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Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion Cover

Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion

Tellus B: Chemical and Physical Meteorology
Volume 65 (2013): Issue 1
By: ,  ,  ,  ,   and    
Open Access
|Jan 2013
Figures & tables

Figures & Tables

Fig. 1. 

Variations in the cloud droplet spectral dispersion as the functions of cloud droplet number concentration for MG07, RL03, GB98 and DM07.

Fig. 2. 

Dependence of autoconversion rate P on the cloud droplet number concentration for the different ɛ−N c relationships: MG07, RL03, GB98 and DM07 (at given L c = 1 g m−3).

Fig. 3. 

Initial profiles of temperature (T), dew point (Td), water vapour mixing ratio (W) and horizontal winds U and V.

Table 1. Summary of the experiments

Experiment name ɛ−N c relationships Aerosol backgrounds MG07-m MG07 C0=120 cm−3 and k=0.4 MG07-c MG07 C0=1000 cm−3 and k=0.5 RL03-m RL03 C0=120 cm−3 and k=0.4 RL03-c RL03 C0=1000 cm−3 and k=0.5 GB98-m GB98 C0=120 cm−3 and k=0.4 GB98-c GB98 C0=1000 cm−3 and k=0.5 DM07-m DM07 C0=120 cm−3 and k=0.4 DM07-c DM07 C0=1000 cm−3 and k=0.5

Table 2. Liquid cloud microphysical properties obtained from whole domain-averaged values during a 3-hour integration time period

MG07-m MG07-c RL03-m RL03-c GB98-m GB98-c DM07-m DM07-c CDNC 1.6 8.0 1.7 8.0 1.6 7.4 1.7 7.3 CWC 4.91 5.54 4.68 5.51 4.95 6.08 4.69 6.19 MVRCD 9.0 5.5 8.7 5.5 9.0 5.8 8.7 5.9 RDNC 182 84 279 85 174 33 277 29 RWC 8.00 7.44 8.20 7.46 7.98 6.71 8.22 6.48 MVRR 102 128 89 128 103 169 89 175

[i] Cloud droplet number concentration (CDNC, 1.e5 m−3), cloud water content (CWC, 1.e−4 g m−3), mean volume radius of cloud droplet (MVRCD, µm), rain drop number concentration (RDNC, m−3), rain water content (RWC, 1.e−4 g m−3) and mean volume radius of raindrops (MVRR, µm).

Table 3. Rates of the microphysical processes obtained from whole domain-averaged values during a 3-hour integration time period

MG07-m MG07-c RL03-m RL03-c GB98-m GB98-c DM07-m DM07-c PRC (1.e–10 kg/kg/s) 1.21 0.68 1.71 0.69 1.16 0.27 2.02 0.23 PRA (1.e–10 kg/kg/s) 31.41 29.18 31.83 29.33 31.44 26.74 32.32 25.88 PRE (1.e–10 kg/kg/s) −16.59 −16.26 −16.56 −16.27 −16.62 −15.45 −16.76 −15.13 NPRC1 (1/kg/s) 1.83 1.05 2.59 1.06 1.76 0.42 3.06 0.35 NSUBR (1/kg/s) −0.13 −0.06 −0.20 −0.06 −0.13 −0.03 −0.27 −0.03 NRAGG (1/kg/s) −1.12 −0.53 −1.80 −0.54 −1.01 −0.15 −2.26 −0.12 PIMMI (1.e–15 kg/kg/s) 2.23 1.94 2.43 1.94 2.19 1.84 2.42 2.00 PSACWS (1.e–10 kg/kg/s) 1.20 1.65 1.17 1.64 1.25 1.92 1.02 2.12 PRACG (1.e–10 kg/kg/s) 9.57 8.21 10.31 8.34 9.46 5.55 10.93 6.19

[i] PRC represents autoconversion rate of cloud droplets to rain; PRA is accretion rate of cloud droplets by rain; PRE is evaporation rate of rain; NPRC1 is autoconversion rate of rain drop number concentration; NSUBR is evaporation rate of rain drop number concentration; NRAGG is rate for self-collection of rain drop number concentration; PIMMI is rate for immersion freezing of cloud water to form cloud ice; PSACWS is rate for accretion of cloud water by snow; PRACG is rate for accretion of rain by graupel.

Fig. 4. 

Schematic diagram showing the aerosol-induced changing trends of liquid cloud microphysical properties, including cloud droplet number concentration (CDNC), cloud water content (CWC), mean volume radius of cloud droplet (MVRCD), rain drop number concentration (RDNC), rain water content (RWC) and mean volume radius of raindrops (MVRR).

Fig. 5. 

Vertical profiles of liquid cloud microphysical properties obtained from the horizontal domain-averaged values during a 3-hour integration time period, including (a) cloud droplet number concentration, (b) cloud water content, (c) rain drop number concentration and (d) rain water content for the different types of the ɛ−N c relationships. Note that MG07-m and MG07-c cases represent the results of ɛ−N c positive relationships, while GB98-m and Gb98-c cases represent the results of the ɛ−N c negative relationships.

Table 4. Hydrometeor species of ice phase obtained from whole domain-averaged values during a 3-hour integration time period

MG07-m MG07-c RL03-m RL03-c GB98-m GB98-c DM07-m DM07-c IC 1.38 1.30 1.44 1.30 1.33 1.32 1.42 1.29 SWC 1.69 1.94 1.56 1.94 1.77 2.35 1.60 2.49 GWC 6.54 6.51 6.55 6.51 6.53 6.33 6.55 6.26 TWC 9.61 9.75 9.55 9.75 9.61 10.00 9.57 10.04

[i] Ice content (IC, 1.e−3 g m−3), snow water content (SWC, 1.e−3 g m−3), graupel water content (GWC, 1.e−3 g m−3), total water content of ice phase (TWC, 1.e−3 g m−3).

Fig. 6. 

Same as Fig. 5, but for (a) ice content, (b) snow water content and (c) graupel water content.

Fig. 7. 

Domain-maximum vertical velocity (m s−1) as functions of time in maritime and continental backgrounds for MG07, RL03, GB98 and DM07.

Fig. 8. 

Vertical profiles of the horizontally averaged convective mass flux MF c within convective cores at 0.5 hours in the clean maritime and polluted continental backgrounds for (a) MG07, (b) RL03, (c) GB98 and (d) DM07.

Table 5. Averaged domain-maximum vertical velocity (Wmax, m s−1) over the whole simulation time (3 hours) in maritime and continental backgrounds

Wmax-m Wmax-c Relative differences (%) MG07 6.36 6.39 0.47 RL03 6.41 6.39 −0.31 GB98 6.36 6.43 1.10 DM07 6.47 6.40 −1.08

[i] Relative differences are calculated by ((Wmax-c)−(Wmax-m))/(Wmax-m)×100%. ‘m’ refers to a maritime concentration of aerosols (i.e. clean background) and ‘c’ refers to a continental concentration of aerosols (i.e. polluted background).

Table 6. Averaged domain-maximum vertical velocity (Wmax, m s−1) during the first 1.5-hour integration time in maritime and continental backgrounds

Wmax-m Wmax-c Relative differences (%) MG07 11.17 11.19 0.18 RL03 11.21 11.19 −0.18 GB98 11.17 11.20 0.27 DM07 11.29 11.16 −1.15

[i] Relative differences are calculated by ((Wmax-c)−(Wmax-m))/(Wmax-m)×100%. Abbreviations are as in Table 5.

Table 7. Average convective mass flux MF c within convective cores between 700 hPa and 200 hPa (0.01×kg m−2 s−1) at 0.5 hours in maritime and continental backgrounds

MF c -m MF c -c Relative differences (%) MG07 4.76 4.66 −2.10 RL03 4.78 4.67 −2.30 GB98 4.75 4.55 −4.21 DM07 4.78 4.53 −5.23

[i] Relative differences are calculated by [(MF c -c)−(MF c -m)]/(MF c -m)×100%. Abbreviations are as in Table 5.

Fig. 9. 

Temporal evolution of the model-estimated domain average accumulated precipitation (mm) in the clean maritime and polluted continental backgrounds for (a) MG07, (b) RL03, (c) GB98 and (d) DM07. The point for time=0 is referred to the start time of simulation.

Table 8. Model-estimated domain average accumulated precipitation (mm) obtained during 3 hours of simulations

Precipitation-m Precipitation-c Relative differences (%) MG07 0.0796 0.0827 3.89 RL03 0.0759 0.0826 8.83 GB98 0.0797 0.0769 −3.51 DM07 0.0750 0.0735 −2.00

[i] Relative differences are calculated by ((Precipitation-c)−(Precipitation-m))/(Precipitation-m)×100%. Abbreviations are as in Table 5.

Table 9. Model-estimated domain average accumulated precipitation (mm) from simulations with maximum θ′ of the thermal to initiate convection of 2.5, 3 and 3.5 K

Precipitation-m Precipitation-c Relative differences (%) MG07 for 2.5 K 0.0662 0.0678 2.42 MG07 for 3.0 K 0.0796 0.0827 3.89 MG07 for 3.5 K 0.0899 0.0923 2.67 RL03 for 2.5 K 0.0639 0.0677 5.95 RL03 for 3.0 K 0.0759 0.0826 8.83 RL03 for 3.5 K 0.0872 0.0920 5.50 GB98 for 2.5 K 0.0665 0.0638 −4.06 GB98 for 3.0 K 0.0797 0.0769 −3.51 GB98 for 3.5 K 0.0902 0.0853 −5.43 DM07 for 2.5 K 0.0620 0.0617 −0.48 DM07 for 3.0 K 0.0750 0.0735 −2.00 DM07 for 3.5 K 0.0845 0.0811 −4.02

[i] Relative differences are calculated by ((Precipitation-c) − (Precipitation-m))/(Precipitation-m)×100%. Abbreviations are as in Table 5 .

DOI: https://doi.org/10.3402/tellusb.v65i0.19054 | Journal eISSN: 1600-0889
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Language: English
Page range: 19054 - 19054
Submitted on: Jun 26, 2012
Accepted on: Jan 27, 2013
Published on: Jan 1, 2013
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
aerosol indirect effects,
cloud droplet spectral dispersion,
autoconversion parameterization,
deep convective systems,
two-moment bulk microphysics scheme

© 2013 Xiaoning Xie, Xiaodong Liu, Yiran Peng, Yi Wang, Zhiguo Yue, Xinzhou Li, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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