Backradiation - fixing the effect of 2 variables plotting the third

Up to now I've plotted the effect of cloud coverage, humidity and temperature on the difference between DLWIR and ULWIR.

However these plots are not a simple xy since there may be a correlation between temperature/humidity and clouds.

To improve the plots it would be best to plot for example humidity vs dlwir/ulwir at a fixed temperature and cloud cover. The problem is there are too few corresponding points to get a meaningful result.

The following plots were made by inspecting plots and choosing a range of values for each parameter where the dlwir/ulwir change is minimal (about 10% or less)

As a trial cloud coverage was replotted at a much closer variation in the other 2 parameters - this shows a good correspondance with the wider variation but with increased variability.

It should be pointed out that the dlwir as a % of ulwir is a combination of at least all the 3 parameters considered. All that can be gleaned from these plots is the effect of variation of  one parameter whilst holding the others static.

It should be noted that cloud cover is only measured during daylight. All the plots below are therefore only relevant for daylight.

From the above it can be seen that the:

temperature effect is inconsistent and small

relative humidity is the largest effect - more humidity more DLWIR

Cloud cover is significant - more clouds more DLWIR



Reconstructions with limited signals

Firs Set is using trend and the second is using cycles only
The minimum amplitude used is 0.03

Period years	amplitude	Offset months
0.5012	0	8.47
0.8395	0	2.82
0.8907	0	1.13
1.7692	0	0.92
1.9373	0	2.77
1.9906	0	5.72
2.0417	0	9.62
2.1095	0	10.57
2.2567	0	9.57
2.3139	0	6.72
2.5418	0	4.42
2.6735	0	2.47
2.7608	0	4.97
2.8737	0	2.52
3.1647	0	0.98
3.2734	0	6.37
3.4699	0	9.59
3.5777	0	3.07
3.7684	0	3.37
4.0192	0	6.87
4.7240	0	6.64
5.1020	0	5.57
5.2675	0	9.87
5.8528	0	6.67
5.9782	0	1.77
6.2558	0	4.37
6.6195	0	3.07
7.5727	0	3.22
8.3954	0	3.07
10.1027	0.034637599	6.87
11.0000	0.043331925	-75
11.8786	0	4.27
12.6922	0	4.77
14.8995	0.033178542	4.87
21.1000	0.046919237	4.37
35.0832	0	3.42
59.7500	0.107447989	3.07
110.2417	0	5.37
118.5000	0.048809315	95.17
290.2778	0	134.32
310.3644	0	-6.58
2508.2497	0	4.17
2508.3333	0	4.12

Period years	amplitude	Offset months
0.5012	0.036054	8.3
0.8395	0	2.9
0.8910	0	1.23
1.7692	0	0.95
1.9373	0	2.7
1.9911	0	5.8
2.0409	0	9.55
2.1091	0	10.55
2.2569	0	9.55
2.3139	0	6.75
2.5418	0	4.4
2.6714	0	2.35
2.7608	0	5
2.8746	0	2.55
3.1638	0	0.96
3.2734	0	6.55
3.4699	0	9.64
3.5794	0	3.15
3.7684	0	3.35
4.0150	0	6.75
4.7240	0	6.68
5.1061	0	5.5
5.2466	0	9.55
5.7274	0	6.65
5.9782	0	1.85
6.2516	0	4.35
6.6153	0	3
7.5693	0	3.2
8.4272	0	3.25
10.0693	0.030061	6.7
11.0000	0.038659	-69
11.7532	0	3.85
12.6336	0	4.55
14.9497	0.030069	5
21.2083	0.048414	4.45
35.6852	0	3.75
60.0833	0.119432	3.05
101.8333	0	96.15
110.2167	0	5.35
290.2778	0	134.3
317.0533	0.395701	2.3
2508.1661	0	4.15
2508.3333	0	4.1

The Total Cycle thing repeated

"With four parameters I can fit an elephant, and with five I can make him wiggle his trunk".
Attributed to von Neumann

The spreadsheet is available on request (11MB)


A plot of all the amplitudes and frequencies used. The 11 year cycle is TSI The scatter of low frequency low amplitude signals gives the noise

300 year and 60 year cycles superimposed on the constructed temperature record

A check to see if volcanic activity can be seen in the difference between actual HADCRUT3 and reconstruct



Remaider HADCRUT3-reconstruct with the used trailing moving average filtered and offset TSI

The reconstructed signal extended beyond the 2 ends of hadcrut3 note that the little ice age becomes a warm period using the 300year cycle

Acomparison of reconstruced cosines with no tren and reconstructed cosines + trend

Frequency/amplitude and phases of cosines + tsi used

Period years	amplitude	Offset months
0.5012	0.036054	8.3
0.8395	0.00624	2.9
0.8910	0.011773	1.23
1.7692	0.011506	0.95
1.9373	0.012512	2.7
1.9911	0.020375	5.8
2.0409	0.012712	9.55
2.1091	0.010769	10.55
2.2569	0.015195	9.55
2.3139	0.017313	6.75
2.5418	0.017742	4.4
2.6714	0.017162	2.35
2.7608	0.011035	5
2.8746	0.027285	2.55
3.1638	0.019767	0.96
3.2734	0.015463	6.55
3.4699	0.01479	9.64
3.5794	0.02302	3.15
3.7684	0.025772	3.35
4.0150	0.019124	6.75
4.7240	0.028562	6.68
5.1061	0.020193	5.5
5.2466	0.020888	9.55
5.7274	0.01294	6.65
5.9782	0.024963	1.85
6.2516	0.024229	4.35
6.6153	0.016764	3
7.5693	0.021827	3.2
8.4272	0.019945	3.25
10.0693	0.030061	6.7
11.0000	0.038659	-69
11.7532	0.013485	3.85
12.6336	0	4.55
14.9497	0.030069	5
21.2083	0.048414	4.45
35.6852	0.026464	3.75
60.0833	0.119432	3.05
101.8333	0.02669	96.15
110.2167	0	5.35
290.2778	0	134.3
317.0533	0.395701	2.3
2508.1661	0	4.15
2508.3333	0	4.1