Detection and Attribution of External Influence on Regional Scales
The IPCC AR4 reported that anthropogenic influence had been detected in every continent except Antarctica and in some sub-continental land areas, but that difficulties remained in attributing temperature changes on smaller than continental scales and over time scales of less than 50 years. This paper will review recent developments. Additional continental, sub-continental and regional scale detection and attribution results have subsequently become available for surface temperature, including results for polar regions, for SST in tropical cyclogenesis regions and for extreme surface temperature in some regions. Constraints on attributed surface temperature changes on sub-continental scales have also been obtained from global detection and attribution analyses. In addition, sub-global to sub-continental scale detection results are now available for a number of non-temperature climate elements, including northern high-latitude precipitation, Arctic sea-ice extent, the western US hydrological cycle, and North Atlantic significant wave height.
Changing Variability Patterns of Atmospheric Temperature in Atlantic Canada
Temporal variability patterns of atmospheric characteristics on different time scales have a direct influence on human health, agriculture, ecosystems, etc. It is thus important to detect reliably and characterize comprehensively any changes that might affect such variability patterns. The paper presents the results of an investigation based on multiscale pattern analysis applied to atmospheric temperature recorded in different locations in Atlantic Canada. The study uses Detrended Fluctuation Analysis and characterizes daily temperature time series from the point of view of scaling exponents, their scale ranges, and the changes these aspects undergo over time. Reliable data availability intervals vary with location; datasets were chosen that cover at least 40 successive years. The results show that robust scaling aspects can be consistently found in all cases and for all the studied intervals. However, the variability aspects change over time. A novel type of iso- correlation maps is used for this comparative study. While the details regarding such changes are location specific, in most cases there is a general tendency towards increased variability. Changes in variability are expressed consistently on time intervals that reach from days to tens of years. These studies support the comprehensive evaluation of climate change aspects at regional scale; they also provide useful elements for an exploratory evaluation of future climate projections.
Detection of the Effect of Changing Land Use on Warm Extremes in Europe and North America
Human health is adversely affected by extreme temperatures and events like heatwaves are often accompanied by mortality increases. It is therefore essential to understand how extremes respond in a climate forced by anthropogenic forcings. We combine information about changes in warm day extremes during 1950- 2005 from observations and the Hadley Centre HadGEM1 general circulation model (GCM) to carry out an optimal detection analysis. We investigate the effect of changing land use in Europe and North America, where the impact on warm day extremes is the opposite. We find that the loss of trees in both regions since 1850 can explain the bulk of the observed change and propose a mechanism for the perhaps counterintuitive cooling over the Southeast United States (SE US).
Precipitation and Evaporation Trends in Texas
Texas is a large land area with at least three different climate types. As such it is expected that the results of climate change will not be homogenous. This paper presents results of a study of long trends in Texas precipitation and evaporation using data from the US Historical Climatology Network and the Texas Water Development Board. It shows that the long term trends of these variables is not homogenous and exhibits great variability in both spatial extent and magnitude. This variability must be considered in planning for future water supply or other mitigation projects.
Detectability of External Influences in Extreme Precipitation Changes
This study assesses the detectability of external influences in changes of precipitation extremes in the 20th century, which is explored through a perfect model analysis with an ensemble of coupled climate model simulations. Three indices of precipitation extremes are defined from the generalized extreme value (GEV) distribution and time variations of their area-averages are analyzed over different spatial domains from the globe to continental regions. Treating all forcing simulations (ALL; natural plus anthropogenic) of the 20th century as observations and using a preindustrial control run (CTL) to estimate the internal variability, the amplitudes of response patterns to anthropogenic (ANT), natural (NAT), greenhouse-gases (GHG), and sulfate aerosols (SUL) forcings are estimated using a Bayesian decision method. Results show that there are 'decisively' detectable ANT signals in global, hemispheric, and zonal band areas. The ANT signals are also detectable in some indices at continental scales over Asia, South America, Africa, and Australia. GHG and NAT signals are also detectable, but less robustly for more limited extreme indices and regions. These results are largely insensitive to the availability of the observed data. An imperfect model analysis in which fingerprints are obtained from simulations with a different GCM suggests that ANT is robustly detectable only at global and hemispheric scales, with high uncertainty in the zonal and continental results.
Climate Change Detection in Hydrological Extremes
Changes may occur, or may be occurring, in extreme hydrological events, such as floods and low flows, as a result of the potential impacts of climate change. Changes in extreme hydrological events can alter the risk to critical infrastructure resulting from changes to the frequency and magnitude of extreme events. This paper examines the detection of trends in extreme hydrological events, both flood and low flow events, for a collection of streamflow gauging stations, using trend analysis applied to the existing data record. The trend analysis involves the use of the Mann-Kendall non-parametric test for trend as well as a bootstrap resampling process to determine the field significance of the trend results. The analysis includes an exploration of the types of trends that may occur in an extreme flow record, which include changes in the timing of extreme events, changes in the extreme event magnitudes or changes in the hydrological processes that lead to extreme conditions. The techniques discussed in the paper are illustrated through application to data from streamflow gauging stations for a collection of rivers in Canada. The database of streamflow gauging stations investigated has been constructed to represent a diversity of hydrological conditions encompassing different extreme flow processes and reflects a national scale analysis of trends. Sixty streamflow gauging stations are analyzed that have a nominal record length of at least 50 years. The results reveal more trends than would be expected to occur by chance for several of the measures of extreme flow characteristics. The data exhibit changes in both the magnitude and the timing of extreme flow events.