Use of atmospheric angular momentum forecasts for UT1 predictions: analyses over CONT08

Real-time orbit determination and interplanetary navigation require accurate predictions of the orientation of the Earth in the celestial reference frame and in particular that for Universal Time UT1. Much of the UT1 variations over periods ranging from hours to a couple of years are due to the global atmospheric circulation. Therefore, the axial atmospheric angular momentum (AAM) forecast series may be used as a proxy index to predict UT1. Our approach taking advantage of this fact is based on an adaptive procedure. It involves incorporating integrations of AAM estimates into UT1 series. The procedure runs on a routine basis using AAM forecasts that are based on the two meteorological series, from the US National Centers for Environmental Prediction and the Japan Meteorological Agency. It is pertinent to test the prediction method for the period that includes the special CONT08 campaign over which we expect a significant improvement in UT1 accuracy. The studies we carried out were aimed both to compare atmospheric forecasts and analyses, as well as to compare the skills of the UT1 forecasts based on the method with atmospheric forecasts and that using current statistical processes, as applied to the C04 Earth orientation parameters series derived by the International Earth rotation and Reference Systems service (IERS). Here we neglect the oceanic sub-diurnal and diurnal variations, as these signals are expected to be smaller than the UT1-equivalent of 100 μs, when averaged over a few days. The prediction performances for a 2-day forecast are similar, but at a forecast horizon of a week, the AAM-based forecast is roughly twice as skillful as the statistically based one.     

Short-term polar motion forecasts from earth system modeling data

Polar motion predictions for up to 10 days into the future are obtained from predicted states of the atmosphere, ocean and continental hydrosphere in a hind-cast experiment covering 2003–2008. High-frequency mass variations within the geophysical fluids are the main cause of wide-band stochastic signals not considered in the presently used statistical prediction approach of IERS bulletin A for polar motion. Taking EAM functions based on forecasted model states, derived from ECMWF medium-range forecasts and corresponding LSDM and OMCT simulations, into account the prediction errors are reduced by 26%. The effective forecast length of the model combination is found to be 7 days, primarily limited by the accuracy of the forecasted atmospheric wind fields. Highest improvements are found for forecast days 4–5 with prediction skill scores of the polar motion excitation functions improved by a factor up to 5. Whereas bulletin A forecasts can explain the observed variance within the first 10 days only by up to 40%, half of the model forecasts reach relative explained variances between 40 and 80%.     

基于MODIS数据的火险潜在指数（FPI）及其应用研究

死、活可燃物含水率大小决定森林点燃的难易度,是判断林火能否发生、进行林火预报的重要因子。本文应用火险潜在指数（FPI,Fire Potential Index）模型,从这2个方面分析研究可燃物湿度对林火发生的影响。利用MODIS遥感数据提取FPI模型所需因素（气象数据： 相对湿度、温度; 植被数据： 10 h时滞可燃物湿度、归一化水分指数、植被绿度）,并将获得的2004年10月黑龙江省和2008年3月南方几省的气象、植被数据输入FPI模型,得到火险指数和火险等级划分。实践证明,应用该模型能够提高火险在时间和地理分布上的预报能力及预防技术。     

融合多源时空数据的城市火灾危险性评估

城市层面的火灾风险评估主要包括火灾危险性、危害性及救援能力等方面。本文选取火灾危险性评估进行针对性研究,在大数据思维的指导下,以相关关系代替因果关系,采用多源数据对评估指标权重、分值进行率定,得出福州市城区火灾危险性时空分布图。首先利用高德地图API对消防历史出警记录进行地址解析,将近万条火灾出警地址空间落点,获得福州市历史火灾空间分布;然后综合城市用地性质现状、用地开发性质、人口分布热力图等多源异构数据,探索其与历史火灾空间分布的相关性;最后以福州城区为例,初步实现具有充分数理支撑的火灾危险性评估方法,形成火灾危险性动态评估成果,为城市消防规划等提供支撑和依据。     

Satellite data and geographic information systems for fire and resource management in the Canadian arctic

Abstract

A method of analyzing remotely sensed data, a geographic information system, and an intelligent fire management system have been developed to provide integrated resource data for fire and other resources management. Natural and cultural features were digitized from 1:50,000 topographic maps using a geographic information system (GIS) to cover the 29 communities below the tree line in the western Canadian Arctic. Landsat Thematic Mapper data covering the same area were classified into land cover or fuel types. Detailed information on each fire such as location, area burned, date of discovery, fire number, fire zone, fire class and source of ignition was obtained and added to each map sheet as attribute data. A generalized vegetation cover map using NOAA AVHRR data was also obtained. The Intelligent Fire Management Information System (IFMIS) integrates relational data bases, geographic information display, and expert systems. It also has a spatial analysis procedure for forest fire preparedness planning. Linking the weather to the forest fuels through the Fire Weather Index system (FWI) and the Fire Behaviour Prediction System (FBPS), fire danger and fire behaviour are calculated and displayed, cell‐by‐cell. Values‐at‐risk and fire suppression resources are used in the dispatching and planning component of the system. The planning component allows the user to evaluate the coverage of fire suppression resources under the prevalent forecast fire behaviour conditions. Through the integration of data from the above systems, a set of maps were created which were used to analyze fire behaviour potential, identify fire hazards, and provide a basis for settlement protection strategies within the context of other land use activities such as wildlife harvesting and recreational activities.     

Combination of modeled short-term angular momentum function forecasts from atmosphere, ocean, and hydrology with 90-day EOP predictions

Angular momentum forecasts for up to 10 days into the future, modeled from predicted states of the atmosphere, ocean and continental hydrosphere, are combined with the operational IERS EOP prediction bulletin A to reduce the prediction error in the very first day and to improve the subsequent 90-day prediction by exploitation of the revised initial state and trend information. EAM functions derived from ECMWF short-range forecasts and corresponding LSDM and OMCT simulations can account for high-frequency mass variations within the geophysical fluids for up to 7 days into the future primarily limited by the accuracy of the forecasted atmospheric wind fields. Including these wide-band stochastic signals into the first days of the 90-day statistical IERS predictions reduces the mean absolute prediction error even for predictions beyond day 10, especially for polar motion, where the presently used prediction approach does not include geophysical fluids data directly. In a hindcast experiment using 1 year of daily predictions from May 2011 till July 2012, the mean prediction error in polar motion, compared to bulletin A, is reduced by 32, 12, and 3 % for prediction days 10, 30, and 90, respectively. In average, the prediction error for medium-range forecasts (30–90 days) is reduced by 1.3–1.7 mas. Even for UT1-UTC, where AAM forecasts are already included in IERS bulletin A, we obtain slight improvements of up to 5 % (up to 0.5 ms) after day 10 due to the additional consideration of oceanic angular momentum forecasts. The improved 90-day predictions can be generated operationally on a daily basis directly after the publication of the related IERS bulletin A product finals2000A.daily.     

基于GIS和RS的森林火灾管理系统的设计与实现

介绍了组件式GIS开发技术的概念和特点,分析了GIS和RS技术在森林防火中的应用前景。针对森林防火管理的特点,将GIS和RS技术结合设计和开发出森林火灾管理系统,该系统实现了对火灾高发区及火场的定位、预测、监控和分析等功能,促进了森林防火信息化管理。利用组件式开发技术,森林火灾管理系统可以实现对林区的基本空间分析功能,并且可以对林区火场实现3维漫游,以辅助决策指挥。     

GPS技术在三峡库区地质灾害专业监测中的应用

分析了GPS监测在三峡库区地质灾害专业监测中的作用,设计并构建了三峡库区三级GPS监测网,满足了国家对库区地质灾害体监测预警的要求。     

南方灵锐S86GPS RTK在煤田火区探测中应用

煤层自燃是煤炭资源的主要危害之一,它对煤层破坏作用巨大,导致自燃煤层周围煤炭资源的开采困难和贬值,同时也对生态环境产生了恶劣影响.利用GPS RTK技术测定平庄煤田火区1∶2 000地形图,确定火区位置,用物探、遥感和遥测等新技术进行煤火监测,火区灾害防治和矿区环境保护,火区灭火工程、矿井安全生产和矿区可持续发展都具有...     

Wildfire Potential Mapping over the State of Mississippi: A Land Surface Modeling Approach

A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern part of Mississippi. The following three indices were tested and used to simulate spatial and temporal wildfire probability changes: (1) the accumulated difference between daily precipitation and potential evapotranspiration (P - E); (2) simulated moisture content of the top 10 cm of soil; and (3) the Keetch-Byram Drought Index (KBDI). These indices were estimated from gridded meterological data and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). The relationships between normalized fire potential index deviations and the probability of at least one fire occurring during the following five consecutive days were evaluated using a 23-year (1986-2008) forest fire record for an evenly spaced grid (0.25° x 0.25°) across the state of Mississippi's coastal plain. Two periods were selected and examined (January-mid June and mid September-December). There was good agreement between the observed and logistic model-fitted fire probabilities over the study area during both seasons. The fire potential indices based on the top 10 cm soil moisture and KBDI had the largest impact on wildfire odds, increasing it by almost 2 times in response to each unit change of the corresponding fire potential index during January-mid-June period and by nearly 1.5 times during mid-September-December. These results suggest that soil moisture-based fire potential indices are good indicators of fire occurrence probability across this region.     

Using cumulative NOAA-AVHRR spectral indices for estimating fire danger codes in northern boreal forests

In Canada, fire danger is rated by the Canadian forest fire danger rating system (CFFDRS). One of its components is the fire weather index (FWI) system, which has among others the drought code (DC). DC is used here as a surrogate of dead forest fuel moisture. DC values were computed from weather data acquired between 1993 and 1999 and compared to 10-day composite NOAA-AVHRR images acquired over Canadian northern boreal forests. They were yearly correlated with single compositing period and cumulative NDVI and surface temperature (ST) NOAA-AVHRR data. Correlations with cumulative spectral variables were stronger than with single compositing period variables and the best correlations occurred for the spring compositing periods (R between 0.57 and 0.80). Spring DC models using both single compositing period and cumulative spectral variables were established. Surface temperature-based indices were more often used in the models than NDVI-based indices. The models were stronger for dry or normal years than for wet years. Limitations and possible improvements of the models are discussed.     

Remote sensing-based assessment of veld fire trends in multiple interwoven land tenure systems in Zimbabwe

The study used Landsat imagery, MODIS fire data and in situ meteorological data to determine emerging fire trends in interwoven multiple tenure systems in Zimbabwe. Remote sensing enabled fire trends to be determined across terrain and official records barriers. The number of fires and area burnt increased from 2001 up to 2009 then fluctuated across tenure systems. Fire events rose from 9 to 80 per year in some of the tenure systems. Complex relationships among number of fires, area burnt and weather variables within and across tenure systems were identified. The fire situation was responsive to intervention; the positive fire trends were reversed from 2009 onwards. Projected trends show that fire events could be reduced to negative values in three systems, while in two they could double by 2026. The veld fire problem could be eliminated if a holistic approach is adopted to tackle it across sectoral and land tenure divides.     

基于NewMap Server的森林防火应急指挥系统设计与实现

综合运用3S技术,以NewMap Server为地理信息系统开发平台,建立森林防火应急指挥系统,具体介绍了系统设计思想,系统结构和系统开发。并结合济源市森林防火应急指挥系统实例,介绍了预报监测、辅助决策、、扑救指挥和灾后评估等系统功能。     

Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece

The main purpose of this study is to explore the relationship between three field-based fire severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and spectral indices derived from Sentinel 2A and Landsat-8 OLI imagery on a recent large fire in Thasos, Greece. We employed remotely sensed indices previously used from the remote sensing fire community (Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), differenced NDVI, differenced NBR, relative differenced NBR, Relativized Burn Ratio) and seven Sentinel 2A-specific indices considering the availability of spectral information recorded in the red-edge spectral region. The statistical correlation indicated a slightly stronger relationship between the differenced NBR and the GeoCBI for both Sentinel 2A (r = 0.872) and Landsat-8 OLI (r = 0.845) imagery. Predictive local thresholds of dNBR values showed slightly higher classification accuracy for Sentinel 2A (73.33%) than Landsat-8 OLI (71.11%), suggesting the adequacy of Sentinel 2A for forest fire severity assessment and mapping in Mediterranean pine ecosystems. The evaluation of the classification thresholds calculated in this study over other fires with similar pre-fire conditions could contribute in the operational mapping and reconstruction of the historical patterns of fire severity over the Eastern Mediterranean region.     

Impact of FORMOSAT-3/COSMIC GPS radio occultation and dropwindsonde data on regional model predictions during the 2007 Mei-yu season

A study of the impact of FORMOSAT-3/COSMIC GPS radio occultation (RO) and dropwindsonde data on regional model simulations for a 11-day period during the 2007 Mei-yu season is presented. The Weather Research and Forecasting (WRF) model and its three-dimensional variation component, WRF-Var, are used for regional model predictions of heavy rainfall events in Taiwan. Without the use of GPS RO and dropwindsonde data, pressure and relative humidity are, in general, underestimated by the model; temperature predictions have a warm bias at the low level and a cold bias at the high level; and the east–west and north–south component winds have positive and negative biases, respectively. Incorporating GPS RO data tends to improve the prediction for longer integration. The assimilation of dropwindsonde data improves the forecast at the earlier time and at higher levels, and the improvement decreases over time. The reason the dropwindsonde data produce a positive impact earlier and the GPS RO data later is that there are few GPS RO observations in the fine domain. The large-scale simulation is first improved using the GPS RO observations, and the resulting changes can have a positive impact on the mesoscale at the later time. The dropwindsonde observations were taken inside the fine domain such that their impact can be detected early in the simulation. With both types of observation included, the prediction shows even greater improvement. At the earlier forecast time, there is nearly no impact from GPS and dropwindsonde data on rainfall forecasts. However, at the later integration time, the GPS data start to significantly improve the rainfall forecast. The dropwindsonde data also provide a positive impact on rainfall forecasts, but it is not as significant as that of the GPS data.     

TM图像在新疆奇台北山煤田火区动态监测中的应用

本文以实测的煤田火区地物波谱数据为依据,对用于煤田火区各地物解译的遥感信息源──TM图像的最佳时相选择、最佳波段组合和煤田火区地物在TM图像上的影像特征进行了探讨。采用多时相TM图像对新疆奇台北山煤田火区进行动态监测及火情预测的成果进行了叙述,该勘查研究成果对指导该煤田火区灭火工程设计及后期防火管理有较大实用价值。对其它煤田火区火情监测也有一定借鉴作用。     

Application of geographical information system for mapping/monitoring seismological hazards in Pakistan

This study attempts to use the geographic information system (GIS) technique to map and understand the tectonics and crustal structures of Pakistan. Maps of surficial tectonic features and seismological parameters including Moho depth, P_n velocity and P_g velocity are complied. Based on the seismological data-set of the country the earthquake hazard map of Pakistan is also presented by applying regression technique on seismological, geological and topographical parameters. A case study of 8 October 2005 earthquake is used to validate the hazard map. It is envisaged that the developed GIS database would help policy-makers and scientists in natural hazard evaluation, seismic risk assessment and understanding of earthquake occurrences in Pakistan.     

Modeling and forecast of the polar motion excitation functions for short-term polar motion prediction

Short-term forecast of the polar motion is considered by introducing a prediction model for the excitation function that drives the polar motion dynamics. The excitation function model consists of a slowly varying trend, periodic modes with annual and several sub-annual frequencies (down to the 13.6-day fortnightly tidal period), and a transient decay function with a time constant of 1.5 days. Each periodic mode is stochastically specified using a second-order auto-regression process, allowing its frequency, phase, and amplitude to vary in time within a statistical tolerance. The model is used to time-extrapolate the excitation function series, which is then used to generate a polar motion forecast dynamically. The skills of this forecast method are evaluated by comparison to the C-04 polar motion series. Over the lead-time horizon of four months, the proposed method has performed equally well to some of the state-of-art polar motion prediction methods, none of which specifically features forecasting of the excitation function. The annual mode in the ₂ component is energetically the most dominant periodicity. The modes with longer periods, annual and semi-annual in particular, are found to contribute more significantly to forecast accuracy than those with shorter periods.     

中国新疆煤层自燃环境动态监测信息系统的开发

针对中国北方煤层自燃的特征,应用地理信息系统理论和方法,研建了为组织、实施煤矿灭火服务的煤层自燃动态监测信息系统(CFMIS),提出和确定了符合煤炭生产、管理和灭火部门实际需要的系统硬件配置,介绍了CFMIS的软件组成、数据内容、应用模型,阐明了该系统总体结构、特点以及使用效果。     

MAPPING THE AVALANCHE HAZARD FOR MOUNTAINOUS AREAS OF AFGHANISTAN

The authors describe a procedure for the compilation of maps of the avalanche hazard in high-mountain regions of Afghanistan. The basic sources of information include space imagery (photographs and scanner imagery), weather station data, and other geographic information on relief, elevation, location of moisture sources, etc. The methodology features the compilation of series of increasingly more specific and informative maps and graphs regarding the avalanche hazard: terrain types, snow cover depth and seasonal extent, duration of snow cover and its elevational zonation, snow as a factor in avalanche formation, and summary map of avalanche hazard. Translated by Elliott B. Urdang, Providence, RI 02906 from: Materialy glyatsiologicheskikh issledovaniy, 1991, No. 71, pp. 86–93.