Status, Evaluation and New Developments of the Automated

Cloud Observations in the Netherlands

Wiel Wauben, Henk Klein Baltink, Marijn de Haij, Nico Maat, Han The

KNMI, The Netherlands Introduction Status and Experiences New/recent developments

Aeronautical observationsMixing layer heightNubiscope

Introduction Automated cloud observations for synop and

climatological reports in MetNet since Nov. 2002.Observers at airports only for aeronautical observations.

Vaisala LD-40 ceilometer in combination with cloud algorithm (30’ cloud base cloud cover/amounts).

Cloud information centrally available every 10 minutes. Currently 24 ceilometer locations in the Netherlands,

+ 4 air bases in 2006/2007,+ 5 platforms in North Sea in 2006/2007.

Changes for automation of aeronautical observations.

MetNetCeilometer locations

KNMINavyAir Force

4

Nogepa

Experiences

6 stations /3 years of data for intercomparison manned/automated.

Results /scores in general the same.

Total cloud cover (n in okta)

SYNOP NA 0 1 2 3 4 5 6 7 8 9 Sum <n>NA 0 0 0 0 0 0 0 0 0 0 0 00 16 151 91 41 15 7 2 4 3 1 1 332 1.011 13 308 252 84 58 20 14 14 10 2 0 775 1.202 9 90 106 78 59 48 23 26 10 4 2 455 2.293 6 65 94 36 66 47 57 32 34 12 2 451 3.104 2 25 51 24 39 44 48 71 58 35 1 398 4.435 13 22 36 19 30 35 47 51 98 79 2 432 5.216 13 42 57 33 22 33 73 89 167 336 4 869 5.977 42 18 55 23 42 43 63 105 276 1713 2 2382 7.268 92 1 10 10 11 10 11 24 91 2278 42 2580 7.859 11 0 0 0 0 0 1 1 0 9 64 86 8.79

Sum 217 722 752 348 342 287 339 417 747 4469 120 8760<n> 1.77 2.58 2.81 3.49 4.14 4.82 5.21 6.05 7.36 8.12

Band0 = 39.2% Band1 = 75.5% Band2 = 88.0% <Dn> = 0.13 <|Dn|> = 1.10 Miss = 7.1% False = 4.9%

39±5% 75±3% 87±3% -0.2±0.3 1.2±0.2 10±3% 4±2%

AUTOSYNOP

Experiences Missing high clouds vs moist layer reported as cloud. “Gaps” in cloud deck during precipitation. Missing information during shallow fog. Faulty isolated hits. Fewer cases with1 and 7 okta compared to observer. Missing spatial representativity.

235_00 33.5% 74.5% 85.4% 0.08 1.21 8.7% 5.9% 64.0%235_01 35.0% 73.8% 85.4% 0.33 1.22 6.6% 8.0% 99.5%235_02 37.8% 74.6% 86.1% 0.13 1.15 7.6% 6.4% 93.7%240_00 34.1% 74.3% 85.5% -0.36 1.25 11.4% 3.0% 99.8%240_01 35.0% 74.5% 85.4% -0.48 1.25 12.3% 2.4% 99.6%240_02 39.1% 77.0% 86.7% -0.33 1.12 10.6% 2.8% 99.1%260_00 40.5% 75.7% 86.2% -0.19 1.18 10.0% 3.8% 97.4%260_01 40.5% 77.1% 88.5% 0.04 1.06 7.6% 3.9% 99.1%260_02 57.1% 86.1% 94.1% 0.19 0.68 3.3% 2.7% 97.9%280_00 38.6% 73.1% 84.5% -0.41 1.23 11.8% 3.7% 91.0%280_01 37.9% 71.3% 83.5% -0.48 1.29 12.9% 3.6% 99.5%280_02 43.5% 77.6% 88.6% -0.02 1.01 6.6% 4.8% 99.4%344_00 33.0% 72.4% 84.9% -0.37 1.27 11.7% 3.4% 93.7%344_01 34.8% 72.8% 84.8% -0.34 1.26 11.8% 3.4% 99.1%344_02 39.9% 76.5% 86.7% -0.28 1.12 10.2% 3.1% 98.9%380_00 35.2% 72.5% 84.3% -0.53 1.28 13.6% 2.1% 90.9%380_01 37.7% 75.2% 87.3% -0.26 1.13 9.8% 2.9% 99.5%380_02 42.1% 78.1% 89.0% -0.24 1.02 8.6% 2.4% 99.3%261_01 39.2% 75.5% 88.0% 0.13 1.10 7.1% 4.9% 97.5%261_12sec 41.8% 78.1% 88.1% -0.19 1.06 9.1% 2.8% 97.5%261_10min 37.6% 73.1% 84.8% -0.18 1.24 10.9% 4.3% 97.5%261_1zero 38.9% 75.1% 87.8% 0.11 1.12 7.3% 4.9% 97.5%261_lowmid 57.8% 88.1% 94.6% 0.41 0.64 0.6% 4.8% 44.5%261_wind 43.3% 76.8% 88.7% 0.07 1.04 7.4% 3.9% 41.4%261_calm 36.1% 74.5% 87.5% 0.18 1.15 6.9% 5.6% 56.1%261_day 35.1% 74.0% 87.0% -0.02 1.19 9.4% 3.7% 53.0%261_night 44.0% 77.3% 89.2% 0.31 1.00 4.4% 6.3% 44.5%261_wet 77.8% 97.0% 98.9% 0.20 0.27 0.1% 1.0% 13.8%261_dry 32.8% 71.9% 86.2% 0.12 1.24 8.3% 5.5% 83.7%

Case Band0 Band1 Band2 < D n> <| D n|> Miss False Valid235_00 33.5% 74.5% 85.4% 0.08 1.21 8.7% 5.9% 64.0%235_01 35.0% 73.8% 85.4% 0.33 1.22 6.6% 8.0% 99.5%235_02 37.8% 74.6% 86.1% 0.13 1.15 7.6% 6.4% 93.7%240_00 34.1% 74.3% 85.5% -0.36 1.25 11.4% 3.0% 99.8%240_01 35.0% 74.5% 85.4% -0.48 1.25 12.3% 2.4% 99.6%240_02 39.1% 77.0% 86.7% -0.33 1.12 10.6% 2.8% 99.1%260_00 40.5% 75.7% 86.2% -0.19 1.18 10.0% 3.8% 97.4%260_01 40.5% 77.1% 88.5% 0.04 1.06 7.6% 3.9% 99.1%260_02 57.1% 86.1% 94.1% 0.19 0.68 3.3% 2.7% 97.9%280_00 38.6% 73.1% 84.5% -0.41 1.23 11.8% 3.7% 91.0%280_01 37.9% 71.3% 83.5% -0.48 1.29 12.9% 3.6% 99.5%280_02 43.5% 77.6% 88.6% -0.02 1.01 6.6% 4.8% 99.4%344_00 33.0% 72.4% 84.9% -0.37 1.27 11.7% 3.4% 93.7%344_01 34.8% 72.8% 84.8% -0.34 1.26 11.8% 3.4% 99.1%344_02 39.9% 76.5% 86.7% -0.28 1.12 10.2% 3.1% 98.9%380_00 35.2% 72.5% 84.3% -0.53 1.28 13.6% 2.1% 90.9%380_01 37.7% 75.2% 87.3% -0.26 1.13 9.8% 2.9% 99.5%380_02 42.1% 78.1% 89.0% -0.24 1.02 8.6% 2.4% 99.3%261_01 39.2% 75.5% 88.0% 0.13 1.10 7.1% 4.9% 97.5%261_12sec 41.8% 78.1% 88.1% -0.19 1.06 9.1% 2.8% 97.5%261_10min 37.6% 73.1% 84.8% -0.18 1.24 10.9% 4.3% 97.5%261_1zero 38.9% 75.1% 87.8% 0.11 1.12 7.3% 4.9% 97.5%261_lowmid 57.8% 88.1% 94.6% 0.41 0.64 0.6% 4.8% 44.5%261_wind 43.3% 76.8% 88.7% 0.07 1.04 7.4% 3.9% 41.4%261_calm 36.1% 74.5% 87.5% 0.18 1.15 6.9% 5.6% 56.1%261_day 35.1% 74.0% 87.0% -0.02 1.19 9.4% 3.7% 53.0%261_night 44.0% 77.3% 89.2% 0.31 1.00 4.4% 6.3% 44.5%261_wet 77.8% 97.0% 98.9% 0.20 0.27 0.1% 1.0% 13.8%261_dry 32.8% 71.9% 86.2% 0.12 1.24 8.3% 5.5% 83.7%

Nubiscope Scanning IR radiometer 1080 measurements every 15 minutes

Tested at KNMI Dec 2005 to Feb 2006

Technical report 291www.knmi.nl/~wauben

Nubiscope parametersMeasures 1080 sky temperatures (10° azimuth, 3° zenith) and ground temperature

Stores raw and derived dataData extracted off-lineParameters available every 15 (10) minutes:Total cloud coverCloud cover and base for main cloud deckCover and base for low, middle and high cloudsCloud maskCloud base height for zenith measurementsCeiling

Ground temperature

-15 -10 -5 0 5 10 15-15

-10

-5

0

5

10

15

T gr

ass (

o C)

Tgnd (oC)

Valid Tgrass and Tgnd T

grass=0.17(1)+0.97(1) T

gnd

N=7753 SD=0.71 R2=0.98

Sky temperatures CS

5 25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345

1.5

7.5

13.5

19.5

25.5

31.5

37.5

43.5

49.5

55.5

61.5

67.5

73.5

79.5

85.5

Azimuth [°]

Zeni

th A

ngle

[°]

De Bilt28 Jan 2006 12:00UT

Nubiscope Sky Temperature [°C]

-65.0--60.0

-60.0--55.0

-55.0--50.0

-50.0--45.0

-45.0--40.0

-40.0--35.0

-35.0--30.0

-30.0--25.0

-25.0--20.0

-20.0--15.0

-15.0--10.0

-10.0--5.0

-5.0-0.0

Cloud cover

0 4 8 12 16 20 240

5000

10000

15000

20000

45000 1st base 2e base 3rd base Vert. vis. Max. range Nubiscope Ceilometer

Clo

ud b

ase

heig

ht (f

t)

Time (hours)

0

25

50

75

100

Total cloud cover (%)

Nubiscope versus ceilometerTotal cloud cover (n in okta)

NUBI NA 0 1 2 3 4 5 6 7 8 9 Sum <n>NA 0 48 19 11 3 2 2 1 2 31 1 1200 0 800 87 19 13 5 9 2 0 1 2 938 0.281 0 133 77 30 29 23 25 14 11 1 0 343 1.782 0 47 32 16 29 15 14 16 10 7 0 186 2.703 0 21 21 18 18 14 9 16 18 12 0 147 3.614 0 10 30 12 2 14 20 18 17 23 0 146 4.295 1 9 8 8 10 11 16 19 41 33 0 156 5.446 1 3 5 5 10 13 16 19 61 92 0 225 6.497 22 9 16 26 26 44 71 91 289 1310 25 1929 7.328 6 3 2 5 9 11 9 15 128 3246 210 3644 7.969 0 0 0 0 0 0 0 0 1 26 11 38 8.26

Sum 30 1083 297 150 149 152 191 211 578 4782 249 7872<n> 0.46 1.88 3.28 3.51 4.53 4.79 5.39 6.56 7.63 7.88

Band0 = 58.4% Band1 = 87.3% Band2 = 93.0% <Dn> = 0.18 <|Dn|> = 0.68 Miss = 3.5% False = 3.5%

Cloud base height (h in height class)

NUBI NA or n=9 <50m <100m <200m <300m <600m <1000m <1500m <2000m <2500m > or n=0 Sum <h>NA or n=9 0 0 1 5 4 8 6 6 1 1 5 37

<50m 38 38 88 127 32 60 13 4 1 0 87 488 3.46<100m 16 20 33 174 68 96 25 5 0 0 0 437 2.67<200m 20 17 22 153 145 140 45 3 0 0 0 545 2.98<300m 24 16 11 39 64 139 53 6 1 1 0 354 3.49<600m 54 14 31 114 206 541 279 28 5 1 1 1274 3.82<1000m 36 23 6 74 194 390 331 207 13 1 4 1279 4.29<1500m 32 18 7 44 73 186 187 292 43 7 7 896 4.82<2000m 26 15 2 21 14 89 87 65 42 12 27 400 5.08<2500m 10 6 1 5 10 29 28 25 12 10 44 180 5.92> or n=0 23 43 32 63 49 125 133 97 55 31 1331 1982 7.49

Sum 279 210 234 819 859 1803 1187 738 173 64 1506 7872<h> 4.39 2.64 3.00 3.98 4.46 5.25 6.09 7.16 7.89 8.39

Band0 = 37.5% Band1 = 65.4% Band2 = 80.6% <Dh> = -0.43 <|Dh|> = 1.47 Miss = 5.3% False = 14.1%

AUTOSYNOP

AUTOSYNOP

Conclusions Network of near real-time automated cloud

observations in the Netherlands (1734 locations). Fully automated synop, climatological and

aeronautical (cloud) reports. Inclusion of CB/CTU cloud type for aviation requires

improvement. Optimisation of automated cloud observations

(sensor; cloud algorithm; combination of sensors e.g. multi-ceilometer, satellite, Nubiscope, validation).

New mixing layer height product.

Aeronautical cloud observations Automated METAR/SPECI reports in mid 2005

during closing hours of regional airports. SYNOP 30 1’ data METAR 50 12” data

Allowed layer separation, METAR coding. Evaluation of ceiling (height of lowest cloud

layer where cloud amount exceeds 4 okta). In 2006 evaluation of CB/TCU determination

from lightning and radar reflectivity threshold.

Ceiling Rotterdam AP 2001Ceiling height (ft) AUTOMETAR

METAR <100 <200 <300 <500 <1000 <1500 1500 Sum < 100 22 0 0 0 0 0 0 22

100-200 82 16 1 1 0 0 3 103

200-300 41 36 21 4 0 0 1 103

300-500 12 25 70 104 7 0 8 226

500-1000 0 3 10 172 506 14 18 723

1000-1500 0 0 0 7 238 308 32 585 1500 44 6 12 35 359 739 13947 15142

Sum 201 86 114 323 1110 1061 14009 16904

Description Group # Cases Percentage

# Cases

Percentage

Agreement 14924 88.3% Adjacent class 1395 8.3%

16319 96.5%

False alarm 554 3.3% Miss 31 0.2%

585 3.5%

Sum 16904 100.0% 16904 100.0%

Mixing layer height determination LD-40 backscatter profile shows aerosol signal. Gradient between top of mixing layer and free

troposphere.

Evolution convective ML

MLH2 MLH1

hSNR

C1

MLH profilerQuality Index

Good > 0.50

Weak > 0.25

Poor ≤ 0.25

Limited range for MLH estimation

MLH profiler/radiosonde

hSNR

Quality Index

Good > 0.50

Weak > 0.25

Poor ≤ 0.25

diurnal cycle

De Bilt 2000-2005

Monthly variability of MLH diurnal cycle captured

Spring/summer: limited vertical range for MLH estimation

LEGEND

SNR stop level

MLH1

Results: detection rates

De Bilt 2000-2005

Overall detection rate:45-70%

‘Good’ QI: 20-30 %

Spring/summer:Largest contribution of ‘Poor’ estimations