A CLOUD-RESOLVING MODELING STUDY OF SURFACE RAINFALL PROCESSES ASSOCIATED WITH LANDFALLING TYPHOON KAEMI(2006)

The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.

A Modeling Study of Surface Rainfall Processes Associated with a Torrential Rainfall Event over Hubei,China,during July 2007

The surface rainfall processes associated with the torrential rainfall event over Hubei,China,during July 2007 were investigated using a two-dimensional cloud-resolving model.The model integrated the large-scale vertical velocity and zonal wind data from National Centers for Environmental Prediction（NCEP）/Global Data Assimilation System（GDAS） for 5 days.The time and model domain mean surface rain rate was used to identify the onset,mature,and decay periods of rainfall.During the onset period,the descending motion data imposed in the lower troposphere led to a large contribution of stratiform rainfall to the model domain mean surface rainfall.The local atmospheric drying and transport of rain from convective regions mainly contributes to the stratiform rainfall.During the mature periods,the ascending motion data integrated into the model was so strong that water vapor convergence was the dominant process for both convective and stratiform rainfall.Both convective and stratiform rainfalls made important contributions to the model domain mean surface rainfall.During the decay period,descending motion data input into the model prevailed,making stratiform rainfall dominant.Stratiform rainfall was mainly caused by the water vapor convergence over raining stratiform regions.

A time fractional model to represent rainfall process

This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.

Analysis of Formation Mechanism of Two Successive Heavy Rainfall Processes on the Edge of the Subtropical High

Based on sounding and ground observation data,GPS/MET and FY-2 E satellite data,NCEP/NCAR reanalysis data（ 1°× 1°）,the formation mechanisms of two successive heavy rainfall processes on the edge of the subtropical high were analyzed. The results showed that the two heavy rainfall processes were caused by weak westerly troughs on the edge of the subtropical high at 500 h Pa,and there was strong southwest jet stream at 850-700 h Pa. As the low-level southwest jet stream intensified and moved northwards,heavy rainfall began. When the jet stream weakened,heavy rainfall ended. The heavy rainfall areas had good consistency with the high-value areas of CAPE,the high-value tongue of low-level water vapor flux,water vapor convergence center and warm advection center. Water vapor monitoring by GPS/MET had certain denotative meaning to the short-term prediction of heavy rainfall. The minimum TBB of convective cloud clusters was between-62 and-78 ℃,and the corresponding hourly maximum precipitation was 40-90 mm. In the heavy rainfall process,mesoscale vortexes occurred at 850 h Pa and below,but the scale was small,with weak low pressure but significant cyclonic circulation. The most intense rainfall was generated at the center of warm advection in the southeast of the vortex center at 925 h Pa. In the first heavy rainfall process,the mesoscale vortexes moved less,while strong rainfall was induced by strong upward movement in the southeast of the vortexes. In the second heavy rainfall process,low-level cold air invaded from the northwest into the vortexes to form cyclones and moved northeastwards. Heavy rainfall happened in the warm zone in front of cold front,and convective instability energy was high. Rainfall intensity was high,and rainfall range was large.

Analysis of Rainfall Weather Process in Most of China from 3-6 October, 2021

Heavy rain is a common abnormal weather in China, which is prone to major natural disasters such as floods. By using China National Climate Center’s DERF2.0 (the second-generation product of monthly dynamic extended ensemble prediction) models and NCEP (National Centers for Environmental Prediction) data, and using synoptic and dynamic methods and other research methods, the rainfall weather process in most of China from October 3-6, 2021 is analyzed. The results show that: 1) this process had a long duration, large cumulative rainfall and strong extreme. 2) The warm and wet flow and the cold air intersected in the central and western regions of China and Northeast China, which resulted in a regional rainstorm process within ten days. 3) There was a low-level jet moving from Guizhou and Hunan to the south of Northeast China, bringing a lot of water vapor. To sum up, the rainfall process of this round has a certain relationship with the adjustment of atmospheric circulation.

Experimental analysis for the dynamic initiation mechanism of debris flows

Debris flow is one of the major secondary mountain hazards following the earthquake. This study explores the dynamic initiation mechanism of debris flows based on the strength reduction of soils through static and dynamic triaxial tests. A series of static and dynamic triaxial tests were conducted on samples in the lab. The samples were prepared according to different grain size distribution, degree of saturation and earthquake magnitudes. The relations of dynamic shear strength, degree of saturation, and number of cycles are summarized through analyzing experimental results. The findings show that the gravelly soil with a wide and continuous gradation has a critical degree of saturation of approximately 87%, above which debris flows will be triggered by rainfall, while the debris flow will be triggered at a critical degree of saturation of about 73% under the effect of rainfall and earthquake(M>6.5). Debris flow initiation is developed in the humidification process, and the earthquake provides energy for triggering debris flows. Debris flows are more likely to be triggered at the relatively low saturation under dynamic loading than under static loading. The resistance of debris flow triggering relies more on internal frication angle than soil cohesion under the effect of rainfall and earthquake. The conclusions provide an experimental analysis method for dynamic initiation mechanism of debris flows.

The characteristics of rill development and their effects on runoff and sediment yield under different slope gradients

Rill formation is the predominant erosion process in slope land in the Loess Plateau, China. This study was conducted to investigate rill erosion characteristics and their effects on runoff and sediment yielding processes under different slope gradients at a rate of 10°, 15°, 20° and 25° with rainfall intensity of 1.5 mm min-1 in a laboratory setting. Results revealed that mean rill depth and rill density has a positive interrelation to the slope gradient. To the contrary, width-depth ratio and distance of the longest rill to the top of the slope negatively related to slope gradient. All these suggested that increasing slope steepness could enhance rill headward erosion, vertical erosion and the fragmentation of the slope surface. Furthermore,total erosion tended to approach a stable maximum value with increasing slope, which implied that there is probably a threshold slope gradient where soil erosion begins to weaken. At the same time, the correlation analysis showed that there was a close connection between slope gradient and the variousindices of soil erosion: the correlation coefficients of slope gradient with maximal rill depth, number of rills and the distance of the longest rill from the top of the slope were 0.98, 0.97 and-0.98, respectively,indicating that slope gradient is the major factor of affecting the development of rills. Furthermore,runoff was not sensitive to slope gradient and rill formation in this study. Sediment concentration,however, is positively related to slope gradient and rill formation, the sediment concentrations increased rapidly after rill initiation, especially. These results may be essential for soil loss prediction.