how does BEST turn this-
into this?
"
BEST assesses record reliability (the quotes are again from Rohde et al.):
… we assess the overall “reliability” of the record by measuring each record’s average level of agreement with the expected field at the same location.
Here’s our first indicator. The records around Mariscal that show warming agree with the Mariscal “expected field” (i.e. the temperature expectation series) and those that show cooling don’t. Hence the warming records will receive a higher reliability ranking than the cooling records.
BEST then uses the reliability rankings to weight individual records:
Another problem is unreliability of stations …… To reduce the effects of such stations, we apply an iterative weighting procedure.
How much difference does this weighting make?
The (reliability metric) is used as an additional deweighting factor for each station …. this metric has a range between 2 and 1/13, effectively allowing a “perfect” station to receive up to 26 times the score of a “terrible” station.
De-weighting the records around Mariscal that show cooling by factors of up to 26 would certainly explain why they disappear during the adjustment process.
And as noted in the second quote final weights are assigned by an iterative weighting procedure:
The determination of the weighting factors is accomplished via an iterative process that seeks convergence. The iterative process generally requires between 10 and 60 iterations to reach the chosen convergence threshold of having no changes greater than 0.001°C in Tavg between consecutive iterations.
This iterative process is probably where the damage is done. Exactly how it’s done isn’t clear, but it may have to do with the fact that the iterations use every record within a 2,000 km radius (up to 300 are used to construct BEST’s final Paraguay series), and since about two-thirds of these records will show warming and only one-third cooling we might expect that the iteration process will progressively de-weight the cooling stations and converge on the warming stations.
"
read the rest at The Worst of BEST Energy Matters
this is a more detailed description to what I have been saying for a few years now. BEST arbitrarily decides what they want to see, and then continues to adjust until it happens.
into this?
"
BEST assesses record reliability (the quotes are again from Rohde et al.):
… we assess the overall “reliability” of the record by measuring each record’s average level of agreement with the expected field at the same location.
Here’s our first indicator. The records around Mariscal that show warming agree with the Mariscal “expected field” (i.e. the temperature expectation series) and those that show cooling don’t. Hence the warming records will receive a higher reliability ranking than the cooling records.
BEST then uses the reliability rankings to weight individual records:
Another problem is unreliability of stations …… To reduce the effects of such stations, we apply an iterative weighting procedure.
How much difference does this weighting make?
The (reliability metric) is used as an additional deweighting factor for each station …. this metric has a range between 2 and 1/13, effectively allowing a “perfect” station to receive up to 26 times the score of a “terrible” station.
De-weighting the records around Mariscal that show cooling by factors of up to 26 would certainly explain why they disappear during the adjustment process.
And as noted in the second quote final weights are assigned by an iterative weighting procedure:
The determination of the weighting factors is accomplished via an iterative process that seeks convergence. The iterative process generally requires between 10 and 60 iterations to reach the chosen convergence threshold of having no changes greater than 0.001°C in Tavg between consecutive iterations.
This iterative process is probably where the damage is done. Exactly how it’s done isn’t clear, but it may have to do with the fact that the iterations use every record within a 2,000 km radius (up to 300 are used to construct BEST’s final Paraguay series), and since about two-thirds of these records will show warming and only one-third cooling we might expect that the iteration process will progressively de-weight the cooling stations and converge on the warming stations.
"
read the rest at The Worst of BEST Energy Matters
this is a more detailed description to what I have been saying for a few years now. BEST arbitrarily decides what they want to see, and then continues to adjust until it happens.