Download or read book Improved quantitative precipitation estimation over complex terrain using cloud to ground lightning data written by Carlos Manuel Minjarez-Sosa and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improving Quantitative Precipitation Estimation in Complex Terrain Using Cloud to Ground Lightning Data written by Carlos Manuel Minjarez-Sosa and published by . This book was released on 2013 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thunderstorms that occur in areas of complex terrain are a major severe weather hazard in the intermountain western U.S. Short-term quantitative estimation (QPE) of precipitation in complex terrain is a pressing need to better forecast flash flooding. Currently available techniques for QPE, that utilize a combination of rain gauge and weather radar information, may underestimate precipitation in areas where gauges do not exist or there is radar beam blockage. These are typically very mountainous and remote areas, that are quite vulnerable to flash flooding because of the steep topography. Lightning has been one of the novel ways suggested by the scientific community as an alternative to estimate precipitation over regions that experience convective precipitation, especially those continental areas with complex topography where the precipitation sensor measurements are scarce. This dissertation investigates the relationship between cloud-to-ground lightning and precipitation associated with convection with the purpose of estimating precipitation- mainly over areas of complex terrain which have precipitation sensor coverage problems (e.g. Southern Arizona). The results of this research are presented in two papers. The first, entitled Toward Development of Improved QPE in Complex Terrain Using Cloud-to-Ground Lighting Data: A case Study for the 2005 Monsoon in Southern Arizona, was published in the Journal of Hydrometeorology in December 2012. This initial study explores the relationship between cloud-to-ground lightning occurrences and multi-sensor gridded precipitation over southern Arizona. QPE is performed using a least squares approach for several time resolutions (seasonal -June, July and August-, 24 hourly and hourly) and for a 8 km grid size. The paper also presents problems that arise when the time resolution is increased, such as the spatial misplacing of discrete lightning events with gridded precipitation and the need to define a "diurnal day" that is synchronized with the diurnal cycle of convection. The second manuscript (unpublished), entitled An Improved QPE Over Complex Terrain by Using Cloud-to-Ground Lightning Occurrences, provides a new method to retrieve lightning-derived precipitation at 5 minutes and 5 Km time and space resolutions. A stationary model that employs spatio-temporal neighboring (Space and Time Invariant model -STI) improves upon the least squares method in the first paper. By applying a Kalman filter to the STI model, lightning-precipitation is retrieved by a dynamic model that changes in time. The results for seasonal and 5 minutes time resolution show that the dynamic model improves the retrievals derived by the STI model.
Download or read book Improving Infrared Based Precipitation Retrieval Algorithms Using Multi Spectral Satellite Imagery written by Nasrin Nasrollahi and published by Springer. This book was released on 2014-11-07 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space. Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved. The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
Download or read book Quantitative Precipitation Estimates in Complex Terrain written by Kyle Evan Pickens and published by . This book was released on 2010 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improving Radar based Estimation of Rainfall Over Complex Terrain written by Tufa Dinku and published by . This book was released on 2001 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysis of Relationships Between Lightning Precipitation and Runoff written by James R. Gosz and published by DIANE Publishing. This book was released on 1993 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops algorithms between lightning & precipitation depth, used lightning data to determine rainfall depth for input to a distributed parameter hydrologic model, & tested the model to predict discharge. Charts, tables & graphs.
Download or read book Improving Satellite Quantitative Precipitation Estimates by Incorporating Deep Convective Cloud Optical Depth written by Ronald D. Stenz and published by . This book was released on 2014 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Measuring Precipitation from Space written by V. Levizzani and published by Springer Science & Business Media. This book was released on 2007-05-11 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: No other book can offer such a powerful tool to understand the basics of remote sensing for precipitation, to make use of existing products and to have a glimpse of the near future missions and instruments. This book features state-of-the-art rainfall estimation algorithms, validation strategies, and precipitation modeling. More than 20 years after the last book on the subject the worldwide precipitation community has produced a comprehensive overview of its activities, achievements, ongoing research and future plans.
Download or read book Precipitation Advances in Measurement Estimation and Prediction written by Silas C. Michaelides and published by Springer Science & Business Media. This book was released on 2008-02-27 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the outcome of contributions from 51 scientists who were invited to expose their latest findings on precipitation research and in particular, on the measurement, estimation and prediction of precipitation. The reader is presented with a blend of theoretical, mathematical and technical treatise of precipitation science but also with authentic applications, ranging from local field experiments and country-scale campaigns to multinational space endeavors.
Download or read book Characterization and Modeling of Satellite Based Precipitation Uncertainty Over Complex Terrain written by Yagmur Derin and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability and quality of precipitation estimates is essential to the accuracy and reliability of hydrological modeling studies. Difficulties in the representation of high rainfall variability over mountainous areas using ground-based sensors make satellite-based precipitation products (SPPs) attractive for hydrological studies over such regions, since these products are quasi-global and available at high spatial resolution. Evaluation of several SPPs using rain gauge networks over ten mountainous regions across the globe has shown their performance is highly dependent on advancing the quality of primary data sources, one of which is passive microwave (PMW) retrievals. The evaluation of PMW retrievals is challenging, since it requires reference datasets with high temporal and spatial resolution. This difficulty can be overcome through the use of experimental ground radar (GR) X-band polarimetric radar observations. The Self-Consistent Optimal Parameterization-Microphysics Estimation (SCOP-ME), an algorithm that uses best-fitted functions of specific attenuation coefficients and backscattering differential phase shifts is used to retrieve rainfall rates and microphysical characteristics from GR. GR deployments over mountainous regions are used to evaluate the error characteristics of SCOP-ME retrieval and provide high-resolution estimates of the 4D rainfall variability. These estimates represented the benchmark precipitation dataset, which are then used in the error characterization and modeling of the PMW retrievals. To understand the source of uncertainties, a sampling volume-matching methodology is implemented between PMW and GR. The PMW retrievals showed weaker covariation than GR, with magnitude-dependent systematic error going from overestimation of light precipitation to, mainly, underestimation of heavier precipitation. Overall, these investigations indicated that PMW retrievals have uncertainties that necessitate the use of error characterization and correction procedures, especially over complex terrain. This called for error modeling of the PMW retrievals, which is conducted with quantile regression forests (QRF), a nonparametric tree-based model. The ensembles generated through the QRF model are validated by independent matchups of PMW and GR data from four complex terrains. Validation of the error model is conducted in two ways, the k-fold and leave-one region out cross validation techniques. The study showed that the error model significantly reduces both mean relative error and the random component of the error compared to the original PMW products. Moreover, it demonstrated transferability of this error model among complex terrain regions around the globe, which will allow algorithm developers to integrate it to produce Level 3 products.
Download or read book NOAA USGS Debris Flow Warning System final Report written by NOAA-USGS Debris Flow Task Force and published by . This book was released on 2005 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Atmospheric Sciences written by Board on Atmospheric Sciences and Climate and published by National Academies Press. This book was released on 1998-11-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology has propelled the atmospheric sciences from a fledgling discipline to a global enterprise. Findings in this field shape a broad spectrum of decisions--what to wear outdoors, whether aircraft should fly, how to deal with the issue of climate change, and more. This book presents a comprehensive assessment of the atmospheric sciences and offers a vision for the future and a range of recommendations for federal authorities, the scientific community, and education administrators. How does atmospheric science contribute to national well-being? In the context of this question, the panel identifies imperatives in scientific observation, recommends directions for modeling and forecasting research, and examines management issues, including the growing problem of weather data availability. Five subdisciplines--physics, chemistry, dynamics and weather forecasting, upper atmosphere and near-earth space physics, climate and climate change--and their status as the science enters the twenty-first century are examined in detail, including recommendations for research. This readable book will be of interest to public-sector policy framers and private-sector decisionmakers as well as researchers, educators, and students in the atmospheric sciences.
Download or read book Using NWP Analysis in Satellite Rainfall Estimation of Heavy Precipitation Events Over Complex Terrain written by Xinxuan Zhang and published by . This book was released on 2012 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Remote Sensing of the Terrestrial Water Cycle written by Venkataraman Lakshmi and published by John Wiley & Sons. This book was released on 2014-10-31 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing of the Terrestrial Water Cycle is an outcome of the AGU Chapman Conference held in February 2012. This is a comprehensive volume that examines the use of available remote sensing satellite data as well as data from future missions that can be used to expand our knowledge in quantifying the spatial and temporal variations in the terrestrial water cycle. Volume highlights include: An in-depth discussion of the global water cycle Approaches to various problems in climate, weather, hydrology, and agriculture Applications of satellite remote sensing in measuring precipitation, surface water, snow, soil moisture, groundwater, modeling, and data assimilation A description of the use of satellite data for accurately estimating and monitoring the components of the hydrological cycle Discussion of the measurement of multiple geophysical variables and properties over different landscapes on a temporal and a regional scale
Download or read book Improved Global High Resolution Precipitation Estimation Using Multi satellite Multi spectral Information written by Ali Behrangi and published by . This book was released on 2009 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, xxii directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Multi-Spectral Analysis (PERSIANN-MSA) the effectiveness of using multi-spectral data for precipitation estimation are examined. In comparison to the use of a single thermal infrared channel, using multi-spectral data has a potential to significantly improve rain detection and estimation skills; (3) a method proposed to integrate the previously developed cloud classification system (PERSIANN CCS) with PERSIANN-MSA. Through the integration, PERSIANN-MSA benefits from both cloud-patch classification capability as well as multi-spectral information to culminate the GEO-based precipitation estimation techniques; (4) finally, a new combination technique that incorporates multi-sensor information is developed. The technique is called REFAME, short for Rain Estimation using Forward Adjusted advection of Microwave Estimates. REFAME allows more consistent integration of MW VIS/IR information through hybrid advection and adjustment of MW precipitation rate along cloud motion streamlines obtained from a 2D cloud tracking algorithm using successive GEO/IR images. Evaluated over a range of spatial and temporal scales it is demonstrated that REFAME is a robust technique for real-time high resolution precipitation estimation using multi-satellite information.
Download or read book Improving Warm Rainfall Detection and Rainfall Estimation of a Multiple Satellite based Rainfall Retrieval Algorithm written by Negar Karbalaee and published by . This book was released on 2017 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precipitation as an essential component of the hydrologic cycle has a great importance to be measured accurately due to various applications such as hydrologic modeling, extreme weather analysis, and water resources management. Among different methods, meteorological satellites are one of the instruments that are widely used for precipitation estimation in fine spatial and temporal resolution. Precipitation Estimation from Remotely Sensed Imagery using Artificial Neural Network Cloud Classification System (PERSIANN-CCS) uses infrared (IR) data from Geostationary Earth Orbit (GEO) satellites to retrieve precipitation based on relationship between clout top temperature (Tb) and rainfall rate (RR) using a neural network technique. The complexity of Tb-RR relationship for estimating precipitation causes uncertainty in PERSIANN-CCS rainfall product. This research is focused on improving PERSIANN-CCS rainfall retrieval using several approaches:1) Bias adjustment of PERSIANN-CCS rainfall estimates using PMW satellite rainfall data: Using multi satellite data can enhance the quality of rainfall estimation considerably; in this research we have combined the rainfall data from PERSIANN-CCS and PMW rainfall to enhance the bias of PERSIANN-CCS precipitation estimates. The results showed improvement of rainfall estimation during summer and winter time.2) Increasing the rainfall detection by including warm clouds rainfall: PERSIANN-CCS currently cannot detect rainfall from clouds with temperature warmer than 253 K. This study explores the impacts of increasing the temperature threshold on precipitation estimation. The results show that increasing the threshold level can improve the PERSIANN-CCS rainfall detection.3) Generating a probabilistic framework for precipitation retrieval: The current version of PERSIANN-CCS retrieves precipitation based on the exponential function fitted to Tb-RR. The major assumption behind this relationship is that the heavier rainfalls are associated with colder clouds which cause underestimation of warmer clouds and overestimation of colder clouds rainfall. The probabilistic approach uses the corresponding sample relationship between cloud temperature and rainfall rate. The model is evaluated during a full summer season which showed improvement in both detection and estimation of rainfall in compare with the current PERSIANN-CCS algorithm.
Download or read book The Climate of Alaska written by Martha Shulski and published by University of Alaska Press. This book was released on 2007 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines the climate of Alaska and its diversity through narrative and maps, tables, and charts. Focuses on climatological features such as temperature, humidity, precipitation, and atmospheric pressure.--(Source of description unspecified.)
