Abstract:
Geophysical signals N of interest are often contained in a parent signal G that also contains a seasonal signal X at a known frequency f_{X}. The general issues associated with identifying N and X and their separation from G are considered for the case where G is the Pacific sea surface temperature monthly data, SST3.4; N is the El Niño/La Niña phenomenon and the seasonal signal X is at a frequency of 1/(12 months). It is shown that the commonly used climatology method of subtracting the average seasonal values of SST3.4 to produce the widely used anomaly index Nino3.4 is shown not to remove the seasonal signal. Furthermore, it is shown that the climatology method will always fail. An alternative method is presented in which a 1/f_{X} (= 12 months) moving average filter F is applied to SST3.4 to generate an El Niño/La Niña index N_{L} that does not contain a seasonal signal. Comparison of N_{L} and Nino3.4 shows, among other things, that estimates of the relative magnitudes of El Niños from index N_{L} agree with observations but estimates from index Nino3.4 do not. These results are applicable to other geophysical measurements.

Abstract:
A recently published estimate of Earth’s global warming trend is 0.63 ± 0.28 W/m2, as calculated from ocean heat content anomaly data spanning 1993-2008. This value is not representative of the recent (2003-2008) warming/cooling rate because of a “flattening” that occurred around 2001-2002. Using only 2003-2008 data from Argo floats, we find by four different algorithms that the recent trend ranges from –0.010 to –0.161 W/m2 with a typical error bar of ±0.2 W/m2. These results fail to support the existence of a frequently-cited large positive computed radiative imbalance.

Abstract:
The global atmospheric temperature anomalies of Earth reached a maximum in 1998 which has not been exceeded during the subsequent 10 years. The global anomalies are calculated from the average of climate effects occurring in the tropical and the extratropical latitude bands. El Nino/La Nina effects in the tropical band are shown to explain the 1998 maximum while variations in the background of the global anomalies largely come from climate effects in the northern extratropics. These effects do not have the signature associated with CO2 climate forcing. However, the data show a small underlying positive trend that is consistent with CO2 climate forcing with no-feedback.

Abstract:
We determine the volcano climate sensitivity and response time for the Mount Pinatubo eruption. This is achieved using observational measurements of the temperature anomalies of the lower troposphere and the aerosol optical density (AOD) in combination with a radiative forcing proxy for AOD. Using standard linear response theory we find sensitivity = 0.18 +- 0.04 K/(W/m2), which implies a negative feedback of -1.0 +- 0.4. The intrinsic response time is 5.8+-1.0 months. Both results are contrary to the conventional paradigm that includes long response times and positive feedback. In addition, we analyze the outgoing longwave radiation during the Pinatubo eruption and find that its time dependence follows the forcing much more closely than the temperature, and even has an amplitude equal to that of the AOD proxy. This finding is independent of the response time and feedback results.

Abstract:
Covariance is used as an inner product on a formal vector space built on n random variables to define measures of correlation Md across a set of vectors in a d-dimensional space. For d = 1, one has the diameter; for d = 2, one has an area. These concepts are directly applied to correlation studies in climate science.

Abstract:
We report that the Atlantic Multi-Decadal Oscillation (AMO) shows the same phase-locked states of period 2 and 3 years that have been reported in many other climate indices. In addition, we find that the report by Muller, Curry et al. of an oscillation in the AMO of 9.1 years is a misinterpretation of a maximum in the Fourier spectrum.

Abstract:
There is great interest in knowing when a future El Niño will occur. Most physical models forecast the future based on climate data from the recent past—about a year. The forecasted future is also a fraction of a year. This approach to predicting the future does not use the fact that the climate system may be in a phase-locked state in which sinusoidal oscillations of 2 or 3 years are observed. These states can last many cycles. Thus, if the climate system is in a phase-locked state, one may be able to make definite statements about the future independent of physical models. Douglass, Knox, Curtiss, Geise and Ray (DKCGR) have used the fact that the climate system is presently in a phase-loxked state of period 3 years to state (December 2016) that the next El Niño episode may show a maximum at about November of 2018. We present an updated analysis and state (September 2018) that if the climate system remains in a phase-locked state of period 3 years there will be an El Niño maximum at about November 2018. If that happens, there could be another El Niño maximum at about November 2021.

Abstract:
This paper is a continuation of a study by Douglass and Clader. We extend the analysis through December 2003 using the latest updates of the observational temperature and solar irradiance data sets in addition to a new volcano proxy data set. We have re-determined the solar effect on the temperature from satellite measurements of the solar irradiance and the temperature of the lower troposphere the sensitivity to solar irradiance. This re-analysis calculates two newly recognized dynamic and non-radiative flux factors which must be applied to the observed sensitivity. The sensitivity is about twice that expected from a no-feedback Stefan-Boltzmann radiation balance model, which implies positive feedback. The sensitivity to volcano forcing is also determined. Preliminary results indicate that negative feedback is present in this case. Response times of fractions of a year are found for both solar and volcano forcing. We note that climate models generally assume relaxation times of 5 to 10 years and we comment on the consequences of this large disparity. We also have determined a linear trend in the data.

Abstract:
We directly determine the sensitivity and time delay of Earth's surface temperature response to annual solar irradiance variations from 60 years of data. A two-layer energy balance model is developed to interpret the results. Explaining both the resulting low sensitivity and time delay of 1-2 months requires negative feedback.