The Seychelles National Meteorological Services. Mahé Seychelles

Transcription

1 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

2 Table of contents Contents Page 1. Background Objectives.4 3. Methodology.4 4. Data and Definitions 5 5. Results and Implications Recommendations Appendix: Metadata 16 Monthly Totals..17 Daily rainfall

3 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 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

4 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 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 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

5 Data and definitions to be used Data to be used is the 30 years rainfall data from 1979 to 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 Annual rainfall totals for the years 1979 to Year The time series plot shows the amount of rainfall totals for the 30 years. Maximum rainfall occurred in 1997 with a maximum of mm and minimum was in 1986 with mm of rainfall. 5

6 Graph 2 and Table 1. Showing the summary values of monthly rainfall (mm) for the 30 years Plot of the monthly rainfall summaries Mean Min Max Median 25% 75% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months 6

7 Table 1. Column Mean Min. Max. Median 25% 75% Jan_t Feb_t Mar_t Apr_t May_t Jun_t Jul_t Aug_t Sep_t Oct_t Nov_t Dec_t 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 Apr_t May_t April is the month amongst the three with the smallest standard deviation and May with the greatest. 7

8 Graph3. Graph showing annual rainfall amount for the three months Mar_t Apr_t May_t Year 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 The minimum was in May as well with 10.7mm in

9 Mar_t Apr_t May_t 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

10 Daily rainfall for year Days of the year in day numbers 120 Daily rainfall for year Days of the year in day numbers

11 200 Daily rainfall for year Days of the year in day numbers Daily rainfall for year Days of the year in day numbers

12 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 Mar(11) Mar (11) Mar (14) 0 10 May (16) May (13) Mar (13) Apr (10) Apr (11) Apr (17) May (13) May (13) Apr (12) 4 May (12) May (15) Mar (10) 9 Apr (10) Apr (15) Mar (14) Total nonzero Earliest 10 March 1 April 3 May Total days of spells for the 3 months Latest 21 March 18 April 19 May

13 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 Approx s.e. of proportion = Simple normal approximation: 95% confidence interval for prop to 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 and with standard error of 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

14 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 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: South and East. Altitude is 4m above mean sea-level. Station number is The station was opened in mid It is a manned station. Data is 24 hours rainfall, collected everyday and rainfall recorder is in open-air with no obstructions nearby. 14

15 - 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

16 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 tr tr tr tr 0.8 tr tr 1.3 tr tr 1.0 tr -- tr tr 1.0 tr tr tr tr 8 tr tr -- tr -- tr tr tr tr tr tr tr -- tr tr tr tr tr tr tr tr tr tr 20 tr tr tr tr tr tr tr tr tr tr tr tr tr -- tr tr tr tr -- tr 1.0 tr tr tr tr tr tr tr tr 2.8 tr tr tr Total (Overall: ) Minimum (Overall: 0.0) Maximum (Overall: 87.2) Number greater than 0 (Overall: 189)