Ensemble retrieval of atmospheric temperature profiles from AIRS

ABSTRACT Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmo spheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an ensemble methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function （PDF） is used to select the optimal profile from the ensemble retrievals. The ensemble retrieval algorithm contains four steps： （1） regression retrieval for original first guess; （2） perturbation of the original first guess to generate new first guesses （ensemble first guesses）; （3） using the ensemble first guesses and nonlinear iterative physical retrieval to generate ensemble physical results; and （4） the final optimal profile is selected from the ensemble physical results by using PDE Temperature eigenvectors （EVs） were used to generate the pertur- bation and generate the ensemble first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder （AIRS）, the ensemble retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal （CombOpt） profile and a mean optimal （MeanOpt） profile of all ensemble physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal （FinOpt） profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.     

Relationships between Interannual and Intraseasonal Variations of the Asian-Western Pacific Summer Monsoon Hindcasted by BCC_CSM1.1（m）

Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability （IAV） and intraseasonal variability （ISV） of the Asian-western Pacific summer monsoon are diagnosed. Predictions show reasonable skill with respect to some basic characteristics of the ISV and IAV of the western North Pacific summer monsoon （WNPSM） and the Indian summer monsoon （ISM）. However, the links between the seasonally averaged ISV （SAISV） and seasonal mean of ISM are overestimated by the model. This deficiency may be partially attributable to the overestimated frequency of long breaks and underestimated frequency of long active spells of ISV in normal ISM years, although the model is capable of capturing the impact of ISV on the seasonal mean by its shift in the probability of phases. Furthermore, the interannual relationships of seasonal mean, SAISV, and seasonally averaged long-wave variability （SALWV; i.e., the part with periods longer than the intraseasonal scale） of the WNPSM and ISM with SST and low-level circulation are examined. The observed seasonal mean, SAISV, and SALWV show similar correlation patterns with SST and atmospheric circulation, but with different details. However, the model presents these correlation distributions with unrealistically small differences among different scales, and it somewhat overestimates the teleconnection between monsoon and tropical central-eastern Pacific SST for the ISM, but underestimates it for the WNPSM, the latter of which is partially related to the too-rapid decrease in the impact of E1 Nifio-Southern Oscillation with forecast time in the model.     

Evaluation of cloud vertical structure simulated by recent BCC_AGCM versions through comparison with CALIPSO-GOCCP data

ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover （TCC）, middle cloud cover （MCC） and low cloud cover （LCC）, and that BCC_AGCM2.2 underestimated the global-mean high cloud cover （HCC）. The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing （RSCRF and RLCRF）. Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.     

大数据环境下道路场景高时空分辨率众包感知方法EI北大核心CSCD

道路场景作为人类发展演变中最重要、最复杂、最典型的载体之一,是道路基础设施与活动行为共同构成的综合体,链接和构建“人地关系”。道路场景感知从二维抽象简略到三维精细丰富、从静态过去式向动态现在时发展,成为智慧城市、智能交通、无人驾驶的关键技术支撑,是我国新型城镇化战略、交通强国战略的核心技术保障。本文立足于时空交通大数据,提出基于道路场景静态基础设施“形”和动态活动行为“流”的高时空分辨率道路场景感知方法。该方法从静态路网“形”角度,以“点-线-面-体”等要素为研究脉络,构建高精度道路地图众包感知的理论体系;在活动行为“流”感知上,突破传统的点模式分析局限,发展了道路网络空间活动流的时空建模与多尺度分析方法。本文揭示了静态基础设施“形”结构与动态活动行为“流”模式交互作用下的道路场景演化规律,形成以“形”控“流”、借“流”定“形”、“形”“流”叠置的高时空精度道路场景众包感知理论体系,为智慧城市、智能交通的发展提供核心技术与数据支撑。     

北斗三号卫星经验型太阳光压模型分析与精化

太阳光压摄动作为在轨导航卫星受到的最大的非保守力,是卫星精密定轨的重要误差源。ECOM模型、ECOM2模型,这两种经验型光压模型被广泛应用于导航卫星定轨。然而,ECOM模型和ECOM2模型分别是针对GPS和GLONASS卫星设计的,并不完全适用于我国北斗三号(BDS-3)卫星。针对五参数ECOM模型在BDS-3卫星低太阳高度角时期轨道不连续性增大的问题,本文提出在 D方向引入一阶周期项来吸收未被模型化光压加速度。结果表明,引入一阶余弦周期项 D_c,能将低太阳高度角时期CAST卫星的切向、法向、径向重叠轨道误差分别减小约60%、52%、29%。针对ECOM2模型中 D_2c和 D₀、D_2s和 B_s之间存在的强相关性,本文提出了不估计 D_2c参数的八参数ECOM2模型和不估计 D_2c与 D_2s的七参数ECOM2模型。结果表明,相较九参数ECOM2模型,不估计 D_2c参数的八参数ECOM2模型能够将CAST卫星和SECM卫星径向重叠轨道误差分别减少约18%和27%。在此基础上,继续移除 D_2s后(七参数ECOM2),径向重叠轨道误差可进一步减小5.2%~8.5%。综合考察重叠轨道精度和SLR检核精度,不顾及 D_2c和 D_2s的七参数ECOM2模型表现最佳。CAST卫星和SECM卫星重叠轨道切向、法向、径向精度分别为5.0、3.4、1.4 cm和5.4、3.5、1.5 cm;SLR检核残差标准差分别为3.1~3.2 cm、4.4~4.7 cm。     

瞬变电磁法在复杂构造背景下深部找矿中的应用

大电流大定源回线瞬变电磁法具有装置简单,探测深度大,工作效率高,对低阻目标体分辨力高等优点;通过应用实例,介绍了该方法在云南某高海拔高起伏复杂构造地区的应用,说明了该方法的切实有效性。     

苏丹北部红海州16区块地质特征及找矿方法探讨

16区块位于苏丹北部红海州,区内已发现金矿点11处,铜矿点6处,优选出了4个成矿远景区,评价了小型金矿床1处。该文介绍了16区的成矿地质条件、矿化特征及矿化类型,以已评价的小型金矿床为例讨论了该区金矿成矿作用及控矿因素,指出该区具备良好的金铜矿成矿远景。针对该区实际情况提出遥感解译配合化探测量、物探测量是选勘查靶区的有效方法,地表槽探揭露配合中深部钻探控制是必要的勘查手段。     

重庆洪官渡铝土矿床镓元素地球化学特征及其成矿环境探讨

重庆洪官渡铝土矿床伴生Ga含量普遍超过了工业综合利用指标。Ga与Cr、TiO2呈强正相关,与V呈中等程度的正相关,与Al2O3、Fe2O3不相关。根据Sr/Ba、u/Th、Ga/Al等地球化学指标值特征,判断该铝土矿床的含矿岩系属海陆交互沉积,但以陆相沉积为主;同时,洪官渡铝土矿床是在以淡水作用为主的弱酸性氧化环境的中形成。     

四川盆地震旦系灯影组葡萄状白云岩成因

四川盆地震旦系灯影组发育巨厚的白云岩,其中灯影组二段和四段发育大量具有各种形态的葡萄状白云岩,其直径最长可达75cm,有的平行于层面,有的穿层。剖面资料表明,葡萄状白云岩发育多期等厚环边胶结物,中部残留大量未充填的不规则洞穴,这成为与岩溶喀斯特作用相关的地下溶蚀作用的证据。围岩泥晶白云石为早期海水中原生结晶的产物,后来的胶结物可划分为4期: (1)自泥晶化白云石(部分样品中可见)作为最早的一期胶结物,由于各种生物化学作用和生物作用的影响而紧贴着围岩发育;(2)第2期胶结物纤维状白云石可能为海水中直接沉淀的产物,经历后期成岩作用后,具有完全有序的结构,晶胞参数接近理想值;(3)细—中晶白云石为第3期胶结物,包含纤维状白云石溶蚀残余,形成于构造抬升之后的近地表大气淡水环境;(4)第4期胶结物中—粗晶白云石为埋藏环境下直接结晶的产物,充填了孔洞中心,残留部分未充填孔洞。灯影组受到了岩溶喀斯特作用、胶结作用以及白云石化作用等成岩作用的影响,其中与葡萄状白云岩有关的岩溶喀斯特作用对于灯影组储集层的发育至关重要。对灯影组葡萄状白云岩的研究,不仅有助于深入探讨灯影组储集层成因和演化及灯影组白云岩的成因,而且有助于指导四川盆地前寒武系油气勘探。