Freeze thaw cycles in Toronto, Canada in a changing climate

Summary Freeze thaw cycles are examined in Toronto Canada. Using data from 1960 to 1989 for three Toronto area weather stations, trends in freeze thaw activity, the relationship to mean monthly temperature and projections of freeze thaw activity are examined. For downtown Toronto the annual frequency of freeze thaw cycles is decreasing significantly, most notably in the shoulder months of October and April. At the Pearson International Airport and the Toronto Island Airport similar annual trends were not found, however there was evidence of decreased freeze thaw activity in April and October. Polynomial curve fitting provided functional relationships between mean monthly temperature and freeze thaw activity. These relationships enabled the assessment of freeze thaw activity under synthetic warming conditions. The results of this analysis show that the warming of the magnitude typically projected for the rest of this century will not likely generate a significant change in the freeze thaw activity although there are indications that the freeze thaw season will contract.     

Quantification of the urban heat island under a changing climate over Anatolian Peninsula

The Anatolian Peninsula is located at the confluence of Europe, Asia, and Africa and houses 81 cities of which 79 of them have population over 100,000. We employed some criteria to select the cities from the 81 cities. After accomplishing all the criteria, eight cities were remaining for the study. Nonparametric Mann–Kendall test procedure was employed for the urban and rural stations of these cities to detect the long-term change in temperature trends. Statistical analysis of daily minimum temperatures for the period between 1965 and 2006 suggest that there is no statistically significant increase in rural areas. In contrast to the findings of the previous studies, however, all the urban sites and difference between urban and rural pairs show significant increase in temperatures, a strong indication for the existence of urban heat island (UHI) affect over the region. Regional Climate Model was also utilized to assess the changes in temperature by the end of century for the region. The findings suggest that an increase of up to 5°C is possible. Climate change effects enforced with UHI have the potential to cause serious problems for the entire region and hence needs to be studied thoroughly.     

Sensitivity analysis of climate on streamflow in north China

The economics and crowded cities of north China play important roles in China’s overall economic development. Streamflow is a hot issue in ecohydrological studies, and research into changes in streamflow in north China is of great significance. In this study, the sensitivities of streamflow to the aridity index, precipitation, and potential evapotranspiration are evaluated to assess the impact of climatic variation in streamflow in north China. The results show that the average coefficient of sensitivity of streamflow to aridity index is ?2.24, and streamflow would decrease by 22.4 % with a 10 % increase in the aridity index. The average coefficients of sensitivity of streamflow to precipitation and potential evapotranspiration are 3.21 and ?2.21, respectively. A 10 % increase in precipitation or potential evapotranspiration would induce a 32.1 % increase or a 22.1 % decrease of streamflow, respectively. Basins with low streamflows would be more sensitive to climatic variation than basins with high streamflows.     

Non-stationary extreme value analysis in a changing climate

This paper introduces a framework for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. This framework is implemented in the Non-stationary Extreme Value Analysis (NEVA) software package, explicitly designed to facilitate analysis of extremes in the geosciences. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.     

Evolution of the Parisian urban climate under a global changing climate

The evolution of the Parisian urban climate under a changing climate is analyzed from long-term offline numerical integrations including a specific urban parameterization. This system is forced by meteorological conditions based on present-climate reanalyses (1970–2007), and climate projections (2071–2099) provided by global climate model simulations following two emission scenarios (A1B and A2). This study aims at quantifying the impact of climate change on air temperature within the city and in the surroundings. A systematic increase of 2-meter air temperature is found. In average according to the two scenarios, it reaches +?2.0/2.4°C in winter and +?3.5/5.0°C in summer for the minimum and maximum daily temperatures, respectively. During summer, the warming trend is more pronounced in the surrounding countryside than in Paris and suburbs due to the soil dryness. As a result, a substantial decrease of the strong urban heat islands is noted at nighttime, and numerous events with negative urban heat islands appear at daytime. Finally, a 30% decrease of the heating degree days is quantified in winter between present and future climates. Inversely, the summertime cooling degree days significantly increase in future climate whereas they are negligible in present climate. However, in terms of accumulated degree days, the increase of the demand in cooling remains smaller than the decrease of the demand in heating.     

Projected increases in near-surface air temperature over Ontario,Canada: a regional climate modeling approach

Climate Dynamics - As the biggest economy in Canada, the Province of Ontario is now suffering many consequences caused by or associated with global warming, such as frequent and intense heat waves,...     

闽东北地区夏季对流云特征的初步分析

利用新一代天气雷达资料分析闽东北地区夏季对流云的回波特征。分析表明:多单体合并对流云在生命史、回波高度、强度、尺度等方面都超过了单体对流云,其液态水总量也更大,自然降水条件和人工影响潜力都优于单体对流云,是夏季降水和人工催化的重要云系。分析得到对流云发展的不同阶段、不同高度层辐合辐散特点,为进一步研究夏季对流云结构和降水原理提供科学依据。通过对两个个例的天气形势分析,指出冷空气对对流发展有一定的激发作用。     

The relationship between climate and outbreak characteristics of the spruce budworm in eastern Canada

The relationship between outbreak characteristics of the spruce budworm and the combination of climate, forest composition, and spatial location was examined in eastern Canada by the method of constrained ordination. Approximately 54% of the spatial variability in outbreak pattern, as described by a matrix of four outbreak characteristics, was explained by the spatial pattern of the climate (a matrix of six variables), forest composition (a matrix of seven variables), and spatial location (a matrix of two variables). The relationships between outbreak variables and climate variables were highlighted, and future outbreak characteristics of the spruce budworm were projected using simulations of a global circulation model for the period 2081–2100 where CO₂ concentrations reach a maximum of approximately 550 ppm. Future outbreaks are predicted to be an average of approximately 6 years longer with an average of 15% greater defoliation. The methodology is described and the potential effects of climate change on landscape-scale outbreaks of the insect are discussed.     

Global streamflow and thermal habitats of freshwater fishes under climate change

Climate change will affect future flow and thermal regimes of rivers. This will directly affect freshwater habitats and ecosystem health. In particular fish species, which are strongly adapted to a certain level of flow variability will be sensitive to future changes in flow regime. In addition, all freshwater fish species are exotherms, and increasing water temperatures will therefore directly affect fishes’ biochemical reaction rates and physiology. To assess climate change impacts on large-scale freshwater fish habitats we used a physically-based hydrological and water temperature modelling framework forced with an ensemble of climate model output. Future projections on global river flow and water temperature were used in combination with current spatial distributions of several fish species and their maximum thermal tolerances to explore impacts on fish habitats in different regions around the world. Results indicate that climate change will affect seasonal flow amplitudes, magnitude and timing of high and low flow events for large fractions of the global land surface area. Also, significant increases in both the frequency and magnitude of exceeding maximum temperature tolerances for selected fish species are found. Although the adaptive capacity of fish species to changing hydrologic regimes and rising water temperatures could be variable, our global results show that fish habitats are likely to change in the near future, and this is expected to affect species distributions.     

Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades

Recent studies predict that projected climate change will lead to significant reductions in summer streamflow in the mountainous regions of the Western US. Hydrologic modeling directed at quantifying these potential changes has focused on the magnitude and timing of spring snowmelt as the key control on the spatial–temporal pattern of summer streamflow. We illustrate how spatial differences in groundwater dynamics can also play a significant role in determining streamflow responses to warming. We examine two contrasting watersheds, one located in the Western Cascades and the other in the High Cascades mountains of Oregon. We use both empirical analysis of streamflow data and physically based, spatially distributed modeling to disentangle the relative importance of multiple and interacting controls. In particular, we explore the extent to which differences in snow accumulation and melt and drainage characteristics (deep ground water vs. shallow subsurface) mediate the effect of climate change. Results show that within the Cascade Range, local variations in bedrock geology and concomitant differences in volume and seasonal fluxes of subsurface water will likely result in significant spatial variability in responses to climate forcing. Specifically, watersheds dominated by High Cascade geology will show greater absolute reductions in summer streamflow with predicted temperature increases.     

Lake surface temperatures in a changing climate: a global sensitivity analysis

We estimate the effects of climatic changes, as predicted by six climate models, on lake surface temperatures on a global scale, using the lake surface equilibrium temperature as a proxy. We evaluate interactions between different forcing variables, the sensitivity of lake surface temperatures to these variables, as well as differences between climate zones. Lake surface equilibrium temperatures are predicted to increase by 70 to 85 % of the increase in air temperatures. On average, air temperature is the main driver for changes in lake surface temperatures, and its effect is reduced by ~10 % by changes in other meteorological variables. However, the contribution of these other variables to the variance is ~40 % of that of air temperature, and their effects can be important at specific locations. The warming increases the importance of longwave radiation and evaporation for the lake surface heat balance compared to shortwave radiation and convective heat fluxes. We discuss the consequences of our findings for the design and evaluation of different types of studies on climate change effects on lakes.     

Error characteristics of high resolution regional climate models over the Alpine area

This study describes typical error ranges of high resolution regional climate models operated over complex orography and investigates the scale-dependence of these error ranges. The results are valid primarily for the European Alpine region, but to some extent they can also be transferred to other orographically complex regions of the world. We investigate the model errors by evaluating a set of 62 one-year hindcast experiments for the year 1999 with four different regional climate models. The analysis is conducted for the parameters mean sea level pressure, air temperature (mean, minimum and maximum) and precipitation (mean, frequency and intensity), both as an area average over the whole modeled domain (the “Greater Alpine Region”, GAR) and in six subregions. The subregional seasonal error ranges, defined as the interval between the 2.5th percentile and the 97.5th percentile, lie between ?3.2 and +2.0 K for temperature and between ?2.0 and +3.1 mm/day (?45.7 and +94.7%) for precipitation, respectively. While the temperature error ranges are hardly broadened at smaller scales, the precipitation error ranges increase by 28%. These results demonstrate that high resolution RCMs are applicable in relatively small scale climate impact studies with a comparable quality as on well investigated larger scales as far as temperature is concerned. For precipitation, which is a much more demanding parameter, the quality is moderately degraded on smaller scales.     

Detection of changes in streamflow and floods resulting from climate fluctuations and land use-drainage changes

Detection of effects of changing climate on the hydrologic responses of rivers can be further complicated by changes in land use, drainage, and water use. To discern effects of human-caused changes in a basin and those due to precipitation over time, a comparison was made of annual mean flows and peakflows in Midwestern basins that experienced increases in annual precipitation and heavy rain events during 1940–1990. Two pairs of basins, one pair in a rural area and one pair in an urbanized area, were selected for in-pair comparisons, with one basin in each pair experiencing more land use and drainage changes during 1940–1990 than the other basin. All basins experienced significant upward trends in annual precipitation and annual mean flows. Human-produced changes affecting runoff in both rural basins accounted for about two-thirds of the fluctuations in the mean flows, and precipitation changes accounted for the other third. However, much of the change in peakflows in the rural basin undergoing sizable changes in drainage was due to these changes (85%) versus 75% in the rural basin without comparable shifts in drainage. The mean and peak flows of the two urban basins showed considerably more response to precipitation shifts than those of the two rural basins. The urbanized area doubled within one urban basin during 1940–1990, and these land use changes explained much more of the increase in mean flows and peakflows there than in the urban basin with less change in land use. By 1990 precipitation accounted for 69% of the upward trend in mean flows since 1941 in the heavily developed urban basin, as compared to 37% of the trend in the less settled urban basin. For purposes of assessing climate change, the precipitation changes over fifty years in all basins produced marked uptrends in basin streamflow, but the magnitude of the precipitation effect was masked by the land use and drainage changes. The results illustrate the need for careful analysis of natural basin characteristics (soils and basin shape), land use and drainage changes, and of various precipitation conditions if the influence of shifting precipitation on hydrologic conditions is to be detected, accurately measured, and correctly interpreted. For such studies the paired basin comparison techniques appears to be a valuable approach.     

Soil temperature response in Korea to a changing climate using a land surface model

The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme — the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change.     

Changing inland lakes responding to climate warming in Northeastern Tibetan Plateau

The main portion of Tibetan Plateau has experienced statistically significant warming over the past 50 years, especially in cold seasons. This paper aims to identify and characterize the dynamics of inland lakes that located in the hinterland of Tibetan Plateau responding to climate change. We compared satellite imageries in late 1970s and early 1990s with recent to inventory and track changes in lakes after three decades of rising temperatures in the region. It showed warm and dry trend in climate with significant accelerated increasing annual mean temperature over the last 30 years, however, decreasing periodically annual precipitation and no obvious trend in potential evapotranspiration during the same period. Our analysis indicated widespread declines in inland lake??s abundance and area in the whole origin of the Yellow River and southeastern origin of the Yangtze River. In contrast, the western and northern origin of the Yangtze River revealed completely reverse change. The regional lake surface area decreased by 11,499 ha or 1.72% from the late 1970s to the early 1990s, and increased by 6,866 ha or 1.04% from the early 1990s to 2004. Shrinking inland lakes may become a common feature in the discontinuous permafrost regions as a consequence of warming climate and thawing permafrost. Furthermore, obvious expanding were found in continuous permafrost regions due to climate warming and glacier retreating. The results may provide information for the scientific recognition of the responding events to the climate change recorded by the inland lakes.