A study of the climatic regimes of the Pleistocene using a stochastic resonance model

A global energy balance model employing the stochastic resonance mechanism, previously used to explain the climatic variability of the late Pleistocene, has now been extended to account for the climatic variations over the full Pleistocene. The possibility that extremely long-term changes (of the order of millions of years) in the boundary conditions of the climate system have altered the response of the Pleistocene climate to the external orbital forcing has been investigated. It is shown that, by slowly changing the only free parameter of the model, the system can undergo a pitchfork bifurcation. The bifurcation point separates a linear regime (identified with the early Pleistocene climate) from a strongly nonlinear regime (the late Pleistocene) where the stochastic resonance mechanism produces rapid and symmetric transitions between the two stable steady states of the system. The main differences in the dynamic features of the two regimes are the change in amplitude of the oscillations, the relative importance of the stochastic forcing, the change in shape of the probability distribution, and the corresponding change in the power centered around the 100000 year cycle: in qualitative agreement with the observed geological record. With the introduction of the external orbital forcing, now spectrally complete and included without requiring any additional hypothesis, the model reproduces the previous results, namely the good correlation with the isotopic record, the appearance of the dominant spectral peaks, as well as the redness of the power spectrum. In particular, it is shown that the orbital forcing in eccentricity acts as a pacemaker of the major glacial cycles of the late Pleistocene through the mechanism of stochastic resonance. A stochastic sensitivity analysis is then applied to validate the significance of the results and to investigate the predictability of the climate system over the time-scales of the orbital cycles.     

The use of general circulation models in the analysis of the ecosystem impacts of climatic change

The use of general circulation models in the estimation of the impact of climatic change on the global ecosystem is seen to depend primarily on their ability to reliably depict the seasonal and geographical distribution of the changes in surface climate variables. While present GCMs generally simulate the observed distribution of surface air temperature reasonably well, they show significantly different changes in the equilibrium temperature as a result of doubled CO₂, for example. These disagreements are attributed to differences in the model's resolution and parameterization of subgrid-scale processes. Such model-dependent errors notwithstanding, much more information of possible use in impact analysis can be extracted from general circulation model simulations than has generally been done so far. The completeness, consistency and experimental possibilities offered by simulated data sets permit the systematic extraction of a wide variety of statistics important to the surface ecosystem, such as the length of the growing season, the duration of rainless periods, and the surface moisture stress.Assuming further model improvements, the elements of a model-assisted methodology for climate impact analysis are seen to be: (1) the determination of the seasonal and geographical distribution of that portion of simulated climatic changes which are both statistically and physically significant; (2) the transformation of the (significant) large-scale climatic changes onto the local scale of impact (the climate inversion problem); and (3) the design of specific statistical parameters or functions relevant to local ecosystem impacts.     

A first approach to assessing future climate states in the UK over very long timescales: Input to studies of the integrity of radioactive waste repositories

Projected timescales for the transport of radionuclides from an undisturbed undergound nuclear waste repository to the surface are in the range of tens of thousands to millions of years. Over these timescales major natural and potentially major anthropogenic changes in climate can be expected. As part of the UK disposal safety assessment programme, time-dependent models of the repository environment are being developed. The Climatic Research Unit has undertaken a study of relevant climatic change and climatic effects. This has required assessment of the probable range, succession and duration of major climate states likely to be experienced in the UK over very long timescales, up to 10⁶ yr. Two methodologies have been employed. The first uses the Milankovitch theory, which is considered to be the major cause of the Pleistocene glacial/interglacial cycles. The second involves empirical analysis of the long-term reconstructed climate record: no assumptions about the specific causes or mechanisms are made. A period of sub-tropical climate is included in the sequence to represent a period of anthropogenically-induced greenhouse warming. The climate sequence established using these methods will form the basis for studying related processes, such as erosion and groundwater movement and transfer by vegetation, and their implications for radioactive waste disposal. This has involved the construction of instrumental climate analogues.     

Sea-ice and its response to CO2 forcing as simulated by global climate models

The simulation of sea-ice in global climate models participating in the Coupled Model Intercomparison Project (CMIP1 and CMIP2) is analyzed. CMIP1 simulations are of the unpertubed control climate whereas in CMIP2, all models have been forced with the same 1% yr^–1 increase in CO₂ concentration, starting from a near equilibrium initial condition. These simulations are not intended as forecasts of climate change, but rather provide a means of evaluating the response of current climate models to the same forcing. The difference in modeled response therefore indicates the range (or uncertainty) in model sensitivity to greenhouse gas and other climatic perturbations. The results illustrate a wide range in the ability of climate models to reproduce contemporary sea-ice extent and thickness; however, the errors are not obviously related to the manner in which sea-ice processes are represented in the models (e.g. the inclusion or neglect of sea-ice motion). The implication is that errors in the ocean and atmosphere components of the climate model are at least as important. There is also a large range in the simulated sea-ice response to CO₂ change, again with no obvious stratification in terms of model attributes. In contrast to results obtained earlier with a particular model, the CMIP ensemble yields rather mixed results in terms of the dependence of high-latitude warming on sea-ice initial conditions. There is an indication that, in the Arctic, models that produce thick ice in their control integration exhibit less warming than those with thin ice. The opposite tendency appears in the Antarctic (albeit with low statistical significance). There is a tendency for models with more extensive ice coverage in the Southern Hemisphere to exhibit greater Antarctic warming. Results for the Arctic indicate the opposite tendency (though with low statistical significance).A list of the CMIP modeling groups is included in the Acknowledgements section.     

Climatic zoning for the calculation of the thermal demand of buildings in Extremadura (Spain)

The present work reports on a methodology to assess the climatic severity of a particular geographic region as compared to specific information available in the current regulations. The viability for each of the 387 municipalities in the Autonomous Community of Extremadura (Spain) is analysed, making a distinction between those with reliable climate reports and those for which no such information is available. In the case study, although the weather conditions in Extremadura are quite homogeneous according to the Spanish Technical Building Code (STBC 2015) classification and most areas are associated to zone C4 (soft winters and hot summers), the southern area in the region is associated to zone D1, similar to the north of Spain, where winters and summers are cool, which does not coincide with the actual climate in the south of Extremadura. The general climatic homogeneity in Extremadura was also highlighted with the new procedure, predominating zone C4, but unexpected or unreal climatic zoning was not generated, giving place to a consistent spatial distribution of zones throughout the region. Consequently, the proposed method allows a more accurate climatic zoning of any region in agreement with the Spanish legislation on energy efficiency in buildings, which would enhance the setting of thermal demand rates according to the actual climatic characterisation of the area in which a particular municipality is located.     

Public expectation as an element of human perception of climate change

Human expectations regarding weather and climate sometimes lead to perceptions of climate change which are not supported by observational evidence. This paper analyses two very characteristic complaints about current climate in Switzerland, i.e., the lack of snow in winter and the lack of sunshine in summer, through a statistical investigation of climatological data. As one major problem of public perception of climate in mid-latitude regions is linked to the strong variability of the climatic parameters, the paper suggests means of presenting climatic data which include a measure of this variability. Such presentations would help overcome the common confusion between the terms weather and climate, and stress the fact that short-term extreme events are not necessarily indicative of a long-term shift in climate.     

Vegetation responses and feedbacks to climate: a review of models and processes

Vegetation changes both in stationary and changing climates. Such changes can significantly affect hydrological and climate dynamics. Probabilistic, inferential, empirical, statistical, threshold, ecophysiological, and mechanistic vegetation models provide tools and ideas to construct coupled climate and vegetation schemes to study climate/vegetation feedbacks. Their logic is discussed, typical applications are presented, and their usefulness is assessed. Developing coupled climate and vegetation schemes also implies tackling scaling issues explicitly. Just as the Courant-Friedrichs-Lewy (CFL) criterion guarantees that information is not transferred faster through space than time in climate models, information should be transmitted fast enough in vegetation models for the landscape to register vegetation responses. To guarantee that this is the case, a migration criterion, or m criterion, is proposed. The CFL criterion and the m criterion set formal constraints on the design of coupled atmosphere and vegetation schemes. In particular, the ratio of climate and vegetation space scales should be approximately five orders of magnitude less than the ratio of climate and vegetation time scales.     

Three basic problems of paleoclimatic modeling: a personal perspective and review

The development of a theory of the evolution of the climate of the earth over millions of years can be subdivided into three fundamental, nested, problems: Firstly, to establish by equilibrium climate models (e.g., general circulation models) the diagnostic relations, valid at any time, between the fast-response climate variables (i.e., the weather statistics) and both the prescribed external radiative forcing and the prescribed distribution of the slow-response variables (e.g., the ice sheets and shelves, the deep ocean state, and the atmospheric CO₂ concentration). Secondly, to construct, by an essentially inductive process, a model of the time-dependent evolution of the slow-response climatic variables over time scales longer than the damping times of these variables but shorter than the time scale of ultra-slow tectonic and astronomical changes in the boundary conditions (e.g., altered geography and elevation of the continents, slow outgassing and weathering and and solar radiative output). Thirdly, to determine the nature of these ultra-slow processes and their effects on the evolution of the equilibrium state of the climatic system about which the previously mentioned time-dependent variations occur. In this review we discuss the basis for this resolution, and give a broad overview of the contributions that have been made thus far in each area, emphasizing the work of the Yale climate group.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

Chrysophyte cysts from lake sediments reveal the submillennial winter/spring climate variability in the northwestern Mediterranean region throughout the Holocene

In the last decade, much effort was dedicated to the reconstruction of past climate at high temporal resolution. Here, we show the suitability of chrysophyte cysts from lake sediments for revealing continental climate variability when used in sensitive sites, such as those in high mountains. We demonstrate that altitude is a main factor influencing the present distribution of chrysophytes and develop a transfer function to evaluate the local altitude anomaly on a lake site throughout time. Based on our knowledge of chrysophyte ecology, the altitude anomalies are interpreted as winter/spring climate signatures. The method was applied to a Holocene record from a lake in the Pyrenees showing submillennial climatic variability in this northwestern Mediterranean zone. A warming trend was present from the early Holocene to 4 kyear BP. Comparison with pollen-based reconstructions of summer temperatures denoted a contrasting decrease in continentality between the two parts of the Holocene. Oscillations of 1 cycle per ca. 2,000 years appeared throughout the record. The warmest Holocene winters were recorded during the Medieval Warm Period at ca. AD 900 and 450 and the Roman Warm Period (2.7–2.4 kyear BP). Winters in the period AD 1,050–1,175 were inferred to be as cold as in the Little Ice Age. The period between 3 and 7 kyear BP showed lower intensity in the fluctuations than in early and late Holocene. The cold event, 8,200 years ago, appeared embedded in a warm fluctuation. Another cold fluctuation was recorded around 9 kyear BP, which is in agreement with Irish and Greenland records.This revised version was published online in January 2005 with corrections to the background of figures 9 and 12.     

Adapting stochastic weather generation algorithms for climate change studies

While large-scale climate models (GCMs) are in principle the most appropriate tools for predicting climate changes, at present little confidence can be placed in the details of their projections. Use of tools such as crop simulation models for investigation of potential impacts of climatic change requires daily data pertaining to small spatial scales, not the monthly-averaged and large-scale information typically available from the GCMs. A method is presented to adapt stochastic weather generation models, describing daily weather variations in the present-day climate at particular locations, to generate synthetic daily time series consistent with assumed future climates. These assumed climates are specified in terms of the commonly available monthly means and variances of temperature and precipitation, including time-dependent (so-called transient) climate changes. Unlike the usual practice of applying assumed changes in mean values to historically observed data, simulation of meteorological time series also exhibiting changes in variability is possible. Considerable freedom in climate change scenario construction is allowed. The results are suitable for investigating agricultural and other impacts of a variety of hypothetical climate changes specified in terms of monthly-averaged statistics.     

Modeling the earth's climate

Mathematical models of the earth's climate provide intriguing opportunities to study a wide range of interdisciplinary problems involving processes within the climate system in a controlled and systematic manner. This paper is intended as a nontechnical review of climate modeling to enable researchers who are unfamiliar with the topic to better evaluate and judge the credibility of the model results. The types of climate models available for climate research are reviewed here, and four broad categories of climate models are identified. These range from the more simple energy balance models (EBMs) and radiative-convective models (RCMs), to the more complex statistical-dynamical models (SDMs), to the most powerful tools yet available for studying climate, the general circulation models (GCMs). This last category includes gridpoint and spectral GCMs. Four representations of the oceans which can be coupled to GCMs are described and include prescribed sea surface temperatures, an energy balance or swamp ocean, a mixed layer or slab ocean, or a fully computed ocean general circulation model. Selected examples considered representative of the types of studies possible with the various classes of models are given. Taken together, the spectrum of climate models provides a hierarchy of learning and research tools with which to effectively study the extremes of past climates, the vagaries of present-day climate, and possible climatic fluctuations well into the future.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Farm-Level Adaptation to Climatic Variability and Change: Crop Diversification in the Canadian Prairies

Among other foci, recent research on adaptation to climatic variability and change has sought to evaluate the merit of adaptation generally, as well as the suitability of particular adaptations. Additionally, there is a need to better understand the likely uptake of adaptations. For example, diversification is one adaptation that has been identified as a potential farm-level response to climatic variability and change, but its adoption by farmers for this reason is not well understood. This paper serves two purposes. The first is to document the adoption of crop diversification in Canadian prairie agriculture for the period 1994–2002, reflect upon its strengths and limitations for managing a variety of risks, including climatic ones, and gauge its likely adoption by producers in response to anticipated climate change. The second purpose is to draw on this case to refine our current understanding of climate change adaptation more generally. Based upon data from over 15 000 operations, it was determined that individual farms have become more specialized in their cropping patterns since 1994, and this trend is unlikely to change in the immediate future, notwithstanding anticipated climate change and the known risk-reducing benefits of crop diversification. More broadly, the analysis suggests that suitable and even possible climate change adaptations need to be more rigorously assessed in order to understand their wider strengths and limitations.     

Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming

Although current global warming may have a large anthropogenic component, its quantification relies primarily on complex General Circulation Models (GCM’s) assumptions and codes; it is desirable to complement this with empirically based methodologies. Previous attempts to use the recent climate record have concentrated on “fingerprinting” or otherwise comparing the record with GCM outputs. By using CO₂ radiative forcings as a linear surrogate for all anthropogenic effects we estimate the total anthropogenic warming and (effective) climate sensitivity finding: ΔT _anth  = 0.87 ± 0.11 K, $\uplambda_{{2{\text{x}}{\text{CO}}_{2} ,{\text{eff}}}} = 3.08 \pm 0.58\,{\text{K}}$ . These are close the IPPC AR5 values ΔT _anth  = 0.85 ± 0.20 K and $\uplambda_{{2{\text{x}}{\text{CO}}_{2} }} = 1.5\!-\!4.5\,{\text{K}}$ (equilibrium) climate sensitivity and are independent of GCM models, radiative transfer calculations and emission histories. We statistically formulate the hypothesis of warming through natural variability by using centennial scale probabilities of natural fluctuations estimated using scaling, fluctuation analysis on multiproxy data. We take into account two nonclassical statistical features—long range statistical dependencies and “fat tailed” probability distributions (both of which greatly amplify the probability of extremes). Even in the most unfavourable cases, we may reject the natural variability hypothesis at confidence levels >99 %.     

Climate change in fact and in theory: Are we collecting the facts?

For the past 100 years, a mostly volunteer group of observers has formed the backbone of the U.S. National Weather Service (NWS) Cooperative (CO-OP) network. These stations have provided most of the observations used to satisfy the Department of Commerce's statutory mandate of 1890... to establish and record the climatic conditions of the United States (15 USCA 313). Originally, this network was intended primarily for agriculture, but many other uses of the data have since emerged, such as the climatic planning of weather sensitive activities, input to engineering design studies, and input and verification for weather and river forecasts. In recent years, heightened awareness regarding climatic change and variability has challenged this network with yet another mission: the monitoring and detection of climate change. While not designed for that mission, the CO-OP network has proved useful in this respect. However, with some changes in operation, it could become even more valuable in monitoring for climatic change, and could do so in a most economical way. Similar practices instituted worldwide will be necessary for comprehensive study of climate change to the degrees of detail necessary to address specific policy issues and practical local-scale decision making.     

Objective comparison of patterns of CO2 induced climate change in coupled GCM experiments

 Four transient GCM experiments simulating the climatic response to gradually increasing CO₂, and two equilibrium doubled CO₂ experiments are compared. The zonally symmetric and asymmetric features of climate are both examined. Surface air temperature, sea level pressure, the 500 mb height and the relative topography between 500 and 1000 mb are analyzed. In the control simulations, the broad aspects of the present climate are in most cases well reproduced, although the stationary eddies tend to be less reliably simulated than the zonal means. However, the agreement between the four transient experiments on the geographical patterns of climate change is less impressive. While some zonally symmetric features, in particular the meridional distribution of surface air warming in the boreal winter, are rather similar in all models, the intermodel cross correlations for the zonally asymmetric changes are low. The agreement is largely restricted to some very general features such as more warming over the continents than over the oceans. The largest discrepancies between the two equilibrium-doubled CO₂ experiments and the transient experiments are found at the high southern latitudes, in particular in the austral winter. To identify the most robust geographical patterns of change in the transient experiments, the standard t test is used to determine if the four-model mean change is significantly above or below the global mean. Received: 18 January 1996 / Accepted: 5 July 1996     

广义极值分布理论在重现期计算的应用

在气候统计学上,常用Weibull、Gumbel、Frechet统计分布函数对极端气候要素的分布进行拟合,广义极值分布理论综合了以上三种极值分布模型,在气候分析中得到了广泛应用。以南昌市年汛期日最大降水量为例,利用广义极值分布理论对其分布进行拟合,并对重现值及其置信区间进行计算,为气候要素极值的统计分析提供了一种新的手段。     

On modelling the seasonal thermodynamic cycle of sea ice in studies of climatic change

Recent work in modelling climatic changes due to increased atmospheric CO₂ has shown the maximum change to occur in the polar regions as a result of seasonal reductions in sea ice coverage. Typically, sea ice thermodynamics is modelled in a very simple way, whereby the storage of both sensible and latent heat within the ice is ignored, and the effects of snow cover on conductivity and on surface albedo and of oceanic heat flux on bottom ablation may also be neglected. This paper considers whether omission of these processes is justified within the context of quantitatively determining regional climatic changes. A related question, whether omission of ice dynamics can be justified, is not considered.Relatively complete one-dimensional models of sea-ice thermodynamics have previously been developed and tested for a variety of environmental conditions by Maykut and Untersteiner (1969, 1971) and by Semtner (1976). A simpler model which neglects the storage of sensible and latent heat is described in the Appendix to Semtner (1976). In that model, the errors in annual-mean ice thickness which would arise from neglect of heat storage can be compensated by increases in albedo and in conductivity. Here we examine the seasonal cycle of ice thickness predicted by such a model and find significant errors in phase (one month lead) and in amplitude (50% overestimate). The amplitude errors are enhanced as snowfall and oceanic heat flux diminish (or are neglected). This suggests that substantial errors may occur in climate simulations which use very simple formulations of sea ice thermodynamics, whereby early and excessive melting exaggerates the seasonal disappearance of sea ice.To illustrate the above point, two models are configured to examine the local response of Arctic sea ice to a quadrupling of atmospheric CO₂. The first model neglects a number of physical processes and mimics the behavior of sea ice found in Manabe and Stouffer (1980), both for present and enhanced levels of CO₂. The more complete second model gives a better simulation of Arctic ice for the present level of CO₂ and shows a reduced response to CO₂ quadrupling relative to that in Manabe and Stouffer (1980). In particular, the change in surface temperature is cut by a factor of two. In view of this result, a more complete treatment of sea ice thermodynamics would seem warranted in further studies of climate change. Only a minor computational increase is required.A portion of this study is supported by the U.S. Department of Energy as a part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Estimation of possible climate change impacts on water availability, extreme flow events and soil moisture in the Goulburn and Ovens Basins, Victoria

A rainfall-runoff model (IHACRES) is applied on a daily timestep to a large area of the state of Victoria, Australia. Successful calibrations of this dynamic lumped parameter model were performed for 5 rivers contributing streamflow to the Ovens Basin, and for 9 rivers of the Goulburn Basin. This is the first application of the model on such a scale, involving two basins where the total drainage area of the catchments modelled is about 6,500 km². The models were tested by simulation over the entire common period of observation for the 14 catchments under consideration. The results show that the models closely simulate the observed streamflow.The effect of historical climate variability on streamflow was investigated. The models were used for estimation of the potential impact of climatic change on water availability for irrigation for different climate scenarios developed in the Division of Atmospheric Research, CSIRO. This allows conditional estimates to be made of water supply in these basins for the periods 2030 and 2070 under current vegetation conditions. Projecting the future hydrologic regime in this region is extremely important, in particular for supporting irrigation management of the Basin.The problem of estimating the impact of climate change on the probability of extreme events of the hydrological regime was analysed. Flood frequency was found to increase for the scenarios providing the maximum amount of water; to 50% at 2030 and 100% at 2070. The probability of flood events for the dry scenarios rapidly decreases for these dates. Drought frequency, as defined by a soil wetness index, increased 35% for the dry scenario at 2030 and 80% for this scenario at 2070.     

Concepts of Good Science in Climate Change Modelling

The paper by Shackley et al. (1998) appears to present a case for re-considering the way in which climatic science is presented for the purpose of climatic policy development. It also creates, perhaps unwittingly, a picture of naive climate scientists driven by the moods of White House administrators to squander funds in ignorance. We believe that this view, while interesting, is incorrect. Here we respond to Shackley et al.'s (1998, p. 137) invitation to climate scientists to take part in such discussions: in a sense, to (re)consider the scientific and implicit social and policy commitments they have entered into through pursuit of a particular scientific research programme.