Project S3 aims at an improved process understanding and characterization of the impact of convection on upper tropospheric cloudiness and its change in a warming climate, contributing to discussions on the decrease in upper tropospheric cloudiness and an increase in anvil top height with climate change (FAT hypothesis).
Microphysical and macrophysical cloud parameterizations will be improved, selected convective events explored, and the vertical structure and temporal evolution of the anvil and stratiform outflow and their dependence on the background temperature in observations and in ICON simulations will be examined. Another goal is to better understand and quantify the formation and lifecycle of anvils and mid-level stratiform clouds generated by deep convection. Their impact on the water budget in the upper troposphere is studied and their representation within models improved. Moreover, the macrophysical, microphysical and optical properties of convectively generated ice clouds and their dependence on background temperatures in observations and model will be studied.
Workpackage 1 focuses on the formation, evolution and growth of ice particles in deep convective clouds and the formation of convectively-generated cirrus (anvils) and convectively-generated mid-level stratiform clouds (stratiform region of convective systems). The questions addressed in this work package are:
In order to answer these questions, a particle-based microphysics model will be developed that can run within the ICON_LEM framework. A Monte-Carlo approach will explicitly sample the multidimensional phase space spanned by the microphysical properties of ice, snow and graupel. It will allow to show what trajectories and pathways individual snowflakes and graupel particles take in a thunderstorm. It then can be explicitly shown how these particles grow, what makes one snowflake different from another and explain why some end up in the anvil, some in mid-levels, and why some reach the ground as precipitation. Those simulations will use very advanced simulation techniques to follow billions of particles in a cloud at a single run.
Work package 2 targets cirrus outflow of Warm Conveyor Belts (WCB). A WCB is a moist airstream ascending polewards in the vicinity of an extratropical cyclone from the boundary layer to the upper troposphere within two days. WCBs are very frequent over the north atlantic and their major outflow region with associated cirrus clouds lies over western Europe.
Different ice forming mechanisms may contribute to the WCB outflow cirrus. Often convection with high updrafts is embedded in WCBs and ice may form via the freezing of supercooled droplets. On the other hand regions aloft the WCB experience moderate lifting and in situ formation due to homogeneous freezing of solution droplets is favoured. Finally dust particles are transported from the boundary layer to the upper troposhere, where they may act as ice nuclei for heterogeneous freezing.
The goals of the work package are to answer the following questions:
The questions are adressed with ICON simulations in different resolutions. WCBs are identified by trajectory calculations and a two-moment, two-mode microphysical scheme will be employed.
Work packages 3 and 4 focus on the how the precipitation generation in convection impacts the resulting outflow of cloud. The goal will be an improvement of the parameterisation of convection and it's outflow in ICON-NWP and ICON-GCM.
To do that the starting point will be an evaluating of ice cloud cover and ice water content in the ICON-LEM, ICON-NWP and ICON-GCM using observations and forward operators from the first phase of HD(CP)². This will require the analysis of ICON-LEM over Germany and the simulation of ICON at NWP and GCM resolutions (10km-100km).
Work package 5 will study the impact of convection on the water budget and variability in the upper troposphere, anvil top temperatures, ice supersaturation and the macro-scale distribution (e.g. cover and ice water) of ice clouds and their temporal evolution in ICON-GCM. It will study those processes within the ICON-LEM simulations for specific case studies of convective situations. It strives to improve the representation of the interaction between the ice cloud and convection parameterizations within the lower resolution ICON model learning from the ICON-LEM simulations and observations. A challenge is coupling convection and large scale clouds in the occurrence of bimodal distributions of total water as have been observed in MOZAIC data. Therefore the form of the distribution of the small to mesoscale variability of total water will be studied and it is tried to estimate the implications for the coupling of convection and large scale cloud schemes.
The following questions regarding the convective transport and the evolution of the anvil will be answered:
In workpackage 6 we will apply a combined on-line feature tracking and trajectory tool to study the life cycle of convective systems, the characteristics of convection and the outflow of convective systems in the extra-tropics and tropics. Trajectories will be started during the simulation in convective regions defined by the on-line feature identification. From these trajectories we will extract statistical distributions of mass fluxes, freezing levels, microphysical conversion rates, detrainment, and anvil top heights and temperature within the convective systems from model simulations. Using these characteristics, we will assess the accuracy of our expectations of anvil cirrus changes due to climate change.The Lagrangian viewpoint will provide more insight in the development of convective cells and will enable a more process-oriented validation of the model system.
On-line trajectories are especially useful when studying atmospheric processes with short time scales and small spatial extend, e.g., in convective cells. We will extend the on-line Lagrangian tool to include properties of trace gases (water) in small air parcels and their changes during the movement along trajectories. This is a prerequisite to investigate moisture transport in deep convection. Combined with on-line feature identification, we will be able to analyse moisture distribution along trajectories, which are started in convective regions identified during the simulation. This combination allows to complement the analysis of the dynamics of large-scale structures (e.g., tracked motion of individual cloud objects) by computation of local quantities and their changes along trajectories (e.g., trace gases entering and leaving those objects during their evolution, moisture transport inside convective cells, etc.).
Work package 7 will provide and analyze observations from passive satellite sensors to assess the fidelity of the modeled macro- and microphysics of cloud ice fields. To achieve this goal, two complementary avenues will be followed. By use of forward operators, the first approach will simulate microwave brightness temperatures from model quantities and then directly compare them with raw satellite observations. Specifically, the sophisticated but computationally expensive ARTS (Atmospheric Radiative Transfer Simulator) package will be used to develop a simplified yet accurate forward operator that is fast enough for calculations at the high spatial resolution of ICON. Special emphasis will be put on mapping the model's two-moment microphysics scheme into ARTS as consistently as possible. This task will include computing ice cloud optical properties for realistic distributions of particle shape and orientation informed by in-situ measurements.
The second approach will utilize the high-level cloud ice water path (IWP) product from the SPARE-ICE algorithm. The method detects clouds and retrieves IWP by a pair of artificial neural networks, trained on collocations between AVHRR infrared and MHS microwave radiances and the CloudSat/CALIPSO combined radar-lidar 2C-ICE product. SPARE-ICE offers IWP data of comparable quality to active sensors that is distributed over a wide swath rather than a narrow transect. In addition to model evaluation, SPARE-ICE will also participate in IWP cross-validation studies with the SEVIRI-based CiPS algorithm and ground-based RAMSES lidar retrievals.
Workpackage 8 provides observational data on the questions of microphysical parametrization of convection. It provides quality assured cloud microphysical remote measurement products in order to verify model simulations and satellite retrieval products. Data origin from the Richard Aßmann Observatory in Lindenberg, which offers a unique suite of remote measurement instruments, most notably, the cloud radar MIRA and the water Raman Lidar RAMSES. The combination of a polarization Doppler radar and a water Raman Lidar is an unique approach. Moreover, RAMSES is the only instrument worldwide with IWC measurement capability.
The ensemble approach (MIRA and RAMSES) and data from the Cloudnet data base will be used to verify various ICON_LEM forecasts of cloud fraction (CF), liquid and ice water content (LWC and IWC), cloud top temperature and radar reflectivity on long time scales. This approach will be supplemented by detailed case studies to evaluate the ice-microphysical scheme of ICON_LEM, especially the cloud ice sedimentation.
Moreover, it is planned to validate satellite retrieval products within this work package. Cloud fraction, IWC, IWP and cloud top temperature (derived from geostationary and polar-orbiting satellites) will be compared to Lindenberg Cloudnet profiles for suitable cases. Besides, the retrieval accuracy of the IWC Cloudnet product will be estimated by comparison of IWC measurements with RAMSES data.
Four main tasks are defined for work package 8: Anvil properties will be statistically evaluated, the ice-microphysical scheme will be evaluated, satellite retrieval products will be validated and the retrieval accuracy of the IWC Cloudnet product will be determined. The first step is to compare the data of cloud radars of different stations to analyze the accuracy of the instruments. In a second step, these data sets will be compared to the satellite data and the RAMSES data to find the results for the four tasks. Hence, different microphysical properties of anvil clouds (Cloud Fraction, Liquid Water Content, Ice Water Content, Cloud Top Temperature) will be analyzed. Different sources (measurement by MIRA, RAMSES, model data and satellite data) will give information about the accuracy of the data sets and will be the base of the statistical analysis.
Work package 9 will provide observations from active satellite sensors that will be useful to the evaluation of convective ice clouds within S3. More particularly, the HD(CP)² database will be extended with the CALIOP backscatter coefficient and the CloudSat reflectivity factor. Combined lidar-radar retrievals of the ice water content from the DARDAR operational products will also be provided, as well as a newly developed estimate of the ice crystal number concentration from satellite. This data will be provided for the German (DE), Tropical Atlantic (TA) and North Atlantic (NA) domains in order to cover the entirety of ICON-LEM simulations.
Moreover, in order to facilitate consistent comparisons between ICON-LEM, ICON-GCM and the aforementioned observations, work package 9 will add additional output capabilities to the online Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP) satellite simulator diagnostics. More particularly, we will work with the workflow module (M-WP4) to post-process the output for full compatibility with the active satellite observational data.
Finally, work package 9 intends to actively participate to the evaluation efforts of convective ice clouds based on the new simulations from ICON-LEM. The ice model diagnostics (water content and number concentration) will thoroughly be compared to satellite observations in order to evaluate the ice microphysical scheme.
Work package 1
Work package 2
Work package 3/4
Work Package 5
Work package 6
Work package 7
Work package 8
Work package 9