I’ve moved to WordPress. This post can now be found at Did A Decrease In Total Cloud Amount Fuel The 1997/98 El Nino?##############
This post illustrates that the 1997/98 El Nino may have been fueled by a significant decrease in Total Cloud Amount over the tropical Pacific Ocean in the years (and decade) before the event.
WHY LOOK AT TOTAL CLOUD AMOUNT?
In “ENSO Surface Shortwave Radiation Forcing over the Tropical Pacific”, (2008) Pavlakis et al studied the relationship between ISCCP Total Cloud Amount data, Downwelling Shortwave Radiation (DSR), and ENSO-related SST.
The Pavlakis et al paper was discussed in my post Recharging The Pacific Warm Pool Part 2.
From that post:
Keep in mind when reading the following that shortwave radiation is visible light, with a small portion of ultraviolet, and that longwave radiation is infrared, with a small portion of microwave. Also keep in mind that visible light (shortwave) warms the top hundred or so meters of the sea…
Pavlakis et al state, “The net heat flux into the ocean is a small residual of four terms; the net shortwave radiation at the surface (NSR), the latent heat loss, the sensible heat transfer and the net downwelling longwave radiation at the Earth’s surface (NSL). The NSL is the difference between the downward longwave radiation (DLR) at the Earth’s surface and the Earth’s surface thermal emission.”They continue, “The NSR is the difference between the downwelling shortwave radiation (DSR) and the reflected radiation from the ocean surface. However, the reflected term is more than one order of magnitude smaller than the DSR, since the ocean albedo is less than 0.07. Thus, DSR dominates the net shortwave flux budget. The variability of DSR, the component of the net heat into the ocean with the largest magnitude, reflects mostly fluctuations in cloud cover caused by variations in atmospheric circulation and thus, it is very important in order to describe and study the intensity or duration of ENSO events.” [Emphasis added.]
In short, changes in Total Cloud Amount cause variations in Downwelling Shortwave Radiation (Visible Light) of the opposite sign that, in turn, cause like changes in SST and OHC. That is, a decrease in Total Cloud Amount yields an increase in Downwelling Shortwave Radiation that yields an Increase in SST. The opposite would hold true for an increase in Total Cloud Amount.
WHY LOOK AT THE CLOUD AMOUNT DATA OVER THE NORTH AND SOUTH EQUATORIAL CURRENTS?
The Pacific Equatorial Currents, North and South, flow westward from the coasts of Central and South America. With the aid of trade winds, they carry warm waters from the east and central tropical Pacific Ocean to the West Pacific Warm Pool. Figure 1 illustrates the Equatorial Pacific Temperature Gradient. This difference in SST between the East and West Equatorial Pacific causes the trade winds to flow. Likewise, the increase in trade winds causes the temperature difference to increase, until an El Nino disturbs the process. The West Pacific Warm Pool serves as the source of warm water for El Nino events.
A more detailed discussion of this process can be found at the “Frequently-(well, at least once)-asked-questions about El Nino” webpage by Bill Kessler of NOAA’s Pacific Marine Environmental Laboratory, specifically:
Therefore, if there was a difference in the cloud amounts during the years before two El Nino events, the El Nino with the lower cloud amount (resulting in higher Downwelling Shortwave Radiation and higher SSTs) before it should have the “benefit” of an additional reservoir of heat in the West Pacific Warm Pool. With a larger reserve of warm water, the El Nino with the lower cloud amount preceding it could be more significant.
The second reason we’ll look at the Total Cloud Amount data over the North and South Equatorial Currents is the Total Cloud Amount data over the equatorial Pacific contains a lot of ENSO noise, as will be illustrated.
NOTE ABOUT THE CLOUD AMOUNT DATA
The ICSSP Cloud Amount data is available through the KNMI Climate Explorer website for the period of July 1983 to June 2006. The data is noisy, so I’ve smoothed it with a 12-month running-average filter.
EQUATORIAL PACIFIC CLOUD AMOUNT ANOMALIES
Figure 2 illustrates the Total Cloud Amount Anomaly (%) of the Equatorial Pacific (5S to 5N, 145E to 90W), for the period of July 1983 to June 2006.
The three maximums in Total Cloud Amount anomaly coincide with the El Nino events of 1987/88, 1991/92, and 1997/98. Note how those peaks have approximately the same maximum values. On the other hand, note that the minimum Total Cloud Amount anomalies following the three ENSO events decreased until 1999. This relationship can also be seen in the comparative graph of Total Cloud Amount Anomaly and Equatorial Pacific SST Anomalies. Note how there was an increase in SST anomaly trend but a decrease in trend for the Total Cloud Amount anomalies.
CLOUD AMOUNT ANOMALIES FOR THE NORTH AND SOUTH EQUATORIAL CURRENTS
Figures 4 and 5 illustrate the Cloud Amount anomalies over the North and South Equatorial Currents. The coordinates used were 20S to 10S, 145E to 90W for the South Equatorial Current and 10N to 20N, 145E to 90W for the North Equatorial Current. There were decreases in Total Cloud Amount anomalies from maximum values in 1985/86 to minimum values 1997/98, with significant drops in Total Cloud Amount anomalies between 1994 and 1996.
Could these drops in Cloud Amount Anomalies have fueled the 1997/98 El Nino?
The Cloud Amount and OI.v2 SST anomaly data are available through the KNMI Climate Explorer webpage:
Middle and high cloud cover follows SST in the cold tongue very well. High clouds are considered to do more to add to the greenhouse effect than to increase albedo. Middle cloud cover depends on the region. Could this represent a positive feedback or even driver of temperature variation in the Cold Tongue?
Very interesting. Does this mean that it may be possible to forecast the strength of El Niño more than the 7 months ahead that Pavlakis et al (2008) suggest?
Willem: Assuming your question wasn't hypothetical, I can't answer it. I have no knowledge of what factors are considered by the the numerous ENSO-forecasting models.
Graciela: Glad you enjoy it.
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