Risk of Drought and Extreme Winds under Climate Change

Science Centres: Climate

These are two 1-year projects that extend the regional modelling work, addressing future changes in drought risk and extreme winds under a warming climate.

The Problem

Climate change will create many challenges and opportunities for New Zealand’s agriculture and forest industries. Productivity will increase in some areas and a wider selection of species will become suitable, but at the same time an increase in a number of potential threats could occur: high temperatures, drought, wind damage, fire risk, and increased insect and plant disease damage. Of these various threats, drought is the hazard that could have the largest effect on the New Zealand economy, and changes in extreme winds is the factor least understood at this time.

The Solution

The drought project will significantly advance previous preliminary estimates of how drought severity and frequency will change as global warming effects New Zealand.

This will be achieved by:

  • Applying the latest IPCC global model projections (2007), to our higher resolution local climate model. The latest IPCC predictions show significant changes in likely seasonal and geographic rainfall patterns compared to the projections from 2001.
  • using regional scenarios from a much wider range of climate models to develop a risk assessment methodology
  • including solar radiation as a predictor of evapotranspiration (PET)
  • Considering more complex soil moisture balance calculations, and the sensitivity of plants to increased carbon dioxide levels

The wind project will quantify for the first time how the risk of strong winds is likely to change for New Zealand over the 21st century.

The key steps involve:

  • Preparing the various data sets required to diagnose weather types, storm tracks and extreme winds, including extending NIWA’s archive of IPCC model data.
  • Developing projections of changes in circulation and extreme winds across the range of climate model and future emissions scenarios, using a mix of low-resolution global model data and high-resolution regional model data.

The Result

These two 1-year projects began January 2009.