Manual 1 – Climate Data Processing
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MARKET ACCESS PROJECT NUMBER: PN07.1052 August 2007 Manual 1 – Climate data processing This report can also be viewed on the FWPA website www.fwpa.com.au FWPA Level 4, 10-16 Queen Street, Melbourne VIC 3000, Australia T +61 (0)3 9927 3200 F +61 (0)3 9927 3288 E [email protected] W www.fwpa.com.au Manual No. 1: Processed Climate Data 1 USP2007/030 MANUAL NO. 1 Processed Climate Data for Timber Service Life Prediction Modelling C-H. Wang and R.H. Leicester March 2008 This report has been prepared for FWPA. Please address all enquiries to: Urban Systems Program CSIRO Sustainable Ecosystems P.O. Box 56, Highett, Victoria 3190 Manual No. 1: Processed Climate Data 2 Contents EXECUTIVE SUMMARY ........................................................................................................ 3 1. PROCESSING OF RAW CLIMATE DATA ................................................................... 4 1.1. Assumptions and Strategies for Data Processing ......................................................... 4 1.2. Correction of Rainfall Duration of Three-Hour Data by Half-Hour Data ................... 5 2. PLOTS OF STATION LOCATIONS, RAINFALL, AND TEMPERATURE .............. 11 Manual No. 1: Processed Climate Data 3 Executive Summary This report documents a set of climate data recorded by the Bureau of Meteorology (BOM) and used for durability model development and analysis in the timber durability project. The original set of data comprises records collected from 144 weather stations; however, the records at a site are typically flawed with missing (or blank) data and/or some outliers. Moreover, among the records from different stations, different temporal steps for data recording were often used. Processing of the original climate data is performed to eliminate the data from some stations from which not enough years of data being recorded for statistical inferences, as well as the data in years in which missing records and outliers were deemed too many to be useful. As a result, data from 132 stations are retained for climate parameter estimation. Plots that show the estimated yearly climate parameters (i.e., rainfall, dry-bulb temperature, and wet-bulb temperature) at these stations are included in this report. The raw data are stored in a folder ―Raw BOM Datafiles.‖ The processed climate data files are used to generate the annual climate parameter estimates needed in the durability prediction and design. More specifically, the following parameters are estimated: annual rainfall (mm/year), number of dry months (months/year), number of rain days (days/year), time of wetness (hours/year), dry-bulb temperature (°C), wet-bulb temperature (°C), wind speed (km/hr), and wind direction (degrees from the north) Manual No. 1: Processed Climate Data 4 1. Processing of Raw Climate Data 1.1. Assumptions and Strategies for Data Processing Durability prediction of timber construction requires knowledge of local climate data such as temperature, relative humidity, vapour pressure, wind speed, wind direction, and rainfall, among others, to make reasonable estimation of adverse attack processes, for example, fungal decay, metal fastener corrosion, termites and borers, on structural and non-structural elements. Availability of climate data thus is a prerequisite for this purpose. A set of climate data recorded by the Bureau of Meteorology (BOM) at 144 weather stations around Australia were obtained. Locations of the weather stations are tabulated in Table 1.1. The number of years being recorded at each station varies widely, with the latest being started in 1984 (Latrobe Valley Airport, VIC, BOM ID 85280, CSIRO ID 84), and the earliest in 1858 (Sydney Regional Office, NSW, BOM ID 66062, CSIRO ID 124). All data were the records prior to either 1997 or 1998 inclusive. An examination of the records reveals that the readings at a site are typically incomplete. It may be attributed to the facts that: (1) Recording was made for discrete periods instead of spanning the entire time period of interest; (2) there are some short intermittent periods where data have not been recorded; and (3) the readings are contaminated by systematic or random errors. Moreover, in each of the recorded datasets, it generally consists of peculiar missing (or blank) data and/or some outliers. Among the records from different stations, different temporal steps for data recording were often used. All of these cause direct use of the raw climate data to be difficult. The following strategies were adopted for estimating the annual rainfall (mm/year), number of dry months (months/year), number of rain days (days/year), time of wetness (hours/year), dry-bulb temperature (°C), wet-bulb temperature (°C), wind speed (km/hr), and wind direction (degrees from the north): 1. Prior to 1988, all the climate data were recorded as what were observed; i.e., if no rainfall observed, it was recorded 0.0 mm. Therefore, when blanks appeared, they were regarded as missing records. The data in a year in which less than of data missing were used for annual climate estimation. For example, if daily observations were carried out eight times (every three hours), then there must be 2920 instances of data recording in a 365- day year. Then if an entity (e.g. rainfall) were recorded more than 2433 instances in a year, the year was used to estimate the average of that entity. 2. In and after 1988, generally observations were more comprehensively carried out; therefore, if observations were maintained for one full calendar year, the data from that Manual No. 1: Processed Climate Data 5 year were used for annual climate estimation. The final year (either 1997 or 1998) was discarded if it was not recorded up to November. 3. A site that has at least two years of good data for all of the recorded climate parameters after processing, as described in points 1 and 2, was chosen for use; otherwise, it was discarded. 4. All the other derived climate data: number of dry months, number of rain days, equilibrium moisture content, relative humidity at 3 o’clock in the afternoon, and time of wetness were calculated from the data records in the years used. The annual quantity of a derived climate entity was then estimated in the same way as was done for the recorded climate entities. Two of the stations were located in Papua New Guinea and thus discarded. Ten of the other stations covered either less than two years of readings or too many data readings missing and are thus discarded, leaving a set of data from 132 stations for use. The twelve discarded records are shown in Table 1.1 with double strikethrough lines. The raw data are stored in a folder ―Raw BOM Datafiles.‖ 1.2. Correction of Rainfall Duration of Three-Hour Data by Half-Hour Data The raw climate data obtained from the Bureau of Meteorology for the 132 weather stations used in this project were recorded at irregular time intervals. They were later processed into three-hour interval data for each site. This set of processed data gives a resolution of three hours — the distribution of an item of interest, e.g. rainfall, in an interval can only be assumed uniformly distributed if no other information is available. This causes the problem of underestimating the rainfall intensity in many cases as durations of rainfall may be well less than three hours. One way to rectify this problem is to use a set of more refined data, e.g. five-minute- interval data, for the computation of rainfall quantities and intensities. A set of half-hour- interval data for the years 2000 and 2001 has been obtained from the BOM for nine cities: Adelaide, Alice Springs, Brisbane, Canberra, Darwin, Hobart, Melbourne, Perth, and Sydney. The equivalent three-hour-interval rainfall quantities for the nine cities were determined from the half-hour-interval data by adding the rainfall in six consecutive half-hour intervals. For rainfall duration estimation, it is assumed that whenever there is rainfall in a half-hour interval, the rainfall intensity is constant over the interval. For each city, the rainfall duration, td (hr), against the three-hour rainfall, R3hr (mm), was grouped and averaged as follows: For = 0 – 4 mm: divided into 16 groups with equal interval of 0.25 mm For = 4 – 8 mm: divided into 4 groups with equal interval of 1 mm For = 8 – 10 mm: 1 group with interval of 2 mm For = 10 – 20 mm: divided into 2 groups with equal interval of 5 mm For > 20 mm: divided into as many groups with equal interval of 10 mm Manual No. 1: Processed Climate Data 6 The averages of the groupings are then used for determination of relationship between three- hour rainfall and its duration. The dots in Figure 1.1 show the grouped averages from all the nine cities, and the solid line is the least-square regression line of rainfall duration on three- hour rainfall, tRd1.2 0.3ln 3 hr , and td 0 (1.1) The estimated rainfall intensity, rrain (mm/hr), is R3hr rrain (1.2) td 3.0 td = 1.2 + 0.3ln R3hr 2.5 2.0 (hr) d t 1.5 Duration Duration 1.0 0.5 0.0 0 10 20 30 40 50 3-hour rainfall R3hr (mm) Figure 1.1 Duration vs. three-hourly rainfall derived from half-hourly rainfall data. Manual No. 1: Processed Climate Data 7 Table 1.1 Location of BOM weather stations for climate data CSIRO BOM Lat Long Elev Year Year State Station Name ID ID Start End 1 23034 34.96 138.53 6 1955 SA- Adelaide (Adelaide Airport Ccmposite) 2 9741 34.94 117.8 68 1942 WA- Albany Airport 3 15590 23.81 133.88 546 1940 NT- Alice Springs Airport 4 56002 30.53 151.67 987 1857 NSW Armidale (Uni New England) 5 85279 37.88 147.56