Just for the record, I had this problem a few days ago as well. QC flagged my dewpoint, even though my station was fine. One day of errors, and then everything went back to normal.
I'd like to try again to convince people that chasing QA is not worthwhile. Most of you probably don't know my life history, but my first career was as a professor of emergency medicine for the University of Miami. All profs have an area where they spend a little extra time to become the local expert of something. With my interest in computers and math I naturally became the UM SoM expert in quantitative analysis and critical analysis. The skill doesn't precisely carry over to meteorology, but the principles do.
The first thing I want to share is how we look at lab tests. If you test some parameter in a group of normal humans, say sodium, you will get a very wide range of values even if your equipment works perfectly. So we rather arbitrarily assume that the values will follow a bell shaped distribution (they don't) and draw the line for normal such that 95% of the healthy populations fits in there. This is really important, because it means that fully 5% of healthy people have abnormal results for this and any other test. Furthermore if you run a panel of 20 lab tests like we love to do nowadays, on average every healthy person will have one abnormal value. This is a big reason why docs don't want you to have your lab results - it takes us forever to convince people that lab values marked abnormal by the lab are actually normal.
This transfers over to CWOP QC only in the general sense, but there is something to be learned. If we expected to have perfect equipment, and if there was a way the QC computer could know exactly what the weather actually was in your location, then a bad QC means there is a problem. But clearly this is not reality.
QC is calculated from surrounding weather data. You might have an acceptable error in one direction, but if everyone around you randomly has an acceptable error in the other direction you will get flagged. But no one has a problem to fix or to fret over. And it is not surprising that humidity is a place where this occurs because it is the hardest of the weather parameters to measure. In medicine we call this a false positive. People die from false positives, when a false positive test value is followed up by an invasive test that causes a complication. That is why we train young doctors to be smart about how they look at data.
The medicine analogy only stretches so far. Now imagine the world was perfect and there were no false positives. The QC computer does know exactly what the weather is at your location, and compares it to your perfectly functioning weather station and always gets zero difference. We don't need CWOP then. The computer already has the answers and we are wasting our time.
We want your weather data precisely because it differs from what the QC predicts. We know the QC computer is not perfect. We know that every sensor, even professional quality sensors, will not be perfect. The more data we get from real world flawed sensors the easier it becomes to extract actual values. THAT is what CWOP is about.
Maybe you recall the late winter 2007 incident in Baltimore Harbor. A tourist pontoon boat flipped in a freak wind gust on a beautiful blue sky day killing five. CWOP had fewer stations then, but we caught a signal from four of this event. It started about 30 minutes beforehand with a long slight increase in wind speed, the closer stations showed the peak getting higher and narrower, just like a wave cresting on a beach. We looked at the data to see if there might be something there that could have provided warning, but the signal was too weak. However, the signal would have tripped the QC, because this wind was not expected or seen by other stations. So this interesting event was not an instrumentation failure, even if the QC failed!
QC is there to look for systemic errors. The saturated humidity sensor that reads 20% high. The exposed temperature sensor that warms up 20 degrees between 2 and 4 pm when the sun hits it. The rainfall gauge that never records rain even though everyone around is in a monsoon. Those are the sorts of things that you need to be checking your QC for. But the occasional value that falls a little outside the arbitrarily set QC cutoff and then returns is not a problem. It is just the normal sort of thing that pops up when you gather an analyze huge amounts of data!
Steve K4HG
