Daniel Argüeso

Temperature response to future urbanization and climate change

This study examines the impact of future urban expansion on local near-surface temperature for Sydney (Australia) using a future climate scenario (A2). The Weather Research and Forecasting model was used to simulate the present (1990–2009) and future (2040–2059) climates of the region at 2-km spatial resolution. The standard land use of the model was replaced with a more accurate dataset that covers the Sydney area. The future simulation incorporates the projected changes in the urban area of Sydney to account for the expected urban expansion. A comparison between areas with projected land use changes and their surroundings was conducted to evaluate how urbanization and global warming will act together and to ascertain their combined effect on the local climate. The analysis of the temperature changes revealed that future urbanization will strongly affect minimum temperature, whereas little impact was detected for maximum temperature. The minimum temperature changes will be noticeable throughout the year. However, during winter and spring these differences will be particularly large and the increases could be double the increase due to global warming alone at 2050. Results indicated that the changes were mostly due to increased heat capacity of urban structures and reduced evaporation in the city environment.

Relationships between climate variability, soil moisture, and Australian heatwaves

While it is established that low-frequency climate variability modes have a dominant role on Australias climate, limited work to date has focused on relationships between climate variability and Australian heatwaves. Moreover, heatwaves are a distinctive type of extreme weather that can be classified by multiple characteristics, such as intensity, frequency, duration, and timing. This study identifies the relationships between known modes of climate variability that influence Australian climate, and discrete seasonal characteristics of the intensity, frequency, duration, and timing of heatwaves. The large-scale seasonal modes of the El Nino/Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Southern Annular Mode (SAM) are investigated for extended Austral summers commencing between the years 1911 and 2012. While ENSO is found to have the strongest relationship with Australian heatwave characteristics, this study finds that ENSOs influence differs between heatwave frequency, duration, intensity, and timing. Regions dominated by ENSO experience more, longer lasting and hotter heatwaves combined with an earlier commencement of the heatwave season during El Nino phases. The exception to this is southeast Australia, where SAM is generally more dominant. In contrast, the IOD provides little indication of seasonal heatwave characteristics due to its relative inactivity during the Austral summer months. Lastly, we show that antecedent soil moisture has varying strengths of relationships with Australian heatwave characteristics, exhibiting relationships with heatwave intensity and timing over some regions where none are detected between large-scale modes. However, while significant relationships between dry antecedent soil moisture and extreme heatwaves do exist over Australia, these appear to be slightly weaker than similar relationships over Europe reported in other studies.

Influence of land‐atmosphere feedbacks on temperature and precipitation extremes in the GLACE‐CMIP5 ensemble

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Evaluation of WRF Mean and Extreme Precipitation over Spain: Present Climate (1970–99)

AbstractThe ability of the Weather Research and Forecasting model (WRF) to simulate precipitation over Spain is evaluated from a climatological point of view. The complex topography and the large rainfall variability make the Iberian Peninsula a particularly interesting region and permit assessment of model performance under very demanding conditions.Three high-resolution (10 km) simulations over the Iberian Peninsula have been completed spanning a 30-yr period (1970–99) and driven by different datasets: the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) as “perfect boundary conditions” and two general circulation models (GCMs), the Max Planck Institute ECHAM5 model (ECHAM5/MPI) and the NCAR Community Climate System Model, version 3 (CCSM3). The daily precipitation observational grid Spain02 is employed to evaluate the model at varying time scales. Not only are the long-term means (annual, seasonal, and monthly) examined but also the high-order statistics (extreme events).Th...

Effects of City Expansion on Heat Stress under Climate Change Conditions

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990–2009) and future (2040–2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort.

Natural hazards in Australia: heatwaves

As part of a special issue on natural hazards, this paper reviews the current state of scientific knowledge of Australian heatwaves. Over recent years, progress has been made in understanding both the causes of and changes to heatwaves. Relationships between atmospheric heatwaves and large-scale and synoptic variability have been identified, with increasing trends in heatwave intensity, frequency and duration projected to continue throughout the 21st century. However, more research is required to further our understanding of the dynamical interactions of atmospheric heatwaves, particularly with the land surface. Research into marine heatwaves is still in its infancy, with little known about driving mechanisms, and observed and future changes. In order to address these knowledge gaps, recommendations include: focusing on a comprehensive assessment of atmospheric heatwave dynamics; understanding links with droughts; working towards a unified measurement framework; and investigating observed and future trends in marine heatwaves. Such work requires comprehensive and long-term collaboration activities. However, benefits will extend to the international community, thus addressing global grand challenges surrounding these extreme events.

Resolution Sensitivity of Cyclone Climatology over Eastern Australia Using Six Reanalysis Products

AbstractThe climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input da...

Comparison of various climate change projections of eastern Australian rainfall

The Australian eastern seaboard is a distinct climate entity from the interior of the continent, with different climatic influences on each side of the Great Dividing Range. Therefore, it is plausible that downscaling of global climate models could reveal meaningful regional detail, or ‘added value’, in the climate change signal of mean rainfall change in eastern Australia un-der future scenarios. However, because downscaling is typically done using a limited set of global climate models and downscaling methods, the results from a downscaling study may not represent the range of uncertainty in plausible projected change for a region suggested by the ensemble of host global climate models. A complete and unbiased representation of the plausible changes in the climate is essential in producing climate projections useful for future planning. As part of this aim it is important to quantify any differences in the change signal between global climate models and downscaling, and understand the cause of these differ-ences in terms of plausible added regional detail in the climate change signal, the impact of sub-sampling global climate models and the effect of the downscaling models themselves. Here we examine rainfall projections in eastern Australia under a high emissions scenario by late in the century from ensembles of global climate models, two dynamical downscaling models and one statistical downscaling model. We find no cases where all three downscaling methods show the same clear regional spatial detail in the change signal that is distinct from the host models. However, some downscaled projections suggest that the eastern seaboard could see little change in spring rainfall, in contrast to the substantial rainfall decrease inland. The change signal in the downscaled outputs is broadly similar at the large scale in the various model outputs, with a few notable exceptions. For example, the model median from dynamical downscaling projects a rainfall increase over the entirety of eastern Australia in autumn that is greater than the global models. Also, there are some instances where a downscaling method produces changes outside the range of host models over eastern Australia as a whole, thus ex-panding the projected range of uncertainty. Results are particularly uncertain for summer, where no two downscaling studies clearly agree. There are also some confounding factors from the model configuration used in downscaling, where the particular zones used for statis-tical models and the model components used in dynamical models have an influence on results and produce additional uncertainty.

Long‐range seasonal streamflow forecasting over the Iberian Peninsula using large‐scale atmospheric and oceanic information

Identifying the relationship between large-scale climate signals and seasonal streamflow may provide a valuable tool for long-range seasonal forecasting in regions under water stress, such as the Iberian Peninsula (IP). The skill of the main teleconnection indices as predictors of seasonal streamflow in the IP was evaluated. The streamflow database used was composed of 382 stations, covering the period 1975–2008. Predictions were made using a leave-one-out cross-validation approach based on multiple linear regression, combining Variance Inflation Factor and Stepwise Backward selection to avoid multicollinearity and select the best subset of predictors. Predictions were made for four forecasting scenarios, from one to four seasons in advance. The correlation coefficient (RHO), Root Mean Square Error Skill Score (RMSESS), and the Gerrity Skill Score (GSS) were used to evaluate the forecasting skill. For autumn streamflow, good forecasting skill (RHO>0.5, RMSESS>20%, GSS>0.4) was found for a third of the stations located in the Mediterranean Andalusian Basin, the North Atlantic Oscillation of the previous winter being the main predictor. Also, fair forecasting skill (RHO>0.44, RMSESS>10%, GSS>0.2) was found in stations in the northwestern IP (16 of these located in the Douro and Tagus Basins) with two seasons in advance. For winter streamflow, fair forecasting skill was found for one season in advance in 168 stations, with the Snow Advance Index as the main predictor. Finally, forecasting was poorer for spring streamflow than for autumn and winter, since only 16 stations showed fair forecasting skill in with one season in advance, particularly in north-western of IP.

Bias-corrected regional climate projections of extreme rainfall in south-east Australia

This study presents future changes in extreme precipitation as projected within the New South Wales and Australian Capital Territory Regional Climate Modelling (NARCliM) project’s regional climate ensemble for south-east Australia. Model performance, independence and projected future changes were considered when designing the ensemble. We applied a quantile mapping bias correction to the climate model outputs based on theoretical distribution functions, and the implications of this for the projected precipitation extremes is investigated. Precipitation extremes are quantified using several indices from the Expert Team on Climate Change Detection and Indices set of indices. The bias correction was successful in removing most of the magnitude bias in extreme precipitation but does not correct biases in the length of maximum wet and dry spells. The bias correction also had a relatively small effect on the projected future changes. Across a range of metrics, robust increases in the magnitude of precipitation extreme indices are found. While these increases are often in-line with a continuation of the trends present over the last century, they are not found to be statistically significant within the ensemble as a whole. The length of the maximum consecutive wet spell is projected to remain at present-day levels, while the length of the maximum dry spell is projected to increase into the future. The combination of longer dry spells and increases in extreme precipitation magnitude indicate an important change in the character of the precipitation time series. This could have considerable hydrological implications since changes in the sequencing of events can be just as important as changes in event magnitude for hydrological impacts.