SST GeoDB collection has differently scaled data for Hamburg POI than other POIs

[lubojr]

for table Sea_Surface_Temperature_Timeseries all POIs have got a standard scaling with values in °C, however Hamburg POI (aoi_id=DE29) has some different scale. Could you please check the data or the algorithms for the older dates? Can it be off by 3 decimal digits?

FR11:

[{"measurement_value":"24.807"},{"measurement_value":"20.241"},{"measurement_value":"20.596999999999998"},{"measurement_value":"24.97"},{"measurement_value":"12.904000000000002"},{"measurement_value":"22.351999999999997"},{"measurement_value":"24.745"},{"measurement_value":"20.480999999999998"},{"measurement_value":"26.878"},{"measurement_value":"22.930999999999997"}]

DE29:

[{"measurement_value":"5.718"}, 
 {"measurement_value":"6.115"}, 
 {"measurement_value":"5.985"}, 
 {"measurement_value":"6.382000000000001"}, 
 {"measurement_value":"6.379"}, 
 {"measurement_value":"5.8020000000000005"}, 
 {"measurement_value":"6.322"}, 
 {"measurement_value":"7.711"}, 
 {"measurement_value":"7.013999999999999"}, 
 {"measurement_value":"5.5920000000000005"}, 
 {"measurement_value":"5.809"}, 
 {"measurement_value":"5.784"}, 
 {"measurement_value":"364.892"}, 
 {"measurement_value":"316.14599999999996"}, 
 {"measurement_value":"274.056"}, 
 {"measurement_value":"250.03"}, 
 {"measurement_value":"222.96099999999998"}, 
 {"measurement_value":"207.014"}, 
 {"measurement_value":"205.347"}, 
 {"measurement_value":"220.95"}, 
 {"measurement_value":"234.74400000000003"}, 
 {"measurement_value":"259.77"}, 
 {"measurement_value":"299.834"}, 
 {"measurement_value":"353.80199999999996"}, 
 {"measurement_value":"420.199"}, 
 {"measurement_value":"470.43699999999995"}, 
 {"measurement_value":"493.458"}, 
 {"measurement_value":"557.654"}, 
 {"measurement_value":"616.506"}, 
 {"measurement_value":"665.8919999999999"}, 
 {"measurement_value":"739.988"}, 
 {"measurement_value":"832.5169999999999"}, 
 {"measurement_value":"913.7869999999999"}, 
 {"measurement_value":"1018.549"}, 
 {"measurement_value":"1072.819"}, 
 {"measurement_value":"1136.184"}, 
 {"measurement_value":"1269.036"}, 
 {"measurement_value":"1380.935"}, 
 {"measurement_value":"1434.031"}, 
 {"measurement_value":"1471.2420000000002"}, 
 {"measurement_value":"1500.142"}, 
 {"measurement_value":"1543.1529999999998"}, 
 {"measurement_value":"1563.491"}, 
 {"measurement_value":"1558.682"}, 
 {"measurement_value":"1568.01"}, 
 {"measurement_value":"1586.915"}, 
 {"measurement_value":"1572.8670000000002"}, 
 {"measurement_value":"1533.475"}, 
 {"measurement_value":"1479.9720000000002"}, 
 {"measurement_value":"1414.2579999999998"}, 
 {"measurement_value":"1360.221"}, 
 {"measurement_value":"1301.068"}, 
 {"measurement_value":"1248.555"}, 
 {"measurement_value":"1192.248"}, 
 {"measurement_value":"1123.486"}, 
 {"measurement_value":"1046.8239999999998"}, 
 {"measurement_value":"972.247"}, 
 {"measurement_value":"885.3639999999999"}, 
 {"measurement_value":"797.3639999999999"}, 
 {"measurement_value":"713.025"}, 
 {"measurement_value":"636.681"}, 
 {"measurement_value":"561.622"}, 
 {"measurement_value":"480.024"}, 
 {"measurement_value":"396.061"}, 
 {"measurement_value":"332.411"}, 
 {"measurement_value":"356.29400000000004"}, 
 {"measurement_value":"355.606"}, 
 {"measurement_value":"310.913"}, 
 {"measurement_value":"269.95"}, 
 {"measurement_value":"250.755"}, 
 {"measurement_value":"253.83900000000003"}, 
 {"measurement_value":"273.231"}, 
 {"measurement_value":"295.389"}, 
 {"measurement_value":"320.32599999999996"}, 
 {"measurement_value":"353.95"}, 
 {"measurement_value":"371.63300000000004"}, 
 {"measurement_value":"374.411"}, 
 {"measurement_value":"422.17800000000005"}, 
 {"measurement_value":"508.024"}, 
 {"measurement_value":"578.7280000000001"}, 
 {"measurement_value":"636.591"}, 
 {"measurement_value":"699.056"}, 
 {"measurement_value":"756.427"}, 
 {"measurement_value":"814.887"}, 
 {"measurement_value":"899.1569999999999"}, 
 {"measurement_value":"998.0989999999999"}, 
 {"measurement_value":"1053.618"}, 
 {"measurement_value":"1165.068"}, 
 {"measurement_value":"1303.888"}, 
 {"measurement_value":"1384.517"}, 
 {"measurement_value":"1416.6660000000002"}, 
 {"measurement_value":"1452.914"}, 
 {"measurement_value":"1489.126"}, 
 {"measurement_value":"1505.703"}, 
 {"measurement_value":"1548.221"}, 
 {"measurement_value":"1620.401"}, 
 {"measurement_value":"1634.116"}, 
 {"measurement_value":"1608.576"}, 
 {"measurement_value":"1579.724"}, 
 {"measurement_value":"1551.036"}]

[AlessandroScremin]

@lubojr cc @dmoglioni We checked the source and indeed values are outscaled only for that AOI and only for the fritst batch of the timeseries they provided (the historic timeserie). For the most recent dates the values are back t normal. I sent an email to data providers.

Keep you updated.

Alessandro

[dmoglioni]

@lubojr the data provider has provided new values for Hamburg timeseries that have been ingested in the geodb and are ready to be re-fetched for visualization. Thank you for spotting the errors.

[lubojr]

@dmoglioni The new data were ingested, but the old data are still there, so the chart shows both. Could you please clear the old rows with still invalid values? Thank you

[dmoglioni]

done

[lubojr]

Confirming and closing the issue. Thank you!