Study Of `Soft' Night-Time Surface-Layer Decoupling Over Forest Canopies In A Land-Surface Model     

Yves Delage  Paul A. Bartlett  J. Harry McCaughey 《Boundary-Layer Meteorology》2002,103(2):253-276

The cause of a night-time land-surface model cold bias over forest canopies at threedifferent sites is studied in connection with various formulations of turbulent transferand the phenomenon of decoupling between the surface and the boundary layer. Themodel is the Canadian Land Surface Scheme (CLASS), a leading internationally knownmodel that has been tested over a variety of instrumented sites. The bias was first attributed to a deficient turbulent transfer and a few formulations were compared. One formulation is the classical log-linear profile with a sharp cut-off of the fluxes at a critical Richardsonnumber around 0.2, while in the other ones the flux decreases less rapidly with increasingstatic stability. While the surface-layer formulations have an impact on the modelled canopy temperature, other causes were found for the negative bias. The CLASS model neglected the heat capacity of the air trapped inside the canopy and its inclusion multiplied theeffective heat capacity of the canopy, by a factor ranging from 2.3 to 3.4 for the canopies studied, and reduced the error. A correction was also made to the air specific humidity at canopy level and the topsoil thermal conductivity was changed from that of organic matter to that of mineral soil. With these modifications, and using the incoming longwave radiative flux instead of the net longwave flux, the bias almost completely disappeared. Using ascheme with more heat transfer at large static stability, obtained by assuming that thefluxes decrease in magnitude with height in the surface layer, reduced the original biaswhile using the log-linear formulation amplified the cold bias. The impact of the turbulent transfer formulations is much reduced when they are applied to model runs in which the other above modifications have been made.The phenomenon of decoupling is presented and its understanding is complementedwith the new notions of `hard' versus `soft' decoupling and complete versus incompletedecoupling, depending on the impact decoupling has on the model and on the effectiveness of the model in achieving the decoupling. The geostrophic wind speed is a determiningfactor in separating cases of hard decoupling (rare) from the soft cases (frequent) while the completeness of the decoupling primarily depends on the form of the turbulent transfer curve as a function of static stability.  相似文献   

GPS网络RTK综合误差线性内插法模拟实验计算     

张照杰  徐治宝  魏世春  王霞 《测绘信息与工程》2008,33(1):14-15

讨论了综合误差内插法数学模型的正确性,进行了模拟计算,说明一般内插值均可满足通常工程的精度要求.  相似文献   

利用双频GPS数据研究区域电离层TEC变化规律     

SUN Zheng-ming  WANG Jian  GAO Jing-xiang 《测绘学院学报》2008,(3)

利用GPS双频观测数据分析了仪器偏差对计算电离层TEC的影响,结果表明忽略仪器偏差的影响不能正确反映测站上空电离层总电子含量的变化规律。验证了短期内仪器偏差的稳定性,并在此基础上研究了2005年太阳活动低峰年区域电离层VTEC的周年变化规律,揭示了电离层VTEC半年变化、季节性变化及冬季异常等现象。  相似文献   

一种自适应两阶段卡尔曼滤波算法     

CAO Yi-zhi  SUI Li-fen 《测绘学院学报》2008,(6)

当动力学模型存在未知的随机系统偏差时,两阶段卡尔曼滤波要优于标准卡尔曼滤波。两阶段卡尔曼滤波的基础是准确的知道随机系统偏差的统计特性,这在实际过程中是很难做到的。提出了基于新息向量的自适应两阶段卡尔曼滤波。它不仅能够很好的估计随机系统偏差,而且在随机系统偏差的先验统计特性不准确时也能取得良好的效果。最后通过一个仿真算例,验证了自适应两阶段卡尔曼滤波的适用性。  相似文献   

Bias and precision of percentiles of bulk grain size distributions     

R. I. Ferguson  C. Paola 《地球表面变化过程与地形》1997,22(11):1061-1077

Percentiles such as D₅₀ and D₈₄, calculated from weights retained on different sieves, are widely used to characterize grain size distributions (GSDs) of bulk samples of sedimentary deposits or sediment fluxes. The sampling variability of such percentiles is not well known, and few sampling guidelines exist for reliable characterization of GSDs. We report results from computer sampling experiments on the variability of sample percentiles in different-sized samples from populations with a log-normal GSD by weight and different sorting coefficients. Sample sizes are scaled by the volume of a median-sized grain so that results can be applied to any log-normal GSD. Sampling is random for the GSD by number that is equivalent to a specified GSD by weight. Results show important differences from standard sampling theory applicable to pebble-count GSDs. In small bulk samples all percentiles, including the median, are underestimated (more so for smaller samples, coarser percentiles and poorer sorting), and precision does not improve with the square root of sample size until fairly large sample sizes are exceeded. Non-dimensional equations fitted by eye to the results give good approximations to expected bias and precision in any percentile from 50 to 95 for any given sample size and population sorting coefficient. They are inverted to estimate the sample size required to avoid significant bias, or achieve specified precision, in any percentile of interest given estimates of the population D₅₀ and sorting coefficient. Target sample sizes are sometimes considerably smaller, but in other circumstances larger, than suggested by previous guidelines relating to estimation of the entire grain size distribution. Bias is likely in small samples of river bedload and good precision requires very large samples of poorly sorted gravel deposits. © 1997 John Wiley & Sons, Ltd.  相似文献   

GFS模式地形高度偏差对地面2 m气温预报的影响          下载免费PDF全文

智协飞  吴佩  俞剑蔚  慕建利  赵倩 《大气科学学报》2019,42(5):652-659

利用2016年1月1日—12月31日全球预报系统(GFS,Global Forecasting System)1～5 d的2 m气温预报资料,以及同期中国地面气象站2 m气温观测资料,研究模式地形高度偏差对地面2 m气温预报的影响。结果表明,较大模式地形高度偏差可严重影响2 m气温模式预报性能,导致较大预报误差。随着模式预报时效延长,2 m气温预报均方根误差也略有增加。比较模式地形高度偏差和预报时效对于模式预报性能的影响,发现模式地形高度偏差对于模式预报效果的影响更加显著。两种地形订正方案,即不做温度垂直订正的线性回归以及对温度进行垂直订正的线性回归都能显著减小2 m气温模式预报的误差,后者的订正效果更好。  相似文献   

Evaluation of bias on the probability of collapse from amplitude scaling using spectral-shape-matched records     

Héctor Dávalos  Eduardo Miranda 《地震工程与结构动力学》2019,48(8):970-986

Although for many years it was thought that amplitude scaling of acceleration time series to reach a target intensity did not introduce any bias in the results of nonlinear response history analyses, recent studies have showed that scaling can lead to an overestimation of deformation demands with increasing scale factors. Some studies have suggested that the bias can be explained by differences in spectral shape between the response spectra of unscaled and scaled records. On the basis of these studies, some record selection procedures assume that if records are selected using spectral-shape-matching procedures, amplitude scaling does not induce any bias on the structural response. This study evaluates if bias is introduced on lateral displacement demands and seismic collapse risk estimates even when spectral shape is carefully taken into consideration when selecting ground motions. Several single-degree-of-freedom and multiple-degree-of-freedom systems are analyzed when subjected to unscaled and scaled ground motions selected to approximately match the mean and the variance of the conditional spectrum at the target level of intensity. Results show that an explicit consideration of spectral shape is not enough to avoid a systematic overestimation of lateral displacement demands and collapse probabilities as the scale factor increases. Moreover, the bias is observed in practically all cases for systems with strength degradation and it increases with decreasing period and decreasing lateral strength relative to the strength required to remain elastic. Key reasons behind the bias are presented by evaluating input energy, causal parameters, and damaging pulse distributions in unscaled and scaled ground motion sets.  相似文献   

Improving global rainfall forecasting with a weather type approach in Japan     

Jean-Francois Vuillaume  Srikantha Herath 《水文科学杂志》2017,62(2):167-181

An automated version of the weather type classification scheme was performed over Japan to characterize daily circulation conditions. A daily gridded field of mean sea-level pressure (MSLP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis dataset (ERA-interim) and the THORPEX Interactive Grand Global Ensemble (TIGGE) daily forecast dataset were used. The weather type is advantageous as it provides an opportunity to improve global rainfall prediction by refining statistical bias correction. We distinguished 11 weather types: anticyclone, cyclone, hybrid and eight purely wind directions. The results indicate that the main weather types contributing to the total volume of rainfall are cyclone, hybrid, purely westerly and northwest winds. A gamma-based bias correction decreases the global rainfall forecast root mean square by 10%, while specific weather type gamma bias correction accounts for 5–10% root mean square error reduction, with a total decrease of errors up to a maximum of 20%. Both global and weather type bias corrections improve the extreme dependency scores (EDS), but for different extreme rainfall thresholds. The study advocates the use of weather type bias-correction methods for extreme event rainfall intensity corrections higher than 100 mm/d.