EGU2020-4939, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-4939
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

A comprehensive estimate of the global cooling effect from hindering homogeneous ice nucleation under cirrus conditions with CAM5

Jiaojiao Liu and Xiangjun Shi
Jiaojiao Liu and Xiangjun Shi
  • Nanjing University of Information Science &Technology, Nanjing, China (shixj@nuist.edu.cn)

The warming effect of cirrus clouds is well-known. In recent years, in order to mitigate global warming, cirrus cloud thinning as a newly emerging method of geoengineering has been studied based on climate modeling. Adding a few (~10 L–1) INPs (ice nucleating particles including ice crystals) might hinder homogeneous ice nucleation, which can produce a large number of ice crystals (~1000 L–1), and then reduce cirrus clouds. On the other hand, the cirrus clouds might increase if too much INPs were added. Therefore, the effectiveness of cirrus seeding on cooling our earth is still in debate. In this study, we developed a method (optimal seeding scheme) to calculate the minimum concentration of seeding INPs, which is just enough to prevent homogeneous nucleation from happening. Simulation with the Community Atmosphere Model version 5(CAM5) using the optimal seeding scheme shows a significant cooling effect (–1.4 W/m2), which is equal to two-thirds of the cooling potential (–2.1 W/m2) derived from the pure heterogeneous simulation (i.e., homogeneous ice nucleation is artificially switched off). Seeding fixed 20 L-1 and 200 L-1 concentrations of INPs show the global average radiative effect at –0.5 W m-2 (cooling) and 0.1 W m-2 (warming), respectively. The cooling effect of seeding fixed number concentration of INPs is not obvious, which is consistent with previous studies. Furthermore, using the optimal seeding scheme, the sensitivities of cooling effects to seeding area, ice nucleation parameterizations and homogeneous ice nucleation occurrence frequency are also investigated.

How to cite: Liu, J. and Shi, X.: A comprehensive estimate of the global cooling effect from hindering homogeneous ice nucleation under cirrus conditions with CAM5, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4939, https://doi.org/10.5194/egusphere-egu2020-4939, 2020

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Presentation version 2 – uploaded on 27 Apr 2020
Updating table that review of cirrus seeding
  • CC1: cirrus cloud radiative effects, Blaž Gasparini, 01 May 2020

    Dear Jiaojiao,

    it is nice to see some more work on cirrus cloud seeding!

    I have a suggestion for you - 
    the radiative impact of cirrus seeding depends on two factors:
    1.) the way you engineer seeding, which is what you optimized based on your slides
    2.) the background (unperturbed) cirrus cloud radiative effects (cirrus CRE). Cirrus CRE are larger in general larger in CAM5 compared to ECHAM-HAM model, as you can see in Fig. 1a) of my new paper - https://iopscience.iop.org/article/10.1088/1748-9326/ab71a3 . As an example, if the seeding effectiveness in reducing the cirrus CRE is 20%, this will lead to 1 W/m2 impact in the case of a cirrus CRE of 5 W/m2 and 2 W/m2 in the case of the cirrus CRE of 10 W/m2. 
    It would be therefore highly informative, if you tried to estimate such cirrus only CRE from your model version. You can easily do that by slightly adjusting the double calls to radiation. 

    Also - you can probably avoid allowing more downward solar radiation by seeding at night only. 

    ps. Which cirrus cloud microphysical scheme do you use in your work?

    Best regards,

    Blaž

    • AC1: Reply to CC1, Jiaojiao Liu, 02 May 2020

      Dear Blaž,

      Thank you so much for your interest and suggestions.
      1.) In our work, the cirrus CRE is 6.5 W/m2, the cirrus CRE anomalies are -3.4 and -3.0 W/m2 in HET and OPT (i.e., two seeding methods) respectively. As shown in your paper Fig. 1(e) and (f), we estimate the seeding effectiveness of our new seeding method, the globally averaged values of 57% and 51% in HET and OPT simulations, shown in the following. 
      2.) We use the modified CAM version 5.3, as compared to the default cirrus scheme in CAM5, the impact of pre-existing ice crystals and vertical velocity fluctuations on ice nucleation were considered (Shi et al.,2015 and 2016). The occurrence frequency of homogeneous ice nucleation with the modified cirrus cloud scheme (<10%) is obviously lower than that from the default scheme(>20%).
      3.) The default ice nucleation parameterization of Liu and Penner's (2005) was used in this study. We also conduct sensitivity simulations by using Barahona and Nenes (2009) and Kärcher et al. (2006) ice nucleation parameterizations (not shown). There are modest differences (<0.2 W/m2) in the seeding effectiveness among different parameterizations

      Best wishes,

      Jiaojiao

      Shi X., et al. (2015), Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5). Atmospheric Chemistry and Physics, 15(3):1503-1520.
      Shi, X., et al. (2016), Effect of cloud-scale vertical velocity on the contribution of homogeneous nucleation to cirrus formation and radiative forcing, Geophysical Research Letter, 43:6588-6595

    • AC2: Reply to CC1, Jiaojiao Liu, 02 May 2020

      I am sorry there is something wrong in the figure caption, I have modified it, shown as follows.

  • CC2: Comment on EGU2020-4939, Blaž Gasparini, 05 May 2020

    Great, thanks for showing that!

    Once you are publishing that even a separate set of plots showing LW only and SW only CRE and effectiveness may be interesting to see  (haven't done that on my own due to figure/text limitations)

    Best,

    Blaž

Presentation version 1 – uploaded on 26 Apr 2020 , no comments