Quantitative performance metrics for stratospheric-resolving chemistry-climate models

International audienceA set of performance metrics is applied to stratospheric-resolving chemistry-climate models (CCMs) to quantify their ability to reproduce key processes relevant for stratospheric ozone. The same metrics are used to assign a quantitative measure of performance ("grade") to each model-observations comparison shown in Eyring et al. (2006). A wide range of grades is obtained, both for different diagnostics applied to a single model and for the same diagnostic applied to different models, highlighting the wide range in ability of the CCMs to simulate key processes in the stratosphere. No model scores high or low on all tests, but differences in the performance of models can be seen, especially for transport processes where several models get low grades on multiple tests. The grades are used to assign relative weights to the CCM projections of 21st century total ozone. However, only small differences are found between weighted and unweighted multi-model mean total ozone projections. This study raises several issues with the grading and weighting of CCMs that need further examination, but it does provide a framework that will enable quantification of model improvements and assignment of relative weights to the model projections

Climatologies of streamer events derived from a transport model and a coupled chemistry-climate model

International audienceStreamers, i.e. finger-like structures, reach from lower into extra-tropical latitudes. They can be detected in N2O or O3 distributions on single lower stratospheric layers in mid-latitudes since they are characterised by high N2O or low O3 values compared to undisturbed mid-latitude values. If irreversible mixing occurs, streamer events significantly contribute to the transfer of tropical air masses to mid-latitudes which is also an exchange of upper tropospheric and stratospheric air. A climatology of streamer events has been established, employing the chemical-transport model KASIMA, which is driven by ECMWF re-analyses (ERA) and operational analyses. For the first time, the seasonal and the geographical distribution of streamer frequencies has been determined on the basis of 9 years of observations. For the current investigation, a meridional gradient criterion has been newly formulated and applied to the N2O distributions calculated with KASIMA. The climatology has been derived by counting all streamer events between 21 and 25 km for the years 1990 to 1998. It has been further used for the validation of a streamer climatology which has been established in the same way employing data of a multi-year simulation with the coupled chemistry-climate model ECHAM4.L39(DLR)/CHEM (E39/C). It turned out that both climatologies are qualitatively in fair agreement, in particular in the northern hemisphere, where much higher streamer frequencies are found in winter than in summer. In the southern hemisphere, KASIMA analyses indicate strongest streamer activity in September. E39/C streamer frequencies clearly offers an offset from June to October, pointing to model deficiencies with respect to tropospheric dynamics. KASIMA and E39/C results fairly agree from November to May. Some of the findings give strong indications that the streamer events found in the altitude region between 21 and 25 km are mainly forced from the troposphere and are not directly related to the dynamics of the stratosphere, in particular not to the dynamics of the polar vortex. Sensitivity simulations with E39/C, which represent recent and possible future atmospheric conditions, have been employed to answer the question how climate change would alter streamer frequencies. It is shown that the seasonal cycle does not change but that significant changes occur in months of minimum and maximum streamer frequencies. This could have an impact on mid-latitude distribution of chemical tracers and compounds. The influence of streamers on the mid-latitude ozone budget has been assessed by applying a special E39/C model configuration. The streamer transport of low ozone is simply inhibited by filling up its ozone content according to the surrounding air masses. It shows that the importance of streamers for the ozone budget strongly decreases with altitude. At 15 km streamers lead to a decrease of ozone by 80%, whereas around 25 km it is only 1 to 5% and at mid-latitude tropopause, ozone decreases by 30% (summer) to 50% (winter)

Global distribution of ship tracks from one year of AATSRdata

The perturbation of a cloud layer by ship-generated aerosol changes the cloud reflectivity and is identified by elongated structures in satellite images, known as ship tracks. As ship tracks indicate a pollution of the clean marine environment and also affect the radiation budget below and above the cloud, it is important to investigate their radiative and climate impact. In this study we use satellite data to examine the effects of ship tracks on a particular scene as well as on the global scale. The cloud optical and microphysical properties are derived using a semi-analytical retrieval technique combined with a look-up-table approach. Within the ship tracks a significant change in the droplet number concentration, the effective radius and the optical thickness are found compared to the unaffected cloud. The resulting cloud properties are used to calculate the radiation budget below and above the cloud. Local impacts are shown for a selected scene from MODIS on Terra. The mean reflectance at top of atmosphere (TOA) is increased by 40.8 Wm-2. For a particular scene chosen close to the West Coast of North America on 10th February 2003, ship emissions increase the backscattered solar radiation at TOA by 2.0Wm-2, corresponding to a negative radiative forcing (RF). A global distribution of ship tracks derived from one year of AATSR data shows high spatial and temporal variability with highest occurrence of ship tracks westward of North America and the southwest coast of Africa, but small RF on the global scale

Emergent constraints on climate-carbon cycle feedbacks in the CMIP5 Earth system models

Journal ArticleAn emergent linear relationship between the long-term sensitivity of tropical land carbon storage to climate warming (γLT) and the short-term sensitivity of atmospheric carbon dioxide (CO2) to interannual temperature variability (γIAV) has previously been identified by Cox et al. (2013) across an ensemble of Earth system models (ESMs) participating in the Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP). Here we examine whether such a constraint also holds for a new set of eight ESMs participating in Phase 5 of the Coupled Model Intercomparison Project. A wide spread in tropical land carbon storage is found for the quadrupling of atmospheric CO2, which is of the order of 252 ± 112 GtC when carbon-climate feedbacks are enabled. Correspondingly, the spread in γLT is wide (-49 ± 40 GtC/K) and thus remains one of the key uncertainties in climate projections. A tight correlation is found between the long-term sensitivity of tropical land carbon and the short-term sensitivity of atmospheric CO2 (γLT versus γIAV), which enables the projections to be constrained with observations. The observed short-term sensitivity of CO2 (-4.4 ± 0.9 GtC/yr/K) sharpens the range of γLT to -44 ± 14 GtC/K, which overlaps with the probability density function derived from the C4MIP models (-53 ± 17 GtC/K) by Cox et al. (2013), even though the lines relating γLT and γIAV differ in the two cases. Emergent constraints of this type provide a means to focus ESM evaluation against observations on the metrics most relevant to projections of future climate change. Key Points Tropical land carbon loss is a key uncertainty in climate change projections CO2 interannual variability is linearly related to tropical carbon loss in CMIP5 Observed variability in CO2 constrains projections of future carbon losses ©2014. American Geophysical Union. All Rights Reserved.European Commission's Seventh Framework Programme, EMBRACE and ESMVa

Impact of high solar zenith angles on dynamical and chemical processes in a coupled chemistry-climate model

International audienceActinic fluxes at high solar zenith angles (SZAs) are important for atmospheric chemistry, especially under twilight conditions in polar winter and spring. The results of a sensitivity experiment employing the fully coupled 3D chemistry-climate model ECHAM4.L39(DLR)/CHEM have been analysed to quantify the impact of SZAs greater than 87.5° on dynamical and chemical processes in the lower stratosphere, in particular their influence on the ozone layer. Although the actinic fluxes at SZAs larger than 87.5° are small, ozone concentrations are significantly affected because daytime photolytic ozone destruction is switched on earlier, especially the conversion of Cl2 and Cl2O2 into ClO at the end of polar night in the lower stratosphere. Comparing climatological mean ozone column values of a simulation considering SZAs up to 93° with those of the sensitivity run with SZAs confined to 87.5° total ozone is reduced by about 20% in the polar Southern Hemisphere, i.e., the ozone hole is "deeper'' if twilight conditions are considered in the model because there is 2?3 weeks more time for ozone destruction. This causes an additional cooling of the polar lower stratosphere (50 hPa) up to ?4 K with obvious consequences for chemical processes. In the Northern Hemisphere the impact of high SZAs cannot be determined on the basis of climatological mean values due to the pronounced dynamic variability of the stratosphere in winter and spring

Global model simulations of the impact of ocean-going ships on aerosols, clouds, and the radiation budget

International shipping contributes significantly to the fuel consumption of all transport related activities. Specific emissions of pollutants such as sulfur dioxide (SO<sub>2</sub>) per kg of fuel emitted are higher than for road transport or aviation. Besides gaseous pollutants, ships also emit various types of particulate matter. The aerosol impacts the Earth's radiation budget directly by scattering and absorbing the solar and thermal radiation and indirectly by changing cloud properties. Here we use ECHAM5/MESSy1-MADE, a global climate model with detailed aerosol and cloud microphysics to study the climate impacts of international shipping. The simulations show that emissions from ships significantly increase the cloud droplet number concentration of low marine water clouds by up to 5% to 30% depending on the ship emission inventory and the geographic region. Whereas the cloud liquid water content remains nearly unchanged in these simulations, effective radii of cloud droplets decrease, leading to cloud optical thickness increase of up to 5–10%. The sensitivity of the results is estimated by using three different emission inventories for present-day conditions. The sensitivity analysis reveals that shipping contributes to 2.3% to 3.6% of the total sulfate burden and 0.4% to 1.4% to the total black carbon burden in the year 2000 on the global mean. In addition to changes in aerosol chemical composition, shipping increases the aerosol number concentration, e.g. up to 25% in the size range of the accumulation mode (typically >0.1 μm) over the Atlantic. The total aerosol optical thickness over the Indian Ocean, the Gulf of Mexico and the Northeastern Pacific increases by up to 8–10% depending on the emission inventory. Changes in aerosol optical thickness caused by shipping induced modification of aerosol particle number concentration and chemical composition lead to a change in the shortwave radiation budget at the top of the atmosphere (ToA) under clear-sky condition of about −0.014 W/m² to −0.038 W/m² for a global annual average. The corresponding all-sky direct aerosol forcing ranges between −0.011 W/m² and −0.013 W/m². The indirect aerosol effect of ships on climate is found to be far larger than previously estimated. An indirect radiative effect of −0.19 W/m² to −0.60 W/m² (a change in the atmospheric shortwave radiative flux at ToA) is calculated here, contributing 17% to 39% of the total indirect effect of anthropogenic aerosols. This contribution is high because ship emissions are released in regions with frequent low marine clouds in an otherwise clean environment. In addition, the potential impact of particulate matter on the radiation budget is larger over the dark ocean surface than over polluted regions over land

On the equation of state of a dense columnar liquid crystal

An accurate description of a columnar liquid crystal of hard disks at high packing fractions is presented using an improved free-volume theory. It is shown that the orientational entropy of the disks in the one-dimensional fluid direction leads to a different high-density scaling pressure compared to the prediction from traditional cell theory. Excellent quantitative agreement is found with recent Monte-Carlo simulation results for various thermodynamic and structural properties of the columnar state.Comment: 4 pages, 2 figures, to appear in Phys. Rev. Let

Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology

We present the new Cloud Class Climatology (CCClim) dataset, quantifying the global distribution of established morphological cloud types over 35 years. CCClim combines active and passive sensor data with machine learning (ML) and provides a new opportunity for improving the understanding of clouds and their related processes. CCClim is based on cloud property retrievals from the European Space Agency's (ESA) Cloud_cci dataset, adding relative occurrences of eight major cloud types, designed to be similar to those defined by the World Meteorological Organization (WMO) at 1° resolution. The ML framework used to obtain the cloud types is trained on data from multiple satellites in the afternoon constellation (A-Train). Using multiple spaceborne sensors reduces the impact of single-sensor problems like the difficulty of passive sensors to detect thin cirrus or the small footprint of active sensors. We leverage this to generate sufficient labeled data to train supervised ML models. CCClim's global coverage being almost gapless from 1982 to 2016 allows for performing process-oriented analyses of clouds on a climatological timescale. Similarly, the moderate spatial and temporal resolutions make it a lightweight dataset while enabling straightforward comparison to climate models. CCClim creates multiple opportunities to study clouds, of which we sketch out a few examples. Along with the cloud-type frequencies, CCClim contains the cloud properties used as inputs to the ML framework, such that all cloud types can be associated with relevant physical quantities. CCClim can also be combined with other datasets such as reanalysis data to assess the dynamical regime favoring the occurrence of a specific cloud type in association with its properties. Additionally, we show an example of how to evaluate a global climate model by comparing CCClim with cloud types obtained by applying the same ML method used to create CCClim to output from the icosahedral nonhydrostatic atmosphere model (ICON-A). CCClim can be accessed via the following digital object identifier: https://doi.org/10.5281/zenodo.8369202 (Kaps et al., 2023b).</p

Machine-learned cloud classes from satellite data for process-oriented climate model evaluation

Clouds play a key role in regulating climate change but are difficult to simulate within Earth system models (ESMs). Improving the representation of clouds is one of the key tasks towards more robust climate change projections. This study introduces a new machine-learning based framework relying on satellite observations to improve understanding of the representation of clouds and their relevant processes in climate models. The proposed method is capable of assigning distributions of established cloud types to coarse data. It facilitates a more objective evaluation of clouds in ESMs and improves the consistency of cloud process analysis. The method is built on satellite data from the MODIS instrument labelled by deep neural networks with cloud types defined by the World Meteorological Organization (WMO), using cloud type labels from CloudSat as ground truth. The method is applicable to datasets with information about physical cloud variables comparable to MODIS satellite data and at sufficiently high temporal resolution. We apply the method to alternative satellite data from the Cloud\_cci project (ESA Climate Change Initiative), coarse-grained to typical resolutions of climate models. The resulting cloud type distributions are physically consistent and the horizontal resolutions typical of ESMs are sufficient to apply our method. We recommend outputting crucial variables required by our method for future ESM data evaluation. This will enable the use of labelled satellite data for a more systematic evaluation of clouds in climate models.Comment: Main Paper 16 pages, 11 figures. Supporting material 7 Pages, 8 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl