基于多源卫星数据扎日南木错湖面变化和气象成因分析

利用Landsat(MSS、TM、ETM+)系列卫星和环境减灾卫星CCD遥感影像数据以及西藏扎日南木错地区近40年(1970-2011年)气象资料,分析湖泊面积的变化特征,并探讨湖泊面积变化的可能气象成因.结果表明,扎日南木错1975-2011年间经历了先萎缩后扩张的过程,湖泊面积呈增长趋势,增长面积为7.08 km2.扎日南木错流域在过去40多年里冰川在退缩,温度升高,降水量增加,而蒸发量和最大冻土深度减少.湖泊面积与年气温之间有显著的正相关关系,气温升高可能是湖面扩大的原因之一.     

Geoidal curvature radii from satellite data for different degrees of smoothing

Summary Radii of curvature and their anomalies of a smoothed geoidal surface are computed using Stokes's constants J _n ^(k) , S _n ^(k) of the Earth's body, obtained from satellite orbit dynamics[2]. Different degrees n of smoothing are used (n = 8, 12, 21). The notations are the same as in[4, 5].     

Integrating TRMM and MODIS satellite with socio-economic vulnerability for monitoring drought risk over a tropical region of India

Drought is a recurring feature of the climate, responsible for social and economic losses in India. In the present work, attempts were made to estimate the drought hazard and risk using spatial and temporal datasets of Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS) in integration with socio-economic vulnerability. The TRMM rainfall was taken into account for trend analysis and Standardized Precipitation Index (SPI) estimation, with aim to investigate the changes in rainfall and deducing its pattern over the area. The SPI and average rainfall data derived from TRMM were interpolated to obtain the spatial and temporal pattern over the entire South Bihar of India, while the MODIS datasets were used to derive the Normalized Difference Vegetation Index (NDVI) deviation in the area. The Geographical Information System (GIS) is taken into account to integrate the drought vulnerability and hazard, in order to estimate the drought risk over entire South Bihar. The results indicated that approximately 36.90% area is facing high to very high drought risk over north-eastern and western part of South Bihar and need conservation measurements to combat this disaster.     

On precursor of Kamchatkan volcanoes eruptions based on data from satellite monitoring

Kamchatka is one of the most active volcanic regions on the planet. Large explosive volcanic eruptions, in which the ash elevates up to 8?C15 km above sea level, occur here every 1.5 years. Study of eruptions precursors in order to reduce a volcanic risk for the population is an urgent problem of Volcanology. The available precursor of strong explosive eruptions of volcanoes, identified from satellite data (thermal anomaly), as well as examples of successful prediction of eruptions using this precursor, are represented in this paper.     

Online service for monitoring the ionosphere based on data from the global navigation satellite system

A service is described that makes possible the effective construction of a three-dimensional ionospheric model based on the data of ground receivers of signals from global navigation satellite positioning systems (GNSS). The obtained image has a high resolution, mainly because data from the IPG GNSS network of the Federal Service for Hydrometeorology and Environmental Monitoring (Rosgidromet) are used. A specially developed format and its implementation in the form of SQL structures are used to collect, transmit, and store data. The method of high-altitude radio tomography is used to construct the three-dimensional model. The operation of all system components (from registration point organization to the procedure for constructing the electron density three-dimensional distribution and publication of the total electron content map on the Internet) has been described in detail. The three-dimensional image of the ionosphere, obtained automatically, is compared with the ionosonde measurements, calculated using the two-dimensional low-altitude tomography method and averaged by the ionospheric model.     

地震地球物理监测数据各库数据差异原因

笔者在工作中发现,使用地震台站、区域地球物理台网、国家台网地震地球物理监测数据库中同一台站、同一测项、相同时段监测数据绘制曲线,存在曲线不一致现象,分析认为,存在差异的原因主要是,数据经审核、反馈、处理,再次上传各库过程中未及时核对、及时发现、及时覆盖,省地震局区域地球物理台网需定时检查、同步各库数据。     

Evaluation of efficiency of different estimation methods for missing climatological data

Reliable estimation of missing data is an important task for meteorologists, hydrologists and environment protection workers all over the world. In recent years, artificial intelligence techniques have gained enormous interest of many researchers in estimating of missing values. In the current study, we evaluated 11 artificial intelligence and classical techniques to determine the most suitable model for estimating of climatological data in three different climate conditions of Iran. In this case, 5 years (2001–2005) of observed data at target and neighborhood stations were used to estimate missing data of monthly minimum temperature, maximum temperature, mean air temperature, relative humidity, wind speed and precipitation variables. The comparison includes both visual and parametric approaches using such statistic as mean absolute errors, coefficient of efficiency and skill score. In general, it was found that although the artificial intelligence techniques are more complex and time-consuming models in identifying their best structures for optimum estimation, but they outperform the classical methods in estimating missing data in three distinct climate conditions. Moreover, the in-filling done by artificial neural network rivals that by genetic programming and sometimes becomes more satisfactory, especially for precipitation data. The results also indicated that multiple regression analysis method is the suitable method among the classical methods. The results of this research proved the high importance of choosing the best and most precise method in estimating different climatological data in Iran and other arid and semi-arid regions.     

Evaluation of hydrologic impact of an irrigation curtailment program using Landsat satellite data

Upper Klamath Lake (UKL) is the source of the Klamath River that flows through southern Oregon and northern California. The UKL Basin provides water for 81,000+ ha (200,000+ acres) of irrigation on the U.S. Bureau of Reclamation Klamath Project located downstream of the UKL Basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water rights calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance model with gridded precipitation and U.S. Geological Survey station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for 2004, 2006, 2008–2010 (base years), and 2013–2016 (target years) over irrigated areas above UKL. Our results indicate that the savings from the curtailment program over the June to September time period were highest during 2013 and declined in each of the following years. The total on-field water savings was approximately 60 hm³ in 2013 and 2014, 44 hm³ in 2015, and 32 hm³ in 2016 (1 hm3 = 10,000 m³ or 810.7 ac-ft). The instream water flow changes or extra water available were 92, 68, 45, and 26 hm³, respectively, for 2013, 2014, 2015, and 2016. Highest water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting extra water available from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. The Landsat-based ETa and other remote sensing datasets used in this study can be used to monitor crop water use at the irrigation district scale and to quantify water savings as a result of land-water management changes.     

Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

The spatial distribution of sub-pixel components has an impact on retrieval accuracy, and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index (LAI). To investigate this effect, we constructed three realistic scenarios with the same LAI values and other properties, except that the simulated plants had different distributions. We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor (BRF) datasets based upon these simulated scenes. The inversion was conducted using these data, which showed that spatial distribution affects retrieval accuracy. The inversion was also conducted for LAI based on charge-coupled device (CCD) data from the Environment and Disaster Monitor Satellite (HJ-1), which depicted both forest and drought-resistant crop land cover. This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion. The spatial distribution of global fractal dimension index, which can be used to describe the area of sub-pixel components and their spatial distribution modes, shows good consistency with the coarse resolution LAI inversion error.

     

Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

The spatial distribution of sub-pixel components has an impact on retrieval accuracy, and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index (LAI). To investigate this effect, we constructed three realistic scenarios with the same LAI values and other properties, except that the simulated plants had different distributions. We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor (BRF) datasets based upon these simulated scenes. The inversion was conducted using these data, which showed that spatial distribution affects retrieval accuracy. The inversion was also conducted for LAI based on charge-coupled device (CCD) data from the Environment and Disaster Monitor Satellite (HJ-1), which depicted both forest and drought-resistant crop land cover. This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion. The spatial distribution of global fractal dimension index, which can be used to describe the area of sub-pixel components and their spatial distribution modes, shows good consistency with the coarse resolution LAI inversion error.     

Reducing atmospheric noise in RST analysis of TIR satellite radiances for earthquakes prone areas satellite monitoring

Space–time fluctuations of the Earth’s emitted Thermal Infrared (TIR) radiation observed from satellite from months to weeks before an earthquake are reported in several studies. Among the others, a Robust Satellite data analysis Technique (RST) was proposed (and applied to different satellite sensors in various geo-tectonic contexts) to discriminate anomalous signal transients possibly associated with earthquake occurrence from normal TIR signal fluctuations due to other possible causes (e.g. solar diurnal–annual cycle, meteorological conditions, changes in observational conditions, etc.). Variations in satellite view angle depending on satellite’s passages (for polar satellites) and atmospheric water vapour fluctuations were recognized in the past as the main factors affecting the residual signal variability reducing the overall Signal-to-Noise (S/N) ratio and the potential of the RST-based approach in identifying seismically related thermal anomalies. In this paper we focus on both factors for the first time, applying the RST approach to geostationary satellites (which guarantees stable view angles) and using Land Surface Temperature (LST) data products (which are less affected by atmospheric water vapour variability) instead of just TIR radiances at the sensor.The first results, obtained in the case of the Abruzzo earthquake (6 April 2009, M_W ∼ 6.3) by analyzing 6 years of SEVIRI (Spinning Enhanced Visible and Infrared Imager on board the geostationary Meteosat Second Generation satellite) LST products provided by EUMETSAT, seem to confirm the major sensitivity of the proposed approach in detecting perturbations of the Earth’s thermal emission a few days before the main shock. The results achieved in terms of increased S/N ratio (in validation) and reduced “false alarms” rate (in confutation) are discussed comparing results obtained by applying RST to LST products with those achieved by applying an identical RST analysis (using the same MSG-SEVIRI 2005–2010 data-set) to the simple TIR radiances at the sensor.     

基于多源卫星数据的小型水体蓝藻水华联合监测——以天津于桥水库为例

近年来水体富营养化呈扩张趋势,蓝藻水华不仅在太湖等大型湖泊频发,水面面积较小的天津于桥水库等也形势严峻,亟需加强卫星遥感监测.但是,以往在太湖等业务化使用非常成功的MODIS等卫星数据(约500 m),由于空间分辨率较低,难以满足小型水体的监测要求;而Landsat-8等空间分辨率较高的卫星数据(30 m),通常重返周期较长,无法满足水华高频监测需求.本文以天津市于桥水库(面积约80 km2)为研究区,针对常用的卫星数据,从空间、时间、光谱范围和数据可获取性共4个方面,评价不同卫星数据蓝藻水华监测能力和算法,同时对不同卫星监测结果一致性进行评估.结果表明:(1)筛选出国产HJ-1A\B CCD、GF-1 WFV和美国Landsat-8 OLI这3种卫星波段合适,空间分辨率较高,适用于桥水库蓝藻水华监测,但考虑到其重返周期较长,建议多星联合观测;(2)各个卫星监测结果与卫星影像目视解译结果基本一致,均方根误差和相对误差均分别控制在0.78 km2和4.9%以内;(3)不同卫星监测结果一致性良好,一致性精度达到99.5%;(4)根据历史影像结果,发现于桥水库2016年水质开始呈富营养化,藻华现象在夏、秋两季最为严重.研究表明,针对小型水面水体蓝藻水华监测,利用较高分辨率数据联合监测,是一种有效的替代策略,今后可在更多小型水域推广.     

Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data

This study aims to model the joint probability distribution of periodic hydrologic data using meta-elliptical copulas. Monthly precipitation data from a gauging station (410120) in Texas, US, was used to illustrate parameter estimation and goodness-of-fit for univariate drought distributions using chi-square test, Kolmogorov–Smirnov test, Cramer-von Mises statistic, Anderson-Darling statistic, modified weighted Watson statistic, and Liao and Shimokawa statistic. Pearson’s classical correlation coefficient r _n , Spearman’s ρ _n, Kendall’s τ, Chi-Plots, and K-Plots were employed to assess the dependence of drought variables. Several meta-elliptical copulas and Gumbel-Hougaard, Ali-Mikhail-Haq, Frank and Clayton copulas were tested to determine the best-fit copula. Based on the root mean square error and the Akaike information criterion, meta-Gaussian and t copulas gave a better fit. A bootstrap version based on Rosenblatt’s transformation was employed to test the goodness-of-fit for meta-Gaussian and t copulas. It was found that none of meta-Gaussian and t copulas considered could be rejected at the given significance level. The meta-Gaussian copula was employed to model the dependence, and these results were found satisfactory.     

卫星通信在地震烈度速报数据传输中的应用

在分析地震烈度速报数据传输特点后,提出将卫星通信引入烈度速报系统。通过对目前中国使用较多的北斗卫星、海事卫星、铱卫星系统和VSAT卫星系统进行对比,选取铱星短消息和海事卫星数据流这两种典型通讯方式,设计由通用数字强震仪与卫星通信系统结合地震速报通讯模块组成的实验系统,实现数字强震动记录信息通过卫星信道进行的数据传输,展现卫星通信在地震烈度速报数据传输中的应用前景。     

How to improve attribution of changes in drought and flood impacts

ABSTRACT

For the development of sustainable, efficient risk management strategies for the hydrological extremes of droughts and floods, it is essential to understand the temporal changes of impacts, and their respective causes and interactions. In particular, little is known about changes in vulnerability and their influence on drought and flood impacts. We present a fictitious dialogue between two experts, one in droughts and the other in floods, showing that the main obstacles to scientific advancement in this area are both a lack of data and a lack of commonly accepted approaches. The drought and flood experts “discuss” available data and methods and we suggest a complementary approach. This approach consists of collecting a large number of single or multiple paired-event case studies from catchments around the world, undertaking detailed analyses of changes in impacts and drivers, and carrying out a comparative analysis. The advantages of this approach are that it allows detailed context- and location-specific assessments based on the paired-event analyses, and reveals general, transferable conclusions based on the comparative analysis of various case studies. Additionally, it is quite flexible in terms of data and can accommodate differences between floods and droughts.     

How to improve attribution of changes in drought and flood impacts

For the development of sustainable, efficient risk management strategies for the hydrological extremes of droughts and floods, it is essential to understand the temporal changes of impacts, and their respective causes and interactions. In particular, little is known about changes in vulnerability and their influence on drought and flood impacts. We present a fictitious dialogue between two experts, one in droughts and the other in floods, showing that the main obstacles to scientific advancement in this area are both a lack of data and a lack of commonly accepted approaches. The drought and flood experts “discuss” available data and methods and we suggest a complementary approach. This approach consists of collecting a large number of single or multiple paired-event case studies from catchments around the world, undertaking detailed analyses of changes in impacts and drivers, and carrying out a comparative analysis. The advantages of this approach are that it allows detailed context- and location-specific assessments based on the paired-event analyses, and reveals general, transferable conclusions based on the comparative analysis of various case studies. Additionally, it is quite flexible in terms of data and can accommodate differences between floods and droughts.     

从卫星观测数据提取地震前兆信息研究中的参考文献

如何从卫星观测数据中提取地震前兆信息,是近年来的一个跨空间物理、地震学和板块构造学等交叉领域的研究焦点,本文收集整理了部分近年来国外学者在该方面研究的论文,以供相关领域研究者参考之用。     

Development of an operational low-flow index for hydrological drought monitoring over Europe

Near real-time monitoring of hydrological drought requires the implementation of an index capable of capturing the dynamic nature of the phenomenon. Starting from a dataset of modelled daily streamflow data, a low-flow index was developed based on the total water deficit of the discharge values below a certain threshold. In order to account for a range of hydrological regimes, a daily 95th percentile threshold was adopted, which was computed by means of a 31-day moving window. The observed historical total water deficits were statistically fitted by means of the exponential distribution and the corresponding probability values were used as a measure of hydrological drought severity. This approach has the advantage that it directly exploits daily streamflow values, as well as allowing a near real-time update of the index at regular time steps (i.e. 10 days, or dekad). The proposed approach was implemented on discharge data simulated by the LISFLOOD model over Europe during the period 1995–2015; its reliability was tested on four case studies found within the European drought reference database, as well as against the most recent summer drought observed in Central Europe in 2015. These validations, even if only qualitative, highlighted the ability of the index to capture the timing (starting date and duration) of the main historical hydrological drought events, and its good performance in comparison with the commonly used standardized runoff index (SRI). Additionally, the spatial evolution of the most recent event was captured well in a simulated near real-time test case, suggesting the suitability of the index for operational implementation within the European Drought Observatory.     

Development of environmental monitoring satellite systems in China

With the increase in global environmental problems, the necessity and urgency of remote sensing technology being applied to environmental monitoring has been widely recognized around the world. China has launched the environment and disaster monitoring and forecasting small satellite constellation HJ-1A/B and the FY3 atmosphere and environmental satellite, but they still cannot fully satisfy requirements for environmental monitoring. This paper summarizes the current status of satellite environmental monitoring in China and the existing problems of inadequate load design and low data utilization efficiency, and discusses the demand for environmental monitoring satellites. Based on the development of foreign satellite systems for environmental monitoring, the future development and key tasks of the environmental monitoring satellite system in China is discussed, as are some related initiatives.     

Comparison of satellite and terrestrial gravity data

Summary The integral mean values of gravity on the surface W=W ₀ , obtained from satellite observations with the use of harmonic coefficients[3, 7] and from terrestrial gravity measurements[12], are compared. The squares and products of the harmonic coefficients were neglected, with the exception of [J ₂ ⁽⁰⁾ ] ² , which was taken into account. The Potsdam correction and the geocentric constant are being discussed. The paper ties up with[13–15] and the symbols used are the same. The given problem was treated, e.g., in[2, 4, 6, 8–10]; in the present paper the values of gravity are compared directly.