Page 1© Crown copyright 2004 Challenges posed by the WMO Integrated Observing System J. Nash, Met Office, Exeter TECO-2006, 4-6 December 2006, Geneva

Page 2© Crown copyright 2004 CIMO’s terms of reference[1] It shall be responsible for matters relating to international standardization and compatibility of instruments and methods of observation of meteorological, related geophysical, and environmental variables, which shall include in particular:  (a) The provision of advice concerning types, characteristics, accuracies, performance, effective and economical use of instruments and methods of observation;  (b) Global and regional field comparisons and evaluations of instruments and methods of observation to achieve data quality consistent with users' requirements and global data compatibility;  (c) Studies and recommendations on methods of observation, including test and calibration methods and the correction to be applied;  (d) Promoting the development of reference instruments.

Page 3© Crown copyright 2004 CIMO’s terms of reference[2] It should support other WMO Programmes and bodies by  (a) the provision of specifications for instruments and observing systems in order to meet requirements for the measurement of meteorological, related geophysical and environmental variables, taking into account both experience and new developments;  (b) Encouraging research and development of new approaches in the field of instruments and methods of observation of meteorological, related geophysical and environmental variables;  (c) Promoting the appropriate and economical production and use of instruments and methods of observation with particular attention to the needs of developing countries for providing technical information, on the different systems.

Page 4© Crown copyright 2004 What is the WMO Integrated Observing System?  Main observing networks now administered by different parts of WMO should be managed as one system to avoid duplication of effort.  In particular this seems to suggest that as a minimum:- Global observing System (GOS), Global Climate Observing System (GCOS) Global Atmospheric watch (GAW) should be organised together. So, which observing systems does CIMO need to support, and so which groups of experts need to be identified and encouraged for the future?

Page 5© Crown copyright 2004 Examples for Upper Air measurements  CIMO needs to support:_  National network operations and hence GOS  GCOS Upper Air network (GUAN) for climate  Possibly GCOS Reference Upper Air network (GRUAN)- a network with higher quality measurements than GUAN,as specified by the scientific community, possibly incorporating special scientific instrumentation  GAW upper air measurements such as ozonesonde operations

Page 6© Crown copyright 2004 How well does CIMO fulfil its terms of reference?  For GOS and GCOS, CIMO probably performs all terms of reference 1, but the scientific community is not very happy with the recommendations for 1(d) – promoting references  Recommendations on specifications have been provided to some extent.  Encouraging research and development with the scientific community- has probably not been properly addressed by CIMO in recent years and some actions need to be taken to rectify the situation since to a large extent the scientific community is the only resource pool for future international instrument experts.  Some actions have been taken to encourage development of new systems in those countries where the upper air systems were becoming obsolete.

Page 7© Crown copyright 2004 Outstanding problems for the scientific community  How to eliminate the regions of substandard upper air measurements in the GOS?  It seems to require some bi-lateral or tri-lateral project, supervised by a task team of the Upper Air OPAG  Nothing works unless the countries in the regions concerned are willing to co-operate in the work.  Are the members of CIMO willing to take up the challenge to eliminate these substandard observations or are we going to continue to pretend they do not exist?  The scientific community has little sympathy with our oprerations, when it is clear that the technology needed to make good measurements is not very expensive and readily available worldwide.

Page 8© Crown copyright 2004 Actions for CIMO  Training Prepare training material for all relevant personnel 1.observers 2.operational managers 3.scientists brought in from other skill areas to support operations.  Ensure staff sent on training courses are those who will benefit from the training  Retention of experts with special skills  Identify staff who have sufficient skill to support the resolution of technical problems in the GUAN networks.  Ensure continuity of support for such staff so that they are retained as long as necessary in the skill pool.  Identify priority tasks for CIMO and ensure that the level of expertise made available is suitable and probably paid to do the work, since voluntary solutions are too haphazard.

Page 9© Crown copyright 2004 Development of future networks, GOS,GUAN,GRUAN, needs co- operation between scientists and CIMO  Within Europe proposals have been developed to use a COST project to facilitate the work and improve dialogue between the various parties.  This COST proposal narrowly failed in the competition for initiation this year, but encouragement has been given to try again in 2007  Success will be aided by a broader level of support from all WMO NMHS who fall within the 25 countries in the COST community.

Page 10© Crown copyright 2004  Proposal based on input from colleagues in Bulgaria, Finland, France, Germany, Italy, The Netherlands, Switzerland, UK.  About half from National Meteorological Services and half from European Universities with interest from manufacturers to ensure effective scientific and technical collaboration between industry, climate and meteorological operations.  Aims are in line with UK Met Office strategic development of observing networks. Proposal also in line with Meteo–France future strategies.  Substantial investment in instruments and scientific effort envisaged Proposal Background [1]

Page 11© Crown copyright 2004  J. Nash required by WMO to generate a policy for CIMO for implementing and supporting WMO Integrated Observing System.  WMO secretariat (IMOP programme) wishes to participate in this proposed action, if it is initiated.  Proposal reflects a desire to co-ordinate activities across Europe, rather than purely on a national basis, preparing a plan for a WMO Region for the 1 st time.  Past experience with WMO Radiosonde Intercomparison, Mauritius show that the combined resources of WMO and COST lead to a more effective work, than from either organisation on its own. Proposal Background [2]

Page 12© Crown copyright 2004 This action would allow the limited number of instrument experts in wind profilers, GPS water vapour, integrated profiling systems, atmospheric lidars, radiosondes to cross-fertilise with scientists specialising in cloud measurements and weather radar measurements and aircraft measurements. The remote sensing observing systems are now sufficiently mature to make it worthwhile:- 1.To think about saving on the number of radiosondes used each year. 2.To develop the data assimilation techniques that will allow the observations to be used in Numerical Weather Prediction (NWP) 3.To exploit the measurements in studying atmospheric processes for climate prediction. 4.To combine in situ and remote sensing to provide a stable observing system for climate monitoring. Motivation

Page 13© Crown copyright 2004 GCOS requirements  GCOS/GEOSS requirements for fundamental atmospheric variables such as  Temperature, humidity, cloud, winds, aerosol  User requirements generated by GCOS/NOAA workshops  Requirement to deploy initial GARON stations  Specification requires combination of microwave radiometer, radiosondes and surface-based radiation measurements  Need to develop operational practices for management of stations  Continuation of GUAN (GCOS Upper Air Network)  with emphasis on stability of radiosonde systems in use  CIMO recommends quality monitoring based on  comparison of remote sensing and NWP background fields as part of data assimilation

Page 14© Crown copyright 2004 EG-CLIMET COST76 Wind Profilers COST716 GPS Water Vapour COST720 Integrated Profiling Systems WinProf WinProf II (EUMETNET) E-GVAP (EUMETNET) COST717 Use of Radar in Hydrological and NWP Models Relationship to other Actions EG-CLIMET Proposal Builds on Outputs of previous COST Actions and EUMETNET programmes COST731 Uncertainty in Hydro- Meteorological Models OBSNET Observatory Network (EUMETNET)

Page 15© Crown copyright 2004 Emphasis of Proposal  Towards Operational Applications  e.g. NWP, nowcasting + climate modelling/monitor  Integration of different elements, instruments  Ground-based systems+ aircraft  High time-resolution available  Emphasis on boundary layer and troposphere  Complements satellite capability  Validate models of atmospheric processes for Climate prediction  Impact on short-range forecasts  4D assimilation in convective scale models  Defining international network across Europe

Page 16© Crown copyright 2004 Scientific Programme Tasks Overview 1.Further develop basic systems for operational networks. 2.Improve integration from groups of systems. 3.Design techniques to assimilate observations or vertical profiles. 4.Deploy Integrated Observing Systems in Testbeds. 5.Analyse Observing System Experiments.

Page 17© Crown copyright 2004 Task 1 Instrumentation  Collaborate to make basic instruments better suited to operational use at minimum cost  For each system: (Wind Profiler, Microwave Radiometer, Cloud Radars, Ceilometers, Lidar, GPS, Weather Radar, … )  Improve hardware and processing of raw data (liaison with manufacturers)  Improve quality control  Optimise observing strategies (temporal & spatial sampling, scanning, … )  Improve retrieval algorithms (scientific problem)  Facilitating data transfer to users:  Definition of terminology  Specification of file content and structures  Establishment of data exchange archive

Page 18© Crown copyright 2004 Task 1 Examples for Wind Profiler  Specify Wind Profiler for Integrated Profiling:  Beamwidth, power, advanced signal processing to estimate spectral moments  For:  Reliable measurement of vertical velocity  Improved height coverage (Better signal to noise)  Better turbulence measurements (spectral width) UFAM 1290 MHz Degreane Wind Profiler at Aberystwyth Antenna array for 46.5 MHz NERC MST Radar can be seen in the background

Page 19© Crown copyright 2004 COST 720 result- technique used in air pollution monitoring in USA Top of the boundary layer

Page 20© Crown copyright 2004 Task 4 Testbed Experiments  Optimise expenditure committed to experiments  Contribute to experiments ’ design to cover needs of climate and weather observing network  design jointly between instrumentation and data assimilation experts  collaborate with CIMO as WMO Remote Sensing Evaluation tests  Review requirements for additional experiment(s) in consultation with other disciplines in GEOSS/GMES

Page 21© Crown copyright 2004 Planned Testbed Experiments  Helsinki Testbed  Coordinated by FMI  Jan 2005 to  Sept 2007  LUAMI Proposed WMO Test  Coordinated by DWD  Lindenberg  2007/8  Integrated Profiling Test  Coordinated by Met Office   SE England  Dedicated experiment for EG-CLIMET?  Extension of others?  France/Netherlands/ Italy/Switzerland ?

Page 22© Crown copyright 2004 Conclusion  Collaborative projects involving both CIMO, the scientific community and manufacturers seem to offer a method of addressing many of the skill problems for the future, since they allow the opportunity for NMHS staff to gain necessary skills whilst addressing work relevant to the future of the Commission and the WIGOS.  Members are encouraged to join in producing suitable proposals and initiating regional collaboration where possible.

Page 23© Crown copyright 2004 GPS Integrated water vapour In Kg.m -2 at on 22 July2006 Wattisham Purple squares lightning strikes

Page 24© Crown copyright 2004 Wattisham wind profiler for 22 July- most winds not used currently in NWP

Page 25© Crown copyright 2004 Task 5 Analyse OSEs - Methods  Analyse Data Assimilation trials  to establish observations ’ impact  Analyse Case Studies from Testbed expts  to identify horizontal and vertical structure in atmospheric fields that need to be observed  associated with significant weather or  atmospheric processes critical to climate studies  Compare observations from different systems:  e.g. Winds from Doppler weather radars and wind profiling radars (with COST 731),  Integrated Water Vapour from radiometer and GPS

Page 26© Crown copyright 2004 Task 5 Analyse OSEs – Benefits & Results  Specify Observing Network for operational applications  Evaluate groups of equipment for GARON Reference network: Compatibility, complementarity, redundancy, what is missed?  Evaluate targeting strategy for in situ observations  Evaluate cost effectiveness of different groups of systems for future climate and weather networks  Optimum methods for each variable from different instruments  Investigate methods to use obs. from groups of systems:  Direct assimilation into models or  Derive products independently before assimilating them  Exploiting high time-resolution to improve process modelling  Check Impact on forecast accuracy for severe weather

Page 27© Crown copyright 2004 Wind profiler

Page 28© Crown copyright 2004 Weather radar Strongest winds in drier air missing

Page 29© Crown copyright 2004

Page 30© Crown copyright 2004 Earth System Science and Environmental Management Domain Committee Meeting, 5 October 2006 European Ground-based observations of essential variables for CLImate and operational METeorology EG-CLIMET OC

Page 31© Crown copyright 2004 Task 1 Examples for Microwave Radiometer  Test and improve noise and calibration stability  Develop optimum observing strategies:  Temporal sampling  Scanning Azimuth/Elevation  Integrate angular and frequency scanning methods  Season/site specific background info.  Test and improve limits of retrieval algorithms  Test Radio Frequency Interference mitigation  Investigate Future Technology  Similar for other instruments Radiometrics TP/WVP-3000 Microwave Radiometer System at Camborne

Page 32© Crown copyright 2004 Task 2 Integration Stand-alone retrievals (not assimilated in NWP)  Improve range of cloud products  Improve temperature and humidity profiles  Liaison with OBSNET community to define integrated products from observatory network  Define standard data products for integration  Develop multi-instrument quality control

Page 33© Crown copyright 2004 Task 2 Example - Improve Cloud Products  Classification algorithms  Combining cloud radar and ceilometer  To improve cloud profiles  e.g. as pre-processing step for other retrievals  Need to understand underlying physics  To use adequate physical description  For example  Combining signal from ceilometer and cloud radar to classify clear/cloud/drizzle Simulated radar-lidar ratio versus the effective radius. Both plots are based on in-situ data taken during the CLARE 98, DYCOMS-II, and CAMEX - 3 campaigns [Krasnov and Russchenberg, 2006, Chapter 5, COST720 Final Report] Drizzling Cloud Non-Drizzling Cloud Drizzling in Formation

Page 34© Crown copyright 2004 Task 2 Example - Multi-instrument quality control  Develop multi-instrument quality control  Use observations from one instrument as QC for retrievals from others  e.g.  Reject rain-contaminated radiometer observations based on wind profiler signals,  Detect backscatter from insects/birds  Detect range aliasing in wind profiler/cloud radars

Page 35© Crown copyright 2004 Task 2 Example - Improve temperature and humidity profiles  Integrated Profiling Technique (IPT) [L öhnert et al., 2004]  Use optimal estimation retrieval theory  to combine observations from different instruments  with background data from NWP/radiosonde/climate  Develop further to include rain, wind profiler, GPS. IPT State Vector, x a Analysis Error, A z Temp/Dew Pt Observation Vector, y Observation Error, R TbTb Frequency Background Data, x b Background Error, B From Radiosonde Forward Model, H (x) Jacobian, H=  y/  x Ulrich Löhnert, Susanne Crewell, Clemens Simmer An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water Journal of Applied Meteorology :

Page 36© Crown copyright 2004 Task 3 Set-up Data Assimilation Key tool to quantify benefit of integrated observing networks  Specify forward model and error characteristics for each obs.  Conduct trials assimilating data (over extended periods)  into high-resolution operational NWP models  including raw observations and/or retrieved profiles  from real proto-type operational systems  or synthetic observations  To address:  Most beneficial data assimilation technique currently feasible, e.g. 3D-VAR or 4D-VAR  Check model ’ s balance when assimilating observations To assess Benefit of co-locating instruments  How to exploit the observations ’ high time-resolution  Monitor developments to allow improvement of some current deficiencies of data assimilation schemes

Page 37© Crown copyright 2004 Task 3 Data Assimilation process  Combine observations with NWP model fields  Optimal – uses errors  Modify NWP model fields to minimise difference between observations and background  Observation space  Continuous cycle

Page 38© Crown copyright 2004 Global monitoring for Environment and Security, GMES “The development of a non-satellite atmospheric monitoring must make best co-ordinated use of what exists” GMES-GATO Atmospheric corrections for most GMES earth observation remote sensing require reliable measurements of water vapour in the lower troposphere, as well as aerosol and ozone. Reliable measurements of fundamental atmospheric variables on a smaller scale than currently available are clearly required for early warning and real-time natural hazard management.

Page 39© Crown copyright 2004 South Uist wind profiler,64 MHz; operational since October 2004 Improved basic signal processing, developed by Vaisala in liaison with Lindenberg

Page 40© Crown copyright 2004 System operates throughout very severe storm – January

Page 41© Crown copyright Wind speed in m.s -1