The heaviest rainfall over 61 yr hit Beijing during 21-22 July 2012.Characterized by great rainfall amount and intensity,wide range,and high impact,this record-breaking heavy rainfall caused dozens of deaths and extensive damage.Despite favorable synoptic conditions,operational forecasts underestimated the precipitation amount and were late at predicting the rainfall start time.To gain a better understanding of the performance of mesoscale models,verification of high-resolution forecasts and analyses from the WRFbased BJ-RUCv2.0 model with a horizontal grid spacing of 3 km is carried out.The results show that water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area.Moreover,model forecasts are first verified statistically using equitable threat score and BIAS score.The BJ-RUCv2.0forecasts under-predict the rainfall with southwestward displacement error and time delay of the extreme precipitation.Further quantitative analysis based on the contiguous rain area method indicates that major errors for total precipitation(〉 5 mm h~(-1)) are due to inaccurate precipitation location and pattern,while forecast errors for heavy rainfall(〉 20 mm h~(-1)) mainly come from precipitation intensity.Finally,the possible causes for the poor model performance are discussed through diagnosing large-scale circulation and physical parameters(water vapor flux and instability conditions) of the BJ-RUCv2.0 model output. 相似文献
The accurate detection of heavy metal-induced stress on crop growth is important for food security and agricultural, ecological and environmental protection. Spectral sensing offers an efficient and undamaged observation tool to monitor soil and vegetation contamination. This study proposed a methodology for dynamically estimating the total cadmium (Cd) accumulation in rice tissues by assimilating spectral information into WOFOST (World Food Study) model. Based on the differences among ground hyperspectral data of rice in three experiments fields under different Cd concentration levels, the spectral indices MCARI1, NREP and RH were selected to reflect the rice stress condition and dry matter production of rice. With assimilating these sensitive spectral indices into the WOFOST + PROSPECT + SAIL model to optimize the Cd pollution stress factor fwi, the dynamic dry matter production processes of rice were adjusted. Based on the relation between dry matter production and Cd accumulation, we dynamically simulating the Cd accumulation in rice tissues. The results showed that the method performed well in dynamically estimating the total amount of Cd accumulation in rice tissues with R2 over 85%. This study suggests that the proposed method of integrating the spectral information and the crop growth model could successfully dynamically simulate the Cd accumulation in rice tissues. 相似文献
Marine heatwaves (MHWs) are extreme ocean events characterized by anomalously warm upper-ocean temperatures, posing significant threats to marine ecosystems. While various factors driving MHWs have been extensively studied, the role of ocean salinity remains poorly understood. This study investigates the influence of salinity on the major 2013–2014 MHW event in the Northeast Pacific using reanalysis data and climate model outputs. Our results show that salinity variabilities are crucial for the development of the MHW event. Notably, a significant negative correlation exists between sea surface temperature anomalies (SSTAs) and sea surface salinity anomalies (SSSAs) during the MHW, with the SSSAs emerging simultaneously with SSTAs in the same area. Negative salinity anomalies (SAs) result in a shallower mixed layer, which suppresses vertical mixing and thus sustains the upper-ocean warming. Moreover, salinity has a greater impact on mixed layer depth anomalies than temperature. Model sensitivity experiments further demonstrate that negative SAs during MHWs amplify positive SSTAs by enhancing upper-ocean stratification, intensifying the MHW. Additionally, our analysis indicates that the SAs are predominantly driven by local freshwater flux anomalies, which are mainly induced by positive precipitation anomalies during the MHW event. 相似文献