Temperature time series

Santer B.D. Wigley T.M.L. Boyle J.S. Gaffen D.J. Hnilo J.J. Nychka D. Parker D.E. and Taylor K.E. (2000). Statistical significance of trends and trend differences in layer average atmospheric temperature time series. J. Geophys. Res., 105(D6), 7337-7356. 

FIGURE 19.16 (a) Observed temperature time series in the central Gotland Sea. (b) Simulated... 

The long-term variability of the vertical temperature profile in the central Gotland Sea is shown in Fig. 19.16. Both, the observed (Fig. 19.16a) and the simulated (Fig. 19.16b) temperature time series, show the two inflow sequences 1993/1994 and 1997/1998. At the end of the stagnation period, the warm deepwater is replaced by colder water due to the 1993 inflow. On the contrary, the inflow in 1997/1998 carried warm water. 

The window length for the temperature time series is taken as 64 min and the window moves in 4 mm intervals. For the test case, initially, the process is assumed to be operating normally. At the 54th window, a... 

Figure 5.20 shows the periodogram for the once-differenced summer temperature time series. Unlike in the previous periodogram, there are now a series of peaks clustered in the area around 2.5-3 years/cycle. Also, there is a secondary peak around 4 years/cycle followed by a rather weak peak in the 8 years/cycle region. All these values seem to be multiples of each other suggesting that they represent a single feature rather than separate features. 

Viola, R, Paiva, S., and Savi, M. (2010) Analysis of global warming dynamics from temperature time series. Ecological Modelling, 221 1964-1978. 

Generai description. Galvanic corrosion refers to the preferential corrosion of the more reactive member of a two-metal pair when the metals are in electrical contact in the presence of a conductive fluid (see Chap. 16, Galvanic Corrosion ). The corrosion potential difference, the magnitude of which depends on the metal-pair combination and the nature of the fluid, drives a corrosion reaction that simultaneously causes the less-noble pair member to corrode and the more-noble pair member to become even more noble. The galvanic series for various metals in sea water is shown in Chap. 16, Table 16.1. Galvanic potentials may vary with temperature, time, flow velocity, and composition of the fluid. 

Fig. 2 Time-series of annual mean water temperature in the San Reservoir (Spain) and air temperature in the Ter River watershed. The series start in 1964, after the first filling of the reservoir. Annual means are based on monthly measures of the volume weighted mean temperature. Only years with at least 10 temperature profiles were included in the figure. The air temperatures are annual means for the whole Ter River watershed, calculated from data collected in several meteorological stations in the basin, and weighted according to their area of influence...

Application of Time to Temperature Control of Semi-Batch Reactors... 

Figure 2. Experimental trial used to Identify transfer function. In this experiment, the reactant flow rate was deliberately varied and the reactant temperature measured on-line in the pilot plant. This allowed us to identify the proper time series model.

One final note While the techniques used here were applied to control temperature In large, semi-batch polymerization reactors, they are by no means limited to such processes. The Ideas employed here --designing pilot plant control trials to be scalable, calculating transfer functions by time series analysis, and determining the stochastic control algorithm appropriate to the process -- can be applied In a variety of chemical and polymerization process applications. 

Figure 3.2.4 shows the calculated results of the time series of temperafure distribution with the total spark energy of 0.7mj and the ratio of capacity spark of 100%. The hot kernel is initially an ellipsoid and the maximum temperature region is located in the center of the spark gap. Afterwards, the hot kernel develops into a torus and the highest temperature region moves into the ring... 

Calculated time series of temperature distribution. Spark energy O.ZOmJ spark gap width 1.0mm spark electrode diameter 0.50mm ratio of capacity spark energy 100%. Left time = 1 ps, central time = 10 ps, right time = 100 ps. 

Figure 4. Time series profiles of and temperature, potential density, Chi a, and nitrate (Slagle and Heimerdinger 1991) at 47°N, 20°W (Atlantic Ocean) in April-May 1989. Dashed vertical line represents estimated activity (Chen et al. 1986). The evolution of " Th/ U disequilibrium with time follows that of Chi a and nitrate, confirming the observations illustrated in Figure 3. The series of profiles taken approximately one week apart permits application of a nonsteady state model to the data. [Reprinted from Buesseler et al., Deep-Sea Research /, Vol. 39, pp. 1115-1137, 1992, with permission from Elsevier Science.]...

The temperature-time superposition principle is illustrated in Figure 8 by a hypothetical polymer with a TK value of 0°C for the case of stress relaxation. First, experimental stress relaxation curves are obtained at a series of temperatures over as great a time period as is convenient, say from 1 min to 10 min (1 week) in (he example in Figure 8. In making the master curve from the experimental data, the stress relaxation modulus ,(0 must first be multiplied by a small temperature correction factor/(r). Above Tg this correction factor is where Ttrt is the chosen reference... 

In the individual compartments quasi-steady state is achieved depending on emissions, degradation rates and spatial distribution of DDT. According to the seasonality of the parameters affecting degradation rates, e.g. temperature and oxidant abundance, the compartmental burdens in steady state follow a seasonal cycle. As the sources and consequently most of the DDT mass is located in the northern hemisphere, the cycle is defined by the climate of that hemisphere. Times needed to to achieve quasi staty state in the compartments are equal in the AGG and SAT experiment, as well as amplitude and phase of the burden time series. Vegetation reaches quasi-steady state within 2-4 years, and atmosphere already within 2 years. These... 

The correlation coefficients between a 10 year monthly mean time series of volatilisation rates and SST, 1 Om wind speed and pollutant concentration are used to elucidate which of the parameters drives the volatilisation rate changes and causes the deviations from the long term mean. All of the parameters do not vary independently. Since both SST and wind speed influence the volatilisation rate in a nonlinear manner, it is not intuitive whether an increase in wind speed leads to an increase in volatilisation rate. A raise in wind speed that coincides with a decrease of the sea surface temperature can lead to a negative linear correlation coefficient between volatilisation rate and wind speed. For that reason the partial correlation coefficient is calculated in addition to the simple linear correlation coefficients. It explains the relation between a dependent and one or more independent parameters with reduced danger of spurious correlations due to the elimination of the influence of a third or fourth parameter, by holding it fixed. One important feature of the partial correlation coefficient is, that it is equal to the linear correlation coefficient if both variables... 

Landsberg, H., Time Series of Temperatures and Rainfall from Records in the Eastern U.S., Reduced to Philadelphia, University of Maryland, College Park, MD, 1975. 

Fig. 10 (a) Fluorescence image of methanol-fixed NIH3T3 cells loaded with peptide encapsulated silver clusters for 1 h at room temperature, (b) Time profile of the time series images of cell stained with silver nitrate showing the fast silver cluster emission centered in the nucleus at short times with a maximum at 320 nm. Note that black indicates an intermediate intensity level in this color scheme [57]... 

Fig. 2. Diagrams of the processes with instrumentation, (a) Schematic diagram for wastewater digester. Two temperature sensors Ti and T2 were nsed for measnre-ments. Time series were acquired from Ti and T2 was nsed for corroborating no transfer heat to surroundings by comparison with TI measnrements. (b) Schematic for the liquid-liquid heat exchanger. Note that the Bioreactor-Exchanger interconnection involves recycle streams between two feedback controlled processes.

Fig. 3. Filtered signal (solid line) and measured time series (dotted line) for the first experiment E.l (see text for details). Temperature oscillation were induced by recycle between heat exchanger and biological reactor. The filtered signal remains the oscillatory behavior of the system.

This was also done in order to attribute the temperature oscillations only to the interconnection. Time series were filtered (see solid lines in Figures 3 and 4) by low-pass filter in order to eliminate noise effects in temperature measurements (in Figures 3 and 4, the dotted line and the solid line correspond, respectively, to the temperature measurements and the filtered temperature). 

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