Presentation is loading. Please wait.

Presentation is loading. Please wait.

MADIS to LITTLE_R Converter MADIS observation types MADIS to LITTE_R converter Future work.

Published byDrusilla Page Modified over 8 years ago

Similar presentations

Presentation on theme: "MADIS to LITTLE_R Converter MADIS observation types MADIS to LITTE_R converter Future work."— Presentation transcript:

1 MADIS to LITTLE_R Converter MADIS observation types MADIS to LITTE_R converter Future work

2 MADIS Observation Types MADIS provides ingest, integration, automated quality control (QC), and distribution support for both NOAA and non-NOAA observations. Observations currently supported by MADIS include: * Meteorological Aviation Reports (METARs) * Surface Aviation Observations (SAOs) * * Surface maritime reports (including Buoy, Ship, and Coastal-Marine Automated Network [C- MAN]) * Modernized NWS Cooperative Observer (COOP-M) Program * * Surface mesonet * Radiosondes * NOAA Profiler Network (NPN) * Cooperating Agency Profiler (CAP) * * Automated aircraft reports and profiles (including MDCRS, ACARS *, AMDAR *, and TAMDAR * observations) * Microwave Radiometers * * GOES 3-h operational winds * GOES 1-h experimental winds *

3 MADIS Observation Types MADIS Meteorological Surface Dataset Provider Most national-scale networks in North America that report surface conditions( temperature, relative humidity, wind, precipitation, etc.) are included. Mesonet stations come from local, state, and federal agencies, and private firms. Geographic Coverage Coverage is densest over North and Central America, plus Hawaii. Global datasets include maritime and METAR, along with some mesonets (APRSWXNET, PCDINPE). Start Date of Data (real time and archived data) METAR, Maritime, Integrated MesonetJuly 1, 2001 Modernized NWS Cooperative ObserverMay 4, 2004 UrbaNetDecember 1, 2006

4 MADIS Observation Types MADIS Hydrological Surface Dataset Provider The MADIS hydrological surface dataset includes reports from observing networks run by different "providers". It report various hydrological variables such as accumulated precipitation and river levels, etc. Geographic Coverage The geographic coverage for automated networks and for the CoCoRaHS mesonet includes data from these states: CO, IN, KS, MO, NM, PA, TX, VA, WY. The GLOBE mesonet has global data. Start Date of Data (real time and archived data) Hydrological SurfaceJuly 1, 2001

5 MADIS Observation Types MADIS Radiosonde Dataset Provider Data comes from all stations in North America and many other stations around the globe. The average continental U.S. station separation is currently 315 km, and two observations are scheduled daily (valid at 0000 and 1200 UTC). Geographic Coverage The geographic coverage is global. Start Date of Data (real time and archived data) RadiosondeJuly 1, 2001

6 MADIS Observation Types MADIS NOAA Profiler Network Dataset Provider The MADIS profiler dataset consists of hourly winds from the NOAA Profiler Network, a quasi-operational network of wind profilers located in the Central United States and Alaska. Geographic Coverage The NOAA Profiler Network is primarily in the central United States, with 3 additional stations in Alaska. Start Date of Data (real time and archived data) NOAA Profiler NetworkJuly 1, 2001

7 MADIS Observation Types MADIS Automated Aircraft Dataset Provider The MADIS automated aircraft dataset provides data obtained from many U.S. airlines reporting through ACARS. ACARS is a superset of the Meteorological Data Collection and Reporting System (MDCRS) data. it also includes Aircraft Meteorological Data Reporting (AMDAR) data from many European and Asian carriers, and Tropospheric Airborne Meteorological Data Reporting (AMDAR) data. Geographic Coverage Approximately 140,000 wind and temperature observations are available per day, 100,000 of which are over the continental United States. These data come from more than 4000 aircraft. There are more data during the day time than at night. Start Date of Data (real time and archived data) Automated Aircraft ReportsJuly 1, 2001

8 MADIS Observation Types MADIS Multi-Agency Profiler Dataset Provider The MADIS Multi-Agency Profiler (MAP) dataset consists of data from a variety of observing systems, which are collected from many different "providers" and integrated into a single dataset. The observing systems produce vertical profiles of wind and virtual temperature. Geographic Coverage Most of the MAP stations are located in the United States and Canada, and a large network of stations are available from Japan. Start Date of Data (real time and archived data) Multi-Agency ProfilerJune 1, 2002

9 MADIS Observation Types MADIS Satellite Wind Dataset Provider The MADIS satellite wind dataset consists of multiple wind products from different "providers". Currently, these products consist of data from the GOES satellites, including the 3-hour winds that are produced on an operational basis, as well as the rapid scan experimental winds that are produced hourly. Geographic Coverage GOES-12 provides coverage over the Eastern U.S., Central and South America, and the Atlantic Ocean. GOES-11 provides coverage over the Western U.S. and the Pacific Ocean. Start Date of Data (real time and archived data) Satellite WindNovember 4, 2003

10 MADIS Observation Types Other MADIS Dataset Start Date of Data (real time and archived data) High Frequency METARFebruary 24, 2009 RadiometerJuly 8, 2003 Satellite SoundingJune 9, 2005 Satellite RadianceNovember 1, 2005 SnowNovember 18, 2005 WISDOMAugust 8, 2008 For detailed info, go to http://madis.noaa.gov/madis_datasets.html

11 Converter This converter includes two parts: Reading MADIS data Refer da_setup_obs_structures_madis subroutine to read obs from MADIS database. Writing to LITTLE_R Refer module_output.F (Yun-Rong) to write different obs type to LITTLE_R.

12 Converter Converted and tested MADIS obs types METAR, Canadian SAO’s, ACARS, SATWND, Marine, radiosonde Sample data METAR, ACARS, marine, radiosonde: 20070423_00, 20070423_06, 20070423_12 SATWND: 20070101_22

13 Future work It is possile to convert other MADIS obs to little_r NWS cooperative observer, UrbaNet mesonets, buoys, C-MAN (Coastal Marine Automated Network) station, NPN (NOAA Profiler Network) winds, MAP (Multi-Agency Profiler) winds, GPSMET integrated precipitable water.

14 if(use_metarobs)then CALL MINIT('SFC',madis_metar_db,.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('ALL-SFC',.false.,istatus) if(istatus /= success_p)stop ! Select all of the surface datasets other than maritime. CALL MSETSFCPVDR('ALL-MTR',.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('SAO',.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('ALL-MESO',.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('COOP',.true.,istatus) if(istatus /= success_p)stop

15 if(use_shipsobs)then CALL MINIT('SFC',madis_ships_db,.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('ALL-SFC',.false.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('MARITIME',.true.,istatus) if(istatus /= success_p)stop if(use_gpspwobs)then CALL MINIT('SFC',madis_gpspw_db,.true.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('ALL-SFC',.false.,istatus) if(istatus /= success_p)stop CALL MSETSFCPVDR('GPSMET',.true.,istatus) if(istatus /= success_p)sto

16 if(use_soundobs)then CALL MINIT('RAOB',madis_sound_db,.true.,istatus) if(istatus /= success_p)stop if(use_airepobs)then CALL MINIT('ACARS',madis_airep_db,.true.,istatus) if(istatus /= success_p)stop if(use_geoamvobs)then CALL MINIT('SATWND',madis_geoamv_db,.true.,istatus) if(istatus /= success_p)stop

Download ppt "MADIS to LITTLE_R Converter MADIS observation types MADIS to LITTE_R converter Future work."

Similar presentations

Objective: To bring together those involved in the activities of water management in Latin America with the Earth observation data providers, in order.

Objective: To bring together those involved in the activities of water management in Latin America with the Earth observation data providers, in order.
ECMWF MetTraining Course- Data Assimilation and use of satellite data (3 May 2005) The Global Observing System Overview of data sources Data coverage Data.

ECMWF MetTraining Course- Data Assimilation and use of satellite data (3 May 2005) The Global Observing System Overview of data sources Data coverage Data.
6/12/20141 NoN Recommendations: Measurements and Infrastructure Meteorological Assimilation Data Ingest System (MADIS) –Update Current Services and Capabilities.

6/12/20141 NoN Recommendations: Measurements and Infrastructure Meteorological Assimilation Data Ingest System (MADIS) –Update Current Services and Capabilities.
Operational Wind Observations and Forecasts Andrew Stern, NOAA/NWS Local Forecast and Warnings Program Manager Silver Spring, MD

Operational Wind Observations and Forecasts Andrew Stern, NOAA/NWS Local Forecast and Warnings Program Manager Silver Spring, MD
CalWater2 Gulfstream-IV Measurements Janet Intrieri NOAA/Earth System Research Laboratory April 23, 2014.

CalWater2 Gulfstream-IV Measurements Janet Intrieri NOAA/Earth System Research Laboratory April 23, 2014.
Report from the GCOS Archive/Analysis Center Matthew Menne NOAA/National Centers for Environmental Information Center for Weather and Climate (NCEI-Asheville)

Report from the GCOS Archive/Analysis Center Matthew Menne NOAA/National Centers for Environmental Information Center for Weather and Climate (NCEI-Asheville)
Atmospheric Sciences 370 Observing Systems January 2007.

Atmospheric Sciences 370 Observing Systems January 2007.
NWS Needs and Requirements Related to Observations on Reservation Lands George Howard and Mike Staudenmaier National Weather Service - Flagstaff.

NWS Needs and Requirements Related to Observations on Reservation Lands George Howard and Mike Staudenmaier National Weather Service - Flagstaff.
Global Forecast System (GFS) Model Previous called the Aviation (AVN) and Medium Range Forecast (MRF) models. Global model and 64 levels Relatively primitive.

Global Forecast System (GFS) Model Previous called the Aviation (AVN) and Medium Range Forecast (MRF) models. Global model and 64 levels Relatively primitive.
National Oceanic and Atmospheric Administration

National Oceanic and Atmospheric Administration
Adrian Simmons Lead author, Status Report for the Global Climate Observing System Consultant, European Centre for Medium-Range Weather Forecasts Surface.

Adrian Simmons Lead author, Status Report for the Global Climate Observing System Consultant, European Centre for Medium-Range Weather Forecasts Surface.
Dr Mark Cresswell Model Assimilation 69EG6517 – Impacts & Models of Climate Change.

Dr Mark Cresswell Model Assimilation 69EG6517 – Impacts & Models of Climate Change.
1 Aircraft Data: Geographic Distribution, Acquisition, Quality Control, and Availability Work at NOAA/ESRL/GSD and elsewhere.

1 Aircraft Data: Geographic Distribution, Acquisition, Quality Control, and Availability Work at NOAA/ESRL/GSD and elsewhere.
MADIS – The Meteorological Assimilation Data Ingest System Current Operational Status and Future Plans Greg Pratt, Leon Benjamin, Thomas Kent, Gopa Padmanabhan,

MADIS – The Meteorological Assimilation Data Ingest System Current Operational Status and Future Plans Greg Pratt, Leon Benjamin, Thomas Kent, Gopa Padmanabhan,
JCOMM Data Buoy Cooperation Panel October 16, 2006 National Data Buoy Center 2006 Review: A Year of Growth Paul F. Moersdorf, PhD, Director.

JCOMM Data Buoy Cooperation Panel October 16, 2006 National Data Buoy Center 2006 Review: A Year of Growth Paul F. Moersdorf, PhD, Director.
Impact study with observations assimilated over North America and the North Pacific Ocean at MSC Stéphane Laroche and Réal Sarrazin Environment Canada.

Impact study with observations assimilated over North America and the North Pacific Ocean at MSC Stéphane Laroche and Réal Sarrazin Environment Canada.
AMDAR Global Status, Benefits and Development Plans* WMO CBS ET Aircraft Based Observations Bryce Ford * Adapted from Presentation at WMO Congress XVII,

AMDAR Global Status, Benefits and Development Plans* WMO CBS ET Aircraft Based Observations Bryce Ford * Adapted from Presentation at WMO Congress XVII,
Leah Kos Sara Lavas Lauryn Gonzalez Mentor: Dr. Michael Douglas, NSSL.

Leah Kos Sara Lavas Lauryn Gonzalez Mentor: Dr. Michael Douglas, NSSL.
A Comparison of the Northern American Regional Reanalysis (NARR) to an Ensemble of Analyses Including CFSR Wesley Ebisuzaki 1, Fedor Mesinger 2, Li Zhang.

A Comparison of the Northern American Regional Reanalysis (NARR) to an Ensemble of Analyses Including CFSR Wesley Ebisuzaki 1, Fedor Mesinger 2, Li Zhang.
GOES Data Collection System (DCS) in the GOES R Era William E. Brockman Short & Associates, Inc.

GOES Data Collection System (DCS) in the GOES R Era William E. Brockman Short & Associates, Inc.

Similar presentations

Ads by Google