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Yiping Zhang
,
Sonia Kreidenweis
, and
Gregory R. Taylor

Abstract

A modeling study of the effects of clouds on the evolution and redistribution of aerosol particles in the troposphere is presented. A two-mode, two-moment aerosol evolution model is coupled with a two-dimensional, mixed-phase, two-moment microphysics, Eulerian cloud model and a sulfate cloud chemistry model. The coupled model is used to simulate evolution of a convective cloud with different assumptions about the initial chemical and aerosol fields. In the simulations, SO2 is convectively transported to the mid- to upper troposphere, where it is oxidized to gas-phase H2SO4. After cloud processing, cloud condensation nuclei (CCN) particles are removed by precipitation and graupel to form a CCN-depleted region above cloud top and in the cold and humidified cloud outflow region. These conditions are favorable for binary homogeneous nucleation of ultrafine sulfuric acid particles to take place. The new particle formation in the mid- and upper troposphere interacts with cloud processing and transport of aerosol particles and produces a peak of small particle concentration in the outflow region. Sensitivity tests varying initial aerosol composition and mass mixing ratio, initial H2SO4 mass mixing ratio, assumed OH· profile, and nucleation rate factor are discussed. The small particle concentration in the upper troposphere is most sensitive to initial aerosol composition and assumed OH· profile. When the nucleation rate factor is increased, the critical H2SO4(g) concentration is lowered, and the nucleation rate adjusts to changes in environmental variables more quickly. The model results suggest that both aerosols and aerosol precursors can be transported into the mid- and upper troposphere by convective clouds, affecting vertical profiles of aerosol concentrations.

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Yiping Li
,
Yaohui Li
,
Xing Yuan
,
Liang Zhang
, and
Sha Sha

Abstract

Land surface models (LSMs) have been widely used to provide objective monitoring of soil moisture during drought, but large uncertainties exist because of the different parameterizations in LSMs. This study aims to evaluate the ability to monitor soil moisture drought over three key regions in China by using the Noah LSM from the Global Land Data Assimilation System, version 2 (GLDASv2), and the Community Atmosphere Biosphere Land Exchange (CABLE) model that is currently used at the China Meteorological Administration. The modeled soil moisture drought indices were verified against the standardized precipitation evapotranspiration index (SPEI), which served as a reference drought indicator over northern China (NC), northwestern China (NWC), and southwestern China (SWC) from 1961 to 2010. The results show that the precipitation forcing data that drive both LSMs have high accuracy when compared with local observational data. GLDASv2/Noah outperforms CABLE in capturing soil moisture anomalies and variability, especially in SWC, but both show good correlations with the 3-month SPEI (SPEI3) in NC, NWC, and SWC. The autumn drought of 2002 and spring drought of 2010 were selected for the comparison of the modeled drought categories with the SPEI3 drought category, where GLDASv2/Noah performed slightly better than CABLE. This work demonstrates that the choice of LSM is crucial for monitoring soil moisture drought and that the GLDASv2/Noah LSM can be a good candidate for the development of a new operational drought-monitoring system in China.

Open access