Report for the fishermen Finding the best days to process sea-cucumber in the Seychelles during the months of March, April and May. The Seychelles National Meteorological Services Mahé Seychelles By: Hyacinth Seeward Seychelles e-siac June 2009 1
Table of contents Contents Page 1. Background..3 2. Objectives.4 3. Methodology.4 4. Data and Definitions 5 5. Results and Implications.5-15 6. Recommendations 16 7. Appendix: Metadata 16 Monthly Totals..17 Daily rainfall.18-37 2
Map showing the Seychelles Islands. The biggest island is Mahe which is also the main island of the Seychelles archipelago. The data used in my report is from the island of Mahe. Background My report is based on the best days to process sea-cucumber in the Seychelles. Seychelles is an archipelago comprising of about 115 islands. It is situated over the western Indian Ocean, within the Tropics, at longitudes 55 31 East and latitudes 4 40 south. The Seychelles has two seasons namely the South-east trade winds, from May to September which is our dry season, and the North-west monsoon, from November to March which is our wet season. And we have two short transitional periods in the months of April and October. Fisheries are one of the main factors of the economy of Seychelles. And processing sea-cucumber also contributes to that industry. The sea-cucumber is a delicacy in some countries. In Seychelles, a special license is given to designated fishermen so that they can do this activity of fishing and processing of seacucumber. After they have fished, they have to put it in the sun to dry, to process and then pack and export. To do this, there must not be rain or the rainfall should be minimal, since it is an outdoor activity. Therefore finding the days ideal for processing is important. The client needs at least 10 days of minimal or no rainfall for processing. 3
The data used is from the National Meteorological station which is situated at the Seychelles International Airport. The National Meteorological Station is on the main island of Seychelles and its station number is 63980. Objectives The client wants to know the best days during the months of March, April and May that are best for processing and what are the risks. The main objective is to find which days during these months will be best days for processing and also the risks attached to those chosen months. Methodology The data is in excel (simple) format. I examine the data in its original format. There are 32 columns, that is 30 for the years and two more columns, one for the day numbers and one for the month. All the columns are of length 367 which 366 for the days and one is used for the header. I inspected the data and satisfied that all the units stayed the same, which is in millimeters. I replaced the missing data with code 9999, trace rainfall with 8888 and for the non-leap year I gave the code 9988. I scrutinized the data for odd values or negative rainfall. The maximum values look reasonable. Then I will import it into Instat which is the tool that will be used for the analysis and it will be examined and investigated again. They are okay. I will use the two-stage events analysis to first, find the events of interest (extract the dates in which processing will take place) and second, I will summarize the data using descriptive statistics. The fivenumber summary will also be used. The above diagram shows the Instat dialog I used to extract the daily data for the three chosen months(march, April and May). 4
Data and definitions to be used Data to be used is the 30 years rainfall data from 1979 to 2008. The monthly and daily rainfall data will be analyzed. There should be at least 10 days with rainfall not greater than 0.85mm. The definitions are: (i) First date from 1 st March when rainfall is less than 0.85mm for 10 consecutive days. (ii) First date from 1 st April when rainfall is less than 0.85mm for 10 consecutive days. (iii) First date from 1 st May when rainfall is less than 0.85mm for 10 consecutive days. Results Graphs and tables of daily and monthly rainfall will be produced to show the results. Summary statistics to show the risks of processing during those three months will also be used. Graph 1. Showing the amount of rainfall totals for the 30 years of data from 1979 to 2008. 3500 Annual rainfall totals for the years 1979 to 2008 3000 2500 2000 1980 1985 1990 1995 Year 2000 2005 The time series plot shows the amount of rainfall totals for the 30 years. Maximum rainfall occurred in 1997 with a maximum of 3559.2mm and minimum was in 1986 with 1656.1mm of rainfall. 5
Graph 2 and Table 1. Showing the summary values of monthly rainfall (mm) for the 30 years. 800 600 Plot of the monthly rainfall summaries Mean Min Max Median 25% 75% 400 200 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months 6
Table 1. Column Mean Min. Max. Median 25% 75% Jan_t 392.5 132 798.2 408.7 259.3 454.7 Feb_t 256.3 9.1 611 242.4 96.35 402.7 Mar_t 202.9 55 465.8 190.7 136.9 249.1 Apr_t 179.6 61.8 463.2 169 101.5 217 May_t 162.4 10.7 558.9 109.2 64.9 230.9 Jun_t 117.1 15.7 528.6 70.2 49.42 131.6 Jul_t 82.82 20.1 276.9 65.35 42.3 108.7 Aug_t 120.8 15 694.1 87.85 37.9 141 Sep_t 156 13 456.8 155.5 74.15 221.2 Oct_t 173.5 8.8 324 164.1 81.33 266.9 Nov_t 204.6 42.4 441.2 194.5 144.5 256.2 Dec_t 302.4 57.9 606.9 268.1 209.8 384.6 May is seen to be the month with the second minimum monthly rainfall. Summary statistics for the months of March, April and May. Column Count Mean Min. Max. SDE Sum Mar_t 30 202.9 55 465.8 91.69 6085 Apr_t 30 179.6 61.8 463.2 88.47 5389 May_t 30 162.4 10.7 558.9 137.7 4873 April is the month amongst the three with the smallest standard deviation and May with the greatest. 7
Graph3. Graph showing annual rainfall amount for the three months 500 400 Mar_t Apr_t May_t 300 200 100 0 1980 1985 1990 1995 Year 2000 2005 Graph 3. Shows that the three months are characterized with rainfall being more than 50mm during the 30 years. May have the maximum rainfall of 558.9mm which occurred in 1992. The minimum was in May as well with 10.7mm in 1984. 8
Mar_t Apr_t May_t 500 400 300 200 100 0 The boxplot shows the daily rainfall for the three months; March, April and May, for the three definitions. It shows that the month of May has more variation in rainfall than the other two months. The nxt four charts show the pattern of daily rainfall through the years. I have chosen the last four years to illustrate that pattern. As the graphs show, there is rarely a 10-day dry spell from day 61 to day 152. Day 61 is 1 st March and day 152 is 31 st May. A dry day or dry spell is considered as a day with rainfall less than 0.85mm. 9
Daily rainfall for year 2005 200 150 100 50 0 100 200 300 Days of the year in day numbers 120 Daily rainfall for year 2006 100 80 60 40 20 0 50 100 150 200 250 300 Days of the year in day numbers 350 10
200 Daily rainfall for year 2007 150 100 50 0 50 100 150 200 250 300 Days of the year in day numbers 350 100 Daily rainfall for year 2008 80 60 40 20 50 100 150 200 250 300 Days of the year in day numbers 350 11
Table 2. Showing the days of the start of the dry spell and their duration. The days are given in days of the year and in day numbers. The year indicated by zero (0), means during that month in those years there were no dry spell of 10 days or more. Dates and number of days of dry spell Day Numbers Year March April May March April May 1979 21 Mar(11) 0 0 81 0 0 1980 0 0 0 0 0 0 1981 0 0 0 0 0 0 1982 11 Mar (11) 0 0 71 0 0 1983 0 0 0 0 0 0 1984 10 Mar (14) 0 10 May (16) 70 0 131 1985 0 0 19 May (13) 0 0 140 1986 11 Mar (13) 0 0 71 0 0 1987 0 0 0 0 0 0 1988 0 0 0 0 0 0 1989 0 18 Apr (10) 0 0 109 0 1990 0 7 Apr (11) 0 0 98 0 1991 0 12 Apr (17) 0 0 103 0 1992 0 0 0 0 0 0 1993 0 0 0 0 0 0 1994 0 0 0 0 0 0 1995 0 0 0 0 0 0 1996 0 0 19 May (13) 0 0 140 1997 0 0 16 May (13) 0 0 137 1998 0 0 0 0 0 0 1999 0 6 Apr (12) 4 May (12) 0 97 125 2000 0 0 0 0 0 0 2001 0 0 0 0 0 0 2002 0 0 3 May (15) 0 0 124 2003 21 Mar (10) 9 Apr (10) 0 81 100 0 2004 0 1 Apr (15) 0 0 92 0 2005 17 Mar (14) 0 0 77 0 0 2006 0 0 0 0 0 0 2007 0 0 0 0 0 0 2008 0 0 0 0 0 0 Total nonzero 6 6 6 6 6 6 Earliest 10 March 1 April 3 May Total days of spells for the 3 months Latest 21 March 18 April 19 May 73 75 82 12
The duration of the spell is greater in the month of May with a total of 82 days. May is also the month with the longest spell of 16 days consecutive. But all three months have only 6 years out of 30 with dry spell of 10 days or more. I used Instat to compute the risk, percentages and confidence intervals. I used the dialog as follows: Statistics Simple models Proportions, one sample. In the dialog box, for the data layout I chose summary values from the drop down arrow. Then in the sample size (n) I typed 30 (the number of years) and in successes(r), I typed 6(the number of years with 10 consecutive dry days or more). Then in the analysis method, I chose the exact results, simple normal approximation and normal approximation. The confidence interval is 95%. Then I click ok. The proportions calculated for the 30 years of data. Binomial model, single sample Sample size 30 Successes 6 Proportion 0.200 Approx s.e. of proportion = 0.073 Simple normal approximation: 95% confidence interval for prop. 0.057 to 0.343 The chance of having a consecutive 10- day dry spell for the months of March, April and May is only 6 years in 30 years for all the three months. 24 years out of 30 for the three months, there is no rainfall of less than 0.85mm for 10 consecutive days. The risk of having 10 consecutive days of dry spell is 0.2 or 20%. This gives a rate of once every 5 years or a 5 years return period. The 95% confidence Interval is between 0.077 and 0.386 with standard error of 0.073.We can say that we are 95% confident that the true percentage of the best days of processing during the months of March, April and May lies between 7.7% and 38.6%. 13
Recommendations It is good to note that the three months carry different periods in our season. March marks the end of our rainy season. April is our month of transition from wet to dry season and May is the starting month of our dry season. Based on the results, I would recommend that either of these three months could be considered to process the sea-cucumber for they all carry the same number of risks. The best days for processing lies between 10 th March which is day 70 and 19 th May which is day 140. Therefore the fishermen can consider processing during the second week of March until the third week of May. Appendix The full dataset and metadata of the Seychelles International Airport for 1979 to 2008. Metadata -Data collected is from the Seychelles National Meteorological Services which is situated at the Seychelles International Airport. The Seychelles International Airport is located on the east coast of Mahé, the main island of Seychelles: Location: 4 40 28 South and 55 31 19 East. Altitude is 4m above mean sea-level. Station number is 63980. The station was opened in mid 1971. It is a manned station. Data is 24 hours rainfall, collected everyday and rainfall recorder is in open-air with no obstructions nearby. 14
- Display of monthly totals for rainfall for 1979 to 2008 Display data DIS X33, X35-X46;DEC 0;FIE 6;PRI 100 Row Year Jan_t Feb_t Mar_t Apr_t May_t Jun_t Jul_t Aug_t Sep_t Oct_t Nov_t Dec_t 1 1979 303 162 242 282 22 61 83 27 27 265 229 264 2 1980 168 494 126 206 241 65 97 39 25 53 214 210 3 1981 403 403 209 62 166 35 55 18 18 80 441 550 4 1982 338 9 208 157 68 47 94 110 216 271 296 351 5 1983 610 87 127 213 276 68 163 225 130 112 106 292 6 1984 426 507 55 75 11 50 31 97 72 295 181 235 7 1985 203 150 345 175 120 16 69 372 89 256 140 272 8 1986 258 57 173 169 57 158 100 15 13 107 152 397 9 1987 449 279 128 118 230 109 51 52 160 260 93 58 10 1988 286 75 172 92 87 121 124 178 161 275 202 240 11 1989 316 234 64 87 98 71 277 117 75 234 252 272 12 1990 415 313 140 220 418 59 44 15 72 29 195 127 13 1991 798 95 142 161 177 26 135 27 191 126 146 474 14 1992 439 97 292 463 559 173 22 176 109 181 42 373 15 1993 505 282 186 257 226 54 24 61 190 165 156 157 16 1994 259 430 122 285 36 90 151 367 152 290 270 334 17 1995 236 433 101 149 233 326 130 41 341 250 205 319 18 1996 471 372 237 105 84 89 62 83 301 51 248 209 19 1997 132 212 340 354 95 529 47 694 265 321 325 245 20 1998 478 329 198 152 312 69 75 22 184 68 121 121 21 1999 391 403 168 83 95 40 104 168 161 106 285 238 22 2000 211 452 466 87 83 29 20 46 101 68 332 552 23 2001 357 611 218 187 175 123 38 132 86 9 153 195 24 2002 735 251 285 216 32 92 29 105 457 257 177 134 25 2003 449 137 154 186 490 197 167 43 236 163 129 593 26 2004 560 230 224 171 90 68 25 70 336 295 228 381 27 2005 434 172 196 92 160 436 103 98 163 108 91 607 28 2006 443 55 270 169 41 34 52 98 242 324 370 220 29 2007 446 42 349 169 152 191 59 92 78 106 166 218 30 2008 260 317 149 246 40 85 50 35 32 82 194 436 15
Display of daily rainfall for the year 1979 to 2008 Daily data for: Yr1979 Mon Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec --------------------------------------------------------------------------- Day. --------------------------------------------------------------------- 1 3.5 7.2 33.5 tr 0.4 -- 2.3 0.8 -- -- 32.0 0.3 2 0.6 0.5 17.4 15.8 5.8 0.5 1.3 0.3 -- -- tr 1.4 3 -- tr 12.4 8.1 0.3 -- tr 0.8 tr -- 8.2 0.2 4 -- -- 0.4 2.1 -- 2.3 -- 10.7 tr 1.3 tr 14.7 5 -- -- 5.8 6.3 -- tr 1.0 tr -- tr -- -- 6 -- 8.8 46.0 4.3 -- 2.0 tr 1.0 tr 5.8 -- 11.9 7 59.0 15.7 33.1 1.1 tr 0.5 1.3 0.8 tr -- -- tr 8 tr 0.3 0.5 13.8 -- 11.9 tr -- tr -- tr 0.1 9 1.4 12.7 2.0 14.2 -- tr tr -- 0.9 -- 8.8 5.1 10 1.4 8.6 -- 0.1 tr -- 0.3 -- -- -- 40.4 4.9 11 -- -- -- 1.8 7.4 tr 1.3 1.5 5.4 -- 5.2 22.4 12 25.5 -- tr 10.4 0.5 tr -- tr tr 2.3 17.3 15.4 13 tr -- -- 0.2 -- -- 0.3 -- -- -- 6.6 0.4 14 2.0 -- tr -- -- 7.4 -- 0.8 7.2 -- -- tr 15 5.2 2.8 19.1 1.8 -- -- 2.3 0.5 0.5 0.5 0.5 -- 16 8.2 5.3 63.2 54.9 -- 8.4 17.0 0.5 tr -- -- -- 17 -- 87.2 tr 62.0 0.5 1.8 16.8 1.6 0.8 6.9 -- tr 18 -- 1.3 -- 31.0 -- 0.6 -- 2.9 tr 30.1 1.0 -- 19 -- -- 4.0 7.0 0.7 7.1 7.6 0.8 -- 9.4 17.0 tr 20 tr -- 4.8 0.5 3.1 4.8 tr tr 1.7 60.2 0.3 3.1 21 41.8 0.8 tr 10.6 -- 4.6 tr tr tr tr -- 21.3 22 -- -- -- 0.2 0.8 tr tr tr -- 40.4 -- -- 23 41.1 -- tr 15.8 1.8 -- tr -- tr tr -- 1.7 24 12.4 -- -- -- -- tr tr -- tr 1.0 tr 27.4 25 12.8 -- -- 10.3 1.0 5.7 -- -- -- -- 2.8 0.2 26 12.7 -- -- 3.8 tr -- 5.3 -- -- 3.6 0.7 53.7 27 53.6 8.7 -- 1.1 tr -- 16.7 4.1 2.3 52.3 4.3 35.0 28 tr 2.3 -- tr tr 0.7 9.7 -- 5.6 -- 15.6 -- 29 4.3 -- tr tr 2.8 tr -- 0.8 10.7 36.1 42.6 30 13.5 -- 5.3 tr tr 0.2 0.1 1.5 9.9 32.3 1.9 31 4.4 -- -- -- -- 31.0 0.1 Total (Overall: 1969.3) 303.4 162.2 242.2 282.5 22.3 61.1 83.4 27.2 26.7 265.4 229.1 263.8 Minimum (Overall: 0.0) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Maximum (Overall: 87.2) 59.0 87.2 63.2 62.0 7.4 11.9 17.0 10.7 7.2 60.2 40.4 53.7 Number greater than 0 (Overall: 189) 18 14 13 25 11 15 15 15 10 15 17 21 16