**4. Web-based information tools to disseminate climate monitoring and seasonal prediction products**

CREWS-PNG is a successor of the Pacific projects of the ICCAI, and its implementation strategy is based on similar approaches to develop climate monitoring and seasonal prediction products as well as means of disseminating information. It is important to ensure that climate monitoring and subseasonal-to-seasonal prediction products are not only of high accuracy but also are delivered to users in a timely manner and in a way that can be utilized in their decision-making. As part of the PASAP and PACCSAP activities, the Pacific Seasonal Prediction Portal was developed to disseminate climate data and dynamical climate model-based forecast products through a range of web-based information tools (**Figure 9**). This portal could be accessed through the Australian Bureau of Meteorology's website: http:// www.bom.gov.au/climate/pacific/projects.shtml.

**163**

**Figure 10.**

*seasons.*

*Climate Risk and Early Warning Systems (CREWS) for Papua New Guinea*

The Pacific Seasonal Prediction Portal provides users with access to a range of products for monitoring and prediction of weather and climate extremes. Here we briefly introduce some of these products, including key features of the tropical cyclone (TC) and seasonal prediction portals, including extreme ocean tempera-

TCs are severe weather events which affects Pacific Island Countries every year, causing loss of life land property. Damage caused by TCs is not only caused by destructive winds but also torrential rain, high ocean waves and storm surge. To be prepared for the multi-hazards associated with TCs, knowledge about regional historical cyclone tracks are important. Meteorological agencies of the Pacific Island Countries as well as numerous other users utilize the portal to access such information for areas of interest. As an example, tracks of 80 tropical cyclones which passed through exclusive economic zone of PNG between the 1969–1970 and 2016–2017 tropical cyclone seasons retrieved through the Southern Hemisphere Tropical Cyclone Data Portal are presented in **Figure 10**. A comprehensive description of the Southern Hemisphere Tropical Cyclone Data Portal could be found in [23], which also provides readers with the users' guide to

the web-based information tool to select, retrieve, display and analyse TC data.

*Tracks of 80 tropical cyclones from the Southern Hemisphere Tropical Cyclone Data Portal which passed through the exclusive economic zone (EEZ) of PNG between the 1969–1970 and 2016–2017 tropical cyclone* 

The importance of seasonal climate prediction to assist with decision-making is recognized by users from climate-sensitive sectors around the world. Seasonal climate outlooks at various levels—national, regional and global—are operationally produced by NMHSs, Regional Climate Centres (RCCs) and the WMO providing users with vital information about state of the El Niño-Southern Oscillation and its expected development, plus seasonal climate outlooks for temperatures, rainfall and a variety of other variables. Climate outlooks at the global scale are disseminated by the WMO, while at a regional level, WMO GPC LRFs and RCCs play a leading role in this task. In the Pacific, WMO GPC LRF Melbourne is tasked with disseminating outputs from the dynamical climate model POAMA to RCCs and NMHSs in the region. As an example, the seasonal prediction of sea surface temperature in the Pacific for January to March 2019 is presented in **Figure 11**, demonstrating a significant oceanic warming in equatorial central Pacific—a possible precursor to El Niño. The livelihood of many people in Pacific Island Countries is highly dependent on the productivity of the oceans including coral reefs which surrounds the islands. A

*DOI: http://dx.doi.org/10.5772/intechopen.85962*

tures and potential coral bleaching.

**Figure 9.**

*Home page of the Pacific Seasonal Prediction Portal.*

*Drought - Detection and Solutions*

enhance the Bureau's capability in weather and climate prediction. Since August 2018 the Bureau's operational climate forecast system for multi-week, monthly, seasonal and longer-range climate outlooks is ACCESS-Seasonal (ACCESS-S). The atmosphere and land model components of ACCESS-S operate at an approximate global resolution of 60 km, providing far greater detail than POAMA which had an approximate resolution of 250 km. The multi-week and seasonal performance of ACCESS-S has been evaluated for Australia based on a 23-year hindcast set and compared to the previous operational system, POAMA [22]. However, hindcast skill and calibration have not been assessed for other countries in the region including PNG. One of the key tasks for CREWS-PNG is to assess and utilize outputs of ACCESS-S in order to produce accurate multi-week and seasonal climate outlooks

**4. Web-based information tools to disseminate climate monitoring and** 

CREWS-PNG is a successor of the Pacific projects of the ICCAI, and its implementation strategy is based on similar approaches to develop climate monitoring and seasonal prediction products as well as means of disseminating information. It is important to ensure that climate monitoring and subseasonal-to-seasonal prediction products are not only of high accuracy but also are delivered to users in a timely manner and in a way that can be utilized in their decision-making. As part of the PASAP and PACCSAP activities, the Pacific Seasonal Prediction Portal was developed to disseminate climate data and dynamical climate model-based forecast products through a range of web-based information tools (**Figure 9**). This portal could be accessed through the Australian Bureau of Meteorology's website: http://

that will improve drought prediction for the country.

www.bom.gov.au/climate/pacific/projects.shtml.

**seasonal prediction products**

**162**

**Figure 9.**

*Home page of the Pacific Seasonal Prediction Portal.*

The Pacific Seasonal Prediction Portal provides users with access to a range of products for monitoring and prediction of weather and climate extremes. Here we briefly introduce some of these products, including key features of the tropical cyclone (TC) and seasonal prediction portals, including extreme ocean temperatures and potential coral bleaching.

TCs are severe weather events which affects Pacific Island Countries every year, causing loss of life land property. Damage caused by TCs is not only caused by destructive winds but also torrential rain, high ocean waves and storm surge. To be prepared for the multi-hazards associated with TCs, knowledge about regional historical cyclone tracks are important. Meteorological agencies of the Pacific Island Countries as well as numerous other users utilize the portal to access such information for areas of interest. As an example, tracks of 80 tropical cyclones which passed through exclusive economic zone of PNG between the 1969–1970 and 2016–2017 tropical cyclone seasons retrieved through the Southern Hemisphere Tropical Cyclone Data Portal are presented in **Figure 10**. A comprehensive description of the Southern Hemisphere Tropical Cyclone Data Portal could be found in [23], which also provides readers with the users' guide to the web-based information tool to select, retrieve, display and analyse TC data.

The importance of seasonal climate prediction to assist with decision-making is recognized by users from climate-sensitive sectors around the world. Seasonal climate outlooks at various levels—national, regional and global—are operationally produced by NMHSs, Regional Climate Centres (RCCs) and the WMO providing users with vital information about state of the El Niño-Southern Oscillation and its expected development, plus seasonal climate outlooks for temperatures, rainfall and a variety of other variables. Climate outlooks at the global scale are disseminated by the WMO, while at a regional level, WMO GPC LRFs and RCCs play a leading role in this task. In the Pacific, WMO GPC LRF Melbourne is tasked with disseminating outputs from the dynamical climate model POAMA to RCCs and NMHSs in the region. As an example, the seasonal prediction of sea surface temperature in the Pacific for January to March 2019 is presented in **Figure 11**, demonstrating a significant oceanic warming in equatorial central Pacific—a possible precursor to El Niño.

The livelihood of many people in Pacific Island Countries is highly dependent on the productivity of the oceans including coral reefs which surrounds the islands. A

#### **Figure 10.**

*Tracks of 80 tropical cyclones from the Southern Hemisphere Tropical Cyclone Data Portal which passed through the exclusive economic zone (EEZ) of PNG between the 1969–1970 and 2016–2017 tropical cyclone seasons.*

dramatic impact of climate change on the health of coral reefs has been observed in recent decades due to the increase in ocean acidification and especially due to increase in frequency and intensity of extreme ocean temperatures which led to severe coral bleaching events and impacts on marine life [24]. Disseminating early warnings

#### **Figure 11.**

*Seasonal prediction of sea surface temperature in the Pacific for January–March 2019 based on outputs of POAMA retrieved through the Pacific Seasonal Prediction Portal—WMO GPC LRF Pacific Seasonal Prediction.*

#### **Figure 12.**

*Seasonal prediction of sea surface temperatures around Kiribati based on outputs of POAMA retrieved through the Pacific Seasonal Prediction Portal—extreme ocean temperatures and coral bleaching.*

**165**

the DFAT.

**Conflict of interest**

Declaration: there is no conflict of interest.

*Climate Risk and Early Warning Systems (CREWS) for Papua New Guinea*

about possible extreme ocean temperatures, e.g. because of a coming El Niño event, is essential—it provides local government authorities with vital information 2–3 months in advance allowing them to implement protective measures. For example, the spatial distribution of predicted sea surface temperatures around Kiribati is presented in **Figure 12** (the forecast for January 2019 is based on outputs of POAMA; model was initialized on December 02, 2018). Extreme ocean temperatures in some areas of exclusive economic zone of Kiribati are expected to exceed 1.3°C compared to climatology (1982–2010), potentially leading to coral bleaching in those areas. CREWS-PNG is taking the outlined above approach to disseminate climate information based on outputs of the new ACCESS-S dynamical climate model as part of its implementation strategy. The introduction of impact-based drought forecasts and associated risk-based warnings for improved decision-making is planned to be delivered through a specialized web-based information tool which will be an integral part of the Pacific Seasonal Prediction Portal. Products and climate services will be developed and implemented based on close consultation with stakeholders

Climate monitoring combined with skilful subseasonal-to-seasonal climate prediction enables NMHS to provide their governments, industry sectors and local communities with accurate information to assist in their decisions around how to adapt to climate variability and change. CREWS-PNG will contribute significantly to enhance EWS in PNG, and it is envisaged that cutting edge weather and climate monitoring and prediction products developed for PNG under this project could be expanded to include NMHS across the Asia-Pacific region. The result would be a significant advance for climate services provided by meteorological agencies of

Climate Risk and Early Warning Systems international initiative and the WMO provided financial support for the CREWS-PNG project. The Australian Government Department of Foreign Affairs and Trade (DFAT) funded the PNG-CDP project. Projects of the Pacific Adaptation Strategy Assistance Program and the Pacific-Australia Climate Change Science Adaptation Planning program of the International Climate Change Adaptation Initiative were financially supported by the Australian Agency for International Development (AusAID), the Australian Government Department of Climate Change and Energy Efficiency (DCCEE) and

*DOI: http://dx.doi.org/10.5772/intechopen.85962*

to understand their decision-making requirements.

**5. Conclusions**

LDCs and SIDS in the region.

**Acknowledgements**

#### *Climate Risk and Early Warning Systems (CREWS) for Papua New Guinea DOI: http://dx.doi.org/10.5772/intechopen.85962*

about possible extreme ocean temperatures, e.g. because of a coming El Niño event, is essential—it provides local government authorities with vital information 2–3 months in advance allowing them to implement protective measures. For example, the spatial distribution of predicted sea surface temperatures around Kiribati is presented in **Figure 12** (the forecast for January 2019 is based on outputs of POAMA; model was initialized on December 02, 2018). Extreme ocean temperatures in some areas of exclusive economic zone of Kiribati are expected to exceed 1.3°C compared to climatology (1982–2010), potentially leading to coral bleaching in those areas.

CREWS-PNG is taking the outlined above approach to disseminate climate information based on outputs of the new ACCESS-S dynamical climate model as part of its implementation strategy. The introduction of impact-based drought forecasts and associated risk-based warnings for improved decision-making is planned to be delivered through a specialized web-based information tool which will be an integral part of the Pacific Seasonal Prediction Portal. Products and climate services will be developed and implemented based on close consultation with stakeholders to understand their decision-making requirements.
