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1.
中国地球气候系统模式的发展及其模拟和预估 总被引：4，自引：0，他引：4
周天军 陈梓明 邹立维 陈晓龙 俞永强 王斌 包庆 鲍颖 曹剑 何编 胡帅 李立娟 李建 林岩銮 马利斌 乔方利 容新尧 宋振亚 唐彦丽 吴波 吴统文 辛晓歌 张贺 张明华 《气象学报》2020,78(3):332-350
地球气候系统模式是开展多学科、多圈层集成研究的重要平台,其发展是国际地学领域特别是全球变化领域竞争的前沿。中国的地球气候系统模式研发工作始于20世纪80年代,最近10年得到快速发展。研发格局上已经形成中国科学院、有关部委和高校三足鼎立的局面。文中在简要回顾中国地球气候系统模式早期发展历史的基础上,总结了中国参加第6次耦合模式比较计划的9个地球气候系统模式的技术特点,初步评估了中国4个模式对全球和东亚气候模拟的基本性能,分析了其在4种共享社会经济路径情景下对全球降水与温度的预估变化及其与平衡态气候敏感度的联系。最后,结合国际态势,从发展的角度提出未来中国气候模式研发工作需要加强的8个方向。 相似文献
2.
南海及周边海域融合海表温度产品的验证与互较 总被引：1，自引：0，他引：1
利用2008年—2009年Argo、Argos现场观测海表面温度SST,对OSTIA、MISST、MWSST以及NGSST4种融合SST产品在南海及其周边海域的适用性进行评估。验证结果表明,4种融合SST产品在外海的均方根误差RMS介于0.3—1.0℃,bias介于-0.1—0.6℃;除了NGSST在近岸出现明显暖偏外,其他3种融合SST与现场SST基本一致,OSTIA与现场SST的偏差为最小。对4种融合SST产品彼此间的互较也表明,它们在水深大于80 m的海区没有显著性差异,但彼此间的偏差会随水深变浅而增大。此外,各产品间偏差在冬季最大,夏季最小。本文为具有高时空覆盖度的融合SST产品在南海及其周边海域的应用提供了一个可靠的依据。 相似文献
3.
WMO第八届阳江国际探空比对辅助遥感综合试验 总被引：1，自引：0，他引：1
第八届阳江国际探空比对辅助遥感综合试验为分析探空仪系统在高空出入云的温湿特性,评估高层云红外辐射对温度传感器的影响以及湿度传感器的系统偏差提供有力帮助。通过试验,还评估了国产X波段双偏振雷达与毫米波云雷达的优缺点和性能差异,以及国产多普勒激光雷达、微脉冲激光雷达的探测性能和应用能力,在改进微波辐射计温湿反演算法、X波段偏振雷达参数的云中粒子相态模糊逻辑识别算法,以及多普勒天气雷达风场反演、云分类算法、高空业务测风算法等方面开展广泛研究并取得一定进展。试验还利用先进的各类遥感设备对阳江热带地区的云、局地对流以及海陆风系统的结构进行了观测和分析,取得了较好的研究结果。 相似文献
4.
Elsa S. Culler Andrew M. Badger Justin Toby Minear Kristy F. Tiampo Spencer D. Zeigler Ben Livneh 《水文研究》2021,35(7):e14260
Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall-triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select from a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide-triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity–duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of 177 reported landslides across the continental United States and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296 mm with an average range of 51 mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8 mm/h and as much as 57 mm/h. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity–duration storm thresholds, but all products exhibited hit ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms. 相似文献
5.
Genevieve Ali Doerthe Tetzlaff Laura Kruitbos Chris Soulsby Sean Carey Jeff McDonnell 《水文科学杂志》2013,58(1):56-72
AbstractSeasonality is an important hydrological signature for catchment comparison. Here, the relevance of monthly precipitation–runoff polygons (defined as scatter points of 12 monthly average precipitation–runoff value pairs connected in the chronological monthly sequence) for characterizing seasonality patterns was investigated to describe the hydrological behaviour of 10 catchments spanning a climatic gradient across the northern temperate region. Specifically, the research objectives were to: (a) discuss the extent to which monthly precipitation–runoff polygons can be used to infer active hydrological processes in contrasting catchments; (b) test the ability of quantitative metrics describing the shape, orientation and surface area of monthly precipitation–runoff polygons to discriminate between different seasonality patterns; and (c) examine the value of precipitation–runoff polygons as a basis for catchment grouping and comparison. This study showed that some polygon metrics were as effective as monthly average runoff coefficients for illustrating differences between the 10 catchments. The use of precipitation–runoff polygons was especially helpful to look at the dynamics prevailing in specific months and better assess the coupling between precipitation and runoff and their relative degree of seasonality. This polygon methodology, linked with a range of quantitative metrics, could therefore provide a new simple tool for understanding and comparing seasonality among catchments.Editor Z.W. Kundzewicz; Associate editor K. HealCitation Ali, G., Tetzlaff, D., Kruitbos, L., Soulsby, C., Carey, S., McDonnell, J., Buttle, J., Laudon, H., Seibert, J., McGuire, K., and Shanley, J., 2013. Analysis of hydrological seasonality across northern catchments using monthly precipitation–runoff polygon metrics. Hydrological Sciences Journal, 59 (1), 56–72. 相似文献
6.
Before data from satellites can be used with confidence in dynamical studies of the middle atmosphere an assessment of their reliability is necessary. To this end, independently analysed data from different instruments may be compared. In this paper, this is done for the Southern Hemisphere as a prelude to the dynamical studies of the middle atmosphere being fostered by the MASH project of the Middle Atmosphere Program. Data from two infrared radiometers are used: a limb scanner (LIMS) and a nadir sounder (SSU). While there is usually qualitative agreement between basic fields (temperatures, winds), substantial quantitative differences are found, with more pronounced differences in fields of Eliassen-Palm flux divergence and Ertel's potential vorticity.The fidelity of the base-level analysis to which satellite data are tied is important for calculating quantities of relevance to dynamical theory. In the Southern Hemisphere, conventional data are sparse and, through the analysis procedure, this introduces errors into derived fields for the middle atmosphere. The impact of using base-level analyses from different sources is assessed. Large discrepancies are found in fields computed by differentiation.Several techniques are suggested whereby the reliability of fields derived from satellite data may be gauged. 相似文献
7.
NCEP/NCAR逐时分析与中国实测地表温度和地面气温对比分析 总被引：3，自引：0，他引：3
美国国家环境预报中心(NCEP) 和国家大气中心(NCAR) 的全球分析资料,不仅应用于气候模拟和预测研究中而且也可作为卫星遥感云检测的初始场资料.通过对2005年NCEP逐6小时全球最终分析资料(FNL)与中国753个台站实测资料的地表温度和地面1.5m高气温进行Cressman插值, 从时次变化和空间变化等方面系统地分析和比较了这一年间NCEP分析值与中国区域内观测值之间的差异, 得到结果: NCEP分析地表温度较观测值普遍偏低, 而地面气温NCEP分析值的空间分布大致表现为在北部地区大于观测值、而南部地区小于观测值;就2005年季节变化而言,NCEP分析值在夏季比冬季符合得好,而在我国东南部比东北、西北符合得好;从时次上看,地温和气温都呈现出随着时次推进(从2时到20时),正值区(NCEP分析值-实测值＞0)减弱、负值区(NCEP分析值-实测值＜0)加强的趋势;而通过标准化均方根误差的分析,可以知道气温的NCEP分析资料在我国可行性比地温要好. 相似文献
8.
升降轨PSInSAR时序分析获得的同一地区2组监测结果分别为升轨和降轨下的地表形变速率与累积变形量。针对研究区地面以下沉为主,水平方向变形极为微小的特点,将视线向(line of sight,LOS)变形转换为垂向的下沉值,以此进行升降轨模式下2组观测值的比较与精度检验。在此基础上,将相干目标的2组观测序列数据融合以实现加密观测。研究结果表明:升降轨模式下沉降速率观测值的互检验精度优于2 mm;2组观测序列数据的融合结果进一步揭示了相干目标在时域上的非线性沉降特征。 相似文献
9.
The successful launch and commissioning of the first geostationary meteorological satellite of Korea has the potential to enhance earth observation capability over the Asia Pacific region. Although the specifications of the payload, the meteorological imager(MI), have been verified during both ground and in-orbit tests, there is the possibility of variation and/or degradation of data quality due to many different reasons, such as the accumulation of contaminants, the aging of instrument components, and unexpected external disturbance. Thus, for better utilization of MI data, it is imperative to continuously monitor and maintain the data quality. As a part of such activity, this study presents an inter-calibration, based on the Global Space-based Inter-Calibration System(GSICS), between the MI data and the high quality hyperspectral data from the Infrared Atmospheric Sounding Interferometer(IASI) of the Metop-A satellite. Both sets of data, acquired for three years from April 2011 to March 2014, are processed to prepare the matchup dataset, which is spatially collocated, temporally concurrent,angularly coincident, and spectrally comparable. The results show that the MI data are stable within the specifications and show no significant degradation during the study period. However, the water vapor channel shows a rather large bias value of-0.77 K, with a root-mean-square difference(RMSD) of around 1.1 K, which is thought to be due to the shift in the spectral response function. The shortwave channel shows a maximum RMSD of around 1.39 K, mainly due to the coarse digitization at the lower temperature. The inter-comparison results are re-checked through a sensitivity analysis with different sets of threshold values used for the matchup dataset. Based on this, we confirm that the overall quality of the MI data meets the user requirements and maintains the expected performance, although the water vapor channel requires further investigation. 相似文献
10.
《International Journal of Digital Earth》2013,6(6):476-494
In recent years, algorithms have been developed to derive land surface temperature (LST) from geostationary and polar satellite systems. However, few works have addressed the intercomparison between Geostationary Operational Environmental Satellites (GOES) and the available suite of polar sensors. In this study, differences in LSTs between GOES and MODerate resolution Imaging Spectroradiometer (MODIS) have been compared and also evaluated against ground observations. Due to the lack of split-window (SW) channels in the GOES M (12)-Q era, a dual-window algorithm using a mid-infrared 3.9 µm channel is compared with traditional SW algorithm. It is found that the differences in LST between different platforms are bigger during daytime than those during nighttime. During daytime, LSTs from GOES with the dual-window algorithm are warmer than MODIS LSTs, while LSTs from the SW algorithm are close to MODIS LSTs. The difference during daytime is found to be related to anisotropy in satellite viewing geometry, and land surface properties, such as vegetation cover and especially surface emissivity at middle infrared (MIR) channel. When evaluated against ground observations, the standard deviation (precision) error (2.35 K) from the dual window algorithm is worse than that (1.83 K) from the SW algorithm, indicating the lack of split-window channel in the GOES M(12)-Q era may degrade the performance of LST retrievals. 相似文献