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Johannes Mülmenstädt

Precipitation and ERF

Objective

The more precipitating warm clouds are simulated in a model, the more opportunity aerosols have to influence the parameterized liquid-phase precipitation microphysics. Therefore, the strength of the cloud-lifetime effect in models may be related to the warm-rain fraction. The aim of this intercomparison project is to test whether this link exists across AeroCom models.

If warm-rain fraction and cloud-lifetime effect are linked, it may be possible to use satellite observations of warm-rain fraction in the present-day climate to constrain the cloud-lifetime effect. In a preliminary study using ECHAM-HAM, we found that it is possible to tune the model warm-rain fraction to agree with the satellite climatology of Mülmenstädt et al. (2015); this retuning of the model reduces the ERF from −1.1 W m−2 to −0.9 W m−2. (More details on this study, and a preliminary comparison between the satellite-derived warm-rain fraction and other models', can be found in the AGU 2016 Fall Meeting/AMS 2017 Annual Meeting slides.)

References

Mülmenstädt et al. (2015) satellite warm-rain climatology
AGU/AMS presentation on warm rain as an ERF constraint in ECHAM-HAM

Simulation setup and required model diagnostics

The intention of this section is to require as little extra work as possible on top of the AeroCom indirect forcing experiment.

If using the same model configuration as for the AeroCom indirect experiment

Please repeat the all_2000 simulation and save one of the following sets of diagnostics:

  1. 3D snow and rain mixing ratios
  2. 3D snow and rain fluxes
  3. 2D snow and rain water paths

As in the indirect experiment 2D output, the required time frequency is 3-hourly non-accumulated. If this is not feasible for the requested 3D fields, it is possible to implement the warm-rain fraction as an online diagnostic in the model; please contact me for details.

If using a different model configuration than for the AeroCom indirect experiment

To minimize the amount of work you have to do, and to make the results of this study easier to correlate with other AeroCom results, I would strongly prefer that you use the same model configuration (including model version) as for the AeroCom indirect experiment. If this is not possible, please perform runs as close as possible to the indirect experiment all_2000 and all_1850 setup.

Please try to provide the 3 h instantaneous diagnostics listed in table (1) of the "Diagnostics" section of the indirect experiment description. If it is not possible to provide all, please provide at least

In addition, please provide one of the following three sets of diagnostics:

  1. 3D snow and rain mixing ratios
  2. 3D snow and rain fluxes
  3. 2D snow and rain water paths

Models participating so far

CAM5 (Contact: Shipeng Zhang, Minghuai Wang)
MIROC-SPRINTARS (Contact: Takuro Michibata, Toshi Takemura)
IFS (Contact: Amund Søvde, Gunnar Myhre)
ECHAM-HAM (Contact: Johannes Mülmenstädt)

Contact

Johannes Mülmenstädt: johannes.muelmenstaedt@uni-leipzig.de

Data deadline

Please provide data by June 2017 so that preliminary results will be ready in time for the AeroCom meeting (October 9, 2017).


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