Depolarization lidar for water cloud remote sensing. Background: MS and Depolaization Short overview of the MC model used in this work Depol -lidar for Water Cld remote sensing: Model cases Example with Real data Summary. Lidar Multiple scattering. Lidar FOV cone. 1 st order.
Depolarization lidar for water cloud remote sensing
Background: MS and Depolaization
Short overview of the MC model used in this work
Depol-lidar for Water Cld remote sensing: Model cases
Example with Real data
Lidar FOV cone
Photons can scatter
Multiple times and remain within lidar Field-Of-View
Enhanced return w.r.t single scattering theory
Scattering by cloud droplets of
At uv-near IR is mainly forward
Multiple Scattering induced depolarization
In order to calculate MS enhanced signal and depol accurately Monte-Carlo approaches must be used.
Launch Photon packet
Determine path length until next interaction using PRNG and Beer’s law
Determine scattering angle using PRNG and scatterer’s phase function
Loop until packet is absorbed, hits receiver or migrates too far from the receiver fov
Loop in packet until desired SNR is reached
ECSIM vs other MC results
Validation (vs other models): Cases presented in Roy and Roy, Appl. Opts. (2km from a C1 cumulus cloud OD=5)
ECSIM MC results
Carswell and Pal 1980: Field Obs.
Roy et al. 2008: Lab results
Connection towater cloud remote sensing….
Not too long ago, motivated by the observations of highly depolarizing volcanic ash I was looking for a way to verify the depol. calibration of a lidar system I operate.
Motivated by Hu’s results for Calipso, I wondered if Strato-cu could be a good target
So I setup a script to run my MC code on several hundred cases using a simple water cloud model (Fixed LWC slope and Constant N)
The results were initially disappointing…..the resulting depol and backscatter relationships depended too much on the LWC slope and N !
Hmmm….. maybe I should look at this in some more detail from the other side.
A simple water cloud model is used:
Adiabatic Linear LWC profile and constant number density
D_LWC/dz = 0.5 gm-3
D_LWC/dz = 1.0 gm-3
Para Profiles normalize so that the peak is 1.0
Look-up-tables were made for several cloud-bases, different size-dist widths and receiver fovs.
Same extinction profile but different Reff profiles
Depol and `Shape’ largely a function of extinction profile but exploitable differences exist, especially at small particle sizes (depends somewhat of fov).
However at larger effective radii values then there is no size sensitivity.
Trial using one of the `blind-test’ LES scenes
WITH DRIZZLE !
Drizzle in lower part of cloud does not present a problem
Since effectively only information from the lowest 100 meters of the clouds is used. Departures from “good behavior” particularly near cloud top are problematic.
A case using real data
A real case:
Cabauw: Leosphere ALS-450
355nm, 2.3 mradfov
Comparison with uwave radiometer observations and sensitivity to size-dist width assumptions , fov and depol calibration uncertainties
Ran out of time…
….but preliminary findings are encouraging.