With the unprecedented spaceborne precipitation radar(PR),the Tropical Rainfall Measuring Mission(TRMM) satellite has collected high-quality precipitation measurements for over ten years.The TRMM/PR data are nowadays extensively exploited in numerous meteorological and hydrological fields.Yet an artificial orbit boost of the TRMM satellite in August 2001 modulated the observation parameters,which inevitably affects climatological applications of the PR data and needs to be clarified.This study investigates the orbit boost effects of the TRMM satellite on the PR-derived precipitation characteristics.Both the potential impacts on precipitation frequency(PF) and precipitation intensity(PI) are carefully analyzed.The results show that the total PF decreases by 8.3% and PI increases by 4.0% over the tropics after the orbit boost.Such changes significantly exceed the natural variabilities and imply the strong effects of orbit boost on precipitation characteristics.The impacts on stratiform precipitation and convective precipitation are inconsistent,which is attributed to their distinct precipitation features.Further analysis reveal that the increased PI of stratiform precipitation is mainly due to the decreased frequencies of light precipitation,while the semi-constant PI of convective precipitation is caused by the concurrently decreased frequencies of light and heavy precipitation.A modification is applied to the post-boost PR precipitation data to retrieve the actual trends of tropical precipitation characteristics.It is found that the PI of total-precipitation approximately keeps invariable from 1998 to 2005.The total PF has no obvious trend over tropical oceans but decreases considerably over tropical lands.
Visible and infrared(VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner(VIRS) and precipitation radar(PR) aboard the Tropical Rainfall Measuring Mission(TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness(COT), effective radius(Re), and brightness temperature of VIRS channel 4(BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from Cloud Parameters information(PISCP). It is essentially a lookup table(LUT) approach that is deduced from the optimal equitable threat score(ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds(PCs) and non-precipitating clouds(N-PCs) are well distinguished by PISCP, with the probability of detection(POD) near 0.80, the probability of false detection(POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.
Taking winter and summer in eastern China as an example application, a grid-cell method of aerosol direct radiative forcing(ADRF) calculation is examined using the Santa Barbara DISORT Atmospheric Radiative Transfer(SBDART) model with inputs from MODIS and AERONET observations and reanalysis data. Results show that there are significant seasonal and regional differences in climatological mean aerosol optical parameters and ADRF. Higher aerosol optical depth(AOD)occurs in summer and two prominent high aerosol loading centers are observed. Higher single scattering albedo(SSA) in summer is likely associated with the weak absorbing secondary aerosols. SSA is higher in North China during summer but higher in South China during winter. Aerosols induce negative forcing at the top of the atmosphere(TOA) and surface during both winter and summer, which may be responsible for the decrease in temperature and the increase in relative humidity.Values of ADRF at the surface are four times stronger than those at the TOA. Both AOD and ADRF present strong interannual variations; however, their amplitudes are larger in summer. Moreover, patterns and trends of ADRF do not always correspond well to those of AOD. Differences in the spatial distributions of ADRF between strong and weak monsoon years are captured effectively. Generally, the present results justify that to calculate grid-cell ADRF at a large scale using the SBDART model with observational aerosol optical properties and reanalysis data is an effective approach.
Yunfei FUJiachen ZHUYuanjian YANGRenmin YUANGuosheng LIUTao XIANPeng LIU
