Search Results

You are looking at 1 - 4 of 4 items for

  • Author or Editor: Warren J. Tennant x
  • Refine by Access: All Content x
Clear All Modify Search
Warren J. Tennant
and
Chris J. C. Reason

Abstract

Large-scale atmospheric processes in the Southern Hemisphere are examined on both seasonal and daily time scales in order to seek associations between these and regional rainfall variability in the summer rainfall areas of South Africa and the winter rainfall regions of South Africa and Western Australia. The basis of the analysis is atmospheric energetics of the vertical mean and shear flow. Self-organizing maps (SOMs) are then used to find archetypical states of the daily flow and to assess how the frequency characteristics of these states change between wet and dry years.

The results show clear associations between the frequency of circulation archetypes on a hemispheric scale and regional rainfall for both summer and winter rainfall areas. Substantial changes in archetype frequencies between wet and dry years are found with as much as a doubling or halving of the number of days in which certain archetypes occur within a season. The physical reasons for observed teleconnections are shown by way of the atmospheric energy cycle, providing a deeper understanding of climate variability that may benefit extended-range prediction.

Full access
Warren J. Tennant
,
Zoltan Toth
, and
Kevin J. Rae

Abstract

The National Centers for Environmental Prediction (NCEP) Ensemble Forecasting System (EFS) is used operationally in South Africa for medium-range forecasts up to 14 days ahead. The use of model-generated probability forecasts has a clear benefit in the skill of the 1–7-day forecasts. This is seen in the forecast probability distribution being more successful in spanning the observed space than a single deterministic forecast and, thus, substantially reducing the instances of missed events in the forecast. In addition, the probability forecasts generated using the EFS are particularly useful in estimating confidence in forecasts. During the second week of the forecast the EFS is used as a heads-up for possible synoptic-scale events and also for predicting average weather conditions and probability density distributions of some elements such as maximum temperature and wind. This paper assesses the medium-range forecast process and the application of the NCEP EFS at the South African Weather Service. It includes a description of the various medium-range products, adaptive bias-correction methods applied to the forecasts, verification of the forecast products, and a discussion on the various challenges that face researchers and forecasters alike.

Full access
Warren J. Tennant
,
Glenn J. Shutts
,
Alberto Arribas
, and
Simon A. Thompson

Abstract

An improved stochastic kinetic energy backscatter scheme, version 2 (SKEB2) has been developed for the Met Office Global and Regional Ensemble Prediction System (MOGREPS). Wind increments at each model time step are derived from a streamfunction forcing pattern that is modulated by a locally diagnosed field of likely energy loss due to numerical smoothing and unrepresented convective sources of kinetic energy near the grid scale. The scheme has a positive impact on the root-mean-square error of the ensemble mean and spread of the ensemble. An improved growth rate of spread results in a better match with ensemble-mean forecast error at all forecast lead times, with a corresponding improvement in probabilistic forecast skill from a more realistic representation of model error. Other examples of positive impact include improved forecast blocking frequency and reduced forecast jumpiness. The paper describes the formulation of the SKEB2 and its assessment in various experiments.

Full access
Nikolaos Christidis
,
Peter A. Stott
,
Adam A. Scaife
,
Alberto Arribas
,
Gareth S. Jones
,
Dan Copsey
,
Jeff R. Knight
, and
Warren J. Tennant

Abstract

A new system for attribution of weather and climate extreme events has been developed based on the atmospheric component of the latest Hadley Centre model. The model is run with either observational data of sea surface temperature and sea ice or estimates of what their values would be without the effect of anthropogenic climatic forcings. In that way, ensembles of simulations are produced that represent the climate with and without the effect of human influences. A comparison between the ensembles provides estimates of the change in the frequency of extremes due to anthropogenic forcings. To evaluate the new system, reliability diagrams are constructed, which compare the model-derived probability of extreme events with their observed frequency. The ability of the model to reproduce realistic distributions of relevant climatic variables is another key aspect of the system evaluation. Results are then presented from analyses of three recent high-impact events: the 2009/10 cold winter in the United Kingdom, the heat wave in Moscow in July 2010, and floods in Pakistan in July 2010. An evaluation assessment indicates the model can provide reliable results for the U.K. and Moscow events but not for Pakistan. It is found that without anthropogenic forcings winters in the United Kingdom colder than 2009/10 would be 7–10 times (best estimate) more common. Although anthropogenic forcings increase the likelihood of heat waves in Moscow, the 2010 event is found to be very uncommon and associated with a return time of several hundred years. No reliable attribution assessment can be made for high-precipitation events in Pakistan.

Full access