Climate and climate change in western canada as simulated by the Canadian regional climate model     

Rene Laprise  Daniel Caya  Michel Giguere  Guy Bergeron  Hélène Côté  Jean‐Pierre Blanchet 《大气与海洋》2013,51(2):119-167

Abstract

A þrst climate simulation performed with the novel Canadian Regional Climate Model (CRCM) is presented. The CRCM is based on fully elastic non‐hydrostatic þeld equations, which are solved with an efþcient semi‐implicit semi‐Lagrangian (SISL) marching algorithm, and on the parametrization package of subgrid‐scale physical effects of the second‐generation Canadian Global Climate Model (GCMII). Two 5‐year integrations of the CRCM nested with GCMII simulated data as lateral boundary conditions are made for conditions corresponding to current and doubled CO₂ scenarios. For these simulations the CRCM used a grid size of 45 km on a polar‐stereographic projection, 20 scaled‐height levels and a time step of 15 min; the nesting GCMII has a spectral truncation of T32, 10 hybrid‐pressure levels and a time step of 20 min. These simulations serve to document: (1) the suitability of the SISL numerical scheme for regional climate modelling, (2) the use of GCMII physics at much higher resolution than in the nesting model, (3) the ability of the CRCM to add realistic regional‐scale climate information to global model simulations, and (4) the climate of the CRCM compared to that of GCMII under two greenhouse gases (GHG) scenarios.  相似文献   

Nonparametric analysis of high wind speed data     

Mario Francisco-Fernández  Alejandro Quintela-del-Río 《Climate Dynamics》2013,40(1-2):429-441

In this paper, nonparametric curve estimation methods are applied to analyze time series of wind speeds, focusing on the extreme events exceeding a chosen threshold. Classical parametric statistical approaches in this context consist in fitting a generalized Pareto distribution (GPD) to the tail of the empirical cumulative distribution, using maximum likelihood or the method of the moments to estimate the parameters of this distribution. Additionally, confidence intervals are usually computed to assess the uncertainty of the estimates. Nonparametric methods to estimate directly some quantities of interest, such as the probability of exceedance, the quantiles or return levels, or the return periods, are proposed. Moreover, bootstrap techniques are used to develop pointwise and simultaneous confidence intervals for these functions. The proposed models are applied to wind speed data in the Gulf Coast of US, comparing the results with those using the GPD approach, by means of a split-sample test. Results show that nonparametric methods are competitive with respect to the standard GPD approximations. The study is completed generating synthetic data sets and comparing the behavior of the parametric and the nonparametric estimates in this framework.  相似文献   

Climate variability and trends in downscaled high-resolution simulations and projections over Metropolitan France   总被引：2，自引：1，他引：1  

Robert Vautard  Thomas Noël  Laurent Li  Mathieu Vrac  Eric Martin  Philippe Dandin  Julien Cattiaux  Sylvie Joussaume 《Climate Dynamics》2013,41(5-6):1419-1437

In order to fulfill the society demand for climate information at the spatial scale allowing impact studies, long-term high-resolution climate simulations are produced, over an area covering metropolitan France. One of the major goals of this article is to investigate whether such simulations appropriately simulate the spatial and temporal variability of the current climate, using two simulation chains. These start from the global IPSL-CM4 climate model, using two regional models (LMDz and MM5) at moderate resolution (15–20 km), followed with a statistical downscaling method in order to reach a target resolution of 8 km. The statistical downscaling technique includes a non-parametric method that corrects the distribution by using high-resolution analyses over France. First the uncorrected simulations are evaluated against a set of high-resolution analyses, with a focus on temperature and precipitation. Uncorrected downscaled temperatures suffer from a cold bias that is present in the global model as well. Precipitations biases have a season- and model-dependent behavior. Dynamical models overestimate rainfall but with different patterns and amplitude, but both have underestimations in the South-Eastern area (Cevennes mountains) in winter. A variance decomposition shows that uncorrected simulations fairly well capture observed variances from inter-annual to high-frequency intra-seasonal time scales. After correction, distributions match with analyses by construction, but it is shown that spatial coherence, persistence properties of warm, cold and dry episodes also match to a certain extent. Another aim of the article is to describe the changes for future climate obtained using these simulations under Scenario A1B. Results are presented on the changes between current and mid-term future (2021–2050) averages and variability over France. Interestingly, even though the same global climate model is used at the boundaries, regional climate change responses from the two models significantly differ.  相似文献   

Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models     

Josefina Blázquez  Mario N. Nuñez 《Climate Dynamics》2013,41(3-4):1039-1056

This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons.  相似文献   

Winter-to-spring temperature dynamics in Turkey derived from tree rings since AD 1125   总被引：2，自引：1，他引：1  

Ingo Heinrich  Ramzi Touchan  Isabel Dorado Liñán  Heinz Vos  Gerhard Helle 《Climate Dynamics》2013,41(7-8):1685-1701

In the eastern Mediterranean in general and in Turkey in particular, temperature reconstructions based on tree rings have not been achieved so far. Furthermore, centennial-long chronologies of stable isotopes are generally also missing. Recent studies have identified the tree species Juniperus excelsa as one of the most promising tree species in Turkey for developing long climate sensitive stable carbon isotope chronologies because this species is long-living and thus has the ability to capture low-frequency climate signals. We were able to develop a statistically robust, precisely dated and annually resolved chronology back to AD 1125. We proved that variability of δ¹³C in tree rings of J. excelsa is mainly dependent on winter-to-spring temperatures (January–May). Low-frequency trends, which were associated with the medieval warm period and the little ice age, were identified in the winter-to-spring temperature reconstruction, however, the twentieth century warming trend found elsewhere could not be identified in our proxy record, nor was it found in the corresponding meteorological data used for our study. Comparisons with other northern-hemispherical proxy data showed that similar low-frequency signals are present until the beginning of the twentieth century when the other proxies derived from further north indicate a significant warming while the winter-to-spring temperature proxy from SW-Turkey does not. Correlation analyses including our temperature reconstruction and seven well-known climate indices suggest that various atmospheric oscillation patterns are capable of influencing the temperature variations in SW-Turkey.  相似文献   

Estimating Buoyancy Heat Flux Using the Surface Renewal Technique over Four Amazonian Forest Sites in Brazil     

Marcelo Zeri  Leonardo D. A. Sá  Carlos A. Nobre 《Boundary-Layer Meteorology》2013,149(2):179-196

The surface renewal (SR) method was applied for the first time to measurements of air temperature over four Amazonian forest sites and different seasons in order to obtain estimates of buoyancy heat flux. The required calibration of this method against eddy covariance resulted in a value for a specific parameter that is close to the range reported in other studies, contributing to the generalization of the SR method to different kinds of canopies. The comparison with fluxes obtained using the eddy covariance technique revealed a good match between the two methods for different sites, heights and seasons. Sites with high levels of non-stationarity in the signals of temperature and wind speed presented higher scatter in the regression with fluxes from eddy covariance. For a particular site with previously reported influence of low-frequency motions, the regression was only satisfactory, i.e., slope parameter close to unity and small offset, when oscillations with periods longer than $\approx $ ≈ 13 min were filtered out. The SR method has a great potential due to the simplicity of the instrumentation required. However, care should be taken when measuring under the influence of mesoscale motions, which can lead to high levels of non-stationarity, compromising the fundamental concepts of the SR theory.  相似文献   

Wake Response to an Ocean-Feedback Mechanism: Madeira Island Case Study     

Rui M. A. Caldeira  Ricardo Tomé 《Boundary-Layer Meteorology》2013,148(2):419-436

We focus on an island wake episode that occurred in the Madeira Archipelago region of the north-east Atlantic at $32.5^{\circ }\mathrm{N}, 17^{\circ }\mathrm{W}$ . The Weather Research and Forecasting numerical model was used in a (one-way) downscaling mode, considering initial and boundary conditions from the European Centre for Medium-range Weather Forecasts system. The current literature emphasizes adiabatic effects on the dynamical aspects of atmospheric wakes. Changes in mountain height and consequently its relation to the atmospheric inversion layer should explain the shift in wake regimes, from a ‘strong-wake’ to ‘weak-wake’ scenario. Nevertheless, changes in sea-surface temperature variability in the lee of an island can induce similar regime shifts because of exposure to stronger solar radiation. Increase in evaporation contributes to the enhancement of convection and thus to the uplift of the stratified atmospheric layer above the critical height, with subsequent internal gravity wave activity.  相似文献   

The challenge to detect and attribute effects of climate change on human and natural systems     

Dáithí Stone  Maximilian Auffhammer  Mark Carey  Gerrit Hansen  Christian Huggel  Wolfgang Cramer  David Lobell  Ulf Molau  Andrew Solow  Lourdes Tibig  Gary Yohe 《Climatic change》2013,118(2):381-395

Future scenarios of the energy system under greenhouse gas emission constraints depict dramatic growth in a range of energy technologies. Technological growth dynamics observed historically provide a useful comparator for these future trajectories. We find that historical time series data reveal a consistent relationship between how much a technology’s cumulative installed capacity grows, and how long this growth takes. This relationship between extent (how much) and duration (for how long) is consistent across both energy supply and end-use technologies, and both established and emerging technologies. We then develop and test an approach for using this historical relationship to assess technological trajectories in future scenarios. Our approach for “learning from the past” contributes to the assessment and verification of integrated assessment and energy-economic models used to generate quantitative scenarios. Using data on power generation technologies from two such models, we also find a consistent extent - duration relationship across both technologies and scenarios. This relationship describes future low carbon technological growth in the power sector which appears to be conservative relative to what has been evidenced historically. Specifically, future extents of capacity growth are comparatively low given the lengthy time duration of that growth. We treat this finding with caution due to the low number of data points. Yet it remains counter-intuitive given the extremely rapid growth rates of certain low carbon technologies under stringent emission constraints. We explore possible reasons for the apparent scenario conservatism, and find parametric or structural conservatism in the underlying models to be one possible explanation.  相似文献   

Do we know each other? Bilateral ties and the location of clean development mechanism projects     

Nives Dolšak  Emily Bowerman Crandall 《Climatic change》2013,118(3-4):521-536

This paper examines how bilateral ties between developed (home) countries and developing (host) countries influence the location of Clean Development Mechanism projects (CDMs). With the home-host country pair as the unit of analysis (2,058 country-pairs), we employ a logistic regression model to analyze decisions of home countries in selecting the location for their CDMs. We are most interested in examining how home countries’ familiarity with the host country influences CDM location decisions. The familiarity factors are: (1) colonial history; (2) bilateral trade; and (3) bilateral aid. Using a binary logistical model, we find that that bilateral familiarity factors strongly influence CDM location decisions. Further, with respect to host country characteristics, we find that total carbon dioxide emissions and UNFCCC specific domestic institutions influence CDM location decisions, but not general investment institutions or high carbon intensity of host country economies.  相似文献   

Climate change and infectious diseases: Can we meet the needs for better prediction?     

Xavier Rodó  Mercedes Pascual  Francisco J. Doblas-Reyes  Alexander Gershunov  Dáithí A. Stone  Filippo Giorgi  Peter J. Hudson  James Kinter  Miquel-Àngel Rodríguez-Arias  Nils Ch. Stenseth  David Alonso  Javier García-Serrano  Andrew P. Dobson 《Climatic change》2013,118(3-4):625-640

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.  相似文献