Dissertations / Theses on the topic 'Weather Research And Forecasting Model (WRF)'

The tropical cyclone is a majestic, yet violent atmospheric weather system occurring over tropical waters. Their majesty evolves from the significant range of spatial scales they operate over: from the mesoscale, to the larger synoptic-scale. Their associated violent winds and seas, however, are often the cause of damage and destruction for settlements in their path. Between 10/11/07 and 16/11/07, tropical cyclone Sidr formed and intensified into a category 5 hurricane over the southeast tropical waters of the northern Indian Ocean. Sidr tracked west, then north, during the course of its life, and eventually made landfall on 15/11/07, as a category 4 cyclone near the settlement of Barguna, Bangladesh. The storm affected approximately 2.7 million people in Bangladesh, and of that number 4234 were killed. In this study, the dynamics of tropical cyclone Sidr are simulated using version 2.2.1 of Advanced Weather Research and Forecasting — a non-hydrostatic, two-way interactive, triply-nested-grid mesoscale model. Three experiments were developed examining model sensitivity to ocean-atmosphere interaction; initialisation time; and choice of convective parameterisation scheme. All experiments were verified against analysed synoptic data. The ocean-atmosphere experiment involved one simulation of a cold sea surface temperature, fixed at 10 °C; and simulated using a 15 km grid resolution. The initialisation experiment involved three simulations of different model start time: 108-, 72-, and 48-hours before landfall respectively. These were simulated using a 15 km grid resolution. The convective experiment consisted of four simulations, with three of these using a different implicit convective scheme. The three schemes used were, the Kain-Fritsch, Betts-Miller-Janjic, and Grell-Devenyi ensemble. The fourth case simulated convection explicitly. A nested domain of 5km grid spacing was used in the convective experiment, for high resolution modelling. In all experiments, the Eta-Ferrier microphysics scheme, and the Mellor-Yamada-Janjic planetary boundary layer scheme were used. As verified against available observations, the model showed considerable sensitivity in each of the experiments. The model was found to be well suited for combining ocean-atmosphere interactions: a cool sea surface caused cyclone Sidr to dissipate within 24 hours. The initialisation simulations indicated moderate model sensitivity to initialisation time: variations were found for both cyclone track and intensity. Of the three simulations, an initialisation time 108 hours prior to landfall, was found to most accurately represent cyclone Sidr’s track and intensity. Finally, the convective simulations showed that considerable differences were found in cyclone track, intensity, and structure, when using different convective schemes. The Kain-Fritsch scheme produced the most accurate cyclone track and structure, but the rainfall rate was spurious on the sub-grid-scale. The Betts-Miller-Janjic scheme resolved realistic rainfall on both domains, but cyclone intensity was poor. Of particular significance, was that explicit convection produced a similar result to the Grell-Devenyi ensemble for both model domain resolutions. Overall, the results suggest that the modelled cyclone is highly sensitive to changes in initial conditions. In particular, in the context of other studies, it appears that the combination of convective scheme, microphysics scheme, and boundary layer scheme, are most significant for accurate track and intensity prediction.

On January 29-30, 2008 a squall line of thunderstorms moved through the Ohio Valley resulting in four deaths and one injury. Such events highlight the importance of accurate forecasting for public safety. Mesoscale Modeling plays an important role in any forecast of a potential squall line. The focus of this study was to examine the performance of several parameterization scheme combinations in the Weather Research and Forecasting Model version three (WRF) as they related to this event. These examinations included cloud microphysics (WRF Single-Moment 3-class, 6-class, and Goddard), cumulus parameterization (Kain-Fritsch and Bets-Miller-Janjic) and planetary boundary layer schemes (Yonsei-University and Mellor-Yamada-Janjic). A total of 12 WRF simulations were conducted for all potential scheme combinations. Data from the WRF simulations for several locations in south central Kentucky were analyzed and compared using Kentucky Mesonet observations for four locations: Bowling Green, Russellville, Murray and Liberty, KY. A fine model resolution of 1 km was used over these locations. Coarser resolutions of 3 km and 9 km were used on the outer two domains, which encompassed the Ohio and Tennessee Valleys. The model simulation performance was assessed using established statistical measures for the above four locations and by visually comparing the North American Regional Reanalysis dataset (NARR) along with modeled simulations. The most satisfactory scheme combination was the WRF Single-Moment 3-class Microphysics scheme, Kain-Fritsch cumulus parameterization scheme and Yonsei University scheme for the planetary boundary layer. The planetary boundary layer schemes were noted to have the greatest influence in determining the most satisfactory model simulations. There was limited influence from different selections of microphysics and cumulus parameterization schemes. The preferred physics parameters from these simulations were then used in six additional simulations to analyze the affect different initialization data sets have with regards to model output. Data sets used in these simulations were the Final Operational Analysis global data, North American Regional Reanalysis (3 and 6 hour) and the North American Mesoscale Model at 1, 3 and 6 hour timesteps, for a total of six simulations. More timesteps or an increase in model resolution did not materially improve the model performance.

Air quality forecasts are of great value since several pollutants in our environment effect both human health, global climate, vegetation, crop yields, animals, materials and acidification of forests and lakes. Air-quality forecasts help to make people aware of the presence and the quantity of pollutants, and give them a chance to protect themselves, their business and the Earth. Many different air-quality models are in daily use all over the world, providing citizens with forecasts of air quality and warnings of unhealthy air quality if recommended highest concentrations are exceeded. This study adapts the WRF meteorological model (Weather research and Forecasting model) to be a driver of the CMAQ air-quality model (models-3 Community Multiscale Air Quality model). Forecasts of ozone and nitrogen dioxide concentrations from this coupled WRF/CMAQ modelling system are tested against observed data during a four-day period in May, 2006. The Lower Fraser Valley study area is a fertile valley surrounded by mountain chains in southwest British Columbia, Canada. The valley stretches from the Pacific coast eastwards towards the Rocky Mountains. This valley hosts more than 2 million people and it is west Canada’s fastest growing region. The Lower Fraser Valley holds a big city, Vancouver, several suburbs, numerous industries and a widespread agricultural production. During the analysed four-day period in May, a synoptic high-pressure built over the region, favoring high concentrations of pollutants as ozone and nitrogen dioxide. The created WRF/CMAQ model forecasted an acceptable magnitude of nitrogen dioxide but the daily variations are not recreated properly by the model. The WRF/CMAQ model forecasts the daily variation of ozone in a satisfying way, but the forecasted concentrations are overestimated by between 20 and 30 ppb throughout the study. Factors that could contribute to the elevated ozone concentrations were investigated, and it was found that the weather forecasting model WRF was not generating fully reliable meteorological values, which in turn hurt the air-quality forecasts. As the WRF model usually is a good weather forecasting model, the short spin-up time for the model could be a probable cause for its poor performance.
Prognoser över luftkvaliteten är mycket värdefulla, då flera luftföroreningar i vår närmiljö påverkar människans hälsa, det globala klimatet, vegetation, djur, material och bidrar till försurning av skog och vattendrag. Luftkvalitetsprognoser gör människan mer medveten om närvaron av luftföroreningar och i vilken mängd de finns. De ger människan en chans att vidta skyddsåtgärder för att skydda sig själv, sitt eventuella levebröd, och Jorden. Många olika luftkvalitetsmodeller används idag dagligdags över hela världen och förser invånare med prognoser för luftkvaliteten och varningar om koncentrationerna av föroreningar överstiger rekommenderade värden. I denna studie används väderprognosmodellen WRF (Weather Research and Forecasting model) för att driva luftkvalitetsmodellen CMAQ (models-3 Community Multiscale Air Quality model). Prognoser av ozon- och kvävedioxidhalterna i luften från den kopplade WRF/CMAQ modellen analyseras mot observerade data under en fyra dagars period i maj, 2006. Studieområdet Lower Fraser Valley är en bördig dalgång som är omgiven av bergskedjor i sydvästra British Columbia, Kanada. Dalen sträcker sig från Stilla havskusten och österut mot Klippiga bergen. I denna dalgång bor mer än 2 miljoner människor och det är västra Kanadas snabbast växande region. Lower Fraser Valley rymmer en storstad, Vancouver, flera förorter, många industrier och även stora jordbruksområden. Den fyra dagars period i maj som analyseras karaktäriseras av ett högtrycksbetonat synoptiskt väderläge med lokala variationer, vilka tillsammans är gynnsamma för att uppmäta höga koncentrationer av luftföroreningar som ozon och kvävedioxid. Den skapade WRF/CMAQ modellen prognostiserar godtagbar magnitud hos kvävedioxid men den dagliga variationen återskapas inte av modellen. Modellen prognostiserar den dagliga variationen av ozonkoncentration på ett tillfredsställande sätt, men storleksmässigt ligger koncentrationerna en faktor 20-30 ppb för högt rakt av under hela studien. Kringliggande faktorer som kan påverka koncentrationen ozon studeras närmare och det framkommer att den meteorologiska prognosmodellen WRF inte genererar fullt tillförlitliga värden för en rättvisande luftkvalitetsprognos. Då WRF modellen vanligtvis är en bra prognosmodell kan den korta initialiseringstiden för modellen vara en trolig orsak till dess otillräckliga prestation.

The action of sea storms is one of the most complex littoral processes with deep management implications. Along the Catalan shoreline which is about 700 km long, 190 km are subject to erosion and/or flooding. Around one million people live in areas potentially affected. Sea Level Rise could exacerbate this problem in the near future. Reactive interventions have been the norm in coastal engineering and management. This dissertation proposes a pre-storm strategy that foster cost-effective eco-compatible measures, termed Quick Defence Measures (QDM). Pre-storm intervention requires to forecast the future post-storm state. Hence, the main objective of this thesis is to assess present coastal risk through a Coastal Early Warning System (CEWS), termed LIM-COPAS, that forecasts the more relevant episodic coastal hazards at the area. LIM-COPAS consists of four modules: (i) meteorological model; (ii) wave generation/propagation code; (iii) coupled morpho-hydrodynamic model and (iv) risk module via non-stationary multivariate probabilistic models. The performance of this suite of models has been tested with (i) a set of hindcast events and (ii) synthetic storm conditions. The hindcasted events have been: December 2008 (D-08); October-2015 (O-15); November 2015 (N-15); January 2016 (J-16); February 2016 (F-16); December 2016 (D-16) and January 2017 (J-17). In D-08, errors in nearshore spectral wave parameters have been about twice than those in the offshore area. The error was around 20% in hydrodynamics and 50% in morphodynamics. The post-storm response has been acceptably reproduced, with a Brier Skill Score near 0.4. LIM-COPAS has shown good accuracy with high return period events (i.e. Tr,waves > 10 yrs, D-16 and J-17), but lower agreement was found for milder storms (i.e. O-15 and F-16). The meteorological module provided wind fields that were systematically overestimated. The integrated Mean Bias (MB) was -1.52 ± 0.78 m/s. Tarragona (Coefficient of Efficiency, COE = 0.27 ± 0.13) and Begur (COE = 0.29 ± 0.17) had metrics above the average value (COE = 0.24 ± 0.14); but lower agreement was found at Mahón (COE = 0.13 ± 0.16) and Dragonera. Wave metrics were more accurate than for the wind fields. The integrated Hs COE was 0.52±0.12 and Tm02 COE was 0.36±0.14. At the central coast, Hs has presented good metrics: low MB (-0.06 ± 0.08 m) and high COE (0.58 ± 0.11). The northern coast metrics were the most stable. The newly developed risk module has been implemented at 79 beaches. Erosion has been estimated as a bounded cost, whereas flooding as a high upside cost. Dissipative beaches tend to exhibit higher costs than reflective beaches under high sea levels. Tr,waves < 10 yrs events joint with storm-surges can lead to significant damage costs. The estimated losses for the N-15 event (2510·10^3 euros) do not differ excessively from J-17 (3200·10^3 euros). Two types of QDM have been numerically tested: (i) sand dunes and (ii) geotextile detached breakwaters. The benefits from maintaining the sand volumes outperform the flooding cost reduction. In general terms, the detached breakwater can be a suitable option for beaches in an intermediate morphodynamic state against low to moderate sea levels and high wave return periods. At dissipative beaches, dunes are the best option, but they require a minimum beach width (around 30 m) that ensures their lifetime. QDM functionality can be enhanced with compatible long-term actions (nourishments, sand bypasses, submerged vegetation, etc.). A healthy beach state is paramount for the QDM effectiveness. A higher sustainable management under present and future climate can be reached with the joint combination of (i) CEWS as a short-term forecasting tool; (ii) QDM that mitigate storm impacts and (iii) long-term interventions that improves the beach health.
La acción de los temporales de mar es uno de los procesos litorales más complejos, con profundas implicaciones en la gestión del litoral. A lo largo de la línea de costa catalana, 190 km están sometidos a erosión y/o inundación. Cerca de un millón de personas viven en áreas potencialmente afectadas. La tradición en ingeniería y gestión costera han sido intervenciones reactivas. Esta tesis propone una estrategia pre-tormenta que fomente una serie de medidas eco-compatibles, denominadas Medidas de Acción Rápida (MAR). Las intervenciones pre-tormenta requieren predecir el estado post-temporal de la costa. Por tanto, el principal objetivo de esta tesis es evaluar el riesgo costero episódico mediante un Sistema de Alarma Temprana Costero (CEWS), denominado LIM-COPAS, que predice las peligrosidades costeras más relevantes en dicha área. LIM-COPAS consiste de cuatro módulos: (i) modelo meteorológico; (ii) código de generación/propagación del oleaje; (iii) modelo acoplado morfo-hidrodinámico y (iv) un módulo de riesgo vía modelos probabilísticos multivariantes y no-estacionarios. El comportamiento de estos módulos ha sido analizado mediante (i) una serie de eventos pasados y (ii) temporales sintéticos. Los eventos pasados han sido: Diciembre 2008 (D-08); Octubre 2015 (O-15); Noviembre 2015 (N-15); Enero 2016 (J-16); Febrero 2016 (F-16); Diciembre 2016 (D-16) y Enero 2017 (J-17). En D-08, los errores en los parámetros espectrales de oleaje costero han sido casi el doble que en mar abierto. El error ha sido del 20% en la hidrodinámica y del 50% en la morfodinámica. La respuesta post-temporal ha sido reproducida aceptablemente, con Brier Skill Score cercanos a 0.4. LIM-COPAS ha demostrado buena precisión con tormentas de alto período de retorno (i.e. Tr,waves _ 10 yrs, D-16 y J-17), pero menor concordancia fue encontrada para las tormentas moderadas (i.e. O-15 y F-16). El módulo meteorológico estimó campos de viento que fueron sistemáticamente sobreestimados. El Sesgo Medio (MB) integrado fue de −1,52 ± 0,78 m/s. Tarragona (Coeficiente de Eficiencia, COE = 0,27±0,13) y Begur (COE = 0,29±0,17) tuvieron métricas por encima de la media (COE = 0,24±0,14); no obstante, peor ajuste se encontró en Mahón (COE = 0,13 ± 0,16) y Dragonera. Las métricas de oleaje fueron más precisas que las del viento. Hs COE integrada fue 0,52±0,12 y Tm02 COE fue 0,36±0,14. En la costa central, Hs presentó buenas métricas: bajo MB (−0,06 ± 0,08 m) y alto COE (0,58 ± 0,11). Las métricas en la costa norte fueron las más estables. El módulo de riesgo ha sido implementado en 79 playas. La erosión se ha estimado como un coste acotado, mientras que la inundación como un coste con alta cota superior. Las playas disipativas tienden a exhibir mayores costes que las playas reflejantes bajo altos niveles del mar. Episodios con Tr,waves _ 10yrs, concomitantes a mareas meteorológicas pueden conllevar costes significantes. Las pérdidas estimadas para N-15 (2510 · 103euros) no difieren en exceso de J-17 (3200 · 103 euros). Dos tipos de MAR han sido testeadas numéricamente: (i) dunas y (ii) diques exentos constituídos por geotextiles llenos de arena. Los beneficios de mantener estables los volúmenes de arena superan la reducción de los costes por inundación. En términos generales, los diques exentos pueden ser una opción adecuada para playas de estado morfodinámico intermedio frente a oleaje de alto período de retorno y niveles del mar bajos a moderados. En playas disipativas, las dunas son la mejor opción, pero requieren un ancho mínimo de playa (cerca de 30 m) que garantice su vida útil. La funcionalidad de las MAR puede mejorarse mediante acciones compatibles a largo-plazo (alimentaciones, bypass de arena, vegetación sumergida, etc.). Un estado de playa saludable es esencial para la efectividad de las MAR. Una gestión más sostenible bajo clima presente y futuro puede ser alcanzada mediante (i) CEWS como herramienta de predicción a corto plazo; (ii) MAR que mitiguen los impactos de los temporales y (iii) intervenciones a largo-plazo que mejoren la salud de la costa.

Soil erosion is a serious threat to agricultural productivity and the sustainable provision of food to a growing world population. Current erosion models employ simplistic treatments of rainfall. This thesis presents a new approach to erosion modelling, using the Weather Research and Forecasting model to simulate rainfall erosivity, an indicator of the erosive capacity of rain. Rainfall erosivity is modelled in the Caucasus region, an area vulnerable to erosion and climate change pressures. Low intensity rainfall (below 2 mmhr^{-1}) is found to contribute significantly to erosivity (23%), contrary to common assumptions. An exponential dependence of the fraction of erosivity from light rain on the proportion of light rain is found. Erosion models focus on storms, but results suggest that storm-based calculations may exclude up to 30% of erosivity. In the Universal Soil Loss Equation, this does not lead to errors in long term soil loss but could cause an underestimation of event erosion. Rainfall kinetic energy flux is an important variable in erosion prediction and is routinely parameterised from intensity. Here this is dynamically simulated from basic physics in a cloud resolving model, using four microphysics schemes. Results are within the range of observations and capture the observed variability in kinetic energy for a given intensity, where current methods fail. Large raindrops are shown to contribute disproportionately to total kinetic energy, and also to surface precipitation, compared with their number. No connection has hitherto been drawn between aerosols and soil erosion. The effect of aerosols on rainfall erosivity is investigated in a cloud resolving model. Aerosols can either enhance or suppress precipitation. In both these cases the response of erosivity to a rise in aerosols is in the same direction as, but amplified beyond, the change in total rain. It is also shown that aerosols can influence erosivity by changing raindrop sizes. These results suggest that anthropogenic aerosol emissions affect erosivity and thus may have important consequences for agricultural productivity.

The radiative transfer cannot be explicitly resolved in the atmospheric models for two reasons: i) a full treatment of the radiative transfer equation (RTE) requires a high amount of computational resources and ii) the radiative transfer fields such as the optical thickness are not a direct solution of the Euler equations and hence, they must be parameterized as a function of the meteorological fields. Consequently, the physical processes related with radiation are simplified and approximated in physical schemes. In the particular case of the solar radiation, the use of these parameterizations were reduced for many years to represent the day/night cycle inside the model. Therefore, the accuracy of the solar schemes was left in the background and the computational resources were prioritized. With the growth of the solar energy industry during the last decade, a paradigm shift has occurred. Now, the solar irradiance (i.e. global horizontal GHI, direct horizontal DHI and diffuse DIF) becomes an important product for resource assessment as well as for forecasting applications. The main objective of this thesis is the identification and quantification of the sources of error that have a direct or an indirect contribution to the accuracy of the solar schemes, particularly, in those available in the Weather Research and Forecasting (WRF-ARW) model, widely used in the sector. First, the thesis presents a review of the set of physical approximations considered in six solar parameterizations available in the WRF-ARW model: Dudhia, Goddard, New Goddard, Rapid Radiative Transfer Model for General Circulation Models (RRTMG), Climate Atmospheric Model (CAM) and Fu-Liou-Gu (FLG). The sources of error are limitations in the representation of the radiative transfer as a conse- quence of the set of approximations assumed by one scheme. In this thesis three sources of error are analyzed: i) errors due to the vertical discretization of the atmosphere in a set of layers that are assumed to be homogeneous (truncation error), ii) errors due to the misrepresentation of the layer between the top of the model (TOM) and the top of the atmosphere (TOA), called TOM error and iii) errors due to the physical simplifications and parameterizations in the RTE, named physical error. In order to avoid the uncertainty introduced by the other components of the model, the source code of each one of the six solar schemes has been separated of the model and adapted for working with 1-dimensional vertical profiles. The studies of the truncation and TOM errors are performed by using ideal vertical profiles under four scenarios: a dry atmosphere, a wet cloudless sky, low water cloud and a high ice cloud. The results for the ETOM show that for the typical range of TOM values in mesoscale appli- cations (i.e. 10 hPa), the error with respect to a full atmospheric column is less than 0.5% and hence, the TOM error can be neglected. The analysis of the Etrun reveals that the sensitivity of the solar schemes on the vertical config- uration (i.e. number of vertical levels and their distribution) is directly related with the method used for the vertical integration of the multiscattering processes. For the typical mesoscale config- urations, the Etrun under clear-sky conditions is determined around 1.1%, 0.9% and 4.9% for the GHI, DHI and DIF, respectively. In both cloudy scenarios, the Etrun increases significantly, being more important for the high clouds. The Ephys is analyzed under clear-sky conditions using real soundings from the Integrated Global Radiosonde Archive data-set and comparing the irradiance outcomes with the Baseline Solar Radiation Network measurements. With the exception of Dudhia, the behavior for all the parameterizations is the same. A large overestimation of the DHI with a large underestimation of the DIF that leads to a near-zero bias for the GHI. Polar sites show the lowest errors with a mean MAE of 2.1%, 5.2% and 3.7% for GHI, DHI and DIF, respectively. Midlatitude sites show the worst results with a mean MAE of 3.4% in GHI, 11.6% in DHI and 7.8% in the DIF.
L’objectiu principal d’aquesta tesi ´es la identificaci´o i quantificaci´o de les fonts d’error que tenen una contribuci´o directa o indirecta en la precisi´o dels esquemes solars, particularment en aquells disponibles en el model Weather Research and Forecasting (WRF-ARW), `ampliament emprat en el sector de l’energia solar. Les fonts d’error s´on limitacions en la representaci´o del transport radiatiu com a consequ¨`encia del conjunt d’aproximacions assumides per cada esquema. En aquesta tesi hi ha tres fonts d’error que s´on analitzades: i) l’error degut a la discretitzaci´o vertical de l’atmosfera en un conjunt d’estrats que s’assumeixen homogenis (error de truncament, Etrun), ii) l’error com a resultat d’una repre- sentaci´o insuficient de l’estrat entre el cim del model (TOM) i el cim de l’atmosfera (TOA), anomenat error de TOM Etom, i iii) l’error degut a les simplificacions i a les parametritzacions f´ısiques de l’RTE, definit com a error físic, Ephys. Per tal d’evitar la incertesa introdu¨ıda pels altres components del model, el codi font de cadas- cun dels sis esquemes solars ha estat separat del model i adaptat per treballar amb perfils verticals 1-dimensionals. Mitjan¸cant aquest m`etode, les habilitats dels esquemes solars poden ´esser anal- itzades sota condicions d’entrada id`entiques. D’una banda l’error de TOM i el de truncament s’analitzen a partir de perfils ideals. De l’altra, l’error f´ısic s’evalua prenent dades de radiosondatge com a perfil vertical i comparant les sortides dels esquemes radiatius amb mesures en superf´ıcie. Els resultats d’aquesta tesi mostren que l’Etom esdev´e negligible per la majoria d’aplicacions de mesoscala. Per configuracions t´ıpiques del model, l’Etrun en condicions de cel ser`e es troba al voltant de l’1.1%, el 0.9% i el 4.9% per la GHI, DHI i DIF, respectivament. En el cas amb nu´vols augmenta de forma significativa. L’estudi de l’Ephys mostra una relaci´o significativa amb el contingut de vapor d’aigua i els aerosols.

Este estudo tem como objetivo a verificação das previsões diárias, das temperaturas máxima e mínima e precipitação acumulada, realizadas pelo modelo operacional de previsão numérica do tempo WRF (Weather Research Forecasting) para o estado de São Paulo. As condições iniciais e de fronteira fornecidas pela análise e previsão das 00UTC do modelo Global Forecast System (GFS), são usados no processamento do WRF, para previsões de 72 horas, em duas grades aninhadas (espaçamentos horizontais de grade de 50 km, D1, e 16,6 km, D2). O período avaliado foi de abril de 2010 a março de 2011. As comparações diárias das temperaturas máxima e mínima foram realizadas entre os valores preditos e observados nas estações de superfície de Registro, São Paulo, Paranapanema, Campinas, Presidente Prudente e Votuporanga (dados da CIIAGRO); através do erro médio (EM) e raiz do erro médio quadrático (REQM), para os prognósticos das 36, 60 e 72 horas. A precipitação acumulada diária é avaliada com relação ao produto MERGE, pela aplicação da ferramenta MODE, na previsão das 36 horas, para um limiar de 0,3 mm, no domínio espacial abrangendo o Estado de São Paulo e vizinhanças. Primeiramente, fez-se uma análise, comparando os pares de grade dos campos previsto e observado, utilizando os índices estatísticos de verificação tradicional de probabilidade de acerto (PA); índice crítico de sucesso (ICS); viés (VIÉS); probabilidade de detecção (PD) e razão de falso alarme (RFA). Posteriormente, foram analisados os campos de precipitação com relação à razão de área (RA); distância dos centroides (DC); razões de percentil 50 (RP50) e 90 (RP90). Os resultados evidenciaram que as saídas numéricas do modelo WRF com D2 tiveram desempenho melhor comparado à grade de menor resolução (maior espaçamento de grade horizontal, D1), tanto no prognóstico diário das temperaturas (máxima e mínima) quanto da precipitação acumulada. A temperatura apresentou um padrão de amortecimento, com temperaturas diárias máxima subestimada e mínima superestimada. Com relação à precipitação, as saídas numéricas do modelo GFS e WRF com D2 mostraram desempenho semelhante, com o D2 apresentando índices ligeiramente melhores, enquanto que as saídas numéricas do modelo WRF com D1 exibiram pior desempenho. Verificou-se um padrão de superestimativa, tanto em termos de abrangência espacial quanto em intensidade, para o modelo GFS e WRF em ambos os domínios simulados, ao longo de todo o período analisado. O percentil 50 é, geralmente, maior que o observado; entretanto, o percentil 90 é mais próximo ao observado. Os resultados também indicam que o viés dos modelos varia ao longo do ano analisado. Os melhores índices tanto com relação à precipitação quanto à temperatura foram obtidos para a estação de verão, com o modelo WRF com D2 apresentando melhores prognósticos. Entretanto, os modelos apresentam os maiores erros no inverno e no outono. Estes erros foram decorrentes de subestimativas das temperaturas máximas e superestimativas de área e intensidade de precipitação.
Forecasts of daily maximum and minimum temperatures and rainfall performed by the operational numerical weather prediction WRF (Weather Research Forecasting) model in the São Paulo are evaluated. Initial and boundary conditions provided by the 00UTC Global Forecast System (GFS) Model and WRF run for 72 hours, with two nested grids (with horizontal grid spacing of 50 km, D1, and 16.6 km, D2). The study was made for April 2010 to March 2011 period. Daily maximum and minimum temperatures comparisons were made, between predicted and observed data of the surface weather stations of Registro, São Paulo, Paranapanema, Campinas, Presidente Prudente and Votuporanga (CIIAGRO Data), through the mean error (ME) and root mean square error(RMSE), for the 36, 60 and 72 hours forecasts. The daily accumulated rainfall is evaluated using MODE with respect to the MERGE product, for the 36 hours forecast, with threshold of 0.3 mm over the spatial domain covering the State of São Paulo and neighborhoods. First, an analysis was made comparing grid pairs of predicted and observed fields, through the traditional statistical verification indexes: accuracy (PA), critical success index (ICS), bias (VIES), probability of detection (PD) and false alarm ratio (RFA). Subsequently, we analyzed the precipitation field with respect to area ratio (AR), distance from the centroids (DC), ratio of the 50th percentile (RP50) and ratio of the 90th percentile (RP90). The WRF, with D2 nested grid, had better performance compared to the grid of lower space resolution (higher horizontal grid spacing, D1) for both, daily temperatures (maximum and minimum) and the accumulated rainfall forecasts. The temperature forecast presented a damped pattern, with underestimated maximum and overestimated minimum values. Rainfall was overall overestimated spatially and in intensity for the three models throughout the analized period. The forecasted 50th percentile is generally higher than that observed, however, the 90th percentile is closer to observations. The results also indicate that the bias of the models varies annually. The best performances for both rainfall and temperature were obtained for the summer season, with the D2 showing slightly better results. However, the models had the biggest errors during the winter and autumn seasons. These errors were due to underestimation of maximum temperatures and overestimation in area and intensity of precipitation.

The global climate is changing due to the accumulation of greenhouse gases (GHGs) in the atmosphere, primarily due to anthropogenic activity. The dominant GHG is CO₂ which originates from combustion of fossil fuels, land use change and management. The terrestrial biosphere is a key driver of climate and biogeochemical cycles at regional and global scales. Furthermore, the response of the Earth system to future drivers of climate change will depend on feedbacks between biogeochemistry and climate. Therefore, understanding these processes requires a mechanistic approach in any model simulation framework. However ecosystem processes are complex and nonlinear and consequently models need to be validated against observations at multiple spatial scales. In this thesis the weather research and forecasting model (WRF) has been coupled to the mechanistic terrestrial ecosystem model soil-plant-atmosphere (SPA), creating WRF-SPA. The thesis is split into three main chapters: i. WRF-SPA model development and validation at multiple spatial scales, scaling from surface fluxes of CO₂ and energy to aircraft profiles and tall tower observations of atmospheric CO₂ concentrations. ii. Investigation of ecosystem contributions to observations of atmospheric CO₂ concentrations made at tall tower Angus, Dundee, Scotland using ecosystem specific CO₂ tracers at seasonal and interannual time scales. iii. An assessment of detectability of a policy relevant national scale afforestation by observations made at a tall tower. Detectability of changes in atmospheric CO₂ concentrations was assessed through a comparison of a control simulation, using current day forest extent, and an experimentally afforested simulation using WRF-SPA. WRF-SPA performs well at both site and regional scales, accurately simulating aircraft profiles of CO₂ concentration magnitudes (error <+- 4 ppm), indicating appropriate source sink distribution and realistic atmospheric transport. Hourly observations made at tall tower Angus were also well simulated by WRF-SPA (R² = 0.67, RMSE = 3.5 ppm, bias = 0.58 ppm). Analysis of CO₂ tracers at tall tower Angus show an increase in the seasonal error between WRF-SPA simulated atmospheric CO₂ and observations, which coincides with simulated cropland harvest. WRF-SPA does not simulate uncultivated land associated with agriculture, which in Scotland represents 36 % of agricultural holdings. Therefore, uncultivated land components may provide an explanation for the increase in model-data error. Interannual variation in weather is indicated to have a greater impact on ecosystem specific contributions to atmospheric CO₂ concentrations at Angus than variation in surface activity. In a model experiment, afforestation of Scotland was simulated to test the impact on Scotland’s carbon balance. The changes were shown to be potentially detectable by observations made at tall tower Angus. Afforestation results in a reduction in atmospheric CO₂ concentrations by up to 0.6 ppm at seasonal time scales at tall tower Angus. Detection of changes in forest surface net CO₂ uptake flux due to afforestation was improved through the use of a network of tall towers (R² = 0.83) compared to tall tower Angus alone (R² = 0.75).

The launch of large stratospheric balloons is highly dependant on the meteorological conditions at ground level, including wind speed. The balloon launch base Esrange Space Center in northern Sweden currently uses forecasts delivered through the Swedish Meteorological and Hydrological Institute to predict opportunities for balloon launches. However the staff at Esrange Space Center experience that the current forecasts are not accurate enough. For that reason the Weather Research and Forecasting model is used to improve the forecast. The model performs a Large Eddy Simulation over the area closest to Esrange Space Center to predict wind speed and turbulence. During twelve hypothetical launch days the improved forecast have an overall accuracy of 93% compared to the old forecast accuracy of 69%. With some improvements and the right computational power the system is thought to be operationally viable.

Eastern Kentucky is a 35-county region that is a part of the Cumberland Plateau of the Appalachian Mountains. With mountaintop removal and associated land cover change (LCC) (primarily deforestation), it is hypothesized that there would be changes in various atmospheric boundary layer parameters and precipitation. In this research, we have conducted sensitivity experiments of atmospheric response of a significant flash flood-producing rainfall event by modifying land cover and topography. These reflect recent LCC, including mountaintop removal (MTR). We have used the Weather Research and Forecasting (WRF) model for this purpose. The study found changes in amount, location, and timing of precipitation. LCC also modified various surface fluxes, moist static energy, planetary boundary layer height, and local-scale circulation wind circulation. The key findings were the modification in fluxes and precipitation totals. With respect to sensible heat flux (H), there was an increase to bare soil (post-MTR) in comparison to pre-MTR conditions (increased elevation with no altered land cover). Allowing for growth of vegetation, the grass simulation resulted in a decrease in H. H increased when permitting the growth of forest land cover (LC) but not to the degree of bare soil. In regards to latent heat flux (LE), there was a dramatic decrease transitioning from pre-MTR to post-MTR simulations. Then with the subsequent grass and forest simulations, there was an increase in LE comparable to the pre-MTR simulation. Under pre-MTR conditions, the total precipitation was at its highest level overall. Then with the simulated loss of vegetation and elevation, there was a dramatic decrease in precipitation. With the grass LC, the precipitation increased in all areas of interest. Then forest LC was simulated allowing overall slightly higher precipitation than grass.

abstract: This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon. Control cases were also run with the parameterization scheme turned off. The primary emphasis was on offshore wind farms. Some analysis on onshore wind farms was also performed. The effects of these wind farms were studied on the vertical profiles of temperature, wind speed, and moisture as well as on temperature and on wind speed near the surface and at hub height. The effects during the day and at night were compared. Seasonal variations were also studied by performing simulations in January and in July. It was seen that wind farms produce a reduction in wind speed at hub height and that the downward propagation of this reduction in wind speed lessens as the atmosphere becomes more stable. In all the cases studied, the wind farms produced a warming effect near the surface, with greater atmospheric stability leading to higher near-surface temperatures. It was also observed that wind farms caused a drying effect below the hub height and a moistening effect above it, because they had facilitated vertical transport of moisture in the air from the lower layers of the atmosphere to the layers of the atmosphere above the wind farm.
Dissertation/Thesis
Masters Thesis Mechanical Engineering 2016

In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land. The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.

In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land. The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.

Two post processing methods for quantifying the shadow effect of the offshore wind farm Princes Amalia (PA) onto Egmond aan Zee (OWEZ) wind farm are analyzed and benchmarked. The first method is the author’s proposed shadow effect determination method (SEDM), which quantifies an offshore wind farm’s shadow effect based on mesoscale WRF (Weather Research Forecast) idealized modeling and the observed frequency of the analyzed site’s wind conditions. The Fitch turbine parametrization scheme and Mellor-Yamada-Nakanishi-Niino (MYNN) surface layer and planetary boundary layer (PBL) schemes were used to simulate the wind farm’s interactions, based on site conditions. The proposed physical downscaling method (SEDM) uses filtered simulated atmospheric stability and wind speed conditions, in order to calculate the percent wind speed deficit downstream of PA, with regard, first, to observed wind speed frequency and, secondly, to wind speed and corresponding atmospheric stability regimes. Then a statistical downscaling method, based on the established Analog Ensemble (AnEn) technique, developed by Luca Delle Monache et al. (2011) was employed to verify the results from the first method. This method runs a post processing algorithm using the weighted average of the observations that were verified when the 15 best analogs were valid. Observed wind speed data at 10 m and 50 m height was used as Numerical Weather Prediction (NWP) input data and fit to observed time series data. From this, wind speeds at 116 m were extrapolated, in order to estimate the reconstructed atmospheric stability. The two methods were benchmarked and shadow effects were quantified in the range of 7.53% - 22.92% for the SEDM and within an 80% confidence interval of 0.23% -1.83% for the statistical downscaling method. Given the physical method’s exceedance of this confidence interval, WRF idealized modeling proves itself as a consistent means of quantifying an offshore wind farm’s wake, as demonstrated by comparable studies, however inaccurate when benchmarked to statistical modelling methods that use observed wind speed data to recreate atmospheric conditions.
Wake Research Group

En esta tesis se aborda la puesta operativa del modelo numérico acoplado de predicción meteorológica Global Forecast System - Weather Research and Forecasting (GFS-WRF), con el objetivo de satisfacer la necesidad de contar con datos de predicción meteorológica, para ser utilizados en sistemas de alerta temprana a emergencias desarrollados dentro de la CONAE, y para potenciales usuarios externos. La automatización completa de los procesos involucrados culmina en la publicación diaria de los datos generados en un servidor web. Se ofrece la opción de descarga en distintos formatos comúnmente utilizados en sistemas, modelos o algoritmos. Esta última modalidad no se brinda actualmente desde ninguna institución pública. Finalmente cabe destacar que las herramientas computacionales utilizadas en esta tesis son de acceso libre y gratuito.

The city of Melbourne in southeast Australia experiences an Urban Heat Island (UHI) effect, which is exacerbated during heatwaves, and the latter are becoming more frequent, intense and longer in southeast Australia. In addition, Melbourne is the fastest growing city in Australia. Therefore, it is urgent to understand the dynamics of UHI and impacts of future urban expansion on the UHI during heatwaves. Based on these issues, there is a crucial need to investigate the effectiveness of potential mitigation strategies to minimize UHI effects during heatwaves. The overarching aim of the thesis is to investigate the impacts of future urban expansion on the UHI during heatwave events in Melbourne, and examine the effectiveness of different Green Infrastructure (GI) scenarios such as green/cool roofs, mixed forest (MF), mixed forest and grassland (MFAG), and mixed shrublands and grasslands (MSAG) in mitigating UHI effects. The Weather Research and Forecasting (WRF) model coupled with the Single Layer Urban canopy Model (SLUCM) was used in simulating the UHI and heatwaves. Since the WRF model is known to be sensitivity to the choice of physical parameterisation options, an initial sensitivity analysis of the model was conducted and the best-possible WRF configuration to simulate the UHI during heatwaves in Melbourne was determined, among a 27-member physics ensemble. This configuration was used throughout the rest of the thesis. Urban expansion increased near surface UHI by 0.75 to 2.80 °C during the night but no substantial impacts during the day. Urban surfaces absorbed more solar heat during the day as compared to vegetated surfaces, and the absorbed heat was released slowly from evening to early morning. The storage heat in urban surfaces was the key driver in increasing UHI during the night. Urban expansion did not substantially affect human health (HTC) comfort in existing and expanded urban areas. Green roofs showed good performance in reducing roof surface UHI (1 to 3.8 °C) and near surface UHI (0.3 to 1.1 °C) during the day but not during the night, while cool roofs showed higher reductions at the roof surface UHI (2.2 to 5.2 °C) and near surface UHI (0.5 to 1.6 °C) during the day. Green roofs increased evapotranspiration and provided shading, and consequently, increased Latent Heat (LH) and substantially decreased storage heat and sensible heat, and as a result, reduced the UHI. Cool roofs reflected a major portion of incoming solar radiation due to higher albedo, and reduced the sensible heat flux and storage heat, and these were the key drivers in reducing UHI during the day. In addition, both green and cool roofs showed good potential in improving HTC from extreme to very strong during the day. Other GI scenarios such as MF, MFAG and MSAG were effective in reducing UHI effects and improving HTC during the night but no substantial reductions were occurred during the day. By increasing GI fractions from 20 to 50 %, the UHI was reduced by 0.6 to 3.4 °C for MF, 0.4 to 3.0 °C for MSAG and 0.6 to 3.7 °C for MFAG. The night time cooling was driven by reductions in storage heat as 20 to 50 % urban areas were replaced by GI, which would have led to even less radiation reaching the ground surface during the day due to their higher LAI and shade factor, and leading to lower storage heat. As the green and cool roofs showed potential in reducing UHI effects during the day while urban vegetated patches showed effectiveness during the night, therefore, a combination of green/cool roofs and urban vegetated patches could be an optimal mitigation strategy in reducing UHI effects and improving HTC during both day and night.

Thesis (M.S.)--Florida State University, 2004.
Advisor: Dr. Paul Ruscher, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Jan. 12, 2005). Includes bibliographical references.

碩士
國立臺灣大學
生物環境系統工程學研究所
100
Recently flood disasters increase due to the frequent extreme rainfall conditions. The violent typhoon not only bring heavy rainfall but also cause water level rising which result in the risk of flooding. Flood prevention agencies often rely on a flood warning system on storm surge forecasting for decision making in the emergency response. Therefore, it is important to provide accurate weather data, such as air pressures and wind velocities, for the simulation of storm surge modeling. The Weather Research and Forecasting Model (WRF) and Advanced Circulation Model (ADCIRC) are simulated under the similar domain in the present study. Air pressures and wind velocities of typhoon were generated by WRF and then provided as boundary conditions of meteorological data for ADCIRC. The ADCIRC, storm surge calculation, was calibrated by typhoon FANAPI 2012. Simulated water levels are good agreement with observations in astronomical tides and surge tides. The valid model was appropriately employed to storm surge forecasting for the typhoon MORAKOT. The storm surge boundary conditions were individually forecasted by WRF Four series meteorological date of typhoon MORAKOT. In order to improve the accuracy of forecasts, the storm surge levels are averaged by the four series of storm surge levels when forecasting periods were overlapping. The results revealed that the predictions were identical with observed date.

The reliable prediction of the South Asian monsoon rainfall and its variability is crucial for various hydrological applications and early warning systems. This study analyzes Global Fore- cast System (GFS) model generated high-resolution precipitation forecast over the South-Asian region during June-September 2012. This work delineates the error characteristics of the model over land and ocean; how forecast errors vary at different hours of the day; the skill of the model in active and break cycle and clustering of the precipitation events. This study shows that forecast errors are much larger over the land than over ocean. More- over, the rate of increase of errors with lead time is rapid over the oceans where observed precipitation shows large day-to-variability. This is possibly due to the one-way air-sea interac- tion in the atmosphere-only model used for forecasting. Furthermore, over ocean, for a smaller range of RMS error there was not much variation in RMS error growth with lead time but for a higher range of RMS error, there was a rapid growth. Over land for a lower and higher value of RMS error, there was no variation in error growth with lead time. It has been also shown that the model had poor forecasting skills in predicting very heavy (>30 mmday􀀀1) precipitation over both land and ocean. The error decomposition analysis shows that error by pattern variation was contributing more than 90% of the total mean square error as compared to an error by mean di erence. This can be probably due to an error in daily and diurnal scale variation. On the daily scale, the transition of the occurrence of active and break phases was well captured by the model. However, the model had considerable difficulties in forecasting long intense break and heavy rainfall events. Diurnal cycle of precipitation in the model shows the phase error of about 6 hours over land. On the other hand, over oceans, there was no phase error in precipitation forecast. Moreover, there was a systematic bias over the ocean. This shift and bias in model forecasted phase result in large error over both land and ocean. Thus, efforts should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model over the South Asian region.