Monitoring for conventional observation systems at ECMWF



Similar documents
WMO Climate Database Management System Evaluation Criteria

Primary author: Laursen, Ellen Vaarby (DMI - Danish Meteorological Institute, Data and Climate Division), evl@dmi.dk

Current posture analysis is nothing without providing bilateral feedback aiming towards improving performance through appropriate remedial actions:

Mode-S Enhanced Surveillance derived observations from multiple Air Traffic Control Radars and the impact in hourly HIRLAM

Tropical Cyclogenesis Monitoring at RSMC Tokyo Mikio, Ueno Forecaster, Tokyo Typhoon Center Japan Meteorological Agency (JMA)

CLIDATA In Ostrava 18/06/2013

Using Application Response to Monitor Microsoft Outlook

Catastrophe Bond Risk Modelling

ANALYSIS OF DATA EXCHANGE PROBLEMS IN GLOBAL ATMOSPHERIC AND HYDROLOGICAL NETWORKS SUMMARY REPORT 1. June 2004

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

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

Big Data at ECMWF Providing access to multi-petabyte datasets Past, present and future

Improved Meteorological Measurements from Merchant Ships. Peter K. Taylor and Elizabeth C. Kent Southampton Oceanography Centre, UK

Primary author: van den Besselaar, Else (KNMI - Royal Netherlands Meteorological Institue, Climate Services), besselaar@knmi.nl


Real-time observation monitoring and analysis network

The impact of window size on AMV

Introduction to the forecasting world Jukka Julkunen FMI, Aviation and military WS

Near Real Time Blended Surface Winds

A.1 Sensor Calibration Considerations

DATA MANAGEMENT (DM) - (e.g. codes, monitoring) software offered to WMO Members for exchange

High-resolution Regional Reanalyses for Europe and Germany

Synoptic assessment of AMV errors

Basic Climatological Station Metadata Current status. Metadata compiled: 30 JAN Synoptic Network, Reference Climate Stations

COSMO Data Assimilation. Applications for Romanian Territory

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

Real-time Ocean Forecasting Needs at NCEP National Weather Service

DEVELOPMENT OF TRAINING PROGRAMME FOR TECHNICAL STAFF PROVIDING METEOROLOGICAL SERVICES FOR AIR NAVIGATION

How we do it!: Managing Client Assets Using Autotask Configuration Management

Towards an NWP-testbed

Microwave observations in the presence of cloud and precipitation

Observation Metadata and its Use in the DWD Weather Data Request Broker

Data Management in support of Climate MeteoSwiss

Design and Deployment of Specialized Visualizations for Weather-Sensitive Electric Distribution Operations

Eastern Caribbean Open-Source Geospatial Data Sharing and Management Workshop

Primary author: Kaspar, Frank (DWD - Deutscher Wetterdienst), Frank.Kaspar@dwd.de

Active Fire Monitoring: Product Guide

Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect

JASPERS Networking Platform

Guidelines on Quality Control Procedures for Data from Automatic Weather Stations

Nowcasting: analysis and up to 6 hours forecast

Options for filling the LEO-GEO AMV Coverage Gap Francis Warrick Met Office, UK

MSG MPEF Products focus on GII Simon Elliott Meteorological Operations Division

Energy Management System CANBUS Interface Specification

Windows Performance Monitor Troubleshooting Guide

EXPRESSION OF INTEREST For SADIS 2G SYSTEM SOFTWARE PROCUREMENT AND INSTALLATION

Baudouin Raoult, Iryna Rozum, Dick Dee

Finnish Meteorological Institute s Services for Insurance Sector

The information in this report is provided in good faith and is believed to be correct, but the Met. Office can accept no responsibility for any

Guide to WMO Table Driven Code Forms: FM 94 BUFR. and FM 95 CREX

MOGREPS status and activities

World Meteorological Organization Organisation météorologique mondiale

Requirements of Aircraft Observations data and Data Management Framework for Services and Other Data Users. (Submitted bymichael Berechree)

J3.3 AN END-TO-END QUALITY ASSURANCE SYSTEM FOR THE MODERNIZED COOP NETWORK

ICES Guidelines for Profiling Float Data (Compiled January 2001; revised April 2006)

Copernicus Atmosphere Monitoring Service (CAMS) Copernicus Climate Change Service (C3S)

An exploratory study of the possibilities of analog postprocessing

Intrusion Detection. Overview. Intrusion vs. Extrusion Detection. Concepts. Raj Jain. Washington University in St. Louis

Observation and Findings

DATA MANAGEMENT (DM) - (e.g. codes, monitoring)

SMARTcontrol. Dashboard. from

How To Useuk Data Service

Direct Investment Compilation Practices, Data Sources and Methodology

Performance Monitor for AutoCAD

Very High Resolution Arctic System Reanalysis for

ArcSDE Spatial Data Management Roles and Responsibilities

Rule 4-004M Payment Card Industry (PCI) Monitoring, Logging and Audit (proposed)

Cloud verification: a review of methodologies and recent developments

Real-time and Archived Antarctic. Interactive Processing Tools

Fog and low cloud ceilings in the northeastern US: climatology and dedicated field study

Monitoring IBM HMC Server. eg Enterprise v6

Procon Engineering. Technical Document PELR TERMS and DEFINITIONS

Monitoring Remedy with BMC Solutions

USING SIMULATED WIND DATA FROM A MESOSCALE MODEL IN MCP. M. Taylor J. Freedman K. Waight M. Brower

How To Find Out If The Winds From The Oak Ridge Site Are Calm

Solar Energy Forecasting Using Numerical Weather Prediction (NWP) Models. Patrick Mathiesen, Sanyo Fellow, UCSD Jan Kleissl, UCSD

MacroFlo Opening Types User Guide <Virtual Environment> 6.0

An improved correction method for high quality wind and temperature observations derived from Mode-S EHS

Benefits accruing from GRUAN

BSRN Station Sonnblick

Low Level Windshear Alert System (LLWAS) An integral part of the U.S. FAA Wind-shear safety program

Data Management Implementation Plan

Transcription:

Monitoring for conventional observation systems at ECMWF M. DAHOUI, L. Isaksen and N.Bormann Slide 1 Observation monitoring meeting, July 2013

Conventional observations daily monitoring Slide 2 Observation monitoring meeting, July 2013

Alarm system for conventional observations Alarm system Detect large scale availability and quality problems over selected areas (delivery problems, metadata change, Data assimilation problems, etc.) Detect severe quality (and persistent) problems affecting individual stations Slide 3 Observation monitoring meeting, July 2013

Alarm system for conventional observations Major data types (SYNOP, METAR, SHIP, TEMP, DRIBU, AIREP, AMDAR, ACARS, PROFILERS) Assimilated variables: Temperature, Pressure, Wind, Q 9 selected geographical areas Three pressure layers (for upper-air observations) Monitor : Data counts, bias correction, First guess departures (average and stdev), Analysis departure (stdev) Slide 4 Observation monitoring meeting, July 2013

Feedback info (ODB) Past Statistics Per Data type, layer and area Current Statistics Per Data type, layer and area Set and adjusted manually Hard limits Detect slow drifts Soft limits Detect sudden changes Anomaly detection Various observation quantities Ignore facility Warning message Web E-mail

Alarm system for conventional observations SYNOP Surface pressure Europe Surface : out of range: (19 times in last 10 days for at least one item) http://wedit.ecmwf.int/products/forecasts/satellite_check//do/get/satcheck/969/59315?showfile=true Slightly: count(*)=13632, expected range: 14227.5(H) 18606.9(H) Severely: stdev(fg_depar)=73.073 < stdev(an_depar)=88.41

Feedback info (ODB) Past Statistics (30 days) Per Station ID and layer Current Statistics Per Station ID and layer Soft limits Detect sudden changes Anomaly detection QC_PGE, RMS(FG_DEP), Bcorr Ignore facility Warning message Web E-mail

Alarm system for conventional observations Anomaly detection Time series analysis (for all un-blacklisted stations) of: Probability of Gross Error (PGE): What s the percentage of having large PGE during the past months? RMS of FG departures (when sufficient data available): Detects sudden changes Bias correction (when applicable): Detects sudden changes Slide 9 Observation monitoring meeting, July 2013

Alarm system for conventional observations Severe and persistent problems : Blacklisting purposes. Severe problems of the day : Daily report investigations (model issues, etc.) Slight problems of the day : Data monitoring purposes Tuning work is needed to agree on appropriate definition of severity levels Slide 10 Observation monitoring meeting, July 2013

Cook Island Cook Island

Alarm website - Publishing by data type - Time series provided - Severity highlighted - Time limited Archive

Way forward - Perform extensive tuning (periods to check, thresholds, definition of severity levels) - Operational implementation (including web publishing and dissemination) - Extend the system to check blacklisted data (looking for improvements) - Improve the usage of the alarms: blacklisting, data assimilation monitoring Slide 15 Observation monitoring meeting, July 2013

Monitoring the Observing System More conventional observations at ECMWF Data Monitoring at ECMWF Primarily by resolving acquisition and decoding errors and problems at ECMWF Updating WMO station list resulted in 432 new SYNOP and 12 new TEMP stations Updating WMO station lists again for SYNOP and METAR resulted in more than 1400 moved or new stations The WMO anemometer height information for SHIP had not been updated for many years resulted in many changes A data usage comparison with UK MetOffice showed ECMWF only decoded 40% of the METAR observations acquired The error was because ECMWF did not decode automatic METAR observations (this was resolved in June 2013) Slide 16 Observation monitoring meeting, July 2013

Observation monitoring meeting, July 2013 Slide 17

Some questions and issues for discussion Do all NWP centres receive the same data? Use, quality, blacklisting. Cross-checking with other centres can be useful in confirming observation problems Monthly reports insufficient to pick up quickly developing serious problems. Improve feedback to data providers - data providers should be easily able to check for themselves up-to-date web site (ideally showing consolidated results from different monitoring centres?) together with alerts for significant changes would be a big advance Any restriction on access to the monitoring information? Slide 18 Include bias correction information in monitoring reports Observation monitoring meeting, July 2013