A series of quality control(QC) procedures were performed on a gauge-based global daily precipitation dataset from the Global Telecommunication System(GTS) for the period 1980-2009.A new global daily precipitation(NGDP) dataset was constructed by applying those QC procedures to eliminate erroneous records.The NGDP dataset was evaluated using the NOAA Climate Prediction Center Merged Analysis of Precipitation(CMAP) and the Global Precipitation Climatology Project(GPCP) precipitation datasets.The results showed that the frequency distribution and spatial distribution pattern of NGDP had a nice match with those from the CMAP and GPCP datasets.The global mean correlation coefficients with the CMAP and GPCP data increased from 0.24 for original GTS precipitation data to about 0.70 for NGDP data.Correspondingly,the root mean square errors(RMSE) decreased from 12 mm per day to 1 mm per day.The interannual variabilities of NGDP monthly precipitation are consistent with the CMAP and GPCP datasets in Asia.Meanwhile,the seasonal variabilities for most land areas on the Earth of NGDP dataset are also consistent with the CMAP and GPCP precipitation products.
NIE Su-PingLUO YongLI Wei-PingWU Tong-WenSHI Xue-LiWANG Zai-Zhi
Using hourly station rain gauge data in the warm season (May-October) during 1961-2006, the climatological features of the evolution of the rainfall process are analyzed by compositing rainfall events centered on the maximum hourly rainfall amount of each event. The results reveal that the rainfall process is asymmetric, which means rainfall events usually reach the maximum in a short period and then experience a relatively longer retreat to the end of the event. The effects of rainfall intensity, duration and peak time, as well as topography, are also considered. It is found that the asymmetry is more obvious in rainfall events with strong intensity and over areas with complex terrain, such as the eastern margin of the Tibetan Plateau, the Hengduan Mountains, and the Yungui Plateau. The asymmetry in short-duration rainfall is more obvious than that in long-duration rainfall, but the regional differences are weaker. The rainfall events that reach the maximum during 14:00-02:00 LST exhibit the strongest asymmetry and those during 08:00-14:00 LST show the weakest asymmetry. The rainfall intensity at the peak time stands out, which means that the rainfall intensity increases and decreases quickly both before and after the peak. These results can improve understanding of the rainfall process and provide metrics for the evaluation of climate models. Moreover, the strong asymmetry of the rainfall process should be highly noted when taking measures to defending against geological hazards, such as collapses, landslides and debris flows throughout southwestern China.
Validated satellite-derived sea surface temperatures (SSTs) are widely used for climate monitoring and ocean data assimilation systems. In this study, the Fengyun-3A (FY-3A) SST experimental product is evaluated using Advanced Very High Resolution Radiometer (AVHRR)-merged and in situ SSTs. A comparison of AVHRR-merged SSTs reveals a negative bias of more than 2K in FY-3A SSTs in most of the tropical Pacific and low-latitude Indian and Atlantic Oceans. The error variance of FY-3A SSTs is estimated using three-way error analysis. FY-3A SSTs show regional error variance in global oceans with a maximum error variance of 2.2 K in the Pacific Ocean. In addition, a significant seasonal variation of error variance is present in FY-3A SSTs, which indicates that the quality of FY-3A SST could be improved by adjusting the parameters in the SST retrieval algorithm and by applying regional and seasonal algorithms, particularly in key areas such as the tropical Pacific Ocean. An objective analysis method is used to merge FY-3A SSTs with the drifter buoy data. The errors of FY-3A SSTs are decreased to-0.45K comparing with SST observations from GTSPP.
