Cloud reporting practices and experiences at KNMI

Slides:



Advertisements
Similar presentations
Slide 1ECMWF forecast products users meeting – Reading, June 2005 Verification of weather parameters Anna Ghelli, ECMWF.
Advertisements

Anthony Illingworth, + Robin Hogan, Ewan OConnor, U of Reading, UK and the CloudNET team (F, D, NL, S, Su). Reading: 19 Feb 08 – Meeting with Met office.
Radar/lidar observations of boundary layer clouds
Sutron Airport Weather Systems SAWS Sutron Corporation.
UPRM Lidar lab for atmospheric research 1- Cross validation of solar radiation using remote sensing equipment & GOES Lidar and Ceilometer validation.
Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.
1 By: Bob Jackson, MIC Seattle CWSU Cloud Heights and Sky Cover Observed And Perceived.
© Crown copyright Met Office UK Met Office investigations into laser disdrometers Present Weather Trial at Eskdalemuir, Scotland: Winter 2007/8 Darren.
ATS 351 Lecture 8 Satellites
16/06/20151 Validating the AVHRR Cloud Top Temperature and Height product using weather radar data COST 722 Expert Meeting Sauli Joro.
Printed Reports and Forecasts
Satellite basics Estelle de Coning South African Weather Service
WEATHER CHARTS. WEATHER CHARTS T L O Enabling Learning Objective (ELO) A Action: The student will interpret the information contained in a surface.
ATMS 373C.C. Hennon, UNC Asheville Observing the Tropics.
Remote-sensing of the environment (RSE) ATMOS Analysis of the Composition of Clouds with Extended Polarization Techniques L. Pfitzenmaier, H. Russchenbergs.
Marijn de Haij Wiel Wauben KNMI
Delft University of Technology 1 Do eddy dissipation rate retrievals work for precipitation profiling Doppler radar?, CESAR Science Day, June 18th, 2014.
Assimilation of GOES Hourly and Meteosat winds in the NCEP Global Forecast System (GFS) Assimilation of GOES Hourly and Meteosat winds in the NCEP Global.
Atmospheric Monitoring in the TA experiment
Gerd-Jan van Zadelhoff & Dave Donovan Comparing ice-cloud microphysical properties using Cloudnet & ARM data.
Boundary layer temperature profile observations using ground-based microwave radiometers Bernhard Pospichal, ISARS 2006 Garmisch-Partenkirchen AMMA - Benin.
Cabauw Experimental Site for Atmospheric Research - CESAR - Henk Klein Baltink Atmospheric Research Section.
Visibility Chain at Regional Airports in the Netherlands Wiel Wauben R&D Information and Observation Technology.
LAPS __________________________________________ Analysis and nowcasting system for Finland/Scandinavia Finnish Meteorological Institute Erik Gregow.
National Lab for Remote Sensing and Nowcasting Dual Polarization Radar and Rainfall Nowcasting by Mark Alliksaar.
1 Often asked questions Eva Červená CZECH HYDROMETEOROLOGICAL INSTITUTE TRAINING ON METEOROLOGICAL TELECOMMUNICATIONS WMO RTC-Turkey facilities, Alanya,
SYNOPTIC OBSERVATIONS DECODING & PLOTTING. ENCODING WEATHER INFORMATION In order for people to send information around the world using the WMO discussed.
Estimation of Cloud and Precipitation From Warm Clouds in Support of the ABI: A Pre-launch Study with A-Train Zhanqing Li, R. Chen, R. Kuligowski, R. Ferraro,
TECO-2010, Helsinki | 30 August 2010 Laboratory and Field Evaluation of the NubiScope Wiel Wauben * Fred Bosveld Henk Klein Baltink KNMI * R&D Information.
Atmospheric Aerosol Measurements at the Pierre Auger Observatory The Pierre Auger Observatory operates an array of monitoring devices to record the atmospheric.
EMS Sep Reading UK Evaluating modelled surface long wave downward radiation with Cabauw observations: The GABLS3 SCM case. Fred Bosveld (KNMI)
TECO-2010, Helsinki | 31 August 2010 On the Generation of an Optimized Fractional Cloudiness Time Series using a Multi-Sensor Approach Wiel Wauben *, Marijn.
Status, Evaluation and New Developments of the Automated Cloud Observations in the Netherlands Wiel Wauben, Henk Klein Baltink, Marijn de Haij, Nico Maat,
CBH statistics for the Provisional Review Curtis Seaman, Yoo-Jeong Noh, Steve Miller and Dan Lindsey CIRA/Colorado State University 12/27/2013.
KNMI 35 GHz Cloud Radar & Cloud Classification* Henk Klein Baltink * Robin Hogan (Univ. of Reading, UK)
Lecture 7: INSTRUMENT LANDING SYSTEM (ILS)
Next Week: QUIZ 1 One question from each of week: –5 lectures (Weather Observation, Data Analysis, Ideal Gas Law, Energy Transfer, Satellite and Radar)
Northeast Winter C&V Program Roy Rasmussen NCAR Wes Wilson MIT/LL.
GII to RII to CII in South Africa Estelle de Coning South African Weather Service Senior Scientist.
Instrument location ceilo pyro radar 10m Ground-based remote sensing instruments of clouds and precip at Princess Elisabeth.
1 PGE04-MSG Precipitating Clouds Product Presented during the NWCSAF Product Assessment Review Workshop October 2005 Prepared by : Anke Thoss, Anna.
Retrieval of cloud parameters from the new sensor generation satellite multispectral measurement F. ROMANO and V. CUOMO ITSC-XII Lorne, Victoria, Australia.
UCLA Vector Radiative Transfer Models for Application to Satellite Data Assimilation K. N. Liou, S. C. Ou, Y. Takano and Q. Yue Department of Atmospheric.
UNIVERSITY OF BASILICATA CNR-IMAA (Consiglio Nazionale delle Ricerche Istituto di Metodologie per l’Analisi Ambientale) Tito Scalo (PZ) Analysis and interpretation.
Cloud Detection: Optical Depth Thresholds and FOV Considerations Steven A. Ackerman, Richard A. Frey, Edwin Eloranta, and Robert Holz Cloud Detection Issues.
Estimating Rainfall in Arizona - A Brief Overview of the WSR-88D Precipitation Processing Subsystem Jonathan J. Gourley National Severe Storms Laboratory.
Slide 1 Investigations on alternative interpretations of AMVs Kirsti Salonen and Niels Bormann 12 th International Winds Workshop, 19 th June 2014.
By Dustin Morris. Introduction General Overview Physics Behind Scattering Why We Care Our Results So Far Plans For Rest of Summer By Fir Own work,
Ultrasound Physics Image Formation ‘97. Real-time Scanning Each pulse generates one line Except for multiple focal zones frame one frame consists of many.
Encast Global forecasting.
Ultrasound Physics Image Formation ‘97.
Fourth TEMPO Science Team Meeting
"CRIME Investigations" Henk Klein Baltink (RDWD, KNMI)
Ultrasound Physics Image Formation ‘97.
Wiel Wauben and Dennis Hart
A Probabilistic Nighttime Fog/Low Stratus Detection Algorithm
Paper Review Jennie Bukowski ATS APR-2017
The Cabauw Experimental Site for Atmospheric Research (CESAR): New developments Fred C. Bosveld (KNMI) Content CESAR and its research themes Long term.
Visibility and Visibility Reducing Phenomena
ATMOSPHERIC MONITORING AND CALIBRATIONS PLANS WITH CTA
FORECASTING COURSE SPECI CODING
Emma Hopkin University of Reading
Long-term Synthesis of ARM Millimeter Cloud Radar and
Geostationary Sounders
Handbook on Meteorological Observations
Quantitative verification of cloud fraction forecasts
ECV definitions Mapping of ECV product with OSCAR variables
ALTIMETRY.
Mike Pavolonis (NOAA/NESDIS/STAR)
M. De Graaf1,2, K. Sarna2, J. Brown3, E. Tenner2, M. Schenkels4, and D
Presentation transcript:

Cloud reporting practices and experiences at KNMI Wiel Wauben R&D Observations & Data Technology

LD40 ceilometer status information Impulsphysik LD40 backscatter profile up to 3 cloud base heights (C1, C2, C3) penetration depth per layer vertical visibility (ZV) measurement range (CX) precipitation indicator Impulsphysik LD40 range: 25 (25) 43000 ft wave length: 855 nm pulse repetition frequency: 6494 Hz FOV: 1.2 mrad Beam overlap at about 300 m MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

LD40 ceilometer Point measurement (12m @ 10km) directly overhead of sensor Every 15” update of LD40 output, detection of high clouds uses integrated up to 10’ Slanted installation (5°) to suppress reflection by precipitation compared to suspended cloud droplets Cloud base 0 of SIAM is clear sky; during fog cloud base of 25 ft is reported. up to 3 cloud base heights (C1,C2,C3) reported by ceilometer every 12” and sensor vertical visibility (ZV) Treat ZV as a cloud base C1 in ‘cloud free’ situations (suppress clear during precipitation). 10’ averaged MOR in SYNOP 10’ MD averaged aeronautical VIS in METAR MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Cloud algorithm SYNOP cloud algorithm uses last 30’ of data and the last 10- minutes have double weight. METAR cloud algorithm uses last 10’. When less than 75% of the data is available all cloud parameters are set invalid. Add the height of the ceilometer above station level to the ceilometer data. Sort ceilometer data according to cloud base height. Determine the number of entries corresponding to each okta region taking account of the weight of the entries. Note that 0 and 8 okta require no cloud hit and nothing but cloud hits, respectively. The lowest cloud hit C1 is the cloud base and the total weight of cloud hits of C1 determines the total cloud cover. Isolated low hits (the first 2 hits of the first layer) are ignored in METAR when the base is below 100 ft and is more than 500 ft below the third hit. MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Cloud algorithm Check for presence of cloud at middle of okta interval and if so use the lowest height in okta interval as the corresponding cloud base. Assume maximum overlap of the cloud layers. Combine lower layer with the one above if they are close enough by making one layer with the height of the lowest and okta amount of the upper. Repeat the above procedure for the C2 and C3 data of the ceilometer. Combine the results of C1, C2 and C3. Make the cloud amount of a higher layer at least that of the layer below (overlap). MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Cloud algorithm Reduce the remaining cloud layers to at most four layers where the amount of the first layer is at least 1 okta, the second layer at least 3 okta, the third 5 okta and the fourth layer 7 okta. Only the first 3 cloud layers are reported. Any cloud layer above an 8 okta layer is ignored. Sky obscure is reported (VertVis in METAR) if: (i) only one cloud layer is reported with 8 okta and (ii) cloud base below 500 ft, (iii) not a single C2/C3 hit occurred, and (iv) the MOR/VIS is less than 1000m. The cloud base of the first and only cloud layer is then reported as the vertical visibility. When MOR/VIS is missing vertical visibility cannot be reported. MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

CB/TCU TS (≤ 20km) gives CB weather radar reflectivity or MSG-SEVERI VIS and IR exceed thresholds within 15 km radius # radar contours > 14 dBz (0.25 mm/hr) maximum occurring radar contour averaged cloud top temperature number of pixels with T03.9-T10.8 < 0 HRV maximum - HRV minimum tuned to reference set evaluated by MET for each location weights vary per location Performance POD=0.6, FAR=0.3 MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

CB/TCU the cloud base height is estimated by the dew point depression MAX[(TA-TD)*400, 1500 ft]. CB/TCU is added to an existing layer when close enough; otherwise a new layer is added. When adding the CB/TCU to the ceilometer cloud information any OVC layer is reduced to BKN and Vertical Visibility is changed to a BKN cloud layer with the same height due to coding rules. CB INFO NOT AVBL MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Issues Ceilometer Cloud base height (definition) Performance during precipitation Shallow fog Cloud detection threshold Poor spatial representativeness Algorithm / processing Spatial representativeness  (larger) time window Spatial representativeness  multiple sensors Related to user complaints of non-representative or too slow First cloud must reach the ceilometer(s) than wait time window interval for transition from 0 to 8 okta Multiple sensors & reduction of time window MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Issues Other information sources (Sky) camera, pyrometer, pyrgeometer, satellite, radar, … How to add cloud cover / assign cloud base height How to handle/select in conflicting situations Runway dependent cloud for local routine and special report (?) versus See also manual overruling / procedures Usage of remote observations The next slides give some examples MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

AUTO versus OBS total cloud cover 6 stations /3 years of data for inter-comparison manned/automated. Results /scores generally the same. MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Experiences Missing high clouds vs moist layer reported as cloud. “Gaps” in cloud deck during precipitation. Missing information during shallow fog. Faulty isolated hits. Fewer cases with 1 and 7 okta compared to observer. Missing spatial representativeness. MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer backscatter precipitation / usage ZV MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer (shallow) fog MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer cloud detection threshold MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer snow MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer snow MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Usage of multiple LD40’s at Schiphol versus OBS MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ongoing developments NubiScope Scanning pyrometer Thermal IR, 8-14μm FOV=3° Scan every 10 minutes 36 azimuth * 23 elevation angles Sky temperature  cloud mask / coverage MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016 MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ongoing developments NubiScope Effect of scanning, spatial information Evaluation: good results for total cloud cover Many applications require accurate height!? cover = 0 and 8 ▼ cover = 1 and 7 ▲ percentage cases in okta interval  cover = 2 to 6 ▲ zenith angle range  MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Ceilometer Acceptance Test at Cabauw (CAT) Goals: verify performance at CESAR site and assess impact of transition on operational (AUTO) SYNOP/METAR cloud reporting Two CHM15k’s at firmware 0.724 28 Sep 2014–18 Jan 2015 Reference systems: ALS450 UV lidar (355 nm) CAELI Raman lidar (355-532-1064 nm) Tower visibility sensors 2-200 m Optimal use of Cabauw facilities as testbed for new operational sensors Cabauw, NL MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Low clouds MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Low clouds Results for low clouds vs FS sensors (2,10,20,40,80,140,200 m) Main issue: no physical WMO definition for cloud & cloud base! LD40 vs CHM <Δh> -35 to -45 m, consistent with Martucci (2010) Offset caused by different (internal) cloud detection algorithms CHM15k agrees much better with TowerVis retrieved “cloud base” “30 m level” (100 ft) “110 m level” (360 ft) Percentage Correct CHM1 46% CHM2 45% LD40 <1% CHM1 84% CHM2 82% LD40 20% MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Precipitation Faulty cloud base in precipitation -> firmware updated (2014-12-03) MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Detection in precipitation ZV output currently used in MetNet to overcome “gaps” in cloud base by LD40 For all precipitation events [N=18376 ~ 306h (12% of time)]: 0.3% not detected vs 7% for LD40, worse for higher precipitation intensities Solid precipitation? MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016

Conclusions/Outlook Conclusions from CAT Lufft CHM15k fulfills KNMI requirements Much better sensitivity for middle/high level clouds Improved consistency between instruments For 113 days <Δn> = +10%, but <Δn_low/middle> = +2% Offset in cloud height on average 35-45 m (115-150 ft) Large impact expected on AUTO METAR cloud reporting: lower ceilings (-1 class 25%/-2 classes 5%) Ignore ZV (VOR) as cloud base Next steps Evaluation of CHM15k data at Schiphol 06 by observer Determination of overlap of each sensor individually (May 2016) Parallel measurements at Cabauw/Vlissingen/De Bilt to assess impact on AUTO METAR and AUTO SYNOP products Implementation at AWS √ -> airports -> North Sea platforms MET Alliance AUTO METAR Workshop | Hamburg June 13-14, 2016