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type
int64
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quality
float64
0
2.65
PN 5 6-7 1.5 M //
3
2.144186
SU 26. 12Z: SW 4 0.5 M //
3
2.403046
MO 27. 00Z: NE-E 0-2 0.5 M //
3
2.416485
MO 27. 12Z: NE-E 2-3 0.5 M //
3
1.908108
TU 28. 00Z: NW-N 2-3 0 M //
3
2.410049
TU 28. 12Z: E 0-2 0.5 M //
3
2.154237
WE 29. 00Z: W
3
1.966906
0-2 0 M //
4
0.846154
WE 29. 12Z: SW 3 0.5 M //
3
2.403046
TH 30. 00Z: SW 3-4 0.5 M //
3
2.398347
TH 30. 12Z: SW 3-4 0.5 M //
3
2.410049
KATTEGAT (57.0N 11.4E) SST: 10 C
2
2.085781
SU 26. 00Z: N 6 7-8 2 M //
3
2.369014
SU 26 8Z: W-NW 2-3
0
0.3
0.5 M //
4
0.591304
MO 27. 00Z: W-NW 3 0.5 M //
3
2.15192
MO 27. 12Z: N 0-2 0 M KK
3
2.150173
TU 28. 00Z: NE 2-3 0.5 M //
3
2.392321
TU 28. 12Z: N 3-4 0.5 M //
3
1.926236
WE 29. 00Z: N-NE 0-2 0.5 M //
3
2.393861
WE 29. 12Z: SW-W 2-3 0 M //
3
2.386172
TH 30. 00Z: W 0-2 0 M //
3
2.152838
TH 30. 12Z: W 2-3 0.5 M //
3
2.394595
BELTS AND SOUND (55.5N 10.9E) SST: 8 C
2
2.082946
SU 26. 00Z: NW-N 4 1 M //
3
2.377778
SU 26. 12Z: NW-N 0-2 0.5 M //
3
2.153018
MO 27. 00Z: NW-N 3 0.5 M //
3
2.392321
MO 27. 12Z: NW-N 2-3 0 M //
3
1.901038
TU 28. 00Z: N-NE 2-3 0 M //
3
2.404255
TU 28. 12Z: N 3 0.5 M //
3
1.91875
WE 29. 00Z: N 2-3 0 M //
3
2.38
WE 29. 12Z: N 0-2 0 M //
3
1.91049
TH 30. 00Z: SW-W 0-2 0 M //
3
2.154906
TH 30. 12Z: W-NW 0-2 0 M //
3
2.379898
KIELER BUCHT (54.6N 10.5E) SST: 7 C
2
1.978571
SU 26. 00Z: NW-N 4 1 M //
3
2.377778
SU 26. 12Z: SW-W 0-2 0 M //
3
2.379898
MO 27. 00Z: NW-N 3 0 M //
3
2.153357
MO 27. 12Z: N 2-3 0 M //
3
1.919481
TU 28. 00Z: NE 3 0 M //
3
2.152106
TU 28. 12Z: N-NE 2-3 0 M //
3
2.392321
WE 29. 00Z: N-NE 2-3 0 M //
3
2.386172
WE 29. 12Z: N-NE 0-2 0 M //
3
1.902479
TH 30. 00Z: SE 0-2 0 M //
3
2.155556
TH 30. 12Z: SE 0-2 0 M //
3
2.384293
MECKLENBURGER BUCHT (54.2N 11.4E) SST: 7 C
2
1.979821
SU 26. 00Z: NW 4-5 1 M //
3
2.155556
SU 26. 12Z: SW 0-2 0.5 M //
3
2.392321
MO 27. 00Z: NW 2-3 0 M //
3
2.153357
MO 27. 12Z: N 0-2 0 M //
3
2.386572
TU 28. 00Z: NE-E 2-3 0 M //
3
2.398347
TU 28. 12Z: N-NE 2-3 '-0-,47-)
3
1.960886
_-'8__
5
0.7
_##98
0
0
41
0
0
9-,_ 1!
5
0.7
__-
0
0
-) M //
5
0.727273
WE 29. 12Z: N-NE 0-2 0 M //
3
1.902479
TH 30. 00Z: E-SE 0-2 0 M //
3
2.379898
TH 30. 12Z: SE-S 0-2 0 M //
3
2.379898
WEST OF RUEGEN (54.7N 12.8E) SST: 7 C
2
1.974085
SU 26. 00Z: NW 5 1 M //
3
2.156264
SU 26. 12Z: SW-W 2-3 0.5 M //
3
1.905576
MO 27. 00Z: W 2-3 0.5 M //
3
2.388396
MO 27. 12Z: N 0-2 0 M //
3
2.386572
TU 28. 00Z: N-NE 0-2 0 M //
3
2.149296
TU 28. 12Z: N-NE 2-3 0 M //
3
2.392321
WE 29. 00Z: NW-N 0-2 0 M //
3
2.15192
WE 29. 12Z: NE-E 0-2 _).5 M //
3
1.870732
TH 30. 00Z: SW-W 2-3 0 M //
3
2.379898
TH 30. 12Z: SW-W 0-2 0 M //
3
2.386172
BODDEN WATERS EAST (54.3N 14.0E) SST: 8 C
2
1.980498
SU 26. 00Z: NW-N 5-6 7 1.5 M //
3
2.377778
SU 26. 12Z: NW 3-4 0.5 M //
3
2.392321
MO 27. 00Z: W 2-3 0.5 M //
3
2.388396
MO 27. 12Z: NE 2-3 ' 0 M //
3
1.920141
TU 28. 00Z: E 2-3 0 M //
3
2.393007
TU 28. 12Z: NE 0-2 ,0 . //
3
2.154237
WE 29. 00Z: SE 3 0 M //
3
2.375503
WE 29. 12Z: E-SE 2-3 0 M //
3
1.920742
TH 30. 00Z: W 2-3 0 M //
3
2.38
TH 30. 12Z: NW 2-3 0 M //
3
2.384293
WESTERF BALTIC NORTHEAST (55.1N 12.7E) SST: 7 C
2
1.965909
SU 26. 00Z: NW-N 4-5 1 M //23. &10+: W-NW 0-2 0.5 M //
3
2.370171
MO 27. 00Z: W 3 0 M //
3
2.153247
MO 27. 12Z: N 0-2 0 M //
3
2.386572
TU 28. 00Z: NW-N 2-3 0 M //
3
2.410049
TU 28.#12Z: NW-N 0-2 0 M //
3
2.147488
WE 29. 00Z: N-NE 2-3 0 M //
3
2.386172
WE 29. 12Z: E-SE 0-2 0.5 M //
3
1.891918
TH 30. 00Z: SW-W 0-2 0 M //
3
2.154906
TH 30. 12Z: S-SW 2-3 0 M //
3
2.386172
SOUTHERN BALTIC SOUTH (54.8N 15.5E) SST: 5 C
2
1.964228
SU 26. 00Z: NW-N 5 6-7 2 M //
3
2.381878
SU 26. 12Z: W-,
3
1.933333
_-4 1 M //
3
1.84
MO 27. 00Z: &,2 3 1 M //
3
2.15443
MO 27. 12Z: VAR 0-2 0.5 M //
3
2.384
TU 28. 00Z: E-SE 2-3 0.5 M //
3
2.387928
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DWD HF CLASSIFY 1

Dataset gathered from a 20m anntena from slovakia, recieving dwd (militarry weather info)

Curently super small, recieving tooks a lot of time at 50 baud (50bps) It was made by using a known list of types and qualities and training a small ml to help together with some rules hardcoded to classify the type and quality. If there are issues please report them and i will try improoving the ml and rules.

TYPE

  1. = garbage / broken line
  2. = metadata header (PN, EDZW, FQEN, WODL, NIL, NNNN station codes)
  3. = region header (KATTEGAT, BALTIC SEA, coordinates + SST lines)
  4. = forecast entry (SU 26. 12Z: SW 4 0.5 M)
  5. = raw weather parameters line fragment
  6. = corrupted-but-structured (important: salvageable noise)
  7. = hf call / cq (CQ CQ CQ DE DDK2 DDH7)
  8. = frequency list / schedule (FREQUENCIES 4583 KHZ 7646 KHZ 10100.8 KHZ)
  9. = test pattern / idle (RYRYRYRYRYRYRYRYRY)
  10. = bulletin board (WEATHER AND SEA BULLETIN FOR THE MEDITERRANEAN SEA, ISSUED BY MARINE WEATHER SERVICE HAMBURG 25.04.2026, 15 UTC:)
  11. = synop (06060 05973 00000 10037 20021 30178 40245 52015 60002)

QUALITY (DECIMAL)

  1. = unusable / noise
  2. = partially readable
  3. = mostly correct with minor corruption
  4. = fully correct and model thinks is acurate
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