Some preliminaries:
Time series of OLR and ISCCP cloud fraction at 0°, 170°W.
You want monthly-average OLR? We got monthly-average OLR
Time series of OLR and net insolation (Reed formula) at 0°, 170°W
Time series of SW at 0°, 170°W: Clear-sky and Reed formula (ISCCP)
Direct comparisons between Reed formula and OLR regression, for
monthly clouds and OLR during 1983-91 when ISCCP clouds were available.
Overall, the agreement is good at the lower values (high cloudiness), but
the Reed formula suggests that at low cloudiness the insolation is much
greater than the OLR regression would indicate. The
Reed formula gives a range of SW values about twice as large as the OLR
regression.
Time series of net SW radiation at 0°, 170°W: Reed (ISCCP) and OLR regression
Net SW radiation at the equator: Reed (ISCCP) and OLR regression. Min/max during Jul 83-Jun 91
Try a regression between OLR and ISCCP clouds.
Figure 1 suggests that a regression could be found between OLR and cloud fraction that might improve the estimate of solar radiation. The regression from OLR to cloudiness could then be used in the Reed formula. This intuitively makes sense, since OLR is really closest to a measure of cloudiness (at least in the west where much of the cloud cover is associated with deep convection that is well-represented by OLR). Another advantage of this method (rather than regressing directly from OLR to radiation), is that Q0 in the Reed formula contains much of the annual cycle variability. Finally, variations of OLR above about 250 W/m2 or so are not meaningful in the context of radiation received at the sea surface. It would be desirable to be able to ignore those variations. Regressing directly OLR -> radiation means that these meaningless signals have as much significance as the low values. However, since the Reed formula ignores cloud variations below 0.3 sky cover, high values of OLR (that regress to low cloud cover values) are less of a factor.
Clouds are available between July 1983 and June 1991. Use monthly-average OLR.
Examples at longitudes across the Pacific (scatter diagrams and regression lines):
130°E
160°E
170°W
140°W
110°W
Some statistics. The correlation is good (>0.8) west of about 140°W, and excellent (>0.9) west of 170°W. East of 140°W the relation is unusable. In the east a lot of cloudiness is stratus, which does not produce an OLR signature. Note the increase in cloud variance, particularly east of 120°W, that is not seen in OLR.
Standard deviation of monthly clouds and OLR
Regression slope and correlation
Basic stats of OLR
Cloud time series estimated by regression:
130°E
160°E
170°W
140°W
110°W
Regression over the entire tropical Pacific
Correlation, slope and intercept based on total ISCCP clouds
Correlation, slope and intercept based on ISCCP high clouds only
Average real and regressed clouds
Standard deviation of real and regressed clouds