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Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example of Birobidzhan, Russian Far East

Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example... Hindawi Publishing Corporation Advances in Meteorology Volume 2013, Article ID 749270, 10 pages http://dx.doi.org/10.1155/2013/749270 Research Article Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example of Birobidzhan, Russian Far East 1 2 1 Jan Paul Bauche, Elena A. Grigorieva, and Andreas Matzarakis Chair of Meteorology and Climatology, Albert Ludwigs University Freiburg, Werthmannstraße 10, 79085 Freiburg, Germany Institute for Complex Analysis of Regional Problems, Far Eastern Branch, Russian Academy of Sciences, Birobidzhan 679016, Russia Correspondence should be addressed to Jan Paul Bauche; paul@mbauche.de Received 4 June 2013; Revised 27 August 2013; Accepted 23 September 2013 Academic Editor: Marialena Nikolopoulou Copyright © 2013 Jan Paul Bauche et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The study shows the eeff ct of urban structures on human thermal comfort indices in the extreme climate region of the Russian Far East, with an annual temperature range of75 C. The study examines different urban zones in Birobidzhan, the capital city of the Jewish Autonomous Region (JAR). The climate of this region can be characterized as continental monsoon climate. eTh difference of thermal values for three zones with different vegetation and build-up density shows the influence of urban planning on the local microclimate. The moderating effect of dense build-up and inner city vegetation on extreme thermal conditions becomes clear when comparing all zones. Through the analysis of daily and monthly timelines it was possible to determine preferable times of the day for inner city outdoor activities. From the results derived from PET with a total of 170 days per year with PET values below 0 C Birobidzhan can be considered a region of extreme cold stress. This means that an adaptation based solely on behaviour and clothing is not sufficient, but an adaptation of the urban surroundings and therefore the identification and choice of preferable urban structures is necessary. 1. Introduction extremely suitable for the purpose of analysing the impact of urbanstructuresonthe humanthermal comfortassuming Since the last decades of the 20th century and due to the an intensification of extreme meteorological conditions in challenges of climate change, climatological and meteorolog- presently moderate climate areas, due to the global climate ical parameters have been in the focus of urban planning. change. During the last 20 years the interest in the human Most of those studies assess the standard meteorological thermal bioclimate has been rising due to great awareness parameters associated with human thermal comfort such of the inu fl ence of climate on our lives which is strongly as air temperature, global radiation, wind velocity, relative connected to the public debate about climate change and its humidity, or precipitation. However, if they are assessed just influence on everyday life. As a result of this development by themselves, the results are taken out of the human context regions that are already under the inu fl ence of harsh climates and lose their original purpose. To put them into context, the are very interesting for analysis of climate change results. application of complex and differentiated human bioclimate eTh indices used for this study are the physiologically indices is needed. For the purpose of this study two of these equivalent temperature (PET) based on the Munich Energy- indices haven been applied to the meteorological conditions balance Model for Individuals (MEMI) [1–3], displayed in and the urban structures of Birobidzhan, the capital city of degrees Celsius ( C) which makes it easy to comprehend and the Jewish Autonomous Region (JAR), at the Russian Far easy to be compared to other indices or measurement, and the East. In the course of a year this region experiences all universal thermal climate index (UTCI), also displayed in C, facets of extreme meteorological conditions from arid cold which is based on a multinode human energy balance model to humid warm (Figure 1). This makes the region of the JAR for a more adaptive approach to extreme climate conditions 2 Advances in Meteorology 30 180 0 Sources: Esri, DeLorme, NAVTEQ, USGS, Intermap, iPC, NRCAN, Esri Japan,METI, Esri 1 : 100.000.000 China (Hong Kong), Esri −10 −20 −30 −40 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (km) 0 30 60 120 180 240 T , Min 1 : 5.000.000 Sources: Esri, DeLorme, NAVTEQ, USGS, Intermap, iPC, NRCAN, Esri Japan, T , Max METI, Esri China (Hong Kong), Esri (a Th iland), TomTom, 2013 Figure 1: Climate diagram for the Birobidzhan area (data source: Figure 2: Regional and local position of Birobidzhan. http://worldweather.wmo.int/). Table 1: Selected locations (zones) and their respective properties. [4, 5]. A selection of studies conducted in the JAR, and Zone Type Build-up Vegetation such concerning the topic of the human biometeorology, is displayed to show what has been done so far. Studies on 1 Residential Dense High this topic have been published since the late eighties [1, 6]. 2 Street Medium Light They show the development and application of PET based 3Square Light None on the human energy balance model MEMI [1–3, 7, 8]and the RayMan model [9, 10] and the eeff ct of shading on outdoor comfort [11, 12]aswellasthe developmentofUTCI 3. Methods [5, 13, 14] and the underlying multinode model [4, 15–17]. In the following years, papers concerning the bioclimate of the For the assessment of the human thermal bioclimate several JAR, focusing on the efficiency of agricultural crop growing indices have been developed over the last 50 years. Two ther- and outdoor recreation and tourism, were published [18– mal indices were used for this study, namely, the physiologi- 22]. These works are designed to nd fi preferable outdoor cally equivalent temperature (PET) and the universal thermal activities or to quantify the inu fl ence of the regional climate climate index (UTCI) [4, 15–17], both of which use the unit on crop seasonsand areusually basedondaily andmonthly degrees Celsius and are based on models of human ther- climate data. This study aims to give an actual and accurate mal balance. eTh meteorological data from the Birobidzhan assessment of the human thermal bioclimate and to n fi d WMO station (WMO index 31713) has been used as input for preferable city structures or at least preferable inner city the calculation of the thermal indices, specicall fi y the data locations at any given time of day in the city of Birobidzhan for air temperature, wind velocity, wind direction, relative using a high temporal resolution of meteorological data. humidity, and cloud cover as a proxy value for the global radiation. These parameters have been recorded at the climate station in a three-hour interval, resulting in eight measuring 2. Area of Investigation points per day, for the 11-year period from 2000 to 2010. Birobidzhan is located close to the Chinese northern border Using this data and the RayMan model the thermal ∘ ∘ at 48 Nand 132 E(Figure 2)withamean altitude of 76ma.sl. indices can be calculated [9, 10]. Additionally the obstacle and is inhabited about 75,000 people on an area of 169 km . parameters at three different locations within the city were Even though the latitude coincides with a moderate climate put into the model to determine their influence on the by the climate in the Jewish Autonomous Region (JAR), human thermal bioclimate. All three locations are highly of which Birobidzhan is the capital, is far from moderate. frequented by the local population, but they are very different Its continental exposition leads to cold winters and warm in terms of their structural specifications. Information for all summers. This eeff ct is intensified by the influence of the three locations is summarised in Table 1.Theterms used to summer monsoon and its close proximity to the Siberian describe “Build-up” and “Vegetation” are relative terms meant high pressure efi ld resulting in an annual variation in air to compare the zones with each other. Pictures of the selected temperature of up to 75 C in the course of six months in areasaswellasfisheyepicturescan be foundinthe appendix. extreme cases. Due to this variation the annual course of the The meteorological data were made freely available via meteorological factors in this region shows great variability. http://www.ogimet.com/ andweredownloadedfor the From a mean maximum air temperature of about 26 CinJuly period from 2000 to 2010 in 3-hour intervals (01:00, 04:00, to−29 C in January and a monthly precipitation of 154 mm in 07:00, 10:00, 13:00, 16:00, 19:00, and 22:00 local time). eTh August to 5 mm in February all facets of an extreme climate availability of these meteorological measurements at eight can be experienced. points of time per day ensures a good temporal resolution of T ( C) P (mm) Advances in Meteorology 3 Birobidzhan, 2000–2010 until the midst of February PET values were not above 0.0 C as it is a period of constant frost. eTh highest PET values occur from the midst of June to the end of August. Values ∘ ∘ between 29.1 C and 41.0 C can be considered a fairly common phenomenon (about 14%). With occurrence frequencies of ∘ ∘ about 1% values between 41.1 Cand 45.0 Coccur rather rarely. With about 30.9% the first decade of August shows the highest occurrence frequency of comfortable PET values ∘ ∘ between 18.1 C and 23.0 C. Spring and autumn generally consistofPET values in therange of slight heat stress to extreme cold stress and require the most flexibility in terms of thermal adaption. In the summer months of July, June, and August PET does not drop to values below 0.0 C. Figure 4 shows the 2-dimensional daily and monthly Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec courses of PET values in January and July, as an example Decade for winter and summer, respectively. The 𝑦 -axis shows the 4.1 to 8.0 41.1 to 45.0 days of July and the𝑥 -axis shows the time steps according to 0.1 to 4.0 35.1 to 41.0 the legend. The highest PET values can be expected towards −9.9 to 0.0 29.1 to 35.0 theend of July around the26thday andingeneral in the −19.9 to −10.0 23.1 to 29.0 time between 13:00 and 16:00. During this time PET reaches −29.9 to −20.0 18.1 to 23.0 ∘ ∘ values up to the range of 35.0 C to 41.0 C. The coolest times <−30.0 13.1 to 18.0 of the day are the ones in the early morning between 4:00 8.1 to 13.0 PET ( C) ∘ ∘ and 7:00. Here PET values range between 13.0 Cand 18.0 C. Figure 3: Mean frequency distribution of PET values in Biro- In winter (January) PET drops to values below−30.0 Cand bidzhan, zone 1, during the year divided into 10-day intervals in extreme cases even below−40.0 C creating extreme cold (decades) for the period 2000–2010. stress in terms of the human bioclimate. These extremely low values can be expected in the midst of January (exemplary for winter) in the early morning hours between 4:00 and 7:00. the data. eTh data were initially available in SYNOP and In general the highest PET values in winter do not reach the hadtobedecoded to standard meteorological units. This 0.0 C mark but rather stay considerably lower. They can be was done using Microsoft Excel. All of the calculations and expected in the time between 13:00 and 16:00. From 16:00 on, simulations in this study are based on the meteorological data PET drops until it reaches its lowest value in the time around obtained from this synoptic station and were modified only 7:00. During January PET does not vary much, but there is an by the surrounding structures via obstacle files in RayMan accumulation of very low values in the time from the 10th to which were based on maps of the city and local observation of the 17th of January. the buildings. eTh general assumption for the transfer of the Zone 2 is less sheltered from solar radiation than zone data is that air temperature and air humidity remain the same 1 and therefore shows a tendency to have more extreme for the city and the rural station, and only wind speed, which PET values. Since the climate data has been recorded at the is changed according to roughness, and radiation ux fl es, same station the yearly change is the same as in zone 1, which can be adjusted with the RayMan model, modify the but its amplitude is different. With 29.4% the frequency of indices. PET values below−30.0 C is about 2% higher than that in zone 1 (Figure 5). Still the winter months from the end of November until the end of February are consistenty below 4. Results 0.0 C, but the PET values are less extreme. In the summer 4.1. Physiologically Equivalent Temperature. The following months the occurrence frequency of comfortable PET values ∘ ∘ section provides the results of PET in the context of the between 18.1 C and 23.0 Cdrops to 29.8%, that is,1%lower in comparison to zone 1. The extremely high values that result in different building situations. It also includes its daily course for selected months in summer and winter. eTh overall results moderate to extreme heat stress increase in comparison. eTh showed a great range of PET values being being between frequency of values above 35.1 C does not increase much in a single-decade but rather occurs in more decades than it does summer and winter seasons as well as between the different zones. The general eeff ct of the building situation on PET is in zone 1. In the summer season zone 2 displayed the same visualized in Table 2. eTh specific dynamics for each zone are dynamics as zone 1, but there are more days with extreme discussed in Section 5 of this paper. PET values. Still the range leads up to about 41.0 Cinthe Figure 3 shows the mean decadal distribution of PET time between 13:00 and 16:00, but now these values can be found throughout the months. eTh coldest time of the day values in Zone 1 during the year. eTh lowest values can be found in the time from the end of November to the beginning during July, used as an example, for summer is 4:00 with PET of March. The highest frequency of extremely low values dropping to values around 10.0 C. The daily course follows the classic pattern with the highest PET values occurring (PET<−30.0 C) is in the second decade of January with an occurrence frequency of 27.7%. From the end of November shortly after the sun reaches its zenith. The monthly course Frequency (%) 4 Advances in Meteorology PET (January) PET (July) 1.1 1.7 2.1 2.7 3.1 3.7 4.1 4.7 5.1 5.7 6.1 6.7 7.1 7.7 8.1 8.7 9.1 9.7 10.1 10.7 11.1 11.7 12.1 12.7 13.1 13.7 14.1 14.7 15.1 15.7 16.1 16.7 17.1 17.7 18.1 18.7 19.1 19.7 20.1 20.7 21.1 21.7 22.1 22.7 23.1 23.7 24.1 24.7 25.1 25.7 26.1 26.7 27.1 27.7 28.1 28.7 29.1 29.7 30.1 30.7 31.1 31.7 I II III IV V VI VII VIII I II III IV V VI VII VIII −40 −35 −30 −25 −20 −15 −10 −5 0 04 8 1318 23 29 35 41 45 50 ( C) ( C) I: 01:00 V: 13:00 II: 04:00 VI: 16:00 III: 07:00 VII: 19:00 V: 10:00 VIII: 22:00 Figure 4: Monthly (along 𝑦 -axis) and daily (along𝑥 -axis) dynamics of thermal comfort in winter (January) and summer (July) calculated with PET for Birobidzhan, zone 1. Table 2: Mean number of days per year with PET values within a specific class for the 3 zones as well as the climate station in Birobidzhan (2000–2010). PET ( C) WMO station Zone 1 Zone 2 Zone 3 <−30 21.0 12.1 14.9 12.9 <−20 68.3 59.4 63.0 60.5 <−10 117.2 113.0 114.6 113.5 <0 170.1 167.6 168.4 167.7 (15≤𝑋≤30 ) 65.4 72.3 70.1 72.2 (18≤𝑋≤27 ) 37.0 42.6 40.5 42.6 >29 19.5 9.9 13.9 10.7 >35 6.0 2.2 3.4 2.4 >41 1.0 0.3 0.6 0.4 does not show a very specific pattern but rather has an even is not visible, but there is a cold spot in the second decade distribution of values over the whole time with a few hotspots of January as it was observed before in the yearly course especially at 13:00. Winter in zone 2 displays a similar pattern of PET for zone 2. Since zone 3 is the one with the lowest as it does in zone 1, but as in summer the values are more building density, it has the highest occurrence frequencies extreme and there are more days with extremely low PET of extreme PET values. In Figure 6 the second decade of values. eTh time of the day they occur remains the same at January showsthat 76.1% of all values are below −20.0 C. 7:00. eTh warmest times of day are still the hours after the As a contrast in the first decade of July 17.8% of all PET suns zenith between 13:00 and 16:00. Then the maximum values lie above 29.1 C. With 26.1% of all values in the second ∘ ∘ ∘ values lie at about−5.0 C. At 22:00 PET starts to drop to decade of August situated in between 18.1 Cand 23.0 Cthe values below−30.0 C and reaches its minimum around 4:00 maximum frequency of comfortable PET values is the lowest with values close to−40.0 C. A significant monthly pattern in comparison to the other two zones. eTh least extreme Advances in Meteorology 5 Birobidzhan, 2000–2010 Birobidzhan, 2000–2010 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Decade Decade 4.1 to 8.0 4.1 to 8.0 41.1 to 45.0 41.1 to 45.0 0.1 to 4.0 0.1 to 4.0 35.1 to 41.0 35.1 to 41.0 −9.9 to 0.0 −9.9 to 0.0 29.1 to 35.0 29.1 to 35.0 −19.9 to −10.0 −19.9 to −10.0 23.1 to 29.0 23.1 to 29.0 −29.9 to −20.0 −29.9 to −20.0 18.1 to 23.0 18.1 to 23.0 <−30.0 <−30.0 13.1 to 18.0 13.1 to 18.0 ∘ ∘ PET ( C) PET ( C) 8.1 to 13.0 8.1 to 13.0 Figure 5: Mean frequency distribution of PET values in Biro- Figure 6: Mean frequency distribution of PET values in Biro- bidzhan, zone 2, during the year divided into 10-day intervals bidzhan, zone 3, during the year divided into 10-day intervals (decades) for the period 2000–2010. (decades) for the period 2000–2010. times marked the end of spring and the beginning of autumn. be expected since both of the indices are based on the human Still they are not the ones with the highest frequency of energy budget and are calculated using the same datasets comfortable values. (Table 3). Instead they have a tendency to cold stress with the However the adaptive nature of the UTCI index results majority of the values between comfort and strong cold stress. in less extreme and more moderate values since clothing and The pattern of maximum and minimum values remains the activity are adapted to the surrounding thermal conditions same in zone 3 since similar meteorological input data were [13]. Thispresentsthe opportunityofamore detailedand used. However the amplitude of those values reaches its diverse look at the thermal comfort. maximum. The hottest time of day was 13:00 with PET values Zone 1 is still the most sheltered and therefore the most even above 41.0 C. Around 4:00 PET reaches its minimum comfortable zone. eTh equivalent temperature calculated of about 8.0 Consomedays. UsuallyeventhenPET does with UTCI actually showed more comfortable conditions not drop to single digit values but stays in between 13.0 C than that with PET. eTh adaption of the clothing insulation in and 18.0 C. The hottest time of July seems to be the end of combination with the wide range of nonstressful values from ∘ ∘ the rfi st decade and the beginning of the second. eTh most 9.0 C to 23.0 C results in a wide range of stress-free UTCI comfortable times of the day are the hours from 22:00 to values from spring to autumn with a maximum of comfort 1:00. At that time most PET values lie in between 18.0 C in summer.Still thesummermonthsholdmorethan30% and 23.0 C. In January the coldest time of day in zone 3 was of moderate to very strong heat stress conditions and winter around 7:00 so about the same time as in zones 1 and 2. eTh still remains a time of cold stress varying from extreme to PET values drop below−40.0 C at that time, especially in moderate cold stress which makes winter the most stressful the ten days from the 8th of January to the 18th of January. time forthe humanbodyinterms of thethermal bioclimate. The warmest times of the day are still occur between 13:00 Following the UTCI scale Figure 7 represents the monthly and 16:00 making the afternoon and early evening the most and daily courses of thermal conditions for January and July pleasant times of the day to be outside on the city square. in zone 1. The warmest time of the day is the time between Still the PET values at that time of day result in extreme 13:00 and 16:00, while the lowest values occur between 4:00 cold stress and remain below 0.0 C. Even around 13:00 PET and7:00althoughcoldstressdoesnot occur. During the ∘ ∘ values are closer to−15.0 Cthantheyare to 0.0 C. A day with warmest time of the day, UTCI reached moderate heat stress PET values of single digits below 0.0 C could therefore be values on several occasions. But in general July can be con- considered a comparatively warm day. sidered a comfortable month. The monthly course showed threephasesofhighUTCIvalueswiththe rfi st beinginthe 4.2. Universal Thermal Climate Index. In general the UTCI beginning of thefirstdecade, thesecondatthe endofthe values follow thesamepattern as thePET values,which is to rfi st decade,and thethird in themiddleofthe thirddecade. Frequency (%) Frequency (%) 6 Advances in Meteorology UTCI (January) UTCI (July) 1.1 1.7 2.1 2.7 3.1 3.7 4.1 4.7 5.1 5.7 6.1 6.7 7.1 7.7 8.1 8.7 9.1 9.7 10.1 10.7 11.1 11.7 12.1 12.7 13.1 13.7 14.1 14.7 15.1 15.7 16.1 16.7 17.1 17.7 18.1 18.7 19.1 19.7 20.1 20.7 21.1 21.7 22.1 22.7 23.1 23.7 24.1 24.7 25.1 25.7 26.1 26.7 27.1 27.7 28.1 28.7 29.1 29.7 30.1 30.7 31.1 31.7 I II III IV V VI VII VIII I II III IV V VI VII VIII −27 26 32 46 −40 −27 −13 0 9 26 32 38 46 −40 −13 0 9 38 ∘ ∘ ( C) ( C) I: 01:00 V: 13:00 II: 04:00 VI: 16:00 III: 07:00 VII: 19:00 V: 10:00 VIII: 22:00 Figure 7: Monthly and daily dynamics of thermal comfort in winter (January) and summer (July) calculated with UTCI for Birobidzhan, zone 1. Table 3: Mean number of days per year with UTCI values within a specific class for the 3 zones as well as for the climate station in Birobidzhan (2000–2010). UTCI ( C) WMO station Zone 1 Zone 2 Zone 3 <−30 21.0 9.0 10.5 9.4 <−20 68.3 54.8 58.6 55.8 <−10 117.2 108.7 109.6 109.1 <0 170.1 156.1 157.0 156.1 (15≤𝑋≤30 ) 65.4 91.7 90.6 92.5 (18≤𝑋≤27 ) 37.0 57.6 55.8 57.8 >29 19.5 10.1 13.5 10.9 >35 6.0 1.1 1.3 1.0 >41 1.0 0.0 0.0 0.0 Winter (exemple in this case January) in zone 1 presents itself The thermal dynamics in zone 2 were observed to be to be much less comfortable than summer. The daily course similartothose in zone 1but with about5%moreheatstress remains the same with the warmest time being between 13:00 in the summer months. Comfortable values occurred from and 16:00 and the coldest around 7:00. In contrast to summer the midst of March until the end of October. The month there were no periods without thermal stress. Throughout the with the most heat stress is July with its second decade being whole month the body suffers from moderate to very strong the one with almost 30% of heat stress values. Winter still ∘ ∘ cold stress. eTh highest values lie between 0.0 Cand−13.0 C presented a time of constant cold stress varying in its intensity whilethe coldestare closeto−40.0 C. The coldest time of from extreme to moderate and with the second decade of January is in the middle of the second decade from the 12th January as the coldest period of the year. With about 42.1% until the 17th of January, while the highest values occurred at of all values below−27.0 C this decade showed the highest 13:00between the23rdand the27th(Figure 7). frequency of very strong cold stress values. The second decade Advances in Meteorology 7 of December shows 92.4% of all values being below−13.0 C 5. Discussion resulting in at least strong cold stress conditions. As in zone The results of the calculations and simulations as well as 1, the summer months are the ones that present the most the measurements of the meteorological parameters show comfortable outdoor conditions but also the most heat stress. a clear picture of the thermal conditions in terms of the The thermal dynamics of zone 2 for July were used as an human bioclimate in the JAR. In general it can be concluded example for the thermal dynamics in summer. The time of that the JAR has a very big gradient of thermal conditions the highest thermal stress is the time between 13:00 and 16:00 throughout the year not only in the direct thermal parameters with UTCI values above 32.0 C. Also around 10:00 and 19:00 such as 𝑇 and 𝑇 [23, 24]but also in thesecondary 𝑎 mrt the human body can experience slight heat stress on some parameters such as VP and RH. The wind is not so much days.Thecoldesttimeofthe dayisthe time between4:00 boundtoanannualcycleandthereforeinufl encesthethermal and 7:00. During this time the values drop almost to the conditions in a similar pattern throughout the year. eTh rangeofcoldstress. In thecourseofJulythere arethree thermal comfort has been determined with PET and UTCI hot spots. eTh rfi st two occurr in the rfi st decade while the and they exhibited similar dynamics in the annual course. last hotspot lies in the middle of the third decade. Winter in However they indicate a great difference in their values. zone 2presentsitselfwithconstantcoldstress. In Januarythe While PET shows a lot of very extreme values and only highest values for UTCI occur in the aer ft noon between 13:00 little thermal comfort throughout the year, UTCI shows and 16:00. During this time UTCI lies between 0.0 Cand a lot of nonstressful conditions especially in the summer −13.0 C causing moderate to strong cold stress. In the course months. This difference was to be expected since PET has of the night the values start to drop to reach their minimum been calculated with the same base parameters for the entire year whileUTCIisanadaptiveindex whichresults in a values below−27.0 C around 4:00 to 7:00. At this time the less extreme setting. Since it can be assumed that no one human body experiences very strong cold stress. eTh coldest is wearing a light business suit (clo = 0.9) in winter in the time of January is between the 10th and the 16th, while the, Russian Far East the adaption of this parameter seems to least cold days are closer to the end of the month. result in a more realistic assessment. Still the winter season Sinceithas themostopenspace,zone3presents itself holds a lot of cold stress and in contrast to summer has no with the least comfortable thermal conditions. eTh summer comfortable values at all. months show the highest frequency of heat stress values, In case of cold stress in winter it does not matter whether while, in winter the frequency of strong and very strong cold it is calculated with PET or UTCI. In both cases winter is stress is increased. Still summer shows the most comfortable not comfortable. eTh only difference is the range of values. settingwithupto70% of allvaluesbeing within onedecade ∘ ∘ While calculated with PET there are more extreme cold stress in the class of 9.0 Cto27.0 C. The highest heat stress occurs in values, UTCI results strong rather in than extreme cold stress. summer around the same time in the middle of July and the The thermal conditions in summer, however, differ greatly beginning of August. In winter the human body experiences depending on the applied index. While PET depicts a rather exclusively cold stress with 43.9% of all values being between harsh picture of the thermal conditions in summer, UTCI ∘ ∘ −27.0 Cand 39.9 C; theseconddecadeofJanuary shows shows a lot of nonstressful values. This difference is the result the most extreme conditions; while the second decade of of the different procedures of calculating the indices as well December can be considered the coldest in general with as the different index classes applied to the definitions of 92.6% of all values below−13.0 C. Times of no thermal stress thermal comfort. While PET provides only a narrow window occurfromthe midstofMarch to themidst of November ∘ ∘ of thermal comfort (18.0 C to 23.0 C), UTCI considers a ∘ ∘ even though they are very rare at those times. In spring and much wider range (9.0 Cto27.0 C) comfortable or at least autumn the range of UTCI covers everything from thermal notstressful forthe humanbody[2, 3, 5]. The result of this stress to strong cold stress and in rare cases even heat stress. calculationisaverycomfortablethermalsituationinsummer The warmest time of day in zone 3 in summer is still the with about 30% of the values resulting in slight to strong heat time from 13:00 to 16:00, but the occurrence of UTCI values stress and the remaining 70% being comfortable. PET shows outside the range of no thermal stress around 10:00 and 19:00 most of the variability in its classed values during summer. is increased. Also the three hotspots in the monthly course It shows little thermal comfort but wide rather a range from that could be observed in zones 1 and 2 are not as prominent extreme heat stress to moderate cold stress. How wide the because they are closer together and cover more days. From range of PET or UTCI is and how narrow the window of 22:00 to 7:00 the values are the lowest with a minimum comfortable values is depend on the surrounding structures around 4:00. Still they do not present any cold stress since as well. eTh higher the building density is in an area and the they stay quite far above 9 C. In zone 3 the winter season more vegetation there is, the more comfortable are outdoor presents itself with the same dynamics as those in the other conditions are. In summer this is the result of shading effects zones. It shows its coldest period in January from the 8th to and the resulting reduction of𝑇 and in winter the high mrt the 17th in the monthly course and in general from 4:00 to urban density results in a reduction of heat loss due to long 7:00 in thedaily course.Thewarmest time of theday is the wave radiation. As a result the outdoor areas of the residential time between 13:00 and 16:00 but even then the UTCI values area (zone 1) can be considered the most comfortable one do not exceed the range of cold stress. In the coldest hours throughout the year while the city square (zone 3) is the ∘ ∘ UTCI values drop far below−27.0 Cand getclose to−40.0 C. least comfortable due to its high exposure to the elements. 8 Advances in Meteorology 27.8. W E Figure 8: Residential area in Birobidzhan (zone 1). 14 12 The results also show the influence of all the parameters that are part of the calculations of PET. eTh higher the relative humidity is the more extreme is the thermal impact of𝑇 and 𝑇 is.Thewindalwayshas acooling eeff ct(except when mrt theair temperatureishigherthanthe surfacetemperatures 1999–2010 RayMan Pro 2.1 of humans), but its role in this region is very important since Figure 9: Polar diagram for the sky view factor (zone 1) in the occurrence of high wind velocities is rather rare. The main Birobidzhan. impact on the human thermal bioclimate in this region lies with the air temperature and the mean radiant temperature. Therefore the best possibilities for human interference lie situation [22, 27, 28]. In summer being located on a wide open in the reduction of irradiation. Using wind channelling to space with close to no vegetation Freiburg and Birobidzhan reduce𝑇 in summer seems premature since the same action present similar heat stress conditions [27–29]. This difference would lead to even more extreme cold stress during winter. in climate situations shows a longitudinal dependency of Another way to reduce thermal stress in urban areas of the the regional climate that is not at all linked to the classic JAR would be the increase of vegetation. climate zones which depend on the latitude but rather to its According to a paper on thermal strain due to a change proximity to pressure systems and its location in the path of in locations within the Russian Far East [25]the dieff rence meteorological phenomena such as a monsoon or El Nino ˜ . in thermal comfort during the winter months is negligible due to an overall extreme cold stress which makes the results of this study applicable for the whole region in winter. In 6. Conclusions summer, however, the thermal conditions within the Far East district vary greatly making more localized investigations After analysing the results of measurements and calculations necessary for a thorough assessment of preferable urban it canbeconcluded that theJAR is aclimaticextreme outdoor structures in summer. region with a massive gradient of thermal comfort conditions. On the topic of the change of extreme climate regions due However there is a variety of possibilities for adaption to this to global climatechangeitcan be assumedthatthe overall phenomenon. eTh rfi st and most simple one is of course to frequency of extremely cold days is reduced in favour of an follow the saying “there is no bad weather, just a bad choice increase in heat stress days which would lead to an overall of clothing” and to choose the right clothing for the meteoro- increase in thermal comfort for regions of high cold stress logical situation. This action is taken into consideration in the [26]. In a region of high gradients of thermal comfort like the application of UTCI and it shows a significant moderation of JAR, however, the result would rather be a shift in types of the otherwise unpleasant conditions in late spring, summer, thermaldiscomfortthananincreaseofcomfortable days. and early autumn. In the cold season, however, even clothing In comparison, Freiburg in south western Germany does not help much. It moderates the extreme cold stress but which lies at the same latitude (48 N) but at a very different it does not suffice to relieve the human body entirely. To gain ∘ ∘ longitude (9 E) than Birobidzhan (127 E) has a very different a maximum of cold stress reduction it is therefore necessary climate setting. In Birobidzhan the annual climate variation to make sure that one stays outside as little as possible is much higher and is based on the summer monsoon or the and—if one does stay outside—to choose the location wisely. Siberian high pressure area. In Freiburg climate is much more According to the results of this study the wisest decision dependent on the pressure systems in the northern Atlantic wouldbetoavoid wide open spaces andtoremaininareas of especially the Northern Atlantic Oscillation (NAO) and the high urban density. Another important factor is of course the interaction with the alpine climate system. As a result the time of the day. While it is advisable to choose the morning climate in Freiburg is much less extreme. In particular in and late afternoon hours of the day and to avoid noon and winter the thermal parameters show a much more moderate early aeft rnoon for outside chores in summer, the opposite Advances in Meteorology 9 Figure 12: Square in Birobidzhan (zone 3). Figure 10: Main street in Birobidzhan (zone 2). 27.8. 60 27.8. 60 80 7 19 W E W E 9 17 10 16 14 12 14 12 13 1999–2010 RayMan Pro 2.1 1999–2010 RayMan Pro 2.1 Figure 13: Polar diagram for the sky view factor (zone 3) in Figure 11: Polar diagram for the sky view factor (zone 2) in Birobidzhan. Birobidzhan. References can be said about winter. eTh least thermal stress in winter occurs for all zones in the time between 13:00 and 16:00 which [1] P. Hop ¨ pe, Die Energiebilanz des Menschen [M.S. thesis],Wis- makes it the most pleasant time to be outside. Staying outside senschaftliche Mitteilungen des Meteorologischen Instituts Universitat ¨ Munc ¨ hen, 1984. at night especially in the hours of early morning around 4:00 [2] P. Hop ¨ pe, “The physiological equivalent temperature—a uni- wouldbeill advisedsince thoseare thehours of thestrongest versal index for the biometeorological assessment of the ther- cold stress. mal environment,” International Journal of Biometeorology,vol. For planning purposes in this region or regions affected 43,no. 2, pp.71–75,1999. by a similar climate it can be concluded that a high urban [3] A. Matzarakis, H. Mayer, and M. G. Iziomon, “Applications of a density combined with a fair amount of inner city vegetation universal thermal index: physiological equivalent temperature,” would be a preferable setting to reduce thermal stress. This International Journal of Biometeorology,vol.43, no.2,pp. 76–84, measure would be especially preferable for locations that are equally important throughout the year such as public [4] D. Fiala, G. Havenith, P. Brode, B. Kampmann, and G. Jen- transport stops, train stations, or other points of public dritzky, “UTCI-Fiala multi-node model of human heat transfer interest. and temperature regulation,” International Journal of Biometeo- rology,vol.56, no.3,pp. 429–441, 2012. [5] G. Jendritzky, R. de Dear, and G. Havenith, “UTCI-Why another Appendix thermal index?” International Journal of Biometeorology,vol.56, See Figures 8, 9, 10, 11, 12,and 13. no.3,pp. 421–428, 2012. 10 Advances in Meteorology [6] H. Mayer and P. Hop ¨ pe, “Thermal comfort of man in different [23] P. O. Fanger, Thermal Comfort , McGraw-Hill, New York, NY, urban environments,” Theoretical and Applied Climatology ,vol. USA, 1972. 38,no. 1, pp.43–49,1987. [24] VDI, Environmental Meteorology, Methods for the Human [7] P. R. Hop ¨ pe, “Heat balance modelling,” Experientia,vol.49, no. BiometeorologicalEvaluationofClimate andAir Qualityfor the 9, pp. 741–746, 1993. Urban and Regional Planning at Regional Level. Part I. Climate, [8] P. Hop ¨ pe, “Die War ¨ mebilanzmodelle MEMI und IMEM zur VDI/DIN—HandbuchReinhaltung der Luft, D uss ¨ eldorf, Ger- many, 1998. Bewertung der thermischen Beanspruchung am Arbeitsplatz,” Verhandlungen der Deutschen Gesellschaft f ur ¨ Arbeitsmedizin [25] C. R. de Freitas and E. A. de Grigorieva, “The acclimatization und Umweltmedizin,vol.34, pp.153–158,1994. thermal strain index (ATSI): a preliminary study of the method- [9] A. Matzarakis, F. Rutz, and H. Mayer, “Modelling radiation ology applied to climatic conditions of the Russian Far East,” fluxes in simple and complex environments—application of the International Journal of Biometeorology,vol.53, no.4,pp. 307– RayMan model,” International Journal of Biometeorology,vol.51, 315, 2009. no. 4, pp. 323–334, 2007. [26] D.H.W.Li,K.K.W.Wan,L.Yang,andJ.C.Lam,“Heatandcold [10] A. Matzarakis, F. Rutz, and H. Mayer, “Modelling radiation stresses in different climate zones across China: a comparison u fl xes in simple and complex environments: basics of the between the 20th and 21st centuries,” Building and Environment, RayMan model,” International Journal of Biometeorology,vol. vol. 46, no. 8, pp. 1649–1656, 2011. 54,no. 2, pp.131–139,2010. [27] D. Frohlic ¨ h and A. Matzarakis, “Heat stress and city planning— [11] R.-L. Hwang, T.-P. Lin, and A. Matzarakis, “Seasonal eeff cts of the example of the “Platz der alten synagoge” in Freiburg in urban street shading on long-term outdoor thermal comfort,” Breisgau,” Gefahrstoffe Reinhaltung der Luft , vol. 71, no. 7-8, pp. Building and Environment,vol.46, no.4,pp. 863–870, 2011. 333–338, 2011. [12] T.-P. Lin, A. Matzarakis, and R.-L. Hwang, “Shading eeff ct on [28] J. Herrmann and A. Matzarakis, “Mean radiant temperature in long-term outdoor thermal comfort,” Building and Environ- idealised urban canyons-examples from Freiburg, Germany,” ment,vol.45, no.1,pp. 213–221, 2010. International Journal of Biometeorology,vol.56, no.1,pp. 199– [13] K. Blazejczyk, Y. Epstein, G. Jendritzky, H. Staiger, and B. 203, 2012. Tinz, “Comparison of UTCI to selected thermal indices,” [29] A. Matzarakis and C. Endler, “Climate change and thermal International Journal of Biometeorology,vol.56, no.3,pp. 515– bioclimate in cities: impacts and options for adaptation in 535, 2012. Freiburg, Germany,” International Journal of Biometeorology, [14] A. Psikuta, D. Fiala, G. Laschewski et al., “Validation of the Fiala vol. 54, no. 4, pp. 479–483, 2010. multi-node thermophysiological model for UTCI application,” International Journal of Biometeorology,vol.56, no.3,pp. 443– 460, 2012. [15] D.Fiala,K.J.Lomas,and M. Stohrer, “A computer modelof human thermoregulation for a wide range of environmental conditions: the passive system,” Journal of Applied Physiology, vol. 87,no. 5, pp.1957–1972,1999. [16] D. Fiala, K. J. Lomas, and M. Stohrer, “Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions,” International Journal of Biometeorology,vol.45, no.3,pp. 143–159, 2001. [17] D. Fiala, K. J. Lomas, and M. Stohrer, “First principles modeling of thermal sensation responses in steady-state and transient conditions,” in Technical and Symposium Papers Presented at the 2003 Winter Meeting of the ASHRAE, pp. 179–186, January 2003. [18] E. Grigorieva and V. Tunegolovets, “Change of climate on the southofthe RussianFar East in thesecondhalfofthe 20th century,” Annalen Der Meteorologie,vol.41, pp.209–212,2005. [19] E. Grigorieva and D. Fetisov, “Estimation of climatic resources for summer sport recreation,” in The Jewish Autonomous Region of Russia, Developments in Tourism Climatology,pp.87–92,2007. [20] E. Grigorieva, “Spatial-temporal dynamics of climate thermal resources for the southern part of the Russian Far East,” in Pro- ceedings of the 18th International Congress of Biometeorology,p. 121, International Society of Biometeorology, Tokyo, September [21] E. Grigorieva, A. Matzarakis, and C. 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Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example of Birobidzhan, Russian Far East

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Copyright © 2013 Jan Paul Bauche et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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10.1155/2013/749270
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Hindawi Publishing Corporation Advances in Meteorology Volume 2013, Article ID 749270, 10 pages http://dx.doi.org/10.1155/2013/749270 Research Article Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example of Birobidzhan, Russian Far East 1 2 1 Jan Paul Bauche, Elena A. Grigorieva, and Andreas Matzarakis Chair of Meteorology and Climatology, Albert Ludwigs University Freiburg, Werthmannstraße 10, 79085 Freiburg, Germany Institute for Complex Analysis of Regional Problems, Far Eastern Branch, Russian Academy of Sciences, Birobidzhan 679016, Russia Correspondence should be addressed to Jan Paul Bauche; paul@mbauche.de Received 4 June 2013; Revised 27 August 2013; Accepted 23 September 2013 Academic Editor: Marialena Nikolopoulou Copyright © 2013 Jan Paul Bauche et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The study shows the eeff ct of urban structures on human thermal comfort indices in the extreme climate region of the Russian Far East, with an annual temperature range of75 C. The study examines different urban zones in Birobidzhan, the capital city of the Jewish Autonomous Region (JAR). The climate of this region can be characterized as continental monsoon climate. eTh difference of thermal values for three zones with different vegetation and build-up density shows the influence of urban planning on the local microclimate. The moderating effect of dense build-up and inner city vegetation on extreme thermal conditions becomes clear when comparing all zones. Through the analysis of daily and monthly timelines it was possible to determine preferable times of the day for inner city outdoor activities. From the results derived from PET with a total of 170 days per year with PET values below 0 C Birobidzhan can be considered a region of extreme cold stress. This means that an adaptation based solely on behaviour and clothing is not sufficient, but an adaptation of the urban surroundings and therefore the identification and choice of preferable urban structures is necessary. 1. Introduction extremely suitable for the purpose of analysing the impact of urbanstructuresonthe humanthermal comfortassuming Since the last decades of the 20th century and due to the an intensification of extreme meteorological conditions in challenges of climate change, climatological and meteorolog- presently moderate climate areas, due to the global climate ical parameters have been in the focus of urban planning. change. During the last 20 years the interest in the human Most of those studies assess the standard meteorological thermal bioclimate has been rising due to great awareness parameters associated with human thermal comfort such of the inu fl ence of climate on our lives which is strongly as air temperature, global radiation, wind velocity, relative connected to the public debate about climate change and its humidity, or precipitation. However, if they are assessed just influence on everyday life. As a result of this development by themselves, the results are taken out of the human context regions that are already under the inu fl ence of harsh climates and lose their original purpose. To put them into context, the are very interesting for analysis of climate change results. application of complex and differentiated human bioclimate eTh indices used for this study are the physiologically indices is needed. For the purpose of this study two of these equivalent temperature (PET) based on the Munich Energy- indices haven been applied to the meteorological conditions balance Model for Individuals (MEMI) [1–3], displayed in and the urban structures of Birobidzhan, the capital city of degrees Celsius ( C) which makes it easy to comprehend and the Jewish Autonomous Region (JAR), at the Russian Far easy to be compared to other indices or measurement, and the East. In the course of a year this region experiences all universal thermal climate index (UTCI), also displayed in C, facets of extreme meteorological conditions from arid cold which is based on a multinode human energy balance model to humid warm (Figure 1). This makes the region of the JAR for a more adaptive approach to extreme climate conditions 2 Advances in Meteorology 30 180 0 Sources: Esri, DeLorme, NAVTEQ, USGS, Intermap, iPC, NRCAN, Esri Japan,METI, Esri 1 : 100.000.000 China (Hong Kong), Esri −10 −20 −30 −40 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (km) 0 30 60 120 180 240 T , Min 1 : 5.000.000 Sources: Esri, DeLorme, NAVTEQ, USGS, Intermap, iPC, NRCAN, Esri Japan, T , Max METI, Esri China (Hong Kong), Esri (a Th iland), TomTom, 2013 Figure 1: Climate diagram for the Birobidzhan area (data source: Figure 2: Regional and local position of Birobidzhan. http://worldweather.wmo.int/). Table 1: Selected locations (zones) and their respective properties. [4, 5]. A selection of studies conducted in the JAR, and Zone Type Build-up Vegetation such concerning the topic of the human biometeorology, is displayed to show what has been done so far. Studies on 1 Residential Dense High this topic have been published since the late eighties [1, 6]. 2 Street Medium Light They show the development and application of PET based 3Square Light None on the human energy balance model MEMI [1–3, 7, 8]and the RayMan model [9, 10] and the eeff ct of shading on outdoor comfort [11, 12]aswellasthe developmentofUTCI 3. Methods [5, 13, 14] and the underlying multinode model [4, 15–17]. In the following years, papers concerning the bioclimate of the For the assessment of the human thermal bioclimate several JAR, focusing on the efficiency of agricultural crop growing indices have been developed over the last 50 years. Two ther- and outdoor recreation and tourism, were published [18– mal indices were used for this study, namely, the physiologi- 22]. These works are designed to nd fi preferable outdoor cally equivalent temperature (PET) and the universal thermal activities or to quantify the inu fl ence of the regional climate climate index (UTCI) [4, 15–17], both of which use the unit on crop seasonsand areusually basedondaily andmonthly degrees Celsius and are based on models of human ther- climate data. This study aims to give an actual and accurate mal balance. eTh meteorological data from the Birobidzhan assessment of the human thermal bioclimate and to n fi d WMO station (WMO index 31713) has been used as input for preferable city structures or at least preferable inner city the calculation of the thermal indices, specicall fi y the data locations at any given time of day in the city of Birobidzhan for air temperature, wind velocity, wind direction, relative using a high temporal resolution of meteorological data. humidity, and cloud cover as a proxy value for the global radiation. These parameters have been recorded at the climate station in a three-hour interval, resulting in eight measuring 2. Area of Investigation points per day, for the 11-year period from 2000 to 2010. Birobidzhan is located close to the Chinese northern border Using this data and the RayMan model the thermal ∘ ∘ at 48 Nand 132 E(Figure 2)withamean altitude of 76ma.sl. indices can be calculated [9, 10]. Additionally the obstacle and is inhabited about 75,000 people on an area of 169 km . parameters at three different locations within the city were Even though the latitude coincides with a moderate climate put into the model to determine their influence on the by the climate in the Jewish Autonomous Region (JAR), human thermal bioclimate. All three locations are highly of which Birobidzhan is the capital, is far from moderate. frequented by the local population, but they are very different Its continental exposition leads to cold winters and warm in terms of their structural specifications. Information for all summers. This eeff ct is intensified by the influence of the three locations is summarised in Table 1.Theterms used to summer monsoon and its close proximity to the Siberian describe “Build-up” and “Vegetation” are relative terms meant high pressure efi ld resulting in an annual variation in air to compare the zones with each other. Pictures of the selected temperature of up to 75 C in the course of six months in areasaswellasfisheyepicturescan be foundinthe appendix. extreme cases. Due to this variation the annual course of the The meteorological data were made freely available via meteorological factors in this region shows great variability. http://www.ogimet.com/ andweredownloadedfor the From a mean maximum air temperature of about 26 CinJuly period from 2000 to 2010 in 3-hour intervals (01:00, 04:00, to−29 C in January and a monthly precipitation of 154 mm in 07:00, 10:00, 13:00, 16:00, 19:00, and 22:00 local time). eTh August to 5 mm in February all facets of an extreme climate availability of these meteorological measurements at eight can be experienced. points of time per day ensures a good temporal resolution of T ( C) P (mm) Advances in Meteorology 3 Birobidzhan, 2000–2010 until the midst of February PET values were not above 0.0 C as it is a period of constant frost. eTh highest PET values occur from the midst of June to the end of August. Values ∘ ∘ between 29.1 C and 41.0 C can be considered a fairly common phenomenon (about 14%). With occurrence frequencies of ∘ ∘ about 1% values between 41.1 Cand 45.0 Coccur rather rarely. With about 30.9% the first decade of August shows the highest occurrence frequency of comfortable PET values ∘ ∘ between 18.1 C and 23.0 C. Spring and autumn generally consistofPET values in therange of slight heat stress to extreme cold stress and require the most flexibility in terms of thermal adaption. In the summer months of July, June, and August PET does not drop to values below 0.0 C. Figure 4 shows the 2-dimensional daily and monthly Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec courses of PET values in January and July, as an example Decade for winter and summer, respectively. The 𝑦 -axis shows the 4.1 to 8.0 41.1 to 45.0 days of July and the𝑥 -axis shows the time steps according to 0.1 to 4.0 35.1 to 41.0 the legend. The highest PET values can be expected towards −9.9 to 0.0 29.1 to 35.0 theend of July around the26thday andingeneral in the −19.9 to −10.0 23.1 to 29.0 time between 13:00 and 16:00. During this time PET reaches −29.9 to −20.0 18.1 to 23.0 ∘ ∘ values up to the range of 35.0 C to 41.0 C. The coolest times <−30.0 13.1 to 18.0 of the day are the ones in the early morning between 4:00 8.1 to 13.0 PET ( C) ∘ ∘ and 7:00. Here PET values range between 13.0 Cand 18.0 C. Figure 3: Mean frequency distribution of PET values in Biro- In winter (January) PET drops to values below−30.0 Cand bidzhan, zone 1, during the year divided into 10-day intervals in extreme cases even below−40.0 C creating extreme cold (decades) for the period 2000–2010. stress in terms of the human bioclimate. These extremely low values can be expected in the midst of January (exemplary for winter) in the early morning hours between 4:00 and 7:00. the data. eTh data were initially available in SYNOP and In general the highest PET values in winter do not reach the hadtobedecoded to standard meteorological units. This 0.0 C mark but rather stay considerably lower. They can be was done using Microsoft Excel. All of the calculations and expected in the time between 13:00 and 16:00. From 16:00 on, simulations in this study are based on the meteorological data PET drops until it reaches its lowest value in the time around obtained from this synoptic station and were modified only 7:00. During January PET does not vary much, but there is an by the surrounding structures via obstacle files in RayMan accumulation of very low values in the time from the 10th to which were based on maps of the city and local observation of the 17th of January. the buildings. eTh general assumption for the transfer of the Zone 2 is less sheltered from solar radiation than zone data is that air temperature and air humidity remain the same 1 and therefore shows a tendency to have more extreme for the city and the rural station, and only wind speed, which PET values. Since the climate data has been recorded at the is changed according to roughness, and radiation ux fl es, same station the yearly change is the same as in zone 1, which can be adjusted with the RayMan model, modify the but its amplitude is different. With 29.4% the frequency of indices. PET values below−30.0 C is about 2% higher than that in zone 1 (Figure 5). Still the winter months from the end of November until the end of February are consistenty below 4. Results 0.0 C, but the PET values are less extreme. In the summer 4.1. Physiologically Equivalent Temperature. The following months the occurrence frequency of comfortable PET values ∘ ∘ section provides the results of PET in the context of the between 18.1 C and 23.0 Cdrops to 29.8%, that is,1%lower in comparison to zone 1. The extremely high values that result in different building situations. It also includes its daily course for selected months in summer and winter. eTh overall results moderate to extreme heat stress increase in comparison. eTh showed a great range of PET values being being between frequency of values above 35.1 C does not increase much in a single-decade but rather occurs in more decades than it does summer and winter seasons as well as between the different zones. The general eeff ct of the building situation on PET is in zone 1. In the summer season zone 2 displayed the same visualized in Table 2. eTh specific dynamics for each zone are dynamics as zone 1, but there are more days with extreme discussed in Section 5 of this paper. PET values. Still the range leads up to about 41.0 Cinthe Figure 3 shows the mean decadal distribution of PET time between 13:00 and 16:00, but now these values can be found throughout the months. eTh coldest time of the day values in Zone 1 during the year. eTh lowest values can be found in the time from the end of November to the beginning during July, used as an example, for summer is 4:00 with PET of March. The highest frequency of extremely low values dropping to values around 10.0 C. The daily course follows the classic pattern with the highest PET values occurring (PET<−30.0 C) is in the second decade of January with an occurrence frequency of 27.7%. From the end of November shortly after the sun reaches its zenith. The monthly course Frequency (%) 4 Advances in Meteorology PET (January) PET (July) 1.1 1.7 2.1 2.7 3.1 3.7 4.1 4.7 5.1 5.7 6.1 6.7 7.1 7.7 8.1 8.7 9.1 9.7 10.1 10.7 11.1 11.7 12.1 12.7 13.1 13.7 14.1 14.7 15.1 15.7 16.1 16.7 17.1 17.7 18.1 18.7 19.1 19.7 20.1 20.7 21.1 21.7 22.1 22.7 23.1 23.7 24.1 24.7 25.1 25.7 26.1 26.7 27.1 27.7 28.1 28.7 29.1 29.7 30.1 30.7 31.1 31.7 I II III IV V VI VII VIII I II III IV V VI VII VIII −40 −35 −30 −25 −20 −15 −10 −5 0 04 8 1318 23 29 35 41 45 50 ( C) ( C) I: 01:00 V: 13:00 II: 04:00 VI: 16:00 III: 07:00 VII: 19:00 V: 10:00 VIII: 22:00 Figure 4: Monthly (along 𝑦 -axis) and daily (along𝑥 -axis) dynamics of thermal comfort in winter (January) and summer (July) calculated with PET for Birobidzhan, zone 1. Table 2: Mean number of days per year with PET values within a specific class for the 3 zones as well as the climate station in Birobidzhan (2000–2010). PET ( C) WMO station Zone 1 Zone 2 Zone 3 <−30 21.0 12.1 14.9 12.9 <−20 68.3 59.4 63.0 60.5 <−10 117.2 113.0 114.6 113.5 <0 170.1 167.6 168.4 167.7 (15≤𝑋≤30 ) 65.4 72.3 70.1 72.2 (18≤𝑋≤27 ) 37.0 42.6 40.5 42.6 >29 19.5 9.9 13.9 10.7 >35 6.0 2.2 3.4 2.4 >41 1.0 0.3 0.6 0.4 does not show a very specific pattern but rather has an even is not visible, but there is a cold spot in the second decade distribution of values over the whole time with a few hotspots of January as it was observed before in the yearly course especially at 13:00. Winter in zone 2 displays a similar pattern of PET for zone 2. Since zone 3 is the one with the lowest as it does in zone 1, but as in summer the values are more building density, it has the highest occurrence frequencies extreme and there are more days with extremely low PET of extreme PET values. In Figure 6 the second decade of values. eTh time of the day they occur remains the same at January showsthat 76.1% of all values are below −20.0 C. 7:00. eTh warmest times of day are still the hours after the As a contrast in the first decade of July 17.8% of all PET suns zenith between 13:00 and 16:00. Then the maximum values lie above 29.1 C. With 26.1% of all values in the second ∘ ∘ ∘ values lie at about−5.0 C. At 22:00 PET starts to drop to decade of August situated in between 18.1 Cand 23.0 Cthe values below−30.0 C and reaches its minimum around 4:00 maximum frequency of comfortable PET values is the lowest with values close to−40.0 C. A significant monthly pattern in comparison to the other two zones. eTh least extreme Advances in Meteorology 5 Birobidzhan, 2000–2010 Birobidzhan, 2000–2010 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Decade Decade 4.1 to 8.0 4.1 to 8.0 41.1 to 45.0 41.1 to 45.0 0.1 to 4.0 0.1 to 4.0 35.1 to 41.0 35.1 to 41.0 −9.9 to 0.0 −9.9 to 0.0 29.1 to 35.0 29.1 to 35.0 −19.9 to −10.0 −19.9 to −10.0 23.1 to 29.0 23.1 to 29.0 −29.9 to −20.0 −29.9 to −20.0 18.1 to 23.0 18.1 to 23.0 <−30.0 <−30.0 13.1 to 18.0 13.1 to 18.0 ∘ ∘ PET ( C) PET ( C) 8.1 to 13.0 8.1 to 13.0 Figure 5: Mean frequency distribution of PET values in Biro- Figure 6: Mean frequency distribution of PET values in Biro- bidzhan, zone 2, during the year divided into 10-day intervals bidzhan, zone 3, during the year divided into 10-day intervals (decades) for the period 2000–2010. (decades) for the period 2000–2010. times marked the end of spring and the beginning of autumn. be expected since both of the indices are based on the human Still they are not the ones with the highest frequency of energy budget and are calculated using the same datasets comfortable values. (Table 3). Instead they have a tendency to cold stress with the However the adaptive nature of the UTCI index results majority of the values between comfort and strong cold stress. in less extreme and more moderate values since clothing and The pattern of maximum and minimum values remains the activity are adapted to the surrounding thermal conditions same in zone 3 since similar meteorological input data were [13]. Thispresentsthe opportunityofamore detailedand used. However the amplitude of those values reaches its diverse look at the thermal comfort. maximum. The hottest time of day was 13:00 with PET values Zone 1 is still the most sheltered and therefore the most even above 41.0 C. Around 4:00 PET reaches its minimum comfortable zone. eTh equivalent temperature calculated of about 8.0 Consomedays. UsuallyeventhenPET does with UTCI actually showed more comfortable conditions not drop to single digit values but stays in between 13.0 C than that with PET. eTh adaption of the clothing insulation in and 18.0 C. The hottest time of July seems to be the end of combination with the wide range of nonstressful values from ∘ ∘ the rfi st decade and the beginning of the second. eTh most 9.0 C to 23.0 C results in a wide range of stress-free UTCI comfortable times of the day are the hours from 22:00 to values from spring to autumn with a maximum of comfort 1:00. At that time most PET values lie in between 18.0 C in summer.Still thesummermonthsholdmorethan30% and 23.0 C. In January the coldest time of day in zone 3 was of moderate to very strong heat stress conditions and winter around 7:00 so about the same time as in zones 1 and 2. eTh still remains a time of cold stress varying from extreme to PET values drop below−40.0 C at that time, especially in moderate cold stress which makes winter the most stressful the ten days from the 8th of January to the 18th of January. time forthe humanbodyinterms of thethermal bioclimate. The warmest times of the day are still occur between 13:00 Following the UTCI scale Figure 7 represents the monthly and 16:00 making the afternoon and early evening the most and daily courses of thermal conditions for January and July pleasant times of the day to be outside on the city square. in zone 1. The warmest time of the day is the time between Still the PET values at that time of day result in extreme 13:00 and 16:00, while the lowest values occur between 4:00 cold stress and remain below 0.0 C. Even around 13:00 PET and7:00althoughcoldstressdoesnot occur. During the ∘ ∘ values are closer to−15.0 Cthantheyare to 0.0 C. A day with warmest time of the day, UTCI reached moderate heat stress PET values of single digits below 0.0 C could therefore be values on several occasions. But in general July can be con- considered a comparatively warm day. sidered a comfortable month. The monthly course showed threephasesofhighUTCIvalueswiththe rfi st beinginthe 4.2. Universal Thermal Climate Index. In general the UTCI beginning of thefirstdecade, thesecondatthe endofthe values follow thesamepattern as thePET values,which is to rfi st decade,and thethird in themiddleofthe thirddecade. Frequency (%) Frequency (%) 6 Advances in Meteorology UTCI (January) UTCI (July) 1.1 1.7 2.1 2.7 3.1 3.7 4.1 4.7 5.1 5.7 6.1 6.7 7.1 7.7 8.1 8.7 9.1 9.7 10.1 10.7 11.1 11.7 12.1 12.7 13.1 13.7 14.1 14.7 15.1 15.7 16.1 16.7 17.1 17.7 18.1 18.7 19.1 19.7 20.1 20.7 21.1 21.7 22.1 22.7 23.1 23.7 24.1 24.7 25.1 25.7 26.1 26.7 27.1 27.7 28.1 28.7 29.1 29.7 30.1 30.7 31.1 31.7 I II III IV V VI VII VIII I II III IV V VI VII VIII −27 26 32 46 −40 −27 −13 0 9 26 32 38 46 −40 −13 0 9 38 ∘ ∘ ( C) ( C) I: 01:00 V: 13:00 II: 04:00 VI: 16:00 III: 07:00 VII: 19:00 V: 10:00 VIII: 22:00 Figure 7: Monthly and daily dynamics of thermal comfort in winter (January) and summer (July) calculated with UTCI for Birobidzhan, zone 1. Table 3: Mean number of days per year with UTCI values within a specific class for the 3 zones as well as for the climate station in Birobidzhan (2000–2010). UTCI ( C) WMO station Zone 1 Zone 2 Zone 3 <−30 21.0 9.0 10.5 9.4 <−20 68.3 54.8 58.6 55.8 <−10 117.2 108.7 109.6 109.1 <0 170.1 156.1 157.0 156.1 (15≤𝑋≤30 ) 65.4 91.7 90.6 92.5 (18≤𝑋≤27 ) 37.0 57.6 55.8 57.8 >29 19.5 10.1 13.5 10.9 >35 6.0 1.1 1.3 1.0 >41 1.0 0.0 0.0 0.0 Winter (exemple in this case January) in zone 1 presents itself The thermal dynamics in zone 2 were observed to be to be much less comfortable than summer. The daily course similartothose in zone 1but with about5%moreheatstress remains the same with the warmest time being between 13:00 in the summer months. Comfortable values occurred from and 16:00 and the coldest around 7:00. In contrast to summer the midst of March until the end of October. The month there were no periods without thermal stress. Throughout the with the most heat stress is July with its second decade being whole month the body suffers from moderate to very strong the one with almost 30% of heat stress values. Winter still ∘ ∘ cold stress. eTh highest values lie between 0.0 Cand−13.0 C presented a time of constant cold stress varying in its intensity whilethe coldestare closeto−40.0 C. The coldest time of from extreme to moderate and with the second decade of January is in the middle of the second decade from the 12th January as the coldest period of the year. With about 42.1% until the 17th of January, while the highest values occurred at of all values below−27.0 C this decade showed the highest 13:00between the23rdand the27th(Figure 7). frequency of very strong cold stress values. The second decade Advances in Meteorology 7 of December shows 92.4% of all values being below−13.0 C 5. Discussion resulting in at least strong cold stress conditions. As in zone The results of the calculations and simulations as well as 1, the summer months are the ones that present the most the measurements of the meteorological parameters show comfortable outdoor conditions but also the most heat stress. a clear picture of the thermal conditions in terms of the The thermal dynamics of zone 2 for July were used as an human bioclimate in the JAR. In general it can be concluded example for the thermal dynamics in summer. The time of that the JAR has a very big gradient of thermal conditions the highest thermal stress is the time between 13:00 and 16:00 throughout the year not only in the direct thermal parameters with UTCI values above 32.0 C. Also around 10:00 and 19:00 such as 𝑇 and 𝑇 [23, 24]but also in thesecondary 𝑎 mrt the human body can experience slight heat stress on some parameters such as VP and RH. The wind is not so much days.Thecoldesttimeofthe dayisthe time between4:00 boundtoanannualcycleandthereforeinufl encesthethermal and 7:00. During this time the values drop almost to the conditions in a similar pattern throughout the year. eTh rangeofcoldstress. In thecourseofJulythere arethree thermal comfort has been determined with PET and UTCI hot spots. eTh rfi st two occurr in the rfi st decade while the and they exhibited similar dynamics in the annual course. last hotspot lies in the middle of the third decade. Winter in However they indicate a great difference in their values. zone 2presentsitselfwithconstantcoldstress. In Januarythe While PET shows a lot of very extreme values and only highest values for UTCI occur in the aer ft noon between 13:00 little thermal comfort throughout the year, UTCI shows and 16:00. During this time UTCI lies between 0.0 Cand a lot of nonstressful conditions especially in the summer −13.0 C causing moderate to strong cold stress. In the course months. This difference was to be expected since PET has of the night the values start to drop to reach their minimum been calculated with the same base parameters for the entire year whileUTCIisanadaptiveindex whichresults in a values below−27.0 C around 4:00 to 7:00. At this time the less extreme setting. Since it can be assumed that no one human body experiences very strong cold stress. eTh coldest is wearing a light business suit (clo = 0.9) in winter in the time of January is between the 10th and the 16th, while the, Russian Far East the adaption of this parameter seems to least cold days are closer to the end of the month. result in a more realistic assessment. Still the winter season Sinceithas themostopenspace,zone3presents itself holds a lot of cold stress and in contrast to summer has no with the least comfortable thermal conditions. eTh summer comfortable values at all. months show the highest frequency of heat stress values, In case of cold stress in winter it does not matter whether while, in winter the frequency of strong and very strong cold it is calculated with PET or UTCI. In both cases winter is stress is increased. Still summer shows the most comfortable not comfortable. eTh only difference is the range of values. settingwithupto70% of allvaluesbeing within onedecade ∘ ∘ While calculated with PET there are more extreme cold stress in the class of 9.0 Cto27.0 C. The highest heat stress occurs in values, UTCI results strong rather in than extreme cold stress. summer around the same time in the middle of July and the The thermal conditions in summer, however, differ greatly beginning of August. In winter the human body experiences depending on the applied index. While PET depicts a rather exclusively cold stress with 43.9% of all values being between harsh picture of the thermal conditions in summer, UTCI ∘ ∘ −27.0 Cand 39.9 C; theseconddecadeofJanuary shows shows a lot of nonstressful values. This difference is the result the most extreme conditions; while the second decade of of the different procedures of calculating the indices as well December can be considered the coldest in general with as the different index classes applied to the definitions of 92.6% of all values below−13.0 C. Times of no thermal stress thermal comfort. While PET provides only a narrow window occurfromthe midstofMarch to themidst of November ∘ ∘ of thermal comfort (18.0 C to 23.0 C), UTCI considers a ∘ ∘ even though they are very rare at those times. In spring and much wider range (9.0 Cto27.0 C) comfortable or at least autumn the range of UTCI covers everything from thermal notstressful forthe humanbody[2, 3, 5]. The result of this stress to strong cold stress and in rare cases even heat stress. calculationisaverycomfortablethermalsituationinsummer The warmest time of day in zone 3 in summer is still the with about 30% of the values resulting in slight to strong heat time from 13:00 to 16:00, but the occurrence of UTCI values stress and the remaining 70% being comfortable. PET shows outside the range of no thermal stress around 10:00 and 19:00 most of the variability in its classed values during summer. is increased. Also the three hotspots in the monthly course It shows little thermal comfort but wide rather a range from that could be observed in zones 1 and 2 are not as prominent extreme heat stress to moderate cold stress. How wide the because they are closer together and cover more days. From range of PET or UTCI is and how narrow the window of 22:00 to 7:00 the values are the lowest with a minimum comfortable values is depend on the surrounding structures around 4:00. Still they do not present any cold stress since as well. eTh higher the building density is in an area and the they stay quite far above 9 C. In zone 3 the winter season more vegetation there is, the more comfortable are outdoor presents itself with the same dynamics as those in the other conditions are. In summer this is the result of shading effects zones. It shows its coldest period in January from the 8th to and the resulting reduction of𝑇 and in winter the high mrt the 17th in the monthly course and in general from 4:00 to urban density results in a reduction of heat loss due to long 7:00 in thedaily course.Thewarmest time of theday is the wave radiation. As a result the outdoor areas of the residential time between 13:00 and 16:00 but even then the UTCI values area (zone 1) can be considered the most comfortable one do not exceed the range of cold stress. In the coldest hours throughout the year while the city square (zone 3) is the ∘ ∘ UTCI values drop far below−27.0 Cand getclose to−40.0 C. least comfortable due to its high exposure to the elements. 8 Advances in Meteorology 27.8. W E Figure 8: Residential area in Birobidzhan (zone 1). 14 12 The results also show the influence of all the parameters that are part of the calculations of PET. eTh higher the relative humidity is the more extreme is the thermal impact of𝑇 and 𝑇 is.Thewindalwayshas acooling eeff ct(except when mrt theair temperatureishigherthanthe surfacetemperatures 1999–2010 RayMan Pro 2.1 of humans), but its role in this region is very important since Figure 9: Polar diagram for the sky view factor (zone 1) in the occurrence of high wind velocities is rather rare. The main Birobidzhan. impact on the human thermal bioclimate in this region lies with the air temperature and the mean radiant temperature. Therefore the best possibilities for human interference lie situation [22, 27, 28]. In summer being located on a wide open in the reduction of irradiation. Using wind channelling to space with close to no vegetation Freiburg and Birobidzhan reduce𝑇 in summer seems premature since the same action present similar heat stress conditions [27–29]. This difference would lead to even more extreme cold stress during winter. in climate situations shows a longitudinal dependency of Another way to reduce thermal stress in urban areas of the the regional climate that is not at all linked to the classic JAR would be the increase of vegetation. climate zones which depend on the latitude but rather to its According to a paper on thermal strain due to a change proximity to pressure systems and its location in the path of in locations within the Russian Far East [25]the dieff rence meteorological phenomena such as a monsoon or El Nino ˜ . in thermal comfort during the winter months is negligible due to an overall extreme cold stress which makes the results of this study applicable for the whole region in winter. In 6. Conclusions summer, however, the thermal conditions within the Far East district vary greatly making more localized investigations After analysing the results of measurements and calculations necessary for a thorough assessment of preferable urban it canbeconcluded that theJAR is aclimaticextreme outdoor structures in summer. region with a massive gradient of thermal comfort conditions. On the topic of the change of extreme climate regions due However there is a variety of possibilities for adaption to this to global climatechangeitcan be assumedthatthe overall phenomenon. eTh rfi st and most simple one is of course to frequency of extremely cold days is reduced in favour of an follow the saying “there is no bad weather, just a bad choice increase in heat stress days which would lead to an overall of clothing” and to choose the right clothing for the meteoro- increase in thermal comfort for regions of high cold stress logical situation. This action is taken into consideration in the [26]. In a region of high gradients of thermal comfort like the application of UTCI and it shows a significant moderation of JAR, however, the result would rather be a shift in types of the otherwise unpleasant conditions in late spring, summer, thermaldiscomfortthananincreaseofcomfortable days. and early autumn. In the cold season, however, even clothing In comparison, Freiburg in south western Germany does not help much. It moderates the extreme cold stress but which lies at the same latitude (48 N) but at a very different it does not suffice to relieve the human body entirely. To gain ∘ ∘ longitude (9 E) than Birobidzhan (127 E) has a very different a maximum of cold stress reduction it is therefore necessary climate setting. In Birobidzhan the annual climate variation to make sure that one stays outside as little as possible is much higher and is based on the summer monsoon or the and—if one does stay outside—to choose the location wisely. Siberian high pressure area. In Freiburg climate is much more According to the results of this study the wisest decision dependent on the pressure systems in the northern Atlantic wouldbetoavoid wide open spaces andtoremaininareas of especially the Northern Atlantic Oscillation (NAO) and the high urban density. Another important factor is of course the interaction with the alpine climate system. As a result the time of the day. While it is advisable to choose the morning climate in Freiburg is much less extreme. In particular in and late afternoon hours of the day and to avoid noon and winter the thermal parameters show a much more moderate early aeft rnoon for outside chores in summer, the opposite Advances in Meteorology 9 Figure 12: Square in Birobidzhan (zone 3). Figure 10: Main street in Birobidzhan (zone 2). 27.8. 60 27.8. 60 80 7 19 W E W E 9 17 10 16 14 12 14 12 13 1999–2010 RayMan Pro 2.1 1999–2010 RayMan Pro 2.1 Figure 13: Polar diagram for the sky view factor (zone 3) in Figure 11: Polar diagram for the sky view factor (zone 2) in Birobidzhan. Birobidzhan. References can be said about winter. eTh least thermal stress in winter occurs for all zones in the time between 13:00 and 16:00 which [1] P. Hop ¨ pe, Die Energiebilanz des Menschen [M.S. thesis],Wis- makes it the most pleasant time to be outside. Staying outside senschaftliche Mitteilungen des Meteorologischen Instituts Universitat ¨ Munc ¨ hen, 1984. at night especially in the hours of early morning around 4:00 [2] P. Hop ¨ pe, “The physiological equivalent temperature—a uni- wouldbeill advisedsince thoseare thehours of thestrongest versal index for the biometeorological assessment of the ther- cold stress. mal environment,” International Journal of Biometeorology,vol. 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