Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: Warren Tennant x
  • Refine by Access: All Content x
Clear All Modify Search
Warren Tennant

Abstract

An assessment of 13-yr simulations of three atmospheric general circulation models (AGCMs) forced by observed sea surface temperatures (SSTs) is presented. The National Centers for Environmental Prediction (NCEP) reanalysis data are used as a baseline for the comparisons. Daily circulation characteristics and interannual variability are investigated in order to improve understanding of the causes of systematic model errors. The focus is to determine the utility of these models in the field of seasonal forecasting.

Daily circulation statistics are well represented by the Hadley Centre Atmospheric Climate Model (HADAM3) but the specific versions of the Center for Ocean–Land–Atmosphere Studies (COLA) and Commonwealth Scientific and Industrial Research Organization (CSIRO9) models examined here produce flow patterns biased toward atmospheric archetype modes characteristic of low spatial variability. All three models show relatively large errors in kinetic energy fields of the vertical mean and shear flow, both in latitudinal placement of the midlatitude jet and geographical location of energy maxima. Evidence suggests that model resolution and model physics affect the accuracy of these simulations.

AGCM interannual variability as forced by sea surface temperatures is realistic in terms of a quasi-SOI (Southern Oscillation index) series and reproduces the El Niño–Southern Oscillation (ENSO) signal above noise levels that are determined from simulations using climatological SSTs. However, rainfall fields over southern Africa show little skill in interannual variability and daily rainfall characteristics indicate that some models are producing too many rain days by up to a factor of 2. Notwithstanding these difficulties, AGCMs, if used carefully, do provide sufficient skillful information for guidance in seasonal forecasting.

Full access
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
Matt Hawcroft, Sally Lavender, Dan Copsey, Sean Milton, José Rodríguez, Warren Tennant, Stuart Webster, and Tim Cowan

Abstract

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies, and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31 January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the Met Office numerical weather prediction (NWP) system, focusing on a 1-week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere–ocean coupling and a known bias associated with the behavior of the convection scheme around the coast. We note that a relatively low-resolution ensemble approach requires limited computing resources, yet has the capacity in this event to provide useful information to decision-makers with over a week’s notice, beyond the duration of many operational deterministic forecasts.

Open 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
Bruce Ingleby, Patricia Pauley, Alexander Kats, Jeff Ator, Dennis Keyser, Alexis Doerenbecher, Enrico Fucile, Jitsuko Hasegawa, Eizi Toyoda, Tanja Kleinert, Weiqing Qu, Judy St. James, Warren Tennant, and Richard Weedon

Abstract

Some real-time radiosonde reports are now available with higher vertical resolution and higher precision than the alphanumeric TEMP code. There are also extra metadata; for example, the software version may indicate whether humidity corrections have been applied at the station. Numerical weather prediction (NWP) centers and other users need to start using the new Binary Universal Form for Representation of Meteorological Data (BUFR) reports because the alphanumeric codes are being withdrawn. TEMP code has various restrictions and complexities introduced when telecommunication speed and costs were overriding concerns; one consequence is minor temperature rounding errors. In some ways BUFR reports are simpler: the whole ascent should be contained in a single report. BUFR reports can also include the time and location of each level; an ascent takes about 2 h and the balloon can drift 100 km or more laterally. This modernization is the largest and most complex change to the worldwide reporting of radiosonde observations for many years; international implementation is taking longer than planned and is very uneven. The change brings both opportunities and challenges. The biggest challenge is that the number and quality of the data from radiosonde ascents may suffer if the assessment of the BUFR reports and two-way communication between data producers and data users are not given the priority they require. It is possible that some countries will only attempt to replicate the old reports in the new format, not taking advantage of the benefits, which include easier treatment of radiosonde drift and a better understanding of instrument and processing details, as well as higher resolution.

Full access
Philippe Bougeault, Zoltan Toth, Craig Bishop, Barbara Brown, David Burridge, De Hui Chen, Beth Ebert, Manuel Fuentes, Thomas M. Hamill, Ken Mylne, Jean Nicolau, Tiziana Paccagnella, Young-Youn Park, David Parsons, Baudouin Raoult, Doug Schuster, Pedro Silva Dias, Richard Swinbank, Yoshiaki Takeuchi, Warren Tennant, Laurence Wilson, and Steve Worley

Ensemble forecasting is increasingly accepted as a powerful tool to improve early warnings for high-impact weather. Recently, ensembles combining forecasts from different systems have attracted a considerable level of interest. The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Globa l Ensemble (TIGGE) project, a prominent contribution to THORPEX, has been initiated to enable advanced research and demonstration of the multimodel ensemble concept and to pave the way toward operational implementation of such a system at the international level. The objectives of TIGGE are 1) to facilitate closer cooperation between the academic and operational meteorological communities by expanding the availability of operational products for research, and 2) to facilitate exploring the concept and benefits of multimodel probabilistic weather forecasts, with a particular focus on high-impact weather prediction. Ten operational weather forecasting centers producing daily global ensemble forecasts to 1–2 weeks ahead have agreed to deliver in near–real time a selection of forecast data to the TIGGE data archives at the China Meteorological Agency, the European Centre for Medium-Range Weather Forecasts, and the National Center for Atmospheric Research. The volume of data accumulated daily is 245 GB (1.6 million global fields). This is offered to the scientific community as a new resource for research and education. The TIGGE data policy is to make each forecast accessible via the Internet 48 h after it was initially issued by each originating center. Quicker access can also be granted for field experiments or projects of particular interest to the World Weather Research Programme and THORPEX. A few examples of initial results based on TIGGE data are discussed in this paper, and the case is made for additional research in several directions.

Full access