Aircraft Takeoff Performance in a Changing Climate For

atmosphere

Article Aircraft Takeoﬀ Performance in a Changing Climate for Canadian Airports

Yijie Zhao * and Laxmi Sushama Department of Civil Engineering and Applied Mechanics and Trottier Institute for Sustainability in Engineering and Design, McGill University, Montreal, QC H3A 0C3, Canada; [email protected] * Correspondence: [email protected]

Received: 15 March 2020; Accepted: 15 April 2020; Published: 21 April 2020

Abstract: Temperature and wind are major meteorological factors that affect the takeoff and landing performance of aircraft. Warmer temperatures and the associated decrease in air density in future climate, and changes to crosswind and tailwind, can potentially impact aircraft performance. This study evaluates projected changes to aircraft takeoff performance, in terms of weight restriction days and strong tailwind and crosswind occurrences, for 13 major airports across Canada, for three categories of aircraft used for long-, medium- and short-haul flights. To this end, two five-member ensembles of transient climate change simulations performed with a regional climate model, for Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, respectively, are analyzed. Results suggest that the projected increases in weight restriction days associated with the increases in daily maximum temperatures vary with aircraft category and airfield location, with larger increases noted for airfields in the south central regions of Canada. Although avoiding takeoff during the warmest period of the day could be a potential solution, analysis focused on the warmest and coolest periods of the day suggests more weight restriction hours even during the coolest period of the day, for these airfields. Though RCP8.5 in general suggests larger changes to weight restriction hours compared to RCP4.5, the differences between the two scenarios are more prominent for the coolest part of the day, as projected changes to daily minimum temperatures occur at a much faster rate for RCP8.5 compared to RCP4.5, and also due to the higher increases in daily minimum temperatures compared to maximum temperatures. Both increases and decreases to crosswind and tailwind are projected, which suggest the need for detailed case studies, especially for those airfields that suggest increases. This study provides useful preliminary insights related to aircraft performance in a warmer climate, which will be beneficial to the aviation sector in developing additional analysis and to support climate change adaptation-related decision-making.

Keywords: climate change; aviation; aircraft performance; maximum daily temperature; weight restriction day; crosswind; tailwind

1. Introduction Projected changes to the mean and/or variability of climatic variables and extreme events in future climate [1] can impact the aviation sector, including aircraft ground and air operations. For instance, more than 30% of reported aviation accidents in North America during the 1990–2006 period were weather related, either directly or indirectly [2]. Besides, according to the Bureau of Transportation Statistics [3], approximately 40% of the total delay minutes are weather related. Aircraft takeoff performance, which primarily refers to the ability of an aircraft to take off in a short distance, is mainly dependent on air density and wind characteristics [4]. Higher air temperatures in the future climate and the associated decrease in air density can reduce the lift generated during takeoff [4]. Besides, it should be noted that air density at constant temperature is lower for high altitude airfields due

Atmosphere 2020, 11, 418; doi:10.3390/atmos11040418 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 418 2 of 21 to lower atmospheric pressure. Lower air density refers to poor aircraft takeoff performance and suggests the need for greater takeoff speed and longer accelerating/takeoff distance. Reducing the gross weight by removing fuel or passengers and cargo is usually used to solve this problem. Another factor that contributes to aircraft takeoff performance is wind, with high crosswinds leading to significant decreases in the controllability of aircraft during takeoff [4]. Furthermore, headwind and tailwind along the runway also play an important role during takeoff. For example, a headwind that is 10% of the takeoff speed reduces the takeoff distance by approximately 10%, while a same speed tailwind increases the takeoff distance by around 21% [4]. Many accidents, such as overrun, have happened for tailwind greater than 10 knots [5]. Given the above, changes to wind characteristics in the future might influence many aspects of runway requirements. So far, few studies have investigated the effects of climate change on aircraft performance. Coffel and Horton [6] studied the impact of rising daily maximum temperature for the May to September period for four major airports in the United States, which suggests more days with weight restriction for aircraft used for short- to medium-haul flights, such as Boeing 737–800. Coffel et al. [7] extended their study to 19 major airports around the world and concluded that 10–30% of flights departing at the time of daily maximum temperature may require some weight restriction below their maximum takeoff weights. Zhou et al. [8] investigated the takeoff distance for Boeing 737–800 for 30 major international airports, and indicated that the average takeoff distance in summer will increase by 1.6% to 11% by the end of the century (2071–2100) for the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Zhou et al. [9] studied weight restriction days for airfields in China for the case of Boeing 737–800 and reported that weight restriction days will increase significantly at three airports located in the southern, central, and high-elevation regions of China. Gratton et al. [10] analyzed the historic changes in temperature and wind conditions and their impacts on aircraft performance at 10 Greek airports. They reported a clear impact of rising temperatures in terms of a steady increase in takeoff distance at airports with longer runways and significant weight restrictions at airports with shorter runways. Climate change impacts on clear-air turbulence and therefore on aviation were addressed in a number of recent studies [11–15]. Williams and Joshi [14], using climate model simulations, were the first to suggest significant increases in clear-air turbulence strength and frequency for the transatlantic flight corridor for doubled carbon dioxide concentration in the atmosphere. This has important implications, such as longer journey times and, hence, increases in fuel consumption and emissions. According to Canada’s Changing Climate Report [16], the average surface temperature for Canada has increased by 1.7 ◦C since 1948, approximately double the rate as that of the world as a whole. The annual and the seasonal mean daily maximum temperature has increased since the beginning of this century across Canada [17]. Furthermore, analysis of projected changes to temperature extremes for the 2040–2069 period for the SRES (Special Report on Emissions Scenarios) A2 scenario by Jeong et al. [18], using Regional Climate Model (RCM) ensembles, suggests increases in extreme temperature events, particularly for southern Canada. Large spatial variability in projected changes to annual maximum three-hourly wind speed, with increases for northern regions of Canada and decreases elsewhere, was reported by Jeong and Sushama [19]. Given the above changes, the main purpose of this study is to investigate the impact of climate change, more specifically projected changes to daily maximum temperature and wind characteristics, on aircraft takeoff performance at 13 major airports across Canada, using outputs from an RCM for different emission scenarios. The rest of the paper is organized as follows. Section2 describes the RCM, simulations and observed dataset used in this study. Section3 discusses the methodology and relation between aircraft takeoff performance and climatic variables and associated thresholds. Section4 presents the validation of the RCM-simulated aviation-related climatic variables, their projected changes and implications for aircraft takeoff in the future climate. Summary and conclusions of the study are provided in Section5. Atmosphere 2020, 11, 418 3 of 21

2. Model, Simulations and Observation Data Atmosphere 2020, 11, x FOR PEER REVIEW 3 of 21 2.1. Model and Simulations 2.1. Model and Simulations The RCM used in this study is a limited area version of the Global Environmental Multiscale (GEM)The model RCM [used20], whichin this is study used is for a numericallimited area weather version prediction of the Global by EnvironmentEnvironmental and Multiscale Climate (GEM)Change model Canada [20], (ECCC). which GEM is used employs for numerical semi-Lagrangian weather transport prediction and aby (quasi) Environment fully implicit and steppingClimate Changescheme. Canada In its fully (ECCC). elastic GEM non-hydrostatic employs semi-Lagrang formulationian [21], transport GEM uses and a vertical a (quasi) coordinate fully implicit based steppingon hydrostatic scheme. pressure In its fully [22]. elas Thetic convection non-hydrostatic schemes formulation of Kain and [21] Fritsch, GEM uses [23] anda vertical Bélair coordinate et al. [24], basedfor deep on andhydrostatic shallow pressure convection, [22]. respectively, The convection are sc used.hemes The of resolvableKain and Fritsch large-scale [23] and precipitation Bélair et al. is [24],calculated for deep following and shallow Sundqvist convection, et al. [ 25respectively,]. Radiation are is used. parameterized The resolvable by the large-scale correlated-K precipitation solar and isterrestrial calculated radiation following of LiSundqvist and Barker et al. [26 [25].]. The Radiat planetaryion is boundaryparameterized layer by follows the correlated-K Benoit et al. solar [27] and terrestrialDelage [28 radiation], with some of Li modifications and Barker [26]. as The described planetary in Zadra boundary et al. layer [29]. follow The Canadians Benoit et land-surface al. [27] and Delagescheme [28], (CLASS) with version some modificati 3.5 [30], allowingons as described a flexible in number Zadra of et soil al. layers[29]. The and Canadian thicknesses, land-surface is used to schemerepresent (CLASS) land processes version and 3.5 lakes[30], allowing are represented a flexible by thenumber one-dimensional of soil layers Flake and thicknesses, model [31]. Ais detailedused to representdescription land of GEM processes can be and found lakes in Diroare represen and Sushamated by [32 the]. one-dimensional Flake model [31]. A detailedThe description experimental of GEM domain can of be the found model in Diro covers and the Sushama Pan-Arctic [32]. region (i.e., region north of the forty-ninthThe experimental parallel), at domain 0.5 horizontal of the model resolution covers (Figurethe Pan-Arctic1a). It consists region (i.e., of 172 region172 north grid of cells the ◦ × forty-ninthand has 76 parallel), levels in theat 0.5° vertical. horizontal The analysisresolution presented (Figure in1a). this It consists study covers of 172 only × 172 Canada grid cells though and (Figurehas 76 levels1a). The in the atmospheric vertical. The lateral analysis boundary present conditionsed in this study are obtained covers only from Canada the European though Centre(Figure 1a).for Medium-RangeThe atmospheric Weather lateral Forecastboundary (ECMWF) conditions Re-Analysis are obtained (ERA)-Interim from the European data [33], Centre and from for Medium-Rangetwo five-member Weather ensembles Forecast of second-generation (ECMWF) Re-Analy Canadiansis (ERA)-Interim Earth System data Model[33], and (CanESM2) from two five- [34], membercorresponding ensembles to RCP 4.5of andsecond-generation 8.5 scenarios. The Canadian CanESM2 drivenEarth GEMSystem simulations Model span(CanESM2) the 1981–2100 [34], period,corresponding while the to RCP ERA-Interim-driven 4.5 and 8.5 scenarios. GEM The simulation CanESM2 covers driven the GEM current simulations 1981–2010 span period the and1981– is 2100used period, to validate while the the model. ERA-Interim-driven The above simulations GEM simulation will be covers referenced the current to as 1981–2010 GEM-CanESM2 period and isGEM-ERAInterim used to validate inthe the model. remainder The above of the simula paper.tions It must will be be noted referenced that the to 1981–2005as GEM-CanESM2 period of and the GEM-ERAInterimGEM-CanESM2 simulations in the remainder for RCP of 4.5 the and paper. 8.5 scenarios It must arebe noted exactly that the the same. 1981–2005 period of the GEM-CanESM2 simulations for RCP 4.5 and 8.5 scenarios are exactly the same. (a)

Figure 1. Cont.

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Figure 1. (a) Model experimental domain consisting of 172 172 grid points; every fifth grid point Figure 1. (a) Model experimental domain consisting of 172 ×× 172 grid points; every fifth grid point is is shown. The region of analysis (Canada) considered in this study has topography shown in color. shown. The region of analysis (Canada) considered in this study has topography shown in color. (b) (b) Runways and their orientations for the 13 airfields considered in this study. The longest runway at Runways and their orientations for the 13 airfields considered in this study. The longest runway at each airport is shown shaded. The colors indicate the number of runways (see legend). each airport is shown shaded. The colors indicate the number of runways (see legend). 2.2. Observation Data 2.2. Observation Data Gridded datasets and point observations are used for model validation purposes. The point observationsGridded are datasets obtained and from point Environment observations Canada are us [35ed]. for For model validating validation GEM-ERAInterim purposes. The simulated point temperatureobservations and are wind obtained fields, ERA-Interimfrom Environment reanalysis Canada [33] at 0.75[35].◦ andFor six-hourlyvalidating resolution, GEM-ERAInterim as well as thesimulated newly releasedtemperature global and reanalysis wind ERA5fields, atERA-Interim 0.25◦ [36] and reanalysis one-hourly [33] resolution at 0.75° for and the 1981–2010six-hourly period,resolution, are used.as well Besides, as the hourly newly wind released roses fromglobal point reanalysis observations ERA5 at theat 0.25° studied [36] airfields, and one-hourly expressed inresolution 10 s of degrees, for the and1981–2010 ERA5 are period, used toare validate used. Besides, the wind hourly speed wind and directions roses from from point model observations simulations at (three-hourly)the studied airfields, for the expressed 1981–2010 in period. 10 s of degrees, It should and be ERA5 noted are that used wind to validate point observations the wind speed are very and sensitivedirections to from changes model in anemometersimulations height(three-hourly) and location, for the and 1981–2010 changes inpe theseriod. factorsIt should can be lead noted to large that changeswind point in the observations wind rose [ 37are]. Thisvery cansensitive lead to to some changes differences in anemometer between observations height and andlocation, reanalysis and orchanges model in simulations, these factors in addition can lead to to the large differences changes that in may the arisewind when rosecomparing [37]. This pointcan lead observations to some withdifferences grid cell between values. observations and reanalysis or model simulations, in addition to the differences that may arise when comparing point observations with grid cell values. 3. Methodology 3. Methodology 3.1. Definitions, Thresholds and Airfields 3.1. Definitions,To assess theThres impactholds and of climate Airfields change on aircraft takeoff performance, this study focuses on weightTo restriction assess the days impact and of strong climate tailwind change and on crosswind aircraft takeoff occurrences, performance, for 13 airports this study situated focuses across on Canadaweight restriction (Figure1b) days in di andfferent strong climatic tailwind regions: and crossw Erik Nielsenind occurrences, Whitehorse for International 13 airports situated Airport (YXY),across VancouverCanada (Figure International 1b) in Airportdifferent (YVR), climatic Calgary regions: International Erik Nielsen Airport Whitehorse (YYC), Yellowknife International Airport Airport (YZF), John(YXY), G. Vancouver Diefenbaker International International Airport (YXE),(YVR), Winnipeg Calgary JamesInternational Armstrong Airp Richardsonort (YYC), InternationalYellowknife AirportAirport (YWG),(YZF), IqaluitJohn G. Airport Diefenbaker (YFB), LesterInternational B. Pearson Airport International (YXE), Winnipeg Airport (YYZ), James Pierre Armstrong Elliott TrudeauRichardson International International Airport Airport (YUL), (YWG), Fredericton Iqaluit International Airport (YFB), Airport Lester (YFC), B. CharlottetownPearson International Airport (YYG),Airport Robert (YYZ), L. Pierre Stanfield Elliott International Trudeau Internationa Airport (YHZ)l Airport and St. (YUL), John’s Fredericton International International Airport (YYT). Airport The runway(YFC), Charlottetown lengths and altitudes Airport for (YYG), these Robert airfields L. are Stanfield shown International in Table1. Runway Airport details (YHZ) (i.e., and orientation St. John’s International Airport (YYT). The runway lengths and altitudes for these airfields are shown in Table

Atmosphere 2020, 11, 418 5 of 21 and the number of runways) are given in Figure1 for the same airfields. These airfields include the top three busiest Canadian airports (YYZ, YVR, and YUL) that have intercontinental flights, and an additional eight international airports with flights mostly connecting North and South Americas and two smaller airports with just domestic flights. The types of aircraft used for the above mentioned long-, medium- and short-haul flights will be referred to as category 1, 2 and 3, respectively, with aircraft’s maximum takeoff weight (MTOW) > 90,000 Kg for category 1, 18,000 Kg < MTOW < 90,000 Kg for category 2 and MTOW < 18,000 Kg for category 3. Table2 shows the annual itinerant movements for the three aircraft categories as well as the fraction of total flights that use these 3 categories of aircraft at the studied airfields.

Table 1. Runway characteristics for the 13 Canadian airports considered in this study, along with the International Air Transport Association (IATA) code. Data obtained from Nav Canada airports chart. Primary runway length are for the longest runway at the airport; crosswind runways are also provided; and they are used during unfavorable conditions of the primary runway.

IATA Code Location Elevation (ft) Longest Runway (ft) Crosswind Runway (ft) YXY Whitehorse 2317 9500 1798 YVR Vancouver 13 11,500 7300 YYC Calgary 3606 14,000 8000 YZF Yellowknife 675 7500 5000 YXE Saskatoon 1654 8300 6200 YWG Winnipeg 783 11,000 8700 YFB Iqaluit 110 8605 - YYZ Toronto 569 11,050 10,775 YUL Montréal 118 11,000 7000 YFC Fredericton 67 8005 6000 YYG Charlottetown 159 7000 5000 YHZ Halifax 447 10,500 7700 YYT St. John’s 46 8502 5028

Table 2. Average annual itinerant movements (i.e., takeoﬀ and landing) for the 2014–2018 period for three categories of aircrafts from Statistics Canada [38] (from busiest to least busy). Itinerant movements, expressed as percentage of total movements, are also included. Data for Iqaluit Airport and Charlottetown Airport was not available.

Maximum Takeoﬀ Weight IATA 18,000 kg and under 18,001 to 90,000 kg 90,001 kg and over Movements Percentage Movements Percentage Movements Percentage YYZ 59,521 13% 334,764 74% 61,047 13% YVR 107,623 33% 181,317 56% 35,263 11% YUL 42,303 19% 162,062 71% 22,967 10% YYC 54,523 23% 174,879 72% 11,975 5% YWG 47,535 43% 56,711 51% 6297 6% YHZ 24,839 32% 50,277 64% 3707 5% YYT 19,756 46% 22,447 52% 934 2% YXE 37,626 59% 25,171 40% 607 1% YFC 51,361 90% 5780 10% 22 0% YZF 24,460 55% 19,704 45% 14 0% YXY 14,466 73% 5251 27% 41 0%

In this study, a weight restriction day is defined as a day with daily maximum temperature higher than a pre-defined temperature threshold (i.e., the temperature at which a given category of aircraft can take off with MTOW for a given location and current runway lengths). We only investigate the case of the longest runway at each airfield in this study. Table3 shows the temperature thresholds for the three categories of aircraft for the studied airfields. These thresholds are based on the most commonly Atmosphere 2020, 11, 418 6 of 21 used aircraft at the studied airfields for categories 1 and 2 (i.e., Boeing 787–800 and Boeing 737–800, respectively), and are obtained from the corresponding performance charts [39,40]. Temperature thresholds for category 3 aircraft are obtained from the Federal Aviation Administration [41], which contain standard performance charts for category 3 type aircraft models for the studied airfields.

Table 3. Temperature thresholds used to estimate weight restriction days for studied airﬁelds. “N/A” means the aircraft cannot takeoﬀ at MTOW at any temperature because of a relatively short runway.

IATA Category 1 (◦C) Category 2 (◦C) Category 3 (◦C) YYZ 30 45 43.3 YVR 30 45 43.3 YUL 30 45 43.3 YYC - 23 29 YHZ - 45 43.3 YWG - 40 43.3 YXE - 26 43.3 YXY - 26 38 YZF - 30 37.8 YFB - 35 43.3 YFC - 30 40.5 YYT - 30 43.3 YYG - N/A 34.4

Following Es and Karwal [42], crosswind larger than 15 knots (7.7 m/s) and tailwind larger than 5 knots (2.6 m/s) are analyzed, as they are potentially considered too windy for takeoﬀ or landing, particularly for light aircraft models that belong to category 3. Tailwind larger than 10 knots (5.1 m/s) is also analyzed as they can cause overrun accidents [4,43]. According to the regulations of the International Civil Aviation Organization (ICAO) [43], the usability of a runway must be no less than 95% with maximum allowable crosswind conditions. Similarly, if the runway is wet or contaminated, no tailwind component (0–3 knots considered as calm) must be present [44]. The tailwind and crosswind analyses are performed for the longest runway at the various airports considered (Figure1b), using 3-hourly wind data simulated by GEM. The wind components along and perpendicular to the runway constitute tailwind and crosswind, respectively. The possibility of takeoﬀ in both directions is considered in estimating tailwind. The probability of high crosswind and tailwind events is obtained by dividing the number of 3-hourly crosswind and tailwind events exceeding respective thresholds by the total number of 3-hourly crosswind and tailwind events for the selected 30-year periods.

3.2. Approaches Validation of GEM simulated variables of interest is performed first by comparing GEM-ERAInterim with available observations for the 1981–2010 period. Boundary forcing errors are also assessed by comparing GEM-CanESM2 with GEM-ERAInterim for the same current period. Ensemble averages of GEM-CanESM2 are used for temperature, while for wind, 3-hourly wind data from the five GEM-CanESM2 members are merged for analysis. Projected changes to maximum daily temperature are studied for three future periods (2011–2040, 2041–2070, and 2071–2099) with respect to the current 1981–2010 period of the GEM-CanESM2 simulations, for RCP 4.5 and 8.5 scenarios, in an effort to quantify emission uncertainties. Evolution of weight restriction days and weight restriction hours for the warmest and coolest periods of a day are then analyzed by considering 30-year moving windows for RCP8.5 and RCP4.5 scenarios for the studied airports. Projected changes to the probability of occurrence of crosswind and tailwind components are also analyzed using the merged 3-hourly wind data, for the same three future periods as for daily maximum temperature. Atmosphere 2020, 11, 418 7 of 21

Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 21 4. Results 4. Results 4.1. Validation 4.1. Validation Previous studies [45] have validated GEM extensively and; therefore, only validation of variables relevantPrevious to this studies study (i.e.,[45] daily have maximum validated temperatureGEM extensively for summer and; andtherefore, annual only three-hourly validation wind of characteristics)variables relevant are presentedto this study here. (i.e., daily maximum temperature for summer and annual three- hourly wind characteristics) are presented here. 4.1.1. Daily Maximum Temperature 4.1.1. Daily Maximum Temperature Before validating the model simulations, the observation datasets are compared for the 1981–2010 periodBefore to understand validating uncertaintiesthe model simulations, in observations. the ob Comparisonservation datasets of ERA-Interim are compared and for ERA5 the shows1981– more2010 spatialperiod structureto understand in the latter,uncertainties especially in over observations. the mountainous Comparison regions of due ERA-Interim to the higher and resolution ERA5 ofshows ERA5 more (Figure spatial2a). structure Comparison in the withlatter, point especial observationsly over the atmountainous the airfields regions shows due that to ERA5 the higher is in betterresolution agreement of ERA5 with (Figure point 2a). observations Comparison compared with point to ERA-Interim,observations at suggesting the airfields clear shows improvements that ERA5 broughtis in better by the agreement higher resolution with point of ERA5 observations (Figure2a). GEM-ERAInterimcompared to ERA-Interim, generally captures suggesting the spatial clear patterns,improvements but suggests brought some by the underestimation higher resolution for of the ERA5 western (Figure regions 2a). ofGEM-ERAInterim Canada, when comparedgenerally withcaptures ERA5. the spatial GEM-ERAInterim patterns, but simulated suggests some temperatures underestimation are in better for the agreement western regions with observations of Canada, andwhen ERA5 compared than ERA-Interimwith ERA5. GEM-ERAInterim for most of the studied simula airfieldsted temperatures (Figure2 b),are suggestingin better agreement added value with inobservations downscaling and ERA-Interim. ERA5 than ERA-Interim To detect boundary for most forcing of the errorsstudied (i.e., airfields error due (Figure to the 2b), driving suggesting GCM data),added GEM-CanESM2value in downscaling is compared ERA-Interim. with GEM-ERAInterim, To detect boundary which forcing suggests errors warmer (i.e., error temperatures due to the in GEM-CanESM2.driving GCM data), This GEM-CanESM2 is due to the warm is biascompared of the driving with GEM-ERAInterim, CanESM2 model. For which interannual suggests variability, warmer GEM-ERAInterimtemperatures in GEM-CanESM2. patterns show This overall is due agreement to the warm with ERA5bias ofand the ERA-Interim,driving CanESM2 particularly model. For for northerninterannual Canada, variability, with some GEM-ERAInterim differences noted patterns for the show mid-central overall regions.agreement However, with ERA5 GEM-CanESM2 and ERA- showsInterim, generally particularly smaller for standardnorthern deviationCanada, with than so otherme differences simulations. noted for the mid-central regions. However, GEM-CanESM2 shows generally smaller standard deviation than other simulations. (a)

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Figure 2. (a) Spatial plots of mean and standard deviation (SD) and (b) point (airfield) values of mean Figure 2. (a) Spatial plots of mean and standard deviation (SD) and (b) point (airfield) values of mean of daily maximum 2 m temperature for summer (JJA) from observations, ERA5 reanalysis, ERA-Interim of daily maximum 2 m temperature for summer (JJA) from observations, ERA5 reanalysis, ERA- reanalysis, GEM-ERAInterim, and GEM-CanESM2, for the 1981–2010 period. Interim reanalysis, GEM-ERAInterim, and GEM-CanESM2, for the 1981–2010 period. 4.1.2. Wind 4.1.2. Wind Mean annual, summer (JJA), and winter (DJF) wind magnitudes simulated by GEM are validated by comparingMean annual, with point summer observations (JJA), and from winter studied (DJF) airfields wind and magnitudes reanalysis datasets. simulated Figure by3 aGEM shows are lowervalidated wind by speeds comparing for the mountainouswith point observations areas of western from Canada studied for airfields ERA5 compared and reanalysis to ERA-Interim, datasets. whichFigure is again3a shows due tolower the higher wind spatialspeeds resolution for the mo of ERA5.untainous The areas point /airfieldof western observations Canada generallyfor ERA5 havecompared larger windto ERA-Interim, magnitudes which than ERA5,is again as expected.due to the This higher is because spatial the resolution roughness of lengthsERA5. areThe generallypoint/airfield smaller observations for airports, generally yielding higher have windlarger magnitudes. wind magnitudes Wind magnitudes than ERA5, for as theexpected. mountainous This is westernbecause regions the roughness are improved lengths in are GEM-ERAInterim generally smaller compared for airports, to ERA-Interim, yielding higher which wind demonstrates magnitudes. addedWind valuemagnitudes of downscaling for the mountainous ERA-Interim. western GEM-CanESM2 regions are improved is generally in GEM-ERAInterim in good agreement compared with GEM-ERAInterim,to ERA-Interim, which suggesting demonstrates less influence added ofvalue boundary of downscaling forcing data. ERA-Interim. Comparison GEM-CanESM2 of 10 m mean is annualgenerally wind in good magnitudes agreement at thewith studied GEM-ERAInterim, airfields (Figure suggesting3b) suggests less influence underestimation of boundary of windforcing magnitudesdata. Comparison in the 0.5–1.8 of 10 m m mean/s range annual in GEM-ERAInterim wind magnitudes when at the compared studied toairfields point observations (Figure 3b) suggests for the westernunderestimation airfields, whileof wind the magnitudes underestimation in the is0.5–1 in the.8 m/s 0.2–1 range m/s in range GEM-ERAInterim for the central when airfields. compared Both underto point and observations overestimations for the are western noted for airfields, the eastern while airfields the underestimation with differences is generallyin the 0.2–1 less m/s than range 1 m /fors. the Thecentral wind airfields. roses from Both ERA5 under for theand airfields overestima exhibittions similar are patternsnoted for to thatthe eastern of point airfields observations with (Figuredifferences4), except generally for Calgary less than and 1 Yellowknife.m/s. The temporal resolution of the two data are the same (i.e., hourly)The wind and roses the difromfferences ERA5 noted for the are airfields primarily exhibi becauset similar ERA5 patterns provides to that average of point values observations for the grid(Figure cell. 4), Di ffexcepterences for can; Calgary therefore, and beYellowknife. large for regions The temporal with important resolution orography of the two and data/or water are the bodies. same Comparison(i.e., hourly) of and the the wind differences roses (Figure noted4 )are at theprimarily airport because locations ERA5 with provides the most average representative values for grid the cellsgrid from cell. theDifferences simulations can; suggest therefore, overall be agreement,large for regions albeit thewith larger important directional orography spread andand/or reduced water magnitudesbodies. Comparison for GEM-ERAInterim, of the wind roses which (Figure can be 4) partly at the due airport to the locations coarse temporalwith the most (three-hourly) representative and spatialgrid cells resolution from the of data.simulations As already suggest mentioned, overall agreement, topographical albeit eff ectsthe larger are strong directional if the observation spread and stationreduced is nearby magnitudes mountains for GEM-ERAInterim, or open water bodies which [46]. can It must be partly be noted due that to the pointcoarse observations temporal (three- may alsohourly) be subject and spatial to biases resolution depending of data. on the As accuracy already andmentioned, sensitivity topographical of the anemometer effects are [37 ],strong especially if the forobservation the case of station weak and is nearby strong windsmountains [47]. Windor open roses wa fromter bodies GEM-CanESM2 [46]. It must are be not noted shown that in Figurethe point4 asobservations the patterns may are very also similar be subject to that to of biases GEM-ERAInterim. depending on As forthe ERA5,accuracy ERA-Interim and sensitivity shows someof the importantanemometer differences [37], especially in wind roses for the for Calgarycase of andweak Yellowknife, and strong when winds compared [47]. Wind to point roses observations. from GEM- TheCanESM2 direction are is not predominantly shown in Figure westerly 4 as the in both patterns ERA5 are and very GEM-ERAInterim similar to that of for GEM-ERAInterim. Calgary; however, As observationsfor ERA5, ERA-Interim also suggest shows southerly some and important northerly differences winds. As in for wind Yellowknife, roses for ERA5 Calgary and and simulations Yellowknife, do when compared to point observations. The direction is predominantly westerly in both ERA5 and GEM-ERAInterim for Calgary; however, observations also suggest southerly and northerly winds.

Atmosphere 2020, 11, 418 9 of 21 Atmosphere 2020, 11, x FOR PEER REVIEW 9 of 21 notAs capturefor Yellowknife, the northerly ERA5 direction and insimulations point observations. do not capture Overall, GEMthe northerly simulations direction show agreement in point withobservations. ERA5 and Overall, are able GEM to display simulations the wind show patterns agreem atent the with airports. ERA5 and are able to display the wind patternsThe at overall the airports. ability of GEM in simulating the observed characteristics of daily maximum temperaturesThe overall and ability wind patternsof GEM suggestin simulating that the the model observed can be characteristics applied to study of daily future maximum changes, withtemperatures careful interpretation and wind patterns for regions suggest with that biases. the model can be applied to study future changes, with careful interpretation for regions with biases. (a)

(b)

FigureFigure 3.3.( a(a)) Spatial Spatial plots plots of meanof mean annual, annual, summer summ ander winterand winter 10 m wind10 m speeds wind andspeeds (b) pointand ( (airﬁeld)b) point values(airfield) of 10values m mean of 10 annual m mean wind annual speed wind forobservations, speed for observations, ERA5 reanalysis, ERA5 ERA-Interimreanalysis, ERA-Interim reanalysis, GEM-ERAInterimreanalysis, GEM-ERAInterim and GEM-CanESM2, and GEM-CanESM2, for the 1981–2010 for the period. 1981–2010 period.

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Figure 4. Distributions of wind direction and magnitude (m/s) from observations, ERA5 reanalysis and Figure 4. Distributions of wind direction and magnitude (m/s) from observations, ERA5 reanalysis GEM-ERAInterimand GEM-ERAInterim for the for 1981–2010 the 1981 period.–2010 Hourlyperiod. windHourly magnitudes wind magnitudes are considered are considered for observations for andobservations ERA5, while and three-hourly ERA5, while values three-hourly are used values for GEM-ERAInterim. are used for GEM-ERAInterim. 4.2. Projected Changes 4.2. Projected Changes 4.2.1. Daily Maximum Temperature and Weight Restriction Days/Hours 4.2.1. Daily Maximum Temperature and Weight Restriction Days/Hours The projected changes to mean daily maximum 2 m temperatures for the June to September The projected changes to mean daily maximum 2 m temperatures for the June to September period, shown in Figure5, suggest increases of the order of 4 to 6 ◦C by the end of the century for RCP period, shown in Figure 5, suggest increases of the order of 4 to 6 °C by the end of the century for

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4.5 scenario, while for RCP 8.5 scenario, it is in the 7–10 ◦C range across Canada. Most of the southern regionsRCP 4.5 will scenario, experience while daily for RCP maximum 8.5 scenario, temperatures it is in over the 307–10◦C °C on range average, across and theyCanada. exceed Most 35 ◦ofC the for thesouthern inland regions regions will of southwest experience Canada daily bymaximum the end ofte themperatures century, whereover 30 the °C average on average, daily maximum and they temperatureexceed 35 °C infor summer the inland is less regions than of 25 southwest◦C for the Canada current by climate. the end These of the changes century, can where have the signiﬁcant average impactsdaily maximum on aviation temperature and aircraft in summer takeoﬀ performance. is less than 25 °C for the current climate. These changes can have significant impacts on aviation and aircraft takeoff performance. (a)

(b)

Figure 5. (a) Mean daily maximum temperature for summer (JJA) for the 2011–2040, 2041–2070 and 2071–2099Figure 5. (a) periods Mean for daily RCP4.5 maximum and RCP8.5 temperature scenarios, for and summer (b) their (JJA) projected for the changes2011–2040, with 2041–2070 respect to and the 1981–20102071–2099 period.periods for RCP4.5 and RCP8.5 scenarios, and (b) their projected changes with respect to the 1981–2010 period. The evolution of the mean number of weight restriction days for 30-year moving windows for diTheﬀerent evolution categories of the of mean aircraft number for the of summer weight re periodstriction for days the studied for 30-year airports moving for RCPwindows 4.5 and for 8.5different scenarios categories are shown of aircraft in Figure for6. Figurethe summer6a shows period the number for the ofstudied weight airports restriction for days RCP for 4.5 category and 8.5 1scenarios aircraft forare YYZshown (Toronto), in FigureYVR 6. Figure (Vancouver) 6a shows and the YUL number (Montreal); of weight results restriction for this days category for category are not considered1 aircraft for for YYZ other (Toronto), airfields since YVR intercontinental (Vancouver) and flights YUL are (Montreal); not common results there. for For this the category RCP8.5 scenario, are not allconsidered three airports for other will encounter airfields weightsince intercontinent restriction daysal afterflights 2040. are Weight not common restriction there. days For are the noted RCP8.5 even towardsscenario, the all end three of theairports current will climate encounter for YYZ; weight it must restriction be noted days that theafter warm 2040. bias Weight in the restriction GEM-CanESM2 days are noted even towards the end of the current climate for YYZ; it must be noted that the warm bias in the GEM-CanESM2 simulations can lead to slightly earlier detection of weight restriction days. By the end of the century, it will increase to around 70 days in summer for YYZ, and more than 40 days

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simulationsAtmosphere 2020 can, 11 lead, x FOR to PEER slightly REVIEW earlier detection of weight restriction days. By the end of the century,12 of 21 it will increase to around 70 days in summer for YYZ, and more than 40 days in YUL and YVR. For the RCP4.5in YULscenario, and YVR. there For the are RCP4.5 few weight scenario, restriction there daysare few in YVRweight in restriction the future, days and thein YVR number in the of future, weight restrictionand the number days are of obviously weight restriction lower than days the are ones obvi forously RCP8.5 lower during than mid the toones late for century. RCP8.5 during mid to late century. (a) Category 1

(b) Category 2

Figure 6. Cont.

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Figure 6. Average number of weight restriction days for 30-year moving windows for summer (JJA) Figure 6. Average number of weight restriction days for 30-year moving windows for summer (JJA) for the 1981 to 2100 period for the RCP4.5 (in blue) and RCP8.5 (in red) scenarios for (a) category 1, for the 1981 to 2100 period for the RCP4.5 (in blue) and RCP8.5 (in red) scenarios for (a) category 1, (b) category 2, and (c) category 3 aircrafts. The mean values for 30-year widows are plotted at the end (b) category 2, and (c) category 3 aircrafts. The mean values for 30-year widows are plotted at the end of the period, and the shaded region shows the interquartile range for respective windows. Results are of the period, and the shaded region shows the interquartile range for respective windows. Results shown only for airfields with weight restriction days. are shown only for airfields with weight restriction days. For category 2 aircraft, Figure6b shows weight restriction even in current climate for YYC (Calgary) For category 2 aircraft, Figure 6b shows weight restriction even in current climate for YYC and YXE (Saskatoon). Weight restriction days increase for YYC and YXE and exceed 60 days by the end (Calgary) and YXE (Saskatoon). Weight restriction days increase for YYC and YXE and exceed 60 of the century for both scenarios, which is due to the higher projected increases in temperature and the days by the end of the century for both scenarios, which is due to the higher projected increases in relatively low temperature thresholds (due to high elevations) used to estimate weight restriction days. temperature and the relatively low temperature thresholds (due to high elevations) used to estimate Weight restriction days appear only in the late century for Fredericton (YFC) and Winnipeg (YWG) for weight restriction days. Weight restriction days appear only in the late century for Fredericton (YFC) RCP8.5 (not shown). Weight restriction days for category 3 aircraft are noted only for YYC (Figure6c), and Winnipeg (YWG) for RCP8.5 (not shown). Weight restriction days for category 3 aircraft are for both scenarios. noted only for YYC (Figure 6c), for both scenarios. In reality, the scheduled takeoff for category 1 and 2 aircraft, being mostly long-range, are during In reality, the scheduled takeoff for category 1 and 2 aircraft, being mostly long-range, are during morning and evening hours for some airfields. Therefore, they can still take off on weight restriction morning and evening hours for some airfields. Therefore, they can still take off on weight restriction days at MTOW by avoiding the warmest period of the day. To better understand the impacts, analysis days at MTOW by avoiding the warmest period of the day. To better understand the impacts, analysis is performed for the warm (10:00 am to 7:00 pm local time) and cool (12:00 am to 10:00 am and 7:00 pm is performed for the warm (10:00 am to 7:00 pm local time) and cool (12:00 am to 10:00 am and 7:00 till 12:00 am combined) periods of the day. Weight restriction hours are estimated for these two periods pm till 12:00 am combined) periods of the day. Weight restriction hours are estimated for these two for the airfields that experience significant weight restriction days in future climate. Figure7 shows the periods for the airfields that experience significant weight restriction days in future climate. Figure 7 average weight restriction hours for the summer period for 30-year moving windows. The results shows the average weight restriction hours for the summer period for 30-year moving windows. The showresults large show di fflargeerences differences between between the warmer the warmer and cooler and periods. cooler periods. ForFor categorycategory 1 aircraft,1 aircraft, the the weight weight restriction restriction hours hours during during the warmer the warmer period period of the day of increasesthe day toincreases more than to more three hoursthan three by the hours end ofby the the century end of the for YYZcentury for RCP8.5.for YYZ Relativelyfor RCP8.5. smaller Relatively increases smaller are notedincreases for RCP4.5.are noted Weight for RCP4.5. restriction Weight hours restriction during hour the coolers during time the of cooler the day time is rareof the in day the futureis rare forin boththe future scenarios. for both scenarios. For category 2 aircraft, YXE and YYC experience a large number of weight restriction hours during the warmer period of the day even in the current climate, which increases to about 6–8 h by the end of the century for both scenarios. However, weight restriction hours during the cooler periods of the day show larger differences between RCP8.5 and RCP4.5, compared to the results for the warmest period of the day. This is because projected changes to daily minimum temperatures are larger than that for daily maximum temperatures, which is more predominant for RCP8.5 scenario. Furthermore, the weight restriction hours seem to stabilize for RCP4.5 towards the end of the century, which is consistent with the changes in temperature. The shaded region, showing the interquartile range, generally becomes thinner by the end of the century for both scenarios for the warmer period of the day as the temperature threshold is generally exceeded for most of the hours of the warmest period. This situation is not reached in the case of the coolest period and hence thinning of the interquartile range is not visible by the end of the century.

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(a) Category 1

(b) Category 2

Figure7. Cont.

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Figure 7. Same as Figure6, but shows weight restriction hours during the warmer (dark shades of red Figureand blue) 7. Same and cooleras Figure (light 6, but shades shows of redweight and restrictio blue) periodsn hours of theduring day. the warmer (dark shades of red and blue) and cooler (light shades of red and blue) periods of the day. For category 3 aircraft, some weight restriction hours are noted during the warmer periods of the day forFor YYC category for RCP8.5. 2 aircraft, This YXE is significantly and YYC experience smaller for RCP4.5.a large number Much smaller of weight increases restriction are noted hours for duringthe cooler the periodwarmer of period the day. of the day even in the current climate, which increases to about 6–8 h by the end of the century for both scenarios. However, weight restriction hours during the cooler periods 4.2.2. Crosswind and Tailwind of the day show larger differences between RCP8.5 and RCP4.5, compared to the results for the warmestAnalysis period of meanof the windday. magnitudesThis is because for futureprojected climate changes suggests to daily increases minimum in wind temperatures magnitudes are for largernorthern than regions that for of daily Canada maximum for both temperatures, scenarios, and which decreases is more in easternpredominant Canada for for RCP8.5 RCP8.5 scenario. by late Furthermore,century (Figure the8). weight restriction hours seem to stabilize for RCP4.5 towards the end of the century, whichNo is majorconsistent changes with in the wind changes directions in temperature. for the studied airfields are noted (figure not shown). Figure9 showsThe the shaded probability region, of occurrenceshowing the for interquartile crosswinds largerrange, than generally 15 knots becomes for the thinner studied by airfields. the end Results of the centurysuggest for that both the scenarios probability for of the occurrence warmer period of crosswind of the day larger as the than temperature 15 knots is threshold generally is lower generally than exceeded5%, with relativelyfor most of large the hours values of for the northeastern warmest period airfields.. This Both situation increases is not and reached decreases in the are case noted of the for coolestfuture climate,period and with hence decreases thinning noted of mostly the interquartile for the eastern range regions, is not visible for both by RCP the end 4.5 and of the 8.5 century. scenarios. For theFor northern category regions, 3 aircraft, YFB some (Iqaluit) weight shows restrictio consistentn hours increases, are noted while during YZF the (Yellowknife) warmer periods and YXY of the(Whitehorse) day for YYC show for decreases.RCP8.5. This Majority is significantly of the southwest smaller for airfields RCP4.5. shows Much increases smaller in increases strong crosswinds. are noted for theThe cooler probability period of of the the day. occurrence of tailwind larger than 5 and 10 knots shown in Figure 10 suggests that most of the studied airfields in the south have around 30% probability of experiencing 4.2.2.tailwind Crosswind larger than and 5 Tailwind knots, and exceeding 50% in some airfields located in the northeast in the current climate. In future climate, the probability remains unchanged for RCP4.5. For RCP8.5, the projected Analysis of mean wind magnitudes for future climate suggests increases in wind magnitudes changes suggest that the probability decreases consistently for most of the airfields in coastal areas for northern regions of Canada for both scenarios, and decreases in eastern Canada for RCP8.5 by across the three future periods. For airfields located in northern areas, the probabilities consistently late century (Figure 8). increase, while they remain the same with slight fluctuations for the airfields in central regions. For tailwind thresholds larger than 10 knots, southern airfields generally have probabilities smaller than 5%, and those for northern airfields are around 10% in current climate. For the three future periods, there are some increases for northern airfields, whereas probabilities experience a larger decrease than for the case of the 5 knots threshold for southern Canada. Overall, crosswind and tailwind probabilities remain unchanged or slightly decrease for most of the southeastern airfields with time but increase for northern and central airfields. The projected increases can impact aircraft operations leading to delays in future climate. For example, in Iqaluit, where only one runway exists, given the increases in the occurrence of high tailwinds in the future climate, from air traffic efficiency point of view, it will be beneficial to consider a crosswind runway.

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(a)

(b)

FigureFigure 8. 8. ProjectedProjected changes changes to to the the mean mean annual, annual, summer summer and and winter winter 10 10 m m wind wind magnitudes magnitudes for for the the 2011–2040,2011–2040, 2041–2070 2041–2070 and and 2071–2100 2071–2100 periods periods with with respec respectt to to the the current current 1981–2010 1981–2010 period period for for (a ()a RCP) RCP 4.54.5 and and (b (b) RCP) RCP 8.5 8.5 scenarios. scenarios.

No major changes in wind directions for the studied airfields are noted (figure not shown). Figure 9 shows the probability of occurrence for crosswinds larger than 15 knots for the studied

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airfields. Results suggest that the probability of occurrence of crosswind larger than 15 knots is generally lower than 5%, with relatively large values for northeastern airfields. Both increases and decreases are noted for future climate, with decreases noted mostly for the eastern regions, for both RCP 4.5 and 8.5 scenarios. For the northern regions, YFB (Iqaluit) shows consistent increases, while Atmosphere 2020YZF, 11(Yellowknife), 418 and YXY (Whitehorse) show decreases. Majority of the southwest airfields shows 17 of 21 increases in strong crosswinds.

Figure 9. ProbabilityFigure 9. Probability of occurrence of occurrence of crosswind of crosswind larger larger than than 15 knots15 knots for for the the longest longest runway runway for current current climate (left), and their projected changes (in %, right) for three future periods for RCP4.5 climate (left), and their projected changes (in %, right) for three future periods for RCP4.5 (top) and (top) and RCP8.5 (bottom) scenarios. RCP8.5Atmosphere (bottom) 2020, 11 scenarios., x FOR PEER REVIEW 18 of 21 The probability of the occurrence of tailwind larger than 5 and 10 knots shown in Figure 10 (a) suggests that most of the studied airfields in the south have around 30% probability of experiencing tailwind larger than 5 knots, and exceeding 50% in some airfields located in the northeast in the current climate. In future climate, the probability remains unchanged for RCP4.5. For RCP8.5, the projected changes suggest that the probability decreases consistently for most of the airfields in coastal areas across the three future periods. For airfields located in northern areas, the probabilities consistently increase, while they remain the same with slight fluctuations for the airfields in central regions. For tailwind thresholds larger than 10 knots, southern airfields generally have probabilities smaller than 5%, and those for northern airfields are around 10% in current climate. For the three future periods, there are some increases for northern airfields, whereas probabilities experience a larger decrease than for the case of the 5 knots threshold for southern Canada. Overall, crosswind and tailwind probabilities remain unchanged or slightly decrease for most of the southeastern airfields with time but increase for northern and central airfields. The projected increases can impact aircraft operations leading to delays in future climate. For example, in Iqaluit, where only one runway exists, given the increases in the occurrence of high tailwinds in the future climate, from air traffic efficiency point of view, it will be beneficial to consider a crosswind runway.

(b)

FigureFigure 10. Same 10. Same as Figure as Figure9, but9, but for for tailwind tailwind larger larger than than (a) (5 aknots) 5 knots and (b and) 10 knots. (b) 10 knots.

5. Discussions and Conclusions This study evaluates projected changes to aircraft weight restriction days, and occurrences of crosswind and tailwind exceeding predefined thresholds that might affect aircraft takeoff performance for 13 airports across Canada. To this end, projected changes to summer daily maximum temperature, wind speed and wind directions, based on GEM simulations for the 1981 to 2100 period, driven by two five-member ensembles of CanESM2, corresponding to RCP4.5 and RCP8.5 emissions scenarios are analyzed. Validation of ERA-Interim-driven GEM simulation indicates that the model is able to reproduce the observed 10 m wind speed and near-surface temperature characteristics reasonably well, confirming the suitability of the model in assessing projected changes. Projected changes to the summer daily maximum temperature suggest that weight restriction days for the three commonly used aircraft types (i.e., those used for long-, medium- and short-haul flights, referred to as category 1, 2 and 3, respectively) will increase significantly by the end of the

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5. Discussion and Conclusions This study evaluates projected changes to aircraft weight restriction days, and occurrences of crosswind and tailwind exceeding predefined thresholds that might affect aircraft takeoff performance for 13 airports across Canada. To this end, projected changes to summer daily maximum temperature, wind speed and wind directions, based on GEM simulations for the 1981 to 2100 period, driven by two five-member ensembles of CanESM2, corresponding to RCP4.5 and RCP8.5 emissions scenarios are analyzed. Validation of ERA-Interim-driven GEM simulation indicates that the model is able to reproduce the observed 10 m wind speed and near-surface temperature characteristics reasonably well, confirming the suitability of the model in assessing projected changes. Projected changes to the summer daily maximum temperature suggest that weight restriction days for the three commonly used aircraft types (i.e., those used for long-, medium- and short-haul flights, referred to as category 1, 2 and 3, respectively) will increase significantly by the end of the century for some of the studied airfields, especially those located at high elevations, such as Calgary and Saskatoon. For RCP4.5, the weight restriction days start to appear much later than for RCP8.5 scenario for low elevation airfields (i.e., for all except Calgary and Saskatoon). Additional analysis for the warmer and cooler periods of the day suggests that the weight restrictions are generally not applicable for cooler periods, except for Calgary and Saskatoon, for category 2 aircraft, with important differences noted between RCP4.5 and RCP8.5 scenarios. It should be noted that the temperature thresholds used to determine the weight restriction days for the aircraft types are defined based on current runway lengths and MTOW, and can change if the aircraft operate with less than MTOW and if the runway lengths are extended, which again can be limited by the aircraft speed limit. The results related to the weight restriction days provide useful preliminary insights, which can inform aircraft takeoff scheduling and/or takeoff weights in future climate. For some short-haul flights, weight restriction can be solved by reducing the fuel weight. However, for long-haul flights, which require full capacity of the fuel tank, passengers and cargo have to be restricted if runway lengths are not extended. Other options such as changing aircraft type and making a stop for additional fuel can be considered. Changes in technology such as power off taxiing, just on time engine power ups and wings better designed for greater lift can also mitigate weight restriction in the future. The temperature threshold used in this study is based on the assumption of maximum takeoff power for the various categories of aircraft considered [39]. Furthermore, the real air temperature around the runway could be higher than that simulated by the model due to the lower albedo of the runway surfaces and surrounding buildings. To capture this better, ultra-high resolution climate simulations can be useful. As for wind, the probability of strong tailwind and crosswind components are projected to decrease for the airports in the eastern region, while increases are noted for the northern and central airports, for both RCP scenarios. No significant changes are noted for the other airports. The crosswind and tailwind analyzed in this study can be used to re-evaluate runway orientation and length. For the northern airfields with increasing probability of tailwind, changing direction on the same runway can be considered as is generally done. However, if there are limitations to this, including those related to topography, planning for an alternate runway in the future could be an option to prevent accidents and delays. Additional analyses are required to guide such airport specific planning. Detailed studies using ultra-high resolution climate simulations focused over regions/airfields of interest coupled with site/runway level computational fluid dynamics modelling, to capture microclimatic conditions, should be undertaken to better inform decision-making and climate change adaptation planning.

Author Contributions: Conceptualization, Y.Z. and L.S.; methodology, Y.Z. and L.S.; validation, Y.Z.; formal analysis, Y.Z.; original draft preparation, Y.Z. and L.S.; manuscript review and editing, L.S. and Y.Z.; visualization, Y.Z.; funding acquisition, L.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Sciences and Engineering Research Council of Canada and the Trottier Institute for Sustainability in Engineering and Design. Atmosphere 2020, 11, 418 19 of 21

Acknowledgments: The GEM simulations used in this study were performed on the supercomputer managed by Compute Canada and Calcul Québec. This research was funded by the National Sciences and Engineering Research Council of Canada and the Trottier Institute for Sustainability in Engineering and Design. The authors would like to thank William Maynard of Transport Canada for reviewing an earlier version of the manuscript and for providing information about the studied airfields. Conflicts of Interest: The authors declare no conflicts of interest.

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