標(biāo)題: Titlebook: Data Assimilation; Making Sense of Obse William Lahoz,Boris Khattatov,Richard Menard Book 2010 Springer-Verlag Berlin Heidelberg 2010 Atmos [打印本頁] 作者: Disperse 時(shí)間: 2025-3-21 16:23
書目名稱Data Assimilation影響因子(影響力)
書目名稱Data Assimilation影響因子(影響力)學(xué)科排名
書目名稱Data Assimilation網(wǎng)絡(luò)公開度
書目名稱Data Assimilation網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Assimilation被引頻次
書目名稱Data Assimilation被引頻次學(xué)科排名
書目名稱Data Assimilation年度引用
書目名稱Data Assimilation年度引用學(xué)科排名
書目名稱Data Assimilation讀者反饋
書目名稱Data Assimilation讀者反饋學(xué)科排名
作者: inundate 時(shí)間: 2025-3-21 22:48
Assimilation of Operational Dataradiation from satellite instruments. Other, recent examples include ground-based GPS (Global Positioning Satellites) and radio-occultation data. The related issues of quality control and data thinning are also covered. Assimilation of time-sequences of observations is discussed. This chapter comple作者: 飛鏢 時(shí)間: 2025-3-22 01:51 作者: esoteric 時(shí)間: 2025-3-22 07:35 作者: Incompetent 時(shí)間: 2025-3-22 12:10
Variational Assimilation function, called the ., that measures the misfit to the available data. In particular, ., usually abbreviated as ., minimizes the misfit between a temporal sequence of model states and the observations that are available over a given assimilation window. As such, and contrary to the standard Kalman作者: 提煉 時(shí)間: 2025-3-22 14:47
Ensemble Kalman Filter: Current Status and Potential representative prototype of these methods, and several examples of how advanced properties and applications that have been developed and explored for 4D-Var (four-dimensional variational assimilation) can be adapted to the LETKF without requiring an adjoint model. Although the Ensemble Kalman filte作者: 提煉 時(shí)間: 2025-3-22 21:02 作者: 微粒 時(shí)間: 2025-3-23 01:17
The Principle of Energetic Consistency in Data Assimilationns requires all the sources of uncertainty – in the initial conditions, the dynamics, and the observations – to be identified and accounted for properly in the data assimilation process. This task is complicated by the fact that the non-linear dynamical system actually being observed is typically an作者: hemophilia 時(shí)間: 2025-3-23 03:59 作者: 猛烈責(zé)罵 時(shí)間: 2025-3-23 06:38
The Global Observing Systemferent techniques to observe the atmosphere, the ocean and land surfaces. It should be stressed that the various observing systems generally tend to be complementary to one another, and that redundancy where it exists is valuable as it enables cross checking and inter-comparison of data.作者: lymphoma 時(shí)間: 2025-3-23 13:46 作者: companion 時(shí)間: 2025-3-23 14:57
Research Satellitest which theories and models must be confronted and evaluated. Predictions of the variability of the Earth System require an understanding of the variability in the observations representing the “truth”. This requires observations that are: (i) high quality, i.e., have small errors and biases; (ii) c作者: Deference 時(shí)間: 2025-3-23 20:44
The Role of the Model in the Data Assimilation Systemive model in an assimilation system. There are numerous books on atmospheric modelling, their history, their construction, and their applications (e.g. Trenberth 1992 Randall 2000 Jacobson 2005). This chapter will focus on specific aspects of the model and modelling in data assimilation.作者: 精致 時(shí)間: 2025-3-24 00:43
Numerical Weather Predictione over a period of several hours up to 1 or 2 weeks ahead. This approach is central to modern operational weather forecasting: it is the improvements in NWP systems that have led to continual improvements in the skill of weather forecasts over recent decades.作者: BLA 時(shí)間: 2025-3-24 03:09
Book 2010 earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observat作者: 消極詞匯 時(shí)間: 2025-3-24 08:31 作者: 親密 時(shí)間: 2025-3-24 13:21 作者: gout109 時(shí)間: 2025-3-24 15:55 作者: profligate 時(shí)間: 2025-3-24 19:15
Research Satellitespending on application, there may be further observational requirements. For example, for monitoring climate change, global coverage would generally be required; for studying high impact weather, high spatial and temporal resolution would generally be required.作者: Prognosis 時(shí)間: 2025-3-25 01:39
Variational Assimilationmporal sequence of model states and the observations that are available over a given assimilation window. As such, and contrary to the standard Kalman filter and, more generally, to sequential algorithms for assimilation, it propagates the information contained in the data both forward and backward in time.作者: 大溝 時(shí)間: 2025-3-25 05:44
Ensemble Kalman Filter: Current Status and Potential 4D-Var (four-dimensional variational assimilation) can be adapted to the LETKF without requiring an adjoint model. Although the Ensemble Kalman filter is less mature than 4D-Var (Kalnay 2003), its simplicity and its competitive performance with respect to 4D-Var suggest that it may become the method of choice.作者: 畸形 時(shí)間: 2025-3-25 07:56
Error Statistics in Data Assimilation: Estimation and Modellingcterized by covariance matrices for the error in the background state and the observations. These covariance matrices determine the level of influence each observation has on the analysis and how this influence is distributed spatially, temporally and among the different types of analysis variables.作者: BUDGE 時(shí)間: 2025-3-25 14:44
Initialization features than those of direct concern. For many purposes these higher frequency components can be regarded as . contaminating the motions of meteorological interest. The elimination of this noise is achieved by adjustment of the initial fields, a process called ..作者: 蹣跚 時(shí)間: 2025-3-25 16:13
Cleaner Combustion and Sustainable Worldn lead to significant differences between the predicted states and the actual states of the system. In this case, observations of the system over time can be incorporated into the model equations to derive “improved” estimates of the states and also to provide information about the “uncertainty” in the estimates.作者: 含糊 時(shí)間: 2025-3-25 20:10 作者: 發(fā)生 時(shí)間: 2025-3-26 03:48 作者: ENNUI 時(shí)間: 2025-3-26 06:39 作者: urethritis 時(shí)間: 2025-3-26 08:59 作者: 摻假 時(shí)間: 2025-3-26 13:58
Beyond Japan: Cleaning, American-Stylecterized by covariance matrices for the error in the background state and the observations. These covariance matrices determine the level of influence each observation has on the analysis and how this influence is distributed spatially, temporally and among the different types of analysis variables.作者: Cupidity 時(shí)間: 2025-3-26 18:06
Blogging from the New Front Lines features than those of direct concern. For many purposes these higher frequency components can be regarded as . contaminating the motions of meteorological interest. The elimination of this noise is achieved by adjustment of the initial fields, a process called ..作者: Lacerate 時(shí)間: 2025-3-26 23:30 作者: 符合你規(guī)定 時(shí)間: 2025-3-27 03:55
Book 2010ions and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation)..作者: 與野獸博斗者 時(shí)間: 2025-3-27 08:11 作者: Water-Brash 時(shí)間: 2025-3-27 12:18 作者: escalate 時(shí)間: 2025-3-27 13:36
Randolph H. Pherson,Ole Donner,Oliver Gnadive model in an assimilation system. There are numerous books on atmospheric modelling, their history, their construction, and their applications (e.g. Trenberth 1992 Randall 2000 Jacobson 2005). This chapter will focus on specific aspects of the model and modelling in data assimilation.作者: 易于 時(shí)間: 2025-3-27 18:07 作者: ALOFT 時(shí)間: 2025-3-28 00:06
Data Assimilation and Informationhis context, we provide a step by step introduction to the need for data assimilation, culminating in an easy to understand description of the data assimilation methodology. Schematic diagrams and simple examples form a key part of this chapter.作者: 轉(zhuǎn)向 時(shí)間: 2025-3-28 05:49 作者: oxidant 時(shí)間: 2025-3-28 06:40 作者: 尋找 時(shí)間: 2025-3-28 10:40 作者: 間諜活動(dòng) 時(shí)間: 2025-3-28 17:50
Edward Blurock,Frédérique Battin-Leclerchis context, we provide a step by step introduction to the need for data assimilation, culminating in an easy to understand description of the data assimilation methodology. Schematic diagrams and simple examples form a key part of this chapter.作者: epidermis 時(shí)間: 2025-3-28 18:54 作者: 主講人 時(shí)間: 2025-3-28 23:44 作者: 護(hù)航艦 時(shí)間: 2025-3-29 03:47 作者: 黃油沒有 時(shí)間: 2025-3-29 09:15
Beyond Japan: Cleaning, American-Stylea background state by using estimates of the uncertainty associated with the background state and the observations. The uncertainty is typically characterized by covariance matrices for the error in the background state and the observations. These covariance matrices determine the level of influence作者: 強(qiáng)行引入 時(shí)間: 2025-3-29 11:57
Clear Air Turbulence and Its Detectionns requires all the sources of uncertainty – in the initial conditions, the dynamics, and the observations – to be identified and accounted for properly in the data assimilation process. This task is complicated by the fact that the non-linear dynamical system actually being observed is typically an作者: commune 時(shí)間: 2025-3-29 16:43 作者: atopic-rhinitis 時(shí)間: 2025-3-29 22:12
Monetizing Your Blog for Fun and Profitferent techniques to observe the atmosphere, the ocean and land surfaces. It should be stressed that the various observing systems generally tend to be complementary to one another, and that redundancy where it exists is valuable as it enables cross checking and inter-comparison of data.作者: 禁止 時(shí)間: 2025-3-30 01:36
Monetizing Your Blog for Fun and Profitediction (NWP). Many in situ observations can be treated as point-wise measurements. Their influence on the analysis is expected to be localized and smoothed according to the specified background error covariance structures (chapters ., Nichols; ., Buehner). Most remotely-sensed sounding data, on th作者: HALL 時(shí)間: 2025-3-30 04:36 作者: 殺子女者 時(shí)間: 2025-3-30 09:52 作者: entice 時(shí)間: 2025-3-30 14:33
Michelle Ann Miller,Tim Bunnelle over a period of several hours up to 1 or 2 weeks ahead. This approach is central to modern operational weather forecasting: it is the improvements in NWP systems that have led to continual improvements in the skill of weather forecasts over recent decades.作者: Aqueous-Humor 時(shí)間: 2025-3-30 19:31
On the Energy Supply of Clear Air TurbulenceOne of the standard assumptions in data assimilation is that observation and model errors are purely random, i.e., they do not contain systematic errors (see chapter ., Nichols). In reality, the distinction between random errors and systematic errors is somewhat academic.作者: 淘氣 時(shí)間: 2025-3-30 21:38
Monetizing Your Blog for Fun and ProfitThe theory of statistical linear estimation (., or . – the term . is also used), upon which a large number of presently existing assimilation algorithms are based, has been described in chapter . (Talagrand).作者: 擴(kuò)音器 時(shí)間: 2025-3-31 02:46
Automatic Speech Recognition(ASR)The aim of this chapter is to give a general overview of the atmospheric circulation, highlighting the main concepts that are important for a basic understanding of meteorology and atmospheric dynamics relevant to atmospheric data assimilation.
