The danger of overvaluing methane’s influence on future climate change

Minimizing the future impacts of climate change requires reducing the greenhouse gas (GHG) load in the atmosphere. Anthropogenic emissions include many types of GHG’s as well as particulates such as black carbon and sulfate aerosols, each of which has a different effect on the atmosphere, and a different atmospheric lifetime. Several recent studies have advocated for the importance of short timescales when comparing the climate impact of different climate pollutants, placing a high relative value on short-lived pollutants, such as methane (CH₄) and black carbon (BC) versus carbon dioxide (CO₂). These studies have generated confusion over how to value changes in temperature that occur over short versus long timescales. We show the temperature changes that result from exchanging CO₂ for CH₄ using a variety of commonly suggested metrics to illustrate the trade-offs involved in potential carbon trading mechanisms that place a high value on CH₄ emissions. Reducing CH₄ emissions today would lead to a climate cooling of approximately ~0.5 °C, but this value will not change greatly if we delay reducing CH₄ emissions by years or decades. This is not true for CO₂, for which the climate is influenced by cumulative emissions. Any delay in reducing CO₂ emissions is likely to lead to higher cumulative emissions, and more warming. The exact warming resulting from this delay depends on the trajectory of future CO₂ emissions but using one business-as usual-projection we estimate an increase of 3/4 °C for every 15-year delay in CO₂ mitigation. Overvaluing the influence of CH₄ emissions on climate could easily result in our “locking” the earth into a warmer temperature trajectory, one that is temporarily masked by the short-term cooling effects of the CH₄ reductions, but then persists for many generations.     

The contribution of timescales to the temperature response of climate models

Both the magnitude and timescale of climate change in response to anthropogenic forcing are important consideration in climate change decision making. Using a familiar, yet simple global energy balance model combined with a novel method for estimating the amount of gain in the global surface temperature response to radiative forcing associated with timescales in the range 10⁰?C10³?years we show that the introduction of large-scale circulation such as meridional overturning leads to the emergence of discrete gain?Ctimescale relationships in the dynamics of this model. This same feature is found in the response of both an intermediate complexity and two atmosphere?Cocean general circulation models run to equilibrium. As a result of this emergent property of climate models, it is possible to offer credible partitioning of the full equilibrium gain of these models, and hence their equilibrium climate sensitivity, between two discrete timescales; one decadal associated with near surface ocean heat equilibration; and one centennial associated with deep ocean heat equilibration. Timescales of approximately 20 and 700?years with a 60:40 partitioning of the equilibrium gain are found for the models analysed here. A re-analysis of the emulation results of 19 AOGCMs presented by Meinshausen et al. (Atmos Chem Phys Discuss 8:6153?C6272, 2008) indicates timescales of 20 and 580?years with an approximate 50:50 partition of the equilibrium gain between the two. This suggests near equal importance of both short and long timescales in determining equilibrium climate sensitivity.     

Latitudinal dependence of signal-to-noise patterns from two general circulation models with CO2 forcing

 Detection of an enhanced greenhouse effect on climate depends on recognition of a signal of change amidst the combined noise of climatic variability and uncertainty in the nature of the signal (functional response to changing CO₂). Using two different GCMs (one with a coupled dynamic upper ocean) and an ensemble of 20 equilibrium experiments with CO₂ ranging from 100 to 3500 ppm, we find that that two measures of signal-to-noise (S/N) for the response of surface temperature to CO₂ forcing are larger over tropical and subtropical oceans than over low-latitude landmasses and larger than at higher latitudes generally. One S/N measure has the noise based solely on inherent model variability, while the other S/N measure includes both this variability and a measure of the uncertainty in the functional nature of the signal. Although the experiments were not for transient forcing and sulphate aerosols and other potentially important forcings (e.g., ozone or solar variability) were not considered, the results suggest that the effects of enhanced greenhouse climate may be detected more readily in surface temperatures from low-latitude oceanic regions than from global or zonal temperature averages. Received: 27 June 1995/Accepted: 28 October 1996     

An example of fingerprint detection of greenhouse climate change

As an example of the technique of fingerprint detection of greenhouse climate change, a multivariate signal or fingerprint of the enhanced greenhouse effect is defined using the zonal mean atmospheric temperature change as a function of height and latitude between equilibrium climate model simulations with control and doubled CO₂ concentrations. This signal is compared with observed atmospheric temperature variations over the period 1963 to 1988 from radiosonde-based global analyses. There is a significant increase of this greenhouse signal in the observational data over this period.These results must be treated with caution. Upper air data are available for a short period only, possibly too short to be able to resolve any real greenhouse climate change. The greenhouse fingerprint used in this study may not be unique to the enhanced greenhouse effect and may be due to other forcing mechanisms. However, it is shown that the patterns of atmospheric temperature change associated with uniform global increases of sea surface temperature, with El NinoSouthern Oscillation events and with decreases of stratospheric ozone concentrations individually are different from the greenhouse fingerprint used here.     

An aridity trend in china and its abrupt feature in association with the global warming

A distinct aridity tread in China in last 100 years is presented by applying a linear fitting to both the climate re-cords and the hydrological records, which is supported by evidence of environmental changes and seems to be associ-ated with a global warming trend during this period.The Mann Kendall Rank statistic test reveals a very interesting feature that the climate of China entered into a dry regime abruptly in about l920’s, which synchronized with the rapid warming of the global temperature at almost the same time.According to an analysis of the meridional profile of observed global zonal mean precipitation anomalies during the peak period of global warming (1930-1940), the drought occurred in whole middle latitude zone (25oN-55oN) of the Northern Hemisphere, where the most part of China is located in. Although this pattern is in good agreement with the latitude distribution of the difference of zonal mean rates of precipitation between 4 × CO2 and 1 × CO2 simu-lated by climate model (Manabe and Wetherald, 1983), more studies are required to understand the linkage between the aridity trend in China and the greenhouse effect.The EOF analysis of the Northern Hemisphere sea level pressure for the season of June to August shows an ab-rupt change of the time coefficient of its first eigenvector from positive to negative in mid-lP^s, indicating an enhancement of the subtropical high over Southeast Asia and the western Pacific after that time. This is an atmos-pheric circulation pattern that is favorable to the development of dry climate in China.     

Towards the detection and attribution of an anthropogenic effect on climate

It has been hypothesized recently that regional-scale cooling caused by anthropogenic sulfate aerosols may be partially obscuring a warming signal associated with changes in greenhouse gas concentrations. Here we use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to test this hypothesis. We use centered [R (t)] and uncentered [C (t)] pattern similarity statistics to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. We show that in most cases, the C (t) statistic reduces to a measure of observed global-mean temperature changes, and is of limited use in attributing observed climate changes to a specific causal mechanism. We therefore focus on R (t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change. Our results indicate that over the last 50 years, the summer (JJA) and fall (SON) observed patterns of near-surface temperature change show increasing similarity to the model-simulated response to combined sulfate aerosol/CO₂ forcing. At least some of this increasing spatial congruence occurs in areas where the real world has cooled. To assess the significance of the most recent trends in R (t) and C (t), we use data from multi-century control integrations performed with two different coupled atmosphere-ocean models, which provide information on the statistical behavior of 'unforced' trends in the pattern correlation statistics. For the combined sulfate aerosol/CO₂ experiment, the 50-year R (t) trends for the JJA and SON signals are highly significant. Results are robust in that they do not depend on the choice of control run used to estimate natural variability noise properties. The R (t) trends for the CO₂-only signal are not significant in any season. C (t) trends for signals from both the CO₂-only and combined forcing experiments are highly significant in all seasons and for all trend lengths (except for trends over the last 10 years), indicating large global-mean changes relative to the two natural variability estimates used here. The caveats regarding the signals and natural variability noise which form the basis of this study are numerous. Nevertheless, we have provided first evidence that both the largest-scale (global-mean) and smaller-scale (spatial anomalies about the global mean) components of a combined CO₂/anthropogenic sulfate aerosol signal are identifiable in the observed near-surface air temperature data. If the coupled-model noise estimates used here are realistic, we can be highly confident that the anthropogenic signal that we have identified is distinctly different from internally generated natural variability noise. The fact that we have been able to detect the detailed spatial signature in response to combined CO₂ and sulfate aerosol forcing, but not in response to CO₂ forcing alone, suggests that some of the regional-scale background noise (against which we were trying to detect a CO₂-only signal) is in fact part of the signal of a sulfate aerosol effect on climate. The large effect of sulfate aerosols found in this study demonstrates the importance of their inclusion in experiments designed to simulate past and future climate change. Received: 10 November 1994 / Accepted: 19 July 1995     

A fractal climate response function can simulate global average temperature trends of the modern era and the past millennium

A climate response function is introduced that consists of six exponential (low-pass) filters with weights depending as a power law on their e-folding times. The response of this two-parameter function to the combined forcings of solar irradiance, greenhouse gases, and SO₂-related aerosols is fitted simultaneously to reconstructed temperatures of the past millennium, the response to solar cycles, the response to the 1991 Pinatubo volcanic eruption, and the modern 1850–2010 temperature trend. Assuming strong long-term modulation of solar irradiance, the quite adequate fit produces a climate response function with a millennium-scale response to doubled CO₂ concentration of 2.0 ± 0.3 °C (mean ± standard error), of which about 50 % is realized with e-folding times of 0.5 and 2 years, about 30 % with e-folding times of 8 and 32 years, and about 20 % with e-folding times of 128 and 512 years. The transient climate response (response after 70 years of 1 % yearly rise of CO₂ concentration) is 1.5 ± 0.2 °C. The temperature rise from 1820 to 1950 can be attributed for about 70 % to increased solar irradiance, while the temperature changes after 1950 are almost completely produced by the interplay of anthropogenic greenhouse gases and aerosols. The SO₂-related forcing produces a small temperature drop in the years 1950–1970 and an inflection of the temperature curve around the year 2000. Fitting with a tenfold smaller modulation of solar irradiance produces a less adequate fit with millennium-scale and transient climate responses of 2.5 ± 0.4 and 1.9 ± 0.3 °C, respectively.     

Transient response to well-mixed greenhouse gas changes

A change in CO₂ concentration induces a direct radiative forcing that modifies the planetary thermodynamic state, and hence the surface temperature. The infrared cooling, by assuming a constant temperature lapse-rate during the process, will be related to the surface temperature through the Stefan–Boltzmann law in a ratio proportional to the new infrared opacity. Other indirect effects, such as the water vapor and ice-albedo feedbacks, may amplify the system response. In the present paper, we address the question of how a global climate model with a mixed layer ocean responds to different rates of change of a well-mixed greenhouse gas such as CO₂. We provide evidence that different rates of CO₂ variation may lead to similar transient climates characterized by the same global mean surface temperature but different values of CO₂ concentration. Moreover, it is shown that, far from the bifurcation points, the model’s climate depends on the history of the radiative forcing displaying a hysteresis cycle that is neither static nor dynamical, but is related to the memory response of the model. Results are supported by the solutions of a zero-dimensional energy balance model.     

Regional climate changes as simulated in time-slice experiments

Three 30 year long simulations have been performed with a T42 atmosphere model, in which the sea-surface temperature (SST) and sea-ice distribution have been taken from a transient climate change experiment with a T21 global coupled ocean-atmosphere model. In this so-called time-slice experiment, the SST values (and the greenhouse gas concentration) were taken at present time CO₂ level, at the time of CO₂ doubling and tripling.The annual cycle of temperature and precipitation has been studied over the IPCC regions and has been compared with observations. Additionally the combination of temperature and precipitation change has been analysed. Further parameters investigated include the difference between daily minimum and maximum temperature, the rainfall intensity and the length of droughts.While the regional simulation of the annual cycle of the near surface temperature is quite realistic with deviations rarely exceeding 3 K, the precipitation is reproduced to a much smaller degree of accuracy.The changes in temperature at the time of CO₂ doubling amount to only 30–40% of those at the 3 * CO₂ level and show hardly any seasonal variation, contrary to the 3 * CO₂ experiment. The comparatively small response to the CO₂ doubling can be attributed to the cold-start of the simulation, from which the SST has been extracted. The strong change in the seasonality cannot be explained by internal fluctuations and cold start alone, but has to be caused by feedback mechanisms. Due to the delay in warming caused by the transient experiment, from which the SST has been derived, the 3 * CO₂ experiment can be compared to the CO₂ doubling studies performed with mixed-layer models.The precipitation change does not display a clear signal. However, an increase of the rain intensity and of longer dry periods is simulated in many regions of the globe.The changes in these parameters as well as the combination of temperature- and precipitation change and the changes in the daily temperature range give valuable hints, in which regions observational studies should be intensified and under which aspects the observational data should be evaluated.     

Multiple temporal scale variability during the twentieth century in global carbon dynamics simulated by a coupled climate–terrestrial carbon cycle model

A coupled climate–carbon cycle model composed of a process-based terrestrial carbon cycle model, Sim-CYCLE, and the CCSR/NIES/FRCGC atmospheric general circulation model was developed. We examined the multiple temporal scale functions of terrestrial ecosystem carbon dynamics induced by human activities and natural processes and evaluated their contribution to fluctuations in the global carbon budget during the twentieth century. Global annual net primary production (NPP) and heterotrophic respiration (HR) increased gradually by 6.7 and 4.7%, respectively, from the 1900s to the 1990s. The difference between NPP and HR was the net carbon uptake by natural ecosystems, which was 0.6 Pg C year^?1 in the 1980s, whereas the carbon emission induced by human land-use changes was 0.5 Pg C year^?1, largely offsetting the natural terrestrial carbon sequestration. Our results indicate that monthly to interannual variation in atmospheric CO₂ growth rate anomalies show 2- and 6-month time lags behind anomalies in temperature and the NiNO₃ index, respectively. The simulated anomaly amplitude in monthly net carbon flux from terrestrial ecosystems to the atmosphere was much larger than in the prescribed air-to-sea carbon flux. Fluctuations in the global atmospheric CO₂ time series were dominated by the activity of terrestrial vegetation. These results suggest that terrestrial ecosystems have acted as a net neutral reservoir for atmospheric CO₂ concentrations during the twentieth century on an interdecadal timescale, but as the dominant driver for atmospheric CO₂ fluctuations on a monthly to interannual timescale.     

Timescales associated with climate change and their relevance in adaptation strategies

Anthropogenic greenhouse gas emissions that induce changes in the Earth’s climate affect particular variables and locations differently. A key part of this difference is the timescale at which this change takes place, which will eventually have important consequences for adaptation requirements. This idea of timescale associated with climate change has been used several times in the past to estimate the urgency of adaptation in particular regions. The definition of climate-change timescale is, however, not unique. For example, we can think of it in terms of an expected trend (e.g. in temperature) reaching a given threshold, or think of it in terms of the time it may take this trend to become statistically significant. We may also wonder about the validity of this speculation given that, due to natural variability, the expected trend may in fact not be realized. In this article we explore alternative ways of defining the timescale of climate-change, compare their properties, and illustrate them with an example for the case of projected surface temperature over North America. It is shown that these timescales are analytically related but may differ substantially in magnitude under certain conditions. In particular, it is shown that climate change impact on vulnerable systems may arrive before statistical detection of the variable’s trend takes place. This fact may have implications on how climate change impacts are seen by those with diverging interests.     

Tropical land savannization: impact of global warming

This study investigates the impact of global warming on the savannization of the tropical land region and also examines the relative roles of the impact of the increase of greenhouse gas concentration and future changes in land cover on the tropical climate. For this purpose, a mechanistic–statistical–dynamical climate model with a bidirectional interaction between vegetation and climate is used. The results showed that climate change due to deforestation is more than that due to greenhouse gases in the tropical region. The warming due to deforestation corresponds to around 60% of the warming in the tropical region when the increase of CO₂ concentration is included together. However, the global warming due to deforestation is negligible. On the other hand, with the increase of CO₂ concentration projected for 2100, there is a lower decrease of evapotranspiration, precipitation and net surface radiation in the tropical region compared with the case with only deforestation. Differently from the case with only deforestation, the effect of the changes in the net surface radiation overcomes that due to the evapotranspiration, so that the warming in the tropical land region is increased. The impact of the increase of CO₂ concentration on a deforestation scenario is to increase the reduction of the areas covered by tropical forest (and a corresponding increase in the areas covered by savanna) which may reach 7.5% in future compared with the present climate. Compared with the case with only deforestation, drying may increase by 66.7%. This corroborates with the hypothesis that the process of savannization of the tropical forest can be accelerated in future due to global warming.     

交叉小波变换在区域气候分析中的应用

将交叉谱与小波变换分析方法相结合,与传统的交叉谱方法相比,交叉小波变换方法用于区域气候变化与大气环流系统之间耦合振荡行为的相关分析更具优越性,不仅可以弥补经典交叉谱分析方法存在的缺陷,而且能够发挥小波变换在时频两域都具有表征气候信号局部化特征的作用;该方法具有较强的耦合信号分辨能力,便于描述耦合信号在时频域中分布状况的优点。采用交叉小波变换分析北极涛动指数(AOI)距平与河南省月平均降水量距平、气温距平序列之间的联合统计特征及其在时频域中的相关关系,根据小波互相关系数、交叉小波凝聚谱和小波位相谱分析北极涛动对河南省气候变化的可能影响。应用结果表明:河南省降水量和气温变化与AOI之间存在着多时间尺度的显著相关振荡,年代际尺度周期上的互相关系数明显大于年际尺度周期,相关程度随耦合振荡频率的增大而减小,相关显著性取决于两者的时频域联合统计特征,时域中小波互相关系数、小波凝聚谱和小波位相谱的分布具有明显的局部化特征;说明北极涛动年际和年代际异常对河南省气候变化具有显著影响。     

1953～2017年黄河源区气温变化的多尺度特征

基于黄河源区8个站点的年平均气温序列,利用集合经验模态分解（Ensemble Empirical Mode Decomposition,EEMD）方法,揭示了以玛多站为代表的黄河源区1953~2017年气温演变的多时间尺度特征,探讨不同时间尺度上的周期振荡对气温变化总体特征的影响程度,分析了黄河源区不同时间尺度的气温变化与海温指数,尤其是与北大西洋多年代际振荡（Atlantic Multidecadal Oscillation,AMO）间的关系。结果表明:（1）1953年以来黄河源区玛多站年平均气温以0.31 ℃/10 a的变化率表现为明显的增暖趋势,20世纪80年代后期开始转暖,尤其是进入20世纪90年代后期变暖更加明显。（2）1953~2017年,黄河源区年平均气温呈现3 a、6 a、11 a、25 a、64 a及65 a以上时间尺度的准周期变化,其中以准3 a和65 a以上时间尺度的振荡最显著,准3 a的年际振荡在21世纪以前振幅较大,而进入21世纪后年际振荡振幅减弱,65 a以上时间尺度的年代际振荡振幅明显加大。（3）1998年气候显著变暖以前,以准3 a周期为代表的年际振荡在气温演变过程中占据主导地位,1998年气候显著变暖以后,65 a以上时间尺度周期振荡的贡献率增加近5倍,与准3 a周期振荡的贡献相当。（4）气温与Nino3.4指数和PDO（Pacific Decadal Oscillation）指数的同期相关均不显著,但当气温领先PDO指数22 a时正相关最大且显著,不同于PDO指数,气温原始序列及其3个年代际尺度分量滞后AMO指数3~7 a或二者同期时相关性最高,这就意味着AMO对黄河源区气温具有显著影响。（5）AMO的正暖位相对应着包括中国的整个东亚地区偏暖,黄河源区只是受影响区域的一部分,20世纪60年代至90年代初期AMO的负冷位相期、20世纪90年代中后期至今AMO的正暖位相与黄河源区气温距平序列的负距平、正距平相对应,气温在65 a以上时间尺度的变化与AMO指数相关性更高,可见,AMO是影响黄河源区气温变化的一个重要的气候振荡,这种影响主要表现在年代际时间尺度上。     

Internal variability,external forcing and climate trends in multi-decadal AGCM ensembles

An atmospheric general circulation model of intermediate complexity is used to investigate the origin and structure of the climate change in the second half of the twentieth century. The variability of the atmospheric flow is considered as a superposition of an internal part, due to intrinsic dynamical variability, and an external part, due to the variations of the sea surface temperature (SST) forcing. The two components are identified by performing a 50-member ensemble of atmospheric simulations with prescribed, observed SSTs in the period 1949–2002. The large number of realizations allows the estimation of statistics of the atmospheric variability with a high confidence level. The analysis performed focuses on interdecadal and interannual variability of 500 hPa geopotential height in the Northern Hemisphere (NH) during winter. The model reproduces well the structure of the observed trend (defined as the difference in the two 25-year intervals 1977–2001 and 1952–1976), particularly in the Pacific region, and about half of the amplitude of the signal. The trend in 500 hPa height projects mainly onto the second empirical orthogonal function (EOF), both in the observations and in the model ensemble. However, differences between the modelled and the observed variability are found in the pattern of the second EOF in the Atlantic sector. SST changes associated with the El Niño southern oscillation (ENSO) are responsible for about 50% of the signal of the 500 hPa height trend in the Pacific. A second 50-member ensemble is used to evaluate the sensitivity of interdecadal variability to an increase in CO₂ optical depth compatible with observed concentration changes. In this second experiment, the simulated trend includes a statistically significant contribution from the positive phase of the Arctic oscillation (AO). Such a contribution is also found in observations. Furthermore, the additional CO₂ forcing accounts for part of the NH trend in near-surface temperature, and brings the zonal-mean temperature changes in the stratosphere and upper-troposphere closer to observations.

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Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields

Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO₂ could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO₂ and temperature or precipitation to have little effect on mean yield changes.     

Asymmetries in tropical rainfall and circulation patterns in idealised CO2 removal experiments

Atmospheric CO₂ removal is currently receiving serious consideration as a supplement or even alternative to emissions reduction. However the possible consequences of such a strategy for the climate system, and particularly for regional changes to the hydrological cycle, are not well understood. Two idealised general circulation model experiments are described, where CO₂ concentrations are steadily increased, then decreased along the same path. Global mean precipitation continues to increase for several decades after CO₂ begins to decrease. The mean tropical circulation shows associated changes due to the constraint on the global circulation imposed by precipitation and water vapour. The patterns of precipitation and circulation change also exhibit asymmetries with regard to changes in both CO₂ and global mean temperature, but while the lag in global precipitation can be ascribed to different levels of CO₂ at the same temperature state, the regional changes cannot. Instead, ocean memory and heat transfer are important here. In particular the equatorial East Pacific continues to warm relative to the West Pacific during CO₂ ramp-down, producing an anomalously large equatorial Pacific sea surface temperature gradient and associated rainfall anomalies. The mechanism is likely to be a lag in response to atmospheric forcing between mixed-layer water in the east Pacific and the sub-thermocline water below, due to transport through the ocean circulation. The implication of this study is that a CO₂ pathway of increasing then decreasing atmospheric CO₂ concentrations may lead us to climate states during CO₂ decrease that have not been experienced during the increase.     

Variation in the climatic response to SRES emissions scenarios in integrated assessment models

Integrated assessment models (IAMs) have commonly been used to understand the relationship between the economy, the earth’s climate system and climate impacts. We compare the IPCC simulations of CO₂ concentration, radiative forcing, and global mean temperature changes associated with five SRES ‘marker’ emissions scenarios with the responses of three IAMs—DICE, FUND and PAGE—to these same emission scenarios. We also compare differences in simulated temperature increase resulting from moving from a high to a low emissions scenario. These IAMs offer a range of climate outcomes, some of which are inconsistent with those of IPCC, due to differing treatments of the carbon cycle and of the temperature response to radiative forcing. In particular, in FUND temperatures up until 2100 are relatively similar for the four emissions scenarios, and temperature reductions upon switching to lower emissions scenarios are small. PAGE incorporates strong carbon cycle feedbacks, leading to higher CO₂ concentrations in the twenty-second century than other models. Such IAMs are frequently applied to determine ‘optimal’ climate policy in a cost–benefit approach. Models such as FUND which show smaller temperature responses to reducing emissions than IPCC simulations on comparable timescales will underestimate the benefits of emission reductions and hence the calculated ‘optimal’ level of investment in mitigation.     

Climatic timescale temperature and precipitation increases on long Island,New York

Abstract

Global warming due to increased greenhouse gases is believed to result in not only higher surface temperatures but also an acceleration of the hydrological cycle leading to increased precipitation. Although climate models consistently predict increases in global temperatures due to increasing greenhouse gases and the accompanying global warming, observations at the climatic timescales necessary to confirm the models are rare. Multidecadal studies at global and regional scales are necessary to determine whether the presently observed changes in temperature and precipitation are due to short‐term fluctuations or long‐term trends. In this study, we address this issue by examining changes in temperature and precipitation on Long Island, New York over a 74‐year time period (1931 to 2004) using a network of rain gauges and temperature measurements. The mean annual temperature on Long Island has increased at a rate of 0.05°C per decade, which is less than that of observed global values and is most likely due to the urban warming effects of New York City, not large‐scale climate change. The mean total annual precipitation has increased at a rate of 0.71 cm per decade during the study period, which is consistent with global observations. Intra‐annual temperature fluctuations are decreasing at a rate of 0.36% per decade, while precipitation variations are increasing at a rate of 0.91% per decade. Empirical orthogonal function analysis indicates that variations in temperature and precipitation on Long Island are dominated by island‐wide fluctuations that are directly related to the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño Southern Oscillation.     

Climatic variability within an equilibrium greenhouse simulation

A simulation of the possible consequences of a doubling of the CO₂ content of the atmosphere has been performed with a low resolution global climatic model. The model included the diurnal and seasonal cycles, computed sea ice amount and cloud cover, and used implied oceanic heat fluxes to represent transport processes in the oceans. A highly responsive 2-layer soil moisture formulation was also incorporated. Twenty year equilibrated simulations for control (1 × CO₂) and greenhouse (2 × CO₂) conditions were generated. The major emphasis of the analysis presented here is on the intra-annual and interannual variability of the greenhouse run with respect to the control run. This revealed considerable differences from the time-averaged results with occasions of marked positive and negative temperature deviations. Of particular interest were the periods of negative temperature departures compared to the control run which were identified, especially over the Northern Hemisphere continents. Temporal and spatial precipitation and soil moisture anomalies also occurred, some of which were related to the surface temperature changes. Substantial sea surface temperature anomalies were apparent in the greenhouse run, indicating that a source of climatic forcing existed in addition to that due to doubling of the CO₂. Comparison of the intra-annual and interannual variability of the control run with that of the greenhouse run suggests that, in many situations, it will be difficult to identify a greenhouse signal against the intrinsic natural variability of the climatic system.