21 research outputs found
Estimating the summertime tropospheric ozone distribution over North America through assimilation of observations from the Tropospheric Emission Spectrometer
The vertical distribution of ozone instantaneous radiative forcing from satellite and chemistry climate models
We evaluate the instantaneous radiative forcing (IRF) of tropospheric ozone predicted by four state-of-the-art global chemistry climate models (AM2-Chem, CAM-Chem, ECHAM5-MOZ, and GISS-PUCCINI) against ozone distribution observed from the NASA Tropospheric Emission Spectrometer (TES) during August 2006. The IRF is computed through the application of an observationally constrained instantaneous radiative forcing kernels (IRFK) to the difference between TES and model-predicted ozone. The IRFK represent the sensitivity of outgoing longwave radiation to the vertical and spatial distribution of ozone under all-sky condition. Through this technique, we find total tropospheric IRF biases from -0.4 to + 0.7 W/m(2) over large regions within the tropics and midlatitudes, due to ozone differences over the region in the lower and middle troposphere, enhanced by persistent bias in the upper troposphere-lower stratospheric region. The zonal mean biases also range from -30 to + 50 mW/m(2) for the models. However, the ensemble mean total tropospheric IRF bias is less than 0.2 W/m(2) within the entire troposphere
Climate change and water resources in arid regions : uncertainty of the baseline time period
Recent climate change studies have given a lot of attention to the uncertainty that stems from general circulation models (GCM), greenhouse gas emission scenarios, hydrological models and downscaling approaches. Yet, the uncertainty that stems from the selection of the baseline period has not been studied. Accordingly, the main research question is as follows: What would be the differences and/or the similarities in the evaluation of climate change impacts between the GCM and the delta perturbation scenarios using different baseline periods? This article addresses this issue through comparison of the results of two different baseline periods, investigating the uncertainties in evaluating climate change impact on the hydrological characteristics of arid regions. The Lower Zab River Basin (Northern Iraq) has been selected as a representative case study. The research outcomes show that the considered baseline periods suggest increases and decreases in the temperature and precipitation (P), respectively, over the 2020, 2050 and 2080 periods. The two climatic scenarios are likely to lead to similar reductions in the reservoir mean monthly flows, and subsequently, their maximum discharge is approximately identical. The predicted reduction in the inflow for the 2080–2099 time period fluctuates between 31 and 49% based on SRA1B and SRA2 scenarios, respectively. The delta perturbation scenario permits the sensitivity of the climatic models to be clearly determined compared to the GCM. The former allows for a wide variety of likely climate change scenarios at the regional level and are easier to generate and apply so that they could complement the latter
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A single-column model ensemble approach applied to the TWP-ICE experiment
Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only
Characterizing the tropospheric ozone response to methane emission controls and the benefits to climate and air quality
Reducing methane (CH4) emissions is an attractive option for jointly addressing climate and ozone (O3) air quality goals. With multidecadal full-chemistry transient simulations in the MOZART-2 tropospheric chemistry model, we show that tropospheric O3 responds approximately linearly to changes in CH4 emissions over a range of anthropogenic emissions from 0–430 Tg CH4 a−1 (0.11–0.16 Tg tropospheric O3 or ∼11–15 ppt global mean surface O3 decrease per Tg a−1 CH4 reduced). We find that neither the air quality nor climate benefits depend strongly on the location of the CH4 emission reductions, implying that the lowest cost emission controls can be targeted. With a series of future (2005–2030) transient simulations, we demonstrate that cost-effective CH4 controls would offset the positive climate forcing from CH4 and O3 that would otherwise occur (from increases in NOx and CH4 emissions in the baseline scenario) and improve O3 air quality. We estimate that anthropogenic CH4 contributes 0.7 Wm−2 to climate forcing and ∼4 ppb to surface O3 in 2030 under the baseline scenario. Although the response of surface O3 to CH4 is relatively uniform spatially compared to that from other O3 precursors, it is strongest in regions where surface air mixes frequently with the free troposphere and where the local O3 formation regime is NOx-saturated. In the model, CH4 oxidation within the boundary layer (below ∼2.5 km) contributes more to surface O3 than CH4 oxidation in the free troposphere. In NOx-saturated regions, the surface O3 sensitivity to CH4 can be twice that of the global mean, with >70% of this sensitivity resulting from boundary layer oxidation of CH4. Accurately representing the NOx distribution is thus crucial for quantifying the O3 sensitivity to CH4
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Impacts of 21st century climate change on global air pollution-related premature mortality
Climate change modulates surface concentrations of fine particulate matter (PM2.5) and ozone (O-3), indirectly affecting premature mortality attributed to air pollution. We estimate the change in global premature mortality and years of life lost (YLL) associated with changes in surface O-3 and PM2.5 over the 21st century as a result of climate change. We use a global coupled chemistry-climate model to simulate current and future climate and the effect of changing climate on air quality. Epidemiological concentration-response relationships are applied to estimate resulting changes in premature mortality and YLL. The effect of climate change on air quality is isolated by holding emissions of air pollutants constant while allowing climate to evolve over the 21st century according to a moderate projection of greenhouse gas emissions (A1B scenario). Resulting changes in 21st century climate alone lead to an increase in simulated PM2.5 concentrations globally, and to higher (lower) O-3 concentrations over populated (remote) regions. Global annual premature mortality associated with chronic exposure to PM2.5 increases by approximately 100 thousand deaths (95 % confidence interval, CI, of 66-130 thousand) with corresponding YLL increasing by nearly 900 thousand (95 % CI, 576-1,128 thousand) years. The annual premature mortality due to respiratory disease associated with chronic O-3 exposure increases by +6,300 deaths (95 % CI, 1,600-10,400). This climate penalty indicates that stronger emission controls will be needed in the future to meet current air quality standards and to avoid higher health risks associated with climate change induced worsening of air quality over populated regions.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000326944000011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Environmental SciencesMeteorology & Atmospheric SciencesSCI(E)EI17ARTICLE2239-25312
On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles
Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO 2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45863/1/382_2006_Article_111.pd
Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)
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The role of large-scale convective organization for tropical high cloud amount
Tropical high clouds are closely coupled to deep convection, but local cloud amount and convective mass flux are nonlinearly related. We use the Geophysical Fluid Dynamics Laboratory atmosphere‐only model AM2 forced with idealized sea surface temperature (SST) perturbations to study the sensitivity of high clouds to the large‐scale distribution of convection. Increasing/decreasing the SST contrast between convective and nonconvective regions decreases/increases the tropical deep convective area, and warming of convective areas decreases the tropical average convective mass flux (〈m c 〉). In all experiments, fractional high cloud amount changes are less than fractional changes in 〈m c 〉. High cloud amount is half as sensitive as expected from the climatological average cloud amount, as a function of convective mass flux, due to strong compensation from nonconvective high clouds. The latter results from changes in relative humidity related to the change in 〈m c 〉. This effect renders high cloud amount remarkably robust to perturbations, though radiative effects of convective and nonconvective clouds will differ
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The influence of ozone precursor emissions from four world regions on tropospheric composition and radiative climate forcing
Ozone (O-3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O-3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO42-). We examine changes in the tropospheric composition of O-3, CH4, SO42- and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O-3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean +/- 1 standard deviation) across multiple CTMs. We evaluate steady state O-3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 +/- 0.6 to 1.7 +/- 2 mWm(-2)/TgN yr(-1)), with some variation among models. Negative net RFs result from reductions in global CH4 (-162.6 +/- 2 mWm(-2) for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (-0.4 +/- 0.2 to -0.7 +/- 0.2 mWm(-2)/Tg C yr(-1)) and CO emissions (-0.13 +/- 0.02 to -0.15 +/- 0.02 mWm(-2)/Tg CO yr(-1)). Including the effect of O-3 on CO2 uptake by vegetation likely makes these net RFs more negative by -1.9 to -5.2 mWm(-2)/Tg N yr(-1), -0.2 to -0.7 mWm(-2)/Tg C yr(-1), and -0.02 to -0.05 mWm(-2)/Tg CO yr(-1). Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO42-, regionally to hemispherically by O-3, and globally by CH4. Global annual average SO42- responses to oxidant changes range from 0.4 +/- 2.6 to -1.9 +/- 1.3 Gg for NOx reductions, 0.1 +/- 1.2 to -0.9 +/- 0.8 Gg for NMVOC reductions, and -0.09 +/- 0.5 to -0.9 +/- 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP(100)) are calculated for the global CH4 reduction (20.9 +/- 3.7 without stratospheric O-3 or water vapor, 24.2 +/- 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (-18.7 +/- 25.9 to -1.9 +/- 8.7 for NOx, 4.8 +/- 1.7 to 8.3 +/- 1.9 for NMVOC, and 1.5 +/- 0.4 to 1.7 +/- 0.5 for CO). Variation in GWP(100) for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusio