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It is known that US paper currency in the general circulation is contaminated with cocaine. Several mechanisms have been offered to explain this finding, including contamination due to handling during drug deals and the use of rolled up bills for snorting. Drug is then transferred from one contaminated bill to others during counting in financial institutions. The possibility of contamination of currency with other drugs has not been reported. In this study, the author reports the analysis of 10 randomly collected US$ 1 bills from five cities, for cocaine, heroin, 6-acetylmorphine (6-AM), morphine, codeine, methamphetamine, amphetamine and phencyclidine (PCP). Bills were immersed in acetonitrile for 2h prior to extraction and GC-MS analysis. Results showed that 92% of the bills were positive for cocaine with a mean amount of 28.75+/-139.07 microg per bill, a median of 1.37 microg per bill, and a range of 0.01-922.72 microg per bill. Heroin was detected in seven bills in amounts ranging from 0.03 to 168.50 microg per bill: 6-AM and morphine were detected in three bills; methamphetamine and amphetamine in three and one bills, respectively, and PCP was detected in two bills in amounts of 0.78 and 1.87 microg per bill. Codeine was not detected in any of the US$ 1 bills analyzed. This study demonstrated that although paper currency was most often contaminated with cocaine, other drugs of abuse may be detected in bills.

A study of the quantities of cocaine on banknotes in general circulation was conducted to investigate regional variations across England and Wales. No meaningful support was found for the proposition that there is regionalvariation in the quantities of cocaine in banknotes in general circulation in England and Wales.

Changes in winter low flow (WLF) in cold-region rivers affect engineering design, water quality, and river ecosystem health. This paper aims to quantify to what extent WLF will change under climate warming and to propose a practical forecasting model for WLF predictions. The new concept of cumulative watershed temperature (CWT) is used as a convenient lumped surrogate for complicated hydrological processes that influence WLF. Statistical analyses of century-long flow data from the Fraser River in British Columbia, Canada show a strong dependence of WLF on CWT. In winter season, time series of CWT and WLF are shown to each divide into a falling and a rising limb at the data point of their lowest values, being −358 °C and 827 m3/s (historical averages), respectively. The falling and rising limbs describe the cumulative freezing and thawing effects of air temperatures fluctuating around the freezing point on WLF changes. The correlation between CWT and WLF (time series) data points on the rising limbs forms the forecasting model, expressing WLF as a function of CWT in terms of their z-scores. The model takes input of Global Circulation Model (GCM) projections of temperature increases by the end of 21st century under different Representative Concentration Pathways (RCPs), and predicts changes of Fraser River WLF from the historical average. RCP4.5 causes a 22.6% increase (ensemble average from six GCMs). RCP8.5 increases WLF by 20% (for some future years) to 44% (for others). The methods reported in this paper can be adapted to other cold regions.

This paper builds on recent work in the critical geographical literature concerned with advancing a more nuanced engagement with climate change science and linked knowledges. The main aim of this paper is to provide insight into the character of Soviet climate science, and reflect on the contribution of Soviet scientists to the international debate concerning anthropogenic climate change and associated forecasting as it developed from the late 1950s through to the first report of the IPCC in 1990. Such a focus is significant for a number of reasons. First, Soviet contributions are given short shrift in general reviews concerning the development of the basic science underpinning anthropogenic climate change, emerging as a subdued ‘other’ despite their relative importance during this period at the international level. Second, the Soviet contingent also played an influential role in the formation of the IPCC as well as the development of associated debates concerning the establishment of future climate change scenarios. Third, the early IPCC process resulted in the relative marginalisation of Soviet scientific input framed by debates over the most effective way to determine future climate change scenarios. The paper examines the significance of Soviet science for the evolving climate change debate on the international stage, and the related involvement of a handful of Soviet scientists in the activities of international bodies such as the World Meteorological Organisation (WMO). It also examines the role of Soviet scientists in the consolidation of a natural science conceptualisation of anthropogenic climate change during the late 1980s. It is shown how the Soviet contingent came to place an emphasis on the use of palaeoclimatic analogues in order to predict future climates, albeit whilst recognising the value of the computer modelling approach favoured by many Western climatologists. Nevertheless, this preference for an analogue approach and resultant debates surfaced strongly during the early work of the IPCC. The robust advancement of General Circulation Models (GCMs) as the prime forecasting technique within Working Group I resulted in the effective side-lining of the Soviet contingent during the process of finalising the first IPCC report in 1990.

The thermal regime of the middle atmosphere is determined to a great extent by the balance between the incoming solar and outgoing infrared radiation. To account for these processes in numerical models of the middle atmosphere, parameterizations that are capable of quickly and accurately calculating infrared cooling and solar heating rates are required. These parameterizations should include the breakdown of local thermodynamic equilibrium (LTE) conditions and allow for feedbacks by ensuring that dependencies on all input parameters are accounted for. This paper discusses the major mechanisms responsible for maintaining the radiative energy budget of the middle atmosphere and presents a brief review of approaches and numerical schemes currently available for use in general circulation models. The main focus of the paper is on the approaches and schemes designed for non-LTE treatment.

This tutorial paper discusses the problem of parameterizing unresolved gravity waves in general circulation models (GCMs) of the middle atmosphere. For readers who are unfamiliar with middle atmosphere dynamics a review of the basic dynamics of both the large-scale circulation and internal gravity waves is presented. A fairly detailed and physically-based description is given of several gravity wave drag (GWD) schemes that are currently employed in middle atmosphere GCMs. These include the parameterizations of McFarlane (1987) , Medvedev and Klaassen (1995) , and Hines, 1997a , Hines, 1997b , which are used in the Canadian Middle Atmosphere Model, as well as the parameterization of Fritts and Lu (1993) , which is used in the TIME-GCM. Results from a mechanistic model and the two above mentioned GCMs are presented and discussed. This paper is not intended as a review of all GWD parameterizations nor is it meant as a quantitative comparison of the schemes that have been chosen.

Policy makers, responsible for the economic well-being of regions and states, have sought a variety of tools for predicting global change. One set of tools for simulating climate change, at a global scale, are the general circulation models (GCMs). Current versions of GCMs are limited to global studies, which are spatially crude and have output that is of minimal use to decision-makers accustomed to day-to-day, synoptic-scale changes in weather events. This paper discusses the use of a mesoscale model to “downscale” GCM output to the regional and local scales desired by policy makers. It presents a “nested” dynamical modeling approach. The paper also addresses several issues associated with the dynamical linking of GCMs and mesoscale models. Issues having to do with the choice of an atmospheric system, a variable as the best indicator of climate change, or having to do with validation of mesoscale simulations, which were based on GCM output, are considered.

This paper reviews the current state of comprehensive, three-dimensional, time-dependent modelling of the circulation in the middle and upper atmosphere from a meteorologist's perspective. The paper begins with a consideration of the various components of a comprehensive model (or general circulation model, GCM), including treatments of processes that can be explicitly resolved and those that occur on scales too small to resolve (and that must be parameterized). The typical performance of GCMs in simulating the tropospheric climate is discussed. Then some important background on current ideas concerning the general circulation of the stratosphere and mesosphere is presented. In particular, the transformed-Eulerian mean flow formalism, the role of vertically-propagating internal gravity waves in driving the large-scale circulation, and the notion of a stratospheric surf zone are all briefly reviewed. Using this background as a guide, some middle atmospheric GCM results are discussed, with a focus on simulations made recently with the GFDL ‘SKYHI’ troposphere-stratosphere-mesosphere GCM. The presentation attempts to emphasize the interaction between theory and comprehensive modelling. Many theoretical notions cannot be confirmed in detail from observations of the real atmosphere due to the various limitations in the observational methods, but can be very completely examined in GCMs in which every atmospheric variable is known perfectly (within the limits of the numerical methods). It will be shown that our understanding of both the role of gravity waves in the general circulation and the nature of the stratospheric surf zone has benefited from analysis of GCM results. From the point of view of the upper atmosphere, one of the most interesting aspects of GCMs is their ability to generate a self-consistent field of upward-propagating gravity waves. This paper concludes with a discussion of the gravity wave field in the middle atmosphere of GCMs. Comparisons of the explicitly-resolved gravity wave field in the SKYHI model with observations are quite encouraging, and it seems that the model is capable of producing a gravity wave field with many realistic features. However, the simulated horizontal spectrum of the eddy momentum fluxes associated with the waves is quite shallow, suggesting that much of the spectrum that is important for maintaining the mean circulation is not explicitly resolvable in current GCMs. A brief discussion of current efforts at parameterizing the mean flow effects of the unresolvable gravity waves is presented.

In this technical report we present the compilation of the abstract of the papers presented at the Joint EU-Japan meeting held in Venice, Dec 6-7, 2006.The European groups and the Frontier group have been cooperating now for almost ten years. The cooperation has been developing exploiting a string of EU projects (SINTEX, ENSEMBLES, CIRCE, DYNAMITE) and national initiatives and centers, like the Max-Planck Institut in Hamburg and the newly established Euromediterranean Center for Climate Change (CMCC) in Italy.The cooperation has been a very fruitful one, several important results have been obtained, many papers have been published, but most importantly a lasting scientific relation has been established.The quasi-annual meetings have marked this advance and served as a checking point for the development of our joint science.

Climate classifications based on temperature and precipitation measurements are increasingly being used for environmental and climate change studies. Using three classification methods (Koppen, Extended Koppen, and Holdridge) and one observational dataset for present climate (CRU, Climate Research Unit), we show that GCMs have bridged the gap that led to the emergence of RCMs thirty years ago, as GCMs can now provide global climate classifications whose accuracy and precision are comparable to those of regional outputs of the RCMs. Projections of high-resolution GCMs for future climates under the assumptions of three Representative Concentration Pathways (RCP26, RCP45 and RCP85) can therefore be used as a primary source for climate change and global warming studies at high resolution. This paper provides comprehensive, model-derived climate classifications for the entire planet, using RCMs and two GCMs for present and future climate-change scenarios, and discusses how well the models actually represent the climates of the world when compared with reference, ground validation data. It turns out that both GCMs and RCMs appear still limited to provide practical estimates of the world climates even for present climate conditions. The modeling of precipitation remains the Achilles' heel of models and thus of multidimensional indices, which are very sensitive to this variable. The conclusion is that model outputs at regional scale need to be taken with extreme caution without venturing into informing policies presenting potentially large societal impacts. Nonetheless, the role of models as privileged tools to advance our scientific knowledge of the Earth's system remains undisputed.

Most estimates of Chinese regional Surface Air Temperatures since the late-19th century have identified two relatively warm periods – 1920s–40s and 1990s–present. However, there is considerable debate over how the two periods compare to each other. Some argue the current warm period is much warmer than the earlier warm period. Others argue the earlier warm period was comparable to the present. In this collaborative paper, including authors from both camps, the reasons for this ongoing debate are discussed. Several different estimates of Chinese temperature trends, both new and previously published, are considered. A study of the effects of urbanization bias on Chinese temperature trends was carried out using the new updated version of the Global Historical Climatology Network (GHCN) – version 4 (currently in beta production). It is shown that there are relatively few rural stations with long records, but urbanization bias artificially makes the early warm period seem colder and the recent warm period seem warmer. However, current homogenization approaches (which attempt to reduce non-climatic biases) also tend to have similar effects, making it unclear whether reducing or increasing the relative warmth of each period is most appropriate. A sample of 17 Chinese temperature proxy series (12 regional and 5 national) is compared and contrasted specifically for the period since the 19th century. Most proxy series imply a warm early-20th century period and a warm recent period, but the relative warmth of these two periods differs between proxies. Also, with some proxies, one or other of the warm periods is absent.

Anthropogenic warming may change precipitation patterns, impacting infrastructure performance and reliability. Future precipitation statistics generated using General Circulation Models (GCM) are, however, often biased and not easily applied to problems such as runoff estimation. Stochastic weather generation is hence used as an alternative to GCMs in hydrology and hydraulic modelling. This paper explores the dependence of fine temporal precipitation characteristics on air pressure and air temperature using historic observations. The goal is to develop, based on the key causes of precipitation, a climatological basis for a stochastic precipitation generator for non-stationary precipitation under climate change conditions. The analysis focuses on precipitation in the urban Northeast United States and utilizes pooled observations from meteorological stations in New York City, Philadelphia, and Boston over 60 years. A negative correlation between hourly Probability of Precipitation (POP) and air pressure is observed. When the historical records are discretized using air Pressure Change Events (PCE), Decreasing Pressure Change Events (DePCEs) had a higher POP and a higher Precipitation Depth (PD) than Increasing Pressure Change Events (InPCEs). Temperature was more strongly associated with PD during DePCEs than InPCEs; this association was more pronounced during high magnitude PCEs and extreme events. The potential for simulating future hourly precipitation by associating historic hourly precipitation patterns with PCE’s and monthly temperature is assessed.

Given that water security is likely to worsen with climate change, rainwater harvesting is one solution that may improve drinking water access directly at home. Although rainwater harvesting devices may be able to reduce drinking water insecurity, this has never been tested systematically across a variety of climates for different climate change scenarios using consistent assumptions. Therefore, the goal of this paper is to assess the ability of rainwater harvesting devices to improve domestic water security in each of the major climate zones under different climate change scenarios and to make design recommendations to achieve levels of reliability for each climatological region. The coupled model incorporates a stochastic weather generator (LARS-WG) to simulate synthetic daily rainfall using historic weather data from 94 sites chosen to represent all Koppen – Griegel climate classification zones. Simulations are run up to year 2099 for three different climate change scenarios using 15 downscaled General Circulation Models. Combinations of different roof area and tank sizes are studied to assess rainwater harvesting system reliability. Results indicate that climate change will have little impact on rainwater harvesting and that rainwater harvesting can reduce domestic water insecurity even in arid regions. Results of this study can be used by implementing agencies to prioritize regions where rainwater harvesting can be effective and to help communities design systems to meet given levels of reliability.

This paper explored the projected changes in precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) Tmax (Tmin) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, Tmax (Tmin) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections.

Several schemes have been proposed for handling gaseous overlapping bands in the context of the correlated k-distribution model (CKD), but they all require manual operation and the accuracy is limited. In this paper, we proposed two automatic methods for gas absorption calculation based on correlated k-distribution, namely finding point method (FPM) and re-optimized method (ROM), to improve the accuracy and the speed of gaseous absorption calculation. Compared with the line-by-line (LBL) results under standard profiles, the resulting accuracy of FPM is 0.09 Kday−1 in troposphere, -0.3 Kday−1 in stratosphere, -0.18 W/m2 for upward flux and -0.44 W/m2 for downward flux; the accuracy of ROM is 0.1 Kday−1 in troposphere, 0.3 Kday−1 in stratosphere, -0.35 W/m2 for upward flux and -0.18 W/m2 for downward flux. The accuracy of the two methods is higher than rapid radiative transfer model for general circulation models (RRTMG). Under realistic profiles, the accuracy of FPM and ROM is slightly lower than that their accuracy under standard profiles but still higher than RRTMG.

High-performance computing of atmospheric general circulation models (AGCMs) has been receiving increasing attention in earth science research. However, when scaling to large-scale multi-core computing, the parallelization of an AGCM which demands fast parallel computing for long-time integration or climate simulation becomes extremely challenging due to its inner complex numerical calculation. The previous Institute of Atmospheric Physics of the Chinese Academy of Sciences Atmospheric General Circulation Model version 4.0 (IAP AGCM4.0) with one-dimensional domain decomposition can only run on dozens of CPU cores, so the paper proposes a two-dimensional domain decomposition parallel algorithm for it. In the parallel implementation of the IAP AGCM4.0, its dynamical core utilizes a hybrid form of latitude/longitude decomposition and vertical direction/longitude circle direction decomposition. Through experiments on a multi-core cluster, we confirmed that our algorithm is efficient and scalable. The parallel efficiency of the IAP AGCM4.0 can reach up to 50.88% on 512 CPU cores, and the IAP AGCM4.0 can be run long-term simulations for climate change research.

This paper quantifies the K 1 internal tide simulated by the 1/10° STORMTIDE model, which simultaneously resolves the eddying general circulation and tides. An evident feature of the K 1 internal tide is the critical latitude φ c at 30°, which in the STORMTIDE model is characterized by variations from a high energy level equatorward of 30° to a low energy level poleward of 30°. This critical latitude separates the internal tide dynamics into bottom-trapped (at latitudes |φ| > |φ c |) and freely propagating (at |φ| c |) motions, respectively. Both types of motions are examined. The bottom-trapping process reveals a gradual vertical decrease of wave energy away from the bottom. The vertical scale, over which the wave energy decrease occurs, is smaller in shallow than in deep water regions. For the freely propagating K 1 internal tides, the STORMTIDE model is able to simulate the first three low modes, with the wavelengths ranging from 200–400 km, 100–200 km, to 60–120 km. These wavelength distributions reveal not only a zonal asymmetry but also a poleward increase up to φ c , in particular in the Pacific. Such distributions indicate the impact of stratification N and the Coriolis frequency f on the wavelengths. The large wavelength gradient near φ c is caused by the wavelength increase from finite values at subcritical latitudes to infinity at φ c . Compared to the M 2 internal tide, the lower K 1 tidal frequency leads to a stronger role of f , hence a weaker effect of N , for the K 1 internal tide.

Due to the diversity of pollution types, previous assessment methods have mostly been based on local conditions. In addition, polluted regions may transfer pollutants to other areas via general circulation of the atmosphere, surface or groundwater flows, and trade. This means that polluted regions actually suffer from fewer pollution hazards than they should and that the contribution of clean areas to the process of environmental purification is also underestimated. When comparing different areas, few studies have well identified, on a global scale, where most of such pollution problems come from. Observational experiments have shown that the slight reduction in the global oxygen pool can be attributed to pollutants, especially in the processes of fossil fuels and biomass burning, as well as contaminant production and degradation. Therefore, this paper innovatively proposes to use oxygen consumption via pollutant production and degradation as a unified indicator, i.e., the pollution manufacturing index (PMI), to quantitatively address the relative contribution of any country to global pollution. The greater the PMI is, the greater the amount of pollution produced in a country, and vice versa. Our results classify all countries into three categories. Approximately 25.6% of countries are contributors to global pollution (PMI>0.5), almost 46.4% of countries are balanced and make nonsignificant contributions to purification and pollution (0.5 > PMI > −0.5), and approximately 28% of countries are purification contributors (PMI

The selection of global climate models (GCMs) for a region remained a difficult step in climate change studies. A state-of-the-art Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm is proposed in this paper for GCM selection. The ranking of GCMs obtained using SVM-RFE was compared to that obtained using entropy-based similarity assessment index known as Symmetrical Uncertainty (SU). The study was conducted in the sub-Himalayan region of Pakistan where a reliable projection of climate is highly significant for water resources management in the entire western part of South Asia. The RF-based regression model was employed to generate a multi-model ensemble (MME) mean of the top-ranked GCMs. The MME mean projection was utilized to estimate the spatiotemporal changes in annual precipitation in comparison with precipitation of 1961‐–2000 for various representative concentration pathway (RCP) scenarios. The SVM-RF selected five GCMs (MIROC5, EC-EARTH, CNRM-CM5, BCC-CSM1.1(m) and BCC-CSM1.1) as most suitable for climate change projections in the study area. Obtained results were found to collaborate well with the results of multiple conventional statistical metrics. The MME mean projections revealed precipitation alteration between −1% and 18% during 2020‐–2059, and 0 and 24% during 2060–2099 for different RCPs. Precipitation was projected to increase up to 20% in the north whereas a decrease up-to −16% in the south.

Urban areas are particularly vulnerable to heat wave (HW). This paper will examine the important question on urban heat island (UHI) during HW and their interactions under present and future conditions. Therefore, a 1 km-resolution urban dynamical downscaling technique has been applied over the Brussels Capital Region. Results from observations, ERA-Interim driven simulations (1981–2010), present (1990–1999) and future (2046–2055) climate simulations under the A1B scenario of the global climate model ARPEGE-Climat indicate that for the present climate: (i) observed nighttime UHI is enhanced under HW by 1.5 °C (0.6 °C ERA-Interim), (ii) due to a dry summer bias in ARPEGE-Climat, the control simulation was not able to reproduce the UHI intensification during HW, and (iii) in the ERA-Interim runs, HW affects urban and rural surface energy balance differently. Hereby, the HW definition and heat stress index are based upon the warnings issued by the Public Health of Belgium. For the 2050s, climate change increases, statistically significant, the intensity of HW for urban (rural) areas during the night (day). Under future HW, the biggest and statistically significant increase of the ratio of number of hours to number of days while the Humidex is above dangerous (> 40) thresholds occurs over urban areas.

In this paper, the dynamics of the Lorenz model of general circulation of the atmosphere is investigated. The global exponential attractive set and positively invariant set are obtained based on well-known Lyapunov stability theory and the function extremum theory for this low-order atmospheric circulation chaotic model. Furthermore, the exponential rate of the trajectories going from the exterior of the attractive set to the interior of the attractive set is also obtained. At last, numerical studies are provided to illustrate the effectiveness of the presented scheme.

This work investigates the prospective impacts of climate change on wind-driven rain (WDR) and walls through simulating the hygrothermal performance of rain screen of common vertical wall constructions for the climatic conditions of Gothenburg in Sweden. While a substantial amount of work has been done on the impact of climate change on the thermal performance of buildings, this paper studies its impact - through changes in rain, wind and other climatic parameters - on the amount of water which penetrates the outmost layer of ventilated facades. Importance of three uncertainty factors of the climate data are investigated: uncertainties from global climate models, emissions scenarios and spatial resolutions. Consistency of the results is examined by modelling walls with different materials and sizes, as well as using two mathematical approaches for WDR modelling. Sensitivity of the wall simulations to the wind data is assessed by using synthetic climate with sole wind data. According to the results, higher amounts of moisture will accumulate in walls in the future; climate uncertainties can cause variations up to 13% in the calculated 30-year average of water content and 28% in its standard deviation. Using sole wind data can augment uncertainties with up to 10% in WDR calculations, however it is possible to neglect changes in future wind data.

The description of the hydrological cycle in Atmospheric General Circulation Models (GCMs) can be validated using water isotopes as tracers. Many GCMs now simulate the movement of the stable isotopes of water, but here we present the first GCM simulations modelling the content of natural tritium in water. These simulations were obtained using a version of the LMDZ General Circulation Model enhanced by water isotopes diagnostics, LMDZ-iso. To avoid tritium generated by nuclear bomb testing, the simulations have been evaluated against a compilation of published tritium datasets dating from before 1950, or measured recently. LMDZ-iso correctly captures the observed tritium enrichment in precipitation as oceanic air moves inland (the so-called continental effect) and the observed north-south variations due to the latitudinal dependency of the cosmogenic tritium production rate. The seasonal variability, linked to the stratospheric intrusions of air masses with higher tritium content into the troposphere, is correctly reproduced for Antarctica with a maximum in winter. LMDZ-iso reproduces the spring maximum of tritium over Europe, but underestimates it and produces a peak in winter that is not apparent in the data. This implementation of tritium in a GCM promises to provide a better constraint on: (1) the intrusions and transport of air masses from the stratosphere and (2) the dynamics of the modelled water cycle. The method complements the existing approach of using stable water isotopes., Accepted paper version. See published version in EPSL Elsevier website

This paper describes a scalable system for quantifying hyper-local heat stress in urban environments and its expected response within the changing climate. A hybrid dynamical-statistical downscaling approach links Global Climate Models (GCMs) with dynamically downscaled extreme heat events using the Weather Research and Forecasting model (WRF). Downscaled historical simulations in WRF incorporate urban canopy physics to better describe localized land surface details in the urban environment relevant to extreme heat. This downscaled library is then used in an analog-based approach. This contribution reports a series of enhancements to existing analog-based methods which can efficiently produce more detailed results. The system here uses advanced statistical methods and simple machine learning (ML) techniques to optimize analog selection, perform spatially-consistent bias correction, and decompose patterns of extreme heat into dynamic components such as the land-sea contrast and inland sea-breeze penetration. Hindcast projections are validated against observational data from in-situ weather observing stations. The results demonstrate the scalability and efficiency of this system as it is deployed in cloud-based architectures with parallelized code. Downscaled predictions are equally applicable to heat stress at weather and climate time scales, supporting infrastructure resilience and adaptation, and emergency response.

This paper presents the release of LTRANS-Zlev, which is a new version of the off-line Lagrangian ocean particle-tracking model LTRANS v.2b that is compatible with a Z-coordinate (constant-depth layers) discretization of the hydrodynamic equations. The model capitalizes on and massively extends the capabilities of the original code LTRANS, which is already quite popular, but can be used only adopting a sigma-coordinate (terrain-following layers) discretization. Among the additional features included in LTRANS-Zlev, there are the backward-in-time particle-tracking algorithm and some new customizable larval behaviour options. The new version also includes the OILTRANS-module for oil spill simulations. The new implementations were validated by using the output of the Z-coordinate Massachusetts Institute of Technology general circulation model (MITgcm) for an idealized case study describing a cyclonic gyre in a mid-latitude closed basin. Another test-case, in which larval dispersal is modelled in the northern Adriatic Sea, illustrates some of the new features of LTRANS-Zlev.

The impact of radiative transfer scheme on global climate model (GCM) simulation is presented in this paper by comparing the difference between δ-two-stream adding method (δ-2DDA) and adding algorithm of the δ-four-stream discrete ordinates method (δ-4DDA) radiation schemes in the Atmospheric General Circulation Model of the Beijing Climate Center (BCC_AGCM). Only consider the effects of the calculation method itself, the δ-4DDA reduces the negative shortwave cloud radiative effect (CRE) in the areas with a significant fraction of low cloud, while enhances the negative shortwave CRE in the areas with the large fraction of high cloud. For the longwave CRE, the δ-4DDA enhances the longwave CRE drastically in the regions with a significant fraction of the high cloud. The feedback of clouds results in more interesting results. The δ-4DDA produces more accurate shortwave CRE in the region over the land and ocean in the middle and high latitude areas. The longwave CRE simulated by δ-4DDA is better than that affected by δ-2DDA over the ground in Africa, South America, and Atlantic. The change of radiation scheme affects the simulation of other meteorological variables. The simulation of global humidity by δ-4DDA is improved obviously. The δ-4DDA simulates more accurate temperature in continents of the northern hemisphere and precipitation in North America, Africa, northern Indian Ocean and western Pacific. Although the improvement of every physical process is required to develop the models, implementing δ-4DDA scheme into GCM and evaluating the effect of it are necessary and meaningful.

In this paper, point prediction and prediction intervals (PIs) of artificial neural network (ANN) based downscaling for mean monthly precipitation and temperature of two stations (Tabriz and Ardabil in North West of Iran) were evaluated using general circulation models (GCMs). PIs were constructed by novel Upper Lower Bound Estimation (LUBE) method in which an ANN with two outputs was constructed for estimating the prediction bounds. Also, Bootstrap method as a classic technique for assessing uncertainty of ANN was used to further examine the proposed LUBE method. In this way, the accuracy of PIs was quantified by coverage and width criteria. Three GCMs, Can-ESM2, BNU-ESM, INM-CM4 and ensemble-GCM (ensemble of mentioned models) were used in four grid points around each of station for evaluating ANN-based downscaling of precipitation and temperature parameters. Comparison between the results of two methods indicated that LUBE method could lead to more reliable results than the Bootstrap method. PIs width and coverage probability were 10–40% lower and 2–10% higher than the Bootstrap method for different GCMs, respectively. Ensemble-GCM led to more accurate results so that computed PIs width and coverage probability were 10–60% lower and 2–20% higher than those for the single GCMs.

In a recent issue of this journal, Loehle (2014) presents a “minimal model” for estimating climate sensitivity, identical to that previously published by Loehle and Scafetta (2011) . The novelty in the more recent paper lies in the straightforward calculation of an estimate of transient climate response based on the model and an estimate of equilibrium climate sensitivity derived therefrom, via a flawed methodology. We demonstrate that the Loehle and Scafetta model systematically underestimates the transient climate response, due to a number of unsupportable assumptions regarding the climate system. Once the flaws in Loehle and Scafetta's model are addressed, the estimates of transient climate response and equilibrium climate sensitivity derived from the model are entirely consistent with those obtained from general circulation models, and indeed exclude the possibility of low climate sensitivity, directly contradicting the principal conclusion drawn by Loehle. Further, we present an even more parsimonious model for estimating climate sensitivity. Our model is based on observed changes in radiative forcings, and is therefore constrained by physics, unlike the Loehle model, which is little more than a curve-fitting exercise.

Evaluating the usefulness and the reliability of retrofitted buildings for future climate can be a challenging task, while different scenarios and uncertainties exist both for retrofitting buildings and future climate. This paper presents a method to assess and quantify the relative robustness of retrofitting measures on long term, while climate variations in different time scales, extreme conditions and uncertainties of climate change are considered. The applicability of the method is examined by comparing two energy retrofitting measures for the existing residential building stock of Stockholm, whose energy performance is numerically simulated during 1961-2100 for five climate scenarios. The considered climate uncertainties are due to downscaling climate data from five different global climate models. The relative robustness of the retrofitting measures are evaluated in five time scales; hourly, daily, monthly, annual and 20-year period. The presented method facilitates the assessment and ranking of retrofitting measures, using few numbers. It also generates an overall view about the relative performance of retrofitting measures in different time scales. (C) 2014 Elsevier B.V. All rights reserved

Signage system is important to lead occupants to circulate as well as to evacuate people in emergency. Multiple exit signs leading to different directions at an intersection for general circulation may create confusion in people under emergency, and therefore can jeopardize the situation into a chaotic state, especially in buildings with a complex layout. Many past studies focused on implementing different techniques or designs to improve the existing signage system for better visual and navigating effects, such as the use of laser beams, the combination of audio and video cues, and the selection of color, location, and mounting height. How to better control the signage system under emergency has been overlooked. This paper proposed a BIM-controlled signage system to solve the problem. With the help of heat sensors that detect the fire prone areas in the building, the proposed system identifies the best route and activates the corresponding sign blinkers with high intensity. During this action, exit signs that do not lead to the best route become inactive. This system provides a natural interface for remote operation in facility management to efficiently guide people to the right exit under emergency. A prototype of the signage system is presented and future research directions are discussed.

Downscaled global climate models can be used to investigate the regional impacts of future emission scenarios. The downscaled models can be validated by how well they can reproduce past, observed climate. This paper investigates the possible future climate of Lake Kariba in Northwestern Zimbabwe under the Intergovernmental Panel on Climate Change's (IPCC) A2 and B1 emission scenarios for the near (2046–2065) and far future (2081–2100). Nine models were employed and all reflected past climate (1961–2009) well, accurately reproducing the annual cycle and capturing the unimodal annual rainy season and temperatures summer maxima and winter minima. The models project a drier climate with an average decrease in rainfall ranging from 3% to 27.46% with the exception of increased rainfall around the early rainy period (October–November) under A2 and in March under both scenarios for both the near and far future periods. Models predict that both minimum and maximum temperatures will increase by an average of 3.17–3.42 °C. A polynomial (order 3) model was used to investigate the implications of the future climate projections on the sardine fish Limnothrissa miodon (Kapenta) production based on the median of all nine models for future climate. If all conditions remain the same the Kapenta fish production in Lake Kariba could continue to decline. Options and strategies for fishery management that can boost Kapenta fish production are suggested in the wake of such possible, detrimental future climate changes.

To project future river discharge in the Yangtze River basin, artificial neural networks were used in this study. Based on observed precipitation, temperature, and river discharge data from 1961 to 2000, artificial neural networks were trained and calibrated. The paper projects river discharges at Yichang and Datong hydrological stations under three greenhouse gas emission scenarios from 2011 to 2050 in the Yangtze River basin, by applying climate projections of global climate model ECHAM5/MPI-OM. The results show that annual river discharges at two hydrological stations have no obvious trends and their decadal variations are also small under three emission scenarios. Seasonal discharges at Yichang and Datong have different trends during 2011–2050. Ratios of river discharge in four seasons within a year tend to change.

This paper describes the model speed and model In/Out (I/O) efficiency of the high-resolution atmospheric general circulation model FAMIL (Finite-volume Atmospheric Model of IAP/LASG) at the National Supercomputer Center in Tianjin, China, on its Tianhe-1A supercomputer platform. A series of three-model-day simulations were carried out with standard Aqua Planet Experiment (APE) designed within FAMIL to obtain the time stamp for the calculation of model speed, simulation cost, and model I/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3456 and 6144 cores, and the lowest simulation costs are 1536 and 3456 cores for 12.5 km and 6.25 km resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and an efficiency of more than 80% on 6 I/Os and more than 99% on 1536 I/Os.

The concern on climate change leads to growing demand for minimization of energy use. As building is one of the largest energy consuming sectors, it is essential to study the impact of climate change on building energy performance. In this regard, building energy simulation software is a useful tool. A set of appropriate typical weather files is one of the key factors towards successful building energy simulation. This paper reports the work of developing a set of weather data files for subtropical Hong Kong, taking into the effect of future climate change. Projected monthly mean climate changes from a selected General Circulation Model for three future periods under two emission scenarios were integrated into an existing typical meteorological year weather file by a morphing method. Through this work, six sets of future weather files for subtropical Hong Kong were produced. A typical office building and a residential flat were modeled using building simulation program EnergyPlus. Hourly building energy simulations were carried out. The simulated results indicate that there will be substantial increase in A/C energy consumption under the impact of future climate change, ranging from 2.6% to 14.3% and from 3.7% to 24% for office building and residential flat, respectively.

This paper presents characteristics of droughts simulated by global climate models (GCMs) under enhanced greenhouse gases conditions. We used a drought index called the Reconnaissance Drought Index (RDI) which takes both rainfall and potential evapotranspiration into account to investigate variations of droughts among 12 regions in Australia. The RDI was applied to simulated climate variables from 14 GCMs performed for the IPCC 4th Assessment Report. The results show a general increase in drought areal extent and/or frequency for most regions. However, the increases are not significant over the North West, North Queensland, Queensland East Coast and Central Queensland. For most regions, the change beyond 2030 is larger than that prior to 2030, but the uncertainty in the projections also increases with time. By 2030, there is a likely (>66% probability) risk of twice or more drought affected area and/or twice as often drought frequency over South West Western Australia. By 2050, this will include the Murray-Darling Basin, South Australia and Victoria, and by 2070 this will extend to New South Wales and Tasmania. For North Queensland such a risk is unlikely (

Atmospheric CO2 is a major cause of reinforcement corrosion in bridges, buildings, wharves, and other concrete infrastructure in Australia, United States, United Kingdom and most other countries. The increase in CO2 levels associated with global warming will increase the likelihood of carbonation-induced corrosion. Moreover, temperature rises will increase corrosion rates. Clearly, the impact of climate change on existing and new infrastructure is considerable, as corrosion damage is disruptive to society and costly to repair. The paper describes a probabilistic and reliability-based approach that predicts the probability of corrosion initiation and damage (severe cracking) for concrete infrastructure subjected to carbonation and chloride-induced corrosion resulting from elevated CO2 levels and temperatures. The atmospheric CO2 concentration and local temperature and relative humidity changes with time over the next 100 years in the Australian cities of Sydney and Darwin are projected based on nine General Circulation Models (GCMs) under (i) high CO2 emission scenario, (ii) medium CO2 emission scenario, and (iii) CO2 emission reduction scenario based on policy intervention. The probabilistic analysis included the uncertainty of CO2 concentration, deterioration processes, material properties, dimensions, and predictive models. It was found that carbonation-induced damage risks can increase by over 400% over a time period to 2100 for some regions in Australia. Damage risks for chloride-induced corrosion increase by no more than 15% over the same time period due to temperature increase, but without consideration of ocean acidity change in marine exposure. Corrosion loss of reinforcement is not significant. The results were most sensitive to increases in atmospheric CO2.

This paper has two purposes. One is to evaluate the ability of an atmospheric general circulation model (IAP9L-AGCM) to predict summer rainfall over China one season in advance. The other is to pro...

Summary The future rainfall series used to drive hydrological models in many climate change impact on runoff studies are informed by rainfall simulated by global climate models (GCMs). This paper assesses how the choice of GCMs based on their abilities to reproduce the observed historical rainfall can affect runoff impact assessment. The 23 GCMs used in IPCC 4AR are considered together with 1961–2000 observed rainfall data over southeast Australia. The results indicate that most of the GCMs can reproduce the observed spatial mean annual rainfall pattern, but the errors in the mean seasonal and annual rainfall amounts can be significant. The future mean annual rainfall projections averaged across southeast Australia range from −10% to +3% change per degree global warming, which is amplified as −23% to +4% change in the future mean annual runoff. There is no clear difference in the future rainfall projections between the better and poorer GCMs based on their abilities to reproduce the observed historical rainfall, therefore using only the better GCMs or weights to favour the better GCMs give similar runoff impact assessment results as the use of all the 23 GCMs. The range of future runoff in impact assessment studies is probably best determined using future rainfall projections from the majority of available archived GCM simulations.

Good performance of sewer systems is of paramount importance in modern cities. The last decades have shown an increase in the frequency of large storms, leading to flooding of urban areas, implying large direct and indirect costs to society. It is becoming necessary to assess to what extent changes in extreme rainfall will continue due to anthropogenic greenhouse gas emissions and socio-economic development paths. Changes in rainfall are usually predicted using General Circulation Models. However, these models cannot be used directly to predict changes in extreme point rainfall because the temporal and spatial resolution is too coarse. This paper presents an approach to overcoming the scale problem by constructing a model of rainfall based on the Random Parameter Bartlett–Lewis rectangular pulse model in combination with a multi-scaling disaggregator. The model performs well and indicates that an increase of 2–15% in extreme rainfall can be expected in Denmark the next 80 years.

On the basis of NCEP/NCAR version I daily reanalysis data from 1971 to 2000 and by the methods of inverse calculation, correlation analysis and comparative analysis, the influences of atmospheric heat source (AHS) over the Tibetan Plateau on the large-scale AHS and the general circulation in summer are studied in this paper. The results show that AHS over the plateau in summer may trigger a heat source wavetrain propagating northeastward along the coast from the East Asian continent and West Pacific to Bering Strait-Arctic or even North America. In addition, if AHS over the eastern plateau is intense, South Asian High moves to southeast and West Pacific subtropical high moves to southwest; on the contrary, if AHS over the eastern plateau is weak, South Asian High moves to northwest and West Pacific subtropical high moves to northeast. Therefore, South Asian High and West Pacific subtropical high move in the horizontally-opposite directions in terms of interannual variation, for which AHS over the eastern plateau seems to be thermodynamically responsible.

When planning the acquisition of new palaeo proxy data for reconstructing past climates, many factors influence the decision of where the proxies are to be collected. One such influence is the likelihood of recording a significant climate change relative to the modern. Another consideration, which is less often considered, is the desire to target regions in which there is significant uncertainty in numerical model predictions of past climate change. New proxy data in these regions enables a more rigorous test of model simulations, and results in better constraints on the various boundary conditions used to force the models. In this paper we present a methodology for targeting new palaeo proxy data, based on model simulations. We use the terrestrial late Miocene (11.6 to 5.3 Ma) as a case study. The late Miocene climate provides insights into future climate behavior, as it is believed to have been considerably warmer than the modern. We carry out a suite of late Miocene atmosphere-only General Circulation Model simulations, which we initially evaluate relative to an example dataset of terrestrial temperature and precipitation. In terms of targeting future data acquisition, we locate those regions in the model which exhibit the largest change in temperature and/or precipitation relative to the pre-industrial. We also locate those regions which display the largest variability between the model simulations, because new data in these regions are most likely to provide a strict test of the reliability of the model results. Among other regions, the Amazon basin, the Chad basin, central Canada, and northern India are identified as potentially useful areas to collect data.

The zonal displacement of the western Pacific subtropical high remarkably influences the climate anomalies in China. In this paper, a new zonal index of the subtropical high is defined by modifying previous indices, and is used to investigate the relationship between the zonal displacement of the subtropical high and the dominant modes of 850-hPa circulations. It is found that the zonal displacement of the subtropical high is significantly correlated with the first two leading modes of circulations. In particular, the correlation coefficient between the index and the time series associated with the second mode is as high as 0.78 in 1958–2003 (46 years). Since the second mode is not associated with significant anomalies of sea surface temperatures, the above results imply the difficulty in seasonal forecasting of the zonal displacement of the subtropical high. In addition, the interannual variability in the zonal displacement of the subtropical high has been considerably enhanced since 1978, due to the effects of both dominant modes, especially the second mode. This is likely to account for the frequent occurrence of anomalous climate in China during the recent two decades.

Direct observations of hydrogen peroxide in the atmosphere of Mars are rare. Few available observations and most 1D model simulations suggest an H 2 O 2 column in the range 10 15 – 10 16 cm - 2 or a mixing ratio in the lower atmosphere of nearly 10–30 ppb. Another estimate of the content of hydrogen peroxide in the atmosphere of Mars is given in this paper, using an atmospheric general circulation model with online chemistry. The simulations confirm the correlation between the amounts of water and hydrogen peroxide and predict an important role for condensation in the polar regions.

Uncertainties related to the climate impact studies are reviewed on the case of onion thrips in Slovenia. Paper illustrates cumulative uncertainty introduced by future emission scenar- ios, general circulation models, downscaling procedures, weather generators and impact (degree-day) models as common tools in climate impact studies. The result of cumulative uncertainty is a wide range of expected warming in Slovenia in the 21st century. An expected increase of air temperature, relative to 1990, is between 1.5 and 7 ◦

This paper gives the yearly 85 Kr emissions of all known reprocessing facilities, which are the main sources of 85 Kr in the atmosphere since 1945, for the years 1945 until 2000. According to this inventory 10,600 PBq (Peta = 10 15 ) of 85 Kr have been globally emitted from the year 1945 until the end of 2000. The global atmospheric inventory at the end of the year 2000 amounts to 4800 PBq. These emissions have been incorporated into the ECHAM4 atmospheric general circulation model as point sources. Monthly mean model results are compared with measurements made at different locations and times. The influence of each source on the measured concentrations at various locations is studied. The calculated concentrations are found to give reasonably good agreement with the observations, indicating that the emission inventory is realistic. Although, at all northern hemispheric observation sites the model tends to slightly overestimate the concentrations. A possible reason for this overestimation can be found in model features (coarse resolution in time and space). The most prominent discrepancy that is consistently repeated at all northern hemispheric stations occurs in the early 1990s. This could most likely be related to an overestimate of sources. Possibly, the Russian emissions declined earlier than assumed in the current database. Another discrepancy between observations and simulations indicating an incompleteness of the release data is found at some southern hemispheric sites. The variability of their observations could only be explained by regional sources. However, several spikes occur after 1992 when no reprocessing facility is known to be in operation in the southern hemisphere. Production of isotopes for radiopharmaceuticals like technetium-99m from highly enriched uranium is the most likely explanation.

Global and climate changes are subject to scientific, societal and political debates. Recent observational evidence and results of global climate models have identified the circumpolar North as a region particularly susceptible to future climate change. To understand and assess the consequences of these changes for environmental and societal components of the European Arctic, the Barents Sea Impact Study (BASIS), an EU-funded integrated regional impact study (IRIS) has been carried out (ENV4-CT-97-0637). In common with global integrated assessments (IAs), IRISs also take a holistic view on climate change and its impact. Contrary to IAs, however, IRISs adopt a regional to sub-regional spatial scale. BASIS was carried out by an interdisciplinary team of specialists from 13 institutions in 6 countries. Major results pertain to impacts of possible climate change on marine and terrestrial ecosystems, freshwater hydrology, marine trace gas budgets, forestry and fishery. However, in this paper we focus on the major methodological aspects of an IRIS in general and on methods applied in BASIS in particular.

This paper investigates the mechanism which generates decadal modulations in the amplitude of the El Nino-Southern Oscillation phenomenon (ENSO). Our analysis is based on a multicentury present-day climate simulation performed with an ENSO-resolving Coupled General Circulation Model (CGCM). In consistency with observations, it is found that ENSO variance undergoes changes with a time scale of about 10–20 years. This decadal beat is closely linked to the second dominant pattern of tropical (sub)surface temperature variability. The dipole-like characteristic of this mode is generated mainly by the interplay of horizontal, vertical advection and mixing. We suggest a nonlinear mechanism, which is capable of generating decadal tropical climate anomalies as well as decadal ENSO amplitude modulations (DEAMs) without invoking extratropical dynamics. This mechanism is based on the idea of homoclinic orbits. This new paradigm is validated using a low-dimensional ENSO model that is derived empirically from the CGCM simulation.

The persistence of the weather is a well-known phenomenon. If, for example, one day is sunny and warm, there is a high tendency that the next day remains similar. In this paper, we review recent results showing that the long-term persistence, characterized by the correlation C ( s ) of temperature variations separated by s days, decays for large s as a power law. For continental stations, the exponent is always close to 0.7, while for stations on islands as well as for sea surface temperatures, the exponent is close to 0.4. In contrast to the temperature fluctuations, the fluctuations of the rainfall usually are not characterized by long-term power-law correlations but rather by short-term correlations. The universal persistence law for the temperature fluctuations on continental stations represents an ideal (and uncomfortable) test bed for the state-of-the-art global climate models and allows to evaluate their performance.

Increasing levels of atmospheric CO2 concentration [CO2] has caused a debate in the scientific community over how vegetation responds to this increase — specifically in the stomatal resistance increase (SR increase) and the transpiration decrease (TRdecrease). This paper presents results in changes of stomatal resistance and transpiration from two canopy model simulations under varying environmental conditions for corn and soybeans for presentday and doubled atmospheric [CO2] conditions. The two canopy models used in the simulations were the off-line version of the land surface exchange parameterization of the GENESIS general circulation model (LSX) and the Penn State University Biosphere-Atmosphere Modeling Scheme (PSUBAMS). Simulations were performed with each model’s original stomatal resistance parameterization (SRP) and then with a field-derived SRP developed from corn and soybeans field measurements taken during 1993‐1995. For corn using the original SRP, the percentage ratio (TRdecrease=SRincrease 100) calculated ranged from 20 to 37% for both models and values of (a non-dimensional ‘decoupling coefficient’ that relates how closely the TR decrease is correlated with SRincrease) ranged from 0.63 to 0.80. The results for corn, using the field derived SRP, showed that the percentage ratio and ranged from 18 to 25% and 0.75 to 0.82, respectively. For soybeans, the values of the percentage ratio and for the original SRP ranged from 20 to 39% and 0.61 to 0.80, respectively, while for the field derived SRP they were 12‐20% and 0.80‐0.87. The model derived values for the percentage ratio were substantially less than those reported in the literature for experiments conducted at the leaf scale. It is also demonstrated, using these models, how inter-canopy (LSX and PSUBAMS) and mixing layer (PSUBAMS) feedbacks modify transpiration beyond those initiated by changes in stomatal resistance alone. © 2001 Elsevier Science B.V. All rights reserved.

This paper addresses the impacts of climate change on forest fires and describes how this, in turn, will impact on the forests of the United States. In addition to reviewing existing studies on climate change and forest fires we have used two transient general circulation models (GCMs), namely the Hadley Centre and the Canadian GCMs, to estimate fire season severity in the middle of the next century. Ratios of 2 x CO2 seasonal severity rating (SSR) over present day SSR were calculated for the means and maximums for North America. The results suggest that the SSR will increase by 10-50% over most of North America; although, there are regions of little change or where the SSR may decrease by the middle of the next century. Increased SSRs should translate into increased forest fire activity. Thus, forest fires could be viewed as an agent of change for US forests as the fire regime will respond rapidly to climate warming. This change in the fire regime has the potential to overshadow the direct effects of climate change on species distribution and migration.