1. Instrument location ceilo pyro radar 10m Ground-based remote sensing instruments of clouds and precip at Princess Elisabeth

2. Cloud properties Ceilometer 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) Infrared Radiation Pyrometer passive radiometer: equivalent blackbody brightness temperature in 8-13 micron atm window  cloud base temperature (assuming  =1)

3. Vaisala algorithm is used for cloud base detection - lidar equation is inverted using Klett (1981) algorithm assuming where k 2 =1 - assumption valid for optically thick liquid clouds => remote visibility - visibility below threshold (as defined for pilots) -sharp change in visibility If these criteria not met => VV “cloud bottom” exists  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) (Krasnov and Russchenberg 2002; Rocadenbosch et al. 1999)

4. 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: 1) lidar equation => where 2) gradient i = single successive measurements in the selected period (eg, 10min) with time resolution of recorded profile (3 s) => temporal evolution of GS i (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 h ref => find GS(max) > thresholdand beta(max) => mean between the two = CBH

5. Jan 25, 16 utc: mid level cloud containing liquid from SE cloud height = 3km optically thick liquid clouds - well defined cloud bottom height

6. 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)

7. Jan 31, 15 utc: virga in the ~500-2000m layer detected by MRR Radar equivalent reflectivity

8. Clouds during February 6-7, 2010 storm

9. Synoptic chart: 7 Feb, 2010 storm Operational meteo information from Neumayer station (ECMWF) 500hPanear surface (10m) Feb 6 Feb 7 pe

10. IR composite image Feb 7, 2010 09 UTC: AMRC, UW-Madison thanks to Matthew Lazzara and his team pe

11. 6 Feb, 8 utc 2 cloud layers detected: 1)~1.2 km, CBT = -18 C 2)~3 km, CBT = -35 C liquid? virga-type ice crystals

12. 6 Feb, 15utc CBH = 2.5km CBT = -35 C liquid? icy cloud

13. Feb 7, 01utc CBH = 1.5 and 3-4 km CBT = -25 C light precipitation glaciated cloud

14. Feb 7, ~3utc: ceilo detects beginning of precipitation data gap Height, m 45 very weak radar signal... cloud probably with liquid very light precip

15. data gap Height, m Feb 7, ~8utc: blowing snow radar detects intensive precipitation, while ceilo completely attenuated blowing snow attenuates lidar signal