The most likely error in reporting wet bulb temperature is that the wet bulb itself becomes dry or does not have air freely circulating around it. Both problems increase the reported wet
bulb temperature. It was felt, after analysis, that the oceanic data had a significant fraction of ‘over-estimated’ wet bulb values, making a difference to the statistics at the high temperature
end of the range. For each of the ocean zones, this has been manually accounted for when fitting Normal distributions to the data. When doing this in Gulf and Red Sea areas,
acknowledgement was also made of the statistics of the more reliable data from adjacent ports. This calibration against the shore data led to a blanket reduction in the mean by 1
o
C being applied to all ship sourced wet bulb statistics. Thus, the data in Table 2.1 may appear
to be 1
o
C too cool if compared only to the NCDC data, however they are now consistent with the shore based records.
2.3 Use of Voyage and Destination Weather
Section 2.2.1 gives the rationale related to data quality by which the available data were used to give cumulative probabilities of wet bulb appropriate to each zone of ocean, for each
month of the year. In order to handle the vast volume of data 200Mb in the NCDC data set, and to avoid meaningless statistics covering a large fraction of the globe at one time, the
relevant ocean areas were divided into zones of roughly constant climatology. Figure 2.1 shows the ocean zones applied. There are 4 zones covering Gulf waters and 5 zones
covering the Red Sea. This is sufficient to capture the climate variation from south to north for each of these bodies of water. The remainder of 33 zones each cover a 5
o
range in latitude and 10
o
range in longitude, and together cover all ocean north of latitude 15
o
S relevant to shipping routes from Australia to the Middle East.
Project: LIVE.116 – Development of a Heat Stress Risk Management Model Revision F
Maunsell Australia Pty Ltd Page 17 of 129
Final Report December 2003
Figure 2.1 Indian Ocean Weather Zones Map
Project: LIVE.116 – Development of a Heat Stress Risk Management Model Revision F
Maunsell Australia Pty Ltd Page 18 of 129
Final Report December 2003
Each of the zones had sufficient data 1000 pointsmonth to generate a realistic probability distribution of wet bulb temperature within the zone for each month. The least populous
zones were 10
o
S to 15
o
S where conditions are milder. Those zones clearly do not control the heat stress risk of voyages to the Middle East and so the sparsity of data is not an issue.
Appendix A tabulates the wet bulb temperature probability distributions derived from the NCDC data set. As discussed in Section 2.2.1, these data were combined into voyage
maxima for each month along each of 4 routes; northern Australia to the Gulf, northern Australia to the Red Sea, southern Australia to the Gulf and southern Australia to the Red
Sea. Normal distributions were adjusted to fit the worst case probabilities for each route and month 48 cases applying meteorological judgement in allowing for the known data
deficiencies. In fitting Normal distributions to the wet bulb data, attention was only paid to the top 50 of the distribution. This may give an error at lower temperatures however low
temperatures are not relevant to heat stress. The resulting 48 pairs of mean and standard deviation are given in Table 2.1. Note that, in order to improve agreement with shore based
data, and acknowledging known data deficiencies, the risk estimation currently applies a 1
o
C shift to all means. This adjustment is already included in Table 2.1.
Table 2.1 Idealized “Normal” Wet Bulb Probability Distributions mean ± standard deviation
Month North to Red Sea
South to Red Sea North to Gulf
South to Gulf
January 24.2 ± 1.30
24.0 ± 1.30 24.1 ± 1.40
24.0 ± 1.40 February
24.4 ± 1.40 24.2 ± 1.30
24.4 ± 1.40 24.2 ± 1.35
March 24.6 ± 1.35
24.5 ± 1.40 24.6 ± 1.35
24.5 ± 1.30 April
25.0 ± 1.45 24.9 ± 1.30
24.9 ± 1.50 24.9 ± 1.30
May 26.3 ± 1.30
26.2 ± 1.40 25.9 ± 1.70
25.9 ± 1.70 June
27.1 ± 1.30 27.1 ± 1.30
27.4 ± 1.70 27.4 ± 1.70
July 27.4 ± 1.55
27.4 ± 1.55 28.1 ± 1.50
28.1 ± 1.50 August
27.3 ± 1.55 27.3 ± 1.55
28.2 ± 1.65 28.2 ± 1.80
September 27.1 ± 1.40
27.1 ± 1.40 27.2 ± 1.80
27.2 ± 1.70 October
25.8 ± 1.50 25.8 ± 1.50
24.7 ± 1.90 24.7 ± 1.90
November 24.0 ± 1.35
24.0 ± 1.35 24.1 ± 1.45
24.1 ± 1.45 December
24.0 ± 1.25 24.0 ± 1.25
24.1 ± 1.25 24.0 ± 1.25
2.4 Departure Ports
