Analysis of long-term temporal variations in atmospheric water vapor time series
|
|
|
- Derek Harrison
- 5 years ago
- Views:
Transcription
1 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf, G. Dick, S. Heise, T. Simeonov, S. Vey, T. Schmidt, and J. Wickert German Research Center for Geosciences GFZ
2 Motivation Improving the assessment of past and projected impacts of climate change Monitoring atmospheric variables: Temperature Precipitable water vapor Precipitation Ice and snow GNSS are not sufficient and time series are not long enough Meteorological data, Radiosonde, Reanalysis and model data Data homogenization 2 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
3 Data sets GPS-based PWV, ZTD, ZWD, at 15 minutes 278 sites 84 sites with time series > 10 years 3 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
4 Data sets Potsdam 4 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
5 Data sets Potsdam 5 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
6 Data sets GPS-based PWV, ZTD, ZWD, at 15 minutes 278 sites 84 sites with time series > 10 years 326 meteorological stations from the German weather service (DWD) Climate Data Center (CDC) ftp://ftp-cdc.dwd.de/pub/cdc/ Hourly observations of P, T, RH, etc. Radiosonde, 2 measurements/day ERA-Interim at 6 hours and 60 km 60 km, since Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
7 GNSS and ERA-Interim Bavaria, 907 m AMSL Downscaling Vertical interpolation Daily mean values Rhineland, 399 m AMSL Bavaria, 1779 m AMSL 7 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
![GNSS and ERA-Interim Bavaria, 907 m AMSL Downscaling Vertical interpolation Daily mean values Rhineland, 399 m AMSL Bavaria, 1779 m AMSL Mean [mm] Std [mm] Corr. Coef.](/docs-images/89/98273246/images/8-1.jpg "Site 0269 (Bavaria) -0.275 0.33 0.998 Site 0522 (Rhinland) 0.205 0.189 0.999 Site 0285 (Bavaria) -0.598 0.492 0.")
8 GNSS and ERA-Interim Bavaria, 907 m AMSL Downscaling Vertical interpolation Daily mean values Rhineland, 399 m AMSL Bavaria, 1779 m AMSL Mean [mm] Std [mm] Corr. Coef. Site 0269 (Bavaria) Site 0522 (Rhinland) Site 0285 (Bavaria) Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
9 GNSS and ERA-Interim Using ERA-Interim pressure and temperature Downscaling and vertical interpolation Site 0522 Rhineland, 399 m AMSL Site 0285 Bavaria, 1779 m AMSL 9 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
10 GNSS and ERA-Interim Using ERA-Interim pressure and temperature Downscaling and vertical interpolation ERA-Interim data are good replacement for synoptic data Site 0522 Rhineland, 399 m AMSL Site 0285 Bavaria, 1779 m AMSL Mean [hpa] Std [hpa] Corr. Coef. Site Site Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
11 GNSS and Radiosonde 11 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
![GNSS and Radiosonde 119.5 m AMSL 12 UTC Corr. Coef. 0.98 Mean [mm] 1.17 Std [mm] 1.](/docs-images/89/98273246/images/12-2.jpg "57 12 Analysis of long-term temporal variations in atmospheric water vapor time series F.")
12 GNSS and Radiosonde m AMSL 12 UTC Corr. Coef Mean [mm] 1.17 Std [mm] Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
![GNSS and Radiosonde 119.5 m AMSL 00 UTC Corr. Coef. 0.98 Mean [mm] 0.19 Std [mm] 1.](/docs-images/89/98273246/images/13-2.jpg "79 13 Analysis of long-term temporal variations in atmospheric water vapor time series F.")
13 GNSS and Radiosonde m AMSL 00 UTC Corr. Coef Mean [mm] 0.19 Std [mm] Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
14 PWV from GNSS, ERA-Interim and Synoptic data Trend analysis For climatology, 15 years is too short! Other long-term data sets: ERA-Interim reanalysis data Synoptic data Using the Reitan relation: ln PPPPPP = aa TTTT bb aa = 1.288, 1.249, bb = , , for hourly, daily, and monthly data, repec. TT dd = TT 100 RRRR 5 14 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
15 PWV from GNSS, ERA-Interim and Synoptic data Site 0897, Berlin, 78 m AMSL 15 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
![PWV from GNSS, ERA-Interim and Synoptic data Site 0897, Berlin, 78 m AMSL Mean [mm] Std [mm] CC ERA-Interim/GNSS -0.184 0.539 0.](/docs-images/89/98273246/images/16-1.jpg "996 ERA-Interim/Synoptic -0.1933 0.9745 0.987 16 Analysis of long-term temporal variations in atmospheric water vapor time series F.")
16 PWV from GNSS, ERA-Interim and Synoptic data Site 0897, Berlin, 78 m AMSL Mean [mm] Std [mm] CC ERA-Interim/GNSS ERA-Interim/Synoptic Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
![PWV from GNSS, ERA-Interim and Synoptic data Site IFU1, Bavaria, 745 m AMSL Mean [mm] Std [mm] CC ERA-Interim/GNSS -0.184 0.539 0.](/docs-images/89/98273246/images/17-1.jpg "996 ERA-Interim/Synoptic -0.835 1.53 0.965 17 Analysis of long-term temporal variations in atmospheric water vapor time series F.")
17 PWV from GNSS, ERA-Interim and Synoptic data Site IFU1, Bavaria, 745 m AMSL Mean [mm] Std [mm] CC ERA-Interim/GNSS ERA-Interim/Synoptic Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
18 Determination of Decadal variations PWV and temperature time series have: Trend component Seasonal component Irregular component Trend estimation with moving average filter Estimation of the seasonal signal from the detrended signal Iterative solution [Days] 18 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
19 Determination of Decadal variations mm/decade Site 0897, Berlin, 78 m AMSL 0.33 C/decade 19 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
20 Determination of Decadal variations 0.42 mm/decade Site IFU1, Bavaria, 745 m AMSL C/decade 20 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
21 Determination of decadal variations Temperature 0.28 C/decade Site ZUGS, Bavaria, 2963 m AMSL 0.18 C/decade 0.3 C/decade 21 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
22 Determination of decadal variations Precipitation and snow Site ZUGS, Bavaria, 2963 m AMSL 22 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
23 Data homogenization 101 GPS stations 47 contain change points Mainly due to inconsistencies in PWV time series made by hardware replacement and installation ERA-Interim, also showed change points The radiosonde RH measurements are not homogenized before assimilated into ERA-Interim Ning, T., J. Wickert, Z. Deng, S. Heise, G. Dick, S. Vey, and T. Schöne, 2016: Homogenized time series of the atmospheric water vapor content obtained from the GNSS reprocessed data. J. Climate. doi: /jcli-d , in press 23 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
24 Data homogenization 101 GPS stations 47 contain change points Mainly due to inconsistencies in PWV time series made by hardware replacement and installation ERA-Interim, also showed change points Site ZUGS The radiosonde RH measurements are not homogenized GAPS before in assimilated the PWV time into ERA-Interim series Lack of meteorological data Ning, T., J. Wickert, Z. Deng, S. Heise, G. Dick, S. Vey, and T. Schöne, 2016: Homogenized time series of the atmospheric water vapor content obtained from the GNSS reprocessed data. J. Climate. doi: /jcli-d , in press Delay in raw data transfer 24 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
25 Outlook Produce sequence of 2D maps of PWV, Temp, etc, for the region of Germany over long time periods Study their temporal evolution on regional scale Compare with model data (WRF, spatial resolution of 2 km 2 km) Involve climate models 25 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
26 Outlook Produce sequence of 2D maps of PWV, Temp, etc, for the region of Germany over long time periods Study their temporal evolution on regional scale Compare with model data (WRF, spatial resolution of 2 km 2 km) Involve climate models Thank you very much 26 Analysis of long-term temporal variations in atmospheric water vapor time series F. Alshawaf
On the statistical significance of climatic trends estimated from GRUAN tropospheric time series
On the statistical significance of climatic trends estimated from GRUAN tropospheric time series Fadwa Alshawaf, Galina Dick, Jens Wickert 1 On the statistical significance of climatic trends estimated
Ground-based GPS networks for remote sensing of the atmospheric water vapour content: a review
Ground-based GPS networks for remote sensing of the atmospheric water vapour content: a review Gunnar Elgered Earth and Space Sciences, Chalmers University of Technology, Onsala Space Observatory, SE-43992
GRUAN GNSS Precipitable Water (GNSS-PW) Task Team: Accomplishment, Progress and Plan
GRUAN GNSS Precipitable Water (GNSS-PW) Task Team: Accomplishment, Progress and Plan Co-chairs: Junhong (June) Wang and Kalev Rannat Members: John Braun, UCAR, USA Galina Dick, GeoForschungsZentrum Potsdam,
Constructing high-resolution, absolute maps of atmospheric water vapor by combining InSAR and GNSS observations
Constructing high-resolution, absolute maps of atmospheric water vapor by combining InSAR and GNSS observations Fadwa Alshawaf, Stefan Hinz, Michael Mayer, Franz J. Meyer fadwa.alshawaf@kit.edu INSTITUTE
Use of ground-based GNSS measurements in data assimilation. Reima Eresmaa Finnish Meteorological Institute
Use of ground-based GNSS measurements in data assimilation Reima Eresmaa Finnish Meteorological Institute 16 June 2006 Outline 1) Introduction GNSS * positioning Tropospheric delay 2) GNSS as a meteorological
The PaTrop Experiment
Improved estimation of the tropospheric delay component in GNSS and InSAR measurements in the Western Corinth Gulf (Greece), by the use of a highresolution meteorological model: The PaTrop Experiment N.
Climate Downscaling 201
Climate Downscaling 201 (with applications to Florida Precipitation) Michael E. Mann Departments of Meteorology & Geosciences; Earth & Environmental Systems Institute Penn State University USGS-FAU Precipitation
Seasonal forecasting of climate anomalies for agriculture in Italy: the TEMPIO Project
Seasonal forecasting of climate anomalies for agriculture in Italy: the TEMPIO Project M. Baldi(*), S. Esposito(**), E. Di Giuseppe (**), M. Pasqui(*), G. Maracchi(*) and D. Vento (**) * CNR IBIMET **
Development and applications of regional reanalyses for Europe and Germany based on DWD s NWP models: Status and outlook
Development and applications of regional reanalyses for Europe and Germany based on DWD s NWP models: Status and outlook Frank Kaspar 1, Michael Borsche 1, Natacha Fery 1, Andrea K. Kaiser-Weiss 1, Jan
Assimilation of ground-based GPS data into a limited area model. M. Tomassini*
Assimilation of ground-based GPS data into a limited area model M. Tomassini* GeoForschungsZentrum, Potsdam, Germany * On assignment to Deutscher Wetterdienst, Offenbach, Germany Abstract Two years of
IMPACT OF GROUND-BASED GPS PRECIPITABLE WATER VAPOR AND COSMIC GPS REFRACTIVITY PROFILE ON HURRICANE DEAN FORECAST. (a) (b) (c)
9B.3 IMPACT OF GROUND-BASED GPS PRECIPITABLE WATER VAPOR AND COSMIC GPS REFRACTIVITY PROFILE ON HURRICANE DEAN FORECAST Tetsuya Iwabuchi *, J. J. Braun, and T. Van Hove UCAR, Boulder, Colorado 1. INTRODUCTION
WG1 Overview. PP KENDA for km-scale EPS: LETKF. current DA method: nudging. radar reflectivity (precip): latent heat nudging 1DVar (comparison)
WG1 Overview Deutscher Wetterdienst, D-63067 Offenbach, Germany current DA method: nudging PP KENDA for km-scale EPS: LETKF radar reflectivity (precip): latent heat nudging 1DVar (comparison) radar radial
Moisture transport to Syowa Station and Dome Fuji Station, Antarctica
Session 5: Science Using Ground-Based and Satellite Measurements Moisture transport to Syowa Station and Dome Fuji Station, Antarctica Kazue Suzuki, Takashi Yamanouchi, Naohiko Hirasawa and Hideaki Motoyama
Developments at DWD: Integrated water vapour (IWV) from ground-based GPS
1 Working Group on Data Assimilation 2 Developments at DWD: Integrated water vapour (IWV) from ground-based Christoph Schraff, Maria Tomassini, and Klaus Stephan Deutscher Wetterdienst, Frankfurter Strasse
Development towards inter-technique tropospheric parameter comparisons and their exploitation
Development towards inter-technique tropospheric parameter comparisons and their exploitation J. Douša 1, S. Byram 2, G. Győri 1, O. Bӧhm 1, C. Hackman 2, F. Zus 3 1 Geodetic Observatory Pecný, RIGTC,
LONG-TERM TRENDS IN THE AMOUNT OF ATMOSPHERIC WATER VAPOUR DERIVED FROM SPACE GEODETIC AND REMOTE SENSING TECHNIQUES
LONG-TERM TRENDS IN THE AMOUNT OF ATMOSPHERIC WATER VAPOUR DERIVED FROM SPACE GEODETIC AND REMOTE SENSING TECHNIQUES Rüdiger Haas, Tong Ning, and Gunnar Elgered Chalmers University of Technology, Onsala
Pseudo-Global warming approach using 4KM WRF model
Pseudo-Global warming approach using 4KM WRF model S. Kurkute 1,2 Y. Li 1,2 1 School of Environment and Sustainability University of Saskatchewan 2 Global Institute of Water Security University of Saskatchewan
Climate Change and Runoff Statistics in the Rhine Basin: A Process Study with a Coupled Climate-Runoff Model
IACETH Climate Change and Runoff Statistics in the Rhine Basin: A Process Study with a Coupled Climate-Runoff Model Jan KLEINN, Christoph Frei, Joachim Gurtz, Pier Luigi Vidale, and Christoph Schär Institute
On the use of meteo data. How to raise the value of EPN s
On the use of meteo data or How to raise the value of EPN s ZTD product? Jan Dousa & Wolfgang Söhne 50th EUREF TWG, Florence, 2009-05-26 Introduction Last TWG (Jan Dousa's presentation): ti Towards more
Model Output Statistics (MOS)
Model Output Statistics (MOS) Numerical Weather Prediction (NWP) models calculate the future state of the atmosphere at certain points of time (forecasts). The calculation of these forecasts is based on
QualiMET 2.0. The new Quality Control System of Deutscher Wetterdienst
QualiMET 2.0 The new Quality Control System of Deutscher Wetterdienst Reinhard Spengler Deutscher Wetterdienst Department Observing Networks and Data Quality Assurance of Meteorological Data Michendorfer
ERA5 and the use of ERA data
ERA5 and the use of ERA data Hans Hersbach, and many colleagues European Centre for Medium-Range Weather Forecasts Overview Overview of Reanalysis products at ECMWF ERA5, the follow up of ERA-Interim,
Statistical Modeling of Atmospheric Mean Temperature in sub Sahel West Africa
Statistical Modeling of Atmospheric Mean Temperature in sub Sahel West Africa Falaiye O. A. *, Sukam Y. M. * and Abimbola O. J. ** arxiv:1901.02342v1 [physics.ao-ph] 27 Dec 2018 * Department of Physics,
The JRA-55 Reanalysis: quality control and reprocessing of observational data
The JRA-55 Reanalysis: quality control and reprocessing of observational data Kazutoshi Onogi On behalf of JRA group Japan Meteorological Agency 29 October 2014 EASCOF 1 1. Introduction 1. Introduction
Characteristics of GPS ZTD products. Jan Douša EUREF Analysis Centre Workshop
Characteristics of GPS ZTD products Jan Douša EUREF Analysis Centre Workshop March 15-16, 2006 Outline ZTD and PWV products Stragegy changes GPS constellation effect solution characteristics ZTD differences
WG3 MEETING POTSDAM SEP 1, 2016, 12:00-17:10 AGENDA AND ABSTRACTS
WG3 MEETING POTSDAM SEP 1, 2016, 12:00-17:10 AGENDA AND ABSTRACTS Olivier Bock and Rosa Pacione COST ES1206 http://gnss4swec.knmi.nl Contents Agenda... 3 Can horizontal delay gradients estimated from GNSS
The Role of CORS GNSS Data for Climate Monitoring: Case Study using NIGNET Network BY
The Role of CORS GNSS Data for Climate Monitoring: Case Study using NIGNET Network BY Abayomi AYOOLA, Adeyemi ADEBOMEHIN, Kufre Eko (Nigeria) and SÁ ANDRÉ (Portugal). Introduction The 2012 rainy season
The role of CORS GNSS data for climate monitoring: case study using NIGNET network
The role of CORS GNSS data for climate monitoring: case study using NIGNET network Adeyemi ADEBOMEHIN, A. AYOOLA, Kufrey EKO, Nigeria and André SÁ, Portugal Key words: GNSS, CORS, Climate, Water Vapor
Atmospheric Water Vapor Effect on GNSS Signals and InSAR Data
Atmospheric Water Vapor Effect on GNSS Signals and InSAR Data Basic Concept and Preliminary Results F. Alshawaf 1, S. Hinz 1, A. Thiele 1 T. Fuhrmann 2, B. Heck 2, A. Knöpfler 2, X. Luo 2, M. Mayer 2,
Northern New England Climate: Past, Present, and Future. Basic Concepts
Northern New England Climate: Past, Present, and Future Basic Concepts Weather instantaneous or synoptic measurements Climate time / space average Weather - the state of the air and atmosphere at a particular
Deutscher Wetterdienst. German Climate Services - A contribution to the Global Framework for Climate Services (GFCS) Tobias Fuchs and Paul Becker
Deutscher Wetterdienst German Climate Services - A contribution to the Global Framework for Climate Services (GFCS) Tobias Fuchs and Paul Becker Deutscher Wetterdienst (DWD) Business Area Climate and Environment
CLIPDAR -- DESIGN GUIDELINE FOR A CLIMATE PROJECTION DATA BASE AND SPECIFIC CLIMATE
CEDR Transnational Road Research Programme Call 2012 Road owners adapting to Climate Change CLIPDAR -- DESIGN GUIDELINE FOR A CLIMATE PROJECTION DATA BASE AND SPECIFIC CLIMATE INDICES FOR ROADS CHRISTOPH
ERA-CLIM: Developing reanalyses of the coupled climate system
ERA-CLIM: Developing reanalyses of the coupled climate system Dick Dee Acknowledgements: Reanalysis team and many others at ECMWF, ERA-CLIM project partners at Met Office, Météo France, EUMETSAT, Un. Bern,
Water vapour above Switzerland over the last 12 years
Water vapour above Switzerland over the last 12 years June Morland*, Martine Collaud**, Klemens Hocke*, Pierre Jeannet**, Christian Mätzler* *Institute of Applied Physics, University of Bern **MeteoSwiss
Recent Data Assimilation Activities at Environment Canada
Recent Data Assimilation Activities at Environment Canada Major upgrade to global and regional deterministic prediction systems (now in parallel run) Sea ice data assimilation Mark Buehner Data Assimilation
16th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes 8-11 September 2014, Varna, Bulgaria
6th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes 8- September 0, Varna, Bulgaria PREPARATION OF INPUT DATA SET FOR DISPERSION MODEL AUSTAL000
Climate Variables for Energy: WP2
Climate Variables for Energy: WP2 Phil Jones CRU, UEA, Norwich, UK Within ECEM, WP2 provides climate data for numerous variables to feed into WP3, where ESCIIs will be used to produce energy-relevant series
Exploitation of ground based GPS for Climate and Numerical Weather Prediction applications COST action 716
Exploitation of ground based GPS for Climate and Numerical Weather Prediction applications COST action 716 COST Objectives and status of COST 716 Overview of work packages / projects Near real-time demonstration
The correction of initial values of temperature based on T2m measurements
The correction of initial values of temperature based on T2m measurements Russian Hydrometeocentre Denis Blinov Anastasia Revokatova Inna Rozinkina Gdaly Rivin COSMO GM215, Wroclaw, 7-1 September Motivation
Report of the Scientific Project Manager
Report of the Scientific Project Manager G. Doms, DWD, 4th COSMO General Meeting, Warsaw, Poland Status of the LM LM Version 2.13 (18 January 2002) - Option for use of Wind profiler/rass reports - Adjustments
ECMWF global reanalyses: Resources for the wind energy community
ECMWF global reanalyses: Resources for the wind energy community (and a few myth-busters) Paul Poli European Centre for Medium-range Weather Forecasts (ECMWF) Shinfield Park, RG2 9AX, Reading, UK paul.poli
The influence of mid-latitude cyclones on European background surface ozone
1 The influence of mid-latitude cyclones on European background surface ozone K. Emma Knowland (USRA/GESTAR NASA/GMAO) In collaboration with: Ruth Doherty (U. Edinburgh) Kevin Hodges (U. Reading) Lesley
Francis O. 1, David H. Bromwich 1,2
Impact of assimilating COSMIC GPS RO moisture and temperature profiles on Polar WRF simulations of West Antarctic cyclones Francis O. O@eno 1, David H. Bromwich 1,2 1 Polar Meteorology Group BPRC 2 Atmospheric
Application and verification of the ECMWF products Report 2007
Application and verification of the ECMWF products Report 2007 National Meteorological Administration Romania 1. Summary of major highlights The medium range forecast activity within the National Meteorological
WRF MODEL STUDY OF TROPICAL INERTIA GRAVITY WAVES WITH COMPARISONS TO OBSERVATIONS. Stephanie Evan, Joan Alexander and Jimy Dudhia.
WRF MODEL STUDY OF TROPICAL INERTIA GRAVITY WAVES WITH COMPARISONS TO OBSERVATIONS. Stephanie Evan, Joan Alexander and Jimy Dudhia. Background Small-scale Gravity wave Inertia Gravity wave Mixed RossbyGravity
Experiences of using ECV datasets in ECMWF reanalyses including CCI applications. David Tan and colleagues ECMWF, Reading, UK
Experiences of using ECV datasets in ECMWF reanalyses including CCI applications David Tan and colleagues ECMWF, Reading, UK Slide 1 Main points Experience shows benefit of integrated & iterative approach
4.5 Comparison of weather data from the Remote Automated Weather Station network and the North American Regional Reanalysis
4.5 Comparison of weather data from the Remote Automated Weather Station network and the North American Regional Reanalysis Beth L. Hall and Timothy. J. Brown DRI, Reno, NV ABSTRACT. The North American
Climatology, Variability and Change In Arctic Surface-Based Inversions
Climatology, Variability and Change In Arctic Surface-Based Inversions Dian J. Seidel NOAA Air Resources Laboratory Yehui (Ally) Zhang Applied Hydrometeorological Research Institute Nanjing University
Radar Interferometry Dealing with atmospheric errors for individual interferograms
Radar Interferometry Dealing with atmospheric errors for individual interferograms Dr Zhenhong Li COMET, School of Geographical and Earth Sciences University of Glasgow Email: Zhenhong.Li@glasgow.ac.uk
HIRLAM Regional 3D-VAR and MESAN downscaling re-analysis for the recent. 20 year period in the FP7 EURO4M project SMHI
HIRLAM Regional 3D-VAR and MESAN downscaling re-analysis for the recent 20 year period in the FP7 EURO4M project Per Undén, Tomas Landelius Per Dahlgren, Per Kållberg Stefan Gollvik, Sébastien Villaume
USE OF TOTAL COLUMN WATER VAPOR MEASUREMENTS FOR FORECASTS OF THE NORTH AMERICAN MONSOON PRECIPITATION
USE OF TOTAL COLUMN WATER VAPOR MEASUREMENTS FOR FORECASTS OF THE NORTH AMERICAN MONSOON PRECIPITATION Presented by Yolande Serra University of Arizona Collaborators / Support Ave Arellano (UA Faculty)
Urban Forest Effects-Dry Deposition (UFORE D) Model Enhancements. Satoshi Hirabayashi
Urban Forest Effects-Dry Deposition (UFORE D) Model Enhancements Satoshi Hirabayashi The Davey Institute, The Davey Tree Expert Company, Syracuse, New York 13210, USA Surface Weather Data NOAA Integrated
A downscaling and adjustment method for climate projections in mountainous regions
A downscaling and adjustment method for climate projections in mountainous regions applicable to energy balance land surface models D. Verfaillie, M. Déqué, S. Morin, M. Lafaysse Météo-France CNRS, CNRM
Impact of GPS and TMI Precipitable Water Data on Mesoscale Numerical Weather Prediction Model Forecasts
Journal of the Meteorological Society of Japan, Vol. 82, No. 1B, pp. 453--457, 2004 453 Impact of GPS and TMI Precipitable Water Data on Mesoscale Numerical Weather Prediction Model Forecasts Ko KOIZUMI
Application and verification of ECMWF products 2009
Application and verification of ECMWF products 2009 RHMS of Serbia 1. Summary of major highlights ECMWF products are operationally used in Hydrometeorological Service of Serbia from the beginning of 2003.
Re-dimensioned CFS Reanalysis data for easy SWAT initialization
Re-dimensioned CFS Reanalysis data for easy SWAT initialization Daniel R Fuka, Charlotte MacAlister, Solomon Seyoum, Allan Jones, Raghavan Srinivasan Cornell University IWMI East Africa Texas A&M Re-dimensioned
Atmospheric Water Vapour Observations
Royal Observatory of Belgium Solar-Terrestrial Centre of Excellence Atmospheric Water Vapour Observations AT ROB AND RMI FOR WEATHER AND CLIMATE MONITORING Eric Pottiaux Roeland Van Malderen Julie Berckmans
GNSS METEOROLOGY AND WATER VAPOUR ESTIMATION IN TURKEY
GNSS METEOROLOGY AND WATER VAPOUR ESTIMATION IN TURKEY DR. CETIN MEKIK ASSOC. PROF., THE DEPT. OF GEOMATICS ENGINEERING BULENT ECEVIT UNIVERSITY, ZONGULDAK/TURKEY GNSS4SWEC MC&WG Meeting, Varna, Bulgaria,
Atmospheric science research for numerical weather prediction and climate modeling in Slovenia: contribution of the PECS program
Atmospheric science research for numerical weather prediction and climate modeling in Slovenia: contribution of the PECS program Matic Šavli, Žiga Zaplotnik, Veronika Hladnik, Gregor Skok and Nedjeljka
MEMORANDUM OF UNDERSTANDING
MEMORANDUM OF UNDERSTANDING between A: EUREF, the Reference Frame Sub-Commission for Europe of the International Association of Geodesy (IAG) and B: EUMETNET, the Network of European Meteorological Services.
SPI: Standardized Precipitation Index
PRODUCT FACT SHEET: SPI Africa Version 1 (May. 2013) SPI: Standardized Precipitation Index Type Temporal scale Spatial scale Geo. coverage Precipitation Monthly Data dependent Africa (for a range of accumulation
From short range forecasts to climate change projections of extreme events in the Baltic Sea region
Great Baltic Sea flood, November 13, 1872 Farm houses in Niendorf (near Lübeck) being torn away. Privately owned, Fam. Muuß, Hotel Friedrichsruh. Sea level 3.50 m above normal. From short range forecasts
Effects of the NAO and other atmospheric teleconnection patterns on wind resources in Western Europe
Effects of the NAO and other atmospheric teleconnection patterns on wind resources in Western Europe Laura Zubiate Sologaistoa Frank McDermott, Conor Sweeney, Mark O Malley The North Atlantic Oscillation
Observation requirements for regional reanalysis
Observation requirements for regional reanalysis Richard Renshaw 30 June 2015 Why produce a regional reanalysis? Evidence from operational NWP 25km Global vs 12km NAE ...the benefits of resolution global
Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system
2nd Workshop on Parameterization of Lakes in Numerical Weather Prediction and Climate Modelling Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system R. Salgado(1),
Modelling approaches for MOSAiC. Klaus Dethloff, A. Rinke, A. Sommerfeld, D. Klaus T. Vihma, M. Müller, J. Inoue, W. Maslowski & modelling team
Modelling approaches for MOSAiC Klaus Dethloff, A. Rinke, A. Sommerfeld, D. Klaus T. Vihma, M. Müller, J. Inoue, W. Maslowski & modelling team Why do we need MOSAiC? High quality co-observations of A-O-I-BGC-E
Implementation of SWAN model with COSMO-CLM and WRF-ARW wind forcing for the Barents Sea storm events (case study).
IGU Regional Conference Moscow 2015 Implementation of SWAN model with COSMO-CLM and WRF-ARW wind forcing for the Barents Sea storm events (case study). Stanislav Myslenkov 1, Vladimir Platonov 2 and Pavel
Homogenization of the Hellenic cloud amount time series
Homogenization of the Hellenic cloud amount time series A Argiriou 1, A Mamara 2, E Dimadis 1 1 Laboratory of Atmospheric Physics, 2 Hellenic Meteorological Service October 19, 2017 A Argiriou 1, A Mamara
Radiation Dry Bias Correction of Vaisala RS92 Humidity Data and Its Impacts on Historical Radiosonde Data
FEBRUARY 2013 W A N G E T A L. 197 Radiation Dry Bias Correction of Vaisala RS92 Humidity Data and Its Impacts on Historical Radiosonde Data JUNHONG WANG National Center for Atmospheric Research,* Boulder,
COSMO Activity Assimilation of 2m humidity in KENDA
COSMO Activity Assimilation of 2m humidity in KENDA Tobias Necker (1), Daniel Leuenberger (2) (1) Hans-Ertel-Centre for Weather Research, Germany (1) Meteorological Institute Munich, LMU Munich, Germany
Developing Operational MME Forecasts for Subseasonal Timescales
Developing Operational MME Forecasts for Subseasonal Timescales Dan C. Collins NOAA Climate Prediction Center (CPC) Acknowledgements: Stephen Baxter and Augustin Vintzileos (CPC and UMD) 1 Outline I. Operational
Toward improved initial conditions for NCAR s real-time convection-allowing ensemble. Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell
Toward improved initial conditions for NCAR s real-time convection-allowing ensemble Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell Storm-scale ensemble design Can an EnKF be used to initialize
Does the stratosphere provide predictability for month-ahead wind power in Europe?
ICEM 2017 Bari 27 June 2017 Does the stratosphere provide predictability for month-ahead wind power in Europe? Remo Beerli, Heini Wernli and Christian Grams Remo.Beerli@env.ethz.ch Institute for Atmospheric
Extreme Air Temperature at the Southwestern Slope of Pirin Mountain (Bulgaria)
Extreme Air Temperature at the Southwestern Slope of Pirin Mountain (Bulgaria) Nina Nikolova, Georgi Rachev, Dimitar Krenchev Sofia University St. Kliment Ohridski Bulgaria Acknowledgements: The study
Accuracy of Meteonorm ( )
Accuracy of Meteonorm (7.1.6.14035) A detailed look at the model steps and uncertainties 22.10.2015 Jan Remund Contents The atmosphere is a choatic system, not as exactly describable as many technical
Use of satellite data in reanalysis
Use of satellite data in reanalysis Dick Dee Acknowledgements: Paul Poli, Adrian Simmons, Hans Hersbach, Carole Peubey, David Tan, Rossana Dragani, the rest of the reanalysis team and many others at ECMWF.
Global reanalysis: Some lessons learned and future plans
Global reanalysis: Some lessons learned and future plans Adrian Simmons and Sakari Uppala European Centre for Medium-Range Weather Forecasts With thanks to Per Kållberg and many other colleagues from ECMWF
Evaluation of the atmospheric water vapor content in the regional climate model ALARO-0 using GNSS observations
Evaluation of the atmospheric water vapor content in the regional climate model ALARO-0 using GNSS observations Julie Berckmans 1, Roeland Van Malderen 1, Eric Pottiaux 2, Rosa Pacione 3 1 Royal Meteorological
NOAA Snow Map Climate Data Record Generated at Rutgers
NOAA Snow Map Climate Data Record Generated at Rutgers David A. Robinson Rutgers University Piscataway, NJ Snow Watch 2013 Downsview, Ontario January 29, 2013 December 2012 snow extent departures Motivation
Progress in the assimilation of groundbased GPS observations using the MM5. 4DVAR system
Progress in the assimilation of groundbased GPS observations using the MM5 4DVAR system Florian Zus1, Hans Stefan Bauer1,Volker Wulfmeyer1, Galina Dick2, Michael Bender2 1 Institute of Physics and Meteorology
The ECMWF coupled data assimilation system
The ECMWF coupled data assimilation system Patrick Laloyaux Acknowledgments: Magdalena Balmaseda, Kristian Mogensen, Peter Janssen, Dick Dee August 21, 214 Patrick Laloyaux (ECMWF) CERA August 21, 214
Online visualization of multi-dimensional spatiotemporal
Online visualization of multi-dimensional spatiotemporal data Visualization of weather data of Germany in a large time scale Keni Han Final presentation Supervisor: Dr.-Ing. Mathias Jahnke Univ.Prof. Mag.rer.nat.
Application and verification of ECMWF products 2008
Application and verification of ECMWF products 2008 RHMS of Serbia 1. Summary of major highlights ECMWF products are operationally used in Hydrometeorological Service of Serbia from the beginning of 2003.
Quantifying and reducing uncertainties
Quantifying and reducing uncertainties Work package 4 DWD, ECMWF, FFCUL, RIHMI, UNIBE, UNIVIE, UVSQ ERA-CLIM2 Review Meeting Jan 19, 2017 Main tasks 4.1 making optimal use of observations in reanalysis,
High-Resolution MPAS Simulations for Analysis of Climate Change Effects on Weather Extremes
High-Resolution MPAS Simulations for Analysis of Climate Change Effects on Weather Extremes ALLISON MICHAELIS, GARY LACKMANN, & WALT ROBINSON Department of Marine, Earth, and Atmospheric Sciences, North
Parallel measurements at German climate reference stations: DWD s approach to compare manual vs. automatic observations
Parallel measurements at German climate reference stations: DWD s approach to compare manual vs. automatic observations Frank Kaspar and Lisa Hannak Deutscher Wetterdienst, National Climate Monitoring,
Subproject 01 Climate Change in the Okavango region
Subproject 01 Climate Change in the Okavango region THE FUTURE OKAVANGO PROJECT General meeting 10. 13. October 2011 Maun-Lodge, Maun, Botswana Dr. Torsten Weber, Prof. Dr. Daniela Jacob Climate Service
JRA-55 Product Users Handbook
Climate Prediction Division Global Environment and Marine Department Japan Meteorological Agency September 2013 Change record Version Date Remarks 1.0 30 September 2013 First version 2.0 3 March 2014 Corrected
Observation minus Background Statistics for Humidity and Temperature from Raman lidar, microwave radiometer and COSMO-2
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Observation minus Background Statistics for Humidity and Temperature from Raman lidar, microwave radiometer
Introduction to Weather Data Cleaning
Introduction to Weather Data Cleaning Speedwell Weather Limited An Introduction Providing weather services since 1999 Largest private-sector database of world-wide historic weather data Major provider
Humidity 3D field comparisons between GNSS tomography, IASI satellite observations and ALARO model. Belgian Institute for Space Aeronomy BIRA 3
Oral Presentation, EGU0-85 Humidity D field comparisons between, H. Brenot, C. Champollion, A. Deckmyn, R. van Malderen, N. Kumps, R. Warnant, E. Goudenhoofdt, L. Delobbe and M. De Mazière contact: Belgian
SENSITIVITY OF THE SURFEX LAND SURFACE MODEL TO FORCING SETTINGS IN URBAN CLIMATE MODELLING
SENSITIVITY OF THE SURFEX LAND SURFACE MODEL TO FORCING SETTINGS IN URBAN CLIMATE MODELLING Gabriella Zsebeházi PhD supervisor: Gabriella Szépszó Regional Climate Modelling Group, Hungarian Meteorological
Future extreme precipitation events in the Southwestern US: climate change and natural modes of variability
Future extreme precipitation events in the Southwestern US: climate change and natural modes of variability Francina Dominguez Erick Rivera Fernandez Hsin-I Chang Christopher Castro AGU 2010 Fall Meeting
Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP
Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP September 2012 Outline Mission Extended Range Outlooks (6-10/8-14)
MOTIVATION. New view of Arctic cyclone activity from the Arctic System Reanalysis
New view of Arctic cyclone activity from the Arctic System Reanalysis Natalia Tilinina 1, Sergey Gulev 1 and David H.Bromwich 2 1) P.P. Shirshov Institute of Oceanology, Moscow 2) Byrd Polar Research Center,
IMPORTANCE OF SATELLITE DATA (FOR REANALYSIS AND BEYOND) Jörg Schulz EUMETSAT
IMPORTANCE OF SATELLITE DATA (FOR REANALYSIS AND BEYOND) Jörg Schulz EUMETSAT Why satellite data for climate monitoring? Global coverage Global consistency, sometimes also temporal consistency High spatial
Introduction to Reanalysis and JRA-55
TCC Training Seminar (29 JAN. 2018) Introduction to Reanalysis and JRA-55 Masashi HARADA Climate Prediction Division, Japan Meteorological Agency Outline 1. Introduction to Reanalysis Basic dataset for
Climate Change and Predictability of the Indian Summer Monsoon
Climate Change and Predictability of the Indian Summer Monsoon B. N. Goswami (goswami@tropmet.res.in) Indian Institute of Tropical Meteorology, Pune Annual mean Temp. over India 1875-2004 Kothawale, Roopakum
Data impact studies in the global NWP model at Meteo-France
Data impact studies in the global NWP model at Meteo-France Patrick Moll, Fatima Karbou, Claudia Faccani, Nathalie Saint- Ramond, Florence Rabier Centre National de Recherches Météorologiques CNRS/GAME,
8-km Historical Datasets for FPA
Program for Climate, Ecosystem and Fire Applications 8-km Historical Datasets for FPA Project Report John T. Abatzoglou Timothy J. Brown Division of Atmospheric Sciences. CEFA Report 09-04 June 2009 8-km