1998年夏季HUBEX/GAME期间热量和水汽收支(英)

By using the high-resolution GAME reanalysis data, the heat and moisture budgets during the period of HUBEX/GAME in the summer of 1998 are calculated for exploring the thermodynamic features of Meiyu over the Changjiang-Huaihe (CH) valley. During the CH Meiyu period, an intensive vertically-integrated heat source and moisture sink are predominant over the heavy rainfall area of the CH valley, accompanied by strong upward motion at 500 hPa. The heat and moisture budgets show that the main diabatic heating component is condensation latent heat released by rainfall. As residual terms, the evaporation and sensible heating are relatively small. Based on the vertical distribution of the heat source and moisture sink, the nature of the rainfall is mixed, in which the convective rainfall is dominant with a considerable percentage of continuous stratiform rainfall. There are similar time evolutions of the main physical parameters (〈Q 1〉, 〈Q 2〉, and vertical motion ω at 500 hPa). The time variations of 〈Q 1〉 and 〈Q 2〉 are in phase with those of −ω 500, and have their main peaks within the CH Meiyu period. This shows the influence of the heat source on the dynamic structure of the atmosphere. The wavelet analyses of those time series display similar multiple timescale characteristics. During the CH Meiyu period, both the synoptic scale(∼6 days) and mesoscale (∼2 days and ∼12 hours) increase obviously and cause heavy rainfall as well as the appearances of the maxima of the main physical parameters. Among them, the mesoscale systems are the main factors.

Refined Evaluation of Satellite Precipitation Products against Rain Gauge Observations along the Sichuan–Tibet Railway

Being constructed in southwestern China, the Sichuan–Tibet Railway(STR) travels across the eastern Tibetan Plateau where there is the most complex terrain and changeable weather in the world. Due to sparse ground-based observations over the Tibetan Plateau, precipitation products retrieved by remote sensing are more widely used;however,satellite-based precipitation products(SPPs) have not yet been strictly and systematically evaluated along the STR.This study aims to evaluate the performance of six SPPs by a series of metrics with available ground observations along the STR during 1998–2020. The six SPPs include the datasets derived from the Tropical Rainfall Measuring Mission(TRMM), Climate Prediction Center morphing technique(CMORPH), Global Precipitation Measurement(GPM), Global Satellite Mapping of Precipitation(GSMaP), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks(PERSIANN), and Fengyun-2 satellites precipitation estimate(FY2PRE). The results indicate that most of the SPPs can capture the precipitation characteristics on multiple timescales(monthly,daily, hourly, and diurnal cycle) as shown by the evaluated metrics. The probability density functions of the daily and hourly precipitation are also well represented by the SPPs, and 30 mm day^(-1) and 16 mm h^(-1) are identified as the daily and hourly thresholds of extreme precipitation events along the STR. The best SPP varies at different timescales:GPM and GSMaP are suitable for the monthly and daily scale, and FY2PRE and GPM are suited to the hourly scale.In general, GPM is relatively optimum on multiple timescales, and PERSIANN gives the worst performance. In addition, the SPPs perform worse at higher altitudes and for more intense precipitation. Overall, the results from this study are expected to provide essential reference for using the SPPs in meteorological services and disaster prevention in the STR construction and its future operation.