Stephen P. Charles

A non‐homogeneous hidden Markov model for precipitation occurrence

A non‐homogeneous hidden Markov model is proposed for relating precipitation occurrences at multiple rain‐gauge stations to broad scale atmospheric circulation patterns (the so‐called ‘downscaling problem’). We model a 15‐year sequence of winter data from 30 rain stations in south‐western Australia. The first 10 years of data are used for model development and the remaining 5 years are used for model evaluation. The fitted model accurately reproduces the observed rainfall statistics in the reserved data despite a shift in atmospheric circulation (and, consequently, rainfall) between the two periods. The fitted model also provides some useful insights into the processes driving rainfall in this region.

A spatiotemporal model for downscaling precipitation occurrence and amounts

A stochastic model that relates synoptic atmospheric data to daily precipitation at a network of gages is presented. The model extends the nonhomogeneous hidden Markov model (NHMM) of Hughes et al. by incorporating precipitation amounts. The NHMM assumes that multisite, daily precipitation occurrence patterns are driven by a finite number of unobserved weather states that evolve temporally according to a first-order Markov chain. The state transition probabilities are a function of observed or modeled synoptic scale atmospheric variables such as mean sea level pressure. For each weather state we evaluate the joint distribution of daily precipitation amounts at n sites through the specification of n conditional distributions. The conditional distributions consist of regressions of transformed amounts at a given site on precipitation occurrence at neighboring sites within a set radius. Results for a network of 30 daily precipitation gages and historical atmospheric circulation data in southwestern Australia indicate that the extended NHMM accurately simulates the wet-day probabilities, survival curves for dry- and wet-spell lengths, daily precipitation amount distributions at each site, and intersite correlations for daily precipitation amounts over the 15 year period from 1978 to 1992.

Decadal Climatic Variability, Trends, and Future Scenarios for the North China Plain

Observed decadal climatic variability and trends for the north China plain (NCP) are assessed for significance with Kendall’s test and discussed in light of future climate scenarios from multi-GCM outputs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The results indicate that the NCP has become warmer and drier over the last four decades. The annual precipitation has declined by about 43.9 mm (6.7%, although not statistically significant), and the annual means of daily mean, maximum, and minimum temperatures have increased by 0.838, 0.188, and 1.468C, respectively, during the past 40 yr. Both trends for annual means of daily mean and minimum temperatures are statistically significant. The future climate of the NCP is projected to be warmer and, with less confidence, wetter. However, streamflow could decline under these projections, based on the results of the two-parameter climate elasticity of streamflow index. This will produce serious challenges for water resources management and likely lead to exacerbated problems for agriculture, industry, urban communities, and the environment.

An assessment of the climate change impacts on groundwater recharge at a continental scale using a probabilistic approach with an ensemble of GCMs

This study used 16 Global Climate Models and three global warming scenarios to make projections of recharge under a 2050 climate for the entire Australian continent at a 0.05° grid resolution. The results from these 48 future climate variants have been fitted to a probability distribution to enable the results to be summarised and uncertainty quantified. The median results project a reduction in recharge across the west, centre and south of Australia and an increase in recharge across the north and a small area in the east of the continent. The range of results is quite large and for large parts of the continent encompasses both increases and decreases in recharge. This makes it difficult to utilise for water resources management so the results have been analysed with a risk analysis framework; this enables the future projections for groundwater recharge to be communicated to water managers in terms of likelihood and consequence of a reduction in recharge. This highlights an important message for water resource managers that in most areas of Australia they will be making decisions on water allocations under considerable uncertainty as to the direction and magnitude of recharge change under a future climate and that this uncertainty may be irreducible.

A comparison of three multi-site statistical downscaling models for daily rainfall in the North China Plain

Three statistical downscaling methods (conditional resampling statistical downscaling model: CR-SDSM, the generalised linear model for daily climate time series: GLIMCLIM, and the non-homogeneous hidden Markov model: NHMM) for multi-site daily rainfall were evaluated and compared in the North China Plain (NCP). The comparison focused on a range of statistics important for hydrological studies including rainfall amount, extreme rainfall, intra-annual variability, and spatial coherency. The results showed that no single model performed well over all statistics/timescales, suggesting that the user should chose appropriate methods after assessing their advantages and limitations when applying downscaling methods for particular purposes. Specifically, the CR-SDSM provided relatively robust results for annual/monthly statistics and extreme characteristics, but exhibited weakness for some daily statistics, such as daily rainfall amount, dry-spell length, and annual wet/dry days. GLIMCLIM performed well for annual dry/wet days, dry/wet spell length, and spatial coherency, but slightly overestimated the daily rainfall. Additionally, NHMM performed better for daily rainfall and annual wet/dry days, but slightly underestimated dry/wet spell length and overestimated the daily extremes. The results of this study could be applied when investigating climate change impact on hydrology and water availability for the NCP, which suffers from intense water shortages due to climate change and human activities in recent years.

Long-Term Temporal Variation of Extreme Rainfall Events in Australia: 1910–2006

Abstract The temporal variability of the frequency of short-duration extreme precipitation events in Australia for the period 1910–2006 is examined using the high-quality rainfall dataset identified by the Bureau of Meteorology, Australia, for 189 stations. Extreme events are defined by duration and recurrence interval: 1, 5, 10, and 30 days, and 1, 5, and 20 yr, respectively. The results indicate that temporal variations of the extreme precipitation index (EPI) for various durations and recurrence intervals in the last 100 yr, except for the low frequencies before 1918, have experienced three U-shaped cycles: 1918–53, 1953–74, and 1974–2006. Seasonal results indicate that about two-thirds of 1-day, 1-yr recurrence interval extreme events occur from December to March. Time series of anomalies of the regional EPIs for four regions indicate that northeast Australia and southeast Australia have almost the same temporal variation as the national anomalies, South Australia experienced a negative anomaly of ext...

Stochastic Down-Scaling of General Circulation Model Simulations

Modelling the response of agricultural and natural ecosystems to climate forecasts requires daily data at local and regional scales. General circulation models (GCMs) provide reasonable simulations of atmospheric fields at the synoptic scale. However, they tend to over-estimate the frequency and under-estimate the intensity of daily precipitation. Stochastic downscaling techniques provide a means of linking the synoptic scale with local scales. They can be used to quantify the relation of climate variables at small space scales to the larger scale atmospheric patterns produced by GCMs. This paper reviews downscaling techniques from an applications perspective. It then presents a case study involving the use of a downscaling technique known as the nonhomogeneous hidden Markov model (NHMM). A NHMM fit to a 15-year record of daily atmospheric-precipitation data is used to downscale GCM atmospheric fields for South-West Western Australia. We compare the downscaled and observed ‘winter’ precipitation statistics at six stations near Perth, Western Australia. The results show that a downscaled GCM simulation provides credible reproductions of observed precipitation probabilities and the frequencies of wet and dry spells at each station.

Simulated Impacts of Climate Change on Groundwater Recharge in the Subtropics of Queensland, Australia

Increased atmospheric concentrations of CO2 could affect Australia’s groundwater resources via changes in rainfall and potential evapotranspiration regimes. The extent to which groundwater resources are affected by climate change will depend upon the local soils and vegetation. As a case study, we assess the potential impacts of climate change on groundwater recharge beneath North Stradbroke Island off the subtropical east coast of Queensland, Australia The simulated climates come from equilibrium (constant CO2 concentration) runs of the CSIRO9 general circulation model (GCM) for present and double-CO2 conditions. Based on the GCM output for each climate, a stochastic point weather generator, MWGEN, produces realisations of the daily climate variables. This climate “data” drives a numerical simulator, WAVES, of rainfall infiltration, variably saturated flow and evapotranspiration, producing temporal distributions of the daily groundwater recharge rate for various soil-vegetation environments. The transformation from rainfall infiltration to groundwater recharge can amplify the effects of climate change because of flow and storage in soils and dynamic plant water use. The simulation results indicate that double-CO2 climate change could more than double the net groundwater recharge; this increase is disproportionate to a 37 percent rise in mean annual rainfall, with ratios of the change in recharge to change in rainfall ranging from 0.76 to 1.05 for different soil-vegetation combinations. Such increases in recharge are enhanced by the dynamic growth and die-back of vegetation. The mean recharge rate, inter-annual variability and persistence in deviations from the mean are related to the soil and vegetation characteristics. Further improvements in estimating future climate and plant-water use should increase our understanding of the sensitivity of groundwater resources to expected climate change and climate variability.