- Email: [email protected]
A weather model for indoor thermal calculations
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Building and Environment, Vol. 29, No. 3, pp. 345-351, 1994 Copyright © 1994 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0360-1323 94 $7.00+0.00
Pergamon 0360-1323(94)E0017-L
A Weather Model For Indoor Thermal Calculations JUHA GABRIELSSON* HANS WILJANEN* Indoor air requirements must be connected to the outdoor weather conditions. This ts necessary when, for instance, simulating indoor thermal conditions, calculating air-conditioning loads or specifying contract conditions. A dimensioning weather model to be used in winter and summer conditions in Finland is presented. For winter it gives mean temperatures for 2- and 5-day-long cold periods andfor summer hourly outdoor temperatures, solar radiation values and outdoor humidities for a 5-day-long dimensioning period. The temperature level of the proposed weather model is selected using the probability distribution of the gliding mean temperatures of 2- and 5-day periods.
INTRODUCTION
statistics for 1968-87, a period of 20 years [3]. The purpose was that these 1-2 week periods could as such be used to calculate indoor conditions and loads. As an example the extreme warm period for Sodankyl[i Observatory is shown in Fig. 1. In practice these periods represent extreme conditions the probability of which is unknown. It was also difficult to select periods which could be generally accepted. To overcome this problem, the original 20-year statistical material was reworked in the following way [4].
I N D O O R air requirements must be connected to the outdoor weather conditions. This is necessary, for instance, when simulating indoor thermal conditions, calculating air-conditioning loads or energy consumption, specifying contract conditions or classifying indoor climate [1]. So far no clear guidelines have been presented for specifying the weather for load calculations, especially in summer conditions, apart from the rather incomplete ones in A S H R A E and similar handbooks [2]. For energy calculations, reference years have been proposed and used. They are, however, not necessarily applicable to load calculations. The need to specify the dimensioning weather for all important parameters is increasing as the calculation methods and programs develop. Comparison of thermal indoor air quality with different air-conditioning solutions is not relevant without well defined and generally accepted weather models. The weather for load calculation is different for winter and summer conditions. Winter is easier because the outdoor temperature is the main parameter and the daily variations are small. For summer conditions the solar radiation and humidity must also be defined and large daily variations considered. The aim of this study was to develop a weather model for load calculations for Finnish winter and summer conditions. We hope that the model presented may be of use in developing and standardizing dimensioning weathers for other regions.
SUMMER CONDITIONS Procedure
From the extreme warm periods the 2- and 5-day "worst" parts were selected for three locations in Finland. These are shown in Table 1. It was assumed that the short periods would be much warmer than the longer ones and could be used in dimensioning specially light buildings. Contrary to expectation, the 2- and 5-day periods did not, however, differ substantially and the day-to-day changes in the parameters were small. They all represent clear sky conditions. As an example, Fig. 2 gives the hourly mean temperatures, relative humidities and radiation values on a horizontal surface for the selected 2and 5-day periods and corresponding periods for the test (reference) year in Sodankyl~i. It seems that during a warm period, the climatic conditions on successive days are very similar. The test year values differ substantially. Results f o r summer conditions
METHOD
As a result of this comparison, a 5-day dimensioning period was selected for each location and hourly mean values were calculated for the period. The dimensioning weather models thus created represent extreme conditions that will very seldom be exceeded. They can, however, be used in critical cases. To get a more "normal" dimensioning weather model
While developing a Finnish test year (reference year) for energy calculations, extreme cold and warm periods were identified for three locations from the meteorological * Climaconsult Ltd, FIN-02230 Espoo, Finland. 345
J. Gabrielsson and H. Wiljanen
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Fig. 1. Variation in the meteorological parameters during the extreme warm period of Sodankyl~i Observatory 15/06-23/06/74. with an approximately known probability, the temperature level of the extreme 5-day periods was evenly lowered while keeping the other important parameters, such as radiation and relative humidity, unchanged. This "normalization" was based on the probability distribution of the gliding 5-day mean of daily maximum temperatures calculated for the summer months from the meteorological statistics for 30 years (1961-1990) [5]. For Sodankyl~i Observatory this distribution is presented in Fig 3. For summer conditions, the probability of 150 times per 30 years or statistically 5 times per year was selected as the basis for the "normalization". As can be seen from Fig. 3, the corresponding 5-day mean of the maximum temperatures for Sodankyl~i Observatory is 24°C. Applying the method to other locations gives 26°C for Helsinki Airport and 25°C for Jyv/iskyl~i Airport. Accordingly, we suggest 5-day dimensioning weather models constructed from the extreme periods by lowering the temperature level so that the daily maximums correspond to the values given above. The results are presented for the three locations in Tables 2-4. Helsinki represents the southern part of the country, Jyv/iskyl~i the central and Sodankyl/i the northern area.
For each hour of the day the dry bulb temperature, total, diffuse and direct radiation on a horizontal surface, the relative humidity and enthalpy of the air are given. The radiation values and relative humidities are the same as for the extreme periods, and the enthalpy is calculated. To obtain the extreme dimensioning weather model, the temperature level (for all hours) has to be increased by 2.7°C for Helsinki, 3.2°C for Jyv/iskyl/i and 5.2°C for Sodankyla. The relative humidity and radiation values are unchanged. New enthalpy values must be calculated. The values in Tables 2-4 are based on actual measurements by the Finnish Meteorological Institute. Corrections for summertime (1/4-30/9), measurement of diffuse radiation and time of radiation measurement have been performed [6]. The radiation values represent onehour means. The radiation angles can be calculated according to the mid-day of the period stated in the Tables. WINTER CONDITIONS Procedure For the winter months the mean temperature of cold periods seems to be the right load design criterion. The
Table 1. From extreme warm periods subjectively selected 2- and 5-day "worst" parts for the generation of a dimensioning weather model at three Finnish locations Location Helsinki Airport Jyv/iskyl~ Airport Sodankyl~iObservatory Helsinki Airport : 60° 19'N, 24°58'E. Jyv/iskyl/i Airport : 62°24'N, 25°38'E. Sodankyl/i Observatory : 67°27'N, 26°39'E.
2-day period
5-day period
27/06-28/06/72 13/06-14/06/77 18/06-19/06/74
27/06-01/07/72 11/06-15/06/77 15/06-19/06/74
Weather Model for Indoor Thermal Calculations
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Fig. 2. Comparison of the hourly mean values of weather parameters for the selected 2- and 5-day periods and the corresponding period of the test (reference) year in Sodankyl~i.
solar radiation is low and the daily variations in the weather parameters are not significant. Besides the outdoor temperature, the only important factor is wind velocity. In the following we have assumed that during cold periods the wind velocity is moderate. For winter, as for summer, the extreme periods from reference [3] were used. The typical variation in outdoor temperature and wind speed for an extreme cold period in Sodankyl/i is shown in Fig. 4. During the coldest 2-3 days the daily temperature variation and wind speed are small. Before and after the period the temperature is much higher. F o r Jyv~iskyl~ithe cold period is very similar and for Helsinki longer and flatter. From these extreme periods the "worst" 2- and 5-day parts were subjectively selected and corresponding mean
temperatures calculated. The results are shown in Table 5. It can be seen that the difference in temperatures between the 2- and 5-day periods is significant, unlike in summer. The cold periods in Table 5 represent extreme conditions for which the probability of occurrence is unknown. The results can be used in critical cases.
Resultsfor winter conditions To obtain an estimate of the probability, thei same method and statistical material as in the summer case were applied, i.e. the probability distribution of gliding 2- and 5-day mean temperatures for the winter months
J. Gabrielsson and H. Wiljanen
348
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Fig. 3. The probability distribution of the gliding 5-day mean of maximum daily temperatures for Sodankyl~i Observatory during the summer months June, July and August. The numbers in the figure show how many times a given temperature is reached or exceeded in 30 years.
locations for b o t h 2- a n d 5-day gliding m e a n s are summarized in Table 6. Because the m e a n t e m p e r a t u r e is the only i m p o r t a n t p a r a m e t e r for winter conditions, these values can be utilized directly in load calculations. It is interesting to note t h a t with the selected p r o b ability the difference in the 2- a n d 5-day temperatures is small also in winter conditions. Accordingly, we suggest t h a t in n o r m a l load calculations 5-day values be used. Only in critical situations w h e n the extreme values from
was calculated f r o m the statistics for 30 years (19611990). T h e results for Sodankyl~i O b s e r v a t o r y are s h o w n in Fig. 5. F o r winter conditions, the p r o b a b i l i t y o f six times per 30 years or statistically once per 5 years was selected as the basis for the " n o r m a l i z a t i o n " . As can be seen from Fig. 5, the c o r r e s p o n d i n g 5-day gliding m e a n for Sodankyl~i O b s e r v a t o r y during the winter m o n t h s December, J a n u a r y a n d F e b r u a r y is - 36°C. T h e results for all three
Table 2. Summertime 5-day dimensioning weather for Helsinki. Location 60°I9'N, 24°58'E. Dimensioning weather 27 June-I July 1972 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m E)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1:00 2 : 00 3 : 00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00
17.4 16.7 16.0 15.9 15.8 15.7 17.1 18.4 19.8 21.4 22.9 24.5 24.9 25.3 25.7 25.8 25.9 26.0 25.3 24.6 23.9 22.0 20.1 18.1
0 0 4 20 70 147 229 331 473 605 668 723 749 700 653 615 517 396 282 160 69 22 3 0
0 0 3 14 42 78 115 157 183 188 216 242 247 240 212 189 167 141 111 77 44 16 3 0
0 0 2 7 28 69 114 174 290 416 452 481 502 461 441 426 350 255 171 83 25 5 1 0
38.0 36.9 35.7 35.7 35.8 35.9 38.3 40.6 43.0 44.5 45.7 46.5 46.1 45.5 44.8 44.9 45.1 45.3 44.9 44.4 43.9 42.4 40.6 38.5
64.8 66.4 67.8 68.8 69.8 70.8 68.0 65.2 62.2 56.4 50.6 44.4 41.6 38.8 35.8 35.8 35.8 35.8 37.8 39.8 41.6 48.0 54.4 61.2
Weather Model for Indoor Thermal Calculations
349
Table 3. Summertime 5-day dimensioning weather for Jyv~iskyl~i. Location 62°24'N, 25°38'E. Dimensioning weather 11 June15 June 1977 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m 2)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1 : 00 2 : 00 3 : 00 4 : 00 5 : 00 6 : 00 7:00 8 : 00 9 : 00 10:00 11:00 12:00 13 : 00 14:00 15:00 16:00 17 : 00 18:00 19 : 00 20: 00 21 : 00 22:00 23 : 00 0 : 00
12.8 11.9 11.0 11.3 11.6 11.9 14.0 16.0 18.0 19.5 21.1 22.6 23.4 24.2 25.0 24.9 24.8 24.8 24.0 23.2 22.3 20.3 18.3 16.3
0 0 4 25 73 152 248 340 429 552 656 698 718 691 571 467 426 338
0 0 3 19 49 82 117 148 169 194 212 227 237 247 231 209 196 161
216
124
113 50 20 4 0
77 40 19 4 0
0 0 1 6 24 70 131 192 260 358 445 471 480 443 340 258 230 177 92 35 10 1 0 0
32.2 31.1 29.1 29.9 30.6 29.6 32.3 34.6 37.5 39.1 40.3 42.5 43.0 43.6 45.5 45.6 45.8 46.9 46.3 45.3 46.4 44.5 42.1 38.9
82.2 86.8 87.0 87.2 87.0 79.6 72.2 64.4 59.0 53.6 48.0 45.2 42.4 39.8 40.2 40.6 41.4 44.0 46.6 48.4 55.8 63.2 70.4 75.8
Table 5 are applicable do we r e c o m m e n d calculations with b o t h 2- a n d 5-day periods.
can be connected to a n exactly defined weather model with all the necessary parameters. Calculations c a n n o t n o w a d a y s be c o m p a r e d because the weather p a r a m e t e r a s s u m p t i o n s differ widely a n d are incomplete. One o f the p r o b l e m s connected with this p r o p o s a l is t h a t it does n o t represent real weather b u t is " m a n i p u l a t e d " weather. The weather model has been " n o r malized" from extreme periods based o n the p r o b a b i l i t y distribution o f the gliding m e a n temperature. M o r e infor-
DISCUSSION T h e d i m e n s i o n i n g weather model presented is well argued, r a t h e r simple, a n d c a n be applied in m o s t comp u t e r p r o g r a m s used today. T h e m a i n a d v a n t a g e is t h a t the t h e r m a l i n d o o r requirements a n d load calculations
Table 4. Summertime 5-day dimensioning weather for Sodankyl~i. Location 67°22'N, 26°39'E. Dimensioning weather 15 June19 June 1974 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m 2)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1:00 2 : 00 3 : 00 4 : 00 5 : 00 6 : 00 7:00 8:00 9:00 10:00 11:00 12:00 13 : 00 14:00 15:00 16 : 00 ! 7:00 18:00 19:00 20 : 00 21 : 00 22:00 23:00 0:00
9.9 8.2 6.5 8.6 10.7 12.7 14.8 16.9 19.1 20.2 21.4 22.5 22.9 23.3 23.7 23.8 23.9 24.0 23.4 22.8 22.2 19.2 16.2 13.3
15 19 39 80 148 237 338 438 531 614 680 722 727 703 659 598 525 440 337 227 138 75 37 17
8 9 15 24 32 42 51 58 64 67 71 78 85 93 96 91 86 77 69 56 38 25 15 8
6 11 24 56 116 195 287 380 467 547 609 643 641 609 563 508 439 363 268 171 100 50 22 9
24.2 22.4 20.3 23.0 25.5 27.6 29.3 30.6 31.4 32.0 32.5 32.7 33.7 34.7 35.4 35.1 34.8 34.3 34.2 34.0 33.6 32.5 30.4 27.6
73.8 82.4 90.8 82.0 73.2 64.0 54.2 44.4 34.8 31.0 27.2 23.2 24.0 24.8 25.0 24.0 23.0 21.6 23.4 25.2 26.6 37.4 48.2 59.0
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extreme cold periods subjectively selected 2- and 5-day "worst" parts and corresponding mean for three Finnish locations. The longitudes and latitudes of the locations are given in Table 1 2-day period
Mean temp (°C)
5-day period
Mean temp (°C)
09-10/01/87 06-07/01/85 05-06/01/85
- 34.0 - 35.3 -42.0
08-12/01/87 04-08/01/85 04--08/01/85
- 31.3 - 30.4 - 34.8
Location Helsinki Airport Jyvtiskylti Airport Sodankyltt Observatory
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oeg.c F i g . 5. T h e p r o b a b i l i t y d i s t r i b u t i o n o f t h e g l i d i n g 5 - d a y m e a n o f m e a n d a i l y t e m p e r a t u r e s for Sodankylti Observatory during the winter months December, January and February. The numbers in the figure show how many times a given temperature is r e a c h e d o r e x c e e d e d i n 3 0 y e a r s .
-21
-20
Weather Model for Indoor Thermal Calculations
351
Table 6, Gliding 2- and 5-day mean temperatures to be statistically reached or exceeded once in 5 years for three locations in Finland according to the meteorological statistics for 30 years (1961-1990). The latitudes and longitudes of the locations are given in Table 1
Location
2-day gliding mean temperature (of)
5-day gliding mean temperature (°c)
- 28 - 34 - 39
- 27 - 33 - 36
Helsinki Airport Jyv/iskyl~i Airport Sodankyl~i Observatory
mation is needed about the real occurrence of the proposed weather model, especially in summer conditions when many parameters are involved. F o r both summer and winter conditions the proposed weather model is near the dimensioning weathers gen-
erally accepted and used in Finland although they have not so far been well argued and defined. Aeknowleflgement--This study is a continuation of the work presented in reference [4] and has been privately financed by the authors..
REFERENCES 1. Classified indoor climate systems, guidelines and specifications, Scanvac, The Swedish Indoor Climate Institute, Hantverkargatan 8, 112 21 Stockholm (1991). 2. ASHRAE 1989 Handbook: Fundamentals, Air Conditioning Cooling Load, Chapter 26, American Society of Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA (1989). 3. B. Tammelin and E. Erki6, Meteorological data for energy calculations--Finnish test year, The Finnish Meteorological Institute, Report No 1987-7, Helsinki (1987) [in Finnish]. 4. J. Gabrielsson, Weather model for indoor air calculations, in Proceedingsoflndoor Air '93, Volume 2, p. 681, Helsinki (1993). 5. Climatological statistics in Finland 1961-1990, The Finnish Meteorogical Institute, Helsinki (1991). 6. T. Laine, LVIS-2000 standard building and testing weather---correction of weather parameters, Report, Olof Granlund Consulting Ltd, Helsinki (1992) [in Finnish].
BAE 29:3-H
Building and Environment, Vol. 29, No. 3, pp. 345-351, 1994 Copyright © 1994 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0360-1323 94 $7.00+0.00
Pergamon 0360-1323(94)E0017-L
A Weather Model For Indoor Thermal Calculations JUHA GABRIELSSON* HANS WILJANEN* Indoor air requirements must be connected to the outdoor weather conditions. This ts necessary when, for instance, simulating indoor thermal conditions, calculating air-conditioning loads or specifying contract conditions. A dimensioning weather model to be used in winter and summer conditions in Finland is presented. For winter it gives mean temperatures for 2- and 5-day-long cold periods andfor summer hourly outdoor temperatures, solar radiation values and outdoor humidities for a 5-day-long dimensioning period. The temperature level of the proposed weather model is selected using the probability distribution of the gliding mean temperatures of 2- and 5-day periods.
INTRODUCTION
statistics for 1968-87, a period of 20 years [3]. The purpose was that these 1-2 week periods could as such be used to calculate indoor conditions and loads. As an example the extreme warm period for Sodankyl[i Observatory is shown in Fig. 1. In practice these periods represent extreme conditions the probability of which is unknown. It was also difficult to select periods which could be generally accepted. To overcome this problem, the original 20-year statistical material was reworked in the following way [4].
I N D O O R air requirements must be connected to the outdoor weather conditions. This is necessary, for instance, when simulating indoor thermal conditions, calculating air-conditioning loads or energy consumption, specifying contract conditions or classifying indoor climate [1]. So far no clear guidelines have been presented for specifying the weather for load calculations, especially in summer conditions, apart from the rather incomplete ones in A S H R A E and similar handbooks [2]. For energy calculations, reference years have been proposed and used. They are, however, not necessarily applicable to load calculations. The need to specify the dimensioning weather for all important parameters is increasing as the calculation methods and programs develop. Comparison of thermal indoor air quality with different air-conditioning solutions is not relevant without well defined and generally accepted weather models. The weather for load calculation is different for winter and summer conditions. Winter is easier because the outdoor temperature is the main parameter and the daily variations are small. For summer conditions the solar radiation and humidity must also be defined and large daily variations considered. The aim of this study was to develop a weather model for load calculations for Finnish winter and summer conditions. We hope that the model presented may be of use in developing and standardizing dimensioning weathers for other regions.
SUMMER CONDITIONS Procedure
From the extreme warm periods the 2- and 5-day "worst" parts were selected for three locations in Finland. These are shown in Table 1. It was assumed that the short periods would be much warmer than the longer ones and could be used in dimensioning specially light buildings. Contrary to expectation, the 2- and 5-day periods did not, however, differ substantially and the day-to-day changes in the parameters were small. They all represent clear sky conditions. As an example, Fig. 2 gives the hourly mean temperatures, relative humidities and radiation values on a horizontal surface for the selected 2and 5-day periods and corresponding periods for the test (reference) year in Sodankyl~i. It seems that during a warm period, the climatic conditions on successive days are very similar. The test year values differ substantially. Results f o r summer conditions
METHOD
As a result of this comparison, a 5-day dimensioning period was selected for each location and hourly mean values were calculated for the period. The dimensioning weather models thus created represent extreme conditions that will very seldom be exceeded. They can, however, be used in critical cases. To get a more "normal" dimensioning weather model
While developing a Finnish test year (reference year) for energy calculations, extreme cold and warm periods were identified for three locations from the meteorological * Climaconsult Ltd, FIN-02230 Espoo, Finland. 345
J. Gabrielsson and H. Wiljanen
346 ,~xlanla/lll
a00
30
f
700.
25
i
20 f-
5OO
40O
3OO lO
n,
oli
m
O. 15.6
16.6
17.6
18.6
19.6
20.6
21.6
22.6
Fig. 1. Variation in the meteorological parameters during the extreme warm period of Sodankyl~i Observatory 15/06-23/06/74. with an approximately known probability, the temperature level of the extreme 5-day periods was evenly lowered while keeping the other important parameters, such as radiation and relative humidity, unchanged. This "normalization" was based on the probability distribution of the gliding 5-day mean of daily maximum temperatures calculated for the summer months from the meteorological statistics for 30 years (1961-1990) [5]. For Sodankyl~i Observatory this distribution is presented in Fig 3. For summer conditions, the probability of 150 times per 30 years or statistically 5 times per year was selected as the basis for the "normalization". As can be seen from Fig. 3, the corresponding 5-day mean of the maximum temperatures for Sodankyl~i Observatory is 24°C. Applying the method to other locations gives 26°C for Helsinki Airport and 25°C for Jyv/iskyl~i Airport. Accordingly, we suggest 5-day dimensioning weather models constructed from the extreme periods by lowering the temperature level so that the daily maximums correspond to the values given above. The results are presented for the three locations in Tables 2-4. Helsinki represents the southern part of the country, Jyv/iskyl~i the central and Sodankyl/i the northern area.
For each hour of the day the dry bulb temperature, total, diffuse and direct radiation on a horizontal surface, the relative humidity and enthalpy of the air are given. The radiation values and relative humidities are the same as for the extreme periods, and the enthalpy is calculated. To obtain the extreme dimensioning weather model, the temperature level (for all hours) has to be increased by 2.7°C for Helsinki, 3.2°C for Jyv/iskyl/i and 5.2°C for Sodankyla. The relative humidity and radiation values are unchanged. New enthalpy values must be calculated. The values in Tables 2-4 are based on actual measurements by the Finnish Meteorological Institute. Corrections for summertime (1/4-30/9), measurement of diffuse radiation and time of radiation measurement have been performed [6]. The radiation values represent onehour means. The radiation angles can be calculated according to the mid-day of the period stated in the Tables. WINTER CONDITIONS Procedure For the winter months the mean temperature of cold periods seems to be the right load design criterion. The
Table 1. From extreme warm periods subjectively selected 2- and 5-day "worst" parts for the generation of a dimensioning weather model at three Finnish locations Location Helsinki Airport Jyv/iskyl~ Airport Sodankyl~iObservatory Helsinki Airport : 60° 19'N, 24°58'E. Jyv/iskyl/i Airport : 62°24'N, 25°38'E. Sodankyl/i Observatory : 67°27'N, 26°39'E.
2-day period
5-day period
27/06-28/06/72 13/06-14/06/77 18/06-19/06/74
27/06-01/07/72 11/06-15/06/77 15/06-19/06/74
Weather Model for Indoor Thermal Calculations
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solar radiation is low and the daily variations in the weather parameters are not significant. Besides the outdoor temperature, the only important factor is wind velocity. In the following we have assumed that during cold periods the wind velocity is moderate. For winter, as for summer, the extreme periods from reference [3] were used. The typical variation in outdoor temperature and wind speed for an extreme cold period in Sodankyl/i is shown in Fig. 4. During the coldest 2-3 days the daily temperature variation and wind speed are small. Before and after the period the temperature is much higher. F o r Jyv~iskyl~ithe cold period is very similar and for Helsinki longer and flatter. From these extreme periods the "worst" 2- and 5-day parts were subjectively selected and corresponding mean
temperatures calculated. The results are shown in Table 5. It can be seen that the difference in temperatures between the 2- and 5-day periods is significant, unlike in summer. The cold periods in Table 5 represent extreme conditions for which the probability of occurrence is unknown. The results can be used in critical cases.
Resultsfor winter conditions To obtain an estimate of the probability, thei same method and statistical material as in the summer case were applied, i.e. the probability distribution of gliding 2- and 5-day mean temperatures for the winter months
J. Gabrielsson and H. Wiljanen
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Fig. 3. The probability distribution of the gliding 5-day mean of maximum daily temperatures for Sodankyl~i Observatory during the summer months June, July and August. The numbers in the figure show how many times a given temperature is reached or exceeded in 30 years.
locations for b o t h 2- a n d 5-day gliding m e a n s are summarized in Table 6. Because the m e a n t e m p e r a t u r e is the only i m p o r t a n t p a r a m e t e r for winter conditions, these values can be utilized directly in load calculations. It is interesting to note t h a t with the selected p r o b ability the difference in the 2- a n d 5-day temperatures is small also in winter conditions. Accordingly, we suggest t h a t in n o r m a l load calculations 5-day values be used. Only in critical situations w h e n the extreme values from
was calculated f r o m the statistics for 30 years (19611990). T h e results for Sodankyl~i O b s e r v a t o r y are s h o w n in Fig. 5. F o r winter conditions, the p r o b a b i l i t y o f six times per 30 years or statistically once per 5 years was selected as the basis for the " n o r m a l i z a t i o n " . As can be seen from Fig. 5, the c o r r e s p o n d i n g 5-day gliding m e a n for Sodankyl~i O b s e r v a t o r y during the winter m o n t h s December, J a n u a r y a n d F e b r u a r y is - 36°C. T h e results for all three
Table 2. Summertime 5-day dimensioning weather for Helsinki. Location 60°I9'N, 24°58'E. Dimensioning weather 27 June-I July 1972 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m E)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1:00 2 : 00 3 : 00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00
17.4 16.7 16.0 15.9 15.8 15.7 17.1 18.4 19.8 21.4 22.9 24.5 24.9 25.3 25.7 25.8 25.9 26.0 25.3 24.6 23.9 22.0 20.1 18.1
0 0 4 20 70 147 229 331 473 605 668 723 749 700 653 615 517 396 282 160 69 22 3 0
0 0 3 14 42 78 115 157 183 188 216 242 247 240 212 189 167 141 111 77 44 16 3 0
0 0 2 7 28 69 114 174 290 416 452 481 502 461 441 426 350 255 171 83 25 5 1 0
38.0 36.9 35.7 35.7 35.8 35.9 38.3 40.6 43.0 44.5 45.7 46.5 46.1 45.5 44.8 44.9 45.1 45.3 44.9 44.4 43.9 42.4 40.6 38.5
64.8 66.4 67.8 68.8 69.8 70.8 68.0 65.2 62.2 56.4 50.6 44.4 41.6 38.8 35.8 35.8 35.8 35.8 37.8 39.8 41.6 48.0 54.4 61.2
Weather Model for Indoor Thermal Calculations
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Table 3. Summertime 5-day dimensioning weather for Jyv~iskyl~i. Location 62°24'N, 25°38'E. Dimensioning weather 11 June15 June 1977 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m 2)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1 : 00 2 : 00 3 : 00 4 : 00 5 : 00 6 : 00 7:00 8 : 00 9 : 00 10:00 11:00 12:00 13 : 00 14:00 15:00 16:00 17 : 00 18:00 19 : 00 20: 00 21 : 00 22:00 23 : 00 0 : 00
12.8 11.9 11.0 11.3 11.6 11.9 14.0 16.0 18.0 19.5 21.1 22.6 23.4 24.2 25.0 24.9 24.8 24.8 24.0 23.2 22.3 20.3 18.3 16.3
0 0 4 25 73 152 248 340 429 552 656 698 718 691 571 467 426 338
0 0 3 19 49 82 117 148 169 194 212 227 237 247 231 209 196 161
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82.2 86.8 87.0 87.2 87.0 79.6 72.2 64.4 59.0 53.6 48.0 45.2 42.4 39.8 40.2 40.6 41.4 44.0 46.6 48.4 55.8 63.2 70.4 75.8
Table 5 are applicable do we r e c o m m e n d calculations with b o t h 2- a n d 5-day periods.
can be connected to a n exactly defined weather model with all the necessary parameters. Calculations c a n n o t n o w a d a y s be c o m p a r e d because the weather p a r a m e t e r a s s u m p t i o n s differ widely a n d are incomplete. One o f the p r o b l e m s connected with this p r o p o s a l is t h a t it does n o t represent real weather b u t is " m a n i p u l a t e d " weather. The weather model has been " n o r malized" from extreme periods based o n the p r o b a b i l i t y distribution o f the gliding m e a n temperature. M o r e infor-
DISCUSSION T h e d i m e n s i o n i n g weather model presented is well argued, r a t h e r simple, a n d c a n be applied in m o s t comp u t e r p r o g r a m s used today. T h e m a i n a d v a n t a g e is t h a t the t h e r m a l i n d o o r requirements a n d load calculations
Table 4. Summertime 5-day dimensioning weather for Sodankyl~i. Location 67°22'N, 26°39'E. Dimensioning weather 15 June19 June 1974 Time (hour)
Temperature (°C)
Tot. rad (W/m 2)
Diff. rad (W/m 2)
Dir. rad (W/m 2)
Enthalpy (kJ/kg)
Rel. humidity (%)
1:00 2 : 00 3 : 00 4 : 00 5 : 00 6 : 00 7:00 8:00 9:00 10:00 11:00 12:00 13 : 00 14:00 15:00 16 : 00 ! 7:00 18:00 19:00 20 : 00 21 : 00 22:00 23:00 0:00
9.9 8.2 6.5 8.6 10.7 12.7 14.8 16.9 19.1 20.2 21.4 22.5 22.9 23.3 23.7 23.8 23.9 24.0 23.4 22.8 22.2 19.2 16.2 13.3
15 19 39 80 148 237 338 438 531 614 680 722 727 703 659 598 525 440 337 227 138 75 37 17
8 9 15 24 32 42 51 58 64 67 71 78 85 93 96 91 86 77 69 56 38 25 15 8
6 11 24 56 116 195 287 380 467 547 609 643 641 609 563 508 439 363 268 171 100 50 22 9
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Mean temp (°C)
5-day period
Mean temp (°C)
09-10/01/87 06-07/01/85 05-06/01/85
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oeg.c F i g . 5. T h e p r o b a b i l i t y d i s t r i b u t i o n o f t h e g l i d i n g 5 - d a y m e a n o f m e a n d a i l y t e m p e r a t u r e s for Sodankylti Observatory during the winter months December, January and February. The numbers in the figure show how many times a given temperature is r e a c h e d o r e x c e e d e d i n 3 0 y e a r s .
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Weather Model for Indoor Thermal Calculations
351
Table 6, Gliding 2- and 5-day mean temperatures to be statistically reached or exceeded once in 5 years for three locations in Finland according to the meteorological statistics for 30 years (1961-1990). The latitudes and longitudes of the locations are given in Table 1
Location
2-day gliding mean temperature (of)
5-day gliding mean temperature (°c)
- 28 - 34 - 39
- 27 - 33 - 36
Helsinki Airport Jyv/iskyl~i Airport Sodankyl~i Observatory
mation is needed about the real occurrence of the proposed weather model, especially in summer conditions when many parameters are involved. F o r both summer and winter conditions the proposed weather model is near the dimensioning weathers gen-
erally accepted and used in Finland although they have not so far been well argued and defined. Aeknowleflgement--This study is a continuation of the work presented in reference [4] and has been privately financed by the authors..
REFERENCES 1. Classified indoor climate systems, guidelines and specifications, Scanvac, The Swedish Indoor Climate Institute, Hantverkargatan 8, 112 21 Stockholm (1991). 2. ASHRAE 1989 Handbook: Fundamentals, Air Conditioning Cooling Load, Chapter 26, American Society of Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA (1989). 3. B. Tammelin and E. Erki6, Meteorological data for energy calculations--Finnish test year, The Finnish Meteorological Institute, Report No 1987-7, Helsinki (1987) [in Finnish]. 4. J. Gabrielsson, Weather model for indoor air calculations, in Proceedingsoflndoor Air '93, Volume 2, p. 681, Helsinki (1993). 5. Climatological statistics in Finland 1961-1990, The Finnish Meteorogical Institute, Helsinki (1991). 6. T. Laine, LVIS-2000 standard building and testing weather---correction of weather parameters, Report, Olof Granlund Consulting Ltd, Helsinki (1992) [in Finnish].
BAE 29:3-H