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Instrument location. Ground-based remote sensing instruments of clouds and precip at Princess Elisabeth. ceilo pyro radar. 10m. Cloud properties. Ceilometer. Infrared Radiation Pyrometer. pulsed diode laser in near IR (910nm)

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instrument location
Instrument location

Ground-based remote sensing

instruments of clouds and precip

at Princess Elisabeth

ceilo

pyro

radar

10m

slide2

Cloud properties

Ceilometer

Infrared Radiation

Pyrometer

  • pulsed diode laser in near IR (910nm)
  • vertical backscatter profiles and cloud base height detection up to 7.5 km
  • range resolution = 10m
  • report interval = 15s (transfer time of
  • accumulated signal)
  • passive radiometer: equivalent blackbody brightness temperature in 8-13 micron atm window
  • cloud base temperature

(assuming =1)

slide3

- visibility below threshold (as defined for pilots)

  • sharp change in visibility
  • If these criteria not met => VV

“cloud bottom” exists

  • Vaisala algorithm is used for cloud base detection
  • - lidar equation is inverted using Klett (1981) algorithm assuming

where k2=1 - assumptionvalid for optically thick liquid clouds

(Krasnov and Russchenberg 2002;

Rocadenbosch et al. 1999)

=> remote visibility

  • Applied to PE:
  • liquid cloud bottom well defined
  • problems with ice clouds: algorithm identifies cloud top as cloud bottom
  • during precipitation/drifting snow - fake cloud bottom heights (=>low cloud bias during storm)
apply new algorithm to cloud base detection tht temporal height tracking martucci et al 2010
Apply new algorithm to cloud base detection:THT (Temporal Height Tracking)Martucci et al. 2010)
  • The THT scheme is based on the information about the mutual positions of the local
  • maxima in the attenuated backscatter coefficient vertical profile and it’s vertical gradient:

where

1) lidar equation =>

2) gradient

  • i = single successive measurements in the selected period (eg, 10min) with time
  • resolution of recorded profile (3 s) => temporal evolution of GSi (average over 10min
  • ensures relatively invariable cloud base initiating the algorithm
  • heights of the largest 10min-mean(GS) and 10-minmean(beta) maxima => reference height
  • look for principal maxima of GS and beta in a limited interval around href

=> find GS(max) > threshold

and beta(max)

=> mean between the two = CBH

jan 25 16 utc mid level cloud containing liquid from se
Jan 25, 16 utc:mid level cloud containing liquid from SE

cloud height = 3km

optically thick liquid clouds

- well defined cloud bottom height

jan 31 15 utc ice cloud precip in the 500 2000m layer
Jan 31, 15 utc:ice cloud/precip in the 500-2000m layer

ice clouds/virga: errors in Vaisala-detected CBH

(precipitation-type profile; Vaisala algorithm

gives cloud top instead of cloud bottom)

synoptic chart 7 feb 2010 storm

500hPa

near surface (10m)

Synoptic chart: 7 Feb, 2010 storm

Feb 6

pe

pe

Feb 7

pe

Operational meteo information from Neumayer station (ECMWF)

ir composite image feb 7 2010 09 utc
IR composite imageFeb 7, 201009 UTC:

pe

AMRC, UW-Madison

thanks to Matthew Lazzara

and his team

6 feb 8 utc
6 Feb, 8 utc

2 cloud layers detected:

~1.2 km, CBT = -18 C

~3 km, CBT = -35 C

liquid?

virga-type ice crystals

6 feb 15utc
6 Feb, 15utc

icy cloud

liquid?

CBH = 2.5km

CBT = -35 C

feb 7 01utc
Feb 7, 01utc

CBH = 1.5 and 3-4 km

CBT = -25 C

glaciated cloud

light

precipitation

feb 7 3utc ceilo detects beginning of precipitation
Feb 7, ~3utc: ceilo detectsbeginning of precipitation

cloud probably with liquid

very light precip

4

5

Height, m

data gap

very weak

radar signal...

feb 7 8utc blowing snow

Height, m

data gap

Feb 7, ~8utc: blowing snow

blowing snow attenuates lidar signal

radar detects intensive

precipitation, while

ceilo completely attenuated

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