Evaluation of Cloud Vertical Structure Simulated by Recent BCC_AGCM Versions through Comparison With CALIPSO-GOCCP Data

ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover （TCC）, middle cloud cover （MCC） and low cloud cover （LCC）, and that BCC_AGCM2.2 underestimated the global-mean high cloud cover （HCC）. The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing （RSCRF and RLCRF）. Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.

Vertical Distribution Characteristics of Precipitation Cloud in Tianjin Based on L-band Sounding Data

Based on L-band sounding data,threshold method of relative humidity was used to analyze vertical distribution characteristics of precipitation cloud system in Tianjin region.The results showed that main precipitation cloud system affecting Tianjin is cold and warm mixed cloud,followed by cold cloud,and precipitation of warm cloud is less.During May-November,precipitation of cold and warm mixed cloud is dominant,and it is dominant by precipitation of cold cloud from January to April.In four seasons,the precipitation frequency of double-layer cloud is the most,and precipitation of single-layer cloud mainly appears during March-November,and peak is in June.Peak of cloud system with three or more layers all appears in July and August.The cold cloud and warm cloud catalysts should be selected respectively for artificial precipitation enhancement in Tianjin.In winter,cold cloud catalyst operation is selected;in spring,summer and autumn,the cold cloud catalyst is spread in the cold cloud area,and the warm cloud catalyst is distributed in the warm cloud area according to the conditions of cloud layer.

Development of Cloud Detection Methods Using CFH, GTS1, and RS80 Radiosondes

The accuracies of three instruments in measuring atmospheric column humidity were assessed during an upper troposphere and lower stratosphere observation campaign conducted from 7 to 13 August 2009 in Kunming, China. The three instruments are a cryogenic frost-point hygrometer （CFH）, a Vaisala RS80 radiosonde （RS80）, and a GTS1 radiosonde （GTS1）. The accuracy of relative humidity （RH） measurements made by the CFH, GTS1, and RS80 was similar between the surface and 500 hPa （～5.5 km above sea level）. However, above 500 hPa, the errors in RH measurements made by the RS80, relative to measurements made by the CFH, are much less than those detected with the GTS1. Three different retrieval methods for determining cloud boundaries from CFH, RS80, and GTS1 measurements were developed and take into account the differences in accuracy among the three instruments. The method for the CFH is based on RH thresholds at all levels, which demands high accuracy. Given that the accuracy of RH measurements decreases at higher altitudes, the cloud detection methods for RS80 and GTS1 are different for different altitude ranges. Below 5 km, the methods for the RS80 and the GTS1 are similar to that of the CFH; above 5 km, the methods for the RS80 and the GTS1 are both developed based on the second-order derivatives of temperature and RH with respect to height, but with different criteria applied. Comparisons of cloud-layer retrievals derived from the three measurements are also made.