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Broadband (spectrally‐integrated) radiation calculations are dominated by the expense of spectral integration, and many applications require fast parameterizations for computing radiative flux. Here we describe a novel approach using a linear weighted sum of monochromatic calculations at a small set of optimally‐chosen frequencies. The empirically‐optimized quadrature method is used to compute atmospheric boundary fluxes, net flux profiles throughout the atmosphere, heating rate profiles, and top‐of‐the‐atmosphere forcing by CO2, in the longwave for clear skies. We evaluate the method against two modern correlated k‐distribution models and find that we can achieve comparable errors with 32 spectral points. We also examine the effect of minimizing different cost functions, and find that in order to accurately represent heating rates and CO2 forcing, these quantities must be included in the cost function. Plain Language Summary: Quantifying the way radiation flows through the atmosphere is computationally expensive, and most applications require fast approximation. In this paper, we develop an empirically‐optimized quadrature method that can compute quantities of interest in climate science and weather prediction such as radiative flux throughout the atmosphere, heating rates, and forcing by carbon dioxide. The method uses a simple optimization algorithm, combined with a linear model, to achieve accuracy and computational cost of similar order of magnitude to the modern correlated k‐distribution models. Depending on the focus of the application, the algorithm can easily be adapted to prioritize desired quantities. Key Points: Spectrally integrated radiative quantities can be estimated from a small weighted set of monochromatic calculationsTradeoffs between computational cost and accuracy are commensurate with correlated k‐distribution modelsOptimization priorities can be tailored to a specific applications [ABSTRACT FROM AUTHOR]

The exchange of CO_{2} between the atmosphere and the ocean surface is a problem that has become increasingly important due to its impact on climatic behavior. Given the large quantity of sources of information available for studying the CO_{2} problem, it is necessary to provide innovative solutions that facilitate the automation of certain tasks and incorporate decision support systems to obtain a better understanding of this phenomenon. This paper presents a multiagent architecture aimed at providing solutions for monitoring the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carbon dioxide. This process is can be modeled by a multiagent system with advanced learning and adaption capabilities. The proposed multiagent architecture incorporates CBR-agents that integrate novel strategies that both monitor the parameters that affect the interaction, and facilitate the creation of models. The system was tested and this paper presents the results obtained. [ABSTRACT FROM AUTHOR]

This paper designs a comprehensive approach based on the engineering machine/ system concept, to model, analyze, and assess the level of carbon dioxide (CO) exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO fluxes. To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as stochastic filtering analysis of variance (SF-ANOVA). The CO flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction, and globalization capabilities of the proposed engineering approach and the SF-ANOVA technique. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures. [ABSTRACT FROM AUTHOR]

The flux of gases between the atmosphere and the oceans can be calculated from the product of the concentration difference across the sea surface and a kinetic term, often called a transfer velocity. The transfer velocity is frequently parameterized in terms of wind speed, although the actual exchange process is also affected by waves, bubbles, wind fetch, and less certainly by surfactants and chemical reactivity. There is currently an uncertainty of about a factor of two in using the wind speed parameterization. In view of the windiness of the Southern Ocean, transfer velocities will often be high, although there are few published in situ measurements of transfer rates made in the region. Data for gas concentration fields in the Southern Ocean are generally sparse compared to other better studied oceanic areas. In this paper we discuss what is known for the region for carbon dioxide, including the oceanic sink for man-made inputs to the atmosphere; dimethyl sulphide, where there appears to be a substantial source, which has the potential for a significant climatic effect due to the low particulate loading in the region; and organo-halogen and alkyl nitrate gases, where marine emissions may play an important role in controlling the oxidation capacity of the Antarctic atmosphere. [ABSTRACT FROM AUTHOR]

The radiative forcing from carbon dioxide is approximately logarithmic in its concentration, producing about 4 W m−2 of global-mean forcing for each doubling. Although these are basic facts of climate science, competing explanations for them have been given in the literature. Here, the reasons for the logarithmic forcing of carbon dioxide are explored in detail and a simplified model for the forcing is constructed. An essential component is the particular distribution of absorption coefficients within the 15-μm band of carbon dioxide. An alternative explanation, which does not depend on the spectrum of carbon dioxide but instead hinges on the tropospheric lapse rate, is shown to be neither necessary nor sufficient to explain the logarithmic forcing of carbon dioxide and to be generally inapplicable to well-mixed greenhouse gases in Earth's atmosphere. [ABSTRACT FROM AUTHOR]

In this study, we investigate links between Arctic sea ice loss and the variability of 2-m temperatures over a 6-month period (November–April) over two domains centered over northern Eurasia and northern North America. Based on data from the Climate Forecast System Reanalysis (CFSR), there has been an increase (a decrease) in recent seasonal temperature variability over Eurasia (North America), which can be attributed to cooling (warming) during the winter months. Decreases in the intraseasonal variability of temperature anomalies, however, are noted in both regions for the November–April period. This study investigates the role of different forcings on the changes seen in the reanalysis product using Atmospheric Model Intercomparison Project simulations forced with repeating sea surface temperature, sea ice, and carbon dioxide concentration relative to climatologies from two different base periods, 1981–90 and 2005–14. The seasonal temperature and intraseasonal anomaly variabilities are examined, and we find that only the simulations with reduction in sea ice (2005–14 base-period sea ice concentration) produce significant decreases in intraseasonal temperature anomaly variability over these regions, agreeing with the CFSR analysis. Runs that reduce sea ice also result in a significant decrease in the frequency and magnitude of extreme warm and cold temperature anomalies. It is proposed that the weakened latitudinal temperature gradient, resulting from decreased sea ice, leads to reduced meridional temperature advection variability, which in turn contributes to the reduction in the variability of temperature anomalies. [ABSTRACT FROM AUTHOR]

Climate change communication efforts grounded in the information deficit model have largely failed to close the gap between scientific and public understanding of the risks posed by climate change. In response, simulations have been proposed to enable people to learn for themselves about this complex and politically charged topic. Here we assess the impact of a widely-used simulation, World Climate, which combines a socially and emotionally engaging role-play with interactive exploration of climate change science through the C-ROADS climate simulation model. Participants take on the roles of delegates to the UN climate negotiations and are challenged to create an agreement that meets international climate goals. Their decisions are entered into C-ROADS, which provides immediate feedback about expected global climate impacts, enabling them to learn about climate change while experiencing the social dynamics of negotiations. We assess the impact of World Climate by analyzing pre- and post-survey results from >2,000 participants in 39 sessions in eight nations. We find statistically significant gains in three areas: (i) knowledge of climate change causes, dynamics and impacts; (ii) affective engagement including greater feelings of urgency and hope; and (iii) a desire to learn and do more about climate change. Contrary to the deficit model, gains in urgency were associated with gains in participants’ desire to learn more and intent to act, while gains in climate knowledge were not. Gains were just as strong among American participants who oppose government regulation of free markets–a political ideology that has been linked to climate change denial in the US–suggesting the simulation’s potential to reach across political divides. The results indicate that World Climate offers a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science. [ABSTRACT FROM AUTHOR]

The goal of the paper is to present and examine the method of classification of daily circulation patterns that allows (i) a fair comparison of groupings among different datasets (typically representing theobserved climate and that simulated by a general circulation model, GCM) and (ii) huge datasets, common in GCM studies based on daily values, to be classified. The circulation classification method is shownto be a useful tool in GCM validation and analysis of climate changeresponse, particularly in comparisons of (i) shapes of the mean typepatterns, (ii) the frequency and persistence of the types, (iii) theprobability of transitions from one type to another, and (iv) conditional surface temperature distributions. It is also shown that a simultaneous examination of multiple classifications is beneficial in eliminating subjectivity of any single classification and allowing a detailed inspection of differences between climates. The classification method is a modification of the T-mode principal component analysis (PCA). The T-mode refers to the input data matrix where gridpoint values are arranged in rows and daily patterns in columns. The classification procedure is applied to observed daily 500 hPa geopotential height patterns and those simulated by the control and $2\times {\rm CO}2$ ECHAM3 GCM runs. [ABSTRACT FROM AUTHOR]

Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two long-term climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains. [ABSTRACT FROM AUTHOR]

The amplitude, phase, and form of the seasonal cycle of atmospheric CO2 concentrations varies on many time and space scales (Peters et al., 2007). Intra-annual CO2 variation is primarily driven by seasonal uptake and release of CO2 by the terrestrial biosphere (Machta et al., 1977; Buchwitz et al., 2007), with a small (Cadule et al., 2010; Heimann et al., 1998), but potentially changing (Gorgues et al., 2010) contribution from the ocean. Variability in the magnitude, spatial distribution, and seasonal drivers of terrestrial net pri- mary productivity (NPP) will be induced by, amongst other factors, anthropogenic CO2 release (Keeling et al., 1996), land-use change (Zimov et al., 1999) and planetary orbital atm variability, and will lead to changes in COatm2 seasonality. Despite COatm2 seasonality being a dynamic and prominent feature of the Earth System, its potential to drive changes in the air-sea flux of CO2 has not previously (to the best of my knowledge) been explored. It is important that we investigate the impact of COatm2 seasonality change, and the potential for carbon-cycle feedbacks to operate through the modification of the COatm2 seasonal cycle, because the decision had been made to prescribe COatm2 concentrations (rather than emissions) within model simulations for the fifth IPCC climate assessment (Taylor et al., 2009). In this study I undertake ocean-model simulations within which different magnitude COatm2 seasonal cycles are prescribed. These simulations allow me to examine the effect of a change in COatm2 seasonal cycle magnitude on the air-sea CO2 flux. I then use an offline model to isolate the drivers of the identified air-sea CO2 flux change, and propose mechanisms by which this change may come about. Three mechanisms are identified by which co-variability of the seasonal cycles in atmospheric CO2 concentration, and seasonality in sea-ice extent, wind-speed and ocean temperature, could potentially lead to changes in the air-sea flux of CO2 at mid-to-high latitudes. The sea-ice driven mechanism responds to an increase in COatm2 seasonality by pumping CO2 into the ocean, the wind-speed and solubility-driven mechanisms, by releasing CO2 from the ocean (in a relative sense). The relative importance of the mechanisms will be determined by, amongst other variables, the seasonal extent of sea-ice. To capture the described feedbacks within earth system models, COatm2 concentrations must be allowed to evolve freely, forced only by anthropogenic emissions rather than prescribed COatm2 concentrations; however, time-integrated ocean simulations imply that the cumulative net air-sea flux could be at most equivalent to a few ppm COatm2. The findings presented here suggest that, at least under pre-industrial conditions, the prescription of COatm2concentrations rather than emissions within simulations will have little impact on the marine anthropogenic CO2 sink. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) changes constitute a major indicator and driver of climate changes induced by greenhouse gas increases. The objective of the present study is to investigate the role played by the detailed structure of the SST change on the large-scale atmospheric circulation and the distribution of precipitation. For that purpose, simulations from the Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4) are used where the carbon dioxide (CO2) concentration is doubled. The response of IPSL-CM4 is characterized by the same robust mechanisms affecting the other coupled models in global warming simulations, that is, an increase of the hydrological cycle accompanied by a global weakening of the large-scale circulation. First, purely atmospheric simulations are performed to mimic the results of the coupled model. Then, specific simulations are set up to further study the underlying atmospheric mechanisms. These simulations use different prescribed SST anomalies, which correspond to a linear decomposition of the IPSL-CM4 SST changes in global, longitudinal, and latitudinal components. The simulation using a globally uniform increase of the SST is able to reproduce the modifications in the intensity of the hydrological cycle or in the mean upward mass flux, which also characterize the double CO2 simulation with the coupled model. But it is necessary (and largely sufficient) to also take into account the zonal-mean meridional structure of the SST changes to represent correctly the changes in the Hadley circulation strength or the zonal-mean precipitation changes simulated by the coupled model, even if these meridional changes by themselves do not change the mean thermodynamical state of the tropical atmosphere. The longitudinal SST anomalies of IPSL-CM4 also have an impact on the precipitation and large-scale tropical circulation and tend to introduce different changes over the Pacific and Atlantic Oceans. The longitudinal SST changes are demonstrated to have a smaller but opposite effect from that of the meridional anomalies on the Hadley cell circulations. Results indicate that the uncertainties in the simulated meridional patterns of the SST warming may have major consequences on the assessment of the changes of the Hadley circulation and zonal-mean precipitation in future climate projections. [ABSTRACT FROM AUTHOR]

The article offers various information related to energy and environment from October-December 2008 in the U.S. The value for carbon dioxide at Mauna Loa in Hawaii Island, Hawaii was 384.7 ppmv, depicting the normal upward trend and an annual rise of 3.33 ppmv. The global sea ice area for the period was the same as in 1979 while human resources contribute about five percent of the annual carbon dioxide input into atmosphere. The European Union (EU) summit declaration dropped all reference to the legal implementation of the climate targets.

The observed relationship between Earth's temperature and CO2 concentration in the atmosphere during glacial and interglacial periods from 420,000 years ago up to 1850 has still not been satisfactorily explained. It is proven that CO2 movements lag temperature, but why did the concentration move up and down in a regular pattern? No universally accepted conclusion exists that can be reliably used for modelling "what if" scenarios. [ABSTRACT FROM AUTHOR]

Predictability studies of the second kind are often carried out to address the potential in predicting atmospheric variables based on knowledge of changes in sea surface temperature (SST). Here a predictability study of the second kind is performed for the coupled atmosphere–ocean system based on knowledge of changes in CO2 concentration. The focus is on potential predictabilities obtained after imposing a CO2 forcing over a short time period (i.e., a few years), which are less sensitive to the exact future time evolution of the CO2 forcing. Potential predictability is measured by the ensemble mean difference resulting from the CO2 forcing relative to the ensemble spread subjected to the same forcing. The measure is calculated from a 50-member prediction ensemble obtained from an atmosphere–ocean GCM forced by a 3% increase in CO2 concentration per year and a reference ensemble obtained under a constant CO2 concentration. The largest potential predictabilities are found in and over the Southern Ocean. The origin of these predictabilities is a positive feedback involving interactions between the atmosphere and the upper ocean. An increase in the meridional gradient of SST resulting from a large SST increase in the southern subtropics leads to a strengthening of atmospheric circulation, and from that increases in surface zonal wind stress result. The latter enhances the northward Ekman transport over the southern high latitudes, which transports polar water equatorward, whereby maintaining the meridional temperature gradient. Potential predictability is also found in the deep ocean, characterized by the downward propagation of the surface warming within a few years through two “corridors,” located at 40°S and 40°N and extending from the near surface to about 3000–3500 m. The warming in the atmosphere and the upper ocean is reduced by half because of this downward heat propagation. [ABSTRACT FROM AUTHOR]

The Integrated Deposition Model (IDEM) was improved by incorporating a novel multilayer biochemical dry deposition module for gases. The aerosol and base cation deposition module was adopted from IDEM. For evaluation of primary and ecosystem productivity, carbon respiration schemes were included. The resulting Framework for Atmosphere-Canopy Exchange Modelling (FACEM) was then evaluated by the case studies presented here. First, results for deposition of SO x, NO y and NH x were compared with site observations, showing correlations of up to . Applicability for grid deposition calculations for these compounds was then evaluated for Europe. The model was clearly able to reproduce the elevated deposition near the important emission areas in Europe. Next, we compared the modelled CO2 fluxes with measurements from 26 European sites. Correlations of up to indicate good performance. To evaluate grid performance, the 2003 European heat wave was studied in a final case study, resulting in convincing correspondence with the observed productivity anomalies. [ABSTRACT FROM AUTHOR]

We investigate the interannual variability in the flux of CO2 between the atmosphere and the Southern Ocean on the basis of hindcast simulations with a coupled physical-biogeochemical-ecological model with particular emphasis on the role of the Southern Annular Mode (SAM). The simulations are run under either pre-industrial or historical CO2 concentrations, permitting us to separately investigate natural, anthropogenic, and contemporary CO2 flux variability. We find large interannual variability (±0.19 PgC yr-1) in the contemporary air-sea CO2 flux from the Southern Ocean (<35°S). Forty-three percent of the contemporary air-sea CO2 flux variance is coherent with SAM, mostly driven by variations in the flux of natural CO2, for which SAM explains 48%. Positive phases of the SAM are associated with anomalous outgassing of natural CO2 at a rate of 0.1 PgC yr-1 per standard deviation of the SAM. In contrast, we find. an anomalous uptake of anthropogenic CO2 at a rate of 0.01 PgC yr-1 during positive phases of the SAM. This uptake of anthropogenic CO2 only slightly mitigates the outgassing of natural CO2, so that a positive SAM is associated with anomalous outgassing in contemporaneous times. The primary cause of the natural CO2 outgassing is anomalously high oceanic partial pressures of CO2 caused by elevated dissolved inorganic carbon (DIC) concentrations. These anomalies in DIC are primarily a result of the circulation changes associated with the southward shift and strengthening of the zonal winds during positive phases of the SAM. The secular, positive trend in the SAM has led to a reduction in the rate of increase of the uptake of CO2 by the Southern Ocean over the past 50 years. [ABSTRACT FROM AUTHOR]

A biogeochemical ocean general circulation model, driven with NCEP-RI and observed atmospheric CO2 history, is used to investigate and quantify the role that the Southern Annular Mode (SAM), identified as the leading mode of climate variability, has in driving interannual variability in Southern Ocean air-sea CO2 fluxes between 1980 and 2000. Our simulations show the Southern Ocean to be a region of decreased CO2 uptake during the positive SAM phase. The SAM induces changes in Southern Ocean CO2 uptake with a 2-month time lag explaining 42% of the variance in the total interannual variability in air-sea CO2 fluxes. Our analysis shows that the response of the Southern Ocean to the SAM is primarily governed by changes in ΔpCO2 (67%), and that this response is driven by changes in ocean physics that control the supply of nutrients to the upper ocean, primarily Dissolved Inorganic Carbon (DIC). The SAM is predicted to become stronger and more positive in response to climate change and our results suggest this will decrease the Southern Ocean CO2 uptake by 0.1PgC/yr per unit change in the SAM. [ABSTRACT FROM AUTHOR]

Carbon cycle feedbacks will have a direct effect on anthropogenic emissions required to stabilize CO2 in the atmosphere. In this study, I used an intermediate complexity coupled climate-carbon model to quantify allowable CO2 emissions for a series of scenarios leading to CO2 stabilization at levels between 350 and 1000 ppmv. For all scenarios, global temperature did not stabilize over the next several centuries, but rather continued to increase well beyond the point of CO2 stabilization. Furthermore, neither long-term climate change, nor total allowable CO2 emissions, were sensitive to the shape of the CO2 stabilization profile, but only to the final stabilization level. For the 550-stabilization scenario, positive carbon cycle-climate feedbacks required a reduction of annual CO2 emissions throughout the simulation, with a maximum reduction of 2.3 GtC/yr occurring at 2050. Total emissions over the 21st century were 20% lower than those derived from an equivalent simulation without feedbacks. In two additional runs with varied climate sensitivities, emissions consistent with 550-stabilization were reduced by between 190 and 540 GtC over the next 400 yr relative to the no-feedbacks run. Allowable emissions were further reduced in all cases if CO2 increases did not affect future vegetation productivity, as this removed an otherwise important negative feedback on atmospheric CO2. [ABSTRACT FROM AUTHOR]

The spatiotemporal variability of upper ocean inorganic carbon parameters and air-sea CO2 exchange in the Indian Ocean was examined using inorganic carbon data collected as part of the World Ocean Circulation Experiment (WOCE) cruises in 1995. Multiple linear regression methods were used to interpolate and extrapolate the temporally and geographically limited inorganic carbon data set to the entire Indian Ocean basin using other climatological hydrographic and biogeochemical data. The spatiotemporal distributions of total carbon dioxide (TCO2), alkalinity, and seawater pCO2 were evaluated for the Indian Ocean and regions of interest including the Arabian Sea, Bay of Bengal, and 10°N-35°S zones. The Indian Ocean was a net source of CO2 to the atmosphere, and a net sea-to-air CO2 flux of +237 ± 132 Tg C yr-1 (+0.24 Pg C yr-1) was estimated. Regionally, the Arabian Sea, Bay of Bengal, and 10°N-10°S zones were perennial sources of CO2 to the atmosphere. In the 10°S-35°S zone, the CO2 sink or source status of the surface ocean shifts seasonally, although the region is a net oceanic sink of atmospheric CO2. [ABSTRACT FROM AUTHOR]

The three carbon gases carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) are important atmospheric constituents affecting air quality and climate. The near-infrared nadir spectra measured by SCIAMACHY on ENVISAT contain information on the vertical columns of these gases which we retrieve using a modified DOAS algorithm (WFM-DOAS or WFMD). Our main data products are CO vertical columns and dry-air column averaged mixing ratios of methane (CH4) and CO2 (denoted XCH4 and XCO2). For CO and CH4 we present new results for the year 2003 obtained with an improved version of WFM-DOAS (WFMDv0.5) retrieved from Level 1 version 4 (Lv1v4) spectra. This data set has recently been compared with a network of ground based FTIR stations. Here we describe the WFMDv0.5 algorithm, present global and regional maps, and comparisons with global reference data. We show that major problems of the previous versions (v0.4 and v0.41) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. Compared to MOPITT the SCIAMACHY CO columns are on average higher by about 10-20%. Regionally, however, especially over central South America, differences can be much larger. For methane we present global and regional maps which are compared to TM5 model simulations performed using standard methane emission inventories. We show that methane source regions can be clearly detected with SCIAMACHY. We also show that the methane data product can be significantly further improved using Lv1v5 spectra with improved calibration. For CO2 we present three years of SCIAMACHY CO2 measurements over Park Falls, Wisconsin, USA, retrieved from Lv1v5. We show that the quality of CO2 retrieved from these spectra is significantly higher compared to WFMDv0.4 XCO2 retrieved from Lv1v4. [ABSTRACT FROM AUTHOR]

A new physiology-based model of canopy stomatal conductance and photosynthesis is described and included in the latest version of the Goddard Institute for Space Studies (GISS) GCM, ModelE1. The submodel includes responses to atmospheric humidity and CO2 concentration, responses missing from previous GISS GCM land surface schemes. Measurements of moisture, energy, and CO2 fluxes over four vegetation types are used to test and calibrate the submodel. Photosynthetic leaf N is calibrated for each vegetation type from the flux measurements. The new submodel results in surface cooling over many regions previously too warm. Some warm biases of over 2°C are cooled by more than 0.5°C, including over central Eurasia, South America, the western United States, and Australia. In addition, some regions that were previously too cool are warmed, such as northern Eurasia and the Tibetan Plateau. A number of precipitation biases are also reduced, particularly over South America (by up to 1 mm day-1) and the oceanic ITCZs (by over ±1 mm day-1); coastal west Africa becomes significantly wetter. Cloud cover increases over many land areas previously too clear. Higher absolute canopy conductances, and positive feedbacks with atmospheric humidity, are largely responsible for the simulated vegetation influence on the atmosphere. High-latitude climate changes through remote effects of increased tropical latent heating, resulting directly from improved characterization of tropical forest canopy conductance. Realistic representation of the stomatal control on land evaporation is critical for accurate simulation of atmospheric dynamics in the GISS GCM. [ABSTRACT FROM AUTHOR]

The separate climate effects of middle-atmospheric and tropospheric CO2 doubling have been simulated and analyzed with the ECHAM middle-atmosphere climate model. To this end, the CO2 concentration has been separately doubled in the middle-atmosphere, the troposphere, and the entire atmosphere, and the results have been compared to a control run. During NH winter, the simulated uniformly doubled CO2 climate shows an increase of the stratospheric residual circulation, a small warming in the Arctic lower stratosphere, a weakening of the zonal winds in the Arctic middle-atmosphere, an increase of the NH midlatitude tropospheric westerlies, and a poleward shift of the SH tropospheric westerlies. The uniformly doubled CO2 response in most regions is approximately equal to the sum of the separate responses to tropospheric and middle-atmospheric CO2 doubling. The increase of the stratospheric residual circulation can be attributed for about two-thirds to the tropospheric CO2 doubling and one-third to the middle-atmospheric CO2 doubling. This increase contributes to the Arctic lower-stratospheric warming and, through the thermal wind relationship, to the weakening of the Arctic middle-atmospheric zonal wind. The increase of the tropospheric NH midlatitude westerlies can be attributed mainly to the middle-atmospheric CO2 doubling, indicating the crucial importance of the middle-atmospheric CO2 doubling for the tropospheric climate change. Results from an additional experiment show that the CO2 doubling above 10 hPa, which is above the top of many current GCMs, also causes significant changes in the tropospheric climate. [ABSTRACT FROM AUTHOR]