Information Server for the Global Soil Wetness Project Phase II
|
|
|
- Meghan Watson
- 5 years ago
- Views:
Transcription
1 1 Information Server for the Global Soil Wetness Project Phase II *T. Oki, N. Hanasaki, Y. Shen, S. Kanae, K. Masuda, and P.A. Dirmeyer *Institute of Industrial Science, University of Tokyo Asian Water Cycle Symposium, Nov. 3 rd, U of Tokyo, Japan
2 2 One of the Goals of the GSWP2 Produce the best global data sets of soil moisture, surface fluxes, and related hydrologic quantities (including runoff) for with 1x1 degree grid spacing considering the uncertainties associated with Land surface models: more than 20 LSMs Model parameters: 2 kinds of vegetation etc. Forcing data: 3 kinds of reanalysis data, corrected precipitation, etc. Temporal and spatial scales to run LSMs
3 3 Net radiation to Precipitation ratio (Rn/lP)
4 4 Evapotranspiration to precipitation ratio (E/P)
5 5 Climatic Zones delineated by Budyko s Aridity Index (BAI)
6 6 Mean Annual Precipitation 3000 Mean Water Balance ( ) (mm/year) Rain Snow Arid Semi Arid Semi Humid Humid Tropical Humid Cold Humid Ice Global
7 7 Mean Water Balance (mm/y) Water Flux from Land Surface ( ) Rsub Rsurf ET (mm/y) Arid Semi Arid Semi Humid Humid Tropical Humid Cold Humid Ice Global
8 GSWP2-ICC: Data viewer & data distributor Work with your internet browser Developed by Drs. E. Ikoma and M. Yasukawa Three interfaces 1. Data visualization on scratch pad Simple, high response, and easy-to-use viewer 2. Time sequential comparison For time series comparison at a grid point 3. Model inter-comparison workbench Matrix type viewer for model inter-comparison Prototype is introduced for B0 run outputs 8
9 SGI ONYX4 UltimateVision Approximately 0.7 PB of Data Archiver GSWP2-ICC/DDC Toppage 9
10 1. Data visualization on scratch pad Select data visualization on scratch pad 10
11 Data visualization on scratch pad Variable Model Period Location Select variable, model, period and location 11
12 Data visualization on scratch pad Selected data appears on the screen as a contour map 12
13 Time step: Daily Monthly mean Annual mean Color bar: Automatic User specified max. and min. 4 figure sizes Unit conversion from kg/m2/s to mm/day You can display several figures at once you can compare between variables/models 13
14 You can download the selected data, as well. (big or little endian, compressed binary file) 14
15 2. Time sequential comparison Select Time sequential comparison 15
16 Time sequential comparison Variable Model Period Location Select variable, model, period and location (Common interface) 16
17 Time sequential comparison Time series (one year) appear on screen 17
18 Time sequential comparison You can overlay several models 18
19 Time sequential comparison You can have a closer look 19
20 Time Sequential Comparison Spatial images of weekly time series around the specific grid point are displayed. Color bar can be modified. Mpeg animation of temporal sequences Frame by frame display by pointing images by mouse 20
21 Time sequential comparison You can download the time series data. 21
22 3. Model inter-comparison workbench Variable Model Period Location Select variable, model, period and location (Common interface) 22
23 3. Model inter-comparison workbench A A-B B A-C C B-A A B B-C C C-A A C-B B Show difference between models on screen C All the figures for comparing every pair of models are displayed at once. Color bar setting. Expansion and erase with a click 23
24 The GSWP2-ICC is scale independent! If you have a big screen, you can display many figures at once and enjoy the modern map discussion! 24
25 ICC workflow Public DVD, DAT, FTP Participants ICC Data Viewer & Data Distributor Dr. E. Ikoma Dr. M. Yasukawa IIS/UT Primary analysis N. Hanasaki Oki Lab Data upload Kitsuregawa Lab 25
26 Prototype of GSWP2-Data Download Center Specify year and month or 10 year mean Monthly/daily All on/off vertically Region by Lon./Lat. Select Experiment or Model All on/off laterally Automatic estimation of total volume
27 Data Download Center User GSWP2 server <haneda> Request HTTP Interface Program Stored data (Plain Binary) netcdf generate Program No Meta-data Retrieve data Send- Program With Meta-data (Self-Describing) GrADS supported FTP or HTTP File size limit: 300MB (Global, 3-hourly, for 1 year) Distribution data (netcdf)
28 You can check your downloaded file immediately via GrADS!! netcdf file Lon/Lat coordinate (GSWP2 original one is dehydrated -1D) COARDS convention Flexible cutout Area: rectangular Period: any month (annually, monthly, daily, 3-hourly(1995)) Model/Run
29 GSWP-2 Modeling Status MODEL CLM-TOP COLA-SSiB ISBA LaD MOSES-2 NOAH SiBUC SWAP VISA BUCKET* Mosaic NSIPP-catchment ORCHIDEE CLM Institute University of Texas at Austin COLA Météo France/CNRM USGS & NOAA/GFDL Met Office. UK NOAA NCEP/EMC Kyoto University Institute of Water Problems, Russian Academy of Sciences University of Texas at Austin University of Tokyo NASA GSFC/HSB NASA GSFC/NSIPP (GMAO) IPSL. France NASA GSFC/HSB Multi-model Analysis Included Ready to be included Not ready to be included HY-SSiB VIC NASA GSFC/HSB NASA GSFC/HSB * May be dropped
30 Validation of GSWP-2 1m Column Soil Moisture (IL, GSMDB) Total Field (1m, ) Correlation RMSE SSiB SiBUC VISA ISBA SWAPNOAH CLMMOSES ave 0 SSiB SiBUC VISA ISBA SWAPNOAH CLMMOSES ave Anomaly (1m, ) Correlation 0.4 RMSE SSiB ISBA SiBUC SWAP VISA NOAHMOSES CLM ave 0 SSiB ISBA SiBUC SWAP VISA NOAHMOSES CLM ave
31 Notice (gswp2; kanpai) DDC is now under TEST-OPERATION Now access is protected by password If you find any trouble, please contact us. Your request to ICC/DDC is welcome If you find any shortage in function, please let us know. We will try our best to support your request. BAMS Article on GSWP2 will appear soon.
32 32
A Global Water Budget Assessment
A Global Water Budget Assessment C. Adam Schlosser and Xiang Gao Joint Program on the Science and Policy of Global Change (JP Tech. Report #179, and accepted with minor revisions to J. of Hydrometeorology)
Analysis of multi-year global evapotranspiration datasets and IPCC AR4 model simulations: Results from the LandFlux-EVAL project
ETH Zürich Analysis of multi-year global evapotranspiration datasets and AR4 model simulations: Results from the LandFlux-EVAL project Brigitte Mueller S. I. Seneviratne, C. Jimenez, T. Corti, W. Dorigo,
GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) INTRODUCTION
GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) Hongliang Fang, Patricia L. Hrubiak, Hiroko Kato, Matthew Rodell, William L. Teng,
Amita Mehta and Ana Prados
Building Capacity in Utilizing NASA Remote Sensing Observations in SWAT for Water Resources and Agricultural Management Applications Amita Mehta and Ana Prados NASA - University of Maryland Baltimore County
Focus Areas. Colorado Rio Grande Jemez. San Pedro. An NSF Science and Technology Center SAHRA
Focus Areas 1 San Pedro Colorado Rio Grande Jemez Geo-database Structure 2 SGB Schemas Upper Rio Grande Research Data Flux Tower Data Public Data Hydrology Rules, Users and Procedures Jemez River Colorado
RESEARCH METHODOLOGY
III. RESEARCH METHODOLOGY 3.1 Time and Location This research has been conducted in period March until October 2010. Location of research is over Sumatra terrain. Figure 3.1 show the area of interest of
Using the EartH2Observe data portal to analyse drought indicators. Lesson 4: Using Python Notebook to access and process data
Using the EartH2Observe data portal to analyse drought indicators Lesson 4: Using Python Notebook to access and process data Preface In this fourth lesson you will again work with the Water Cycle Integrator
1.0 Implications of using daily climatological wind speed prior to 1948
Supplemental Material 1.0 Implications of using daily climatological wind speed prior to 1948 As detailed in the manuscript, NCEP-NCAR reanalysis wind data were used for the period 1948/01/01-2011/12/31.
The National Operational Hydrologic Remote Sensing Center Operational Snow Analysis
The National Operational Hydrologic Remote Sensing Center Operational Snow Analysis World Meteorological Organization Global Cryosphere Watch Snow-Watch Workshop Session 3: Snow Analysis Products Andrew
Interaction of North American Land Data Assimilation System and National Soil Moisture Network: Soil Products and Beyond
Interaction of North American Land Data Assimilation System and National Soil Moisture Network: Soil Products and Beyond Youlong Xia 1,2, Michael B. Ek 1, Yihua Wu 1,2, Christa Peters-Lidard 3, David M.
The Community Noah LSM with Multi-physics Options
The Community Noah LSM with Multi-physics Options Guo-Yue Niu Collaborators: ZL Yang, KE Mitchell, F Chen, MB Ek, M. Barlage, L. Longuevergne, A Kumar, K Manning, D Niyogi, E Rosero, M Tewari, and Y. Xia
Recent Developments in Climate Information Services at JMA. Koichi Kurihara Climate Prediction Division, Japan Meteorological Agency
Recent Developments in Climate Information Services at JMA Koichi Kurihara Climate Prediction Division, Japan Meteorological Agency 1 Topics 1. Diagnosis of the Northern Hemispheric circulation in December
Impacts of climate change on flooding in the river Meuse
Impacts of climate change on flooding in the river Meuse Martijn Booij University of Twente,, The Netherlands m.j.booij booij@utwente.nlnl 2003 in the Meuse basin Model appropriateness Appropriate model
Simulating Future Climate Change Using A Global Climate Model
Simulating Future Climate Change Using A Global Climate Model Introduction: (EzGCM: Web-based Version) The objective of this abridged EzGCM exercise is for you to become familiar with the steps involved
Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS
Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS Wenli Yang, Pham Long, Peisheng Zhao, Steve Kempler, and Jennifer Wei * NASA Goddard Earth Science Data and Information Services Center
PP COLOBOC. Status Report
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss PP COLOBOC Status Report Jean-Marie Bettems MeteoSwiss COLOBOC/SOILVEG Workshop 01 March 2010, Langen Review
Regional offline land surface simulations over eastern Canada using CLASS. Diana Verseghy Climate Research Division Environment Canada
Regional offline land surface simulations over eastern Canada using CLASS Diana Verseghy Climate Research Division Environment Canada The Canadian Land Surface Scheme (CLASS) Originally developed for the
Enhancing Weather Forecasts via Assimilating SMAP Soil Moisture and NRT GVF
CICS Science Meeting, ESSIC, UMD, 2016 Enhancing Weather Forecasts via Assimilating SMAP Soil Moisture and NRT GVF Li Fang 1,2, Christopher Hain 1,2, Xiwu Zhan 2, Min Huang 1,2 Jifu Yin 1,2, Weizhong Zheng
Global Flood Awareness System GloFAS
Global Flood Awareness System GloFAS Ervin Zsoter with the help of the whole EFAS/GloFAS team Ervin.Zsoter@ecmwf.int 1 Reading, 8-9 May 2018 What is GloFAS? Global-scale ensemble-based flood forecasting
Guide to Hydrologic Information on the Web
NOAA s National Weather Service Guide to Hydrologic Information on the Web Colorado River at Lees Ferry Photo: courtesy Tim Helble Your gateway to web resources provided through NOAA s Advanced Hydrologic
DEVELOPMENT OF A LARGE-SCALE HYDROLOGIC PREDICTION SYSTEM
JP3.18 DEVELOPMENT OF A LARGE-SCALE HYDROLOGIC PREDICTION SYSTEM Ji Chen and John Roads University of California, San Diego, California ABSTRACT The Scripps ECPC (Experimental Climate Prediction Center)
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
Lecture on outline of JMA s interactive tool for analysis of climate system
Lecture on outline of JMA s interactive tool for analysis of climate system November 4, 2008 Ushida Shingo Climate Prediction Division of JMA Introduction To announce advanced information about climate
Practical Session Instructions. Terrestrial Water Storage. Drought Monitoring
Practical Session Instructions Terrestrial Water Storage Drought Monitoring Prof. Bob Su & M.Sc. Lichun Wang ITC, The Netherlands (July 2013) 1 Terrestrial water storage and Drought Monitoring using satellite
MET 3102-U01 PHYSICAL CLIMATOLOGY (ID 17901) Lecture 14
MET 3102-U01 PHYSICAL CLIMATOLOGY (ID 17901) Lecture 14 The hydrologic cycle evaporation vapor transport precipitation precipitation evaporation runoff Evaporation, precipitation, etc. in cm Vapor transported
Water Information Portal User Guide. Updated July 2014
Water Information Portal User Guide Updated July 2014 1. ENTER THE WATER INFORMATION PORTAL Launch the Water Information Portal in your internet browser via http://www.bcogc.ca/public-zone/water-information
Watershed simulation and forecasting system with a GIS-oriented user interface
HydroGIS 96: Application of Geographic Information Systems in Hydrology and Water Resources Management (Proceedings of the Vienna Conference, April 1996). IAHS Publ. no. 235, 1996. 493 Watershed simulation
Land Data Assimilation at NCEP NLDAS Project Overview, ECMWF HEPEX 2004
Dag.Lohmann@noaa.gov, Land Data Assimilation at NCEP NLDAS Project Overview, ECMWF HEPEX 2004 Land Data Assimilation at NCEP: Strategic Lessons Learned from the North American Land Data Assimilation System
Climpact2 and PRECIS
Climpact2 and PRECIS WMO Workshop on Enhancing Climate Indices for Sector-specific Applications in the South Asia region Indian Institute of Tropical Meteorology Pune, India, 3-7 October 2016 David Hein-Griggs
C o p e r n i c u s E m e r g e n c y M a n a g e m e n t S e r v i c e f o r e c a s t i n g f l o o d s
C o p e r n i c u s E m e r g e n c y M a n a g e m e n t S e r v i c e f o r e c a s t i n g f l o o d s Copernicus & Copernicus Services Copernicus EU Copernicus EU Copernicus EU www.copernicus.eu W
6.2 VALIDATION OF THE GSWP2 BASELINE SIMULATION. Kenji Tanaka, Kazuaki Yorozu, Ryo Hamabe, Shuichi Ikebuchi Kyoto University, Japan
6.2 VALIDATION OF THE GSWP2 BASELINE SIMULATION Kenji Tanaka, Kazuaki Yorozu, Ryo Hamabe, Shuichi Ikebuchi Kyoto University, Japan 1. INTRODUCTION Global Soil Wetness Project (GSWP) is open to anyone with
Influence of Model Version, Resolution and Driving Data on High Resolution Regional Climate Simulations with CLM
Influence of Model Version, Resolution and Driving Data on High Resolution Regional Climate Simulations with CLM C. Meißner, G. Schädler, C. Kottmeier Universität / Forschungszentrum Karlsruhe 7.3.27 LM-User-Seminar
CLIMATE MODEL DOWNSCALING: HOW DOES IT WORK AND WHAT DOES IT TELL YOU?
rhgfdjhngngfmhgmghmghjmghfmf CLIMATE MODEL DOWNSCALING: HOW DOES IT WORK AND WHAT DOES IT TELL YOU? YAN FENG, PH.D. Atmospheric and Climate Scientist Environmental Sciences Division Argonne National Laboratory
Drought Monitoring with Hydrological Modelling
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Drought Monitoring with Hydrological Modelling Stefan Niemeyer IES - Institute for Environment and Sustainability Ispra -
CONCURRENT ATMOSPHERE-LAND- OCEAN ANOMALIES Time series: Causal effects and Local Feedbacks
CONCURRENT ATMOSPHERE-LAND- OCEAN ANOMALIES Time series: Removing short-lived transient anomalies and periodic modes Selecting anomalies: Thresholds, duration Local relationships in two-ways and oneway
Michael B. Ek 1, Youlong Xia 1,2, Jesse Meng 1,2, and Jiarui Dong 1,2
Michael B. Ek 1, Youlong Xia 1,2, Jesse Meng 1,2, and Jiarui Dong 1,2 1 Land-Hydrology Team Environmental Modeling Center (EMC) National Centers for Environmental Prediction (NCEP) National Weather Service
THE METEOROLOGICAL DATA QUALITY MANAGEMENT OF THE ROMANIAN NATIONAL SURFACE OBSERVATION NETWORK
THE METEOROLOGICAL DATA QUALITY MANAGEMENT OF THE ROMANIAN NATIONAL SURFACE OBSERVATION NETWORK Ioan Ralita, Ancuta Manea, Doina Banciu National Meteorological Administration, Romania Ionel Dragomirescu
4. GIS Implementation of the TxDOT Hydrology Extensions
4. GIS Implementation of the TxDOT Hydrology Extensions A Geographic Information System (GIS) is a computer-assisted system for the capture, storage, retrieval, analysis and display of spatial data. It
VIC Hydrology Model Training Workshop Part II: Building a model
VIC Hydrology Model Training Workshop Part II: Building a model 11-12 Oct 2011 Centro de Cambio Global Pontificia Universidad Católica de Chile Ed Maurer Civil Engineering Department Santa Clara University
Climate Change or Climate Variability?
Climate Change or Climate Variability? Key Concepts: Greenhouse Gas Climate Climate change Climate variability Climate zones Precipitation Temperature Water cycle Weather WHAT YOU WILL LEARN 1. You will
KEY WORDS: Palmer Meteorological Drought Index, SWAP, Kriging spatial analysis and Digital Map.
PALMER METEOROLOGICAL DROUGHT CLASSIFICATION USING TECHNIQUES OF GEOGRAPHIC INFORMATION SYSTEM IN THAILAND S. Baimoung, W. Waranuchit, S. Prakanrat, P. Amatayakul, N. Sukhanthamat, A. Yuthaphan, A. Pyomjamsri,
StreamStats: Delivering Streamflow Information to the Public. By Kernell Ries
StreamStats: Delivering Streamflow Information to the Public By Kernell Ries U.S. Department of the Interior U.S. Geological Survey MD-DE-DC District 410-238-4317 kries@usgs.gov StreamStats Web Application
Leon Creek Watershed October 17-18, 1998 Rainfall Analysis Examination of USGS Gauge Helotes Creek at Helotes, Texas
Leon Creek Watershed October 17-18, 1998 Rainfall Analysis Examination of USGS Gauge 8181400 Helotes Creek at Helotes, Texas Terrance Jackson MSCE Candidate University of Texas San Antonio Abstract The
METADATA MANAGEMENT TOOL (LIO)
METADATA MANAGEMENT TOOL (LIO) Climate data - High resolution projections Metadata Metadata (XML) Title Climate data - High resolution projections Date Date type Creation Date Date type Abstract Publication
Regional Drought Decision Support System (RDDSS) Project Update and Product Concepts
Regional Drought Decision Support System (RDDSS) Project Update and Product Concepts Part of the Red River Basin Decision Information Network (RRBDIN) NEXT-GEN RRBDIN Decision Support for the Red River
Introduction to Climatology. GEOG/ENST 2331: Lecture 1
Introduction to Climatology GEOG/ENST 2331: Lecture 1 Us! Graham Saunders (RC 2006C) graham.saundersl@lakeheadu.ca! Jason Freeburn (RC 2004) jtfreebu@lakeheadu.ca Graham Saunders! Australian Weather Bureau!
Seasonal Prediction in France : Application to Hydrology
Seasonal Prediction in France : Application to Hydrology CERON J-P, SINGLA S., MARTIN E., ROUSSET-REGIMBEAU F., DEQUE M., HABETS F. and VIDAL J.-P. ECAM 2013 Introduction A first study showed the feasibility
Physical Geography Lab Activity #16
Physical Geography Lab Activity #16 Due date Name California Climate Classification COR Objective 6, SLO 3 16.1. Introduction One of the most important factors in the physical geography of a place is its
An Ensemble Land Surface Modeling and Assimilation Testbed for HEPEX
GSFC s Land Data Assimilation Systems: An Ensemble Land Surface Modeling and Assimilation Testbed for HEPEX Christa Peters-Lidard Lidard,, Paul Houser, Matthew Rodell, Brian Cosgrove NASA Goddard Space
The role of soil moisture in influencing climate and terrestrial ecosystem processes
1of 18 The role of soil moisture in influencing climate and terrestrial ecosystem processes Vivek Arora Canadian Centre for Climate Modelling and Analysis Meteorological Service of Canada Outline 2of 18
Assimilation of satellite derived soil moisture for weather forecasting
Assimilation of satellite derived soil moisture for weather forecasting www.cawcr.gov.au Imtiaz Dharssi and Peter Steinle February 2011 SMOS/SMAP workshop, Monash University Summary In preparation of the
Water cycle changes during the past 50 years over the Tibetan Plateau: review and synthesis
130 Cold Region Hydrology in a Changing Climate (Proceedings of symposium H02 held during IUGG2011 in Melbourne, Australia, July 2011) (IAHS Publ. 346, 2011). Water cycle changes during the past 50 years
Texas Alliance of Groundwater Districts Annual Summit
Texas Alliance of Groundwater Districts Annual Summit Using Remote-Sensed Data to Improve Recharge Estimates August 28, 2018 by Ronald T. Green1, Ph.D., P.G. and Stu Stothoff2, Ph.D., P.G. Earth Science
Soil Moisture Prediction and Assimilation
Soil Moisture Prediction and Assimilation Analysis and Prediction in Agricultural Landscapes Saskatoon, June 19-20, 2007 STEPHANE BELAIR Meteorological Research Division Prediction and Assimilation Atmospheric
Quality Control of the National RAWS Database for FPA Timothy J Brown Beth L Hall
Quality Control of the National RAWS Database for FPA Timothy J Brown Beth L Hall Desert Research Institute Program for Climate, Ecosystem and Fire Applications May 2005 Project Objectives Run coarse QC
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
Summary and concluding remarks
Contents Introduction Experimental design Model domain: CORDEX-East Asia domain Model description: HadGEM3-RA Evaluation results Mean climate Inter-annual variability Climate extreme Summary and concluding
Satellite-Based Precipitation Data Delivery System for Thailand. Infrastructure Development Institute-Japan
Satellite-Based Precipitation Data Delivery System for Thailand Infrastructure Development Institute-Japan 1 About the Satellite-Based Precipitation Data Delivery System The Satellite-Based Precipitation
NASA Web-Based Tools for Water Resources Data Access
National Aeronautics and Space Administration ARSET Applied Remote Sensing Training http://arset.gsfc.nasa.gov @NASAARSET NASA Web-Based Tools for Water Resources Data Access www.nasa.gov Outline Overview
1. Header Land-Atmosphere Predictability Using a Multi-Model Strategy Paul A. Dirmeyer (PI) Zhichang Guo (Co-I) Final Report
1. Header Land-Atmosphere Predictability Using a Multi-Model Strategy Paul A. Dirmeyer (PI) Zhichang Guo (Co-I) Final Report 2. Results and Accomplishments Output from multiple land surface schemes (LSS)
A PARAMETER ESTIMATE FOR THE LAND SURFACE MODEL VIC WITH HORTON AND DUNNE RUNOFF MECHANISM FOR RIVER BASINS IN CHINA
A PARAMETER ESTIMATE FOR THE LAND SURFACE MODEL VIC WITH HORTON AND DUNNE RUNOFF MECHANISM FOR RIVER BASINS IN CHINA ZHENGHUI XIE Institute of Atmospheric Physics, Chinese Academy of Sciences Beijing,
SuperPack North America
SuperPack North America Speedwell SuperPack makes available an unprecedented range of quality historical weather data, and weather data feeds for a single annual fee. SuperPack dramatically simplifies
GMAO Analyses and Forecasts for YOTC
GMAO Analyses and Forecasts for YOTC Michele Rienecker and Max Suarez Arlindo da Silva Global Modeling and Assimilation Office NASA/Goddard Space Flight Center YOTC Implementation Planning Meeting Hawaii,
S e a s o n a l F o r e c a s t i n g f o r t h e E u r o p e a n e n e r g y s e c t o r
S e a s o n a l F o r e c a s t i n g f o r t h e E u r o p e a n e n e r g y s e c t o r C3S European Climatic Energy Mixes (ECEM) Webinar 18 th Oct 2017 Philip Bett, Met Office Hadley Centre S e a s
JMA Contribution to SWFDDP in RAV. (Submitted by Yuki Honda and Masayuki Kyouda, Japan Meteorological Agency) Summary and purpose of document
WORLD METEOROLOGICAL ORGANIZATION COMMISSION FOR BASIC SYSTEMS OPAG on DPFS DPFS/RAV-SWFDDP-RSMT Doc. 7.1(1) (28.X.2010) SEVERE WEATHER FORECASTING AND DISASTER RISK REDUCTION DEMONSTRATION PROJECT (SWFDDP)
Prototyping a Data Sharing System for Flood Forecasting: A Case Study on Sri Lanka
Prototyping a Data Sharing System for Flood Forecasting: A Case Study on Sri Lanka Masaki Yasukawa 1, Eiji Ikoma 1, Toshihiro Nemoto 1, Mohamed Rasmy 2, Morimasa Tsuda 2, Tomoki Ushiyama 2, Katsunori Tamakawa
Data sources for FAO worldmaps of Koeppen climatologies and climatic net primary production
Data sources for FO worldmaps of Koeppen climatologies and climatic net primary production Jürgen Grieser, René Gommes, Stephen Cofield and Michele Bernardi The gromet Group, SDRN FO of the UN, Viale delle
The 2 nd phase of the Global Land-Atmosphere Coupling Experiment. Randal Koster GMAO, NASA/GSFC
The 2 nd phase of the Global Land-Atmosphere Coupling Experiment Randal Koster GMAO, NASA/GSFC randal.d.koster@nasa.gov GLACE-1 was a successful international modeling project that looked at soil moisture
Land Analysis in the NOAA CFS Reanalysis. Michael Ek, Ken Mitchell, Jesse Meng Helin Wei, Rongqian Yang, and George Gayno
Land Analysis in the NOAA CFS Reanalysis Michael Ek, Ken Mitchell, Jesse Meng Helin Wei, Rongqian Yang, and George Gayno 1 Outline CFS Reanalysis execution Land surface model upgrade from OSU to Noah LIS/GLDAS
Climate Information for Managing Risk. Victor Murphy NWS Southern Region Climate Service Program Mgr. June 12, 2008
Climate Information for Managing Risk Victor Murphy Climate Service Program Mgr. June 12, 2008 Currently From Fort Worth, TX but climate challenges abound everywhere as does the need to mitigate impacts
The Texas drought. Kingtse Mo Climate Prediction Center NWS/NCEP/NOAA
The 2011-2012 Texas drought Kingtse Mo Climate Prediction Center NWS/NCEP/NOAA 1 outline Evolution of the 2011-2012 Texas drought Climatology and historical perspective The 2011 drought Onset Feedback
GeoWEPP Tutorial Appendix
GeoWEPP Tutorial Appendix Chris S. Renschler University at Buffalo - The State University of New York Department of Geography, 116 Wilkeson Quad Buffalo, New York 14261, USA Prepared for use at the WEPP/GeoWEPP
An Arctic Perspective NCEI's Prototype Arctic Data Viewer
An Arctic Perspective NCEI's Prototype Arctic Data Viewer NCEI Arctic Action Team Kate Rose NOAA National Environmental Satellite, Data, and Information Service National Centers for Environmental Information
Finnish Open Data Portal for Meteorological Data
18.11.2013 1 Finnish Open Data Portal for Meteorological Data 14th Workshop on meteorological operational systems Roope Tervo Finnish Meteorological Institute Example of Data Sets -- Observations Data
GE G Climate Science Lab
GE G Climate Science Lab North American Soil Moisture Database: Development and Applications Steven M. Quiring Texas A&M University Trenton Ford Texas A&M University http://climatology.tamu.edu http://facebook.com/geogcsl
Name the surface winds that blow between 0 and 30. GEO 101, February 25, 2014 Monsoon Global circulation aloft El Niño Atmospheric water
GEO 101, February 25, 2014 Monsoon Global circulation aloft El Niño Atmospheric water Name the surface winds that blow between 0 and 30 What is the atmospheric pressure at 0? What is the atmospheric pressure
Climate Prediction Center National Centers for Environmental Prediction
NOAA s Climate Prediction Center Climate Monitoring Tool Wassila M. Thiaw and CPC International Team Climate Prediction Center National Centers for Environmental Prediction CPC International Team Vadlamani
Environment and Climate Change Canada / GPC Montreal
Environment and Climate Change Canada / GPC Montreal Assessment, research and development Bill Merryfield Canadian Centre for Climate Modelling and Analysis (CCCma) with contributions from colleagues at
Investigating Weather with Google Earth Student Guide
Investigating Weather with Google Earth Student Guide In this activity, you will use Google Earth to explore some factors that affect weather. You will: 1. Determine how different factors affect a location
Status report on the Great Lakes Runoff Inter-comparison Project for Lake Erie (GRIP-E)
Status report on the Great Lakes Runoff Inter-comparison Project for Lake Erie (GRIP-E) Juliane Mai, Bryan A. Tolson, Hongren Shen, E tienne Gaborit, Nicolas Gasset, Vincent Fortin, Maria Abrahamowicz,
Watershed Application of WEPP and Geospatial Interfaces. Dennis C. Flanagan
Watershed Application of WEPP and Geospatial Interfaces Dennis C. Flanagan Research Agricultural Engineer USDA-Agricultural Research Service Adjunct Professor Purdue Univ., Dept. of Agric. & Biol. Eng.
Drought and Climate Extremes Indices for the North American Drought Monitor and North America Climate Extremes Monitoring System. Richard R. Heim Jr.
Drought and Climate Extremes Indices for the North American Drought Monitor and North America Climate Extremes Monitoring System Richard R. Heim Jr. NOAA/NESDIS/National Climatic Data Center Asheville,
5. General Circulation Models
5. General Circulation Models I. 3-D Climate Models (General Circulation Models) To include the full three-dimensional aspect of climate, including the calculation of the dynamical transports, requires
Report. Northern Africa. RAIDEG-8, 1-2 Nov 2017
Report Northern Africa RAIDEG-8, 1-2 Nov 2017 Report Northern Africa RAIDEG-8, 1-2 Nov 2017 Important Note: Formal letters have been sent from the PR of Morocco with WMO to PRs of Algeria, Tunisia, Libya
Arctic System Reanalysis *
Arctic System Reanalysis * David H. Bromwich 1,2, Keith M. Hines 1 and Le-Sheng Bai 1 1 Polar Meteorology Group, Byrd Polar Research Center 2 Atmospheric Sciences Program, Dept. of Geography The Ohio State
The next generation in weather radar software.
The next generation in weather radar software. PUBLISHED BY Vaisala Oyj Phone (int.): +358 9 8949 1 P.O. Box 26 Fax: +358 9 8949 2227 FI-00421 Helsinki Finland Try IRIS Focus at iris.vaisala.com. Vaisala
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)
A Near Real Time Drought Monitoring Capability
A Near Real Time Drought Monitoring Capability Kingtse Mo, Muthuvel Chelliah, Wayne Higgins and The NCEP Drought Monitoring Team Climate Prediction Center NCEP/NWS/NOAA An Experimental Drought Early Warning
Hydro-Meteorological Simulations for the Poyang Lake Region using WRF and HMS
Hydro-Meteorological Simulations for the Poyang Lake Region using WRF and HMS, Benjamin Fersch, Harald Kunstmann KIT University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz
Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean-
Tokyo, 14 November 2016, TCC Training Seminar Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean- Yasushi MOCHIZUKI Tokyo Climate Center Japan Meteorological
Land Surface Processes and Their Impact in Weather Forecasting
Land Surface Processes and Their Impact in Weather Forecasting Andrea Hahmann NCAR/RAL with thanks to P. Dirmeyer (COLA) and R. Koster (NASA/GSFC) Forecasters Conference Summer 2005 Andrea Hahmann ATEC
Climate Variability in South Asia
Climate Variability in South Asia V. Niranjan, M. Dinesh Kumar, and Nitin Bassi Institute for Resource Analysis and Policy Contents Introduction Rainfall variability in South Asia Temporal variability
ERA-5 driven land surface reanalysis : LDAS-Monde applied to the Continental US
ERA-5 driven land surface reanalysis : LDAS-Monde applied to the Continental US Clement Albergel 1, Emanuel Dutra 2, Simon Munier 1, Jean-Christophe Calvet 1, Joaquin Munoz-Sabater 3, Patricia de Rosnay
Precipitation: Evapotranspiration: S i o l il M o t s ure: Groundwater: Streamflow: Vegetation:
Satellite and Ground-based Approaches for Monitoring Impacts of Agriculture on Ground Resources Bridget R. Scanlon, Laurent Longuevergne, Guillaume Favreau*, Claudia Faunt** Center for Sustainable Water
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
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
Climate Change Service
Service Metadata for the Data Store Dick Dee, ECMWF C3S: data + expertise + operational Open and free access to climate data (observations, reanalyses, model predictions) Tools and best scientific practices
Speedwell High Resolution WRF Forecasts. Application
Speedwell High Resolution WRF Forecasts Speedwell weather are providers of high quality weather data and forecasts for many markets. Historically we have provided forecasts which use a statistical bias
Near-surface observations for coupled atmosphere-ocean reanalysis
Near-surface observations for coupled atmosphere-ocean reanalysis Patrick Laloyaux Acknowledgement: Clément Albergel, Magdalena Balmaseda, Gianpaolo Balsamo, Dick Dee, Paul Poli, Patricia de Rosnay, Adrian
an accessible interface to marine environmental data Russell Moffitt
an accessible interface to marine environmental data Russell Moffitt The Atlas Project GOAL: To provide a single point of access to oceanographic and environmental data for use by marine resource researchers,