Part of the book: Modern Climatology
Tropical cyclones (TCs) frequently affect coastal areas of Australia and islands in the tropical Indian and Pacific oceans. Multi-hazards associated with TCs (destructive winds, storm surges and torrential rain) have dramatic impact on population and infrastructure. Accurate forecasting of TC seasonal activity is an important part of a Climate Risk Early Warning System (CREWS) for improving resilience of the society to potentially destructive impacts of TCs. Currently, a statistical model-based prediction of TC activity in the coming season is used for operational seasonal forecasting in the Australian region and the South Pacific Ocean. In this chapter, a possibility of improving the accuracy of seasonal TC prediction using advanced statistical model-based approaches is demonstrated. It is also demonstrated that an alternative approach—dynamical (physics-based) climate modelling—is promising for skilful seasonal TC forecasting. Using improved statistical and dynamical model-based methodologies for TC seasonal prediction as an integral part of the CREWS will provide valuable information about TC seasonal variability and will assist with decision making, responses and adaptation in island countries.
Part of the book: Tropical Cyclone Dynamics, Prediction, and Detection
To improve monitoring of extreme weather and climate events from space, the World Meteorological Organization (WMO) initiated the space-based weather and climate extremes monitoring demonstration project (SEMDP). Presently, SEMDP is focused on drought and heavy precipitation monitoring over Southeast Asia and the Pacific. Space-based data and derived products form critical part of meteorological services’ operations for weather monitoring; however, satellite products are still not fully utilized for climate applications. Using SEMDP satellite-derived precipitation products, it would be possible to monitor extreme precipitation events with uniform spatial coverage and over various time periods – pentad, weekly, 10 days, monthly and longer time-scales. In this chapter, SEMDP satellite-derived precipitation products over the Asia-Pacific region produced by the Earth Observation Research Center/Japan Aerospace Exploration Agency (EORC/JAXA) and the Climate Prediction Center/National Oceanic and Atmospheric Administration (CPC/NOAA) are introduced. Case studies for monitoring (i) drought in Australia in July-October 2007 and September 2018 and (ii) heavy precipitation over Australia in December 2010 and Thailand and the Peninsular Malaysia in November-December 2014 which caused widespread flooding are also presented. Satellite observations are compared with in situ data to demonstrate value of satellite-derived estimates of precipitation for drought and heavy rainfall monitoring.
Part of the book: Rainfall
Developing and least developed countries are particularly vulnerable to the impact of climate change and climate extremes, including drought. In Papua New Guinea (PNG), severe drought caused by the strong El Niño in 2015–2016 affected about 40% of the population, with almost half a million people impacted by food shortages. Recognizing the urgency of enhancing early warning systems to assist vulnerable countries with climate change adaptation, the Climate Risk and Early Warning Systems (CREWS) international initiative has been established. In this chapter, the CREWS-PNG project is described. The CREWS-PNG project aims to develop an improved drought monitoring and early warning system, running operationally through a collaboration between PNG National Weather Services (NWS), the Australian Bureau of Meteorology and the World Meteorological Organization that will enable better strategic decision-making for agriculture, water management, health and other climate-sensitive sectors. It is shown that current dynamical climate models can provide skillful predictions of regional rainfall at least 3 months in advance. Dynamical climate model-based forecast products are disseminated through a range of Web-based information tools. It is demonstrated that seasonal climate prediction is an effective solution to assist governments and local communities with informed decision-making in adaptation to climate variability and change.
Part of the book: Drought