Sentences with phrase «olr seasonal cycle»

None of them gave as high a skill (as low a Spread ratio) as just using the OLR seasonal cycle predictor, but they all showed more skill than the use of all three predictors simultaneously, save to a marginal extent in one case.

In view of the general pattern of more predictors producing a less skilful result, I thought it worth investigating using just a cut down version of the OLR seasonal cycle spatial field.

Frank, I think the choice of the OSL / OLR seasonal cycle (many models are tuned to this measure) is some kind of circular reasoning.

I accordingly tested all combinations of OLR seasonal cycle plus one of the other eight predictors.

I tested use of the OLR seasonal cycle over the 30S — 30N latitude zone only, thereby reducing the number of predictor variables to 936 — still a large number, but under 4 % of the 23,976 predictor variables used in BC17.

For instance, although use of the OLR seasonal cycle predictor is clearly preferable to use of all predictors simultaneously, some combination of two predictors might provide higher skill.

Panel c shows that using just the OLR seasonal cycle predictor produces a much more skillful result than using all predictors simultaneously.

The RCP8.5 2090 Prediction ratio using the OLR seasonal cycle predictor is under half that using all predictors — it implies a 6 % uplift in projected warming, not «about 15 %».

Nic, if I understand correctly, you're saying the basic statistical intention of the paper was not achieved; the PLS method as applied apparently improperly weighted predictors as evidenced by the superior skill of a single predictor, OLR seasonal cycle, over their group of predictors.

It is not fully clear to me why using all the predictors simultaneously results in much less skilful prediction than using just the OLR seasonal cycle.

As I have shown, in CMIP5 models that relationship is considerably stronger for the OLR seasonal cycle than for any of the other predictors or any combination of predictors.

Your point «The superior utility of the OLR seasonal cycle in narrowing the spread of climate sensitivity may arise because it is a better measure of dOLR / dTs.»

If just the OLR seasonal cycle magnitude field is used, the RMSE prediction error redues to 0.32 C, or a bit lower if only 30S - 30N latitidue zone values are used.

Not exact matches

Unlike OLR, the seasonal cycle in global OSR is only partially explained by the seasonal cycle in global Ts.

These are all cell mean values on a grid with 37 latitudes and 72 longitudes, giving nine predictor fields each with 2664 values for three aspects (climatology, seasonal cycle and monthly variability) for each of three variables (OLR, OSR and N).

frankclimate: Tsushima and Manabe (2013) shows that various AOGCMs disagree seriously with each other and with CERES about the change the seasonal cycle for: 1) OLR from cloudy skies, 2) OSR from cloudy skies, and 3) OSR from clear skies (seasonal change in surface albedo).

Brown comments that I suggested that rather than focusing on the simultaneous use of all predictor fields, BC17 should have focused on the results associated with the single predictor field that showed the most skill: The magnitude of the seasonal cycle in OLR.