The crystallization kinetics of polypropylene (PP), polyamide (PA66), and poly(ethylene terephthalate) (PET) were studied, using a pressure dilatometer (to 200 MPa) to follow the volume changes associated with the crystallization process. The commonly used Avrami equation fitted the isothermal/isobaric crystallization data of PP and PA66 well. The Avrami exponent n was between 1.3 and 1.7, independent of crystallization pressure and temperature. Lines of constant Avrami rate parameter Z in the P‐T plane were essentially parallel to the pressure dependence of the melting points and crystallization temperatures. However, the Avrami equation was not suitable for PET. The Malkin, Dietz, and Kim equations provided better fits. The crystallization half‐time of PET increased with pressure at constant supercooling, in contrast to PP and PA66, for which it remained essentially unchanged. X‐ray diffraction, differential scanning calorimetry, and pressure dilatometry were used to study the effect of formation pressure on the crystal structure, the melting point, and the density of products which were crystallized for short times (minutes) at various temperatures and pressures. No new crystal structures were found for PA66 and PET, but a mixture of monoclinic and triclinic crystals existed in PP above a formation pressure of 50 MPa. The melting points increased with formation pressure for PET, but remained unchanged for PP and PA66. Density at ambient conditions decreased with formation pressure for PP, but increased for PET and PA66. © 1994 John Wiley & Sons, Inc.

Abstract.One of the greatest sources of uncertainty in the science of anthropogenic climate change is from aerosolcloud interactions. The activation of aerosols into cloud droplets is a direct microphysical linkage between aerosols and clouds; parameterizations of this process link aerosol with cloud condensation nuclei (CCN) and the resulting indirect effects. Small differences between parameterizations can have a large impact on the spatiotemporal distributions of activated aerosols and the resulting cloud properties. In this work, we incorporate a series of aerosol activation schemes into the Community Atmosphere Model version 5.1.1 within the Community Earth System Model version 1.0.5 (CESM/CAM5) which include factors such as insoluble aerosol adsorption and giant cloud condensation nuclei (CCN) activation kinetics to understand their individual impacts on global-scale cloud droplet number concentration (CDNC). Compared to the existing activation scheme in CESM/CAM5, this series of activation schemes increase the computation time by ∼ 10 % but leads to predicted CDNC in better agreement with satellite-derived/in situ values in many regions with high CDNC but in worse agreement for some regions with low CDNC. Large percentage changes in predicted CDNC occur over desert and oceanic regions, owing to the enhanced activation of dust from insoluble aerosol adsorption and reduced activation of sea spray aerosol after accounting for giant CCN activation kinetics. Comparison of CESM/CAM5 predictions against satellite-derived cloud optical thickness and liquid water path shows that the updated activation schemes generally improve the low biases. Globally, the incorporation of all updated schemes leads to an average increase in column CDNC of 150 % and an increase (more negative) in shortwave cloud forcing of 12 %. With the improvement of model-predicted CDNCs and better agreement with most satellite-derived cloud properties in many regions, the inclusion of these aerosol activation processes should result in better predictions of radiative forcing from aerosol-cloud interactions.

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmosphere Model version 4.1 (AM4.1), which builds on developments at GFDL over 2013-2018 for coupled carbon-chemistry-climate simulation as part of the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's AM4.0 development effort, which focused on physical and aerosol interactions and which is used as the atmospheric component of CM4.0, AM4.1 focuses on comprehensiveness of Earth system interactions. Key features of this model include doubled horizontal resolution of the atmosphere (~200 to~100 km) with revised dynamics and physics from GFDL's previous-generation AM3 atmospheric chemistry-climate model. AM4.1 features improved representation of atmospheric chemical composition, including aerosol and aerosol precursor emissions, key land-atmosphere interactions, comprehensive land-atmosphere-ocean cycling of dust and iron, and interactive ocean-atmosphere cycling of reactive nitrogen. AM4.1 provides vast improvements in fidelity over AM3, captures most of AM4.0's baseline simulations characteristics, and notably improves on AM4.0 in the representation of aerosols over the Southern Ocean, India, and China-even with its interactive chemistry representation-and in its manifestation of sudden stratospheric warmings in the coldest months. Distributions of reactive nitrogen and sulfur species, carbon monoxide, and ozone are all substantially improved over AM3. Fidelity concerns include degradation of upper atmosphere equatorial winds and of aerosols in some regions. Plain Language Summary GFDL has developed a coupled chemistry-climate Atmospheric Model (AM4.1) as part of its fourth-generation coupled model development activities. AM4.1 includes comprehensive atmospheric chemistry for representing ozone and aerosols and has been developed for use in chemistry and air quality applications, including advanced land-atmosphere-ocean coupling. With fidelity near to that of AM4.0, AM4.1 features vastly improved representation of climate mean patterns and variability from previous GFDL atmospheric chemistry-climate models.

The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 with the Carbon Bond 2005 (CB05) gas-phase mechanism is evaluated for its first decadal application during 2001-2010 using the Representative Concentration Pathway 8.5 (RCP 8.5) emissions to assess its capability and appropriateness for long-term climatological simulations. The initial and boundary conditions are downscaled from the modified Community Earth System Model/Community Atmosphere Model (CESM/CAM5) v1.2.2. The meteorological initial and boundary conditions are bias-corrected using the National Center for Environmental Protection's Final (FNL) Operational Global Analysis data. Climatological evaluations are carried out for meteorological, chemical, and aerosol-cloud-radiation variables against data from surface networks and satellite retrievals. The model performs very well for the 2 m temperature (T2) for the 10-year period, with only a small cold bias of −0.3 • C. Biases in other meteorological variables including relative humidity at 2 m, wind speed at 10 m, and precipitation tend to be site-and season-specific; however, with the exception of T2, consistent annual biases exist for most of the years from 2001 to 2010. Ozone mixing ratios are slightly overpredicted at both urban and rural locations with a normalized mean bias (NMB) of 9.7 % but underpredicted at rural locations with an NMB of −8.8 %. PM 2.5 concentrations are moderately overpredicted with an NMB of 23.3 % at rural sites but slightly underpredicted with an NMB of −10.8 % at urban/suburban sites. In general, the model performs relatively well for chemical and meteorological variables, and not as well for aerosol-cloud-radiation variables. Cloudaerosol variables including aerosol optical depth, cloud water path, cloud optical thickness, and cloud droplet number concentration are generally underpredicted on average across the continental US. Overpredictions of several cloud variables over the eastern US result in underpredictions of radiation variables (such as net shortwave radiation -GSW -with a mean bias -MB -of −5.7 W m −2 ) and overpredictions of shortwave and longwave cloud forcing (MBs of ∼ 7 to 8 W m −2 ), which are important climate variables. While the current performance is deemed to be acceptable, improvements to the bias-correction method for CESM downscaling and the model parameterizations of cloud dynamics and thermodynamics, as well as aerosol-cloud interactions, can potentially improve model performance for long-term climate simulations.Published by Copernicus Publications on behalf of the European Geosciences Union.

Earth system models have been used for climate predictions in recent years due to their capabilities to include biogeochemical cycles, human impacts, as well as coupled and interactive representations of Earth system components (e.g., atmosphere, ocean, land, and sea ice). In this work, the Community Earth System Model (CESM) with advanced chemistry and aerosol treatments, referred to as CESM-NCSU, is applied for decadal (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) , and PM 10 are also reasonably well predicted over Europe with NMBs of 220.8 to 25.2%, so are predictions of SO 2 concentrations over the East Asia with an NMB of 218.2%, and the tropospheric ozone residual (TOR) over the globe with an NMB of 23.5%. Most meteorological and radiative variables predicted by CESM-NCSU agree well overall with those predicted by CESM-CMIP5. The performance of LWP and AOD predicted by CESM-NCSU is better than that of CESM-CMIP5 in terms of model bias and correlation coefficients. Large biases for some chemical predictions can be attributed to uncertainties in the emissions of precursor gases (e.g., SO 2 , NH 3 , and NO x ) and primary aerosols (black carbon and primary organic matter) as well as uncertainties in formulations of some model components (e.g., online dust and sea-salt emissions, secondary organic aerosol formation, and cloud microphysics). Comparisons of CESM simulation with baseline emissions and 20% of anthropogenic emissions from the baseline emissions indicate that anthropogenic gas and aerosol species can decrease downwelling shortwave radiation (FSDS) by 4.7 W m 22 (or by 2.9%) and increase SWCF by 3.2 W m 22 (or by 3.1%) in the global mean.