Priority Project "T2(RC)2"
Testing and Tuning of Revised Cloud Radiation Coupling

Last updated: 20 Feb 2020

Project leader: Harel Muskatel (IMS)

Project resources

Project duration:

September 2015 - March 2020

FTEs (plan/used):

2.60/2.51 in COSMO year 2015-2016
2.70/2.33 in COSMO year 2016-2017
2.30/2.39 in COSMO year 2017-2018
2.40/2.35 in COSMO year 2018-2019
1.15/1.19 in COSMO year 2019-2020

Total FTEs planned:


Total FTEs used:



PP CAIIR, Cloud-Optics application


1. Introduction 2. Motivation 3. Actions Proposed 4. Main deliverables 5. Risks 6. Participants 7. Documents 8. References


This project is following the PT Revised Cloud Radiation Coupling (RC)2 (see presentation). The main goal is to improve the current cloud-radiation-coupling. In this project we intend to test the (RC)2 results of the new optical properties of clouds. Also we will continue to explore the model sensitivities to several new tuning parameters and try to further reduce their number. The new radiation scheme will be tested under different weather conditions. The second goal of this project deals with other physical aspects of the radiation scheme: aerosols and Sub-Grid Scale (SGS) clouds. Currently, the radiation scheme uses climatology data as the base for aerosols concentration. We shall examine the possibility of integration of the ECMWF project- MACC (Monitoring Atmospheric Composition & Climate) prognostic aerosols fields to the COSMO radiation scheme. The SGS clouds parametrization scheme for radiation should also be reviewed and revised in light of the last years increase in resolution, the recent scientific progress in the field and in aid of a consistent overall description of clouds in the model.

The third goal is testing numerical aspects of the radiation code namely the temporal resolution optimization and the 'Monte-Carlo Spectral Integration' (MCSI) as suggested in the CSP. We also will evaluate the possibility of transforming the radiation code (at least parts of it) into single precision.

In addition, experimental datasets in clear/cloudy sky conditions using the complex data of Moscow State University Meteorological Observatorywill be used for testing both the radiation code (longwave and shortwave radiative components) and the application of two aerosol products; the MACC prognostic aerosol fields and a new aerosol climatology from Kinne et al. (2013). The results obtained with the above new cloud parameterization will be also verified against the experimental datasets. We also plan to apply accurate model simulations to verify the RT code used in COSMO. Testing the sensitivity of main prognostic meteorological characteristics to the changes in radiation fields and the assessment of the forecast quality to the changes made in radiation scheme with the different aerosol/cloud inputs will be also fulfilled.

In the second phase of the project we wish to implement the new cloud droplets and ice particles optical properties in the ICON RRTM scheme and testing it against observational data. Another sequel outcome for the implementation of prognostic aerosols in the radiation scheme is to couple the prognostic/new climatology aerosols content with cloud microphysics. Aerosols number concentration, aerosols type and size distribution can tremendously affect the clouds microphysics and dynamics. So far COSMO model aerosols number concentration input for the microphysics is taken to be a fixed number which is a tuning parameter. Of course this input is in many cases non-realistic. The Tanre climatology is known to have high aerosols overestimation and the Tegen climatology can be both under-estimated (i.e. dust events) or overestimated (i.e. due to wash out events). Instead of using a monthly climatological averages a more realistic input can be taken from CAMS which is initiated using a very complex data assimilation system and is driven with IFS model. Giving the model a realistic aerosols content can improve significantly COSMO forecast in general and especially improve the precipitation forecast. The second natural outcome from the CAMS implementation is using ICON-ART prognostic aerosols input. While COSMO-ART is not running on operational basis in all COSMO-users site, ICON-ART is running globally twice a day, as for now only the dust tracer, and it is possible to use it as an input to COSMO radiation scheme.


Radiation is the main source of earth's energy and is strongly coupled to other elements of NWP models especially the heating and cooling rates. On the other hand, precise line by line calculation of extinction of radiation in the atmosphere due to different scatterers and absorbers is computationally costly. Wise parametrizations of the cloud hydrometeors and aerosols optical properties and also a smart computational algorithm are key aspects of a fast and accurate operational radiation transfer model.

In the (RC)2 - Revised Cloud Radiation CouplingPriority Task, re-computation of optical properties (optical thickness, single scattering albedo, asymmetry factor and delta-transmission function) of different hydrometeors in clouds in the COSMO model has been done using state of the art spectroscopic data (Fu 2007). These parameters are input to the radiation scheme and determine the model behaviour to a certain extent. Also, the aerosols were treated by the newer climatology of Tegen (Tegen et al. 1997) instead of the older Tanre-climatology (Tanre et al. 1984), the latter giving mostly a too high optical thickness. The new scheme changes the systematic behaviour of the current one: the cloud optical thickness of different cloud types is changed, not only cloud drops and cloud ice are input to radiation calculations, but also snow, graupel and rain (snow is most important), and in cloud-free situations there is less aerosol extinction now. Although the use of Tegen climatology already improved the situation for cloud-free situations, it is still a climatology which can obviously cause large biases in the estimates of radiation currents on a daily basis. The use of prognostic operational fields of a forecast model for aerosols as an input to the radiation scheme has some potential to improve COSMO forecasts. However, we are aware of possible drawbacks for extreme cases (e.g., cold front passage), where the aerosol fields of the aerosol forecast model might not be in phase with the weather conditions in the COSMO forecast.

As far as related to radiation, cloudiness (cloud-water and cloud-fraction of a model-grid-box) is currently derived from 3 contributions in the COSMO-model: grid scale cloud-water (according to grid-scale saturation adjustment) and 2 SGS contributions. One of them (based on a diagnostic relative-humidity-closure) is applied to that part of the grid box being not covered by shallow and deep convective clouds, and the other (employing a constant in-cloud value) is applied to the convective cloud-fraction, where the latter is estimated by our Tiedtke-type parameterization schemes for convection. According to the CSP, the over-all estimate of cloudiness has to be reviewed since the current parametrization seems to be too simplistic and in some cases not realistic. It possibly compensates for systematic biases related to the old Tanre-climatology, the old cloud optical properties and the missing snow category in radiation. In order to gain more accuracy as well as consistency, the local-saturation-adjustment procedure of the turbulence scheme should be examined for calculating overall cloudiness of that grid-box-fraction being not covered by convective clouds. For full consistency in this respect, the so far grid-scale saturation adjustment should be substituted by the overall cloudiness estimate (as demanded in the CSP).

The computational changes suggested above have an obvious motivation. Using single precision can save significant CPU time as was shown in the POMPA PP. So far we have been careful with moving towards single precision in the radiation scheme due to accuracy reasons but the idea should be tested and considered. Here we can build on previous experiences of the POMPA project. Refining the temporal resolution could save computational costs in some cases and on the other hand define a better resolution in rapidly changed environments.

The MCSI method is also a possible way of reducing computational effort by a wise randomization of spectral interval calculations while preserving accuracy in a statistical sense.

Preliminary results (Polyukhov et al., 2015) show that even the Tegen aerosol climatology (1997) provide too high aerosol loading. At the same time the sensitivity studies revealed high impact of aerosol on temperature near surface. The new aerosol dataset proposed by Kinne et al (2013) is considered to better describe real aerosol loading (Mueller and Träger-Chatterjee, 2014). Verification of both the computationally cheap new Kinne et al. (2013) climatology as well as the prognostic MACC aerosol against the data of Moscow State University Meteorological Observatory is needed.

Actions proposed


Main deliverables

Task 1:
1. Final set of tuning parameters available.
2. Re-write the new radiation related portions of the code to be adapted to GPU architecture
3. Automatic parameter tuning performed, "best" settings available, probably different for different climatic zones
Task 2:
4. Testing and adaption of the alternative SGSC parameterization in the turbulence scheme
5. HUCM idealized 2D cases for the simpler stratiform cloud types mentioned above and analysis of their Reff under different aerosol conditions
6. 3D SAM simulations of the more convective cloud types mentioned above and analysis of R_eff
Task 3:
7. Adaptation of MACC aerosols fields into COSMO framework, usable in test versions of INT2LM and COSMO
8. Case studies, documentation of effects of MACC aerosols
Task 4:
9. Experiments for comparison of quality and efficiency of SP and DP radiation. Test code for single precision radiation available
10. Experiments evaluated and recommendations for official COSMO code
Task 5:
11. Experiments conducted and effects documented of temporal resolution of radiation scheme
12. Implementation MCSI method in test version of COSMO
13. Case studies and documentation of effects
Task 6:
14. The implementation of Kinne MAC-v1 aerosol climatology in the model
15. The results of intercomparisons of different aerosol COSMO simulations with the accurate experimental measurements in clear sky conditions
16. The results of intercomparisons of different aerosol COSMO simulations with the accurate off-line model simulations in clear sky conditions
17. The results of intercomparison of different aerosol COSMO simulations with the accurate experimental measurements in cloudy conditions
18. The assessment of the accuracy of implementation of new aerosol climatology to radiation fields and several meteorological parameters
19. The assessment of the deviations between the forecasted and observed meteorological parameters due to new cloud and different aerosol inputs
Task 7:
20. Implementation of Fu's ice particles optical properties in ICON-RRTM
21. Implementation of Hu and Stamnes water droplets optical properties in ICON-RRTM
22. Case studies and documentation of effects
Task 8:
23. Implementation of ICON-ART aerosols fields into INT2LM code
24. Implementation of ICON-ART aerosols fields into COSMO radiation scheme
25. Case studies and documentation of effects
Task 9:
26. Implementation of CAMS aerosols fields into COSMO cloud water droplets nucleation schemes
27. Implementation of CAMS aerosols fields into COSMO cloud ice nucleation schemes
28. Case studies and documentation of effects
Task 10:
29. Check Boeing parametrization components using SAM LES simulations with BOMEX setup, implementation of the new parametrization in COSMO CLC scheme
30. New shallow convection shutdown scheme development
31. SGS cloud cover schemes verifications against ground base and satellite observations including fish-eye camera verification and testing radiation response


  1. Allocation of computer resources for automatic tuning exercise at CSC.
  2. Other than that, the usual risks of scientific developments that planned developments and tasks do not work out as originally anticipated.


Harel Muskatel (IMS), Pavel Khain (IMS), Alon Shtivelman (IMS)
Ulrich Blahak (DWD), Matthias Raschendorfer (DWD), Martin Kohler (DWD), Daniel Rieger (DWD), Simon Gruber (KIT)
Oliver Fuhrer (MCH), Xavier Lapillonne (MCH)
Gdaly Rivin (RHM), Natalia Chubarova (RHM), Marina Shatunova (RHM), Alexey Poliukhov (RHM), Alexander Kirsanov (RHM)



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