Quality control on the mixing layer height retrieved from...
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European Geosciences Union, General Assembly 2013, Austria, Vienna 7-12 April 2013 Quality control on the mixing layer height retrieved from LIDAR-ceilometer measurements Q. Laffineur, H. De Backer, A. Delcloo, R. Hamdi, J. Nemeghaire and F. Debal Royal Meteorological Institute of Belgium, RMI Introduction → LIDAR ceilometers offer now the opportunity to monitor the mixing layer height (MLH) on a continuous time scale. → Several operational MLH monitoring networks of LIDAR ceilometers are established around the world, and in particular in Europe. → Different algorithms have been developed to retrieve the MLH from the ceilometer measurements. → Under specific atmospheric conditions, these algorithms fail to retrieve a similar MLH than other remote sensing retrieval techniques. → The ceilometers are sometimes located in places where no other remote sensing measurements are available to assess the accuracy of the MLH retrieved by the algorithm. Objectives → To detect automatically the failure of the MLH retrieval algorithms without the support of additional measurements. → To develop and to validate quality control flags on the MLH defined by two quality criteria based only on the ceilometer measurements. Datasets References: HAYDEN et al., 1997: The Vertical Chemical and Meteorological Structure of the Boundary Layer in the Lower Fraser Valley during Pacific ’93, J. Atmos. Environ. 31, 2089–2105 MENUT et al., 1999: Urban Boundary-Layer Height Determination from Lidar Measurements Over the Paris Area, Appl. Opt. 38, 945– 954 Data Data Method Method Date Date Time scale Time scale Place Place MLHLIDAR Retrieval from ceilometer data Vaisala CL51 02/05/2011 30/01/2013 30 min Uccle station BLHECMWF Deterministic European Centre for Medium- Range Weather Forecasts (ECMWF) 02/05/2011 16/11/2011 3 h Grid point (0.125) closest to the Uccle station 17/11/2011 30/01/2013 1 h BLHALARO7 Deterministic Limited Area Model (ALARO) 02/05/2011 30/01/2013 1 h Grid point (7km) closest to the Uccle station BLHRadio Retrieval from potential temperature profile (radio-sounding) 02/05/2011 30/01/2013 One every 2-3 days (at 12h30) Uccle station Humidity, wind Meteorological station 02/05/2011 30/01/2013 1 h Uccle station Quality criteria ➢ Algorithm ═ data preprocessing + gradient method (MLH = ▲, Hayden et al., 1997) + variance method (MLH =▲, Menut et al., 1999) ➢ The MLH is determined as the level at which in a 30 min time frame, is located the maximum number of ▲ accompanied by ▲, within a bandwidth of 165 m. ➢ An average (●) of MLH (▲, ▲) is computed each half-hour. ● Q1: the difference between the average backscatter from 150 m below ● up to the last level below ● and the average backscatter from the first level above ● up to 150 m above ●. ● Q2: the standard deviation of ▲ and ▲ each half-hour. MLH retrieval algorithm ● In Belgium, in 2013, three new ceilometers (Vaisala CL51) will be installed by the Royal Meteo- rological Institute of Belgium (RMI) in addition to the one in Uccle that has already been installed since May 2011. 1 2 3 4 Network in Belgium Conclusions Parametrization - Three quality flags on the MLHLIDAR were parameterized with the two criteria (Q1 and Q2) depending only on the ceilometer data. - The determination of thresholds on Q1 and Q2 was made on base of the 95 th percentile of the absolute difference between the MLHLIDAR and the BLHMODEL - The thresholds were established with ALARO7 due to its higher spatial and time resolution than ECMWF. - The quality flags were validated with the radio-sounding data by comparing the MLHLIDAR and the MLHRADIO - The under-estimation of the MLH by the ceilometer decreased in function of the quality flag (poor → good) but the over-estimation was not significantly affected by the quality control. - Under high humidity conditions, the frequency of MLH LIDAR of good quality was higher than those of poor quality. The sensibility of the backscatter signal to the humidity is likely strengthen the detection of the mixing layer. - Under low wind speed, the frequency of MLHLIDAR of good quality was higher than those of poor quality. - In the wind sector (60-120°), the frequency of MLH LIDAR of good quality was higher than those of poor quality. In this wind direction, more aerosols may be present in the air than in others wind directions and are likely strengthen the trace of the mixing layer in the backscatter signal. - Over the year, the frequency of MLHLIDAR of good quality was higher during the autumn and the winter periods than during the other periods. - Over the day, the frequency of MLHLIDAR of good quality was higher during the second part of the night and at early morning than during the day. Figure 4. Frequency of the occurrence of the three quality flags for each month (left) and for each hour oh the day (right). Figure 3. Box plot of the difference between MLHLIDAR and MLHRADIO for the three quality flags. The central box represents the values from the 25th to 75th percentile. The middle line represents the median, the square represents the mean, the error bars represent the 5 th and 95 th percentile and the cross represent the minimum and the maximum of the difference. Figure 5. Frequency distribution of the relative humidity, the wind speed and the wind direction for the three quality flags. Figure 2. 3D representation of the 95 th percentile of the absolute difference between MLHLIDAR and MLHALARO7 (A), MLHECMWF (B) in relation with Q1 and Q2. Time evolution Validation Atmospheric conditions Figure 1. Example of one day of backscatter measurement at Uccle between 120 and 3000 m (see the text at left for the explanations). Figure 6. Belgium map with the locations of future ceilometers in addition to the one already installed at Uccle (1) BLH: Boundary Layer Height The Solar-Terrestrial Centre of Excellence ● It is possible to control the quality on the MLH retrieved with ceilometer without the support of additional measurements (after the parametrization). ● The quality flags can be improved by ground meteorological measurements and by other quality criteria based on the MLH retrieval algortithm and on the backscatter signal. A B
Transcript of Quality control on the mixing layer height retrieved from...
European Geosciences Union, General Assembly 2013, Austria, Vienna 7-12 April 2013
Quality control on the mixing layer height retrieved from LIDAR-ceilometer measurementsQ. Laffineur, H. De Backer, A. Delcloo, R. Hamdi, J. Nemeghaire and F. Debal
Royal Meteorological Institute of Belgium, RMI
Introduction→ LIDAR ceilometers offer now the opportunity to monitor the mixing layer height (MLH) on a continuous time scale. → Several operational MLH monitoring networks of LIDAR ceilometers are established around the world, and in particular in Europe. → Different algorithms have been developed to retrieve the MLH from the ceilometer measurements. → Under specific atmospheric conditions, these algorithms fail to retrieve a similar MLH than other remote sensing retrieval techniques. → The ceilometers are sometimes located in places where no other remote sensing measurements are available to assess the accuracy of the MLH retrieved by the algorithm.
Objectives→ To detect automatically the failure of the MLH retrieval algorithms without the support of additional measurements.→ To develop and to validate quality control flags on the MLH defined by two quality criteria based only on the ceilometer measurements.
Datasets
References:HAYDEN et al., 1997: The Vertical Chemical and Meteorological Structure of the Boundary Layer in the Lower Fraser Valley during Pacific ’93, J. Atmos. Environ. 31, 2089–2105MENUT et al., 1999: Urban Boundary-Layer Height Determination from Lidar Measurements Over the Paris Area, Appl. Opt. 38, 945–954
DataData MethodMethod DateDate Time scaleTime scale PlacePlaceMLHLIDAR Retrieval from ceilometer
data Vaisala CL5102/05/2011 30/01/2013
30 min Uccle station
BLHECMWF Deterministic European Centre for Medium-Range Weather Forecasts (ECMWF)
02/05/201116/11/2011
3 h Grid point (0.125) closest to the Uccle station17/11/2011
30/01/20131 h
BLHALARO7 Deterministic Limited Area Model (ALARO)
02/05/201130/01/2013
1 h Grid point (7km) closest to the Uccle station
BLHRadio Retrieval from potential temperature profile (radio-sounding)
02/05/201130/01/2013
One every 2-3 days (at 12h30)
Uccle station
Humidity, wind Meteorological station 02/05/201130/01/2013
1 h Uccle station
Quality criteria ➢Algorithm ═ data preprocessing + gradient method (MLH = ▲, Hayden et al., 1997) + variance method (MLH =▲, Menut et al., 1999)
➢The MLH is determined as the level at which in a 30 min time frame, is located the maximum number of ▲ accompanied by ▲, within a bandwidth of 165 m.
➢An average (●) of MLH (▲, ▲) is computed each half-hour.
● Q1: the difference between the average backscatter from 150 m below ● up to the last level below ● and the average backscatter from the first level above ● up to 150 m above ●.
● Q2: the standard deviation of ▲ and ▲ each half-hour.
MLH retrieval algorithm ● In Belgium, in 2013, three new ceilometers (Vaisala CL51) will be installed by the Royal Meteo-rological Institute of Belgium (RMI) in addition to the one in Uccle that has already been installed since May 2011.
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Network in Belgium Conclusions
Parametrization - Three quality flags on the MLHLIDAR were parameterized with the two criteria (Q1 and Q2) depending only on the ceilometer data. - The determination of thresholds on Q1 and Q2 was made on base of the 95th percentile of the absolute difference between the MLHLIDAR and the BLHMODEL
- The thresholds were established with ALARO7 due to its higher spatial and time resolution than ECMWF.
- The quality flags were validated with the radio-sounding data by comparing the MLHLIDAR and the MLHRADIO
- The under-estimation of the MLH by the ceilometer decreased in function of the quality flag (poor → good) but the over-estimation was not significantly affected by the quality control.
- Under high humidity conditions, the frequency of MLHLIDAR of good quality was higher than those of poor quality. The sensibility of the backscatter signal to the humidity is likely strengthen the detection of the mixing layer. - Under low wind speed, the frequency of MLHLIDAR of good quality was higher than those of poor quality.
- In the wind sector (60-120°), the frequency of MLHLIDAR of good quality was higher than those of poor quality. In this wind direction, more aerosols may be present in the air than in others wind directions and are likely strengthen the trace of the mixing layer in the backscatter signal.
- Over the year, the frequency of MLHLIDAR of good quality was higher during the autumn and the winter periods than during the other periods.
- Over the day, the frequency of MLHLIDAR of good quality was higher during the second part of the night and at early morning than during the day.
Figure 4. Frequency of the occurrence of the three quality flags for each month (left) and for each hour oh the day
(right).
Figure 3. Box plot of the difference between MLHLIDAR and MLHRADIO for the three quality flags. The central box represents the values from the 25th to 75th percentile. The middle line represents the median, the square represents the mean, the error bars represent the 5th and 95th percentile and the cross represent the minimum and the maximum of the difference.
Figure 5. Frequency distribution of the relative humidity, the wind speed and the wind direction for the three quality flags.
Figure 2. 3D representation of the 95th percentile of the absolute difference between MLHLIDAR and MLHALARO7 (A), MLHECMWF (B) in relation with Q1 and Q2.
Time evolution
Validation Atmospheric conditions
Figure 1. Example of one day of backscatter measurement at Uccle between 120 and 3000 m
(see the text at left for the explanations).
Figure 6. Belgium map with the locations of future ceilometers in addition to the
one already installed at Uccle (1)
BLH: Boundary Layer Height
The Solar-Terrestrial Centre of Excellence
● It is possible to control the quality on the MLH retrieved with ceilometer without the support of additional measurements (after the parametrization).● The quality flags can be improved by ground meteorological measurements and by other quality criteria based on the MLH retrieval algortithm and on the backscatter signal.
A
B
