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Updated : 16/10/2016

GHowSAW Cloud Type Recognition

Introduction

The methodology used here has been adapted from "Estimating Cloud Type from Pyranometer Observations" by Caude E. Duchon and Mark S. O’Malley and published in the Journal of Applied Meteorology vol 38 1998. The authors present an inexpensive and automatable method to estimate cloud type at a given location during daylight hours using the time series of irradiance from a pyranometer. Since measurements of solar illuminance are quite easy to capture using an inexpensive photo-diode system (refer to the pages on radiation in GHowSA) I thought it might be interesting to try and replicate their results.

Pyranometer response to clouds

A pyranometer measures the hemispheric broadband solar radiation and these measurements naturally integrate the effects of clouds. The concept of using a pyranometer to estimate cloud type is illustrated in figure 1 in which comparatively fast-moving clouds cross the slow moving path of the solar beam. For cloud bases at 1 km the speed of the solar beam varies from 0.07 overhead to 2.4 m/s at a zenith angle of 80°, while at a cloud base of 10 km, the comparable speeds are 0.7 and 24.1 m/s. There will be times when the cloud speed is similar to the speed of the solar beam.

Fig 1. The basis for using a pyranometer to estimate cloud type is that the clouds cross the solar beam causing fluctuations in the pyranometer readings. Fig 2.Comparison of diffuse and global irradiance for (a) a clear day, (b) a partly cloudy day, and (c) a mostly cloudy day.

With clear skies the irradiance signal is dominated by the solar beam. Diffuse irradiance is around 10-15% of the total irradiance. With variable cloudiness, the signal fluctuates principally in response to the occurrence or nonoccurrence of clouds intersecting the path between the sun and the pyranometer.
When clouds are present along the beam path, the diffuse radiation as a fraction of the signal increases and becomes nearly indistinguishable from the total irradiance in overcast skies. This is shown in figure 2 for a clear day, in which the diffuse irradiance is about 15% of the global irradiance; a partly cloudy day, where the diffuse to global ratio is variable but greater than 15%; and a mostly overcast day, where the global and diffuse irradiances are essentially equivalent. In summary, the time series of irradiance captures the character of the cloudiness weighted toward the portion of the sky where the sun is located and provides the basis for estimating cloud type.
Because the fluctuations due to clouds are in proportion to the clear-sky solar irradiance, which varies systematically during the course of a day it is necessary to linearize the estimated clear sky irradiance.

Decision criteria

Figure 3 shows the decision criteria for each of the seven cloud types. The determination of cloud-type boundaries is based primarily on a comparison of human- observed cloud types coincident with the measured irradiance parameters and secondarily on nominal values of the two parameters intuitively expected for the different categories based on the standard cloud-type descriptions. Thus the rectangular boundaries should not be considered as precise delineations.

The lower-left-hand side of Fig. 5 contains stratus, precipitation, and fog. Here the attenuation of solar radiation is high, and the variability in the irradiance signal is small. The large area of cumulus is bounded on the left by a ratio of scaled observed to scaled clearsky irradiances of 0.5 and on the bottom by a standard deviation of scaled irradiance of about 120 W/m2, which is 20 W/m2 higher than the upper-stratus boundary. In addition, there must be at least one value of the 21-min time series that has an irradiance greater than the clear-sky value, as is typical of cumulus clouds (see, for example, Fig. 3). This criterion was used to separate cumulus from cumulus and cirrus, the other large rectangle in Fig. 5. The argument is that cirrus added to cumulus lowers the general level of irradiance relative to clear-sky irradiance to such a value that the above criterion is not met. Nevertheless, the cumulus contribution continues to yield large variance.

Cirrus occupies an area with the ratio of irradiances varying from 0.8 to 1.05. A ratio greater than unity is again due to scattering of the solar beam, this time by patchy cirrus clouds. The standard deviation is low because of the thinness of the clouds and limited attenuation. The clear-sky area is defined by an irradiance ratio extending from 0.88 to 1.05 and a standard deviation of scaled irradiance less than 30 W/m2(Originally 10 W/m2 but increased to accommodate the observer standard deviation of clear sky reading). The area outside specific cloud types represents clouds of indeterminate types.

FIG. 3. Decision criteria for estimating cloud type based on the standard deviation of scaled observed irradiance and the ratio of scaled observed irradiance to scaled clear-sky irradiance

The seven original cloud types shown as coloured regions in the above figure plus and additional type of Stratus-Hazy are shown on the left-hand side of the table below. On the right-hand side are the associated human observations and the lower and upper bound limits of irradiation ration and standard deviation for each cloud type.


No Cloud
Classification
Description Lower Bounds Upper Bounds
Irradiation
Ratio
Standard
Deviation
Irradiation
Ratio
Standard
Deviation
1 Clear sky No cloud reported 0.9 0 1.05 30
2 Cirrus Any high clouds of 0.1 to 1.0 coverage 0.8 30 1.05 100
3 Cumulus Any low and/or midlevel cumuloform clouds with 0.1 to 0.8 coverage 0.5 120. 1.2 800
4 Cirrus and cumulus Any high clouds of 0.1 to 1.0 coverage and any low or midlevel cumuloform clouds of 0.1 to 1.0 coverage 0.42 100 0.95 750
5 Stratus - Hazy Any low or midlevel light clouds of 0.9 to 1.0 coverage 0,4 0 0.8 99
6 Stratus - Overcast Any low or midlevel heavy clouds of 0.9 to 1.0 coverage 0 0 0.4 99
7 Precipitation
and/or fog
Precipitation reported and/or sky obscured by fog 0 0 0.1 80
8 Indeterminate or other Multiple levels containing different cloud types 0 0 1.2 800

Methodology

Clear-Sky Model

Estimating clear-sky solar radiation is one of the primary pre-requisites of the pyranometer method. The model used by Duchonando and Malley is that developed by Meyers and Dale (1983). However, I have elected to use the Bird and Hulstrom's model from the publication "A Simplified Clear Sky model for Direct and Diffuse Insolation on Horizontal Surfaces" by R.E. Bird and R.L Hulstrom, SERI Technical Report SERI/TR-642-761, Feb 1991. Solar Energy Research Institute, Golden, CO. in conjunction with the NOAA JavaScript solar position calculator.(N.B. if using this javascript please note the reverse convention used for longitude and time zone).

Obtaining the parameters

The basis for our classification scheme is the premise that certain types of clouds have statistical properties that can be used to identify their occurrence.

The first step in the scheme is to determine the clear-sky irradiance for the date and time under investigation using the Bird and Hulstrom model. This value is then used to scale the measured irradiation to a constant value of 1400 W/m2. This scale is greater than the solar constant and should not be exceeded on a cloudless day at any latitude.

Scaled Irradiation Value = Measured Irradiance Value X 1400 / Model Clear-Sky Irradiance Value

A clear-sky irradiation model is required each day since the irradiation varies on a daily basis.

Next the mean and standard deviation of the scaled values over the preceding 20 minutes are then determined as follows.

Fig 4. Measured global irradiance and modeled clear-sky irradiance. The data are 1-min averages. Fig. 5. The solid line is the 21-min running mean and the short dashed line is the 21-min running standard deviation of the observed irradiances in Fig. 4 after they are scaled. The long dashed line is the scaled modeled clear-sky irradiance.

Figure 4 shows the unscaled clear-sky model and measured irradiance. The character of the observed irradiance in Fig. 4 reveals that beginning at about 1630 UTC there is sufficient convection to initiate cumulus clouds, which last through much of the remainder of the day. Observed irradiance greater than clear-sky irradiance is a consequence of reflection from the sides of clouds.

Application of scaling and smoothing to Fig. 4 results in the time series of the 21-min running means of 1- min-scaled measured irradiances and the corresponding standard deviations shown in Fig. 5 by the solid and short dashed lines, respectively. The rapid rise in standard deviation coincides with the development of cumulus clouds; simultaneously, the mean scaled irradiance decreases. The horizontal long dashed line is the scaled modeled clear-sky irradiance. The ratio of the running mean scaled irradiance to the scaled clear-sky irradiance and the running standard deviation of scaled observed irradiance in Fig. 5 are the two parameters used in the cloud-type decision criteria.

Figure 6 above shows a sample of my own data where between 09h30 and 11h45 the Irradiance ratio was about 0.4 with a Standard deviation of about 100 W/m2 indicating stratus clouds bordering towards cumulus or indeterminate.

The cloud regimes presented in the table and figure 5 are approximate and can be refined using regular comparison of observed cloud types and the measured mean and standard deviaation of the measured irradiation. This obviously requires consistency in the visual identification of cloud types and therefore for inexperienced users such as myself the use of photographs or images of the various cloud types is essential.(see cloud types or Clouds at TheAirlinePilots.com)

Sources

  • Bird and Hulstrom A Simplified Clear Sky model for Direct and Diffuse Insolation on Horizontal Surfaces by R.E. Bird and R.L Hulstrom, SERI Technical Report SERI/TR-642-761, Feb 1991. Solar Energy Research Institute, Golden, CO.
  • NOAA JavaScript solar position calculator.
  • Solrad.zip MS EXCEL™ VBA version of the NOAA calculator by Greg Pelletier of the Washngton Department of Ecology
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