We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byAleah Adee
Modified over 2 years ago
© Crown copyright Met Office E-AMDAR evaluation. Mark Smees & Tim Oakley, Met Office, May 2008
© Crown copyright Met Office Contents This presentation covers the following areas Introduction Data processing procedure Example of a Good and Bad comparison Statistical results Comments and Observations Questions and answers
© Crown copyright Met Office Next Generation Upper-Air Network Large-scale project to produce costed options for the future (2010 – 2020) Benefits Optimize current network. Meet User Requirements. (i.e. High resolution) Reduce costs. FUND – Future Upper-air Network Development
© Crown copyright Met Office Introduction The purpose of this study was to use data from operational radiosonde ascents to examine whether radiosonde data would provide a good comparison for AMDAR data.
© Crown copyright Met Office Data processing procedure AMDAR units EU4593, EU5331, and EU6564 were used as these were capable of recording humidity. Radiosonde ascents from UK and German stations were selected. All the radiosonde stations selected flew Vaisala RS92 radiosondes.
© Crown copyright Met Office Data processing procedure Radiosonde ascents were selected from stations that were closely located to airports where aircraft fitted with AMDAR units operate, and radiosonde ascents chosen that were within an hour of take off or landing. The Radiosonde data was retrieved from the University of Wyoming web site at The raw temp message was used to identify the type of radiosonde and the time of launch, and the text data containing selected points, was opened in an excel spreadsheet and saved as a comma separated file to enable it to be used by the RSKOMP radiosonde comparison software.
© Crown copyright Met Office Data processing procedure AMDAR data was retrieved in text format, from the Met Office database. The data used was the altitude, temperature, converted from Kelvin to Centigrade, and the Mixing ratio, converted to grams per kilogram (g/kg). Once converted the data was saved as a comma separated file, to enable it to be used by the RSKOMP radiosonde comparison software.
© Crown copyright Met Office Data processing procedure During the comparison period, June 2007 to March 2008, 49 Comparisons were made, of which 34 where within the one hour period. Of these 34 comparisons 2 were rejected, as their profiles were suspect, the remaining 32 comparisons have been used in the statistics. 14 comparisons with EU comparisons with EU comparisons with EU4593 We suspect that EU4593 had the humidity function removed during the comparison period.
© Crown copyright Met Office GOOD AND BAD examples The following 4 slides show examples of good and bad matches. The Radiosonde is the blue trace and the AMDAR is the red trace. Temperature is on the left, and Mixing ratio on the right. The Y axis is height from 0 to 11km, the temperature is in degrees Celsius, and the mixing ratio in grams per kilogram (g/kg).
© Crown copyright Met Office Good Comparison (24) The following slide shows the Temperature and Mixing Ratio (g/kg) plot for comparison 24. AMDAR Unit EU6564, take off from Munich 10:42 3 rd Feb RS92 radiosonde from Muenchen- Oberschleissheim (10868) 10:45 3 rd Feb Sonde station and airport are approximately 18km apart.
© Crown copyright Met Office Comparison 24
© Crown copyright Met Office Bad Comparison (4) The following slide shows the Temperature and Mixing Ratio (g/kg) plot for comparison 4. AMDAR Unit EU6564, landing at Manchester 11:49 22 nd August RS92 radiosonde from Watnall (03354) 11:15 22 nd August Sonde station and airport are approximately 78km apart. This comparison has been removed from the statistics.
© Crown copyright Met Office Comparison 4
© Crown copyright Met Office Mixing Ratio Statistical analysis The following 3 slides show the Mixing Ratio statistics. The statistics produced show the flight-by-flight differences (left plot) and the flight-by-flight standard deviations (right plot) as a function of height, with the humidity expressed as a mixing ratio in grams per kilogram (g/kg). Direct differences are the results of taking all the samples in a given category [each 100m in the vertical] and computing the average value for the difference and the standard deviation. In flight by flight differences, differences for a given collocation (comparison) are averaged for a given category and then the individual averages are combined to estimate the overall average and the flight by flight standard deviation. In the following mixing ratio statistics graphs, the radiosonde (link reference) mixing ratio is the blue line, and the AMDAR mixing ratio is the red line. The Y axis is height from 0 to 11km, and the red and blue numbers on the graph are the corresponding sample sizes.
© Crown copyright Met Office Mixing Ratio statistics for all 32 comparisons
© Crown copyright Met Office Mixing Ratio statistics for EU5331
© Crown copyright Met Office Mixing Ratio statistics for EU6564
© Crown copyright Met Office Temperature Statistical analysis The following 3 slides show the Temperature statistics. The statistics produced show the flight-by-flight differences (left plot) and the flight-by-flight standard deviations (right plot) as a function of height, with the temperature in degrees Celsius. Direct differences are the results of taking all the samples in a given category [each 100m in the vertical] and computing the average value for the difference and the standard deviation. In flight by flight differences, differences for a given collocation (comparison) are averaged for a given category and then the individual averages are combined to estimate the overall average and the flight by flight standard deviation. In the following temperature statistics graphs, the radiosonde (link reference) temperature is the blue line, and the AMDAR temperature is the red line. The Y axis is height from 0 to 11km, and the red and blue numbers on the graph are the corresponding sample sizes.
© Crown copyright Met Office Temperature statistics for all 32 comparisons
© Crown copyright Met Office Temperature statistics for EU5331
© Crown copyright Met Office Temperature statistics EU6564
© Crown copyright Met Office Comments and Observations We were limited to aircraft flights that took off or landed at the launch times for radiosondes. Humidity measurements vary rapidly in space and time, even when the basic vertical structure is not changing rapidly. Unlike temperature it is unwise to interpolate over relatively large distances, therefore precise validation of humidity would require radiosondes launched close to an airport as near as possible to landing or take off time. It would be better if we could use high resolution radiosonde data, e.g. BUFR or 2 second ASCII data. Also it would be advantages to increase the AMDAR resolution during ascent and decent. Of the 49 AMDAR reports 9 had their altitude at landing or take off below zero. This was not restricted to one AMDAR unit, or individual airport. I had to apply height offsets to some of the profiles to get them to match, for this I used distinct turning points, such as inversions.
© Crown copyright Met Office Comments and Observations We suspect that EU4593 had the humidity function removed during the comparison period. (It has subsequently been confirmed that this sensor had to be replaced.) No account was taken of the weather at the time of comparison. The number of samples at higher altitude is limited. Not all radiosonde stations are located close to an airport. Most of the comparisons were during daylight. There was no separate comparison between day and night. There are small variations between day and night radiosonde readings.
© Crown copyright Met Office Future Work Increase data samples, concentrating on flights into Munich airport. Work with E-AMDAR team to access GPS heights and increase the vertical resolution of data near the surface. Proposal to E-AMDAR to produce statistics on a more formal agreement. Discuss this work within the CIMO ET on Intercomparisons.
© Crown copyright Met Office Questions & answers
Page 1© Crown copyright 2004 Initial results from Tropospheric Airborne Meteorological Data Reporting (TAMDAR) evaluation Dr J. Nash and M. Smees.
© Crown copyright Met Office Future Upper-Air Network Development (FUND)-Integration TECO 2008 St Petersburg Russia Catherine Gaffard, John Nash, Alec.
© Crown copyright Met Office Future Upper-Air Network Development (FUND) WMO ET-UASI, Payerne June 2008, Agenda Item 3.4.
Station lists and bias corrections Jemma Davie, Colin Parrett, Richard Renshaw, Peter Jermey © Crown Copyright 2012 Source: Met Office© Crown copyright.
Page 1© Crown copyright 2004 The Challenges for an operational wind profiler. Remote and unattended Tim Oakley TECO-05 Bucharest, 4 th -7 th May 2005.
Page 1© Crown copyright 2004 Introduction to upper air measurements with radiosondes and other in situ observing systems  John Nash, C. Gaffard,R. Smout.
MMS - Ozonesonde Wind and Temperature Comparison during CR-AVE T.P. Bui, J. Dean-Day, C. Chang, R. Castaneda NASA-Ames Research Center H. Voemel University.
The University of Reading Helen Dacre AGU Dec 2008 Boundary Layer Ventilation by Convection and Coastal Processes Helen Dacre, Sue Gray, Stephen Belcher.
Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS.
Acknowledgments Jennifer Fowler, University of Montana, Flight Director UM-BOREALIS Roger DesJardins, Canadian East Fire Region, Incident Meteorologist.
Page 1© Crown copyright 2005 Voluntary Cooperation Work Richard Smout, John Nash, Jeremy Gillham, Mark Smees and Steve Palmer.
Provision of AMDAR Data for the Region David R. Helms Office of Science and Technology NOAA National Weather Service AMDAR Regional Workshop Mexico City,
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss TECO-2006, WMO, Geneva, Global Criteria for.
Page 1© Crown copyright 2004 Results of the RS92 Acceptance Test performed by the Met Office (UK) Richard Smout, John Nash, Mark Smees, Darren Lyth, May.
© Crown copyright Met Office Operational OpenRoad verification Presented by Robert Coulson.
WEB OF KNOWLEDGE 5.2
AREP GURME 1 Section 10 Exercise Exercise Interpreting Radiosondes Mixing height calculator Using HYSPLIT Flowchart of good/poor air quality.
Ozone time series and trends Various groups compute trends in different ways. One goal of the workshop is to be able to compare time series and trends.
00/XXXX1 Upper Air Network UK National Report. Tim Oakley & John Nash Met Office, Exeter, UK CIMO ET on Upgrading the Global Radiosonde Network – Geneva.
Analysis of Select Data Biases in North America Dr. Bradley Ballish NCEP/NCO/PMB October 2008 JAG/ODAA Meeting “Where America’s Climate and Weather Services.
Intro Energy. Explain that physical and chemical changes in matter involve transfers of energy. Apply the law of conservation of energy to analyze changes.
National Center for Health Statistics Data Online Query System Overview
Abstract has 6 upper air stations for GPS S SR2K2 Modemwith Radiosonde M2K2_DC, 6 Upper Air stations of RDF Radiotidolite RT20A ( Vaisala ) and three Upper.
COSMIC GPS Radio Occultation Temperature Profiles in Clouds L. LIN AND X. ZOU The Florida State University, Tallahassee, Florida R. ANTHES University Corporation.
Leah Kos Sara Lavas Lauryn Gonzalez Mentor: Dr. Michael Douglas, NSSL.
Page 1© Crown copyright 2005 Met Office Verification -status Clive Wilson, Presented by Mike Bush at EWGLAM Meeting October 8- 11, 2007.
Validating the moisture predictions of AMPS at McMurdo using ground- based GPS measurements of precipitable water Julien P. Nicolas 1, David H. Bromwich.
Ewan OConnor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat Radar/lidar observations of boundary layer clouds.
MnSGC Ballooning Team Techniques: APRS tracking-data processing James Flaten Summer 2010.
© Paradigm Publishing, Inc Excel 2013 Level 2 Unit 2Managing and Integrating Data and the Excel Environment Chapter 8Importing, Exporting, and Distributing.
Part 6. Altimetry TOPICS ISA and the Aircraft Altimeter Height, Pressure, and the Aircraft Altimeter Temperature and the Aircraft Altimeter Altimeter.
On average TES exhibits a small positive bias in the middle and lower troposphere of less than 15% and a larger negative bias of up to 30% in the upper.
World Meteorological OrganizationIntergovernmental Oceanographic Commission of UNESCO Ship Observations Team ~ integrating and coordinating international.
Sections 1.3 & 1.4. Why is scientific notation useful? Using Scientific Notation Scientists often work with very large or very small numbers. Astronomers.
© Paradigm Publishing, Inc Excel 2013 Level 2 Unit 2Managing and Integrating Data and the Excel Environment Chapter 6Protecting and Sharing Workbooks.
U.S. and foreign air carriers operating passenger flights in, to, or from the U.S. with at least one aircraft with an original passenger capacity of 30.
Comparison of Radiosonde and Profiler Data with ACARS Data for Describing the Great Plains Low-Level Jet Ross W. Bradshaw Meteorology Program, Dept. of.
© Crown copyright Met Office An update on plans for CAVIAR field campaigns Stuart Newman NPL, 2 June 2008.
WRF Four-Dimensional Data Assimilation (FDDA) Jimy Dudhia.
1 Recent AMDAR (MDCRS/ACARS) Activities at GSD New AMDAR-RUC database that helps evaluate AMDAR data quality Optimization study that suggests data can.
Introduction Lesson 1 Microsoft Office 2010 and the Internet Microsoft Office 2010 Advanced Cable / Morrison 1.
© Crown copyright Met Office DIAMET & Met Office Kevin Linklater – Upper Air & Remote Sensing Networks Team Leader, Reading 9 th June 2011.
TAMDAR AERIBAGO Validation Experiment (TAVE) - Memphis Wayne Feltz, Erik Olson, John Short, Sarah Bedka, Kristopher Bedka, Tim Wagner, and Scott Cultice.
Running a model's adjoint to obtain derivatives, while more efficient and accurate than other methods, such as the finite difference method, is a computationally.
Page 1© Crown copyright 2004 Development of a Ground Based GPS Network for the Near Real Time Measurement of Integrated Water Vapour (IWV) Jonathan Jones.
SRL/Reference sonde P. Di Girolamo, D. Whiteman, B. Demoz, J. Wang, K. Beierle, T. Weckwerth The Reference sonde (C34) consists of a Snow White (SW) chilled-mirror.
Matthew Lagor Remote Sensing Stability Indices and Derived Product Imagery from the GOES Sounder
Course Registration Overrides SLCM_WP_220 1SLCM_WP_220 Overrides.
Page 1© Crown copyright 2004 Introduction to upper air measurements with radiosondes and other in situ observing systems John Nash, C. Gaffard,R. Smout.
© 2017 SlidePlayer.com Inc. All rights reserved.