the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report: Influence of long-range transported dust on cirrus cloud formation over remote ocean: Case studies near Midway Island, Pacific
Huijia Shen
Zhenping Yin
Longlong Wang
Yifan Zhan
Dongzhe Jing
Abstract. Cirrus clouds play an essential role in regulating the global radiative balance and climate by both reflecting the incoming shortwave solar radiation and reserving the outgoing longwave radiation in the atmosphere. The cirrus-induced net radiative forcing is mainly determined by their microphysical properties, which are strongly associated with the competition between two ice-nucleating mechanisms, i.e., heterogeneous and homogeneous nucleation. However, it is still not well understood whether the long-range transoceanic dust can potentially urge heterogeneous nucleation to the initial ice formation in cirrus clouds even farther over vast remote ocean regions and the response of dominant ice-nucleating mechanism to the concentrations of available ice nucleating particles (INPs). Here we report on the influence of transpacific dust plumes on the ice formation in cirrus clouds via heterogeneous nucleation based on the combined observations of space-borne instruments, i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). Two cases near Midway Island (28.21° N, 177.38° W), located in the central Pacific, are studied, in which the long-range transported dust plumes originate from intense Asian dust events. For both cases, partial cloud parcels show the typical in-cloud ice crystal number concentrations (ICNC) of <100 L-1 for heterogeneous nucleation with a good agreement (within an order of magnitude) of in-cloud ICNC and nearby dust-related INP concentration (INPC) values, indicating that dust-related heterogeneous nucleation is dominated in ice formation. In addition, for the other parts of clouds without sufficient INP supply, homogeneous nucleation can still be dominated with ICNC values exceeding 300 L-1. Therefore, dust events with sufficient intensity are capable of conducting long-range transport and influencing cirrus formation over remote ocean regions. This study shows that the natural supply of effective INPs to the upper troposphere, such as long-range transported dust aerosols can increase the cloud cover to reflect more solar radiation over oceanic regions and modulate the microphysical properties of cirrus clouds through different ice-nucleating regimes, both of which may further result in a cooling effect on global climate and should be well considered in climate evaluation.
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Huijia Shen et al.
Status: open (until 18 Oct 2023)
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RC1: 'Comment on egusphere-2023-1844', Anonymous Referee #1, 03 Oct 2023
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General Comments:
This is an interesting study that relates mineral dust plumes from Asian deserts to the number concentration of ice particles in cirrus clouds over Midway Island in the Central Pacific. It does this strictly through satellite remote sensing, using retrieval methods for mineral dust concentration (i.e., ice nucleating particle concentration or INPC) and ice particle number concentration (ICNC). It is well written and organized, but some of the arguments do not appear to be supported by the data, and the results may be overinterpreted. Specifics are given below. I recommend major revisions in rewriting the article, but this may not require a great deal of additional work.
Specific Comments:
1. Figure 4: The high column dust density measurements shown here in the back-trajectory do not ensure that air overlying these Asian deserts at ~ 10 km is having a relatively high concentration of mineral dust, since the column dust magnitude could result almost entirely from dust much below 10 km. This needs to be stated. On the other hand, it is commendable that the authors did this analysis since, although incomplete, it may be using all the available data and does provide important information.
2. Figure 5: There appears to be a problem with color legend. The plotting background is violet, which corresponds to an ice water content of 10-20 mg/m3. Not possible. The same problem occurs with Fig. 9c.
3. Lines 234-235: For what purpose are ICNCs shown for n_ice,25um and n_ice,100um? They provide no closure information with respect to dust INP concentration since most of the ICNC can be associated with D < 25 um (Kramer et al., 2009, ACP). Only n_ice,5um is relevant to the closure being sought with INPC.
4. Lines 236-237: Suggest citing Diao et al. (2015, JGR) to back up this statement.
5. Lines 252-253: Figure 6e shows agreement between ICNC and INPC only near cloud top for Si = 1.15, where ICNC is for n_ice,5um. From the previous page, it states that the layer average INPC is 7 L-1 and 96 L-1 for Si of 1.15 and 1.25, respectively. Since the layer average ICNC is 111 L-1 for Part B, optimal agreement is for Si = 1.25, with ICNC-to-INPC ratio of 1.16. Therefore, Si here should be 1.25, not 1.15.
6. Line 253: It is not clear how the ICNC-to-INPC ratio can be 0.9 for Si = 1.15, based on the previous text. As noted above, this ratio appears to be 1.16 for Si = 1.25, for which closure is optimal.
7. Lines 317-320: Since a large portion of the ICNC resides at D < 25 μm, n_ice,5um should be used rather than n_ice,25um (as assumed in this study). This practice (of using n_ice,5um) was followed for the other May 5th case study. In Fig. 10e, Si = 1.25 agrees best with n_ice,5um, consistent with the previous case study based on Comment 5 above.
8. Lines 308-312: If Si = 1.25 in the 2nd case study as indicated above, then the cirrus cloud of Part A could be produced only by heterogeneous ice nucleation since n_ice,5um = 635 L-1 and the mean dust-related INPC (U17-D) is 417 L-1. This is contrary to what the article states here; that Part A is dominated by homogeneous ice nucleation.
9. Lines 350-352: Alternatively, could this also be explained by variability in cloud updraft velocities?
10. Table 2: As mentioned earlier, for what purpose are ICNCs shown for n_ice,25um and n_ice,100um? They provide no closure information regarding dust INPC.
11. Lines 375-377: RHi (relative humidity with respect to ice) rarely reaches 140-150% in cirrus clouds since het (heterogeneous ice nucleation) always occurs before hom (homogeneous freezing nucleation), and INP and/or pre-existing ice tend to prevent the RHi from reaching the RHi threshold for hom. But if INP concentrations were low enough, the RHi threshold for hom would occur much more often to produce hom cirrus clouds, and their coverage could even exceed the coverage of het cirrus due to the smaller ice crystal sizes having lower fall speeds, as demonstrated in Mitchell et al. (2008, GRL). That is, lower ice sedimentation rates lead to longer cirrus lifetimes and greater cloud coverage. Moreover, the citation of Dekoutsidis et al. is misguided since that paper was showing hom is common in cirrus clouds and occurs mostly near cloud top where RHi is greatest, consistent with the modeling study by Spichtinger and Geirens (2009, ACP). The reference by Cziczo et al. does not support the author’s claim either; rather it argues that most cirrus are het cirrus.
12. Lines 377-380: While changes in UT INPC may alter the microphysical properties of cirrus clouds, this may not result in an increase in cloud cover and associated albedo for the reasons stated above. Moreover, the net radiative effect of cirrus clouds considers the absorption/emission of LW radiation in addition to SW radiation, and whether a net cooling or warming effect occurs may depend primarily on cloud optical thickness, the season, and the latitude.
Citation: https://doi.org/10.5194/egusphere-2023-1844-RC1
Huijia Shen et al.
Data sets
Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation data base CALIPSO https://subset.larc.nasa.gov
Cloud properties combining the CloudSat radar and the CALIPSO lidar measurment from raDAR/liDAR data base DARDAR https://www.icare.univ-lille.fr
MERRA-2 inst3_3d_aer_Nv: 3d,3-Hourly, Instantaneous, Model-Level, 490 Assimilation, Aerosol Mixing Ratio V5.12.4 Global Modeling and Assimilation Office (GMAO) (2015) https://doi.org/10.5067/LTVB4GPCOTK2
AERONET Aerosol Inversion (V3) database, Aerosol Robotic Network [data set] AERONET https://aeronet.gsfc.nasa.gov/new_web/data.html
Huijia Shen et al.
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