University of East Anglia

About: University of East Anglia is a education organization based out in Norwich, Norfolk, United Kingdom. It is known for research contribution in the topics: Population & Climate change. The organization has 13250 authors who have published 37504 publications receiving 1669060 citations. The organization is also known as: UEA.

Regional climate impacts of the Southern Annular Mode

Abstract: [1] Previous work on the influence of the Southern Annular Mode (SAM) on surface climate has focused mainly on individual countries. In this study we use station observations of temperature and rainfall to identify the influence of the SAM on land regions over the whole of the Southern Hemisphere. We demonstrate that the positive phase of the SAM is associated with a significant cooling over Antarctica and much of Australia, and a significant warming over the Antarctic Peninsula, Argentina, Tasmania and the south of New Zealand. The positive phase of the SAM is also associated with anomalously dry conditions over southern South America, New Zealand and Tasmania, due to the southward shift of the stormtrack; and to anomalously wet conditions over much of Australia and South Africa. These influences on populated regions of the Southern Hemisphere may have implications for weather and seasonal forecasting, and for future climate change.

Calculating regional climatic time series for temperature and precipitation: Methods and illustrations

Abstract: Various methods for combining station temperature and precipitation time series into regional series are examined. Interpolation of the station series on to regular grid-boxes of some kind reduces the effects of both spatial and temporal changes in station coverage. Regional time series are best produced by using anomaly or standardized anomaly values rather than the raw values. For temperature, and for spatially coherent regions in terms of precipitation variance, the exact method does not seriously affect the resulting time series, provided anomalies are used, although the magnitudes of trends may differ. For regions with large spatial variations in precipitation variance, the additional step of standardizing the anomaly values is recommended. Both anomaly and standardized anomaly series can be easily transformed back to the original units, although the exact method for doing so can alter the resulting time series in non-trivial ways.