张家界自动站与人工站降水量误差原因分析及处理方法

利用张家界2003～2008年自动站与人工站降水量资料,从日降水量误差年平均情况、主汛期日降水量误差及小时降水昔误差方面进行了分析,并寻找原因和解决办法,结果表明:总体上误差在允许范围,但随降水量和降水强度增大而增大,暴雨以上级别降水时,有超过正常范围现象.仪器故障、人为原因产生的误差各有处理方法,系统误差需要改进仪器.     

自动站与人工站气压记录分析评估

利用2005年1月至12月凭祥站自动与人工第二年平行观测气压资料,就自动与人工观测气压的差值及引起差异的原因进行了分析。结果表明:(1)自动观测气压值比人工观测气压值,日平均值普遍偏低0.3～0.4hPa。日最低气压在5～6月高温期差值最大,有时可达到1.3 hPa。(2)自动与人工观测气压的差值具有明显的日变化和季节变化。(3)自动与人工观测气压值主要分布在0.3～0.4hPa之间,在业务规定允许误差范围内(4)人工操作不当读数误差;观测时间不一致;仪器性能误差;自动观测在高温状况下的非线性以及其他原因均会导致自动与人工观测气压产生差异。     

自动站与人工站数据对比分析

由于仪器工作原理、数据观测时间以及数据采样方式与样本数的不同，人工站与自动站观测的数据存在着明显的差异。通过两组数据的对比分析，对误差原因进行了初步诊断，认为自动站对气象要素的反映更接近实际。     

中山市新气象观测站人工站与自动站气象要素对比

通过图表的形式,对广东省中山市气象局2007年人工站与自动站的各项气象要素观测日数据进行对比分析,发现人工站与自动站各气象要素数据之间存有差异,但是这些差异都在允许的范围之内,初步阐述了造成这些差异的原因.     

浅析自动站与人工站地面温度差值原因

1引言自动气象站投入气象业务运行后,所测得的气象要素值和人工观测值常常存在某些差异。当人工观测数据和自动值之间差值较大时,应进行综合分析判断,确定产生误差的原因并加以解决是确保自动气象站采集数据准确的必要措施。通过对比分析,总结出人工观测地温值与自动站数据差值较     

“ZDJ长期自记气候站”测温误差的对比分析

本文根据“ZDJ长期自记气候站”(以下简称ZDJ)的温度记录和同步对比观测的百叶箱等的温度资料,计算分析几种温度的均方差及其变化规律,以及在不同条件下温度日变化特点,并从辐射和滞后性方面分析其误差原因。进而计算ZDJ自记温度与同步对比观测温度值的相关系数,建立相应的线性回归方程,在适当范围内,该方程可作为ZDJ测温误差的订正公式。     

洛川国家基准气候站迁站数据对比分析

利用2013年洛川国家基准气候站迁站前后气温、相对湿度、降水量、风向风速等观测资料对比分析,发现新站月平均气温、月最低气温、降水量、2min月平均风速、最大风速大于旧站,大风日多于旧站,6—8月最高气温、相对湿度小于旧站,新旧站风向有显著差异。造成迁站前后气象要素差异的原因,主要是观测场周围环境、下垫面性质改变,海拔高度变化对气象要素的影响不明显。     

地面遥测自动站和人工站数据分析

对博罗站2005年新安装并投入业务运行的遥测站数据与人工站的数据进行对比,分析了造成其差异的原因。     

赤峰市自动站与人工站的地面观测对比分析

文章通过对自动观测与人工观测资料的对比,寻找其规律,并查找观测中仪器、人为等因素造成的误差。为自动站代替人工站的观测提供准确数据、平均误差、预报规律和技术参考。     

区域自动站雨量资料质量控制方法及应用

针对翻斗式雨量计测量地面降雨量时出现误差的原因,介绍了石家庄市区域自动站雨量资料质量控制系统流程、有关质量控制技术及最终数据的输出。提出均值与范围值检查方法,并将时间一致性与内部一致性检查纳入空间一致性检查过程中。该系统人机交互界面友好,自动化程度高,能较好地检出自动站中雨量资料的异常值,保证了区域自动站雨量资料在决策及公共气象服务中的准确、及时和可视性。     

内蒙古自动站与人工观测数据差异对比分析

利用2006年内蒙古自治区共36个自动站和人工站平行观测资料,对观测得到的气象要素进行了统计和评估。通过分析气温、气压、相对湿度、风等要素的对比差值及其标准差、对比差值的频次分布和空间分布等,探讨自动站与人工观测数据差异的可能原因。结果表明：内蒙古自动观测与人工观测各气象要素均存在一定的差异,对所有台站平均而言,其差异均在自动站差值允许范围之内。产生差异的原因：观测仪器结构与观测原理差异、观测时空差异、观测方式差异等,在将人工观测数据与自动观测数据连续使用时,需要根据当地情况进行适当订正,以确保资料的连续性。     

Intercomparison of Two Box Models of the Chemical Evolution in Biomass-Burning Smoke Plumes

Results from two independently developed biomass-burning smoke plume models are compared. Model results were obtained for the temporal evolution of two nascent smoke plumes originating from significantly different fire environments (an Alaskan boreal forest and an African savanna). The two smoke plume models differed by 1%–10% for [O₃], with similar differences for NO _x and formaldehyde (relative percent differences). Smaller intermodel differences were observed for the African savanna smoke plume as compared to the plume from the Alaskan boreal fire. Mechanistic differences between the models are heightened for the Alaskan smoke plume due to the higher VOC emission ratios as compared to the African savanna fire. The largest deviations result from the differences in oxidative photochemical mechanisms, with a smaller contribution attributable to the calculation of photolysis frequencies. The differences between the two smoke plume models are significantly smaller than the uncertainties of available photokinetic data or field measurements. Model accuracy depends most significantly on having the fullest possible VOC data, a requirement that is constrained by currently available instrumentation.     

春季地气温差与长江中下游夏季旱涝异常的相关

利用1957-2006年50年的地温、气温和降水资料,分析了中国区域春季地气温差的分布特征,并利用线性相关和奇异值分解方法对春季地气温差与夏季降水的关系进行了探讨。结果表明：中国大陆春季地气温差分布与地势大体吻合。在长江中下游为涝年时,青藏高原春季的地气温差偏大,而黄淮流域的春季地气温差偏小,与青藏高原相反。青藏高原春季的地气温差与长江中下游地区夏季降水存在显著的正相关,即春季青藏高原地区地气温差较大（小）,长江流域的夏季降水会比正常年份偏多（少）,青藏高原春季地气温差对长江中下游夏季降水有一定的指示意义。     

自动气象站温湿传感器校准（更换）对人工和自动站对比差值的影响

选取陕西省5个基准站2003年1月至2007年12月自动站和人工站平行观测气温和相对湿度资料,研究同一地点温湿传感器校准(更换)后人工站和自动站月对比差值的变化。研究表明,温湿传感器校准(更换)后易形成两个不同的人工与自动站对比差值序列,对比差值突变的节点是今后进行单站资料订正非常关健的依据。     

Origin of regional climate differences: role of boundary conditions and model formulation in two GCMs

Model differences in projections of extratropical regional climate change due to increasing greenhouse gases are investigated using two atmospheric general circulation models (AGCMs): ECHAM4 (Max Planck Institute, version 4) and CCM3 (National Center for Atmospheric Research Community Climate Model version 3). Sea-surface temperature (SST) fields calculated from observations and coupled versions of the two models are used to force each AGCM in experiments based on time-slice methodology. Results from the forced AGCMs are then compared to coupled model results from the Coupled Model Intercomparison Project 2 (CMIP2) database. The time-slice methodology is verified by showing that the response of each model to doubled CO₂ and SST forcing from the CMIP2 experiments is consistent with the results of the coupled GCMs. The differences in the responses of the models are attributed to (1) the different tropical SST warmings in the coupled simulations and (2) the different atmospheric model responses to the same tropical SST warmings. Both are found to have important contributions to differences in implied Northern Hemisphere (NH) winter extratropical regional 500 mb height and tropical precipitation climate changes. Forced teleconnection patterns from tropical SST differences are primarily responsible for sensitivity differences in the extratropical North Pacific, but have relatively little impact on the North Atlantic. There are also significant differences in the extratropical response of the models to the same tropical SST anomalies due to differences in numerical and physical parameterizations. Differences due to parameterizations dominate in the North Atlantic. Differences in the control climates of the two coupled models from the current climate, in particular for the coupled model containing CCM3, are also demonstrated to be important in leading to differences in extratropical regional sensitivity.     

National leverage points to reduce global pesticide pollution

There is an urgent need to reduce the environmental risk of pesticide pollution worldwide. We here explore national leverage points, using a novel dataset of 21.4 million georeferenced grid cells and a spatial regression discontinuity design. Our analysis lets us separate how much cross-country differences in the risk of pesticide pollution are caused by differences in countries’ agricultural systems and policies and how much is explained by other factors, such as environmental differences between the countries for example (e.g. pest pressures). We estimate that a third of the global cross-country differences in the pesticide pollution risk are caused by differences in countries’ agricultural systems and policies. The main explanations, and thus leverage points for policies, are differences in countries’ pesticide regulations, their share of organic farming, and type of crops that are grown. We find a trade-off between pesticide pollution risk and soil erosion only in the Americas and in Asia, but not elsewhere, and we do not find a trade-off between pesticide pollution risk and crop yield gaps.     

自动与人工观测气压的差异及原因分析

利用全国373个基准基本站自动与人工平行观测期间的气压对比观测资料,进行了自动与人工观测气压的差异分析,重点从本站气压计算公式和环境温度方面分析了两种观测方式引起气压观测数据差异的原因。结果表明:(1)自动观测的气压值比人工观测气压值普遍偏低0.1～0.2 hPa。日最低气压差异最大,可达到0.34 hPa。自动与人工观测气压的差值有较明显的日变化和季节变化;(2)从分布区域看,自动与人工观测气压差异较大的区域位于海拔较高的西部地区,我国中东部地区则差异较小,绝大多数在0.2 hPa以内;(3)由于人工观测气压计算公式的问题,在2004年之前人工观测的本站气压值偏大,海拔高度越高的地方,偏大程度越高。统计结果还表明,30℃以上的高温环境和-30℃以下的低温环境,自动与人工观测气压差异明显。     

Analysis of Urban Atmosphere Plume Concentration Fluctuations

Concentration variability in the fast-response tracer dataset for continuous, near-surface, point source releases in the urban core from the Joint Urban 2003 field study is analyzed. Concentration variability for conditionally and unconditionally sampled time series is characterized by probability densities, concentration fluctuation intensity, skewness, and kurtosis. Significant day-night differences in plume dispersion are observed. Relative to daytime, nighttime plumes were more likely to have reduced concentration fluctuation intensities, higher normalized surface concentrations, suppressed vertical mixing, and a greater prevalence of Gaussian-like distributions rather than log-normal or mixed mode distributions. This was in spite of the similar stability and turbulence conditions in the urban core for day and night. The potential roles of flow meander and thermal stability in explaining these differences are examined. Probability densities of concentration are found to be a strong function of fluctuation intensity. There are few differences in probability densities between day and night when classified by fluctuation intensity. There are no appreciable differences between conditional and unconditional probability densities and only small differences between conditional and unconditional sampling statistics relative to the larger differences usually observed in more homogeneous settings. Fluctuation intensity, skewness, and kurtosis are higher for the daytime experiments, and closer to the source, but show little difference between conditional and unconditional results over most of their range of values. The log-normal distribution provides a better overall fit to a broader range of the dataset than the exponential or clipped-normal distributions.     

用初估场对比中芬探空仪温度和位势高度记录

对部分高空台站2007—2009年近3年探空记录的统计分析表明:邻近测站同一型号探空仪的温度和位势高度记录与6 h数值预报初估场的平均偏差一致,但不同型号探空仪记录与初估场的平均偏差存在明显差异,因此可以利用初估场进行邻近测站不同型号探空仪之间的间接对比。该文利用初估场与台站探空记录的差值,分析了使用芬兰Vaisala公司RS92型探空仪的中国香港站与邻近的使用L波段探空仪的梧州、汕头、东源、阳江4站2年的温度和位势高度记录的系统差,结果表明:19:00(北京时,下同),L波段探空仪的温度和位势高度记录在平流层分别偏低达1℃和30 gpm;07:00,L波段探空仪的温度记录在对流层偏高0.4℃,导致其位势高度记录也在对流层偏高;两套设备的系统差不仅有显著的日夜差异和季节性差异,也存在一定的年际差异。     

Effects of Different Initial Fields on GRAPES Numerical Prediction

In this paper,a heavy rainfall process occurring in the Huaihe River Basin during 9-10 July 2005 is studied by the new generation numerical weather prediction model system-GRAPES,from the view of different initial field effects on the prediction of the model.Several numerical experiments are conducted with the initial conditions and lateral boundary fields provided by T213 L31 and NCEP final analyses,respectively. The sensitivity of prediction products generated by GRAPES to different initial conditions,including effects of three-dimensional variational assimilation on the results,is discussed.After analyzing the differences between the two initial fields and the four simulated results,the memonic ability of the model to initial fields and their influences on precipitation forecast are investigated.Analyses show the obvious differences of sub-synoptic scale between T213 and NCEP initial fields,which result in the corresponding different simulation results,and the differences do not disappear with the integration running.It also shows that for the same initial field whether it has data assimilation or not,it only obviously influences the GRAPES model results in the initial 24 h.Then the differences reduce.In addition,both the Iocation and intensity of heavy rain forecasted by GRAPES model Further is very close to the fact,but the forecasting area of strong torrential rain has some differences from the fact.For the same initial field when it has assimilation, the 9-12-,12-24-,and 0-24-h precipitation forecasts of the model are better than those without assimilation. All these suggest that the ability of GRAPES numerical prediction depends on the different initial fields and lateral boundary conditions to some extent,and the differences of initial fields will determine the differences of GRAPES simulated results.