopytko and Perkins, 2011]] ; [[#van%20Vliet--2016|van Vliet et al., 2016]] ; [[#Tobin--2018|Tobin et al., 2018]] ). Extreme temperature can also reduce photovoltaic panel efficiency ( [[#Jerez--2015|Jerez et al., 2015]] ).

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==== 12.3.1.3 Cold Spells ====

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The magnitude and timing (relative to developmental stages) of cold extremes (such as the typical coldest day of the year) set limits in the range of species habitat for ecosystems as well as for agricultural and forest pests ( [[#Osland--2013|Osland et al., 2013]] ; [[#Cavanaugh--2014|Cavanaugh et al., 2014]] ; [[#Parker--2016|Parker and Abatzoglou, 2016]] ; [[#Brunner--2018|Brunner et al., 2018]] ; [[#Unterberger--2018|Unterberger et al., 2018]] ). Cold air outbreaks can lead to chilling injuries for crops (even above 0°C) and may kill outdoor livestock (particularly young animals; [[#Mader--2010|Mader et al., 2010]] ; [[#Liu--2013|Liu et al., 2013]] ; [[#Grotjahn--2021|Grotjahn, 2021]] ), but are often necessary for crop chill requirements ( [[#Dennis--2009|Dennis and Peacock, 2009]] ).

Increases in human mortality can occur on exceptionally cold days (e.g., &lt;1st percentile of temperatures in winter) although thresholds and human-perceived temperatures linked to wind speed (i.e., ‘wind chill’) vary geographically due to acclimatization ( [[#Li--2013|Li et al., 2013]] ; [[#Gao--2015|Gao et al., 2015]] ; J. [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|Li et al., 2018]] ; J. [[#Zhu--2019|]] [[#Zhu--2019|Zhu et al., 2019]] ). The timing of ‘unseasonal’ cold spells also affect human health ( [[#Kinney--2015b|Kinney et al., 2015b]] ). Extreme cold can increase heat and electricity demand ( [[#Stuivenvolt-Allen--2019|Stuivenvolt-Allen and Wang, 2019]] ), cause water pipes to burst, and mechanically alter roads, railroads and buildings ( [[#Underwood--2017|Underwood et al., 2017]] ).

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==== 12.3.1.4 Frost ====

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Frost (T <sub>min</sub> &lt;0°C) is a natural and fundamental aspect of many ecosystems, with more extreme conditions defined as ice (or icing) days (T <sub>max</sub> &lt;0°C) ( [[#Vincent--2018|L.A. Vincent et al., 2018]] ). Agricultural systems planning (e.g., planting calendars, seed selection or the opportunity to double-crop) requires information about the start and end of the frost-free season ( [[#Wypych--2017|Wypych et al., 2017]] ; [[#Wolfe--2018|Wolfe et al., 2018]] ). Crops and wild plants can be directly damaged by frost, but hard or killing frosts (at a threshold several degrees below freezing) can kill crops or lower harvest quality depending on duration (which relates to soil temperature penetration) and plant developmental stage ( [[#Crimp--2016a|Crimp et al., 2016a]] ; [[#Cradock-Henry--2017|Cradock-Henry, 2017]] ; G. [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|]] [[#Li--2018|Li et al., 2018]] ; [[#Mäkinen--2018|Mäkinen et al., 2018]] ; [[#Grotjahn--2021|Grotjahn, 2021]] ). Earlier disappearance of snow cover reduces natural insulation that protects plants and burrowing animals from hard frost damages ( [[#Trnka--2014|Trnka et al., 2014]] ; [[#Mäkinen--2018|Mäkinen et al., 2018]] ). In some cases an early season warm spell may reduce plant hardiness or induce fruit tree flowering that exposes plants to devastating subsequent frost impacts ( [[#Hufkens--2012|Hufkens et al., 2012]] ; [[#Hatfield--2014|Hatfield et al., 2014]] ; [[#Tripathi--2016|Tripathi et al., 2016]] ; [[#Brunner--2018|Brunner et al., 2018]] ; [[#DeGaetano--2018|DeGaetano, 2018]] ; [[#Unterberger--2018|Unterberger et al., 2018]] ; [[#Wolfe--2018|Wolfe et al., 2018]] ). Shifts in the seasonality of frozen soils also affect groundwater recharge and surface streamflow for water resource applications, particularly when peak precipitation is shifted to a season that no longer has frozen soils ( [[#Jyrkama--2007|Jyrkama and Sykes, 2007]] ).

Regional information about the spring and autumn seasonal periods in which freeze-thaw cycles are common (such as the dates of first spring thaw and last spring frost, or the number of days where T <sub>max</sub> &gt;0°C and T <sub>min</sub> &lt;0°C) are particularly useful in estimating the rate of potential road and building damage or determining seasonal truck weight restrictions ( [[#Kvande--2009|Kvande and Lisø, 2009]] ; [[#Chinowsky--2012|Chinowsky and Arndt, 2012]] ; [[#Palko--2017|Palko, 2017]] ; [[#Daniel--2018|Daniel et al., 2018]] ). The altitude of the freezing level also identifies portions of mountain slopes where freeze/thaw transitions or changes in snowpack condition can influence landslide and snow avalanche hazards ( [[#Coe--2018|Coe et al., 2018]] ). The geographical distribution of frost is also a determining factor in the range of vectors for human diseases such as malaria (X. [[#Zhao--2016|]] [[#Zhao--2016|Zhao et al., 2016]] ; [[#Smith--2020|Smith et al., 2020]] ).

Figure 12.3 illustrates how successive heat and cold hazards can potentially affect important natural and human systems, with climatic pressures reaching new sectoral assets or becoming increasingly severe as conditions become more extreme. While the precise value of any CID threshold may depend strongly on local environmental and system characteristics, there are common patterns and interdependencies in the types of thresholds encountered. Changes in the regional profile of CIDs can thus substantially alter threshold exceedance likelihoods.

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[[File:1fbbe02ba84f8df0d3124b2557ff7990 IPCC_AR6_WGI_Figure_12_3.png]]

'''Figure 12.3''' '''|''' '''Conceptual illustration of representative climatic impact-driver thresholds showing how graduating thresholds affect successive sectoral assets and lead to potentially more acute hazards as conditions become more extreme (exact values are not shown as these must be tailored to reflect diverse vulnerabilities of regional assets).''' Representative threshold definitions (T = instantaneous temperature; T '''''' = mean temperature): '''Cities and Infrastructures:''' T <sub>trans</sub> = temperature at which energy transmission lines efficiency reduced; T <sub>aircraft</sub> = temperature at which aircraft become weight-restricted for takeoff; T <sub>hotroads</sub> = temperature above which roads begin to warp; T <sub>stream</sub> = temperature at which streams are not capable of adequately cooling thermal plants; CDD <sub>min</sub> = minimum temperature for calculating cooling degree days; HDD <sub>max</sub> = maximum temperature for calculating heating degree days; T <sub>ice</sub> = temperature at which ice threatens transportation; T '''''' <sub>permafrost</sub> = mean seasonal temperature above which permafrost thaws at critical depths; T <sub>coldroads</sub> = temperature below which road asphalt performance suffers. '''Health:''' T <sub>deadly</sub> = temperature above which prolonged exposure may be deadly (often combined with humidity for heat indices); T <sub>severe</sub> = temperature above which prolonged exposure may cause elevated morbidity; T '''''' <sub>blooms</sub> = mean temperature for harmful algal or cyanobacteria blooms; T <sub>danger</sub> = level of dangerous cold temperatures (often combined with wind for chill indices); T <sub>overwinter</sub> = temperature below which disease vector species cannot survive winter. '''Ecosystems''' (CID indices for air and ocean temperature): T <sub>hotlim</sub> and T <sub>coldlim</sub> = limiting hot and cold temperatures for a given species range; T <sub>frost</sub> = frost threshold; T '''''' <sub>max</sub> and T '''''' <sub>min</sub> = maximum and minimum suitable annual mean temperatures for a given species; T <sub>crit</sub> = critical temperature above which a given species is stressed. '''Agriculture:''' T <sub>hotlim</sub> = temperature above which a crop or livestock species dies; T <sub>hotpest</sub> = maximum (or ‘lethal’) temperature above which an agricultural pest/disease/weed cannot survive; T <sub>crit</sub> = temperature at which productivity for a given crop is depressed; T '''''' <sub>opt</sub> = optimal mean temperature for a given plant’s productivity; GDD <sub>min</sub> = threshold temperature for growing degree days determining plant development; T <sub>chill</sub> = temperature below which chilling units are accumulated; T <sub>frost</sub> = temperature below which frost occurs; T <sub>hfrost</sub> = temperature below which a hard frost threatens crops or livestock; T <sub>coldpest</sub> = minimum winter temperature below which a given agricultural pest cannot survive; T <sub>coldlim</sub> = minimum temperature below which a given crop cannot survive.

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