Bertrand Timbal

The Hadley Circulation in Reanalyses: Climatology, Variability, and Change

AbstractAnalysis of the annual cycle of intensity, extent, and width of the Hadley circulation across a 31-yr period (1979–2009) from all existent reanalyses reveals a good agreement among the datasets. All datasets show that intensity is at a maximum in the winter hemisphere and at a minimum in the summer hemisphere. Maximum and minimum values of meridional extent are reached in the respective autumn and spring hemispheres. While considering the horizontal momentum balance, where a weakening of the Hadley cell (HC) is expected in association with a widening, it is shown here that there is no direct relationship between intensity and extent on a monthly time scale.All reanalyses show an expansion in both hemispheres, most pronounced and statistically significant during summer and autumn at an average rate of expansion of 0.55° decade−1 in each hemisphere. In contrast, intensity trends are inconsistent among the datasets, although there is a tendency toward intensification, particularly in winter and sprin...

A proposal for a general interface between land surface schemes and general circulation models

The aim of this paper is to propose a general interface for coupling general circulation models (GCMs) to land surface schemes (LSS) in order to achieve a plug compatibility between these complex models. As surface parameterizations include more processes, they have moved from being subroutines of GCMs to independent schemes which can also be applied for other purposes. This evolution has raised the problem within climate modeling groups of coupling these schemes to GCMs in a simple and flexible way. As LSS reaches a larger independence, a general interface is needed to enable exchange within the community. This paper discusses the tasks LSS have to fulfill when coupled to a GCM after a review of the current state of the art and the likely future evolutions of both components. The numerical schemes used for the processes which couple the land surfaces to the atmosphere are reviewed to ensure that the interface can be applied to all LSS and GCMs after only minor changes.

Does Soil Moisture Influence Climate Variability and Predictability over Australia

Abstract Interannual variations of Australian climate are strongly linked to the El Nino–Southern Oscillation (ENSO) phenomenon. However, the impact of other mechanisms on prediction, such as atmosphere–land surface interactions, has been less frequently investigated. Here, the impact of soil moisture variability on interannual climate variability and predictability is examined using the Bureau of Meteorology Research Centre atmospheric general circulation model. Two sets of experiments are run, each with five different initial conditions. In the first set of experiments, soil moisture is free to vary in response to atmospheric forcing in each experiment according to a set of simple prognostic equations. A potential predictability index is computed as the ratio of the models internal variability to its external forced variability. This estimates the level of predictability obtained assuming perfect knowledge of future ocean surface temperatures. A second set of five experiments with prescribed soil moist...

Evaluating the Consistency between Statistically Downscaled and Global Dynamical Model Climate Change Projections

The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

Indian Ocean Dipole Overrides ENSO’s Influence on Cool Season Rainfall across the Eastern Seaboard of Australia

AbstractThe strong relationship between eastern Australian winter–spring rainfall and tropical modes of variability such as the El Nino–Southern Oscillation (ENSO) does not extend to the heavily populated coastal strip east of the Great Dividing Range in southeast Australia, where correlations between rainfall and Nino-3.4 are insignificant during June–October. The Indian Ocean dipole (IOD) is found to have a strong influence on zonal wind flow during the winter and spring months, with positive IOD increasing both onshore winds and rainfall over the coastal strip, while decreasing rainfall elsewhere in southeast Australia. The IOD thus opposes the influence of ENSO over the coastal strip, and this is shown to be the primary cause of the breakdown of the ENSO–rainfall relationship in this region.

A pressure gradient metric capturing planetary‐scale influences on eastern Australian rainfall

The Gayndah-Deniliquin index (GDI), a measure of the north-south atmospheric pressure gradient across eastern Australia, is presented. The 113 year long GDI record reveals strong interannual to decadal scale variability in zonal geostrophic wind flow across eastern Australia. The GDI, as a measure of easterly geostrophic wind strength and associated moisture transport from the Pacific Ocean, is shown to be significantly correlated with summer rainfall over vast areas of the Australian continent, especially over the Murray Darling Basin and the state of New South Wales. The latest abrupt decline in the GDI, which commenced around 2001, corresponded with the onset of a severe prolonged drought across eastern Australia. We demonstrate that the northern and southern poles of the MSLP derived GDI are differentially influenced by El Nino-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Understanding the effects of these interactions between SAM and ENSO on moisture transport to eastern Australia could have implications for future Australian climate variability and climate change. the Murray Darling Basin and the state of New South Wales. The latest abrupt decline in the GDI, which commenced around 2001, corresponded with the onset of a severe prolonged drought across eastern Australia. We demonstrate that the northern and southern poles of the MSLP derived GDI are differentially influenced by El Nin˜o- Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Understanding the effects of these interactions between SAM and ENSO on moisture transport to eastern Australia could have implications for future Australian climate variability and climate change.

Expansion of the Southern Hemisphere Hadley Cell in Response to Greenhouse Gas Forcing

AbstractChanges of the Southern Hemisphere Hadley cell over the twentieth century are investigated using the Twentieth Century Reanalysis (20CR) and coupled model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Trends computed on a 30-yr sliding window on the 20CR dataset reveal a statistically significant expansion of the Hadley cell from 1968 forced by an increasing surface global warming. This expansion is strongly associated with the intensification and poleward shift of the subtropical dry zone, which potentially explain the increasing trends of droughts in the subtropical regions such as southern Australia, South America, and Africa. Coupled models from the CMIP5 do not adequately simulate the observed amount of the Hadley expansion, only showing an average of one-fourth of the expansion as determined from the 20CR and only when simulations include greenhouse gas forcing as opposed to simulations including natural forcing only.

The climate of the Eastern Seaboard of Australia: A challenging entity now and for future projections

The Eastern SeaBoard (ESB) of Australia has long been recognised as a separate climate entity. Using the latest gridded observations from the Bureau of Meteorology, a definition of the spatial extent of the ESB is proposed. It appears that, while this area has recorded below average rainfall over the last 12 years, the ongoing deficiency is not record breaking in historic terms. This contrasts with record breaking droughts across large parts of inland, eastern Australia. The lesser severity of ongoing rainfall deficiencies in the ESB, compared to the rest of the region, is linked to the different impact of observed changes in regional surface pressure and, in particular, changes in the position of the sub-tropical ridge. It is also observed that while tropical modes of variability in the Pacific and Indian oceans are known to influence the climate of eastern Australia, that influence appears very weak and not statistically significant across the ESB. Finally, some issues relevant to future rainfall projections for the ESB are discussed. It is argued that providing reliable climate projections across this climatic region is a difficult challenge.

Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

AbstractSeasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each m...

A comparison of downscaling techniques in the projection of local climate change and wheat yields

This study aims to evaluate the performance of two mainstream downscaling techniques: statistical and dynamical downscaling and to compare the differences in their projection of future climate change and the resultant impact on wheat crop yields for three locations across New South Wales, Australia. Bureau of Meteorology statistically- and CSIRO dynamically-downscaled climate, derived or driven by the CSIRO Mk 3.5 coupled general circulation model, were firstly evaluated against observed climate data for the period 1980–1999. Future climate projections derived from the two downscaling approaches for the period centred on 2055 were then compared. A stochastic weather generator, LARS-WG, was used in this study to derive monthly climate changes and to construct climate change scenarios. The Agricultural Production System sIMulator-Wheat model was then combined with the constructed climate change scenarios to quantify the impact of climate change on wheat grain yield. Statistical results show that (1) in terms of reproducing the past climate, statistical downscaling performed better over dynamical downscaling in most of the cases including climate variables, their mean, variance and distribution, and study locations, (2) there is significant difference between the two downscaling techniques in projected future climate change except the mean value of rainfall across the three locations for most of the months; and (3) there is significant difference in projected wheat grain yields between the two downscaling techniques at two of the three locations.