標題: Titlebook: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV); Seon Ki Park,Liang Xu Book 2022 The Editor(s) (if applic [打印本頁] 作者: 瘦削 時間: 2025-3-21 17:58
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作者: PRISE 時間: 2025-3-21 23:09 作者: Omnipotent 時間: 2025-3-22 03:08 作者: 天空 時間: 2025-3-22 08:14 作者: indignant 時間: 2025-3-22 11:55 作者: novelty 時間: 2025-3-22 16:51 作者: novelty 時間: 2025-3-22 19:26 作者: 搜集 時間: 2025-3-23 01:09
observations, sensitivity analysis, parameter estimation?and AI applications.?The book?is?useful to individual researchers as well as graduate students for a reference in the field of data assimilation.?978-3-030-77724-1978-3-030-77722-7作者: sleep-spindles 時間: 2025-3-23 01:38 作者: 誘導 時間: 2025-3-23 06:59
Climate Change Adaptation in Latin Americantals of the measurement, the derivation of the typical observation which is used in NWP, the assimilation methods and error assumptions which are used, and finally some conjecture on the direction to improve the use of the observations and what future measurement systems may look like.作者: Ischemia 時間: 2025-3-23 10:09 作者: 誘惑 時間: 2025-3-23 17:22
Stochastic Representations for Model Uncertainty in the Ensemble Data Assimilation System,ation?hybrid tendencies (SPHT) scheme, which perturbs both physical tendency and dynamical tendency using the random forcing, and assessed its impact on the spread of ensemble forecast and ensemble mean?error.作者: Pander 時間: 2025-3-23 18:39
GNSS-RO Sounding in the Troposphere and Stratosphere,ntals of the measurement, the derivation of the typical observation which is used in NWP, the assimilation methods and error assumptions which are used, and finally some conjecture on the direction to improve the use of the observations and what future measurement systems may look like.作者: 謙卑 時間: 2025-3-24 01:14
Images Assimilation: An Ocean Perspective,ters should consider making image assimilation an integral part of their future assimilation systems. Beyond the motivation, we also discuss whether images should be assimilated directly or indirectly, the latter consisting of assimilating information derived from images.作者: PANEL 時間: 2025-3-24 03:52 作者: nerve-sparing 時間: 2025-3-24 09:42
Climate Change Adaptation in North Americasful extension of the sensitivity of acoustic pressure to temperature and salinity implies that acoustic pressure observations in a given range-depth plane can be assimilated into an ocean model using the acoustic propagation model as the observation operator.作者: Audiometry 時間: 2025-3-24 12:39
Perturbations by the Ensemble Transform,l perturbations. Results of forecast experiments using the local ensemble transform Kalman filter (LETKF) for a simplified global model and a regional NWP model are shown. The spin-up issue in a cloud resolving model is shown with the comparison to an alternative method (diagonal LETKF).作者: 疼死我了 時間: 2025-3-24 17:42 作者: fulcrum 時間: 2025-3-24 20:03 作者: 令人發(fā)膩 時間: 2025-3-25 00:44 作者: Picks-Disease 時間: 2025-3-25 07:06
Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation,ate of the system based on available observations, the so-called filtering?problem. Standard filtering?solutions are computed recursively as successive cycles of alternating time-update (forecast) and observation-update (analysis) steps. This path is however not the only recursive way to compute the作者: transient-pain 時間: 2025-3-25 07:46
Sparsity-Based Kalman Filters for Data Assimilation,d engineering applications. However, traditional UKFs?or EKFs?cannot assimilate big data sets associated with models that have high dimensions, such as those in operational numerical weather prediction. In this chapter, we introduce two sparsity-based Kalman filters, namely the sparse-UKFand the pro作者: Redundant 時間: 2025-3-25 11:48 作者: MARS 時間: 2025-3-25 18:47 作者: cliche 時間: 2025-3-25 21:32
Second-Order Methods in Variational Data Assimilation,d, the second-order adjoint?method among them. General sensitivity analysis?for the? optimality system?is presented. Using the Hessian, the sensitivity of the optimal solution and its functionals?is studied with respect to observations and uncertainties in model parameters. Numerical examples for jo作者: 媒介 時間: 2025-3-26 01:30 作者: Aura231 時間: 2025-3-26 07:14
Observability Gramian and Its Role in the Placement of Observations in Dynamic Data Assimilation,e efficiency with which it determines the cost function?gradient with respect to control and available observations. Then through use of any of the gradient-based optimization?algorithms, the minimum is iteratively found. The alternate methodology does not depend on available observations; rather, t作者: triptans 時間: 2025-3-26 11:22 作者: Regurgitation 時間: 2025-3-26 12:56 作者: assent 時間: 2025-3-26 17:24
Assimilation of In-Situ Observations, weather prediction, even in the current era when observations from satellites provide approximately 90% of the observations assimilated.In addition, these observations are widely used in verification for both model forecasts and satellite datasets, and radiosonde data serve as critical anchor obser作者: 推崇 時間: 2025-3-27 00:33
GNSS-RO Sounding in the Troposphere and Stratosphere, has become a standard practice of many numerical weather prediction (NWP) centers. The introduction of this observation has seen broad positive impact on analyses and forecasts. On longer timescales the impact of the introduction of this data type in re-analyses can be clearly seen. Further, the ob作者: Ischemia 時間: 2025-3-27 03:09 作者: 航海太平洋 時間: 2025-3-27 09:15 作者: 陪審團 時間: 2025-3-27 09:35
Sensitivity Analysis in Ocean Acoustic Propagation,opagation model. The sensitivity analysis is extended to temperature and salinity, by deriving the adjoint of the sound polynomial function of temperature and salinity. Numerical experiments using a range dependent model are carried out in a deep and complex environment at the frequency of 300?Hz. I作者: 緯度 時間: 2025-3-27 13:56
Difficulty with Sea Surface Height Assimilation When Relying on an Unrepresentative Climatology,ct, with the construction of synthetic temperature (T) and salinity (S) profiles based on observationally-derived climatological covariances between SSHA, T, and S. The other approach is direct via a four-dimensional variational system, but it relies on a mean SSH (here, one constrained by observati作者: 障礙 時間: 2025-3-27 20:11
Theoretical and Practical Aspects of Strongly Coupled Aerosol-Atmosphere Data Assimilation,deling systems. Among various coupling options, strongly coupled data assimilation is the most efficient option for processing the information from observations. At the same time, coupled aerosol-atmosphere modeling is steadily gaining more interest due to its relevance to air quality, aviation, sol作者: 細微差別 時間: 2025-3-28 00:06
,Improving Near-Surface Weather Forecasts with Strongly Coupled Land–Atmosphere Data Assimilation,eather prediction (NWP) due to difficulties in surface data assimilation and uncertainties in representing complicated land–atmosphere interactions in numerical models. This chapter summarizes recent developments from the author’s research team to understand and develop effective data assimilation m作者: 談判 時間: 2025-3-28 05:34
https://doi.org/10.1007/978-3-030-77722-7Hybrid Data Assimilation; Kalman Filter; Monte Carlo Method; Artificial Intelligence Application; Wiener作者: –scent 時間: 2025-3-28 09:43
978-3-030-77724-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: Rejuvenate 時間: 2025-3-28 12:15 作者: 最有利 時間: 2025-3-28 17:50 作者: gruelling 時間: 2025-3-28 22:40
Conclusions and Recommendations,er geophysical fluid flows. Data assimilation is the process whereby the uncertainty in initial conditions?is reduced by the astute combination of model predictions and real-time data. This chapter reviews recent findings from investigations on the impact of chaos?on data assimilation methods: for t作者: Fraudulent 時間: 2025-3-28 22:57 作者: saphenous-vein 時間: 2025-3-29 05:42
Chiara Trabacchi,Martin Stadelmannate of the system based on available observations, the so-called filtering?problem. Standard filtering?solutions are computed recursively as successive cycles of alternating time-update (forecast) and observation-update (analysis) steps. This path is however not the only recursive way to compute the作者: inquisitive 時間: 2025-3-29 09:06 作者: 殺菌劑 時間: 2025-3-29 15:28 作者: Motilin 時間: 2025-3-29 15:34 作者: foliage 時間: 2025-3-29 23:14
Climate Change Adaptation in Africad, the second-order adjoint?method among them. General sensitivity analysis?for the? optimality system?is presented. Using the Hessian, the sensitivity of the optimal solution and its functionals?is studied with respect to observations and uncertainties in model parameters. Numerical examples for jo作者: 無聊點好 時間: 2025-3-30 02:32
Alebachew Adem,Karl Deering,Samuel Molla best estimate of the current state of the atmosphere. Appropriately specifying observation error statistics is necessary to obtain an optimal analysis. Observation error can originate from instrument error as well as the error of representation. While representation error is most commonly associate作者: 小官 時間: 2025-3-30 05:50 作者: 侵略者 時間: 2025-3-30 11:43
Yasushi Honda,Masaji Ono,Kristie L. Ebit function’s gradient presents problems in the iterative passage to the cost function’s minimum. Determination of observation placement that avoids these flat zones generally permits expeditious passage to the cost function minimum. A contribution to this volume (Lakshmivarahan S, Lewis JM, Maryada 作者: dithiolethione 時間: 2025-3-30 13:24
https://doi.org/10.1007/978-94-007-0567-8vation impact?framework in a limited-area atmospheric model. High temporal frequency estimates of forecast error?are produced using aircraft observations for validation. Using these estimates, forecast error?reduction between background and analysis trajectories is shown to decrease through the firs作者: 能得到 時間: 2025-3-30 18:56
Climate Change Adaptation in Latin America weather prediction, even in the current era when observations from satellites provide approximately 90% of the observations assimilated.In addition, these observations are widely used in verification for both model forecasts and satellite datasets, and radiosonde data serve as critical anchor obser作者: Mhc-Molecule 時間: 2025-3-30 23:57
Climate Change Adaptation in Latin America has become a standard practice of many numerical weather prediction (NWP) centers. The introduction of this observation has seen broad positive impact on analyses and forecasts. On longer timescales the impact of the introduction of this data type in re-analyses can be clearly seen. Further, the ob作者: 尊敬 時間: 2025-3-31 02:33 作者: 使尷尬 時間: 2025-3-31 05:14 作者: Spinal-Tap 時間: 2025-3-31 12:26 作者: Free-Radical 時間: 2025-3-31 15:06
C. Daniel Myers,Tara Ritter,Andrew Rockwayct, with the construction of synthetic temperature (T) and salinity (S) profiles based on observationally-derived climatological covariances between SSHA, T, and S. The other approach is direct via a four-dimensional variational system, but it relies on a mean SSH (here, one constrained by observati作者: 知識 時間: 2025-3-31 19:30
M. Le Duff,P. Dumas,O. Cohen,M. Allenbachdeling systems. Among various coupling options, strongly coupled data assimilation is the most efficient option for processing the information from observations. At the same time, coupled aerosol-atmosphere modeling is steadily gaining more interest due to its relevance to air quality, aviation, sol作者: CEDE 時間: 2025-3-31 22:08
M. Le Duff,P. Dumas,O. Cohen,M. Allenbacheather prediction (NWP) due to difficulties in surface data assimilation and uncertainties in representing complicated land–atmosphere interactions in numerical models. This chapter summarizes recent developments from the author’s research team to understand and develop effective data assimilation m作者: CANE 時間: 2025-4-1 04:47
Data Assimilation for Chaotic Dynamics,nfilter?in the context of a chaotic, coupled, atmosphere-ocean model with a quasi-degenerate spectrum?of Lyapunov exponents, showing the importance of having sufficient ensemble members?to track all of the near-null modes. Secondly, for the fully non-Gaussian method?of the particle filter, numerical作者: 你不公正 時間: 2025-4-1 06:33
Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation,Kalman?filters (EnKF-OSAS), depending on the size and the linear-Gaussian character of the underlying state-space system. While the standard KF?and KF-OSAS?provide the same (exact) estimator, the use of the same data twice in the estimation process generally leads to improved trade-off between estim作者: Psychogenic 時間: 2025-4-1 12:44 作者: 鋪子 時間: 2025-4-1 15:16