EAR70、CLDAS和ERA Interim表层土壤温度在中国地区的评估

本文利用2010—2015年2400多国家气象站逐小时观测数据对覆盖中国的EAR70、CLDAS和ERA Interim 3种表层土壤温度进行了评估和对比。结果表明：空间上CLDAS表层土壤温度精度最高（平均误差为-0.5 ℃，均方根误差为3.0 ℃，相关系数为0.96），受益于CLDAS高精度的陆面初始场，EAR70平均误差得到了改善；时间上ERA Interim再分析表层土壤温度在6:00和夏、秋季精度会明显下降，再分析表层土壤温度在数值较高时段表现出冷偏差，原因是模拟的土壤温度数值上升速度慢，对应的参数化方案有待改进。再分析表层土壤温度在东北地区冬季存在冷偏差，可能和积雪覆盖有关，陆面参数化方案也有待提高。在地形复杂的青藏高原地区，融合地面观测的CLDAS提高了大气驱动的质量进而改进了土壤的模拟。ERA Interim分辨率较粗不适合在青藏高原或者沿海地区使用，结合了CLDAS的EAR70在青藏高原精度提高。土壤表层温度的精度随着高精度的土壤状态初始场进入模式中时间延长会显著下降。因此，CLDAS的实时同化方式，能够有效提高在分析数据的精度。     

辽宁避暑旅游气候适宜度评价

利用辽宁省59个国家气象站2008—2017年6—8月逐时地面观测资料，综合考虑夏季气候舒适度和高影响天气对避暑旅游的不利影响，确定辽宁避暑旅游气候适宜度评价方法，分析了辽宁避暑旅游适宜度时空分布，为公众及旅游相关部门了解当地避暑旅游气候资源提供参考。研究表明：①辽宁避暑旅游适宜度由西北到东南逐渐增强， 59个地市（县）中，很适宜避暑的有14个，适宜避暑的有22个，较适宜避暑的有16个。②夏季辽宁大部避暑旅游气候舒适度较好，辽东和辽南气候舒适度优于辽宁中部和西部。辽宁东部的本溪和沿海的丹东、大连、葫芦岛和锦州南部气候舒适度等级最高，避暑气候条件更好。③辽宁夏季暴雨高风险区在东南部的宽甸、丹东和凤城一带。高温高风险区在朝阳大部和锦州西部。大风高风险区在铁岭北部、彰武、锦州、营口和长海。雷暴高风险区在铁岭、抚顺东部、朝阳西部和庄河一带。④6月、8月是辽宁适合避暑旅游的月份，尤其是 6月，避暑旅游适宜度最高，适宜面积最大。8月份次之， 7月避暑旅游适宜度较差。     

Efficient generation of conditional simulations by chebyshev matrix polynomial approximations to the symmetric square root of the covariance matrix

Consider the problem of generating a realization y₁ of a Gaussian random field on a dense grid of points ₁ conditioned on field observations y₂ collected on a sparse grid of points ₂. An approach to this is to generate first an unconditional realization y over the grid =_{1 2}, and then to produce y₁ by conditioning y on the data y₂. As standard methods for generating y, such as the turning bands, spectral or Cholesky approaches can have various limitations, it has been proposed by M. W. Davis to generate realizations from a matrix polynomial approximations to the square root of the covariance matrix. In this paper we describe how to generate a direct approximation to the conditional realization y₁, on ₁ using a variant of Davis' approach based on approximation by Chebyshev polynomials. The resulting algorithm is simple to implement, numerically stable, and bounds on the approximation error are readily available. Furthermore we show that the conditional realization y₁ can be generated directly with a lower order polynomial than the unconditional realization y, and that further reductions can be achieved by exploiting a nugget effect if one is present. A pseudocode version of the algorithm is provided that can be implemented using the fast Fourier transform if the field is stationary and the grid ₁ is rectangular. Finally, numerical illustrations are given of the algorithm's performance in generating various 2-D realizations of conditional processes on large sampling grids.     

突发性地面增温与临震前兆——以1988年澜沧、耿马7.6,7.2级地震为例

本文通过较多的地面温度资料分析,认为1988年11月6日澜沧、耿马地震前几天,震区及其周围大范围的突发性地面增温异常是一种临震前兆,总结了增温异常的时空演变规律与地震活动的关系,并对其形成机制提出初步想法     

近45 a来中国西北年极端高、低温的变化及对区域性增暖的响应

利用中国西北五省(区)1960-2004年129个台站逐日最低、最高温度资料,从中统计出年极端高温发生频次、年极端低温发生频次、年极端高温强度、年极端低温强度以及年极端高温和低温开始和结束日期,分析了它们近45 a来的变化情况。结果表明:近45 a来中国西北年极端高温发生频次的增加趋势是明显的,而年极端低温发生频次的减少趋势更显著;中国西北近45 a来年极端高温的强度在不断增强,而极端低温的强度在不断减弱;近45 a来中国西北年极端高温开始日期逐渐提前,结束日期逐渐推迟,而年极端低温的开始日期在逐渐推迟,结束日期在逐渐提前;年极端低温发生频次的减少对于西北区域增暖的响应比年极端高温发生频次增加更显著,而年极端低温强度的减弱要比年极端高温强度的增强对西北区域性增暖的响应偏弱,年极端高温发生频次的增加同年极端高温强度的增强对西北区域性增暖的响应程度基本相当。     

Statistical evaluation of methods for the calculation of static formation temperatures in geothermal and oil wells using an extension of the error propagation theory

The feasibility of using the more sophisticated weighted least-squares (WLS) model, as opposed to the traditional ordinary least-squares (OLS), in linear regressions of BHT data to estimate the static formation temperatures (SFT) was investigated. The most commonly used analytical methods (line-source; spherical and radial heat flow; and cylindrical heat source) were applied. Error propagation equations were derived to calculate errors in the time function of each method. These errors were combined with the BHT measurement errors to compute weighting factors for applying the WLS. Intercept uncertainties were estimated for all regressions using sets of synthetic and actual borehole logs taken from geothermal and oil applications. SFT computed with the spherical and radial heat flow method were generally greater than those from the other two methods.     

Water temperature behaviour in the River Loire since 1976 and 1881

Analysis of monthly mean river temperatures, recorded on an hourly basis in the middle reaches of the Loire since 1976, allows reconstruction by multiple linear regression of the annual, spring and summer water temperatures from equivalent information on air temperatures and river discharge. Since 1881, the average annual and summer temperatures of the Loire have risen by approximately 0.8?°C, this increase accelerating since the late 1980s due to the rise in air temperature and also to lower discharge rates. In addition, the thermal regime in the Orleans to Blois reach is considerably affected by the inflow of groundwater from the Calcaires de Beauce aquifer, as shown by the summer energy balance. To cite this article: F. Moatar, J. Gailhard, C. R. Geoscience 338 (2006).     

近几十年我国极端气温变化特征分区方法探讨

采用聚类统计检验分析和旋转主分量分析相结合确定中心站的方法,利用我国多年极端气温资料,对我国最高和最低气温年际变化型态进行区划。结果表明,这两种方法结合可以互相补充,使分区结果更具客观性。中国极端高温和极端低温年际变化分别可划为12和11个不同类型的区域,分别计算了各区域第一主成分的方差贡献率以及各区域之间的两两相关系数,检验证明分区是合理的。     

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.