GISS General Circulation Model Research Articles

The application of a plant community model to evaluate adaptation strategies for alleviating climate change impacts on grassland productivity, biodiversity and forage quality

Grasslands are environments characterized by an elevated biodiversity in plant species, which dynamically evolves over time as a function of management practices, soil properties, and climate conditions. Climate change can locally affect grassland growth and floristic composition and, in turn, the quality and quantity of provided ecosystem services. We show how the use of the plant community model CoSMo allows to explicitly account for the dynamics of floristic composition as response to environmental variables. This, in turn, allows quantifying climate change impacts on grasslands growth and composition and evaluating alternative strategies to improve adaptation in the mid-term. As a case study, we focused on mountain areas in the northern Apennines (Italy), where temporary alfalfa (Medicago sativa L.)-dominated grasslands are sown for the production of Parmesan cheese. Five sites and four alternative climate scenarios (RCP4.5 and RCP8.5 projections as provided by the HadGEM2 and GISS general circulation models) were considered, to explore a wide range of agro-environmental conditions. Results showed that the observed dynamics of floristic composition and biomass accumulation were successfully simulated, with a mean absolute error lower than 10% for floristic composition and less than 1 t ha−1 for total biomass. Climate change impacts were globally negative, with a clear decrease of forage production as compared to the baseline (from -3.6% to -14.3% according to the climate scenario). The biodiversity of the plant community also declined (12.5% average decrease in the inverse Simpson index) due to the increase in alfalfa dominance. The latter, however, led to preserve the forage crude protein content (+0.9% on average). Guidelines for optimizing grassland productivity and forage protein under future climate were defined, mainly focused on reducing the alfalfa field duration, sowing grass-legume mixtures, and delaying the last cut of the season. These practices can be easily adopted under operational farming conditions to support the adaptation of temporary grasslands to climate change. According to our knowledge, this is one of the first study of climate change impact that uses a plant community model to explicitly considers phytocoenosis dynamics, biodiversity, and their effect on forage production (quantity and quality). Considering the role of grasslands as providers of key ecosystem services ‒ especially in marginal areas ‒ we believe that our modelling approach can support the identification of effective adaptation strategies to address future climate challenges.

Cloud scattering impact on thermal radiative transfer and global longwave radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800–1250 cm−1). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300–600 cm−1) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ∼3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important.The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%–4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m2, and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m2 and 1.8 W/m2, respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6 W/m2, −1.1 W/m2, and −2.5 W/m2, respectively. The global scattering impact of 2.7 W/m2 on the OLR is small when compared to the typical global OLR value of 240 W/m2, but it is significant when compared to cloud LW radiative forcing (30 W/m2) and net cloud forcing (−14 W/m2). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO2.

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

Abstract The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change’s (IPCC) Fifth Assessment Report (AR5). Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

The Tropical Subseasonal Variability Simulated in the NASA GISS General Circulation Model

Abstract The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden–Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

The MJO Transition from Shallow to Deep Convection inCloudSat/CALIPSO Data and GISS GCM Simulations

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden–Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10 MJO events show the following anticipated MJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) column water vapor (CWV) increases by ~5 mm during the shallow–deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between ~46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow–deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990–1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-surface temperatures derived from the NCEP Global Reanalysis and output from the CCSM3 and GISS general circulation models (GCMs). The simulation results are compared to the North American Regional Reanalysis (NARR). The three RCM simulations appeared to be more accurate in winter and least accurate in summer, and more accurate aloft than near the surface. The reanalysis-constrained simulation adequately captured the spatial distribution and seasonal cycle of the observed surface-air temperature and precipitation, but it produced consistently across all seasons a cold bias that is generally larger over the lakes than over land and a wet bias due to an overestimation of non-convective precipitation. The simulated seasonal cycle of moisture–flux convergence over the region was in very good agreement with NARR. The two GCM-driven runs adequately simulated the spatial and seasonal variation of temperature, but overestimated cold-season precipitation and underestimated summer precipitation, reversing the observed annual precipitation cycle. The GISS-driven run failed to simulate the prevailing low-level flow and moisture convergence patterns. All three RCM simulations successfully captured the impact of the Great Lakes on the region's climate, especially on winter precipitation, a significant improvement over coarse-resolution GCM simulations over the region.

Climatic effects of 1950–2050 changes in US anthropogenic aerosols – Part 2: Climate response

Abstract. We investigate the climate response to changing US anthropogenic aerosol sources over the 1950–2050 period by using the NASA GISS general circulation model (GCM) and comparing to observed US temperature trends. Time-dependent aerosol distributions are generated from the GEOS-Chem chemical transport model applied to historical emission inventories and future projections. Radiative forcing from US anthropogenic aerosols peaked in 1970–1990 and has strongly declined since due to air quality regulations. We find that the regional radiative forcing from US anthropogenic aerosols elicits a strong regional climate response, cooling the central and eastern US by 0.5–1.0 °C on average during 1970–1990, with the strongest effects on maximum daytime temperatures in summer and autumn. Aerosol cooling reflects comparable contributions from direct and indirect (cloud-mediated) radiative effects. Absorbing aerosol (mainly black carbon) has negligible warming effect. Aerosol cooling reduces surface evaporation and thus decreases precipitation along the US east coast, but also increases the southerly flow of moisture from the Gulf of Mexico resulting in increased cloud cover and precipitation in the central US. Observations over the eastern US show a lack of warming in 1960–1980 followed by very rapid warming since, which we reproduce in the GCM and attribute to trends in US anthropogenic aerosol sources. Present US aerosol concentrations are sufficiently low that future air quality improvements are projected to cause little further warming in the US (0.1 °C over 2010–2050). We find that most of the warming from aerosol source controls in the US has already been realized over the 1980–2010 period.

Climatic effects of 1950–2050 changes in US anthropogenic aerosols – Part 1: Aerosol trends and radiative forcing

Abstract. We calculate decadal aerosol direct and indirect (warm cloud) radiative forcings from US anthropogenic sources over the 1950–2050 period. Past and future aerosol distributions are constructed using GEOS-Chem and historical emission inventories and future projections from the IPCC A1B scenario. Aerosol simulations are evaluated with observed spatial distributions and 1980–2010 trends of aerosol concentrations and wet deposition in the contiguous US. Direct and indirect radiative forcing is calculated using the GISS general circulation model and monthly mean aerosol distributions from GEOS-Chem. The radiative forcing from US anthropogenic aerosols is strongly localized over the eastern US. We find that its magnitude peaked in 1970–1990, with values over the eastern US (east of 100° W) of −2.0 W m−2 for direct forcing including contributions from sulfate (−2.0 W m−2), nitrate (−0.2 W m−2), organic carbon (−0.2 W m−2), and black carbon (+0.4 W m−2). The uncertainties in radiative forcing due to aerosol radiative properties are estimated to be about 50%. The aerosol indirect effect is estimated to be of comparable magnitude to the direct forcing. We find that the magnitude of the forcing declined sharply from 1990 to 2010 (by 0.8 W m−2 direct and 1.0 W m−2 indirect), mainly reflecting decreases in SO2 emissions, and project that it will continue declining post-2010 but at a much slower rate since US SO2 emissions have already declined by almost 60% from their peak. This suggests that much of the warming effect of reducing US anthropogenic aerosol sources has already been realized. The small positive radiative forcing from US BC emissions (+0.3 W m−2 over the eastern US in 2010; 5% of the global forcing from anthropogenic BC emissions worldwide) suggests that a US emission control strategy focused on BC would have only limited climate benefit.

Meteorological modes of variability for fine particulate matter (PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt;) air quality in the United States: implications for PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; sensitivity to climate change

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

Assessment of climate change impact on floodplain and hydrologic ecotones

Current modeling efforts continue to indicate that the effects of climate change will be both global and local in scale, and that ecohydrologic factors including vegetation pattern, altered precipitation events, reduced system yields due to streamflow changes, increased flooding and changes to current floodplain characteristics will be affected. Therefore, using technology such as light detection and ranging (LiDAR) data, using future general circulation model (GCM) data, and conducting floodplain analyses to predict the changes to ecohydrologic factors are critical for cataloging existing ecosystem resources and for understanding the effects that different climate change scenarios may have on these resources at the basin scale. This study considers the effects of three different GCM climate change emissions scenarios (high from the IPSL GCM’s A2 scenario, middle from the ECHAM5 GCM’s A2 scenario and low from the GISS GCM’s B1 scenario) using daily downscaled precipitation and temperature data over the Lower Tualatin basin in the Pacific Northwest US. The Tualatin River basin is a dynamic watershed that supports urban and agricultural uses and is also 50% forested. Its economic drivers include agricultural and forest products, as well as other consumer products including high-tech software and hardware industries. The Soil and Water Assessment Tool (SWAT) software was used as a distributed hydrologic model to predict the daily flows in the basin. It is predicted the 50-year recurrence interval (RI) flow will decrease significantly for the low and middle emissions scenarios (to between approximately 18,000–19,000 cfs compared to the observed 50-year RI of near 26,000 cfs) and will increase significantly under the high emissions scenario to nearly 33,000 cfs. Floodplain extents for the various climate scenarios and timeframes were delineated using the HEC-RAS model. A geo-processing procedure was employed to delineate hydrologic ecotones to evaluate the condition of riparian areas and streams. A current and future conditions analysis was performed using the combination of aerial imagery and LiDAR data for the vegetation within the ecotones in order to: (1) provide an existing inventory of vegetation within the basin and (2) to predict the effects that climate change may have on vegetation within the basin.

Cloud Vertical Distribution across Warm and Cold Fronts in CloudSat–CALIPSO Data and a General Circulation Model

Abstract Cloud vertical distributions across extratropical warm and cold fronts are obtained using two consecutive winters of CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations and National Centers for Environmental Prediction reanalysis atmospheric state parameters over the Northern and Southern Hemisphere oceans (30°–70°N/S) between November 2006 and September 2008. These distributions generally resemble those from the original model introduced by the Bergen School in the 1920s, with the following exceptions: 1) substantial low cloudiness, which is present behind and ahead of the warm and cold fronts; 2) ubiquitous high cloudiness, some of it very thin, throughout the warm-frontal region; and 3) upright convective cloudiness near and behind some warm fronts. One winter of GISS general circulation model simulations of Northern and Southern Hemisphere warm and cold fronts at 2° × 2.5° × 32 levels resolution gives similar cloud distributions but with much lower cloud fraction, a shallower depth of cloudiness, and a shorter extent of tilted warm-frontal cloud cover on the cold air side of the surface frontal position. A close examination of the relationship between the cloudiness and relative humidity fields indicates that water vapor is not lifted enough in modeled midlatitude cyclones and this is related to weak vertical velocities in the model. The model also produces too little cloudiness for a given value of vertical velocity or relative humidity. For global climate models run at scales coarser than tens of kilometers, the authors suggest that the current underestimate of modeled cloud cover in the storm track regions, and in particular the 50°–60°S band of the Southern Oceans, could be reduced with the implementation of a slantwise convection parameterization.

Sensitivity of US air quality to mid-latitude cyclone frequency and implications of 1980–2006 climate change

Abstract. We show that the frequency of summertime mid-latitude cyclones tracking across eastern North America at 40°–50° N (the southern climatological storm track) is a strong predictor of stagnation and ozone pollution days in the eastern US. The NCEP/NCAR Reanalysis, going back to 1948, shows a significant long-term decline in the number of summertime mid-latitude cyclones in that track starting in 1980 (−0.15 a−1). The more recent but shorter NCEP/DOE Reanalysis (1979–2006) shows similar interannual variability in cyclone frequency but no significant long-term trend. Analysis of NOAA daily weather maps for 1980–2006 supports the trend detected in the NCEP/NCAR Reanalysis 1. A GISS general circulation model (GCM) simulation including historical forcing by greenhouse gases reproduces this decreasing cyclone trend starting in 1980. Such a long-term decrease in mid-latitude cyclone frequency over the 1980–2006 period may have offset by half the ozone air quality gains in the northeastern US from reductions in anthropogenic emissions. We find that if mid-latitude cyclone frequency had not declined, the northeastern US would have been largely compliant with the ozone air quality standard by 2001. Mid-latitude cyclone frequency is expected to decrease further over the coming decades in response to greenhouse warming and this will necessitate deeper emission reductions to achieve a given air quality goal.

Simulated effects of climate change on summertime nitrogen deposition in the eastern US

It is anticipated that climate change may impact regional-scale air quality and atmospheric deposition in the coming decades. To simulate the effects of climate change on nitrogen (N) deposition across numerous watersheds in the eastern US, we applied the NASA Goddard Institute for Space Studies General Circulation Model (GISS-GCM), Fifth Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system, and the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model. Keeping chemical initial and boundary conditions, land use, and anthropogenic area and point source emissions fixed, this modeling system was applied over five summers (June–August) from 1993 to 1997 and five summers from 2053 to 2057. Over these eastern US watersheds, the modeling system estimated 3–14% increases in summertime N deposition as a result of climate change. This increase is primarily due to the direct effects of climate change on atmospheric conditions and chemistry. Wet N deposition is predicted to increase as a result of increased precipitation, while dry N deposition is predicted to increase as higher surface temperatures favor gas-phase nitric acid to particulate nitrate. The simulated increase suggests that additional reductions in N oxides and/or ammonia may be needed to fully realize the anticipated benefits of planned reduction strategies, including the Clean Air Interstate Rule (CAIR).

The Tropical Atmospheric El Niño Signal in Satellite Precipitation Data and a Global Climate Model

AbstractAspects of the tropical atmospheric response to El Niño related to the global energy and water cycle are examined using satellite retrievals from the Tropical Rainfall Measuring Mission and the Advanced Microwave Scanning Radiometer-E and simulations from the Goddard Institute for Space Studies (GISS) general circulation model (GCM). The El Niño signal is extracted from climate fields using a linear cross-correlation technique that captures local and remote in-phase and lagged responses. Passive microwave and radar precipitation anomalies for the 1997/98 and 2002/03 El Niños and the intervening La Niña are highly correlated, but anomalies in stratiform–convective rainfall partitioning in the two datasets are not. The GISS GCM produces too much rainfall in general over ocean and too little over land. Its atmospheric response to El Niño is weaker and decays a season too early. Underestimated stratiform rainfall fraction (SRF) and convective downdraft mass flux in the GISS GCM and excessive shallow convective and low stratiform cloud result in latent heating that peaks at lower altitudes than inferred from the data. The GISS GCM also underestimates the column water vapor content throughout the Tropics, which causes it to overestimate outgoing longwave radiation. The response of both quantities to interannual Hadley circulation anomalies is too weak. The GISS GCM’s Walker circulation also exhibits a weak remote response to El Niño, especially over the Maritime Continent and western Indian Ocean. This appears to be a consequence of weak static stability due to the model’s lack of upper-level stratiform anvil heating, excessive low-level heating, and excessive dissipation due to cumulus momentum mixing. Our results suggest that parameterizations of mesoscale updrafts, convective downdrafts, and cumulus-scale pressure gradient effects on momentum transport are keys to a reasonable GISS GCM simulation of tropical interannual variability.

A comparison of statistical and dynamical downscaling for surface temperature in North America

Projections from general circulation model (GCM) simulations must be downscaled to the high spatial resolution needed for assessing local and regional impacts of climate change, but uncertainties in the downscaling process are difficult to quantify. We employed a multiple linear regression model and the MM5 dynamical model to downscale June, July, and August monthly mean surface temperature over eastern North America under greenhouse gas‐driven climate change simulation by the NASA GISS GCM. Here we examine potential sources of apparent agreement between the two classes of models and show that arbitrary parameters in a statistical model contribute significantly to the level of agreement with dynamical downscaling. We found that the two methods and all permutations of regression parameters generally exhibited comparable skill at simulating observations, although spatial patterns in temperature across the region differed. While the two methods projected similar regional mean warming over the period 2000–2087, they developed different spatial patterns of temperature across the region, which diverged further from historical differences. We found that predictor domain size was a negligible factor for current conditions, but had a much greater influence on future surface temperature change than any other factor, including the data sources. The relative importance of SD model inputs to downscaled skill and domain‐wide agreement with MM5 for summertime surface temperature over North America in descending order is Predictor Domain; Training Data/Predictor Model; Predictor Variables; and Predictor Grid Resolution. Our results illustrate how statistical downscaling may be used as a proxy for dynamical models in sensitivity analysis.

Biogenic secondary organic aerosol over the United States: Comparison of climatological simulations with observations

Understanding the effects of global climate change on regional air quality is central in future air quality planning. We report here on the use of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) III to drive the GEOS‐CHEM global atmospheric chemical transport model to simulate climatological present‐day aerosol levels over the United States. Evaluation of model predictions using surface measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network indicates that the GISS GCM III/GEOS‐CHEM model is a suitable tool for simulating aerosols over the United States in the present climate. The model reproduces fairly well the concentrations of sulfate (mean bias of −0.36 μg m−3, normalized mean bias (NMB) of −25.9%), black carbon (−0.004 μg m−3, −1.9%), organic carbon that comprises primary and secondary components (−0.56 μg m−3, −34.2%), and PM2.5 (−0.87 μg m−3, −20.4%). Nitrate concentrations are overpredicted in the western United States (west of 95°W) with a NMB of +75.6% and underestimated in the eastern United States with a NMB of −54.4%. Special attention is paid to biogenic secondary organic aerosol (SOA). The highest predicted seasonal mean SOA concentrations of 1–2 μg m−3 and 0.5–1.5 μg m−3 are predicted over the northwestern and southeastern United States, respectively, in the months of June–July–August. Isoprene is predicted to contribute 49.5% of the biogenic SOA burden over the United States, with the rest explained by the oxidation of terpenes. Predicted biogenic SOA concentrations are in reasonable agreement with inferred SOA levels from IMPROVE measurements. On an annual basis, SOA is predicted to contribute 10–20% of PM2.5 mass in the southeastern United States, as high as 38% in the northwest and about 5–15% in other regions, indicating the important role of SOA in understanding air quality and visibility over the United States.

Preindustrial-to-present-day radiative forcing by tropospheric ozone from improved simulations with the GISS chemistry-climate GCM

Abstract. Improved estimates of the radiative forcing from tropospheric ozone increases since the preindustrial have been calculated with the tropospheric chemistry model used at the Goddard Institute for Space Studies (GISS) within the GISS general circulation model (GCM). The chemistry in this model has been expanded to include simplified representations of peroxyacetylnitrates and non-methane hydrocarbons in addition to background NOx-HOx-Ox-CO-CH4 chemistry. The GCM has improved resolution and physics in the boundary layer, improved resolution near the tropopause, and now contains a full representation of stratospheric dynamics. Simulations of present-day conditions show that this coupled chemistry-climate model is better able to reproduce observed tropospheric ozone, especially in the tropopause region, which is critical to climate forcing. Comparison with preindustrial simulations gives a global annual average radiative forcing due to tropospheric ozone increases of 0.30 W/m2 with standard assumptions for preindustrial emissions. Locally, the forcing reaches more than 0.8 W/m2 in parts of the northern subtropics during spring and summer, and is more than 0.6 W/m2 through nearly all the Northern subtropics and mid-latitudes during summer. An alternative preindustrial simulation with soil NOx emissions reduced by two-thirds and emissions of isoprene, paraffins and alkenes from vegetation increased by 50% gives a forcing of 0.33 W/m2. Given the large uncertainties in preindustrial ozone amounts, the true value may lie well outside this range.

Predicting global aerosol size distributions in general circulation models

To better represent the indirect effect of aerosols on climate, a size‐resolved simulation of aerosol microphysics, size distributions, number and mass concentrations has been incorporated into the GISS general circulation model (GCM). The TwO‐Moment Aerosol Sectional (TOMAS) microphysics model used here conserves aerosol number as well as mass. It has high size resolution, 30 bins between 0.01 and 10 μm diameter. As a first application, a size‐resolved simulation of sulfate has been performed. The model reproduces important features of the atmospheric aerosol such as number concentrations that increase with altitude and land‐sea contrasts in aerosol number concentrations and size distributions. Comparisons with observations show that simulated size distributions are realistic and condensation nuclei (CN) concentrations agree with observations within about 25%. Predicted cloud condensation nuclei (CCN) concentrations are also in reasonable agreement with observations, although there are locations for which agreement would be improved by including other aerosol components such as sea salt and carbonaceous aerosols. Sensitivity scenarios show that uncertainties in nucleation and primary emissions from fossil fuels can have significant effects on predictions of CN and CCN concentrations.

Climate response to basin‐specific changes in latitudinal temperature gradients and implications for sea ice variability

We use experiments with the GISS general circulation model to investigate how changes in latitudinal temperature gradients affect atmospheric circulation in different ocean basins, with particular attention paid to the implications for high‐latitude sea ice. The results are relevant to both estimated past climate changes, current climate gradient changes (e.g., El Niño‐Southern Oscillation events), and proposed future climate responses to greenhouse gases. Sea surface temperature gradients are increased/decreased in all ocean basins, and in the Pacific and Atlantic separately, without changing sea ice or global average temperature. Additional experiments prescribe sea ice growth/reduction with global cooling/warming. As expected, increased gradients strengthen the subtropical jet stream and deepen the subpolar lows in each hemisphere, but results in the Northern and Southern Hemispheres differ in fundamental ways. In the Northern Hemisphere, increased storm intensities occur in the ocean basin with the increased gradient; in the Southern Hemisphere the deeper storms occur in the ocean basin with the decreased gradient. Alterations of the gradient in one ocean basin change longitudinal temperature gradients; an increased gradient in one basin from tropical heating results in subsidence in the tropics in the other basin, mimicking the effect of a decreased gradient in that basin. The subtropical jet is therefore strengthened over the basin with the increased gradient and decreased over the other ocean basin. Hence in many respects, regional effects, such as the strength of subpolar lows in an individual basin, are amplified when the gradient changes are of opposite sign in the two ocean basins. The Southern Hemisphere response occurs because gradient increases in one ocean basin, by strengthening the subtropical jet, shift storm tracks equatorward and away from the potential energy source associated with cold air advection from Antarctica. At the same time, with a weaker subtropical jet in the other basin, storms move poleward and strengthen. This latter effect may explain observed sea ice variations that are out of phase in the Atlantic and Pacific Ocean basins in the Southern Hemisphere (referred to as the Antarctic dipole) as well as upper ocean variability in the Weddell gyre. Gradient changes produce little effect on sea level pressure in the Arctic, unless sea ice is changed. With Arctic sea ice reductions, the sea ice response acts as a positive feedback, inducing cyclonic circulation changes that would enhance its removal, as may be occurring due to the current high phase of the North Atlantic Oscillation.

Stratospheric ozone in 3‐D models: A simple chemistry and the cross‐tropopause flux

Two simple and computationally efficient models for simulating stratospheric ozone in three‐dimensional global transport models are presented. The first, linearized ozone (or Linoz), is a first‐order Taylor expansion of stratospheric chemical rates in which the ozone tendency has been linearized about the local ozone mixing ratio, temperature, and the overhead column ozone density. The second, synthetic ozone (or Synoz), is a passive, ozone‐like tracer released into the stratosphere at a rate equivalent to that of the cross‐tropopause ozone flux which, based on measurements and tracer‐tracer correlations, we have calculated to be 475±120 Tg/yr. Linoz and Synoz have been evaluated in the UC Irvine chemical transport model (CTM) with three different archived meteorological fields: the Goddard Institute for Space Studies (GISS) general circulation model (GCM) version II′, the GISS GCM version II, and merged forecast data from the European Centre forecast model (EC/Oslo). Linoz produced realistic annual, cross‐tropopause fluxes of 421 Tg/yr for the GISS II′ winds and 458 Tg/yr for the EC/Oslo winds; the GISS II winds produced an unrealistic flux of 790 Tg/yr. Linoz and Synoz profiles in the vicinity of the tropopause using the GISS II′ and EC/Oslo winds were found to be in good agreement with observations. We conclude that either approach may be adequate for a CTM focusing on tropospheric chemistry but that Linoz can also be used for calculating ozone fields interactively with the stratospheric circulation in a GCM. A future version of Linoz will allow for evolving background concentrations of key source gases, such as CH4 and N2O, and thus be applicable for long‐term climate simulations.