Weather Disasters In The South China Sea And Surrounding Regions Observations Theories Data Assimilation And Numerical Forecasting
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Weather Disasters In The South China Sea And Surrounding Regions Observations Theories Data Assimilation And Numerical Forecasting
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Author : Jianjun Xu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-08-28
Weather Disasters In The South China Sea And Surrounding Regions Observations Theories Data Assimilation And Numerical Forecasting written by Jianjun Xu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-28 with Science categories.
The South China Sea (SCS) is the linkage between the western Pacific Ocean and the Indian Ocean. Its weather/climate variations are regarded as an important factor influencing social and economic development. The SCS and its surrounding regions suffer from various weather disasters (e.g., typhoons, extreme rainfall, sea fog, severe convection, tornado, and wind hazards), which are serious threats to life and property. As such, accurate nowcasting is life-critical in this area. However, it is still a worldwide challenge to improve the forecast accuracy due to less understanding of the formation mechanism, evolution pattern, internal structure, and physical processes. As a dominant physical process, the ocean-atmosphere interaction plays an important role in affecting the weather/climate system and disasters over the SCS and surrounding regions, particularly vertical mixing between the interface of ocean and atmosphere. This research topic aims to provide an in-depth understanding of the physical processes related to these disasters, applications of data assimilation, and the development of forecasting techniques, which are essential to enhance disaster prevention and mitigation capabilities. In addition, in-depth research of these disasters and their impacts could help to uncover the hazard-causing characteristics and establish a corresponding risk assessment system.
Tropical Cyclone Intensity And Structure Changes Theories Observations Numerical Modeling And Forecasting
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Author : Eric Hendricks
language : en
Publisher: Frontiers Media SA
Release Date : 2023-09-29
Tropical Cyclone Intensity And Structure Changes Theories Observations Numerical Modeling And Forecasting written by Eric Hendricks and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Science categories.
Advances In Numerical Model Data Assimilation And Observations For Hazardous Weather Prediction
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Author : Feifei Shen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-10-30
Advances In Numerical Model Data Assimilation And Observations For Hazardous Weather Prediction written by Feifei Shen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-30 with Science categories.
Accurate and timely forecasting of hazardous weather events induced by meso-scale convection systems (MCSs) is the key to safeguarding lives and property. Yet the MCS forecasting is challenging due to imperfect initial numerical conditions that lack meso-scale convective information and multi-scale dynamic and thermodynamic consistency. Remote sensing observations are the primary source of estimating weather conditions, such as moisture, wind velocity, and precipitation. It is of fundamental pivotality to develop data assimilation technologies to enhance applications of multi-source observations. Performance assessments of new types of observations facilitate the network designment for regional- and storm-scale numerical models. This Research Topic seeks submissions underscoring the improvement of the accuracy of MCS predictions, warnings, and decision support for high-impact weather events as well as observation network designs.
Understanding The Influence Of Assimilating Satellite Derived Observations On Mesoscale Analyses And Forecasts Of Tropical Cyclone Track And Structure
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Author : Ting-Chi Wu
language : en
Publisher:
Release Date : 2014
Understanding The Influence Of Assimilating Satellite Derived Observations On Mesoscale Analyses And Forecasts Of Tropical Cyclone Track And Structure written by Ting-Chi Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
This dissertation research explores the influence of assimilating satellite-derived observations on mesoscale numerical analyses and forecasts of tropical cyclones (TC). The ultimate goal is to provide more accurate mesoscale analyses of TC and its surrounding environment for superior TC track and intensity forecasts. High spatial and temporal resolution satellite-derived observations are prepared for two TC cases, Typhoon Sinlaku and Hurricane Ike (both 2008). The Advanced Research version of the Weather and Research Forecasting Model (ARW-WRF) is employed and data is assimilated using the Ensemble Adjustment Kalman Filter (EAKF) implemented in the Data Assimilation Research Testbed. In the first part of this research, the influence of assimilating enhanced atmospheric motion vectors (AMVs) derived from geostationary satellites is examined by comparing three parallel WRF/EnKF experiments. The control experiment assimilates the same AMV dataset assimilated in NCEP operational analysis along with conventional observations from radiosondes, aircraft, and advisory TC position data. During Sinlaku and Ike, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) generates hourly AMVs along with Rapid-Scan (RS) AMVs when the satellite RS mode is activated. With an order of magnitude more AMV data assimilated, the assimilation of hourly CIMSS AMV dataset exhibit superior initial TC position, intensity and structure estimates to the control analyses and the subsequent short-range forecasts. When RS AMVs are processed and assimilated, the addition of RS AMVs offers additional modification to the TC and its environment and leads to Sinlaku's recurvature toward Japan, albeit prematurely. The results demonstrate the promise of assimilating enhanced AMV data into regional TC models. The second part of this research continues the work in the first part and further explores the influence of assimilating enhanced AMV datasets by conducting parallel data-denial WRF/EnKF experiments that assimilate AMVs subsetted horizontally by their distances to the TC center (interior and exterior) and vertically by their assigned heights (upper, middle, and lower layers). For both Sinlaku and Ike, it is found: 1) interior AMVs are important for accurate TC intensity, 2) excluding upper-layer AMVs generally results in larger track errors and ensemble spread, 3) exclusion of interior AMVs has the largest impact on the forecast of TC size than exclusively removing AMVs in particular tropospheric layers, 4) the largest ensemble spreads are found in track, intensity, and size forecasts when interior and upper-layer AMVs are not included, 5) withholding the middle-layer AMVs can improve the track forecasts. Findings from this study could influence future scenarios that involve the targeted acquisition and assimilation of high-density AMV observations in TC events. The last part of the research focuses on the assimilation of hyperspectral temperature and moisture soundings and microwave based vertically-integrated total precipitable water (TPW) products derived from polar-orbiting satellites. A comparison is made between the assimilation of soundings retrieved from the combined use of Advanced Microwave Scanning Radiometer and Atmospheric Infrared Sounder (AMSU-AIRS) and sounding products provided by CIMSS (CIMSS-AIRS). AMSU-AIRS soundings provide broad spatial coverage albeit coarse resolution, whilst CIMSS-AIRS is geared towards mesoscale applications and thus provide higher spatial resolution but restricted coverage due to the use of radiance in clear sky. The assimilation of bias-corrected CIMSS-AIRS soundings provides slightly more accurate TC structure than the control case. The assimilation of AMSU-AIRS improves the track forecasts but produces weaker and smaller storm. Preliminary results of assimilating TPW product derived from the Advanced Microwave Scanning Radiometer-EOS indicate improved TC structure over the control case. However, the short-range forecasts exhibit the largest TC track errors. In all, this study demonstrates the influence of assimilating high-resolution satellite data on mesoscale analyses and forecasts of TC track and structure. The results suggest the inclusion and assimilation of observations with high temporal resolution, broad spatial coverage, and greater proximity to TCs does indeed improve TC track and structure forecasts. Such findings are beneficial for future decisions on data collecting and retrievals that are essential for TC forecasts.
Ai Based Prediction Of High Impact Weather And Climate Extremes Under Global Warming A Perspective From The Large Scale Circulations And Teleconnections
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Author : Xiefei Zhi
language : en
Publisher: Frontiers Media SA
Release Date : 2023-02-14
Ai Based Prediction Of High Impact Weather And Climate Extremes Under Global Warming A Perspective From The Large Scale Circulations And Teleconnections written by Xiefei Zhi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-14 with Science categories.
Numerical Methods For Data Assimilation In Weather Forecasting
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Author : Hanjun Yan
language : en
Publisher:
Release Date : 2018
Numerical Methods For Data Assimilation In Weather Forecasting written by Hanjun Yan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Climatology categories.
Data assimilation plays an important role in weather forecasting. The purpose of data assimilation is try to provide a more accurate atmospheric state for future forecast. Several existed methods currently used in this field fall into two categories: statistical data assimilation and variational data assimilation. This thesis focuses mainly on variational data assimilation. The original objective function of three dimensional data assimilation (3D-VAR) consists of two terms: the difference between the pervious forecast and analysis and the difference between the observations and analysis in observation space. Considering the inaccuracy of previous forecasting results, we replace the first term by the difference between the previous forecast gradients and analysis gradients. The associated data fitting term can be interpreted using the second-order finite difference matrix as the inverse of the background error covariance matrix in the 3D-VAR setting. In our approach, it is not necessary to estimate the background error covariance matrix and to deal with its inverse in the 3D-VAR algorithm. Indeed, the existence and uniqueness of the analysis solution of the proposed objective function are already established. Instead, the solution can be calculated using the conjugate gradient method iteratively. We present the experimental results based on WRF simulations. We show that the performance of this forecast gradient based DA model is better than that of 3D-VAR. Next, we propose another optimization method of variational data assimilation. Using the tensor completion in the cost function for the analysis, we replace the second term in the 3D-VAR cost function. This model is motivated by a small number of observations compared with the large portion of the grids. Applying the alternating direction method of multipliers to solve this optimization problem, we conduct numerical experiments on real data. The results show that this tensor completion based DA model is competitive in terms of prediction accuracy with 3D-VAR and the forecast gradient based DA model. Then, 3D-VAR and the two model proposed above lack temporal information, we construct a third model in four-dimensional space. To include temporal information, this model is based on the second proposed model, in which introduce the total variation to describe the change of atmospheric state. To this end, we use the alternating direction method of multipliers. One set of experimental results generates a positive performance. In fact, the prediction accuracy of our third model is better than that of 3D-VAR, the forecast gradient based DA model, and the tensor completion based DA model. Nevertheless, although the other sets of experimental results show that this model has a better performance than 3D-VAR and the forecast gradient based DA model, its prediction accuracy is slightly lower than the tensor completion based model.
Weather Radar Polarimetry
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Author : Guifu Zhang
language : en
Publisher: CRC Press
Release Date : 2016-08-19
Weather Radar Polarimetry written by Guifu Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-19 with Science categories.
This book presents the fundamentals of polarimetric radar remote sensing through understanding wave scattering and propagation in geophysical media filled with hydrometers and other objects. The text characterizes the physical, statistical, and electromagnetic properties of hydrometers and establishes the relations between radar observables and physical state parameters. It introduces advanced remote sensing techniques (such as polarimetric phased array radar) and retrieval methods for physical parameters. The book also illustrates applications of polarimetric radar measurements in hydrometer classification, particle size distribution retrievals, microphysical parameterization, and weather quantification and forecast.
Ensemble Data Assimilation For The Analysis And Prediction Of Multiscale Tropical Weather Systems
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Author : Yue Ying
language : en
Publisher:
Release Date : 2018
Ensemble Data Assimilation For The Analysis And Prediction Of Multiscale Tropical Weather Systems written by Yue Ying and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Tropical weather systems are important components of the global circulation that span a wide range of spatial and temporal scales. On the large-scale end of the spectrum, the Madden-Julian Oscillation (MJO) is found to be the dominant mode. Atmospheric wave motion due to Earths rotation and gravity fills the spectrum from weeks to hours and from tens of thousands of kilometers to a few tens of kilometers. The thermally driven convective processes at smaller scales are chaotic in nature, which poses an intrinsic limit on the long-term predictability of tropical weather through coupling and scale interaction. This dissertation seeks to identify the predictability limits for tropical atmosphere, establishing an upper bound in expected prediction skill of these weather systems. Other scientific questions this dissertation answered are how much future satellite observations can improve the prediction skill, and how to design adaptive multiscale data assimilation methods that make better use of the available observations.Using a convection-permitting numerical model, Weather Research and Forecasting (WRF), an MJO active phase during October 2011 is simulated. The practical predictability limit is estimated from an ensemble forecast with realistic initial and boundary condition uncertainties sampled from the operational global model forecasts. Predictability limit is reached when the ensemble spread is indistinguishable from random climatological draws. Results indicate predictability is scale dependent. There is a sharp transition from slow to fast error growth at the intermediate scales (~500 km), separating the more predictable large-scale components (~2 weeks) from the less predictable small-scale components (1 day). The intrinsic predictability limits, estimated by reducing the uncertainties to 1%, are 2 weeks for larger scales and
Operational Weather Forecasting
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Author : Peter Michael Inness
language : en
Publisher: John Wiley & Sons
Release Date : 2012-12-06
Operational Weather Forecasting written by Peter Michael Inness and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
This book offers a complete primer, covering the end-to-end process of forecast production, and bringing together a description of all the relevant aspects together in a single volume; with plenty of explanation of some of the more complex issues and examples of current, state-of-the-art practices. Operational Weather Forecasting covers the whole process of forecast production, from understanding the nature of the forecasting problem, gathering the observational data with which to initialise and verify forecasts, designing and building a model (or models) to advance those initial conditions forwards in time and then interpreting the model output and putting it into a form which is relevant to customers of weather forecasts. Included is the generation of forecasts on the monthly-to-seasonal timescales, often excluded in text-books despite this type of forecasting having been undertaken for several years. This is a rapidly developing field, with a lot of variations in practices between different forecasting centres. Thus the authors have tried to be as generic as possible when describing aspects of numerical model design and formulation. Despite the reliance on NWP, the human forecaster still has a big part to play in producing weather forecasts and this is described, along with the issue of forecast verification – how forecast centres measure their own performance and improve upon it. Advanced undergraduates and postgraduate students will use this book to understand how the theory comes together in the day-to-day applications of weather forecast production. In addition, professional weather forecasting practitioners, professional users of weather forecasts and trainers will all find this new member of the RMetS Advancing Weather and Climate series a valuable tool. Provides an end-to-end description of the weather forecasting process Clearly structured and pitched at an accessible level, the book discusses the practical choices that operational forecasting centres have to make in terms of what numerical models they use and when they are run. Takes a very practical approach, using real life case-studies to contextualize information Discusses the latest advances in the area, including ensemble methods, monthly to seasonal range prediction and use of ‘nowcasting’ tools such as radar and satellite imagery Full colour throughout Written by a highly respected team of authors with experience in both academia and practice. Part of the RMetS book series ‘Advancing Weather and Climate’
Parameterization Schemes
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Author : David J. Stensrud
language : en
Publisher: Cambridge University Press
Release Date : 2007-05-03
Parameterization Schemes written by David J. Stensrud and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-03 with Science categories.
Contents: 1.