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									Draft 9/20/2004

      Workshop on Climate Variability and Change and Health In Small
                              Island States

                             Nadi, Fiji 14 and 15 September 2004

                                  Meeting Notes

Introduction and welcome by the Director of the Fiji Meteorological Service,
Rajendra Prasad

Overview of the meeting and climate applications, Michael Hamnett

Climate Variability and Change and Health in Small Island States, Nancy Lewis
      (see Powerpoint A: Lewis)

Climate Variability and Climate Forecasting in the Pacific – Janita Pahalad
      (see Powerpoint B: Pahalad #1)

Breakout Groups: Climate and Health in the Pacific Islands: How does climate
      affect and how might it affect health? Brainstorming sessions on important
      health problems influenced by climate, Cheryl Anderson, facilitator
      (See Handout 1)

Report Back:

Dengue, Malaria (Solomons, Vanuatu), NCDs, HIV/Aids, Typhoid, Diarrhea,
Influenza, Filariasis, Ciguatera (Kiribati), Food Poisoning, Leptospirosis
Pesticide Poisoning

Relationship with Climate:

Dengue – wet season, warmer temperature; human behavior (Cook Islands);
low-lying areas brackish water – first cases (Tonga); high magnitude rainfall
events.

Malaria - Declining in the Solomons, malaria control team does not want to
accept that this may in part be due to climate. They argue it has to do with
effective public health programs but climate may be involved. There are issues
concerning reliability of data in both sectors. Malaria varies by season, increases
after tropical cyclones; awareness programs are important. If forecasts were in
the newspaper they would only reach 20% of population.

Noncommunicable Disease diabetes, hypertension, obesity, cancer – food
related – extreme event – tropical cyclones – relief supplies may include food that
is not nutritious.

Typhoid – after rainy season the cases peaks (Samoa)
Gastroenteritis – slight increase in children after flooding (Cook Islands)
Also related to drought – contamination of water supply; contaminated soil; long
drought Ponaphei; contaminated food supplies

Influenza – Cook Islands in the cooler months; sudden changes in seasons; also
spreads fast during the dry season (Samoa); Cooler months people congregate
inside, aerosol transmission

Filariasis – same as other mosquito borne diseases.

Ciguatera – seasonal – balolo season – difficulties in reporting, the ciguatera kit
test is expensive. Related to coral damage; related in Samoa to high Sea
Surface Temperature (SST).

Food Poisoning –spoilage of food – not refrigerated.

Leptospirosis – Fiji – northern region/sugar cane – more leptospirosis
transmitted in rat urine in the wet season – American Samoa – several
fatal cases (May/June) – cooler months.

Pesticide poisoning – logically the rainy season --- no observations.

Malnutrition – droughts; cyclones.

Climate and Health in Fiji, results of the research project, Angela Faanunu
      (See Powerpoint C: Faanunu)

Breakout Groups: How are risks to health influenced by changes in seasons, by
      El Niňo and La Niňa, by tropical cyclones and by droughts. Regional
      Breakout sessions: Federated States of Micronesia and Palau; Fiji and
      Kiribati; Solomons and Vanutatu and Cook Islands, Samoa and Tonga.
      (See Handout 2)

Wednesday, September 15

Overview of Fiji Climate and Health Workshop, September 17-18, 2003,
      Navi Litidamu and Simon McGree
      (See Powerpoint D: Litidamu and Report from National Workshop)

Organizers were Fiji School of Medicine, the Fiji Meteorological Service, the
University of Hawaii Social Science Research Institute and the East West Center
with support from the U.S. National Oceanographic and Atmospheric
Administration.

Participants were doctors, environmental health officers and meteorological
officers. It provided the opportunity for individuals from the two sectors to discuss
issues of common concern. Data problems, especially with respect to the
epidemiological data, were discussed. Participants from the health sector were
made aware of the forecast products that might be useful in the health sector and
discussed further needs. Recommendations included providing thee monthly
seasonal forecasts including level of skill and forecasts to provide ample warming
at beginning and end of wet and dry seasons and onset of climate changes
associated with ENSO events. Health officers asked for a summary of rainfall and
temperature patterns for preceeding 12 months and, if possible, a seasonal
forecast going out as far as 12 months including level of skill. The Fiji
Meteorological Service and the Fiji School of Medicine along with the Ministry of
Health will work together to develop ways in which climate forecasts can improve
public health services in Fiji. The Permanent Secretary of Health wrote a letter to
the Permanent Secretary of the Ministry of Transport and Civil Aviation
requesting that the Meteorological Service provide specialized climate forecast
services to the Ministry of Health at the divisional and district levels. Navi
Litidamu and Simon McGree were interviewed by Fiji TV which resulted in
interest by the Minister of Health.

Comments by Simon McGree

Prior to the beginning of this project, Ministry of Health personnel had very little
knowledge of what the Meteorological Service did. The information they provided
was thought to be too technical. They requested a clear, one page summary.
The top half of the page should have a summary of weather over the past 1-3
months; the bottom half should have climate predictions for 1 to 3 months. I
important information includes temperature, rainfall, cyclone season predictions
(Nov to April), SST predictions (there is probably not enough long term local data
to do this). The problems with accuracy in the press were discussed. It is
important to develop good connections with the media and to provide press
releases.

Breakout Groups: What public health measures are currently being used to
             address important diseases? How could climate information be
             used to do it better?
Report Back:

Kiribati – mosquito control – public awareness, vector control at port and airport;
house survey to clean up breeding grounds; national clean up day; Health
officials in Kiribati are interested in climate and meteorological information,
although it is not provided at this time. Forecasts would be useful for dengue.

Solomon Islands – malaria – methods used to reduce risk – bednets, awareness,
larval survey, dengue fever – proper disposal of trash/water containers. Is
climate forecast information used? There is a general understanding it is related
to climate. There is a need for information to be made known to the health
communities. For Gastroenteritis and skin disease the use health
promotion/awareness, stressing the importance of personal hygiene.

Federated States of Micronesia and Palau. Gastroenteritis and dengue. The
measures used include: public awareness, education, survey, port of entry,
indoor/out door spraying, food safety and water safety, campaigns. They would
like the weather service to provide information on climate and rainfall and
frequency of cyclones per year as well as ENSO updates and tidal information.
They have an effective public health campaign during the 97-98 drought.

The Cook Islands, Samoa and Tonga. Dengue – there were recent fatalities in
Tonga, but last year was worse. If correlated with climate, there are actually more
cases of other diseases, but dengue can be fatal. Cook Islands - surveillance of
affected areas, awareness in schools, clinics, spraying. Because of the life cycle
of the larva they spray again 10-14 days later. They have a network PPHSN –
Pacific Public Health Surveillance Network (SPC). This is the answer to the
second question. It could also be used as a means to convey any forecast
climate information. Climate data used indirectly by those in the health sector.
Importance of combining resources for each specific country. Those in the health
sector are sometimes prone to keep data to themselves. Who does this data
belong to? Ownership issues. There are also issues surrounding confidentiality
of health data. Data needs to stay within country – analysis should have
relevance. This message needs to be conveyed to the politicians. There are
implications (economic, tourism) with respect to the release of sensitive
epidemiological information. SPC regional epidemiological database. Tonga has
a climate data rescue project – we need health data rescue project. WMO
DARE. There was considerable discussion during the meeting of a health data
rescue project similar to the climate data rescue project although this may not be
feasible given the problems with the data and competing issues within the health
sector.


Climate Forecast Services in the Pacific Islands

                    PEAC & US National Weather Service, NIWA, Michael
                     Hamnett
                    Australian Bureau of Meteorology, Janita Pahalad

PEAC & US National Weather Service, NIWA, Michael Hamnett
           (See Powerpoint E: Hamnett # 1 and Powerpoint F: Hamnett #2))

Australian Bureau of Meteorology, Janita Pahalad
              (See Powerpoint G Pahalad # 2 and http://www.bom.gov.au/climate/pi-
              cpp.index.shtml)

Climate Service from National Meteorological Services (brief reports by Met
Services that provide climate services)

See Appendix A for documents submitted by Wilfred Nanpei (Pohnpei) and Selu
             Finaulahi (Tonga)

Fiji – 9 individuals in climate section, 4 scientists and 5 technical; there are
       considerable number of stations, for climate and synoptic (3 hr.) they have
       close to 40 and for rainfall almost 80 – also automatic weather stations –
      11. Provides basic and processed data as needed to wide range industry
      and services and students and now also for research (Dr. Lal visiting
      faculty at USP; IPCC). Fiji has been in climate prediction business since
      99 with rainfall, and now adding temperature with Janita’s project; climate
      variability and streams analysis with APN (Asia Pacific Network for Global
      Change Research). Climate and health, climate and sugar. Products:
      Fiji Islands Weather Summary – the last month – rainfall past three
      months, climate extremes, ENSO, climate prediction – Fiji and Australian
      rainman; information sheets – climatological summaries; historical floods,
      cyclones, droughts, developing a regional SW Pacific tropical cyclone
      capacity; GIS MapInfo to digitize tropical cyclone information. Digitizing
      tropical cyclone SE Pacific, past thirty years. Janita – there has been
      significant progress since 93/94 –recognition that climate is important. No
      user fees at this point. May charge a fee if the data will be used for a
      product for resale, e.g. construction and tourism industry. They will put
      resources back into observation network. They rely almost completely on
      volunteer observers that is no longer entirely feasible.

Tonga – providing data to students, construction industry, summary reports,
     annual summaries. Hope to get ENSO forecasting capacity.
            See Word Document #1 Tonga Met

Samoa – they are developing prediction capability, focusing on collecting,
    archiving and analyzing data. Also dissemination – but not in a systematic
    manner. Tourism and other sectors are interested. Give data to a lot of
    students, mainly geography students at secondary and tertiary levels.
    Give them averages based on historical record. Climate section heavily
    involved in national disaster committee chaired by Prime Minister.
    Representatives of climate and meteorology/climate are involved in
    international conventions. Data provided to hydro scheme. Hope to work
    with PICPP. Samoa has the software, but needs to test and verify
    internally before it is given to the public. Have had stakeholder
    workshops. Expand the network. Most information from Upolu. Need to
    expand to other islands. Digitize archival information. 100 years of
    records, 30 years digitized (partial), data management system to be
    developed using GIS. Would like stronger partnerships with stakeholders.
    No communication between meteorological service and the public; health
    sector has a much longer record and they are trusted, it would be a good
    idea to piggyback with health. Would like to see higher prioritization of
    metrological service; it was not mentioned in most recent development
    strategy. Major issues are resources. J. Pahalad commented that if it
    saves the country money, the government will listen. We have to get their
    interest, although this is a bit of a ‘chicken and egg’ issue.

Vanuatu – most people think only in terms of cyclones. They have been
     producing a climate bulletin since mid 2000 using models from IRI and
     CPC. They have 30 clients, including schools, health, agriculture.
     Reviewed after 6 mos. – ‘at least it is better than nothing’; island climate
     update – SST and SOI (too complicated for end users). A big problem is
             that three languages are spoken in Vanuatu and pidgin is not really a
             written language; there are also demands from the French speakers. 80%
             of the population is rural; have held an end-users workshop. Now there is
             a demand for climate forecasts – agriculture, education, Chamber of
             Commerce (mostly deal with commercial farmers), health – environment
             officers workshop when they go back. With development of the AusAid
             project - used June, July, Aug – off for Aug. Agriculture, forestry,
             livestock, tourism key for economic development. Awareness programs.
             Only 4 staff (one with climate); monthly bulletin, annual and quarterly
             summary. Make sure that health is included in the stakeholders workshop
             for AusAid project.

      Cook Islands – does not directly supply information to clients, does work with
            NIWA and PEAC - convey their information to clients. With respect to the
            AusAid project, there is a lot of interest. Have chosen banana (?) and
            pearl industries. Health folks need to come up with data – partnership is
            already there. They would like to pursue other products. There is much
            that can be done with new communications technologies. The
            meteorological service has developed a three month forecasting
            capability.

QUESTION: If an ENSO develops in the next year, how would that affect your timeline?
           Are we prepared to use forecast information? How could it be used to
           promote the importance of forecast information.

      Public Health and Meteorological Service in parallel session

             What are options for communicating climate information to officials in public
             health? (Met/Weather Service Officials)

             Given what we now know, what kinds of climate information would be
             useful in public health? What else do we need to know about diseases
             and disease patterns to maximize climate forecasts in public health and
             other sectors? (Health officials)

      The reports from these groups are included in the Recommendations.
Appendix A written reports from Meteorological Services

          Climate Change, Climate Variability and Health Workshop
                     Nadi, Fiji, 14-15 September 2004

Agenda item xx: Country reports on climate change & variability in relation to Health.

             CLIMATE CHANGE & VARIABILITY VS. HEALTH IN TONGA

                                 (presented by Tonga)


                                         SUMMARY
                        Informs the meeting of the current climate
                        trends in Tonga, its effects on human health
                        and potential future trends and applications



Introduction

        Climatological records for Tonga are reasonable enough to relate to climate
change and variability. Records date back to the 1940s. Data collected throughout
Tonga indicates a marked increase in temperature while rainfall trends indicate drier
conditions in southern Tonga. Recently, sea level data suggest an increase in sea level
rise while there is an indication of increased tropical cyclone activity. These changes in
climate have had negative effects of human health. Often a consequence on effects to
the environment.

Climate Summary of Tonga

        Tonga’s climate reflects its position within the trade wind zone of the South
Pacific. Mean temperatures range from 23-28oC and humidity persists around 75%.
Wind speeds norms range from 12 to 15 knots from the east to southeast, although
tropical cyclones can bring strong winds during the cyclone season (Nov-Apr). Tonga
averages 1 tropical cyclone per year.

       The climate of Tonga is characterized by the contrast between the wet (Nov-Apr)
and dry (May-Oct) season. At least 60-70% of the annual rainfall occurs during the wet
season. The northern islands of Tonga receive more rainfall (approx 2500 mm a year),
owing to the seasonal proximity of the SPCZ, while the southern islands receive about
1700 mm of rainfall a year.

       Severe water shortages can occur in places during the dry season, particularly if
the precipitation during the wet season has been lower than usual. During El Nino
events, the drought can be devastating.

        Temperatures also show some variance. Mean annual temperatures in Northern
Tonga averages about 27oC while in the south it is about 24oC, showing a difference in
daily and seasonal variations with latitude.
Observed climate chnage trends in Tonga

Temperature
                                                                                                                                 18
                                                                                                                                                                                       E
                                                                                                                                 16                                                                                       Series1
                      1949 1954 1959 1964 1969 1974 1979 1984 1989 1994 1999                                                                                                                                              Series2
                                                                                                                                 14
                  1.50                                                                                                                                                                         E          EE




                                                                                                                  number of TC
                             Annual   5 year mean       Linear (Annual)                                                          12                                                                                       Linear (Series1)
                                                                                                                                                                  E       EE                                              Linear (Series2)
                  1.00                                                                                                           10
                                                                                                                                               E           E
 Anomaly(deg C)




                  0.50                                                                                                           8                                                                                 y = 0.0742x + 7.521
                                                                                                                                                                                                                          2
                                                                                                                                 6                                                                                       R = 0.063
                  0.00
                                                                                                                                                   E
                                                                                                                                 4
                  -0.50                                                                                                          2                                                                                   E
                                                                                       y = 0.0289x - 0.7191                      0
                  -1.00                                                                     R2 = 0.5043                               59/60 62/63 65/66 68/69 71/72 74/75 77/78 80/81 83/84 86/87 89/90 92/93 96/97 99/2000 2002/03
                  -1.50                                                                                                                                                           season

                                                                                                                  Figure 4: tropical cyclone trend for Tonga and the South
Figure 1. : Temperature trend for Nuku’alofa                                                                      Pacific



Rainfall trend

                      1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
                  1200
                            Annual 5 year run mean Linear (Annual) y = -2.5471x + 85.812
                  1000
                                                                        R2 = 0.0089
                   800
                   600
 Anomaly(mm)




                   400
                   200
                      0
                   -200
                   -400
                   -600
                   -800
                  -1000


Figure 2: Rainfall trend for Nuku’alofa




Sea level

                      1993   1994     1995          1996       1997         1998       1999         2000   2001
                   0.2

                  0.15

                   0.1
 Anomaly(m)




                  0.05

                     0

                  -0.05

                   -0.1                                                                  y = 0.0014x - 0.0759
                                                                                              R2 = 0.312
                  -0.15
                                                     Monthly        6 month run mean    Linear (Monthly)

                   -0.2


Figure 3. : Sea level trend for Nuku’alofa


Tropical cyclone trend
Future global temperature and sea level projections (IPCC 2000)

Date        Global        Global         Per capita CO2                Global          Global
            population    GDP            income      concentration temperature sea level
            (billions)    (trillions     ratio       (ppm)             change (°C) rise (cm)
                          of US$/yr)
2050         8.4-11.3     59-187         2.4-8.2     463-623           0.8-2.6         5-32
2100         7.0-15.1     197-550        1.4-6.3     478-1099          1.4-5.8         9-88
Per capita income ratio - ratio of developed countries and economies in transition to developing
                          countries (Annex I to non-Annex I countries)
Temperature change - averaged across simple climate model runs emulating results of seven
                          AOGCMs with a climate sensitivity of 2.8°C for the range of 35 fully
                          quantified SRES emissions scenarios
Sea level rise          - based on global mean temperature changes but also accounting for
                          uncertainties in model parameters for land ice, permafrost, and
                          sediment deposition


Health Impacts of Climate Change and Variability in Tonga

        Tonga experiences the impacts of a changing and variable climate system.
Much of which is consistent with the anticipated impacts of global climate change.
Climate affects health directly through extreme events such as cyclones, droughts,
floods, storm surges, landslides, or heat waves.

       Assessments of impacts related to climate change from the Tonga Health
Department are that some diseases are favored depending on the season. There is
evidence, locally, that dengue fever affects the Tonga islands during the onset of ENSO
(enhanced rainfall). Dengue Fever is the most common weather related disease in
Tonga. Reports from the Health Department, suggest that the outbreak of Dengue fever
coincides with the local wet season. The pattern is consistent with the warm and wet
season (November – April) which provides the right environment for Aedes Egypdi
(mosquitoes), Aedes Tonga and Aedes Tabu to thrive.

       Sea Level Rise coupled with low rainfall also result in contamination of drinking
water in low lying and costal areas in Tonga, most notably the small isolated islands of
the Ha’apai and Vava’u groups. Tropical cyclone events and associated storm surge
also contribute.

       It should be noted that weather extremes such as floods or droughts as well as
severe cyclones have a negative effect on food and water supplies. The supply of
freshwater is limited especially on atolls and on other low lying islands that are
dependent on surface catchments. During the recent droughts, associated with El Nino
events, the Government of Tonga has had to ship millions of liters of water to the
Ha’apai group to facilitate live.

National support for improved climate services.

       Recently, the Government of Tonga has approved the establishment of a
National Weather Forecasting Centre. A move to establish a national authority and
capacity in meteorology. Part of the excersice includes the enhancement of Tonga’s
ability to address climate change and variability.

         A seasonal prediction project (statistical model) has been implemented in Tonga
which involves the Meteorological service and the various users. The project, which is
funded by the Australian Government, addresses the need for the National
Meteorological Service to provide the necessary services required by the National
Strategic Action Plan 7 for sustainable socio-economic development. The project is in its
initial stages , but it is anticipated that it will yeild improved climate prediction
capabilities.

       The Tonga Meteorological Service, as part of its endeavor to establish its service
has established a local weather and climate website at www.mca.gov.to/Met/. The
service is free of charge and is designed to encourage free exchange of data between
government and non-government agencies and the national meteorological authority.




Regional and international support

        International and Regional agencies that have supported Tonga’s project for
improved meteorological and climate services includes, the National Atmospheric and
Water Institute (NIWA), Bureau of Meteorology (BOM), Australia, the South Pacific
Regional Envirnmental Program (SPREP), University of Hawaii through the National
Meteorological Centre par the Government of the United States, The World
Meteorological Organization and the United Nations body for Climate Change
(UNFCCC) to name a few. These support are usually in the form of training, provision of
specialised services and technical support.

Public Awareness

       National awareness programs are on going promoting programs to raise
awareness of stakeholders and public in general with respect to Climate Change,
Climate Variability and Sea Level Rise on the national radio and local television. The
National Health authority, Environment Department, Natural Disaster Office and
Meteorological Service all provide different awareness programs for the public. During
recent programs the Health Department has concentrated on the public awareness of
mosquito borne diseases and the eradication of elephantitis and dengue fever in Tonga.
Other climate related diseases such as those of the skin are also touched on by the
Health authority from time to time.

Problem to be addressed

      It is the view of the National Meteorological Service that the main limitations in
addressing of illnesses caused by climate change and variability include:
           1. the poor collection and analysis of data. Many health related impacts of
              climate variability can be identified, prevented and forecast by raising the
              local capacity to collect and manage data.

           2. Little research work carried out on both the current and future effects of
              climate change and variability on the health sector in Tonga.

           3. Little access to specialised training.


           ___________________________________________



Report from Wilfred Nanpei
National Weather Service
Weather Service Office
Pohnpei
Federated States of Micronesia


Basic Responsibilities

       1. Data Collection (surface and upper air observations)
             a. surface observation:
                -hourly and six hourly observations
                -12hour and daily climate report
                -hourly, daily and monthly rainfall collection


              b. upper air observations
                 -balloon and radiosonde: collection of pressure, wind direction and
                 speed, relative humidity other atmospheric conditions.

       2. Outreach
             Good Public Awareness
                   -targeting schools
                   -community centers

             *have to make sure that your message is SIMPLE and CLEAR
                     -choice of vocabulary in weather statements, form of language
       3. Forecasting
             -3 day forecasting w/support from WFO Guam
                     e.g. AVN models, wind analysis,
             -WFO Guam releases 5-day forecast for all Micronesia

       4. Climate
             WSO Pohnpei DO NOT have a climate division
                      -monthly and annual climate forms are released by NCDC.
                      -non government agencies need to buy data online from NCDC


       5. Cyclone Forecasting
             Supported by JTWC (cyclone track, location and intensity) and WFO
             Guam (public statements)


Summary:
     WSO Pohnpei – mostly data collection (surface and upper air)
                   medium for getting the message out to Public

       Goals: to be able to do our own weather forecasting (have already started a 3day
forecast but still with a lot of support from Guam Forecast Office.)

								
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