Tropical thin cirrus and relative humidity observed by the Atmospheric Infrared Sounder

International audienceGlobal observations of cloud and humidity distributions in the upper troposphere within all geophysical conditions are critically important in order to monitor the present climate and to provide necessary data for validation of climate models to project future climate change. Towards this end, tropical oceanic distributions of thin cirrus optical depth (?), effective diameter (De), and relative humidity with respect to ice (RHi) within cirrus (RHic) are simultaneously derived from the Atmospheric Infrared Sounder (AIRS). Corresponding increases in De and cloud temperature are shown for cirrus with ?>0.25 that demonstrate quantitative consistency to other surface-based, in situ and satellite retrievals. However, inferred cirrus properties are shown to be less certain for increasingly tenuous cirrus. In-cloud supersaturation is observed for 8?12% of thin cirrus and is several factors higher than all-sky conditions; even higher frequencies are shown for the coldest and thinnest cirrus. Spatial and temporal variations in RHic correspond to cloud frequency while regional variability in RHic is observed to be most prominent over the N. Indian Ocean basin. The largest cloud/clear sky RHi anomalies tend to occur in dry regions associated with vertical descent in the sub-tropics, while the smallest occur in moist ascending regions in the tropics. The characteristics of RHic frequency distributions depend on ? and a peak frequency is located between 60?80% that illustrates RHic is on average biased dry. The geometrical thickness of cirrus is typically less than the vertical resolution of AIRS temperature and specific humidity profiles and thus leads to the observed dry bias, shown with coincident cloud vertical structure obtained from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The joint distributions of thin cirrus microphysics and humidity derived from AIRS provide unique and important regional and global-scale insights on upper tropospheric processes not available from surface, in situ, and other contemporary satellite observing platforms

Sensitivity Studies of Dust Ice Nuclei Effect on Cirrus Clouds with the Community Atmosphere Model CAM5

In this study the effect of dust aerosol on upper tropospheric cirrus clouds through heterogeneous ice nucleation is investigated in the Community Atmospheric Model version 5 (CAM5) with two ice nucleation parameterizations. Both parameterizations consider homogeneous and heterogeneous nucleation and the competition between the two mechanisms in cirrus clouds, but differ significantly in the number concentration of heterogeneous ice nuclei (IN) from dust. Heterogeneous nucleation on dust aerosol reduces the occurrence frequency of homogeneous nucleation and thus the ice crystal number concentration in the Northern Hemisphere (NH) cirrus clouds compared to simulations with pure homogeneous nucleation. Global and annual mean shortwave and longwave cloud forcing are reduced by up to 2.0+/-0.1Wm (sup2) (1 uncertainty) and 2.4+/-0.1Wm (sup2), respectively due to the presence of dust IN, with the net cloud forcing change of 0.40+/-0.20W m(sup2). Comparison of model simulations with in situ aircraft data obtained in NH mid-latitudes suggests that homogeneous ice nucleation may play an important role in the ice nucleation at these regions with temperatures of 205-230 K. However, simulations overestimate observed ice crystal number concentrations in the tropical tropopause regions with temperatures of 190- 205 K, and overestimate the frequency of occurrence of high ice crystal number concentration (greater than 200 L(sup-1) and underestimate the frequency of low ice crystal number concentration (less than 30 L(sup-1) at NH mid-latitudes. These results highlight the importance of quantifying the number concentrations and properties of heterogeneous IN (including dust aerosol) in the upper troposphere from the global perspective

The Evolution of Climate Sensitivity and Climate Feedbacks in the Community Atmosphere Model

The major evolution of the National Center for Atmospheric Research Community Atmosphere Model (CAM) is used to diagnose climate feedbacks, understand how climate feedbacks change with different physical parameterizations, and identify the processes and regions that determine climate sensitivity. In the evolution of CAM from version 4 to version 5, the water vapor, temperature, surface albedo, and lapse rate feedbacks are remarkably stable across changes to the physical parameterization suite. However, the climate sensitivity increases from 3.2 K in CAM4 to 4.0 K in CAM5. The difference is mostly due to (i) more positive cloud feedbacks and (ii) higher CO₂ radiative forcing in CAM5. The intermodel differences in cloud feedbacks are largest in the tropical trade cumulus regime and in the midlatitude storm tracks. The subtropical stratocumulus regions do not contribute strongly to climate feedbacks owing to their small area coverage. A “modified Cess” configuration for atmosphere-only model experiments is shown to reproduce slab ocean model results. Several parameterizations contribute to changes in tropical cloud feedbacks between CAM4 and CAM5, but the new shallow convection scheme causes the largest midlatitude feedback differences and the largest change in climate sensitivity. Simulations with greater cloud forcing in the mean state have lower climate sensitivity. This work provides a methodology for further analysis of climate sensitivity across models and a framework for targeted comparisons with observations that can help constrain climate sensitivity to radiative forcing.Keywords: Cloud forcing, Cloud radiative effects, Feedback, Climate sensitivity, Climate model

The potential to narrow uncertainty in projections of stratospheric ozone over the 21st century

Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an "ensemble of opportunity" of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21st century, up-to and after the time when ozone concentrations return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

This is the final version. Available from National Academy of Sciences via the DOI in this recordA large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.The Pacific Northwest National Laboratory (PNNL) is operated for the Department of Energy (DOE) by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830. Work at PNNL was supported by the US DOE Decadal and Regional Climate Prediction using Earth System Models program and by the US DOE Earth System Modeling program. Work of M.W. and S.Z. performed at Nanjing University was supported by the One Thousand Young Talent Program, Jiangsu Province Specially-Appointed Professor Grant, and the National Natural Science Foundation of China (41575073). A portion of this research was performed using PNNL Institutional Computing resources. The ECHAM6-HAM model was developed by a consortium composed of ETH Zurich, Max Planck Institut für Meteorologie, Forschungszentrum Jülich, University of Oxford, the Finnish Meteorological Institute, and the Leibniz Institute for Tropospheric Research, and is managed by the Center for Climate Systems Modeling (C2SM) at ETH Zurich. D.N. acknowledges support by the Austrian Science Fund (J 3402-N29, Erwin Schrödinger Fellowship Abroad). C2SM at ETH Zurich is acknowledged for providing technical and scientific support. This work was also supported by a grant from the Swiss National Supercomputing Centre under Project ID s431. D.G.P. and P.S. acknowledge support from the United Kingdom (UK) Natural Environment Research Council Grant NE/I020148/1. P.S. and Z.K. acknowledge funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013) ERC project ACCLAIM (Grant Agreement FP7-280025). The development of modal version of the GLObal Model of Aerosol Processes (GLOMAP-mode) within Hadley Center Global Environmental Mode (HadGEM) is part of the United Kingdom Chemistry and Aerosols (UKCA) project, which is supported by both National Environmental Research Council (NERC) and the Joint Department of Energy & Climate Change/Department for Environment, Food & Rural Affairs Meteorology Office Hadley Centre Climate Programme. We acknowledge use of the Met Office and NERC MONSooN high performance computing system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the Met Office and the NERC. Simulations by SPRINTARS were executed with the supercomputer system SX-9/ACE of the National Institute for Environmental Studies, Japan. SPRINTARS is partly supported by the Environment Research and Technology Development Fund (S-12-3) of the Ministry of the Environment, Japan and Japan Society for the Promotion of Science KAKENHI Grants-in-Aid for Scientific Research 15H01728 and 15K12190. Computing resources for CAM5-MG2 simulations were provided by the Climate Simulation Laboratory at National Center for Atmospheric Research (NCAR) Computational and Information Systems Laboratory. NCAR is sponsored by the US National Science Foundation

On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models

This is the final version of the article. Available from EGU via the DOI in this record.Aerosol–cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (ω500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strong large-scale ascent (ω500   0.1 mm day−1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes compared to the uncertainty in its global mean values, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.M. Wang acknowledged the support from the Jiangsu Province Specially-appointed professorship grant and the One Thousand Young Talents Program and the National Natural Science Foundation of China (41575073). The contribution from Pacific Northwest National Laboratory was supported by the US Department of Energy (DOE), Office of Science, Decadal and Regional Climate Prediction using Earth System Models (EaSM program). H. Wang acknowledges support by the DOE Earth System Modeling program. The Pacific Northwest National Laboratory is operated for the DOE by Battelle Memorial Institute under contract DE-AC06-76RLO 1830. The ECHAM-HAMMOZ model is developed by a consortium composed of ETH Zurich, Max Planck Institut für Meteorologie, Forschungszentrum Jülich, University of Oxford, the Finnish Meteorological Institute and the Leibniz Institute for Tropospheric Research, and managed by the Center for Climate Systems Modeling (C2SM) at ETH Zurich. D. Neubauer gratefully acknowledges the support by the Austrian Science Fund (FWF): J 3402-N29 (Erwin Schrödinger Fellowship Abroad). The Center for Climate Systems Modeling (C2SM) at ETH Zurich is acknowledged for providing technical and scientific support. This work was supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID s431. D. G. Partridge would like to acknowledge support from the UK Natural Environment Research Council project ACID-PRUF (NE/I020148/1) as well as thanks to N. Bellouin for useful discussions during the course of this work. The development of GLOMAP-mode within HadGEM is part of the UKCA project, which is supported by both NERC and the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the Met Office and the Natural Environment Research Council. P. Stier would like to acknowledge support from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. FP7-280025

Sea-ice-free Arctic during the Last Interglacial supports fast future loss

The Last Interglacial (LIG), a warmer period 130-116 ka before present, is a potential analog for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4-5 °C higher than the preindustrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show the latest version of the fully-coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the longstanding puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice

Tropopause sharpening by data assimilation

Data assimilation was recently suggested to smooth out the sharp gradients that characterize the tropopause inversion layer (TIL) in systems that did not assimilate TIL-resolving observations. We investigate whether this effect is present in the ERA-Interim reanalysis and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational forecast system (which assimilate high-resolution observations) by analyzing the 4D-Var increments and how the TIL is represented in their data assimilation systems. For comparison, we also diagnose the TIL from high-resolution GPS radio occultation temperature profiles from the COSMIC satellite mission, degraded to the same vertical resolution as ERA-Interim and ECMWF operational analyses. Our results show that more recent reanalysis and forecast systems improve the representation of the TIL, updating the earlier hypothesis. However, the TIL in ERA-Interim and ECMWF operational analyses is still weaker and farther away from the tropopause than GPS radio occultation observations of the same vertical resolution