Jack Katzfey

Performance of downscaled regional climate simulations using a variable‐resolution regional climate model: Tasmania as a test case

[1] In this study we develop methods for dynamically downscaling output from six general circulation models (GCMs) for two emissions scenarios using a variable-resolution atmospheric climate model. The use of multiple GCMs and emissions scenarios gives an estimate of model range in projected changes to the mean climate across the region. By modeling the atmosphere at a very fine scale, the simulations capture processes that are important to regional weather and climate at length scales that are subgrid scale for the host GCM. We find that with a multistaged process of increased resolution and the application of bias adjustment methods, the ability of the simulation to reproduce observed conditions improves, with greater than 95% of the spatial variance explained for temperature and about 90% for rainfall. Furthermore, downscaling leads to a significant improvement for the temporal distribution of variables commonly used in applied analyses, reproducing seasonal variability in line with observations. This seasonal signal is not evident in the GCMs. This multistaged approach allows progressive improvement in the skill of the simulations in order to resolve key processes over the region with quantifiable improvements in the correlations with observations.

On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania, Australia

The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961–2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5-day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century.

GCM Simulations of Eastern Australian Cutoff Lows

Abstract The ability of the CSIRO-9 General Circulation Model (GCM) to capture surface cutoff lows over eastern Australia is investigated by comparing composites of ten GCM cases with ten observed lows. The lows are also studied individually to compare their development and movement, as well as synoptic features, which may have been smoothed out in the compositing process. Finally, the incidence of all such lows in the 1 × CO2 and 2 × CO2 simulations are examined to determine the possible effects a doubling of CO2 will have on their occurrence. The GCM surface lows were found to develop from an upper-level cutoff low in a manner similar to the observed lows. In both sets, this development took place between the upper-level subtropical and polar jets in all seasons except summer, where only one jet was evident. Latent heat release appeared to play an important role in the intensification of the surface lows. The main difference between the two sets of cutoff lows was that the GCM surface lows tended to dev...

A regional response in mean westerly circulation and rainfall to projected climate warming over Tasmania, Australia

Coupled ocean–atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall.

An assessment of CSIRO Conformal Cubic Atmospheric Model simulations over Sri Lanka

In this study, we present an assessment of the Conformal Cubic Atmospheric Model (CCAM) 50xa0km simulations forced by the sea surface temperature and sea ice concentration of six global climate models (GCMs) (ACCESS1-0, CCSM4, GFDL-CM3, NorESM, MPI-ESM and CNRM-CM5) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) over South Asia, centred on Sri Lanka. The model simulations were compared with the data provided by the Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation of Water Resource (APHRODITE) project and ERA-Interim from the European Centre for Medium range Weather Forecast (ECMWF) over a broad region centred on Sri Lanka. This broad region includes South Asia and northern Indian Ocean. Statistical measures such as pattern correlations, mean biases and root mean square errors were calculated separately for the four seasons. Results based on statistical tests indicate that the current CCAM simulations capture the spatial patterns of 10xa0m wind speed, mean sea level pressure, temperature and rainfall over a broad region over South Asia fairly well. The annual cycles of temperature and rainfall were also compared against observations over the northern and southern regions of Sri Lanka by taking the field average of each model and the observed data. The characteristics of the observed annual variations of rainfall and temperature over the smaller domains are not very well captured by the CCAM simulations. There are differences in the magnitudes of the temperature and rainfall in the six member CCAM simulations. Comparatively, the two CCAM simulations CNRM-CM5 and GFDL-CM3 show slightly better agreement over the Sri Lankan region.

Regional Climate Modelling for the Energy Sector

Detailed, regionally specific information about the present and future climate is useful to the energy industry. Climate change impacts both energy demand (e.g. heating and cooling) and also generation (e.g. wind regime for turbines). New projects need to consider the current climate as well as future climate projections for the lifespan of the infrastructure. Typical global climate models give information for a 100–200 km grid box but dynamically downscaling using a regional climate model (RCM) can give more detailed information. This chapter describes the different approaches to dynamical downscaling, the issues associated with them and possible applications for the energy sector.

Improved regional climate modelling through dynamical downscaling

Coupled Ocean-Atmosphere General Circulation Models (GCMs) provide the best estimates for assessing potential changes to our climate on a global scale out to the end of this century. Because coupled GCMs have a fairly coarse resolution they do not provide a detailed picture of climate (and climate change) at the local scale. Tasmania, due to its diverse geography and range of climate over a small area is a particularly difficult region for drawing conclusions regarding climate change when relying solely on GCMs. The foundation of the Climate Futures for Tasmania project is to take the output produced by multiple GCMs, using multiple climate change scenarios, and use this output as input into the Conformal Cubic Atmospheric Model (CCAM) to downscale the GCM output. CCAM is a full atmospheric global general circulation model, formulated using a conformal-cubic grid that covers the globe but can be stretched to provide higher resolution in the area of interest (Tasmania). By modelling the atmosphere at a much finer scale than is possible using a coupled GCM we can more accurately capture the processes that drive Tasmanias weather/climate, and thus can more clearly answer the question of how Tasmanias climate will change in the future. We present results that show the improvements in capturing the local-scale climate and climate drivers that can be achieved through downscaling, when compared to a gridded observational data set. The underlying assumption of this work is that a better simulated current climatology will also produce a more credible climate change signal.