I Workshop on Lidar Inversion Algorithms-ALINE Concepción, Chile
Analysis.Concepcion2014 History
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- Bg=10^8-- download holger-poisson-S1k-bg1e8.txt
- Bg=10^7-- download holger-poisson-S1k-bg1e7.txt
- Bg=10^6-- download holger-poisson-S1k-bg1e6.txt
- Bg=10^5-- download holger-bg1e5.txt
- Bg=10^4-- download holger-bg1e4.txt
- Bg=10^3-- download holger-bg1e3.txt
- Bg=10^2-- download holger-bg1e2.txt
- Bg=10^1-- download holger-bg1e1.txt
- Bg=10^0-- download holger-bg1e0.txt
- Bg=10^5-- download holger-poisson-S1k-bg1e5.txt
- Bg=10^4-- download holger-poisson-S1k-bg1e4.txt
- Bg=10^3-- download holger-poisson-S1k-bg1e3.txt
- Bg=10^2-- download holger-poisson-S1k-bg1e2.txt
- Bg=10^1-- download holger-poisson-S1k-bg1e1.txt
- Bg=10^0-- download holger-poisson-S1k-bg1e0.txt
- Noise and background added to the input signal as Signal -> Poissrnd(1000*Signal + BG)). Columns are: alt, 355, 532 and 1064.
- Noise and background added to the input signal as Signal -> Poissrnd(1000*(Signal + BG)). Columns are: alt, 355, 532 and 1064.
- Noise and background added to the input signal as Signal -> Poissrnd(Signal + BG). Columns are: alt, 355, 532 and 1064.
- Noise and background added to the input signal as Signal -> Poissrnd(Signal + BG). Columns are: alt, 355, 532 and 1064. This is wrong because the original signal if very small at the end and the Poisson() will result in single values.
- Noise and background added to the input signal as Signal -> Poissrnd(1000*Signal + BG)). Columns are: alt, 355, 532 and 1064.
- Bg=10^5-- download holger-bg1e5.txt
- Bg=10^4-- download holger-bg1e4.txt
- Bg=10^3-- download holger-bg1e3.txt
- Bg=10^2-- download holger-bg1e2.txt
- Bg=10^1-- download holger-bg1e1.txt
- Bg=10^0-- download holger-bg1e0.txt
- Noise and background added to the input signal as Signal -> Poissrnd(1000*Signal + BG)). Columns are: alt, 355, 532 and 1064.
- Input is
- 1- altitude
- 2 - signal at 355nm
- Input is
- Input is: 1- altitude and 2 - signal at 355nm
- Input is
- 1- altitude
- 2 - signal at 355nm
- Input is
- Input is: 1- altitude and 2 - signal at 355nm
- Input is
- 1- altitude
- 2 - signal at 355nm
- Input is
- Input is
- 1- altitude
- 2 - signal at 355nm
- Input is
- Alternative input with extra noise and background
- Bg=10^6-- download ristori-bg1e6.txt
- Bg=10^4-- download ristori-bg1e4.txt
- Bg=10^2-- download ristori-bg1e2.txt
- Bg=10^0-- download ristori-bg1e0.txt
- Alternative input with extra noise and background
Pablo Ristori (Ceilap - Argetina) also provided a simulated dataset. This is more complicated as it includes clouds and aerosols. Two versions are available:
Pablo Ristori (Ceilap - Argetina) also provided a simulated dataset. This is more complicated as it includes clouds and aerosols. Input is only available for 355nm at the moment. Two versions are available:
- Noise and background added to the input signal: Signal -> Poissrnd(Signal + BG)
- Bg=10^6-- download Attach:holger-bg1e6.txt
- Bg=10^4-- download Attach:holger-bg1e4.txt
- Bg=10^2-- download Attach:holger-bg1e2.txt
- Bg=10^0-- download Attach:holger-bg1e0.txt
- Noise and background added to the input signal: Signal -> Poissrnd(Signal + BG)
- Noise and background added to the input signal as Signal -> Poissrnd(Signal + BG). Columns are: alt, 355, 532 and 1064.
- Bg=10^6-- download holger-bg1e6.txt
- Bg=10^4-- download holger-bg1e4.txt
- Bg=10^2-- download holger-bg1e2.txt
- Bg=10^0-- download holger-bg1e0.txt
- Noise and background added to the input signal as Signal -> Poissrnd(Signal + BG). Columns are: alt, 355, 532 and 1064.
- Noise and background added to the input signal: Signal -> Poissrnd(Signal + BG)
- Bg=10^6-- download Attach:holger-bg1e6.txt
- Bg=10^4-- download Attach:holger-bg1e4.txt
- Bg=10^2-- download Attach:holger-bg1e2.txt
- Bg=10^0-- download Attach:holger-bg1e0.txt
- Noise and background added to the input signal: Signal -> Poissrnd(Signal + BG)
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and residual aerosols, LR=28, beta = 0.5 Mm^-1 sr^-1
- BL Aerosols up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1
- Residual aerosols, LR=28, beta = 0.5 Mm^-1 sr^-1
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and no residual aerosols
- BL Aerosols up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1
- No residual aerosols
- Expected output , and
- P and T with better format download
- P and T with better format download
- Expected output , and
- Signals for 355, 387, 532, 608, 1064 download
- Signals for 355, 387, 532, 608, 1064 download input and output
- Cloud at 6km LR=28 and beta = ~ 280 Mm^-1 sr^-1 (Cloud optical depth = 1.0)
- Cloud at 6km LR=28 and beta ~= 280 Mm^-1 sr^-1 (Cloud optical depth = 1.0)
- Cloud at 6km LR=28 and beta = ~ 57 Mm^-1 sr^-1 (Cloud optical depth = 0.2)
- Cloud at 6km LR=28 and beta ~= 57 Mm^-1 sr^-1 (Cloud optical depth = 0.2)
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. Aerosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A., B�senberg, J., … Wang, X. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3. Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio. Applied Optics, 43(28), 5370. doi:10.1364/AO.43.005370
- Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A., Bösenberg, J., … Wang, X. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3. Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio. Applied Optics, 43(28), 5370. doi:10.1364/AO.43.005370
Participants
- Antonieta Silva, CEFOP - Chile
- Daniel Nisperuza, UNAL - Colombia
- Fabio Lopes, IPEN - Brasil
- Henrique Barbosa, USP - Brasil
- Pablo Ristori, CEILAP - Argentina
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- height = m
- backscatter = 1/Mm / sr
- extinction = 1/Mm
- lidar ratio = sr
- molecular backscatter = 1/Mm / sr (step 3)
- molecular extinction = 1/Mm (step 3)
- synthetic molecular signal = 1/m / sr /m2 (step 3)
- Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A., B�senberg, J., … Wang, X. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3. Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio. Applied Optics, 43(28), 5370. doi:10.1364/AO.43.005370
- Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A., B�senberg, J., … Wang, X. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3. Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio. Applied Optics, 43(28), 5370. doi:10.1364/AO.43.005370
- output - 1 (aerosoles)
- ascii file, up to four columns. Use -999 if not giving some of these columns..
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- ascii file, up to four columns. Use -999 if not giving some of these columns..
The output of your algorithms should produce simple ascii files without header and columns separated by TAB with the following columns:
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- Strong cloud - download input and the
- Strong cloud - download input
- Weak cloud download
- Weak cloud - download input and the
- Profiles used for the raman Earlinet paper
- Profiles used for the raman Earlinet paper (Pappalardo et al, 2004)
Data set by Pablo Ristori, Argentina
- Cloud at 6km LR=28 and beta = ~ 50 Mm^-1 sr^-1
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and residual aerosols, LR=28, beta = 0.5 Mm^-1 sr^-1
- Data set #2 by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28 and not residual aerosols
- Strong cloud - download input and the
- Cloud at 6km LR=28 and beta = ~ 280 Mm^-1 sr^-1 (Cloud optical depth = 1.0)
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and residual aerosols, LR=28, beta = 0.5 Mm^-1 sr^-1
- Weak cloud download
- Cloud at 6km LR=28 and beta = ~ 57 Mm^-1 sr^-1 (Cloud optical depth = 0.2)
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and no residual aerosols
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A., B�senberg, J., … Wang, X. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3. Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio. Applied Optics, 43(28), 5370. doi:10.1364/AO.43.005370
- The profiles used for the first Earlinet paper on the elastic retrievals (Bockmann et al, App. Opt. 2004)
- Profiles used for the first Earlinet paper on the elastic retrievals (Bockmann et al, App. Opt. 2004)
- The profiles used for the raman Earlinet paper
- Profiles used for the raman Earlinet paper
- Data set by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28 and residual aerosols 10%
Pablo Ristori (Ceilap - Argetina) also provided a simulated dataset. This is more complicated as it includes clouds and aerosols. Two versions are available:
Data set by Pablo Ristori, Argentina
- Cloud at 6km LR=28 and beta = ~ 50 Mm^-1 sr^-1
- Aerosols at BL up to 1.5km, LR=28, beta = 5 Mm^-1 sr^-1 and residual aerosols, LR=28, beta = 0.5 Mm^-1 sr^-1
- Data sent by H. Baars, iFT, Leipzig - Germany - This should be the profiles used for the first Earlinet paper on the elastic retrievals (Bockmann et al, App. Opt. 2004)
- Data set by Gelsomina, Italy - This should be the profiles used for the raman Earlinet paper
- The profiles used for the raman Earlinet paper
- Signals for 355, 387, 532, 608, 1064 download
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- Earlinet
- Data sent by H. Baars, iFT, Leipzig - Germany - This should be the profiles used for the first Earlinet paper on the elastic retrievals
Our friends from Earlinet have provided datasets for us to try our algorithms.
- Data sent by H. Baars, iFT, Leipzig - Germany - This should be the profiles used for the first Earlinet paper on the elastic retrievals (Bockmann et al, App. Opt. 2004)
References
- Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V., Boselli, A., … Wiegner, M. (2004). Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 2. A erosol Backscatter Algorithms. Applied Optics, 43(4), 977. doi:10.1364/AO.43.000977
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- fourth lidar ratio = sr
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- output - 2 (moleculas)
- ascii file, header lines starting with #
- # rayleigh cross section at std pressure and temperature = m2
- # avogadro number = #
- # co2 concentration = ppmv
- altitude = m
- rayleigh cross section at press and temperature of each level = m2
- rayleigh signal
- Data set #2 by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28
- Data set #2 by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28 and not residual aerosols
- Data set by Pablo Ristori, Argentina - Cloud at 6km, BL at 1.5km
- Data set by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28 and residual aerosols 10%
- Data set #2 by Pablo Ristori, Argentina - Cloud at 6km LR=28, BL at 1.5km LR=28
- Data set by Pablo Ristori, Argentina - Cloud at 6km, BL at 1.5km
- second molecular backscatter = 1/Mm / sr (step 3)
- third molecular extinction = 1/Mm (step 3)
- Data sent by H. Baars, iFT, Leipzig - Germany
- This should be the profiles used for the first Earlinet paper on the elastic retrievals
- Data sent by H. Baars, iFT, Leipzig - Germany
- Data sent by H. Baars, iFT, Leipzig - Germany - This should be the profiles used for the first Earlinet paper on the elastic retrievals
- Input
- pressure = hPa
- temperature e dew point = degC
- lidar ratio = sr
- altitude = m
- Input
- Data set by Gelsomina, Italy
- This should be the profiles used for the raman Earlinet paper
- pressure = hPa
- temperature e dew point = degC
- lidar ratio = sr
- altitude = m
- Data set by Gelsomina, Italy - This should be the profiles used for the raman Earlinet paper
- Input
- pressure = hPa
- temperature e dew point = degC
- lidar ratio = sr
- altitude = m
- Input
- Input
- pressure = hPa
- temperature e dew point = degC
- lidar ratio = sr
- altitude = m
- This should be the profiles used for the raman Earlinet paper
- This should be the profiles used for the raman Earlinet paper
Data format
- Input
- pressure = hPa
- temperature e dew point = degC
- lidar ratio = sr
- altitude = m
- output - 1 (aerosoles)
- ascii file, up to four columns. Use -999 if not giving some of these columns..
- first height = m
- second backscatter = 1/Mm / sr
- third extinction = 1/Mm
- fourth lidar ratio = sr
- ascii file, up to four columns. Use -999 if not giving some of these columns..
- output - 2 (moleculas)
- ascii file, header lines starting with #
- # rayleigh cross section at std pressure and temperature = m2
- # avogadro number = #
- # co2 concentration = ppmv
- altitude = m
- rayleigh cross section at press and temperature of each level = m2
- rayleigh signal
- Data sent by H. Baars, iFT, Leipzig - Germany
- This should be the profiles used for the first Earlinet paper on the elastic retrievals
- Data set by Gelsomina, Italy
- This should be the profiles used for the raman Earlinet paper
- Data sent by H. Baars, iFT, Leipzig - Germany
- Holger
- Gesolomina
- Earlinet
Lidar researchers representing each Lidar group from the Latin America Lidar Network (ALINE) will participate in the first workshop on Lidar inversion algorithms supported by the Center for Optics and Photonics (CEFOP) of the Universidad de Concepción. Main goal of this first workshop is the establishment of a quantitative Lidar dataset to describe the aerosol vertical, horizontal, and temporal distribution, including its variability on a continental scale. This dataset could be a comprehensive data source to address the four- dimensional spatio-temporal distribution of aerosols on a global scale.
The working days will be held in the Universidad de Concepción, according to the following program:
Day 1. (Monday, March 10th, 2014)
09h. Meeting on the hall (first floor) of Faculty of Physical Sciences and Mathematics, Universidad de Concepción, Chile (Calle Esteban Iturra).
09.15-09.45: 30min Step 1. Getting acquainted with the first EARLINET simulation case (Boeckmann et al., Appl. Opt., 2004). File structure, available variables, input format and units will be described. Expected output format and units will be defined for easy comparison.
09:45-10h: Coffe Break
10h-13h: 3hs Step 2. Each group should processes this dataset using their own version of the Klett-Fernald method and compute separately Rayleigh and particle backscattering.
Step 3. Upload of results #1. 13h-14-30h: Lunch
14.30-16h: 1h30 Step 4. Presentation of each group’s methodology: from the molecular calculation to the method of integration. These presentations should be prepared prior to the workshop.
16-16.30h: 30min Step 5. Comparison of calculated particle properties with the simulation input profiles. Discussion should follow.
16:30-17h: 30min Coffee break.
17h-19h: 2h Step 6. Simulation input files will be distributed. Groups should use those for helping debugging the algorithms and obtaining an improved inversion. Step 7. Upload of results #2. 30min Step 8. Comparison of calculated particle properties with the simulation input profiles. Discussion should follow.
Day 2. (Tuesday, March 11th, 2014)
09-09.30h: 30min Step 9. Paper discussion: Bucholtz (1995) and Bodhaine (1999), or, computing the molecular backscattering from first principles.
09:30-11h: 1h30 Step 10. Check the calculation of all molecular quantities in all algorithms; take into account that absolute no difference should occur the same inputs are used. Then it should be checked how the reference height is chosen.
Step 11. Upload of results #4.
11h-11.30: 30min Step 12. Comparison of calculated molecular properties. Discussion should follow.
11.30-13h: 1h Step 13. Calibration of Lidar signal. Define the use of one single point or a height range to calibrate the Lidar signal.
Step 14. Upload of results #4. 13h-14-30h: Lunch
14:30-15h: 30min Step 15. Comparison of calibrated lidar signals. Discussion should follow.
15h-16h: 1h Step 16. Checked how the reference height is chosen. If the same reference height and the same lidar ratio is used by each user, the output should be almost identical.
Step 17. Upload of results #5. 16h-16.30: 30min Coffee break
16:30-17h: 30min Step 18. Comparison of inverted lidar signals: now we should have same molecular reference, same calibration and same reference height. Discussion should follow.
Day 3. (Wednesday, March 12th, 2014)
09:30-13h: 3h Step 19. Time for working on the codes and last intercomparison. Focus on signal processing: background removal, binning, smoothing and gluing.
13h-14-30h: Lunch
14:30-16:30: 2h Step 19. Time for discussing the unified algorithm (or two: matlab and mathematica). Preparation of the codes to be shared via ALINE from the contribution of the groups.
16:30-17h: 30min Coffee break
17h-19h: 2h Step 20. Time for discussing the unified algorithm (or two: matlab and mathematica). Preparation of the codes to be shared via ALINE from the contribution of the groups.
Day 4. (Thursday, March 13th, 2014)
09h-19h: All day Step 21. A manuscript will be write with the results. Emphasis will be done due to South America lidar network would be very valuable to contrast northern hemispheric with southern hemispheric aerosol conditions, and the consequences on climate.
13h-14-30h: Lunch
March, 10 to 13, 2014
March, 10 to 13, 2014
Lidar researchers representing each Lidar group from the Latin America Lidar Network (ALINE) will participate in the first workshop on Lidar inversion algorithms supported by the Center for Optics and Photonics (CEFOP) of the Universidad de Concepción. Main goal of this first workshop is the establishment of a quantitative Lidar dataset to describe the aerosol vertical, horizontal, and temporal distribution, including its variability on a continental scale. This dataset could be a comprehensive data source to address the four- dimensional spatio-temporal distribution of aerosols on a global scale.
The working days will be held in the Universidad de Concepción, according to the following program:
Day 1. (Monday, March 10th, 2014)
09h. Meeting on the hall (first floor) of Faculty of Physical Sciences and Mathematics, Universidad de Concepción, Chile (Calle Esteban Iturra).
09.15-09.45: 30min Step 1. Getting acquainted with the first EARLINET simulation case (Boeckmann et al., Appl. Opt., 2004). File structure, available variables, input format and units will be described. Expected output format and units will be defined for easy comparison.
09:45-10h: Coffe Break
10h-13h: 3hs Step 2. Each group should processes this dataset using their own version of the Klett-Fernald method and compute separately Rayleigh and particle backscattering.
Step 3. Upload of results #1. 13h-14-30h: Lunch
14.30-16h: 1h30 Step 4. Presentation of each group’s methodology: from the molecular calculation to the method of integration. These presentations should be prepared prior to the workshop.
16-16.30h: 30min Step 5. Comparison of calculated particle properties with the simulation input profiles. Discussion should follow.
16:30-17h: 30min Coffee break.
17h-19h: 2h Step 6. Simulation input files will be distributed. Groups should use those for helping debugging the algorithms and obtaining an improved inversion. Step 7. Upload of results #2. 30min Step 8. Comparison of calculated particle properties with the simulation input profiles. Discussion should follow.
Day 2. (Tuesday, March 11th, 2014)
09-09.30h: 30min Step 9. Paper discussion: Bucholtz (1995) and Bodhaine (1999), or, computing the molecular backscattering from first principles.
09:30-11h: 1h30 Step 10. Check the calculation of all molecular quantities in all algorithms; take into account that absolute no difference should occur the same inputs are used. Then it should be checked how the reference height is chosen.
Step 11. Upload of results #4.
11h-11.30: 30min Step 12. Comparison of calculated molecular properties. Discussion should follow.
11.30-13h: 1h Step 13. Calibration of Lidar signal. Define the use of one single point or a height range to calibrate the Lidar signal.
Step 14. Upload of results #4. 13h-14-30h: Lunch
14:30-15h: 30min Step 15. Comparison of calibrated lidar signals. Discussion should follow.
15h-16h: 1h Step 16. Checked how the reference height is chosen. If the same reference height and the same lidar ratio is used by each user, the output should be almost identical.
Step 17. Upload of results #5. 16h-16.30: 30min Coffee break
16:30-17h: 30min Step 18. Comparison of inverted lidar signals: now we should have same molecular reference, same calibration and same reference height. Discussion should follow.
Day 3. (Wednesday, March 12th, 2014)
09:30-13h: 3h Step 19. Time for working on the codes and last intercomparison. Focus on signal processing: background removal, binning, smoothing and gluing.
13h-14-30h: Lunch
14:30-16:30: 2h Step 19. Time for discussing the unified algorithm (or two: matlab and mathematica). Preparation of the codes to be shared via ALINE from the contribution of the groups.
16:30-17h: 30min Coffee break
17h-19h: 2h Step 20. Time for discussing the unified algorithm (or two: matlab and mathematica). Preparation of the codes to be shared via ALINE from the contribution of the groups.
Day 4. (Thursday, March 13th, 2014)
09h-19h: All day Step 21. A manuscript will be write with the results. Emphasis will be done due to South America lidar network would be very valuable to contrast northern hemispheric with southern hemispheric aerosol conditions, and the consequences on climate.
13h-14-30h: Lunch
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA
Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT \\
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA
Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT
March, 10 to 13, 2014
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT March, 10 to 13, 2014
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA
Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT
March, 10 to 13, 2014
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA
Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT
March, 10 to 13, 2014
March, 10 to 13, 2014
UNIVERSIDAD DE CONCEPCIÓN, CENTRO DE ÓPTICA Y FOTÓNICA
Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia -CONICYT
March, 10 to 13, 2014
(:Title I Workshop on Lidar Inversion Algorithms-ALINE Concepción, Chile :) March, 10 to 13, 2014