NOWCASTING OF PRECIPITATION Isztar Zawadzki* McGill University, Montreal, Canada

Size: px
Start display at page:

Download "NOWCASTING OF PRECIPITATION Isztar Zawadzki* McGill University, Montreal, Canada"

Transcription

1 NOWCASTING OF PRECIPITATION Isztar Zawadzki* McGill University, Montreal, Canada 1. INTRODUCTION Short-term methods of precipitation nowcasting range from the simple use of regional numerical forecasts to complex radar data assimilation schemes. Presently, the skill of numerical models is rather poor for precipitation. Figure 1 shows some typical scores for precipitation detection for two limited area models. The skill is low, thus, nowcasting presently requires other, mostly heuristic, techniques Figure 1.- Probability of detection (POD), false alarm rate (FAR), critical success index (CSI) and conditional mean absolute error (CMAE) for GEM at 15km resolution and WRF at 28km resolution for the first 24 and 60 hours, respectively for rain rates above 0.1 mm/h. Radar composites are used as truth. *Isztar Zawadzki, McGill University, 805 Sherbrooke St. W, Montreal, Canada H3A 2K6. Telephone (514) , We will give here a brief description of the method most commonly used operationally, that is, the method based on persistence of the precipitation pattern in the moving coordinates (Lagrangian Persistence, or LP for short). All the skill values and diagrams presented here were obtained for the Central- Eastern United States (that is excluding the mountainous regions) and are certainly not universal results 2. NOWCASTING BY LP In this method the immediate past of the precipitation patterns is used to determine the field of motion of the pattern. Then this field of motion is used to forward advect the present pattern. Longer lead times of the nowcast are given by further advection. The quality of this method depends on many factors but an important one is the availability of radar composites. Single radar LP nowcast have useful skill for up to one hour only. The limiting factor is the impossibility of seeing far enough to predict what will be arriving. In addition, the field of motion is poorly evaluated due to range effects of scanning radar. With continental scale composites the useful lead times extend up to six hours. Obviously, the physical limit to the predictability by LP is growth and decay (including generation of new regions of

2 precipitation). Let us point out that LP includes some growth and decay. For example, if there is some persistent dissipation at the rear of a system this will result in a motion pattern that is confluent. If the dissipation at the rear continues into the future the advection will capture the narrowing of the pattern. predictable, and it was predicted. The decrease in intensity within this area, however, was not predictable by LP. The example above illustrates that the method of determining the velocity field and pattern advection are critical to the method s skill. Another physical limitation of LP is the evolution of the motion field. Figure 3 shows that around 20% of loss of skill (defined here as the time to decorrelation to 1/e) is due to time evolution of motion field. Figure 3: Decorrelation between nowcasted and observed reflectivity patterns using stationary motion filed and a posteriori observed motion field during the 60 h of nowcast. Figure 2.- Precipitation patterns 2:30 hours apart. The differential motion along the trajectories at the initial time leads to a prediction of the observed narrowing of the pattern. An example is given in Fig. 2, where at the initial time it can be seen within the circled area that the motion vectors at the rear are longer that at the front. At the later time the pattern has narrowed. This was Predictability of meteorological fields is scale dependent and the fundamental limit to predictability due to non-linearity of the processes governing precipitation is a difficult issue beyond the scope of this discussion. Here, the term predictability is used denote the limit of skill of the method of forecast used. In relation to LP we note that small cells evolve rapidly and therefore are less predictable that large scale systems. Haar wavelet scale decomposition was used to compare nowcasts of radar precipitation patterns and radar observed patterns at the nowcast time for

3 different scales. An analysis of four days of data is summarized in Figure 4. that the ensemble represents the probabilities as determined above. In addition, each member of the ensemble is a possible realization of the precipitation field that respects the statistical properties (such as mean, variance, decorrelation time and distance) of the observations made in the immediate past. Figure 4.- Life-time (as defined by the time to decorrelation to 1/e) for four days of data as a function of filtered out scales. Since the loss of predictability is faster the smaller the scale of the precipitation pattern, a scale filtering, increasing with leadtime, is needed to avoid attempts at predicting the unpredictable. An evaluation of the skill in precipitation detection of a particular algorithm of LP nowcast (MAPLE, McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation), the filtered nowcast (O- MAPLE, Optimized MAPLE * ) as well as numerical model outputs is shown in Fig. 5. The small scales can be only predicted by a probabilistic method. One approach is nowcasting of fields of probability by LP. The fields of probability are determined in the immediate past and advected by the motion field. Another, more complete, possibility is the generation of ensembles of nowcasts so * The algorithm is described in three papers: Germann and Zawadzki (2002), Germann and Zawadzki (2004), Turner et al (2004). Figure 5.- skill scores of nowcasting by LP (unfiltered and filtered) compared to numerical model outputs. In relation to this there is another issue that requires a statistical approach. Nowcasting of precipitation intensity based on radar data relies on the transformation from reflectivity Z to rain rate R. The Z-R relationship has a strong stochastic component that is related to the physical processes responsible for the formation of different raindrop size distributions. These processes are not totally random (in the Gaussian sense). On the contrary, they are quite structured and correlated in space and time. Thus the differences in the fields of Z and

4 R are also structured with spatial and temporal scales of correlation. Figure 6.- A rain rate field obtained from Z to R transformation by a climatological Z-R relationship and four stochastic realizations of the R-filed that have the same mean, variance and correlation structure of the variability in the Z-R relationship around the climatological one. Figure 6 shows four plausible fields of rain rate that correspond to a single reflectivity filed. These four fields are members of an ensemble that incorporates the uncertainty in the Z-R relationship. To produce these realizations we analyze the fluctuations around a mean Z-R relationship as given by disdrometric observations. In particular we determine the correlation between Z and R, the variance of the fluctuations around a mean regression and the time structure function of these fluctuations. A self-afine cascade is then generated that respects the observed stochastic properties and the result is added to the deterministic R-field obtained by the transformation from Z to R using the mean Z-R regression. Each realization of the self-affine cascade produces a member of the ensemble. The average of the ensemble is the deterministic R-field. The procedure is similar to the one used by Bowler et al. (2004) to downscale model outputs in order to generate ensemble nowcasts. In the same manner one can generate an ensemble that contains as well other errors in radar measurements (notably extrapolation

5 to ground) and the uncertainty due to the nonpredictability of the small scales. 3. COMBINING MODEL AND NOWCASTS Figure 7 shows the critical success index of the weighted (by the skill of each member in the immediate past) average of precipitation patterns of ensembles made of LP nowcasts and numerical model outputs. Figure 8.- Same as Fig. 7 but for cases where WRF skill was significantly above the average Figure 7.- Skill scores of precipitation forecasted by a numerical model, of filtered and non-filtered LP nowcasting and their weighted combinations. Although the WRF model performance is rather poor when combined with LP nowcasts it leads to significant improvement in skill. For short lead times, up to three hours, MAPLE is superior. The addition of the filtered nowcast, O-MAPLE, helps to improve the score. All this is case dependent. Fig. 8 shows the detection CSI for cases where model performance was particularly good (WRF model CSI at least 1.4 times the one in Fig. 7). These cases represent 8.8% of the analyzed period. Again MAPLE outperforms model for lead times of up to 3 hours. However, in this limited sample scale filtering was particularly effective at increasing the score. On the other hand, the score of the ensemble including the filtered LP nowcast is not as good as without it. All this points out to the need of carefully adapting the algorithm to each situation. 4. FINAL COMMENTS Nowcasting by LP, introduced over three decades ago, remains still the choice method for operational nowcasting. It has better skill than present days numerical models for up to six hours. However, this statement must be made with caution since radar maps are used for verification and consequently priviledge radar based nowcasts. It should be also pointed out that LP nowcasts are only good in regions where advection of precipitation dominates over generation. In mountainous

6 regions LP has little skill (this also holds for NWP). Further improvements in the skill of LP nowcasts will be difficult to achieve. Attempts at incorporating tendencies have been unsuccessful. The motion field already captures growth and decay that leads to persistent changes in the pattern. It is likely that incorporating uncertainties as well as physical information from other sources (including information from NWP) into a stochastic generation of ensembles is the road to follow. Combination of LP nowcasts with NWP leads to improvement in skill. It is likely that progress in technology, particularly computing capability, will lead to improvements in resolution of numerical models and beter data assimilation. We should expect some improvement in NWP. This will be automatically incorporated into the nowcasts obtained by combination of LP nowcasting and NWP. REFERENCES Bowler, N., C. Pierce and A. Seed, 2004: STEPS: A probabilistic precipitation forecasting scheme which merges extrapolation nowcast with downscaled NWP. Q. J. R. Meteolol. Soc., 999, Germann, U. and I. Zawadzki, 2002: Scale dependence of predictability of precipitation from continental radar images. Part I: Description of methodology. Weather and Forecasting, 130, Germann, U. and I. Zawadzki, 2004: Scale dependence of predictability of precipitation from continental radar images. Part 2: Probability Forcasts. J. of Appl. Meteorology, 43, Turner, B., I. Zawadzki and U. Germann, 2004: Scale dependence of predictability of precipitation from continental radar images. Part 3: Operational implementation. J. of Appl. Meteorology, 43, Acknowledgments Many people contributed to obtain the results shown in this extended abstract, notably: Gyuwon Lee, Urs Germann, Alamelu Kilambi, Alan Seed and Barry Turner. WRF model outputs were provided by Weather Decision Technologies, Inc. Financial support for this work was provided by a grant from the Canadian Foundation for Climate and Atmospheric Sciences (CFAS)

Team Members. Lei Wen, Slavko Vasi, Barry Turner, Olivier Bousquet. Isztar Zawadzki. McGill University

Team Members. Lei Wen, Slavko Vasi, Barry Turner, Olivier Bousquet. Isztar Zawadzki. McGill University Quantitative Precipitation Forecast (QPF) from Weather Prediction Models and Radar Nowcasts, and Atmospheric Hydrological Modelling for Flood Simulation Charles Lin Professor, Department of Atmospheric

More information

Development of a. Solar Generation Forecast System

Development of a. Solar Generation Forecast System ALBANY BARCELONA BANGALORE 16 December 2011 Development of a Multiple Look ahead Time Scale Solar Generation Forecast System John Zack Glenn Van Knowe Marie Schnitzer Jeff Freedman AWS Truepower, LLC Albany,

More information

FLOODALERT: A SIMPLIFIED RADAR-BASED EWS FOR URBAN FLOOD WARNING

FLOODALERT: A SIMPLIFIED RADAR-BASED EWS FOR URBAN FLOOD WARNING 11 th International Conference on Hydroinformatics HIC 2014, New York City, USA FLOODALERT: A SIMPLIFIED RADAR-BASED EWS FOR URBAN FLOOD WARNING XAVIER LLORT (1), RAFAEL SÁNCHEZ-DIEZMA (1), ÁLVARO RODRÍGUEZ

More information

Meteorological Forecasting of DNI, clouds and aerosols

Meteorological Forecasting of DNI, clouds and aerosols Meteorological Forecasting of DNI, clouds and aerosols DNICast 1st End-User Workshop, Madrid, 2014-05-07 Heiner Körnich (SMHI), Jan Remund (Meteotest), Marion Schroedter-Homscheidt (DLR) Overview What

More information

Solar Irradiance Forecasting Using Multi-layer Cloud Tracking and Numerical Weather Prediction

Solar Irradiance Forecasting Using Multi-layer Cloud Tracking and Numerical Weather Prediction Solar Irradiance Forecasting Using Multi-layer Cloud Tracking and Numerical Weather Prediction Jin Xu, Shinjae Yoo, Dantong Yu, Dong Huang, John Heiser, Paul Kalb Solar Energy Abundant, clean, and secure

More information

Proposals of Summer Placement Programme 2015

Proposals of Summer Placement Programme 2015 Proposals of Summer Placement Programme 2015 Division Project Title Job description Subject and year of study required A2 Impact of dual-polarization Doppler radar data on Mathematics or short-term related

More information

RAPIDS Operational Blending of Nowcasting and NWP QPF

RAPIDS Operational Blending of Nowcasting and NWP QPF RAPIDS Operational Blending of Nowcasting and NWP QPF Wai-kin Wong and Edwin ST Lai Hong Kong Observatory The Second International Symposium on Quantitative Precipitation Forecasting and Hydrology 5-8

More information

Nowcasting of significant convection by application of cloud tracking algorithm to satellite and radar images

Nowcasting of significant convection by application of cloud tracking algorithm to satellite and radar images Nowcasting of significant convection by application of cloud tracking algorithm to satellite and radar images Ng Ka Ho, Hong Kong Observatory, Hong Kong Abstract Automated forecast of significant convection

More information

Next generation models at MeteoSwiss: communication challenges

Next generation models at MeteoSwiss: communication challenges Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Next generation models at MeteoSwiss: communication challenges Tanja Weusthoff, MeteoSwiss Material from

More information

Weather Help - NEXRAD Radar Maps. Base Reflectivity

Weather Help - NEXRAD Radar Maps. Base Reflectivity Weather Help - NEXRAD Radar Maps Base Reflectivity Base Reflectivity Severe Thunderstorm/Torna do Watch Areas 16 levels depicted with colors from dark green (very light) to red (extreme) that indicate

More information

Data Integration and long-term planning of the Observing Systems as a cross-cutting process in a NMS

Data Integration and long-term planning of the Observing Systems as a cross-cutting process in a NMS Data Integration and long-term planning of the Observing Systems as a cross-cutting process in a NMS ECAC Zurich, Setpember 15 2020 Ch. Häberli Deputy Head Climate Division/Head Meteorological Data Coordination

More information

Partnership to Improve Solar Power Forecasting

Partnership to Improve Solar Power Forecasting Partnership to Improve Solar Power Forecasting Venue: EUPVSEC, Paris France Presenter: Dr. Manajit Sengupta Date: October 1 st 2013 NREL is a national laboratory of the U.S. Department of Energy, Office

More information

HUNGARIAN METEOROLOGICAL SERVICE, BUDAPEST

HUNGARIAN METEOROLOGICAL SERVICE, BUDAPEST WWW TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA- PROCESSING AND FORECASTING SYSTEM (GDPFS), AND THE ANNUAL NUMERICAL WEATHER PREDICTION (NWP) PROGRESS REPORT FOR THE YEAR 2005 HUNGARIAN METEOROLOGICAL

More information

Hong Kong Observatory Summer Placement Programme 2015

Hong Kong Observatory Summer Placement Programme 2015 Annex I Hong Kong Observatory Summer Placement Programme 2015 Training Programme : An Observatory mentor with relevant expertise will supervise the students. Training Period : 8 weeks, starting from 8

More information

Verifying Extreme Rainfall Alerts for surface water flooding potential. Marion Mittermaier, Nigel Roberts and Clive Pierce

Verifying Extreme Rainfall Alerts for surface water flooding potential. Marion Mittermaier, Nigel Roberts and Clive Pierce Verifying Extreme Rainfall Alerts for surface water flooding potential Marion Mittermaier, Nigel Roberts and Clive Pierce Pluvial (surface water) flooding Why Extreme Rainfall Alerts? Much of the damage

More information

Distributed Computing. Mark Govett Global Systems Division

Distributed Computing. Mark Govett Global Systems Division Distributed Computing Mark Govett Global Systems Division Modeling Activities Prediction & Research Weather forecasts, climate prediction, earth system science Observing Systems Denial experiments Observing

More information

7.10 INCORPORATING HYDROCLIMATIC VARIABILITY IN RESERVOIR MANAGEMENT AT FOLSOM LAKE, CALIFORNIA

7.10 INCORPORATING HYDROCLIMATIC VARIABILITY IN RESERVOIR MANAGEMENT AT FOLSOM LAKE, CALIFORNIA 7.10 INCORPORATING HYDROCLIMATIC VARIABILITY IN RESERVOIR MANAGEMENT AT FOLSOM LAKE, CALIFORNIA Theresa M. Carpenter 1, Konstantine P. Georgakakos 1,2, Nicholas E. Graham 1,2, Aris P. Georgakakos 3,4,

More information

Comprehensive Forecasting System for Variable Renewable Energy

Comprehensive Forecasting System for Variable Renewable Energy Branko Kosović Sue Ellen Haupt, Gerry Wiener, Luca Delle Monache, Yubao Liu, Marcia Politovich, Jenny Sun, John Williams*, Daniel Adriaansen, Stefano Alessandrini, Susan Dettling, and Seth Linden (NCAR,

More information

The Wind Integration National Dataset (WIND) toolkit

The Wind Integration National Dataset (WIND) toolkit The Wind Integration National Dataset (WIND) toolkit EWEA Wind Power Forecasting Workshop, Rotterdam December 3, 2013 Caroline Draxl NREL/PR-5000-60977 NREL is a national laboratory of the U.S. Department

More information

H13-187 INVESTIGATING THE BENEFITS OF INFORMATION MANAGEMENT SYSTEMS FOR HAZARD MANAGEMENT

H13-187 INVESTIGATING THE BENEFITS OF INFORMATION MANAGEMENT SYSTEMS FOR HAZARD MANAGEMENT H13-187 INVESTIGATING THE BENEFITS OF INFORMATION MANAGEMENT SYSTEMS FOR HAZARD MANAGEMENT Ian Griffiths, Martyn Bull, Ian Bush, Luke Carrivick, Richard Jones and Matthew Burns RiskAware Ltd, Bristol,

More information

Forecaster comments to the ORTECH Report

Forecaster comments to the ORTECH Report Forecaster comments to the ORTECH Report The Alberta Forecasting Pilot Project was truly a pioneering and landmark effort in the assessment of wind power production forecast performance in North America.

More information

Flexible Neural Trees Ensemble for Stock Index Modeling

Flexible Neural Trees Ensemble for Stock Index Modeling Flexible Neural Trees Ensemble for Stock Index Modeling Yuehui Chen 1, Ju Yang 1, Bo Yang 1 and Ajith Abraham 2 1 School of Information Science and Engineering Jinan University, Jinan 250022, P.R.China

More information

STUDY ON EFFICIENCY IMPROVEMENT OF TRAIN DISPATCH UNDER SEVERE RAINFALL BY USING RADAR

STUDY ON EFFICIENCY IMPROVEMENT OF TRAIN DISPATCH UNDER SEVERE RAINFALL BY USING RADAR STUDY ON EFFICIENCY IMPROVEMENT OF TRAIN DISPATCH UNDER SEVERE RAINFALL BY USING RADAR TOMOKI OSHIRO (1) & SATORU OISHI (2) (1) Department of Civil Engineering, Graduate School of Engineering, Kobe University,

More information

Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations

Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations S. C. Xie, R. T. Cederwall, and J. J. Yio Lawrence Livermore National Laboratory Livermore, California M. H. Zhang

More information

IBM Big Green Innovations Environmental R&D and Services

IBM Big Green Innovations Environmental R&D and Services IBM Big Green Innovations Environmental R&D and Services Smart Weather Modelling Local Area Precision Forecasting for Weather-Sensitive Business Operations (e.g. Smart Grids) Lloyd A. Treinish Project

More information

Precipitation nowcasting at Finnish Meteorological Institute

Precipitation nowcasting at Finnish Meteorological Institute Precipitation nowcasting at Finnish Meteorological Institute Jarmo Koistinen (1), Erik Gregow (1), Harri Hohti (1), Janne Kauhanen (1), Juha Kilpinen (1), Pekka Rossi (1), Mari Heinonen (2), Daniel Sempere-Torres

More information

ANALYSIS OF THUNDERSTORM CLIMATOLOGY AND CONVECTIVE SYSTEMS, PERIODS WITH LARGE PRECIPITATION IN HUNGARY. Theses of the PhD dissertation

ANALYSIS OF THUNDERSTORM CLIMATOLOGY AND CONVECTIVE SYSTEMS, PERIODS WITH LARGE PRECIPITATION IN HUNGARY. Theses of the PhD dissertation ANALYSIS OF THUNDERSTORM CLIMATOLOGY AND CONVECTIVE SYSTEMS, PERIODS WITH LARGE PRECIPITATION IN HUNGARY Theses of the PhD dissertation ANDRÁS TAMÁS SERES EÖTVÖS LORÁND UNIVERSITY FACULTY OF SCIENCE PhD

More information

NowCastMIX. A fuzzy logic based tool for providing automatic integrated short-term warnings from continuously monitored nowcasting systems

NowCastMIX. A fuzzy logic based tool for providing automatic integrated short-term warnings from continuously monitored nowcasting systems NowCastIX A fuzzy logic based tool for providing automatic integrated short-term warnings from continuously monitored nowcasting systems Paul James, Deutscher Wetterdienst ES eeting, Berlin, 12.09.2011

More information

Convective Weather PDT. Marilyn Wolfson MIT LL and Cindy Mueller NCAR

Convective Weather PDT. Marilyn Wolfson MIT LL and Cindy Mueller NCAR Convective Weather PDT Marilyn Wolfson MIT LL and Cindy Mueller NCAR Outline CWPDT Approach Improving 0-2 hr Forecasts 1-hr TCWF 2-hr RCWF AutoNowcaster Initial Work on 2-6 hr Forecasts 2-hr NCWF Combined

More information

A State Space Model for Wind Forecast Correction

A State Space Model for Wind Forecast Correction A State Space Model for Wind Forecast Correction Valérie Monbe, Pierre Ailliot 2, and Anne Cuzol 1 1 Lab-STICC, Université Européenne de Bretagne, France (e-mail: valerie.monbet@univ-ubs.fr, anne.cuzol@univ-ubs.fr)

More information

118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES

118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES 118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES Donald F. Van Dyke III * Florida State University, Tallahassee, Florida T. N. Krishnamurti Florida State

More information

SOLAR IRRADIANCE FORECASTING, BENCHMARKING of DIFFERENT TECHNIQUES and APPLICATIONS of ENERGY METEOROLOGY

SOLAR IRRADIANCE FORECASTING, BENCHMARKING of DIFFERENT TECHNIQUES and APPLICATIONS of ENERGY METEOROLOGY SOLAR IRRADIANCE FORECASTING, BENCHMARKING of DIFFERENT TECHNIQUES and APPLICATIONS of ENERGY METEOROLOGY Wolfgang Traunmüller 1 * and Gerald Steinmaurer 2 1 BLUE SKY Wetteranalysen, 4800 Attnang-Puchheim,

More information

Towards an NWP-testbed

Towards an NWP-testbed Towards an NWP-testbed Ewan O Connor and Robin Hogan University of Reading, UK Overview Cloud schemes in NWP models are basically the same as in climate models, but easier to evaluate using ARM because:

More information

Big Data Assimilation Revolutionizing Weather Prediction

Big Data Assimilation Revolutionizing Weather Prediction February 23, 2015, ISDA2015, Kobe Big Data Assimilation Revolutionizing Weather Prediction M. Kunii, J. Ruiz, G.-Y. Lien, K. Kondo, S. Otsuka, Y. Maejima, and Takemasa Miyoshi* RIKEN Advanced Institute

More information

High Performance Computing for Numerical Weather Prediction

High Performance Computing for Numerical Weather Prediction High Performance Computing for Numerical Weather Prediction Isabella Weger European Centre for Medium-Range Weather Forecasts Slide 1 ECMWF ECMWF A European organisation with headquarters in the UK Established

More information

The accuracy of weather forecasts for Melbourne, Australia

The accuracy of weather forecasts for Melbourne, Australia The accuracy of weather forecasts for Melbourne, Australia Harvey Stern Bureau of Meteorology, Melbourne, Australia Email: h.stern@bom.gov.au An analysis of the accuracy, and trends in the accuracy, of

More information

A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning.

A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning. A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning. 31st Annual International Symposium on Forecasting Lourdes Ramírez Santigosa Martín

More information

Intra-seasonal and Annual variability of the Agulhas Current from satellite observations

Intra-seasonal and Annual variability of the Agulhas Current from satellite observations Intra-seasonal and Annual variability of the Agulhas Current from satellite observations Marjolaine Krug Ecosystem Earth Observation (CSIR NRE) Pierrick Penven Laboratoire de Physique des Océans (IRD)

More information

Validation n 2 of the Wind Data Generator (WDG) software performance. Comparison with measured mast data - Flat site in Northern France

Validation n 2 of the Wind Data Generator (WDG) software performance. Comparison with measured mast data - Flat site in Northern France Validation n 2 of the Wind Data Generator (WDG) software performance Comparison with measured mast data - Flat site in Northern France Mr. Tristan Fabre* La Compagnie du Vent, GDF-SUEZ, Montpellier, 34967,

More information

http://www.isac.cnr.it/~ipwg/

http://www.isac.cnr.it/~ipwg/ The CGMS International Precipitation Working Group: Experience and Perspectives Vincenzo Levizzani CNR-ISAC, Bologna, Italy and Arnold Gruber NOAA/NESDIS & Univ. Maryland, College Park, MD, USA http://www.isac.cnr.it/~ipwg/

More information

Nowcasting: analysis and up to 6 hours forecast

Nowcasting: analysis and up to 6 hours forecast Nowcasting: analysis and up to 6 hours forecast Very high resoultion in time and space Better than NWP Rapid update Application oriented NWP problems for 0 6 forecast: Incomplete physics Resolution space

More information

Atmospheric kinetic energy spectra from high-resolution GEM models

Atmospheric kinetic energy spectra from high-resolution GEM models Atmospheric kinetic energy spectra from high-resolution GEM models Bertrand Denis NWP Section Canadian Meteorological Centre Environment Canada SRNWP 2009 Bad Orb, Germany Outline Introduction What we

More information

Development of an Integrated Data Product for Hawaii Climate

Development of an Integrated Data Product for Hawaii Climate Development of an Integrated Data Product for Hawaii Climate Jan Hafner, Shang-Ping Xie (PI)(IPRC/SOEST U. of Hawaii) Yi-Leng Chen (Co-I) (Meteorology Dept. Univ. of Hawaii) contribution Georgette Holmes

More information

Investigations on COSMO 2.8Km precipitation forecast

Investigations on COSMO 2.8Km precipitation forecast Investigations on COSMO 2.8Km precipitation forecast Federico Grazzini, ARPA-SIMC Emilia-Romagna Coordinator of physical aspects group of COSMO Outline Brief description of the COSMO-HR operational suites

More information

Evaluation of clouds in GCMs using ARM-data: A time-step approach

Evaluation of clouds in GCMs using ARM-data: A time-step approach Evaluation of clouds in GCMs using ARM-data: A time-step approach K. Van Weverberg 1, C. Morcrette 1, H.-Y. Ma 2, S. Klein 2, M. Ahlgrimm 3, R. Forbes 3 and J. Petch 1 MACCBET Symposium, Royal Meteorological

More information

DELIVERABLE REPORT D-1.10:

DELIVERABLE REPORT D-1.10: ANEMOSplus Advanced Tools for the Management of Electricity Grids with Large-Scale Wind Generation Project funded by the European Commission under the 6 th Framework Program Priority 61 Sustainable Energy

More information

Application of Numerical Weather Prediction Models for Drought Monitoring. Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia

Application of Numerical Weather Prediction Models for Drought Monitoring. Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia Application of Numerical Weather Prediction Models for Drought Monitoring Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia Contents 1. Introduction 2. Numerical Weather Prediction Models -

More information

Hybrid-DA in NWP. Experience at the Met Office and elsewhere. GODAE OceanView DA Task Team. Andrew Lorenc, Met Office, Exeter.

Hybrid-DA in NWP. Experience at the Met Office and elsewhere. GODAE OceanView DA Task Team. Andrew Lorenc, Met Office, Exeter. Hybrid-DA in NWP Experience at the Met Office and elsewhere GODAE OceanView DA Task Team Andrew Lorenc, Met Office, Exeter. 21 May 2015 Crown copyright Met Office Recent History of DA for NWP 4DVar was

More information

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D Munn V. Shukla and P. K. Thapliyal Atmospheric Sciences Division Atmospheric and Oceanic Sciences Group Space Applications

More information

Climate modelling. Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change

Climate modelling. Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change Hessisches Landesamt für Umwelt und Geologie Climate modelling Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change Climate: Definition Weather: momentary state

More information

WEATHER RADAR VELOCITY FIELD CONFIGURATIONS ASSOCIATED WITH SEVERE WEATHER SITUATIONS THAT OCCUR IN SOUTH-EASTERN ROMANIA

WEATHER RADAR VELOCITY FIELD CONFIGURATIONS ASSOCIATED WITH SEVERE WEATHER SITUATIONS THAT OCCUR IN SOUTH-EASTERN ROMANIA Romanian Reports in Physics, Vol. 65, No. 4, P. 1454 1468, 2013 ATMOSPHERE PHYSICS WEATHER RADAR VELOCITY FIELD CONFIGURATIONS ASSOCIATED WITH SEVERE WEATHER SITUATIONS THAT OCCUR IN SOUTH-EASTERN ROMANIA

More information

Air Masses and Fronts

Air Masses and Fronts Air Masses and Fronts Air Masses The weather of the United States east of the Rocky Mountains is dominated by large masses of air that travel south from the wide expanses of land in Canada, and north from

More information

9. Model Sensitivity and Uncertainty Analysis

9. Model Sensitivity and Uncertainty Analysis 9. Model Sensitivity and Uncertainty Analysis 1. Introduction 255 2. Issues, Concerns and Terminology 256 3. Variability and Uncertainty In Model Output 258 3.1. Natural Variability 259 3.2. Knowledge

More information

REGIONAL CLIMATE AND DOWNSCALING

REGIONAL CLIMATE AND DOWNSCALING REGIONAL CLIMATE AND DOWNSCALING Regional Climate Modelling at the Hungarian Meteorological Service ANDRÁS HORÁNYI (horanyi( horanyi.a@.a@met.hu) Special thanks: : Gabriella Csima,, Péter Szabó, Gabriella

More information

Thomas Fiolleau Rémy Roca Frederico Carlos Angelis Nicolas Viltard. www.satmos.meteo.fr

Thomas Fiolleau Rémy Roca Frederico Carlos Angelis Nicolas Viltard. www.satmos.meteo.fr Comparison of tropical convective systems life cycle characteristics from geostationary and TRMM observations for the West African, Indian and South American regions Thomas Fiolleau Rémy Roca Frederico

More information

Solar forecasting for grid management with high PV penetration

Solar forecasting for grid management with high PV penetration Solar forecasting for grid management with high PV penetration Lu ZHAO, Wilfred Walsh Solar Energy Research Institute of Singapore (SERIS) InterMET Asia 23 Apri 2015 1! Presentation outline About SERIS

More information

Science Goals for the ARM Recovery Act Radars

Science Goals for the ARM Recovery Act Radars DOE/SC-ARM-12-010 Science Goals for the ARM Recovery Act Radars JH Mather May 2012 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States

More information

A Reliability Point and Kalman Filter-based Vehicle Tracking Technique

A Reliability Point and Kalman Filter-based Vehicle Tracking Technique A Reliability Point and Kalman Filter-based Vehicle Tracing Technique Soo Siang Teoh and Thomas Bräunl Abstract This paper introduces a technique for tracing the movement of vehicles in consecutive video

More information

Turbulent mixing in clouds latent heat and cloud microphysics effects

Turbulent mixing in clouds latent heat and cloud microphysics effects Turbulent mixing in clouds latent heat and cloud microphysics effects Szymon P. Malinowski1*, Mirosław Andrejczuk2, Wojciech W. Grabowski3, Piotr Korczyk4, Tomasz A. Kowalewski4 and Piotr K. Smolarkiewicz3

More information

A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions

A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions Jing Gao Wei Fan Jiawei Han Philip S. Yu University of Illinois at Urbana-Champaign IBM T. J. Watson Research Center

More information

Decadal/Interdecadal variations in ENSO predictability in a hybrid coupled model from 1881-2000

Decadal/Interdecadal variations in ENSO predictability in a hybrid coupled model from 1881-2000 Decadal/Interdecadal variations in ENSO predictability in a hybrid coupled model from 1881-2000 Ziwang Deng and Youmin Tang Environmental Science and Engineering, University of Northern British Columbia,

More information

Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison

Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison Suman Goyal Sc E /In-charge SYNOPTIC Application Unit Satellite Meteorology Davison Introduction What is ForTraCC? It is an algorithm for tracking and forecasting radiative and morphological characteristics

More information

Real-time Ocean Forecasting Needs at NCEP National Weather Service

Real-time Ocean Forecasting Needs at NCEP National Weather Service Real-time Ocean Forecasting Needs at NCEP National Weather Service D.B. Rao NCEP Environmental Modeling Center December, 2005 HYCOM Annual Meeting, Miami, FL COMMERCE ENVIRONMENT STATE/LOCAL PLANNING HEALTH

More information

Chapter 2 False Alarm in Satellite Precipitation Data

Chapter 2 False Alarm in Satellite Precipitation Data Chapter 2 False Alarm in Satellite Precipitation Data Evaluation of satellite precipitation algorithms is essential for future algorithm development. This is why many previous studies are devoted to the

More information

Decision support for urban drainage using radar data of HydroNET-SCOUT

Decision support for urban drainage using radar data of HydroNET-SCOUT Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2011). 1 Decision support for urban drainage using radar data of HydroNET-SCOUT ARNOLD LOBBRECHT

More information

Robotics. Chapter 25. Chapter 25 1

Robotics. Chapter 25. Chapter 25 1 Robotics Chapter 25 Chapter 25 1 Outline Robots, Effectors, and Sensors Localization and Mapping Motion Planning Motor Control Chapter 25 2 Mobile Robots Chapter 25 3 Manipulators P R R R R R Configuration

More information

Project Title: Quantifying Uncertainties of High-Resolution WRF Modeling on Downslope Wind Forecasts in the Las Vegas Valley

Project Title: Quantifying Uncertainties of High-Resolution WRF Modeling on Downslope Wind Forecasts in the Las Vegas Valley University: Florida Institute of Technology Name of University Researcher Preparing Report: Sen Chiao NWS Office: Las Vegas Name of NWS Researcher Preparing Report: Stanley Czyzyk Type of Project (Partners

More information

Fire Weather Index: from high resolution climatology to Climate Change impact study

Fire Weather Index: from high resolution climatology to Climate Change impact study Fire Weather Index: from high resolution climatology to Climate Change impact study International Conference on current knowledge of Climate Change Impacts on Agriculture and Forestry in Europe COST-WMO

More information

Conclusions and Future Directions

Conclusions and Future Directions Chapter 9 This chapter summarizes the thesis with discussion of (a) the findings and the contributions to the state-of-the-art in the disciplines covered by this work, and (b) future work, those directions

More information

A Statistical Framework for Operational Infrasound Monitoring

A Statistical Framework for Operational Infrasound Monitoring A Statistical Framework for Operational Infrasound Monitoring Stephen J. Arrowsmith Rod W. Whitaker LA-UR 11-03040 The views expressed here do not necessarily reflect the views of the United States Government,

More information

SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations

SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations 22 September 2011 Hervé LE GLEAU, Marcel DERRIEN Centre de météorologie Spatiale. Lannion Météo-France 1 Fog or low level clouds?

More information

1.24 APPLICATION AND DEVELOPMENT OF THE OFIS MODEL WITHIN THE FRAMEWORK OF CITYDELTA

1.24 APPLICATION AND DEVELOPMENT OF THE OFIS MODEL WITHIN THE FRAMEWORK OF CITYDELTA 1.24 APPLICATION AND DEVELOPMENT OF THE MODEL WITHIN THE FRAMEWORK OF CITYDELTA Nicolas Moussiopoulos and Ioannis Douros Laboratory of Heat Transfer and Environmental Engineering, Aristotle University

More information

An Analysis of the Rossby Wave Theory

An Analysis of the Rossby Wave Theory An Analysis of the Rossby Wave Theory Morgan E. Brown, Elise V. Johnson, Stephen A. Kearney ABSTRACT Large-scale planetary waves are known as Rossby waves. The Rossby wave theory gives us an idealized

More information

Recent activities on Big Data Assimilation in Japan

Recent activities on Big Data Assimilation in Japan August 17, 2014, WWOSC, Montreal, Canada Recent activities on Big Data Assimilation in Japan M. Kunii, J. Ruiz, K. Kondo, and Takemasa Miyoshi* RIKEN Advanced Institute for Computational Science *PI and

More information

Predicting daily incoming solar energy from weather data

Predicting daily incoming solar energy from weather data Predicting daily incoming solar energy from weather data ROMAIN JUBAN, PATRICK QUACH Stanford University - CS229 Machine Learning December 12, 2013 Being able to accurately predict the solar power hitting

More information

CLOUD COVER IMPACT ON PHOTOVOLTAIC POWER PRODUCTION IN SOUTH AFRICA

CLOUD COVER IMPACT ON PHOTOVOLTAIC POWER PRODUCTION IN SOUTH AFRICA CLOUD COVER IMPACT ON PHOTOVOLTAIC POWER PRODUCTION IN SOUTH AFRICA Marcel Suri 1, Tomas Cebecauer 1, Artur Skoczek 1, Ronald Marais 2, Crescent Mushwana 2, Josh Reinecke 3 and Riaan Meyer 4 1 GeoModel

More information

PTE505: Inverse Modeling for Subsurface Flow Data Integration (3 Units)

PTE505: Inverse Modeling for Subsurface Flow Data Integration (3 Units) PTE505: Inverse Modeling for Subsurface Flow Data Integration (3 Units) Instructor: Behnam Jafarpour, Mork Family Department of Chemical Engineering and Material Science Petroleum Engineering, HED 313,

More information

Weather Radar Basics

Weather Radar Basics Weather Radar Basics RADAR: Radio Detection And Ranging Developed during World War II as a method to detect the presence of ships and aircraft (the military considered weather targets as noise) Since WW

More information

Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF

Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF 3 Working Group on Verification and Case Studies 56 Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF Bogdan Alexandru MACO, Mihaela BOGDAN, Amalia IRIZA, Cosmin Dănuţ

More information

Distributed Solar Prediction with Wind Velocity

Distributed Solar Prediction with Wind Velocity Distributed Solar Prediction with Wind Velocity Justin Domke, Nick Engerer, Aditya Menon, Christfried Webers National ICT Australia and the Australian National University Abstract The growing uptake of

More information

Signal Detection. Outline. Detection Theory. Example Applications of Detection Theory

Signal Detection. Outline. Detection Theory. Example Applications of Detection Theory Outline Signal Detection M. Sami Fadali Professor of lectrical ngineering University of Nevada, Reno Hypothesis testing. Neyman-Pearson (NP) detector for a known signal in white Gaussian noise (WGN). Matched

More information

Annealing Techniques for Data Integration

Annealing Techniques for Data Integration Reservoir Modeling with GSLIB Annealing Techniques for Data Integration Discuss the Problem of Permeability Prediction Present Annealing Cosimulation More Details on Simulated Annealing Examples SASIM

More information

Classification of Bad Accounts in Credit Card Industry

Classification of Bad Accounts in Credit Card Industry Classification of Bad Accounts in Credit Card Industry Chengwei Yuan December 12, 2014 Introduction Risk management is critical for a credit card company to survive in such competing industry. In addition

More information

6.4 THE SIERRA ROTORS PROJECT, OBSERVATIONS OF MOUNTAIN WAVES. William O. J. Brown 1 *, Stephen A. Cohn 1, Vanda Grubiši 2, and Brian Billings 2

6.4 THE SIERRA ROTORS PROJECT, OBSERVATIONS OF MOUNTAIN WAVES. William O. J. Brown 1 *, Stephen A. Cohn 1, Vanda Grubiši 2, and Brian Billings 2 6.4 THE SIERRA ROTORS PROJECT, OBSERVATIONS OF MOUNTAIN WAVES William O. J. Brown 1 *, Stephen A. Cohn 1, Vanda Grubiši 2, and Brian Billings 2 1 National Center for Atmospheric Research, Boulder, Colorado.

More information

Verification of Summer Thundestorm Forecasts over the Pyrenees

Verification of Summer Thundestorm Forecasts over the Pyrenees Verification of Summer Thundestorm Forecasts over the Pyrenees Introduction Météo-France have conducted a study of summer thunderstorm forecasts in the Pyrenees in order to evaluate the performance, the

More information

Advances in data assimilation techniques

Advances in data assimilation techniques Advances in data assimilation techniques and their relevance to satellite data assimilation ECMWF Seminar on Use of Satellite Observations in NWP Andrew Lorenc,, 8-12 September 2014. Crown copyright Met

More information

Satellite Remote Sensing of Volcanic Ash

Satellite Remote Sensing of Volcanic Ash Marco Fulle www.stromboli.net Satellite Remote Sensing of Volcanic Ash Michael Pavolonis NOAA/NESDIS/STAR SCOPE Nowcasting 1 Meeting November 19 22, 2013 1 Outline Getty Images Volcanic ash satellite remote

More information

Sub-grid cloud parametrization issues in Met Office Unified Model

Sub-grid cloud parametrization issues in Met Office Unified Model Sub-grid cloud parametrization issues in Met Office Unified Model Cyril Morcrette Workshop on Parametrization of clouds and precipitation across model resolutions, ECMWF, Reading, November 2012 Table of

More information

Flash Flood Guidance Systems

Flash Flood Guidance Systems Flash Flood Guidance Systems Introduction The Flash Flood Guidance System (FFGS) was designed and developed by the Hydrologic Research Center a non-profit public benefit corporation located in of San Diego,

More information

APPLICATIONS OF DATA MINING TO PREDICT MESOSCALE WEATHER EVENTS (TORNADOES AND CLOUDBURSTS)

APPLICATIONS OF DATA MINING TO PREDICT MESOSCALE WEATHER EVENTS (TORNADOES AND CLOUDBURSTS) International Journal of Computer Engineering and Technology (IJCET) Volume 6, Issue 7, July 2015, pp. 19-26, Article ID: 50120150607003 Available online at http://www.iaeme.com/currentissue.asp?jtype=ijcet&vtype=6&itype=7

More information

User Perspectives on Project Feasibility Data

User Perspectives on Project Feasibility Data User Perspectives on Project Feasibility Data Marcel Šúri Tomáš Cebecauer GeoModel Solar s.r.o., Bratislava, Slovakia marcel.suri@geomodel.eu http://geomodelsolar.eu http://solargis.info Solar Resources

More information

Cloud Model Verification at the Air Force Weather Agency

Cloud Model Verification at the Air Force Weather Agency 2d Weather Group Cloud Model Verification at the Air Force Weather Agency Matthew Sittel UCAR Visiting Scientist Air Force Weather Agency Offutt AFB, NE Template: 28 Feb 06 Overview Cloud Models Ground

More information

Dear Editor. Answer to the General Comments of Reviewer # 1:

Dear Editor. Answer to the General Comments of Reviewer # 1: Dear Editor The paper has been fully rewritten and the title changed accordingly to Referee 1. Figures have been updated in order to answer to the well-posed questions of the reviewers. The general structure

More information

New challenges of water resources management: Title the future role of CHy

New challenges of water resources management: Title the future role of CHy New challenges of water resources management: Title the future role of CHy by Bruce Stewart* Karl Hofius in his article in this issue of the Bulletin entitled Evolving role of WMO in hydrology and water

More information

National Weather Service Flash Flood Modeling and Warning Services

National Weather Service Flash Flood Modeling and Warning Services National Weather Service Flash Flood Modeling and Warning Services Seann Reed, Middle Atlantic River Forecast Center Peter Ahnert, Middle Atlantic River Forecast Center August 23, 2012 USACE Flood Risk

More information

Reprint Seamless Weather Forecast from Minutes to Days to Support Air Travel. W.K. Wong, S.M. Tse & P. Cheung

Reprint Seamless Weather Forecast from Minutes to Days to Support Air Travel. W.K. Wong, S.M. Tse & P. Cheung Reprint 1020 Seamless Weather Forecast from Minutes to Days to Support Air Travel W.K. Wong, S.M. Tse & P. Cheung HKIE ICT Conference: Technologies for a Smart City Hong Kong, China 11 May 2012 Seamless

More information

The Weather Intelligence for Renewable Energies Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

The Weather Intelligence for Renewable Energies Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation Energies 2015, 8, 9594-9619; doi:10.3390/en8099594 Article OPEN ACCESS energies ISSN 1996-1073 www.mdpi.com/journal/energies The Weather Intelligence for Renewable Energies Benchmarking Exercise on Short-Term

More information

The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network

The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network , pp.67-76 http://dx.doi.org/10.14257/ijdta.2016.9.1.06 The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network Lihua Yang and Baolin Li* School of Economics and

More information

Monitoring and Early Management of Emergences: New Instruments

Monitoring and Early Management of Emergences: New Instruments Monitoring and Early Management of Emergences: New Instruments Daniele Caviglia, DITEN - University of Genoa Domenico Sguerso, DICCA - University of Genoa Bianca Federici, DICCA - University of Genoa Andrea

More information