Academic literature on the topic 'Rain model'

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Journal articles on the topic "Rain model"

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Grieser, Jürgen, and Steve Jewson. "The RMS TC-Rain Model." Meteorologische Zeitschrift 21, no. 1 (February 1, 2012): 79–88. http://dx.doi.org/10.1127/0941-2948/2012/0265.

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Bridger, Nguyen, and Chiao. "Developing Spatially Accurate Rainfall Predictions for the San Francisco Bay Area through Case Studies of Atmospheric River and other Synoptic Events." Atmosphere 10, no. 9 (September 12, 2019): 541. http://dx.doi.org/10.3390/atmos10090541.

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Rainfall patterns in the San Francisco Bay Area (SFBA) are highly influenced by local topography. It has been a forecasting challenge for the main US forecast models. This study investigates the ability of the Weather Research and Forecasting (WRF) model to improve upon forecasts, with particular emphasis on the rain shadow common to the southern end of the SFBA. Three rain events were evaluated: a mid-season atmospheric river (AR) event with copious rains; a typical non-AR frontal passage rain event; and an area-wide rain event in which zero rain was recorded in the southern SFBA. The results show that, with suitable choices of parameterizations, the WRF model with a resolution around 1 km can forecast the observed rainfall patterns with good accuracy, and would be suitable for operational use, especially to water and emergency managers. Additionally, the three synoptic situations were investigated for further insight into the common ingredients for either flooding rains or strong rain shadow events.
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Choi, Dong You, Jae Young Pyun, Sun Kuh Noh, and Sang Woong Lee. "Comparison of Measured Rain Attenuation in the 12.25 GHz Band with Predictions by the ITU-R Model." International Journal of Antennas and Propagation 2012 (2012): 1–5. http://dx.doi.org/10.1155/2012/415398.

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Quantitative analysis and prediction of radio attenuation is necessary in order to improve the reliability of satellite-earth communication links and for economically efficient design. For this reason, many countries have made efforts to develop their own rain attenuation prediction models that are suited to their rain environment. In this paper, we present the results of measurements of rain-induced attenuation in vertically polarized signals propagating at 12.25 GHz during certain rain events, which occurred in the rainy wet season of 2001 and 2007 at Yong-in, Korea. The rain attenuation over the link path was measured experimentally and compared with the attenuation obtained using the ITU-R model.
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Fu, Fangfa, Yao Wang, Fengchang Lai, Weizhe Xu, and Jinxiang Wang. "Efficient rain–fog model for rain detection and removal." Journal of Electronic Imaging 29, no. 02 (April 7, 2020): 1. http://dx.doi.org/10.1117/1.jei.29.2.023020.

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Matricciani, Emilio. "Rain attenuation predicted with a two-layer rain model." European Transactions on Telecommunications 2, no. 6 (November 1991): 715–27. http://dx.doi.org/10.1002/ett.4460020615.

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Zhang, Tao, Wanmin Zhao, and Dongjun Tong. "Multiscale Model for Urban Flood Control Planning Based on Microcirculation." Open House International 41, no. 3 (September 1, 2016): 66–70. http://dx.doi.org/10.1108/ohi-03-2016-b0011.

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Flood season in our country is characterized by frequent heavy rains, and flood problems are becoming increasingly serious. The uneven distribution of water resources causes conflicts in the occurrence of floods and droughts. Implementing effective flood control planning and solving drought and flood disasters are the research highlights of relevant institutions both domestic and abroad. This study develops a multiscale method of urban flood control planning based on microcirculation. A microcirculation water ecosystem, which consists of six elements, namely, collecting, interacting, precipitating, reserving, storing, and purifying, is introduced. This study investigates precipitation; peak shaving; recycle mode of filtration at the macro level in different regions; “hierarchy” in rainwater ecosystems in rain parks, heavy rain garden parks, and wetland parks at the meso level; and the concept of zero-emission rain in residential areas and roads at the micro level. Finally, this study analyzes a rain garden and its domestic application. A conclusion is drawn that the flood control planning model based on microcirculation can effectively reduce rain runoff. Empirical measurement proves that the proposed multiscale model for city flood control planning based on microcirculation promotes flood control and effectively reduces the occurrence of droughts and floods.
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Chen, Shan-Tai, Chien-Chen Wu, Wann-Jin Chen, and Jen-Chi Hu. "Rain-Area Identification Using TRMM/TMI Data by Data Mining Approach." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 3 (May 20, 2008): 243–48. http://dx.doi.org/10.20965/jaciii.2008.p0243.

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Rain-area identification distinguishes between rainy and non-rainy areas, which is the first step in some critical real-world problems, such as rain intensity identification and rain-rate estimation. We develop a data mining approach for oceanic rain-area identification during typhoon season, using microwave data from the Tropical Rainfall Measuring Mission (TRMM) satellite. Three schemes tailored for the problem are developed, namely (1) association rule analysis for uncovering the set of potential attributes relevant to the problem, (2) three-phase outlier removal for cleaning data and (3) the neural committee classifier (NCC) for achieving more accurate results. We created classification models from 1998-2004 TRMM Microwave Imager (TRMM-TMI) satellite data and used Automatic Rainfall and Meteorological Telemetry System (ARMTS) rain gauge data measurements to evaluate the model. Experimental results show that our approach achieves high accuracy for the rain-area identification problem. The classification accuracy of our approach, 96%, outperforms the 78.6%, 77.3%, 83.3% obtained by the scattering index, threshold check, and rain flag methods, respectively.
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Liu, Jia Jun, Xiao Yang Jiao, Zhi Gang Yang, and Jian Fang Liu. "The Research for the Piezoelectricity Rain-Removing System of Rearview Mirror." Applied Mechanics and Materials 215-216 (November 2012): 74–77. http://dx.doi.org/10.4028/www.scientific.net/amm.215-216.74.

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In order to solve the problem of blurry sight made by rain drop on the rearview mirror on rainy day, a rain-removing device making use of piezoelectric vibrator is put forward. Design the structure of the rain-removing device, build its finite element model and modal analysis for the piezoelectric vibrator is done. Piezoelectric rain-removing device prototype is manufactured and amplitude of the mirror is tested with different voltages and frequency. At last rain-removing effect for the rear mirror is measured with varies of angle at which piezoelectric vibrator is installed. The proportion of the removed rain drop is 80% when piezoelectric vibrator angle is 60° and the voltage and frequency on the piezoelectric vibrator is100V and 800Hz respectively.
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Tang, Hongzhong, Ling Zhu, Dongbo Zhang, and Xiang Wang. "Single image rain removal model using pure rain dictionary learning." IET Image Processing 13, no. 10 (August 22, 2019): 1797–804. http://dx.doi.org/10.1049/iet-ipr.2018.5122.

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Carstensen, Jacob, Marinus K. Nielsen, and Helle Strandbæk. "Prediction of hydraulic load for urban storm control of a municipal WWT plant." Water Science and Technology 37, no. 12 (June 1, 1998): 363–70. http://dx.doi.org/10.2166/wst.1998.0562.

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Three different methodologies are assessed which provide predictions of the hydraulic load to the treatment plant one hour ahead. The three models represent three different levels of complexity ranging from a simple regression model over an adaptive grey-box model to a complex hydrological and full dynamical wave model. The simple regression model is estimated as a transfer function model of rainfall intensity to influent flow. It also provides a model for the base flow. The grey-box model is a state space model which incorporates adaptation to the dry weather flow as well as the rainfall runoff. The full dynamical flow model is a distributed deterministic model with many parameters, which has been calibrated based on extensive measurement campaigns in the sewer system. The three models are compared by the ability to predict the hydraulic load one hour ahead. Five rain events in a test period are used for evaluating the three different methods. The predictions are compared to the actual measured flow at the plant one hour later. The results show that the simple regression model and the adaptive grey-box model which are identified and estimated on measured data perform significantly better than the hydrological and full dynamical flow model which is not identifiable and needs calibration by hand. For frontal rains no significant difference in the prediction performance between the simple regression model and the adaptive grey-box model is observed. This is due to a rather uniform distribution of frontal rains. A single convective rain justifies the adaptivity of the grey-box model for non-uniformly distributed rain, i.e. the predictions of the grey-box model were significantly better than the predictions of the simple regression model for this rain event. In general, models for model-based predictive control should be kept simple and identifiable from measured data.
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Dissertations / Theses on the topic "Rain model"

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To, Chun-hung. "Stochastic model of daily rainfall." Click to view the E-thesis via HKUTO, 1989. http://sunzi.lib.hku.hk/hkuto/record/B31976098.

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Nie, Congling. "Wind/Rain Backscatter Modeling and Wind/Rain Retrieval for Scatterometer and Synthetic Aperture Radar." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1632.

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Using co-located space-borne satellite (TRMM PR, ESCAT on ERS 1/2) measurements, and numerical predicted wind fields (ECMWF), the sensitivity of C-band backscatter measurement to rain is evaluated. It is demonstrated that C-band radar backscatter can be significantly altered by rain surface perturbation, an effect that has been previously neglected. A low-order wind/rain backscatter model is developed that has inputs of surface rain rate, incidence angle, wind speed, wind direction, and azimuth angle. The wind/rain backscatter model is accurate enough for describing the total backscatter in raining areas with relatively low variance. Rain has a more significant impact on measurements at high incidence angles than at low incidence angles. Using three distinct regimes, the conditions for which wind, rain, and both wind and rain can be retrieved from scatterometer backscatter measurements are determined. The effects of rain on ESCAT wind-only retrieval are evaluated. The additional scattering from rain causes estimated wind speeds to be biased high and estimated wind directions to be biased toward the along-track direction in heavy rains. To compensate for rain-induced backscatter, we develop a simultaneous wind/rain retrieval method (SWRR), which simultaneously estimates wind and rain from ESCAT backscatter measurements with an incidence angle of over 40 degrees. The performance of SWRR under typical wind/rain conditions is evaluated through simulation and validation with collocated TRMM PR and ECMWF data sets. SWRR is shown to significantly improve wind velocity estimates and the SWRR-estimated rain rate has relatively high accuracy in moderate to heavy rain cases. RADARSAT-1 ScanSAR SWA images of Hurricane Katrina are used to retrieve surface wind vectors over the ocean. Collocated H*wind wind directions are used as the wind direction estimate and the wind speed is derived from SAR backscatter measurements by inversion of a C-band HH-polarization Geophysical Model Function (GMF) that is derived from the VV-polarization GMF, CMOD5, using a polarization ratio model. Because existing polarization models do not fit the ScanSAR SWA data well, a recalibration model is proposed to recalibrate the ScanSAR SWA images. Validated with collocated H*wind wind speed estimates, the mean difference between SAR-retrieved and H*wind speed is small and the root mean square (RMS) error is below 4 m/s. Rain effects on the ScanSAR measurements are analyzed for three different incidence angle ranges using collocated ground-based Doppler weather radar (NEXRAD) rain measurements. Compared with the scatterometer-derived model, the rain-induced backscatter observed by the ScanSAR at incidence angles 44 to 45.7 degrees is consistent with the scatterometer-derived model when the polarization difference between HH and VV polarizations is considered.
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To, Chun-hung, and 杜振雄. "Stochastic model of daily rainfall." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31976098.

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Faridhosseini, Alireza. "Evaluation of Summer Rainfall Estimation by Satellite Data using the ANN Model for the GCM Subgrid Distribution." Thesis, The University of Arizona, 1998. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_etd_hy0021_m_sip1_w.pdf&type=application/pdf.

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Ramdass, Indarjit. "Modelling forest dynamics and management of natural tropical rain forests." Thesis, University of Edinburgh, 1987. http://hdl.handle.net/1842/11890.

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Cardoso, Tamre Porter. "A hierarchical Bayes model for combining precipitation measurements from different sources /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6372.

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SOUZA, RODOLFO SABOIA LIMA DE. "A RAIN INDUCED ATTENUATION PREDICTION MODEL IN TROPICAL AND EQUATORIAL REGIONS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1992. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9513@1.

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A propagação das ondas eletromagnéticas em freqüências superiores a 10 GHz sofre uma degradação causada pela chuva. O efeito da precipitação é particularmente importante em regiões de clima tropical e equatorial onde se observam as mais elevadas taxas de precipitação. Este trabalho apresenta resultados de um programa de medidas de propagação realizado no Brasil, desde 1987, utilizando radiômetros operando na faixa de 12 GHz e pluviômetros. A partir dos dados de atenuação e taxa de precipitação medidos simultaneamente em 6 locais em diferentes regiões do Brasil, durante pelo menos 1 ano, que forneceram distribuições estatísticas de 10 anos em 6 estações, foi desenvolvido um modelo de previsão da atenuação causada pela chuva em enlaces satélite. Apresenta-se ainda resultados do estudo do comportamento dinâmico da atenuação por chuvas.
The rain attenuation is a major impairment on the radio wave propagation at frequencies above 10 GHz. The rain effect is particularly important in tropical and equatorial regions which experience the most severe rain rates. This work presents results of the propagation measurement campaign conducted in Brazil since 1987, using radiometers, operating at the frequency of 12 GHz, and raingauges. A rain induced attenuation prediction model for satellite- Earth links was developed from the data of 10 year- stations measured in Brazil. The results of the dynamic behaviour of rain attenuation are also presented.
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DeSordi, Steven Paul. "Utah local area model sensitivity to boundary conditions for summer rain simulations." Wright-Patterson AFB, Ohio : Dept. of the Air Force, 1996. http://stinet.dtic.mil/cgi-bin/fulcrum%5Fmain.pl?database=ft%5Fu2&searchid=0&keyfieldvalue=ADA319136&filename=%2Ffulcrum%2Fdata%2FTR%5Ffulltext%2Fdoc%2FADA319136.pdf.

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Thesis (M.S.)--University of Utah, 1996. Thesis from the University of Utah's Department of Meteorology explores the sensitivity of the pecipitation-predicting model known as the Utah Limited Area Model (LAM) to the way that the lateral and upper boundary conditions are applied. The approach is different from most past studies of LAM boundary specification because it is founded upon a medium-range simulation using real data. Many other studies of boundary conditions have used idealized cases or short-term (a few days or less) predictions.
Title from web page (viewed Oct. 30, 2003). "96-084." "August 1996." Includes bibliographical references p. [110]-112. Also available in print version.
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Nielsen, Seth N. "A wind and rain backscatter model derived from AMSR and SeaWinds data /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1979.pdf.

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Nielsen, Seth Niels. "A Wind and Rain Backscatter Model Derived from AMSR and SeaWinds Data." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1410.

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The SeaWinds scatterometers aboard the QuikSCAT and ADEOS II satellites were originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross-section. Recently, an algorithm for simultaneously retrieving wind and rain (SWR) from scatterometer measurements was developed that enables SeaWinds to correct rain-corrupted wind measurements and retrieve rain rate data. This algorithm is based on co-locating Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) and SeaWinds on QuikSCAT data. In this thesis, a new wind and rain radar backscatter model is developed for the SWR algorithm using a global co-located data set with rain data from the Advanced Microwave Scanning Radiometer (AMSR) and backscatter data from the SeaWinds scatterometer aboard the Advanced Earth Observing Satellite 2 (ADEOS II). The model includes the effects of phenomena such as backscatter due to wind stress, atmospheric rain attenuation, and effective rain backscatter. Rain effect parameters of the model vary with integrated rain rate, which is defined as the product of rain height and rain rate. This study accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. A simple model for the mean rain height versus latitude and longitude is proposed based on AMSR data and methods of incorporating this model into the SWR retrieval process are developed. The performance of the new SWR algorithm is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and NCEP numerical weather prediction winds. The new SWR algorithm produces accurate rain estimates and detects rain with a low false alarm rate. The wind correction capabilities of the SWR algorithm are effective at correcting rain-induced inaccuracies. A qualitative comparison of the wind and rain retrieval for Hurricane Isabel demonstrates these capabilities.
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Books on the topic "Rain model"

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Huth, Andreas. The rain forest growth model FORMIX3: Model description and analysis of forest growth and logging scenarios for the Deramakot forest reserve (Malaysia). Göttingen: E. Goltze, 1998.

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Pink, Michael. The planet's most successful business model. Lake Mary, Fla: Excel Books, 2008.

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Hogan, T. Description of the industrial combustion emissions model (version 6.0). Research Triangle Park, NC: U.S. Environmental Protection Agency, Air and Energy Engineering Research Laboratory, 1988.

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Holden, Nicholas Mark. The mechanism of milled peat rewetting: Development of a stockpile rewetting model. Dublin: University College Dublin, 1998.

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Kulkarni, Ashwini. Examining Indian monsoon variability in coupled climate model simulations and projections. Pune: Indian Institute of Tropical Meteorology, 2010.

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Rientjes, Thomas Henricus Maria. Inverse modelling of the rainfall-runoff relation: A multi objective model calibration approach. Delft: Delft University Press, 2004.

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Tattelman, Paul. Model vertical profiles of extreme rainfall rate, liquid water content, and drop-size distribution. Hanscom AFB, MA: Atmospheric Sciences Division, Air Force Geophysics Laboratory, 1985.

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Fulton, James L. Application of a distributed-routing rainfall-runoff model to flood-frequency estimation in Somerset County, New Jersey. West Trenton, N.J: U.S. Dept. of the Interior, U.S. Geological Survey, 1990.

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1960-, Ramankutty Ramesh, and Shah Jitendra J. 1952-, eds. Rains-Asia: An assessment model for acid deposition in Asia. Washington, D.C: World Bank, 1997.

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C, Risley John. Use of a precipitation-runoff model for simulating effects of forest management on streamflow in 11 small drainage basins, Oregon coast range. Portland, Or: U.S. Dept. of the Interior, U.S. Geological Survey, 1994.

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Book chapters on the topic "Rain model"

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Mill, Wojciech. "Integrated Modelling of Acidification Effects to Forest Ecosystems — Model Sonox." In Acid rain 2000, 1289–94. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-007-0810-5_62.

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Li, Hu, Akikazu Kaga, and Katsuhito Yamaguchi. "Prediction of Soil Acidification Using a Dymanic Model at a Bamboo Forest in Osaka Prefecture." In Acid rain 2000, 1295–300. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-007-0810-5_63.

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Hao, Jiming, Xuemei Ye, Lei Duan, and Zhongping Zhou. "Calculating Critical Loads of Sulfur Deposition for 100 Surface Waters in China Using the Magic Model." In Acid rain 2000, 1157–62. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-007-0810-5_40.

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Thornton, Gareth J. P. "Calculating Weathering Rates of Stream Catchments in the English Lake District Using Critical Element Ratios, Mass-Balance Budgets and the Magic Model." In Acid rain 2000, 1241–46. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-007-0810-5_54.

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Fumoto, Tamon, Junko Shindo, Noriko Oura, and Harald Sverdrup. "Adapting the Profile Model to Calculate the Critical Loads for East Asian Soils by Including Volcanic Glass Weathering and Alternative Aluminum Solubility System." In Acid rain 2000, 1247–52. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-007-0810-5_55.

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Kandelaars, Patricia P. A. A. H. "A Static Optimization Model for Rain Gutters." In Economic Models of Material-Product Chains for Environmental Policy Analysis, 89–109. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-6399-8_6.

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Islam, Md Anoarul, Manabendra Maiti, Pradip Kumar Ghosh, and Judhajit Sanyal. "Machine Learning-Based Rain Attenuation Prediction Model." In Computers and Devices for Communication, 15–22. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8366-7_3.

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Yamartino, R., J. Pleim, and W. Lung. "Development of an Acid Rain Impact Assessment Model." In Air Pollution Modeling and Its Application IV, 91–117. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2455-3_5.

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Pan, Chenxi, Xuan Min, and Yuanyuan Mu. "Designing Rain Classroom-Based Blended Learning Model for English Public Speaking Course." In Learning Technologies and Systems, 454–60. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66906-5_43.

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Perales, Javier, Gianpierre Zapata, and Carlos Raymundo. "Energy Model Based on Fluvial Rainfall for the Rural Population with Torrential Rain." In Proceedings of the 4th Brazilian Technology Symposium (BTSym'18), 171–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16053-1_16.

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Conference papers on the topic "Rain model"

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Ermis, Seda, and Saibun Tjuatja. "A microwave backscattering model for rain column." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723724.

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Jacob, Maria, W. Linwood Jones, Kyla Drushka, Andrea Santos-Garcia, William Asher, and Marcelo Scavuzzo. "Salinity rain impact model (RIM) optimization: Preliminary results." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8127614.

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Zhang, Mei, and Soo Kim. "A Statistical Approach for Dynamic Rain Attenuation Model." In 29th AIAA International Communications Satellite Systems Conference (ICSSC-2011). Reston, Virigina: American Institute of Aeronautics and Astronautics, 2011. http://dx.doi.org/10.2514/6.2011-8042.

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Beauvilliers, Paul, A. K. Wang, Leonard Ponzio, April Babbit, and Gary Cho. "A rain attenuation time series model for MUOS." In MILCOM 2008 - 2008 IEEE Military Communications Conference (MILCOM). IEEE, 2008. http://dx.doi.org/10.1109/milcom.2008.4753491.

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Ong, J. T. "Rain rate and attenuation prediction model for Singapore." In Ninth International Conference on Antennas and Propagation (ICAP). IEE, 1995. http://dx.doi.org/10.1049/cp:19950388.

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Kumar, Vivek, Hitesh Singh, Kumud Saxena, Boncho Bonev, and Ramjee Prasad. "Approximations for ITV Rain Model Using Machine Learning." In 2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). IEEE, 2021. http://dx.doi.org/10.1109/icest52640.2021.9483552.

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Awan, Malik Shahzad Kaleem, and Mian Muhammad Awais. "Towards a Generic Model for Forecasting Rain Duration Using GITIC Model." In 2008 15th Annual IEEE International Conference on Engineering of Computer Based Systems (ECBS). IEEE, 2008. http://dx.doi.org/10.1109/ecbs.2008.25.

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Hirano, T., J. Hirokawa, and M. Ando. "Estimation of rain rate using measured rain attenuation in the Tokyo tech millimeter-wave model network." In 2010 IEEE International Symposium Antennas and Propagation and CNC-USNC/URSI Radio Science Meeting. IEEE, 2010. http://dx.doi.org/10.1109/aps.2010.5562253.

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H. Khraisat, Yahya. "Computational Model of Radar Signal Spectrum Reflected from Rain." In 2006 European Radar Conference. IEEE, 2006. http://dx.doi.org/10.1109/eurad.2006.280300.

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Chankeaw, Natthapong, Pongputhai Udomariyasap, Donekeo Lakanchanh, Suthichai Noppanakeepong, and Nipha Leelaruji. "Rainfall Rate and Rain Attenuation Model in Bangkok Thailand." In 2008 International Symposium on Communications and Information Technologies (ISCIT). IEEE, 2008. http://dx.doi.org/10.1109/iscit.2008.4700202.

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Reports on the topic "Rain model"

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Jacobson, J., P. Irving, A. Kuja, J. Lee, D. Shriner, J. Troiano, S. Perrigan, and V. Cullinan. A collaborative effort to model plant response to acidic rain. Office of Scientific and Technical Information (OSTI), January 1989. http://dx.doi.org/10.2172/5415201.

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Douglas, Thomas, Merritt Turetsky, and Charles Koven. Increased rainfall stimulates permafrost thaw across a variety of Interior Alaskan boreal ecosystems. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41050.

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Earth’s high latitudes are projected to experience warmer and wetter summers in the future but ramifications for soil thermal processes and permafrost thaw are poorly understood. Here we present 2750 end of summer thaw depths representing a range of vegetation characteristics in Interior Alaska measured over a 5-year period. This included the top and third wettest summers in the 91-year record and three summers with precipitation close to mean historical values. Increased rainfall led to deeper thaw across all sites with an increase of 0.7 ± 0.1 cm of thaw per cm of additional rain. Disturbed and wetland sites were the most vulnerable to rain-induced thaw with ~1 cm of surface thaw per additional 1 cm of rain. Permafrost in tussock tundra, mixed forest, and conifer forest was less sensitive to rain-induced thaw. A simple energy budget model yields seasonal thaw values smaller than the linear regression of our measurements but provides a first-order estimate of the role of rain-driven sensible heat fluxes in high-latitude terrestrial permafrost. This study demonstrates substantial permafrost thaw from the projected increasing summer precipitation across most of the Arctic region.
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3

Bahder, Thomas B., and John D. Bruno. Transient Response of an Electromagnetic Rail Gun: A Pedagogical Model. Fort Belvoir, VA: Defense Technical Information Center, May 1998. http://dx.doi.org/10.21236/ada345008.

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4

Estler, W. Tyler, Bruce R. Borchardt, Charles J. Fronczek, and Ralph C. Veale. Rail straightness metrology at the David W. Taylor model basin. Gaithersburg, MD: National Bureau of Standards, 1986. http://dx.doi.org/10.6028/nbs.ir.86-3443.

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5

Peterson, Eric, Wenbin Wei, and Lydon George. A Model for Integrating Rail Services with other Transportation Modalities: Identifying the Best Practices and the Gaps for California’s Next State Rail Plan. Mineta Transportation Institute, July 2021. http://dx.doi.org/10.31979/mti.2021.1949.

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The California State Rail Plan (CSRP) is among the best rail plan documents published by any jurisdiction in the United States to date. As such, the CSRP is used in this paper as the basis of comparison to other state rail service plans. These plans will have been submitted to the Federal Railroad Administration (FRA) on record as of June 2020—as required under Section 303 of the Passenger Rail Investment and Improvement Act (PRIIA) of 2008. The purpose of this paper is to identify the best practices and gaps that may inform California and other states in their future rail service plan development. This paper is grounded in the realization that, while the general outline of FRA requirements is uniform for all states, the actual content and inclusion of these requirements in the myriad state plans varies greatly. For example, California was granted an exception to help update FRA Rail Plan Guidance for its 2018 Rail Plan, other states have complained that FRA guidance and requirements on rail service planning have put state rail agencies in the position of constantly writing plans with little or no time to implement them. Throughout this research, the authors identify all the elements of FRA guidelines as reflected in the CSRP and rail plans of other states. This report also identifies the best features and planning strategies that may inform and improve the state rail planning process going forward, steps that will positively contribute to the public benefit of enhanced rail systems.
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6

Tazaz, Amanda, Lance King, Melissa Dyehouse, Robert Schoen, Rachel Wilson, Steve Blumsack, and Carmen Green. Planning for a Rainy Day: A Lesson Study Model Eliciting Activity Toolkit. Florida State University Libraries, January 2013. http://dx.doi.org/10.17125/fsu.1517867082.

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7

Wang, Yao, Mirela D. Tumbeva, and Ashley P. Thrall. Evaluating Reserve Strength of Girder Bridges Due to Bridge Rail Load Shedding. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317308.

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This research experimentally and numerically evaluated the reserve strength of girder bridges due to bridge rail load shedding. The investigation included: (1) performing non-destructive field testing on two steel girder bridges and one prestressed concrete girder bridge, (2) developing validated finite element numerical models, and (3) performing parametric numerical investigations using the validated numerical modeling approach. Measured data indicated that intact, integral, reinforced concrete rails participate in carrying live load. Research results culminated in recommendations to evaluate the reserve strength of girder bridges due to the participation of the rail, as well as recommendations for bridge inspectors for evaluating steel girder bridges subjected to vehicular collision.
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8

Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, Stacey L. Clark, Lisa O'Donnell, April Rose, Annamarie Rutledge, and Emily King. Vulnerability of Austin’s urban forest and natural areas: A report from the Urban Forestry Climate Change Response Framework. U.S. Department of Agriculture, Northern Forests Climate Hub, October 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Projected shifts in plant hardiness and heat zones were used to understand how less common native species, nonnative species, and cultivars may tolerate future conditions. We also assessed the adaptability of planted and naturally occurring trees to stressors that may not be accounted for in habitat suitability models such as drought, flooding, wind damage, and air pollution. The summary of the contemporary landscape identifies major stressors currently threatening trees and forests in Austin. Major current threats to the region’s urban forest include invasive species, pests and disease, and development. Austin has been warming at a rate of about 0.4°F per decade since measurements began in 1938 and temperature is expected to increase by 5 to 10°F by the end of this century compared to the most recent 30-year average. Both increases in heavy rain events and severe droughts are projected for the future, and the overall balance of precipitation and temperature may shift Austin’s climate to be more similar to the arid Southwest. Species distribution modeling of native trees suggests that suitable habitat may decrease for 14 primarily northern species, and increase for four more southern species. An analysis of tree species vulnerability that combines model projections, shifts in hardiness and heat zones, and adaptive capacity showed that only 3% of the trees estimated to be present in Austin based on the most recent Urban FIA estimate were considered to have low vulnerability in developed areas. Using a panel of local experts, we also assessed the vulnerability of developed and natural areas. All areas were rated as having moderate to moderate-high vulnerability, but the underlying factors driving that vulnerability differed by natural community and between East and West Austin. These projected changes in climate and their associated impacts and vulnerabilities will have important implications for urban forest management, including the planting and maintenance of street and park trees, management of natural areas, and long-term planning.
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Lewis, Michael E., Donald M. Maffei, and Michael M. Schutte. Design of an Advanced Development Model Optical Disk-Based Redundant Array of Independent Disks (RAID) High Speed Mass Storage Subsystem. Fort Belvoir, VA: Defense Technical Information Center, October 1997. http://dx.doi.org/10.21236/ada341320.

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Fu, Rong, Rong Fu, and Rong Fu. Using the GoAmazon-CHUVA measurements to understand what causes the biases in the onset of the rainy season in Amazonia in climate models. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1556997.

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