The COST725 meta-analysis project used a very large phenological network of more than 125,000 observational series of various phases in 542 plant and 19 animal species in 21 European countries, for the period 1971 to 2000. The time-series were systematically (re-)analysed for trends in order to track and quantify phenological responses to changing climate. The advantage of this study is its inclusion of multiple verified nationally reported trends at single sites and/or for selected species, which individually may be biased towards predominant reporting of climate-change-induced impacts. Overall, the phenology of the species (254 national series) was responsive to temperature of the preceding month, with spring/summer phases advancing on average by 2.5 days/°C and leaf colouring/fall being delayed by 1.0 day/°C.
The aggregation of more than 100,000 trends revealed a clear signal across Europe of changing spring phenology with 78% of leaf unfolding and flowering records advancing (31 % significantly (sig.)) and only 22% delayed (3% sig.) (Figure 1.6). Fruit ripening was mostly advanced (75% advancing, 25% sig.; 25% delayed, 3% sig.). The signal in farmers' activities was generally smaller (57% advancing, 13% sig.; 43% delayed, 6% sig.). Autumn trends (leaf colouring/fall) were not as strong. Spring and summer exhibited a clear advance by 2.5 days/decade in Europe, mean autumn trends were close to zero, but suggested more of a delay when the average trend per country was examined (1.3 days/decade).
The patterns of observed changes in spring (leafing, flowering and animal phases) were spatially consistent and matched measured national warming across 19 European countries (correlation = -0.69, P < 0.001); thus the phenological evidence quantitatively mirrors regional climate warming. The COST725 results assessed the possible lack of evidence at a continental scale as 20%, since about 80% of spring/summer phases were found to be advancing. The findings strongly support previous studies in Europe, confirming them as free from bias towards reporting global climate change impacts (Menzel et al., 2006b).
al., 2006; Trenberth et al., 2007, Figure 3.9). These warming trends are consistent with the response to increasing greenhouse gases and sulphate aerosols and likely cannot be explained by natural internal climate variations or the response to changes in natural external forcing (solar irradiance and volcanoes).
Attributing temperature changes on smaller than continental scales and over time-scales of less than 20 years is difficult due to low signal-to-noise ratios at those scales. Attribution of the observed warming to anthropogenic forcing is easier at larger scales because averaging over larger regions reduces the natural variability more, making it easier to distinguish between changes expected from different external forcings, or between external forcing and climate variability.
The influence of anthropogenic forcing has also been detected in various physical systems over the last 50 years, including increases in global oceanic heat content, increases in sea level, shrinking of alpine glaciers, reductions in Arctic sea ice extent, and reductions in spring snow cover (Hegerl et al., 2007).
188.8.131.52 Joint attribution using climate model studies
Several studies have linked the observed responses in some biological and physical systems to regional-scale warming due to anthropogenic climate change using climate models.
One study demonstrated joint attribution by considering changes in wild animals and plants (Root et al., 2005). They found spring phenological data for 145 Northern Hemisphere species from 31 studies. The changes in the timing of these species' spring events (e.g., blooming) are significantly associated with the changes in the actual temperatures recorded as near to the study site as possible and for the same years that the species were observed. If the temperature was warming and the species phenology was getting earlier in the year, then the expected association would be negative, which is what was found for the correlations between the species data and the actual temperatures (Figure 1.7).
Temperature data from the HadCM3 climate model were used to determine whether the changes in the actual temperatures with which the phenological changes in species were associated were due to human or natural causes. Modelled temperature data were derived for each species, over the same years a species was studied and for the grid box within which the study area was located. Three different forcings were used when calculating the modelled values: natural only, anthropogenic only, and combined natural and anthropogenic. Each species' long-term phenological record was correlated with the three differently forced temperatures derived for the location where the species was recorded. The agreement is quite poor between the phenological changes in species and modelled temperatures derived using only natural climatic forcing (K = 60.16, P >0.05; Figure 1.7a). A stronger agreement occurs between the same phenological changes in species and temperatures modelled using only anthropogenic forcing (K = 35.15, P >0.05; Figure 1.7b). As expected, the strongest agreement is with the modelled temperatures derived using both natural and anthropogenic (combined) forcings (K =3.65, P <0.01; Figure 1.7c). While there is uncertainty in downscaling the model-simulated temperature changes to the areas that would affect the species being examined, these results demonstrate some residual skills, thereby allowing joint attribution to be shown.
Other similar studies have shown that the retreat of two glaciers in Switzerland and Norway cannot be explained by natural variability of climate and the glaciers alone (Reichert et al., 2002), that observed global patterns of changes in streamflow are consistent with the response to anthropogenic climate change (Milly et al., 2005), and that the observed increase in the area of forests burned in Canada over the last four decades is consistent with the response due to anthropogenic climate change (Gillett et al., 2004). Each of these studies has its limitations for joint attribution. For example, the analysis by Reichert used a climate model linked to a local glacier mass balance model through downscaling and showed that the observed glacier retreat over the 20th century could not be explained by natural climate variability. However, they did not show that the observed retreat was consistent with the response to anthropogenic climate change, nor did they eliminate other possible factors, such as changes in dust affecting the albedo of the glacier. Similarly, Gillett and colleagues showed that the observed increases in area of forests burned was consistent with the response to anthropogenic forcing and not consistent with natural climate variability. However, they did not consider changes in forest management as a factor, nor did they consider the climate response to other external forcing factors.
Taken together, these studies show a discernible influence of anthropogenic climate change on specific physical (cryosphere, hydrology) and biological (forestry and terrestrial biology) systems.
Next, a synthesis of the significant observed changes described in Section 1.3 and the observed regional temperatures over the last three decades was performed. Significant observed changes documented since the TAR were divided into the categories of cryosphere, hydrology, coastal processes, marine and freshwater biological systems, terrestrial biological systems, and agriculture and forestry, as assessed in Section 1.3. Studies were selected that demonstrate a statistically significant trend in change in systems
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