[1] Solar geoengineering-deliberate reduction in the amount of solar radiation retained by the Earth-has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO 2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO 2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO 2 levels but, compared to the preindustrial climate, leaves the tropics cooler (À0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2 mm day À1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO 2 fertilization, but also in part due to reduced plant heat stress compared to a high CO 2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.
International audienceThe collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint ESA-JAXA EarthCARE satellite mission, scheduled for launch in 2017, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, CALIPSO, and Aqua. Specifically, EarthCARE's Cloud Profling Radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle and raindrop fall speeds. EarthCARE's 355-nm High Spectral Resolution Lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The Multi-Spectral Imager will provide a context for, and the ability to construct the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross-section. The consistency of the retrievals will be assessed to within a target of ±10 W m−2 on the (10 km2) scale by comparing the multi-view Broad-Band Radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains
Despite continued growth in atmospheric levels of greenhouse gases, globalmean surface and tropospheric temperatures show slower warming since 1998 1−5 . Possible explanations for this "warming hiatus" include internal climate variability 3,4,6,7 , external cooling influences 1,2,4,8−11 , and observational errors 12,13 . One contributory factor to the relatively muted surface warming -early 21st century volcanic forcing -has been examined in several modelling studies 1,2,4,8 . Here we present the first analysis of the impact of recent volcanic forcing on tropospheric temperature, and the first observational assessment of the significance of early 21st century volcanic signals. We identify statistically significant signals in the correlations between stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without early 21st century volcanic forcing overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic forcing following the 1991 Pinatubo eruption, differences between modelled and observed tropospheric temperature trends over 1998 to 2012 are decreased by up to 15%, with large uncertainties in the size of the effect. Reducing these uncertainties will require better observational understanding of eruption-specific differences in volcanic aerosol properties, and improved representation of these differences in model simulations. B. D. Santer et al. 3Our analysis uses satellite measurements of changes in the temperature of the lower troposphere (TLT) made by Microwave Sounding Units (MSU) on NOAA polarorbiting satellites 13,14 . Satellite TLT data have near-global, time-invariant spatial coverage; in contrast, global-mean trends estimated from surface thermometer records can be biased by spatially-and temporally non-random coverage changes 15 . We compare MSU TLT data to synthetic satellite temperatures 3 calculated from simulations Although our primary focus is on the recent "warming hiatus", we also examine volcanically-induced changes in warming rate following the eruptions of El Chichón (April 1982) and Pinatubo (June 1991). Both volcanic events increased stratospheric loadings of liquid-phase sulfate aerosols, leading to stratospheric warming and tropospheric cooling ( Supplementary Fig. 1) 17−19 . Stratospheric temperature recovers within 1-2 years after El Chichón and Pinatubo. Because of the large thermal inertia of the ocean, the recovery of tropospheric temperatures is slower (ca. 8-10 years) 20,21 .To analyze volcanic contributions to observed changes in warming rates, it is useful to reduce the amplitude of internal noise 20−22 . Our noise reduction strategy involves removing the temperature signal of the El Niño/Southern Oscillation (ENSO), a (Fig. 1C). After 1999, however, a "warming hiatus" is still apparent in the observed residual TLT time series, but the lower troposphere continues to warm in the CMIP-5 multi-mo...
[1] Using NASA's A-Train satellite measurements, we evaluate the accuracy of cloud water content (CWC) and water vapor mixing ratio (H 2 O) outputs from 19 climate models submitted to the Phase 5 of Coupled Model Intercomparison Project (CMIP5), and assess improvements relative to their counterparts for the earlier CMIP3. We find more than half of the models show improvements from CMIP3 to CMIP5 in simulating column-integrated cloud amount, while changes in water vapor simulation are insignificant. For the 19 CMIP5 models, the model spreads and their differences from the observations are larger in the upper troposphere (UT) than in the lower or middle troposphere (L/MT). The modeled mean CWCs over tropical oceans range from $3% to $15Â of the observations in the UT and 40% to 2Â of the observations in the L/MT. For modeled H 2 Os, the mean values over tropical oceans range from $1% to 2Â of the observations in the UT and within 10% of the observations in the L/MT. The spatial distributions of clouds at 215 hPa are relatively well-correlated with observations, noticeably better than those for the L/MT clouds. Although both water vapor and clouds are better simulated in the L/MT than in the UT, there is no apparent correlation between the model biases in clouds and water vapor. Numerical scores are used to compare different model performances in regards to spatial mean, variance and distribution of CWC and H 2 O over tropical oceans. Model performances at each pressure level are ranked according to the average of all the relevant scores for that level.Citation: Jiang, J. H., et al. (2012), Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA "A-Train" satellite observations,
ABSTRACT:Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) programme's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud-top temperature of −15 • C. The average liquid water path of around 160 g m −2 was about two-thirds of the adiabatic value and far greater than the average mass of ice which when integrated from the surface to cloud top was around 15 g m −2 .Simulations of 17 single-column models (SCMs) and 9 cloud-resolving models (CRMs) are compared. While the simulated ice water path is generally consistent with observed values, the median SCM and CRM liquid water path is a factor-of-three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path.Despite this underestimate, the simulated liquid and ice water paths of several models are consistent with observed values. Furthermore, models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter exists. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.
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