Mesozoic climates: General circulation models and the rock record

General circulation models (GCMs) use the laws of physics and an understanding of past geography to simulate climatic responses. They are objective in character. However, they tend to require powerful computers to handle vast numbers of calculations. Nevertheless, it is now possible to compare results from different GCMs for a range of times and over a wide range of parameterisations for the past, present and future (e.g. in terms of predictions of surface air temperature, surface moisture, precipitation, etc.). GCMs are currently producing simulated climate predictions for the Mesozoic, which compare favourably with the distributions of climatically sensitive facies (e.g. coals, evaporites and palaeosols). They can be used effectively in the prediction of oceanic upwelling sites and the distribution of petroleum source rocks and phosphorites. Models also produce evaluations of other parameters that do not leave a geological record (e.g. cloud cover, snow cover) and equivocal phenomena such as storminess. Parameterisation of sub-grid scale processes is the main weakness in GCMs (e.g. land surfaces, convection, cloud behaviour) and model output for continental interiors is still too cold in winter by comparison with palaeontological data. The sedimentary and palaeontological record provides an important way that GCMs may themselves be evaluated and this is important because the same GCMs are being used currently to predict possible changes in future climate.

The Mesozoic Earth was, by comparison with the present, an alien world, as we illustrate here by reference to late Triassic, late Jurassic and late Cretaceous simulations. Dense forests grew close to both poles but experienced months-long daylight in warm summers and months-long darkness in cold snowy winters. Ocean depths were warm (8 °C or more to the ocean floor) and reefs, with corals, grew 10° of latitude further north and south than at the present time. The whole Earth was warmer than now by 6 °C or more, giving more atmospheric humidity and a greatly enhanced hydrological cycle. Much of the rainfall was predominantly convective in character, often focused over the oceans and leaving major desert expanses on the continental areas. Polar ice sheets are unlikely to have been present because of the high summer temperatures achieved. The model indicates extensive sea ice in the nearly enclosed Arctic seaway through a large portion of the year during the late Cretaceous, and the possibility of sea ice in adjacent parts of the Midwest Seaway over North America. The Triassic world was a predominantly warm world, the model output for evaporation and precipitation conforming well with the known distributions of evaporites, calcretes and other climatically sensitive facies for that time.

The message from the geological record is clear. Through the Phanerozoic, Earth's climate has changed significantly, both on a variety of time scales and over a range of climatic states, usually baldly referred to as “greenhouse” and “icehouse”, although these terms disguise more subtle states between these extremes. Any notion that the climate can remain constant for the convenience of one species of anthropoid is a delusion (although the recent rate of climatic change is exceptional).     

Geological evaluation of climate General Circulation Models and model implications for Mesozoic cloud cover

General Circulation Models (GCMs) are currently used to predict future global change. However, the robustness of GCMs can, and should, be evaluated by their ability to simulate past climate regimes. Their success in ‘retrodiction’ can then be assessed by reference to the testimony of the geological record. Geological evidence provides a database which can be used in the estimation of sea surface temperatures and other proxy data useful in palaeoclimatic studies. These data can then be used to refine the prescribed boundary conditions for running GCMs themselves. Results of modelling experiments confirm a generally warmer Mesozoic earth with arid tropics and convective rainfall higher over the oceans than at present. Circum-polar wetlands are also indicated. Modelled cloudiness is also higher in the Mesozoic, contributing to greenhouse conditions and possibly influencing terrestrial biomes and marine ecosystems.     

Multi-model ensemble schemes for predicting northeast monsoon rainfall over peninsular India

The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes, viz., simple arithmetic mean of models (EM), principal component regression (PCR) and singular value decomposition based multiple linear regressions (SVD). It is found out that among these three schemes, SVD based MME has more skill than other MME schemes as well as member models.     

Probabilistic multi-model ensemble prediction of Indian summer monsoon rainfall using general circulation models: A non-parametric approach

Probabilistic prediction has the ability to convey the intrinsic uncertainty of forecast that helps the decision makers to manage the climate risk more efficiently than deterministic forecasts. In recent times, probabilistic predictions obtained from the products from General Circulation Models (GCMs) have gained considerable attention. The probabilistic forecast can be generated in parametric (assuming Gaussian distribution) as well as non-parametric (counting method) ways. The present study deals with the non-parametric approach that requires no assumption about the form of the forecast distribution for the prediction of Indian summer monsoon rainfall (ISMR) based on the hindcast run of seven general circulation models from 1982 to 2008. Probabilistic prediction from each of the GCM products has been generated by non-parametric methods for tercile categories (viz. below normal (BN), near-normal (NN), and above normal (AN)) and evaluation of their skill is assessed against observed data. Five different types of PMME schemes have been used for combining probabilities from each GCM to improve the forecast skill as compared to the individual GCMs. These schemes are different in nature of assigning the weights for combining probabilities. After a rigorous analysis through Rank Probability Skill Score (RPSS) and relative operating characteristic (ROC) curve, the superiority of PMME has been established over climatological probability. It is also found that, the performances of PMME1 and PMME3 are better than all the other methods whereas PMME3 has showed more improvement over PMME1.     

大气环流模式在黄河流域的适用性评价

本文以国际上较流行的5个大气环流模式(HadCM3、GFDL、ECHAM4、CSIRO-Mk2以及CGCM2)对黄河流域1961～1990年温度和降水的模拟结果为基础,通过与该流域同期观测值比较,分析了各大气环流模式(GCM)在黄河流域的适用性.研究结果表明:HadCM3、GFDL两个模式对黄河流域温度的模拟结果较好;ECHAM4、HadCM3两个模式对黄河流域降水的模拟结果较好.5个大气环流模式对温度的模拟明显优于对降水的模拟.总体而言,英国的HadCM3模式在黄河流域的适用性最好,可为黄河流域水文水资源、水土流失对全球气候变化响应等相关研究,提供未来气候变化情景的借鉴.     

Climate and hydrological models to assess the impact of climate change on hydrological regime: a review

Quantitative knowledge about the impacts of climate change on the hydrological regime is essential in order to achieve meaningful insights to address various adverse consequences related to water such as water scarcity, flooding, drought, etc. General circulation models (GCMs) have been developed to simulate the present climate and to predict future climatic change. But, the coarse resolution of their outputs is inefficient to resolve significant regional scale features for assessing the effects of climate change on the hydrological regimes, thus restricting their direct implementation in hydrological models. This article reviews hierarchy and development of climate models from the early times, importance and inter-comparison of downscaling techniques and development of hydrological models. Also recent research developments regarding the evaluation of climate change impact on the hydrological regime have been discussed. The article also provides some suggestions to improve the effectiveness of modelling approaches involved in the assessment of climate change impact on hydrological regime.     

未来不同排放情景下气候变化预估研究进展

概述未来不同排放情景下气候变化预估研究的主要进展。首先,对用于开展气候变化预估研究的不同复杂程度的气候系统及地球系统模式及其模拟能力进行了简要的介绍,指出虽然目前气候系统模式在很多方面存在着较大的不确定性,但大体说来可提供当前气候状况的可信模拟结果;进而介绍了IPCC不同的排放情景,以及不同排放情景下全球与东亚区域气候变化预估的主要结果。研究表明,尽管不同模式对不同情景下未来气候变化预估的结果存有差异,但对未来50～100年全球气候变化的模拟大体一致,即全球将持续增温、降水出现区域性增加。在此基础上,概述了全球气候模式模拟结果的区域化技术,并重点介绍了降尺度方法的分类与应用。同时对气候变化预估的不确定性进行了讨论。最后,对气候变化预估的研究前景进行了展望,并讨论了未来我国气候变化预估研究的重点发展方向。     

气候模式对长江流域气温和降水的模拟性能评估及未来情景预估

利用政府间气候变化专门委员会第四次评估报告的22个新一代全球气候模式基准期(1961～1990年)模拟结果,从时空尺度分别讨论了与观测过程的差异,评估了模式对长江流域气温和降水的模拟性能。结果表明22个气候模式对长江流域具有一定的模拟能力,地面气温的模拟值都偏低,部分降水的模拟值局部偏高。不同的气候模式的模拟能力差异显著,大部分模式对长江流域的模拟精度有待进一步改进,只有少数几个模式（降水有6个模式,气温有5个模式）的年变化趋势与实况基本一致。综合比较,UKMO_HadCM3和NCAR_PCM两个模式基本能再现长江流域降水和气温的年变化特征。长江流域降水和气温未来情景预估表明各个模式和情景结果虽然存在差异,但对未来90年气候变化的模拟趋势基本一致,将持续增温、降水出现区域性增加,并着重讨论了UKMO_HadCM3模式在2020s（2010～2039年）、2050s（2040～2069年）和2080s（2070～2099年）3个时段的降水和气温时空变化特征,研究结果表明3个时段气温和降水在不同情景下都是逐渐增加的,A2情景下未来降水增幅最显著,B1情景增幅最小。     

Performance of general circulation models and their ensembles for the prediction of drought indices over India during summer monsoon

The drought during the months of June to September (JJAS) results in significant deficiency in the annual rainfall and affects the hydrological planning, disaster management, and the agriculture sector of India. Advance information on drought characteristics over the space may help in risk assessment over the country. This issue motivated the present study which deals with the prediction of drought during JJAS through standardized precipitation index (SPI) using nine general circulation models (GCM) product. Among these GCMs, three are the atmospheric and six are atmosphere–ocean coupled models. The performance of these GCM’s predicted SPI is examined against the observed SPI for the time period of 1982–2010. After a rigorous analysis, it can be concluded that the skill of prediction by GCM is not satisfactory, whereas the ability of the coupled models is better than the atmospheric models. An attempt has been made to improve the accuracy of predicted SPI using two different multi-model ensemble (MME) schemes, viz., arithmetic mean and weighted mean using singular value decomposition-based multiple linear regressions (SVD-MLR) of GCMs. It is found that among these MME techniques, SVD-MLR-based MME has more skill as compared to simple MME as well as individual GCMs.     

Impact of Climate Change on the Regional Hydrology – Scenario-Based Modelling Studies in the German Rhine Catchment

The aim of the study is an impact analysis of global climate change on regional hydrology with special emphasis on discharge conditions and floods. The investigations are focussed on the major part of the German Rhine catchment with a drainage area of approx. 110,000 km². This area is subdivided into 23 subcatchments. In a first step, the hydrological model HBV-D serves to simulate runoff conditions under present climate for the individual subbasins. Simulated, large scale atmospheric fields, provided by two different Global Circulation Models (GCMs) and driven by the emission scenario IS95a (“business as usual”) are then used as input to the method of expanded downscaling (EDS). EDS delivers local time series of scenario climate as input to HBV-D. In a final step, the investigations are focussed on the assessment of possible future runoff conditions under the impact of climate change. The study indicates a potential increase in precipitation, mean runoff and flood discharge for small return intervals. However, the uncertainty range that originates from the application of the whole model chain and two different GCMs is high. This leads to high cumulative uncertainties, which do not allow conclusions to be drawn on the development of future extreme floods.     

Climate change impact projections at the catchment scale in Tunisia using the multi-model ensemble mean approach

In this work, we developed a mean projection for climate change and assessed its impact on some hydro-meteorological indicators relevant to climatic condition, precipitation extremes magnitude and frequency for the Siliana catchment in Tunisia based on an ensemble of seven combinations of global circulation models (GCMs) and regional climate models (RCMs) derived from the EU-FP6 ENSEMBLES project. We performed quantile-based mapping (QM) bias correction technique of climate model projection using local observations. Because there is no warranty that the best climate model based on its performances in reproducing historic climate will be superior to other models in simulating future climate, we used the multi-model ensemble (MME) mean approach to derive a mean projection as the best guess for climate change projection for the Siliana catchment. We also quantified the uncertainty of the MME in the projected change in the selected indicators by comparing their values in the reference period (1981–2010) to these in the future period (2041–2070). Results reveal that the Siliana catchment will be prone to drier and warmer climate in the future with less rainy days for each month. The uncertainty associated with the MME projection suggests that no clear general tendency for extreme rainy days in the future is expected. These findings highlight the need to consider an ensemble of multi-climate models with an uncertainty framework if reliable climate change impact study is sought at the catchment scale.     

A “marginality” model to explain major spatial and temporal gaps in the old and new world Pleistocene settlement records

A key argument currently invoked to cast skepticism on certain South American sites, that suggest a first peopling of the New World by ca. 35,000 B.P., is the perplexingly low visibility of the archaeological record until 12,000 B.P. But, contrary to a popular misconception, great spatial and temporal discontinuities are common in the Old World Paleolithic settlement record. In Southern Africa, carefully controlled archaeological stratigraphies show that the now semiarid interior was unoccupied for 50,000 and more years at a time. Episodes of widespread settlement in marginal environments were relatively brief, limited to periods of substantially wetter climate, and closely linked with moist habitats. A risk-minimization model is proposed to explain these discontinuities. Plant and animal resources in the region, given a climate as dry or drier than today, were of low productivity and low reliability for unspecialized hunter-gatherers during the dry seasons of poor years. This would require large foraging territories and very wide spacing of proximal bands, so that the exchange of vital information on temporary or migratory resources was minimal. Finally, during extended droughts, fat-depleted animals provided an unsatisfactory source of food. These variables suggest that environments with low productivity and predictability were too risky for unspecialized hunter-gatherers with a pre-Upper Paleolithic technology, such as those who would have been able to enter the New World 35,000 B.P. Major spatial and temporal gaps in the New World settlement record should therefore be expected prior to the appearance of specialized Paleoindian hunter-gatherers ca. 12,000 B.P. Implications for geoarchaeological strategies are discussed.     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.     

The influence of model structure on groundwater recharge rates in climate-change impact studies

Numerous modeling approaches are available to provide insight into the relationship between climate change and groundwater recharge. However, several aspects of how hydrological model choice and structure affect recharge predictions have not been fully explored, unlike the well-established variability of climate model chains—combination of global climate models (GCM) and regional climate models (RCM). Furthermore, the influence on predictions related to subsoil parameterization and the variability of observation data employed during calibration remain unclear. This paper compares and quantifies these different sources of uncertainty in a systematic way. The described numerical experiment is based on a heterogeneous two-dimensional reference model. Four simpler models were calibrated against the output of the reference model, and recharge predictions of both reference and simpler models were compared to evaluate the effect of model structure on climate-change impact studies. The results highlight that model simplification leads to different recharge rates under climate change, especially under extreme conditions, although the different models performed similarly under historical climate conditions. Extreme weather conditions lead to model bias in the predictions and therefore must be considered. Consequently, the chosen calibration strategy is important and, if possible, the calibration data set should include climatic extremes in order to minimise model bias introduced by the calibration. The results strongly suggest that ensembles of climate projections should be coupled with ensembles of hydrogeological models to produce credible predictions of future recharge and with the associated uncertainties.     

基于中等复杂地球系统模式的全新世 气候突变事件模拟试验*

全新世暖湿气候背景下的代表性气候突变是发生在约8.2kaB.P. 和4.2kaB.P. 的气候突然变冷变干的事件。对于气候突变事件的出现,海洋环流被普遍认为是其中的关键环节。科学家们利用不同类型的气候模式进行过个例和机理模拟试验,但还未能对气候突变机理做出合理的解释。本研究使用一个中等复杂程度的地球系统模式EMIC ( Earth-system Models Intermediate Complexity) MPM-2,模拟研究了全新世气候背景下北大西洋区域,淡水强迫机制作用对温盐环流以及全球气候的可能影响、气候系统响应和恢复时间特征以及南北半球的差异。模拟结果表明海洋对北大西洋淡水通量异常的强度响应敏感,海洋环流对热量和盐份的输送与淡水通量异常强度之间的平衡决定了温盐环流能否对淡水强迫产生不可逆转变,当淡水通量异常达到某一阈值后可能引起海洋和气候平衡态的改变。同时还发现,在气候变化过程中,两次淡水通量异常对海洋和大气系统的强迫作用是不同的,首次淡水通量异常对气候平衡态的影响要远大于其后的淡水通量异常。模拟结果还表明,北大西洋海洋的异常状况可以通过海洋、大气等各圈层相互作用传递到不同圈层和空间区域,在南北半球出现不同的响应特征。上述模拟结果对于认识全新世气候变化特征、不同突变事件之间的关系及其对现代气候的可能影响具有启发意义。     

Glaciomarine varves and the character of deglaciation, Säveån valley, southwestern Sweden

Glaciomarine varves, in contrast to glaciolacustrine varves, are primarily dependent upon sedimentation from meltwater overflow. They are usually developed in proximal positions and are a more reliable reflection of deglaciation character within a specific area than 'classical' glaciolacustrine varves, which are generally more distal and greater influenced by bottom topography. The close relationship with ice-front processes in the glaciomarine environment is discussed and utilized to suggest correlations between the varve stratigraphy, ice-front positions and climate shifts during the deglaciation of the Savean valley, where two varve localities have been documented. A varve sequence outside this valley shows similar general trends in varve-thickness variation, and comparison between localities may help in extending the lines connecting positions of concurrent ice-marginal deposition. The study of glaciomarine varves provides a more continuous record of changes in the ice-front character than can be obtained from intermittent moraine positions.     

The relationship between the isotopic content of precipitation and the precipitation amount in tropical regions

General circulation models (GCMs) fitted with stable isotope schemes are widely used to interpret the isotope–climate relationship. However, previous studies have found that the spatiotemporal isotope/precipitation correlation simulated by GCMs is stronger and more widespread than the observed value. To understand the reason for this failure, we investigated the factors influencing the empirically well-known isotope/precipitation relationship, or precipitation amount effect, in the tropics using newly obtained daily precipitation isotope monitoring data over Asia. As in previous studies, we found an apparent correlation between the long-term monthly mean isotopic content and the corresponding precipitation amount (local precipitation) observed at sub-tropical island stations. Furthermore, on a monthly timescale, the isotopic variability of precipitation for these stations was more clearly related to the regional precipitation amount than to local precipitation. This correlation of isotopic content with the regional precipitation amount was observed at the equatorial (Maritime Continent) stations. For these stations, isotope/local precipitation relationships only appeared over longer timescales, with different regression line slopes at each station. However, at the coastal stations, there was a strong linear relationship between the monthly mean isotopic content and corresponding regional precipitation, and regression line slopes were spatially uniform. For the two sub-tropical terrestrial (Indochina Peninsula) stations, the isotopic minimum appeared without any relationship to rainfall amount but usually occurred at the leeward station during the rainy season. These results suggest that the isotopic variations of precipitation did not depend on the ’local’ rain-out history but on the rain-out process in the surrounding region. However, local rainfall events were associated not only with large-scale disturbances but also with regional circulation. Thus, the scale difference of controlling factors between local rainfall amount and isotopic value results in the weakening of the rainfall amount effect at the observation site and in the discrepancy between GCM simulations and observations. This finding suggests that regional precipitation–isotope relationships should be compared with GCM results. Additionally, because the isotope signal reflects the rain-out history at a regional scale, evaluation of the isotopic field using isotopic GCMs will be useful not only to reconstruct paleoclimate conditions but also to examine how GCMs can reproduce real atmospheric circulation over the tropics.     

基于分段三伽玛分布的降雨偏差纠正方法

为解决全球气候模式模拟降雨与实测降雨存在较大偏差的问题,提出了一种基于分段三伽玛分布的偏差纠正方法。该方法将降雨序列按其分位点分为极小值、常规值和极大值3部分,分别对3部分降雨序列的累积概率分布曲线进行偏差纠正;基于分位数偏差累积思想提出了一种综合性评价指标C,对分段三伽玛方法的偏差纠正效果进行综合评估。应用该方法对CMIP5下18个GCMs在雅鲁藏布江附近17个气象站点的模拟降雨进行偏差纠正,并与单伽玛方法和双伽玛方法进行对比分析。结果表明:分段三伽玛方法可以很好地消除GCMs模拟降雨与实测降雨的偏差,率定期和验证期的偏差纠正效果大多在0.85以上;相比单伽玛和双伽玛方法,分段三伽玛方法在验证期的偏差纠正效果更好,表现更稳健。     

Were last glacial climate events simultaneous between Greenland and France? A quantitative comparison using non‐tuned chronologies

Several large abrupt climate fluctuations during the last glacial have been recorded in Greenland ice cores and archives from other regions. Often these Dansgaard–Oeschger events are assumed to have been synchronous over wide areas, and then used as tie‐points to link chronologies between the proxy archives. However, it has not yet been tested independently whether or not these events were indeed synchronous over large areas. Here, we compare Dansgaard–Oeschger‐type events in a well‐dated record from southeastern France with those in Greenland ice cores. Instead of assuming simultaneous climate events between both archives, we keep their age models independent. Even these well‐dated archives possess large chronological uncertainties that prevent us from inferring synchronous climate events at decadal to multi‐centennial time scales. If possible, comparisons between proxy archives should be based on independent, non‐tuned time‐scales. Copyright © 2009 John Wiley & Sons, Ltd.     

Climate change and groundwater conditions in the Mekong Region–A review

Changes in the climatic system introduce uncertainties in the supply and management of water resources. The Intergovernmental Panel on Climate Change(IPCC) predicts an increase of 2 to 4 °C over the next 100 years. Temperature increases will impact the hydrologic cycle by directly increasing the evaporation of surface water sources. Consequently, changes in precipitation will indirectly impact the flux and storage of water in surface and subsurface reservoirs(i.e., lakes, soil moisture, groundwater, etc.). In addition, increases in temperature contribute to increases in the sea level, which may lead to sea water intrusions, water quality deterioration, potable water shortages, etc. Climate change has direct impacts on the surface water and the control of storage in rivers, lakes and reservoirs, which indirectly controls the groundwater recharge process. The main and direct impact of climate change on groundwater is changes in the volume and distribution of groundwater recharge. The impact of climate change on groundwater resources requires reliable forecasting of changes in the major climatic variables and accurate estimations of groundwater recharge. A number of Global Climate Models(GCMs) are available for understanding climate and projecting climate change.These GCMs can be downscaled to a basin scale, and when they are coupled with relevant hydrological models, the output of these coupled models can be used to quantify the groundwater recharge, which will facilitate the adoption of appropriate adaptation strategies under the impact of climate change.