Parametric plots of smoothed climate variables at Manilla
“August 2015: cooler, moister trend persists”
Fully smoothed data (red)
The last fully-smoothed data point (February 2015) completes the summer of 2014-15. This summer had a steady cooling and moistening trend for all variables except subsoil temperature, which passed through a minimum. Three of these seven variables were very close to normal: daily maximum temperature, rainfall, and subsoil temperature. Skies were rather cloudy, dew point was three degrees low (as is now usual), daily temperature range was half a degree low, and daily minimum temperature was half a degree high. These four variables all relate to moisture. Only the dew point shows low moisture: the others show high moisture, while the rainfall was normal.
August raw anomaly data (orange)
The partially-smoothed data points from March to July (uncoloured) show excursions, but the unsmoothed data point for August (orange) is close to the trend established in the summer. That is, cooler and moister. However, no variables had values far from normal.
Fully smoothed data – Gaussian smoothing with half-width 6 months – are plotted in red, partly smoothed data uncoloured, and raw data for the last data point in orange. January data points are marked by squares.
Blue diamonds and the dashed blue rectangle show the extreme values in the fully smoothed data record since September 1999.
Normal values are based on averages for the decade from March 1999.* They appear on these graphs as a turquoise (turquoise) circle at the origin (0,0). A range of anomalies called “normal” is shown by a dashed rectangle in aqua (aqua). For values in degrees, the assigned normal range is +/-0.7°; for cloudiness, +/-7%; for monthly rainfall, +/-14 mm.
* Normal values for rainfall are based on averages for the 125 years beginning 1883.
2 thoughts on “3-year trends to August 2015”
Are parametric graphs a recent idea?
I wonder if I could do a similar thing here in the UK with monthly (or daily) CET and UKP and if they would be coherent?
No, xmetman. parametric plots are used often, but seldom called by name.
In this case, the parameter is time (or date). All the climate variables vary with time, but I aim to show how one varies relative to another. In particular, how do other variables relate to daily maximum temperature? To show the passage of time, which is not on either axis, I must label the data points. Using an Excel option, I date-label key points, such as the first and the last, and those with extreme values. January points I have “labelled” intrinsically by using a square marker.
I sometimes do other variables, such as early morning dew point versus daily minimum temperature, shown here:
I always seek pattern, which usually means the data needs to be smoothed. I demonstrate how chaos can overwhelm unsmoothed data in this post:
I guess you would say that my raw data are not coherent.