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DISCLAIMER: This is an EXPERIMENTAL site exploring the use of Artificial Intelligence for aviation weather prediction. The forecasts presented cannot be assumed to be accurate and are used entirely AT YOUR OWN RISK
EGAC
EGNH
EGNS
EGPF
EGPK
KLAX
KSFO
EGAC -- Belfast City United Kingdom (54.6181, -5.8725)
METAR (actual weather observation from US NOAA/NWS, updated every half-hour or so)
Date & Time (UTC)
Temp. (C)
Dewpoint (C)
Cloud base (ft)
Clouds (oktas)
Clouds
QNH (hPa)
Visibility (miles)
Windspeed (kts)
Degrees True
Flight Category
7/20/2018 9:20:00 PM
15.0
13.0
1300
8.0
OVC
1014
6.21
7.0
320
MVFR
NeuralMET Forecasts (via FlyLogical Deep Learning Neural Networks, refreshed every half-hour or so)
Hours ahead
Date & Time (UTC)
Temp. (C)
Dewpoint (C)
Cloud base (ft)
Clouds (oktas)
Clouds
QNH (hPa)
Visibility (miles)
Windspeed (kts)
Degrees True
Flight Category
0.5
7/20/2018 9:50:00 PM
14.7
12.6
5502
7.6
OVC
1015
5.72
6.3
145
VFR
1
7/20/2018 10:20:00 PM
14.8
12.7
5660
7.6
OVC
1015
5.74
5.3
124
VFR
3
7/21/2018 12:20:00 AM
13.7
12.0
6037
6.7
BKN
1017
5.46
3.7
140
VFR
6
7/21/2018 3:20:00 AM
16.5
12.5
6406
5.5
BKN
1016
5.59
6.8
86
VFR
12
7/21/2018 9:20:00 AM
16.1
12.3
6464
4.0
SCT
1017
5.60
4.6
92
VFR
24
7/21/2018 9:20:00 PM
16.0
12.2
6829
3.9
SCT
1017
5.51
4.4
105
VFR
36
7/22/2018 9:20:00 AM
16.8
12.3
7547
1.5
FEW
1018
5.35
4.3
87
VFR
48
7/22/2018 9:20:00 PM
16.0
12.3
8965
4.0
SCT
1018
5.89
2.9
74
VFR
72
7/23/2018 9:20:00 PM
16.3
11.7
7963
3.8
SCT
1017
6.04
4.4
103
VFR
Forecast Historical Performance
Neural Network Forecast average errors (rms)
since last model update on 2018-06-10 09:56:53. Naive estimate (ZOH) errors in square brackets for comparison. Standard deviation of observations in round brackets.
[Click here for recent plots of historical performance for all ICAOs]
Hours ahead
Samples (in avg)
Temp. (C)
Dewpoint (C)
Cloud base (ft)
Clouds (oktas)
QNH (hPa)
Visibility (miles)
Windspeed (kts)
Degrees True
0.5
266
1.3 [0.7] (3.5)
1.2 [0.6] (2.6)
1861 [770] (1374)
1.9 [2.0] (2.5)
3 [0] (7)
0.74 [0.83] (0.69)
1.8 [1.6] (3.8)
97 [87] (121)
1
450
1.5 [1.1] (3.5)
1.4 [0.8] (2.6)
1857 [889] (1374)
2.1 [2.1] (2.5)
3 [0] (7)
0.59 [0.62] (0.69)
2.0 [1.8] (3.8)
110 [92] (121)
3
417
2.1 [2.3] (3.5)
1.7 [1.4] (2.6)
1912 [1120] (1374)
2.2 [2.6] (2.5)
4 [1] (7)
0.69 [0.81] (0.69)
3.1 [3.1] (3.8)
113 [108] (121)
6
394
2.5 [3.9] (3.5)
2.1 [1.9] (2.6)
2188 [1390] (1374)
2.4 [2.9] (2.5)
4 [2] (7)
0.75 [0.92] (0.69)
3.7 [4.2] (3.8)
127 [124] (121)
12
343
3.2 [5.5] (3.5)
2.5 [2.8] (2.6)
1840 [1617] (1374)
2.4 [2.8] (2.5)
5 [3] (7)
0.93 [0.99] (0.69)
3.9 [5.3] (3.8)
129 [141] (121)
24
330
2.3 [2.6] (3.5)
2.4 [3.1] (2.6)
2016 [1547] (1374)
2.3 [2.7] (2.5)
6 [5] (7)
0.58 [0.69] (0.69)
3.5 [4.3] (3.8)
144 [166] (121)
36
286
3.3 [5.6] (3.5)
2.4 [3.3] (2.6)
2208 [1686] (1374)
2.7 [3.2] (2.5)
7 [7] (7)
0.79 [1.02] (0.69)
4.3 [6.5] (3.8)
135 [176] (121)
48
287
2.7 [3.2] (3.5)
2.6 [3.3] (2.6)
2121 [1581] (1374)
2.5 [2.9] (2.5)
7 [7] (7)
0.90 [0.98] (0.69)
3.8 [4.4] (3.8)
145 [164] (121)
72
328
2.6 [3.4] (3.5)
2.6 [3.3] (2.6)
2311 [1588] (1374)
2.4 [3.0] (2.5)
7 [8] (7)
0.82 [0.79] (0.69)
3.2 [4.6] (3.8)
131 [165] (121)