A Note on Reviving the Goddard Satellite-Based Surface Turbulent Fluxes （GSSTF） Dataset

Accurate sea surface flux measurements are crucial for understanding the global water and energy cycles. The oceanic evaporation, which is a major component of the global oceanic fresh water flux, is useful for predicting oceanic circulation and transport. The global Goddard Satellite-based Surface Turbulent Fluxes Version-2 (GSSTF2; July 1987--December 2000) dateset that was officially released in 2001 has been widely used by scientific community for global energy and water cycle research, and regional and short period data analyses. We have recently been funded by NASA to resume processing the GSSTF dataset with an objective of continually producing a uniform dataset of sea surface turbulent fluxes, derived from remote sensing data. The dataset is to be reprocessed and brought up-to-date (GSSTF2b) using improved input datasets such as a recently upgraded NCEP/DOE sea surface temperature reanalysis, and an upgraded surface wind and microwave brightness temperature V6 dataset (Version 6) from the Special Sensor Microwave Imager (SSM/I) produced by Remote Sensing Systems (RSS). A second new product (GSSTF3) is further proposed with a finer temporal (12-h) and spatial (0.25^ox0.25^o) resolution. GSSTF2b (July 1987--December 2008) and GSSTF3 (July 1999--December 2009) will be released for the research community to use by late 2009 and early 2011, respectively.     

Bulk Transfer Relations for the Roughness Sublayer

In the roughness sublayer (RSL), Monin–Obukhov surface layer similarity theory fails. This is problematic for atmospheric modelling applications over domains that include rough terrain such as forests or cities, since in these situations numerical models often have the lowest model level located within the RSL. Based on empirical RSL profile functions for momentum and scalar quantities, and scaling the height with the RSL height z _*, we derive a simple bulk transfer relation that accounts for RSL effects. To verify the validity of our approach, these relations are employed together with wind speed and temperature profiles measured over boreal forest during the BOREAS experimental campaign to estimate momentum and heat fluxes. It is demonstrated that, when compared with observed flux values, the inclusion of RSL effects in the transfer relations yields a considerable improvement in the estimated fluxes.     

Errors and correction of precipitation measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.     

Surface and groundwater quality characterization of Deoria District,Ganga Plain,India

A water quality investigation was carried out in the Deoria district, Ganga plain, to assess the suitability of surface and groundwaters for domestic, agricultural, and industrial purposes. As much as 50 representative samples from river and groundwater were collected from various stations to monitor the water chemistry of various ions, comprising Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃ ⁻, SO₄ ²⁻, NO₃ ⁻, Cl⁻, F⁻, and trace metals, such as Fe, Cu, Mn, Zn, Cd, and Pb. The results showed that electrical conductance (EC), total dissolved solids (TDS), HCO₃ ⁻, Mg²⁺, Na⁺, and total hardness (TH) are above the maximum desirable limit, and apart from Fe and Mn all other trace metals are within the maximum permissible limit for drinking water. The calculated values for sodium absorption ratio (SAR), salinity, residual sodium carbonate (RSC), and permeability index (PI) indicate well to permissible use of water for irrigation. High values of Na%, RSC, and Mg-hazard (MH) at some stations restrict its use for agricultural purpose. Anthropogenic activities affect the spatial variation of water quality. Economic and social developments of the study area is closely associated with the characteristics of the hydrological network.     

流速逆变张量隐式求解方法及其在航道港池流场计算中的应用

运用高分辨率的边界适应网格进行流体动力学数值计算时,如何提高计算稳定性和减少计算量成为数值求解的关键性问题.在非正交的边界适应坐标系中,每个动量方程中同时出现了两个交叉方向的水位偏导数项,给隐式求解带来困难,而显式格式下的时间步长由于受与空间步长有关的Courant-Friedrichs-Lewy条件限制,计算量成倍增加.本文从广义曲线坐标系下浅海动力学方程组出发,导出了流速的逆变张量所满足的动量方程组,使方程中的水位偏导数项变成了沿某一协变基向量方向占优的形式,方便地采用了交替方向隐式差分格式,从而提高了计算稳定性并减小了计算量.本文通过对澳门海域航道和港池中流场的计算,证实了该模式是一种进行高分辩率数值计算的有效方法.     

Assessment of rock slope stability by probabilistic-based Slope Stability Probability Classification method along highway cut slopes in Adilcevaz-Bitlis (Turkey)

Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property. In rock slope engineering, stability evaluations are commonly performed by means of analytical or numerical analyses, principally considering the factor of safety concept. As a matter of fact, the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods. Additionally, the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept. In this study, slope stability of high and steep sedimentary rock cut slopes along a state highway in Adilcevaz-Bitlis (Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification (SSPC) system. The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements. Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities. Additionally, the probability of planar and toppling failures is significantly high with respect to the SSPC system. The stability problems along the investigated rock slopes were also verified by field reconnaissance. Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway. On the other hand, the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.     

青藏高原净生态系统碳交换量的遥感评估模型研究

青藏高原作为世界海拔最高的区域,是全球气候变化的敏感区之一。定量估算这一区域的净生态系统碳交换量（NEE）有利于理解陆地生态系统碳平衡对未来气候变化的响应。本文构建了一个模拟该地区NEE动态变化的净碳收支模型（NCBM）。该模型由来源于MODIS影像的增强型植被指数（EVI）、陆地表面水分指数（LSWI）以及来源于地面观测的空气温度和短波辐射共同驱动,并利用青藏高原地区的3种植被类型（包括高寒灌丛、高寒湿地和高寒草甸）的碳通量长期观测数据对模型进行了校准和验证。结果表明,在模型校准站点年,NCBM模型可以模拟NEE观测值81%的变化,均方根误差（RMSE）为0.03molC/m2/d,模型效率（EF）为0.81。在模型验证站点年,NCBM模型可以预测NEE观测值84%的变化,RMSE为0.03molC/m2/d,EF为0.81。在大多数情况下,NCBM模型可以清晰地模拟各植被类型的NEE季节和年际变化。此外,NCBM模型因为结构简单,模型驱动变量易于获取等优势,具有在区域尺度上模拟NEE时空变化的潜力。但是该模型还需要进一步的改进和发展,特别需要提高对植被非常稀疏地区NEE变化的模拟能力。     

Misconceptions about the Hubble recession law

Almost all astronomers now believe that the Hubble recession law was directly inferred from astronomical observations. It turns out that this common belief is completely false. Those models advocating the idea of an expanding universe are ill-founded on observational grounds. This means that the Hubble recession law is really a working hypothesis. One alternative to the Hubble recession law is the tired-light hypothesis originally proposed by Zwicky (Proc. Nat. Acad. Sci. 15:773, 1929). This hypothesis leads to a universe that is an eternal cosmos continually evolving without beginning or end. Such a universe exists in a dynamical state of virial equilibrium. Observational studies of the redshift-magnitude relation for Type Ia supernovae in distant galaxies might provide the best observational test for a tired-light cosmology. The present study shows that the model Hubble diagram for a tired-light cosmology gives good agreement with the supernovae data for redshifts in the range 0<z<2. This observational test of a static cosmology shows that the real universe is not necessarily undergoing expansion nor acceleration. An erratum to this article can be found at     

Seismic clusters and their characteristics at the Arabian Sea Triple Junction: Supportive evidences for plate margin deformations

The plate margin features defining the Arabian Sea Triple Junction (ASTJ) are: the Aden Ridge (AR), Sheba Ridge (SR) with their intervening Alula-Fartak Transform (AFT), Carlsberg Ridge (CR) and Owen Fracture Zone (OFZ). Exact nature of ASTJ is presently debated: whether it is RRF (ridge-ridge-fault) or RRR (ridge-ridge-ridge) type. A revised seismicity map for ASTJ is given here using data for a period little more than a century. “Point density spatial statistical criterion” is applied to short-listed 742 earthquakes (mb ≥ 4.3), 10 numbers of spatio-temporal seismic clusters are identified for ASTJ and its arms. Relocated hypocentres help better constraining the cluster identification wherever such data exist. Seismic clusters actually diagnose the most intense zones of strain accumulation due to far field as well as the local stress operating at ASTJ. An earthquake swarm emanating from a prominent seismic cluster below SR provides an opportunity to investigate the pore pressure diffusion process (due to the active source) by means of “r-t plot”. Stress and faulting pattern in the active zones are deduced from 43 CMT solutions. While normal or lateral faulting is characteristic for these arms, an anomalous thrust earthquake occurs in the triangular ‘Wheatley Deep’ deformation zone proximal to ASTJ. The latter appears to have formed due to a shift of the deformational front from OFZ towards a transform that offsets SR. Though ASTJ is still in the process of evolution, available data favour that this RRF triple junction may eventually be converted to a more stable RRR type.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.