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Why do clouds matter when we measure surface temperature from space?

By: Claire Bulgin

We can use satellites up in house to measure the surface temperature of the Earth over the land and sea.  Satellites have now been making measurements for 40+ years and these knowledge are actually useful for understanding developments in surface temperature as our local weather modifications.  Measuring surface temperature from house isn’t with out its challenges although, and one of many largest of those is cloud.

So why do clouds matter?  Basically, they block the view of the Earth’s surface from the satellite tv for pc.  If we attempt to measure the surface temperature and there’s a cloud in the best way, what we actually measure is partially the temperature of the cloud.  How a lot it impacts our temperature measurement depends upon how clear it’s, and the way excessive up within the environment it’s. 

So what do we do?  We actually solely need to measure the temperature when the sky is obvious.  This implies that we first display screen our knowledge for cloud, after which solely use the clear-sky observations.  However, this screening course of isn’t all the time 100% correct.  Some clouds are tough to identify even from house!  Consider chilly, white cloud over a chilly, vibrant snow surface as within the instance of Figure 1.  This was the winter of 2010 the place practically the entire of the UK was coated in snow in early December.   Some clouds are very tough to select above the snow surface.

 

Figure 1:  Snow and clouds over the UK on 08/12/10 in a picture from the MODIS Terra satellite tv for pc (NASA Earth Observatory, 2010). 

So what do we must do in these instances the place screening is tough?  We want to know what affect these clouds may have on our measured surface temperature.  In a latest research, we in contrast various completely different cloud screening approaches towards a cloud screening executed manually by an knowledgeable.  By trying on the variations between every cloud screening strategy and the cloud screening executed manually, and the way these differ, we can construct up an image of how a lot getting the cloud screening mistaken can introduce uncertainty in our measurement of land surface temperature.

Perhaps not surprisingly, we discover that the uncertainty in land surface temperature is increased as the quantity of clear-sky within the space we are decreases.  This is proven in Figure 2.   The left hand plot reveals that the uncertainty in land surface temperature is on common increased when solely 20 % of the sky is cloud-free (2 °C) than when 90 % of the sky is cloud free (0.75 °C). This reveals that close to cloud edges (the place a excessive fraction of the surface we are is roofed by cloud) the uncertainty in our measured surface temperature from cloud screening is increased than in areas with fewer clouds.  The uncertainties are bigger at evening as a result of cloud screening is tougher with out observations at seen wavelengths.

Figure 2: Left: Uncertainty in measured land surface temperature from clouds as a operate of the clear-sky fraction (left).  Right: The variety of observations for every clear-sky fraction (Bulgin et al, 2018).

If we select a constant share of clear-sky pixels from our pictures, we can even assess how the uncertainty varies as a operate of the underlying surface sort.  In this research we have been ready to have a look at 5 land surface varieties: Cropland, evergreen forest, bare-soil, shifting-sand and everlasting snow and ice.  We discovered that for a standardised clear-sky fraction of 74.2 %, uncertainties over snow and ice have been largest at 1.95 °C, while for cropland they have been a lot smaller, solely 0.09  °C.  The different surfaces had uncertainties between these two extremes: 1.2 °C for forest, 0.9 °C for naked soil and 1 °C for shifting sand (Bulgin et al, 2018).

References:

Bulgin, C. E., Merchant, C. J., Ghent, D., Klüser, L., Popp, T., Poulsen, C. and Sogacheva, L. 2018.  Quantifying uncertainty in satellite-retrieved land surface temperature from cloud detection errors. Remote Sensing, 10, 616, doi:10.3390/rs10040616.

NASA Earth Observatory (2010).  Snow in Great Britain and Ireland.  Images courtesy of Jeff Schmaltz, MODIS Rapid Response Team.  Accessed 29/01/21.

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