Cross-season relation of the South China Sea precipitation variability between winter and summer

The present study reveals cross-season connections of rainfall variability in the South China Sea (SCS) region between winter and summer. Rainfall anomalies over northern South China Sea in boreal summer tend to be preceded by the same sign rainfall anomalies over southern South China Sea in boreal winter (denoted as in-phase relation) and succeeded by opposite sign rainfall anomalies over southern South China Sea in the following winter (denoted as out-of-phase relation). Analysis shows that the in-phase relation from winter to summer occurs more often in El Niño/La Niña decaying years and the out-of-phase relation from summer to winter appears more frequently in El Niño/La Niña developing years. In the summer during the El Niño/La Niña decaying years, cold/warm and warm/cold sea surface temperature (SST) anomalies develop in tropical central North Pacific and the North Indian Ocean, respectively, forming an east–west contrast pattern. The in-phase relation is associated with the influence of anomalous heating/cooling over the equatorial central Pacific during the mature phase of El Niño/La Niña events that suppresses/enhances precipitation over southern South China Sea and the impact of the above east–west SST anomaly pattern that reduces/increases precipitation over northern South China Sea during the following summer. The impact of the east–west contrast SST anomaly pattern is confirmed by numerical experiments with specified SST anomalies. In the El Niño/La Niña developing years, regional air-sea interactions induce cold/warm SST anomalies in the equatorial western North Pacific. The out-of-phase relation is associated with a Rossby wave type response to anomalous heating/cooling over the equatorial central Pacific during summer and the combined effect of warm/cold SST anomalies in the equatorial central Pacific and cold/warm SST anomalies in the western North Pacific during the mature phase of El Niño/La Niña events.     

A Comparison of Modified Fuzzy Weights of Evidence,Fuzzy Weights of Evidence,and Logistic Regression for Mapping Mineral Prospectivity

Weights of evidence and logistic regression are two of the most popular methods for mapping mineral prospectivity. The logistic regression model always produces unbiased estimates, whether or not the evidence variables are conditionally independent with respect to the target variable, while the weights of evidence model features an easy to explain and implement modeling process. It has been shown that there exists a model combining weights of evidence and logistic regression that has both of these advantages. In this study, three models consisting of modified fuzzy weights of evidence, fuzzy weights of evidence, and logistic regression are compared with each other for mapping mineral prospectivity. The modified fuzzy weights of the evidence model retains the advantages of both the fuzzy weights of the evidence model and the logistic regression model; the advantages being (1) the predicted number of deposits estimated by the modified fuzzy weights of evidence model is nearly equal to that of the logistic regression model, and (2) it can deal with missing data. This method is shown to be an effective tool for mapping iron prospectivity in Fujian Province, China.     

Subseasonal variability during the South China Sea summer monsoon onset

Analysis of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data for the period 1998–2007 reveals large subseasonal fluctuations in sea surface temperature (SST) of the South China Sea during the summer monsoon onset. These subseasonal SST changes are closely related to surface heat flux anomalies induced by surface wind and cloud changes in association with the summer monsoon onset. The SST changes feed back on the atmosphere by modifying the atmospheric instability. The results suggest that the South China Sea summer monsoon onset involves ocean–atmosphere coupling on subseasonal timescales. While the SST response to surface heat flux changes is quick and dramatic, the time lag between the SST anomalies and the atmospheric convection response varies largely from year to year. The spatial–temporal evolution of subseasonal anomalies indicates that the subseasonal variability affecting the South China Sea summer monsoon onset starts over the equatorial western Pacific, propagates northward to the Philippine Sea, and then moves westward to the South China Sea. The propagation of these subseasonal anomalies is related to the ocean–atmosphere interaction, involving the wind-evaporation and cloud-radiation effects on SST as well as SST impacts on lower-level convergence over the equatorial western Pacific and atmospheric instability over the Philippine Sea and the South China Sea.     

勘查地球化学数据挖掘与弱异常识别

我国积累的大量高质量、多元素、多尺度的地球化学数据,为矿产勘查与环境评价提供了有效的数据支撑。如何对这些数据进行二次开发和再利用,提取有价值的地球化学异常信息并带动找矿突破,是缓解当前矿产资源短缺的重要途径之一。在覆盖区和深部的找矿实践中,由于矿体埋深和覆盖层的影响,往往在表生介质中形成弱小的地球化学异常,识别和评价弱小地球化学异常是当前勘查地球化学数据处理的重要方向之一。本文围绕地球化学异常信息的提取和评价,主要从以下几个方面讨论了相关的国内外研究进展和发展趋势:勘查地球化学数据处理与异常识别方法和模型,勘查地球化学数据闭合效应的影响及其解决方案,基于大数据和机器学习的勘查地球化学数据处理以及弱小地球化学异常的识别和评价。研究发现,在地质环境的约束下,基于大数据思维和机器学习相结合的方法,注重地球化学空间分布模式与已发现矿床的相关关系,同时使用所有地球化学变量能有效刻画具有非线性特征的地球化学空间分布模式,可识别出传统方法无法识别的异常,为开展地球化学空间模式识别与异常提取提供了新的途径。     

ArcFractal: An ArcGIS Add-In for Processing Geoscience Data Using Fractal/Multifractal Models

Natural Resources Research - Fractal and multifractal models, including the concentration-area (C–A) fractal model, spectrum-area (S–A) multifractal model, and local singularity...     

Relationship of boreal summer 10–20-day and 30–60-day intraseasonal oscillation intensity over the tropical western North Pacific to tropical Indo-Pacific SST

Climate Dynamics - The present study contrasts interannual variations in the intensity of boreal summer 10–20-day and 30–60-day intraseasonal oscillations (ISOs) over the tropical...     

Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing,China

We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP–Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency(period 90 days) variations in meteorological conditions on persistent pollution events(those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions.Some results from this study are based on a limited number of events and thus require validation using more data.     

Identifying gravity anomalies caused by granitic intrusions in Nanling mineral district,China: a multifractal perspective

Several power‐law relationships of geophysical potential fields have been discussed recently with renewed interests, including field value–distance () and power spectrum–wavenumber () models. The singularity mapping technique based on the density/concentration–area (C–A) power‐law model is applied to act as a high‐pass filter for extracting gravity and magnetic anomalies regardless of the background value and to detect the edges of gravity or magnetic sources with the advantage of scale invariance. This is demonstrated on a synthetic example and a case study from the Nanling mineral district, Southern China. Compared with the analytic signal amplitude and total horizontal gradient methods, the singularity mapping technique provides more distinct and less noisy boundaries of granites than traditional methods. Additionally, it is efficient for enhancing and outlining weak anomalies caused by concealed granitic intrusions, indicating that the singularity method based on multifractal analysis is a potential tool to process gravity and magnetic data.     

Seasonality of interannual atmosphere–ocean interaction in the South China Sea

The present study documents the atmosphere–ocean interaction in interannual variations over the South China Sea (SCS). The atmosphere–ocean relationship displays remarkable seasonality and regionality, with an atmospheric forcing dominant in the northern and central SCS during the local warm season, and an oceanic forcing in the northern SCS during the local cold season. During April–June, the atmospheric impact on the sea surface temperature (SST) change is characterized by a prominent cloud-radiation effect in the central SCS, a wind-evaporation effect in the central and southern SCS, and a wind-driven oceanic effect along the west coast. During November–January, regional convection responds to the SST forcing in the northern SCS through modulation of the low-level convergence and atmospheric stability. Evaluation of the precipitation–SST and precipitation–SST tendency correlation in 24 selected models from CMIP5 indicates that the simulated atmosphere–ocean relationship varies widely among the models. Most models have the worst performance in spring. On average, the models simulate better the atmospheric forcing than the oceanic forcing. Improvements are needed for many models before they can be used to understand the regional atmosphere–ocean interactions in the SCS region.