Microphysical characteristics of the raindrop size distribution(RSD)in Typhoon Morakot(2009) have been studied through the PARSIVEL disdrometer measurements at one site in Fujian province,China during the passage of the storm from 7 to 10 August 2009.The time evolution of the RSD reveals different segments of the storm.Significant difference was observed in the microphysical characteristics between the outer rainband and the eyewall;the eyewall precipitation had a broader size distribution(a smaller slope) than the outer rainband and eye region.The outer rainband and the eye region produced stratiform rains while the eyewall precipitation was convective or mixed stratiform-convective.The RSD was typically characterized by a single peak distribution and well represented by the gamma distribution.The relations between the shape(μ)and slope(Λ)of the gamma distribution and between the reflectivity(Z)and rainfall rate(R)have been investigated.Based on the NW-Dm relationships,we suggest that the stratiform rain for the outer rainband and the eye region was formed by the melting of graupel or rimed ice particles,which likely originated from the eyewall clouds. 相似文献
Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner–Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner–Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest. 相似文献
The paper uses a capital asset pricing model to analyze the market risk in the European Union Emission Trading System (EU ETS) and clean development mechanisms (CDM) and Zipf analysis technology to analyze the carbon price volatility in different expectations of returns in the two markets. The results show that the systematic risk of the EU ETS market is around 0.07 %, but the CDM market is clearly divided into two stages; the systematic risk of the futures contracts in the first stage (DEC09–DEC12) is less than the EU ETS market, but the systematic risk of the futures contracts that enter the market is greater than the EU ETS market and has a higher market sensitivity, although on the unsystematic risk. The CDM market is always greater than the EU ETS market. Abnormal returns in the two carbon markets are both lower than 0.02 %, but CDM is higher. The probability of price down is greater than that of price up. The carbon price is affected by market mechanisms and external factors (economic crisis and environmental policies) in the low expectations of returns. However, in the high expectations of returns, compared with the CDM market, the carbon price change in the EU ETS market is less stable and has higher risks.