Nowcasting of the fog formation by radiative cooling, based on ground-based and satellite observations

Transcription

1 Nowcasting of the fog formation by radiative cooling, based on ground-based and satellite observations Thierry Elias, Dominique Jolivet, HYGEOS, Lille, France Jean-Charles Dupont, IPSL, Palaiseau, France Acknowledgements: Laurent Gomes, Frédéric Burnet (CNRM, France), Martial Haeffelin (IPSL, France)

2 1. The assistance tool prototype for low visibility events Formation of fog by radiative cooling (RAD) Near real-time observations by satellite Increasing probability of fog formation in 2.25 hours Probability level: Fog presence No clouds -> radiative cooling: RAD Real-time ground-based Moderate visibility event: mv Predictors Predicted observations + any pertinent visibility (GAM) parameter Measured visibility Favourable conditions for fog formation, according WRF, run the previous day [Menut et al., 2014]

3 RH Visibility 2. Water uptake by aerosols: signals and promoting processes Relative humidity (RH), hydrated aerosol concentration, visibility 10 km 90% pre-fog moderate visibility event (mv) 5 km pre-fog mist D~1 mm Na ~ cm ±100 cm -3 [Elias et al., 2015] ~1 km FOG! D~10 mm 100% Time 1.5±1.4 h 1.9±1.6 h 520±320 cm -3

4 2. The approach: visibility as signal of water uptake 4 other parameters observed during mv as predictors The 3-year 500-keuros PreViBOSS project at SIRTA ParisFog field campaign ( ) [ SIRTA: observation site 20 km South-West of Paris -> nowcasting for a single point [Dupont et al., 2015] November 2011 to identify the predictors and the criteria because: - Many mist and fogs occurred, and also many 'no-fog' situations (low visibility but without droplet formation) - Three main fog types observed at SIRTA: STL, RAD thin, RAD developed - Optimal instrumentation [Menut et al., 2014; Stolaki et al., 2014; Elias et al., 2015; Haeffelin et al., 2016] 5 months of data to estimate the probability levels because: -variable meteorological conditions, and variable fog occurrence November 2011, March, October, November 2012, January pre-fog and 'no-fog' mv events

5 Outline. 1. The assistance tool prototype for low visibility events 2. The approach: visibility as signal of water uptake 3. Visibility evolution as 2 nd predictor: no-mist then mist after 4. Cloud cover above the SIRTA as 3 rd to 4 th predictors 5. Regional change in the cloud cover as 5 th predictor 6. Thermal structure of the 30-m atmospheric layer as 6 th predictor 7. Favourable and unfavourable scenarii 8. Conclusion

6 Visibility 3. Visibility evolution as 2 nd predictor No-fog and pre-fog moderater visibility event (mv). (mist-mv-clear) (clear-mv-clear) 10 km no-fog mv pre-fog mv 5 km ~1 km Time no-mist mv NO-FOG mv PRE-FOG mv FOG! Total = 542 mv events 46 pre-fog no-fog -> 46/542 = 8.5% fog formation probability We assume that we can distinguish soon enough the 184 clear-mv-clear events Total = = 358 mv events -> 46/358 = 13% fog formation probability

7 4. Cloud cover above the SIRTA as 3 rd and 4 th predictors CL31 and MSG: overall agreement and complementarity METEOSAT Second Generation (MSG) -> cloud typology from NWCSAF/EUMETSAT 1. Selection of clear-sky with CL31 2. What cloud type from MSG? 3. Example in November 2011 at SIRTA All clear-sky (CS) situations during mv events according to CL31: Max altitude for CL31 ~6 km agl Cloud-free according to MSG ~20% cirrus according to MSG The CL31 ceilometer 5 cloud categories during mv: CF/CL31 CT/MSG formation fog type OC STL SC CS Cloud-free RAD CS Cirrus RAD CS clouds in the pixel

8 4. Cloud cover above the SIRTA as 3 rd and 4 th predictors Proba > 20%, and cirrus as predictors of thin fog 2 nd predictor: Visibility evolution RAD 1 st predictor: visibility (4m agl) STL 3 rd predictor: cloud cover above the SIRTA (CF/CL31) Fog formation probability = Npre-fog / Npre P. 4 th predictor: cloud cover above the SIRTA (CL31+MSG) All developed and other thin fogs Only thin fogs under cirrus Unfavourable scenario Scenarii no-fog events probability MHP 7 0 %

9 5. Change in the regional cloud cover as 5 th predictor What tempo from clear-sky to low cloud cover? November 2011 Pre-fog mv fog Thin fog: Cloud-free and cirrus Cloud-free and few others Developed fog: Cloud-free and low clouds Where and when? Low clouds RAD Thin fog Developed fog

10 5. Change in the regional cloud cover as 5 th predictor Anticipation on a regional scale? 15 November 2011 One pixel above the SIRTA Low clouds (CT=3) Fog formation time Cloud-free according to MSG (CT=1) 4 cloud cover change categories: 9x9 pixels, with center pixel above the SIRTA Unfavourable scenario Scenarii no-fog events probability MHP 7 0 % CF-MHD 4 0 % Low cloud cover increase (LCI) Cloud-free increase (CSI) Mid cloud increase (MHI) Mid cloud decrease (MHD) Proportion of low cloud cover

11 6. Thermal structure of the 30-m atmospheric layer as 6 th predictor Distinction of THIN pre-fog / DEV pre-fog / no-fog Measurements of visibility at two altitudes 17 m 4 m Measurements of temperature and relative humidity along a meteorological mast 30 m 20 m 10 m 5 m Strongly stratified Moderately stratified No stratification

12 7. Favourable and unfavourable scenarii 4 unfavourable and 4 favourable scenarii in cloud-free bottom-top 5 th predictor: regional tendency of the cloud cover (MSG) 4 th predictor: cloud cover above the SIRTA (CL31+MSG) 6 th predictor: Vertical thermal gradient (30-m mast) Favourable: probability > 20% Unfavourable: probability < 20% Developed fog formation in only 1 scenario: - Cloud-free bottom to top - Low cloud cover increasing in the region - No stratification

13 7. Favourable and unfavourable scenarii 3 favourable and 1 unfavourable under cirrus

14 7. Favourable and unfavourable scenarii. Unfavourable scenarii Scenarii no-fog events probability MHP 7 0 CF-MHD 4 0 CF-CSI-NS 7 0 CF-LCI-MS 10 (2) 17% CF-CSI-MS 6 (1) 14% CIR-LCI-MS 2 0 Total 36 8% 46% of the no-fog events and 3 missed fogs pre-fog mv FOG! Favourable scenarii no-fog mv Scenarii pre-fog events probability +mv-mist CF-LCI-NS (dev) 6 26% 40% CF-LCI-Str 6 33% CIR-LCI-Str 2 67% CF-CSI-Str 3 27% CF-MHI-Str 1 50% CIR-MHI-Str 1 33% CIR-MHD-MS 1 100% Total 20 33% 40% 87% of all fog events

15 7. Favourable and unfavourable scenarii Other tested parameters: RH for the water uptake by aerosols relative humidity (RH, %) in: November 2011 March 2012 All mv 96±3 74±16 Pre-fog mv 96±3 93±1 No-fog mv 97±2 72±14 Optical particle counter at ground level [Elias et al., 2015] Ceilometer [Haeffelin et al., 2016: presentations by Laffineur et al.] Process: water uptake by aerosols Possible fog formation With further threshold of 85% on RH: We identify correctly almost all no-fog events of March, CF-CLI-NS scenario for developed fog formation: 26% probability 40% 67% Process: Increase of the aerosol number concentration No fog but polluted air (increase of PM2.5) [Dupont et al., 2016]

16 Conclusion Decision assistance tool prototype mv (5-10 km visi) event below clear sky (CL31), with and without cirrus (MSG) Six predictors allow to multiply fog formation probability by 2.5 in mv event (> 2h anticipation time) 5 just after the mv (> 1h anticipation time) Possible improvement with further predictors: RH, OPC, ceilometer, others? Only 1 scenario for developed fog: cloud-free, low cloud cover regional increase, no or weak stratification in first 30 m 26% -> 40% probability after mv. -> 67% if high humidity Unfavourable scenarii identify almost 50% of the no-fog mv conditions, with 8% fog proba Favourable scenarii identify 87% of the pre-fog conditions, with 33% fog formation proba Same kind of study was done for STL Several animations on the web:

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18 5. Change in the regional cloud cover as 5 th predictor What tempo from clear-sky to low clouds? November 2011 Pre-fog mv Clear-sky and low clouds Where and when? fog Low clouds Fog starts