More AQUA StuffA

AQUA satellite data is not a particularly long set and with the gaps it does have issues. The chart above AQUA ocean surface temperature for the length of the series is adjust to anomalies showing seasonal variation. When the sun is in the southern hemisphere, the ocean warms more and it cools more in the southern winter. Nothing shocking about that. There appears to be a slight downward trend, but not much. To compare years, I averaged each year of the series produce an "average" season, short record, not much significance in that, just something to look at.

As you can see in the first four years, "average" is not something we can expect very often. Each year has significant variations. I did at a mean value line so that general warming or cooling for the whole year versus "average" can be seen. 2006, is the year before the great Arctic Ice Melt. It was warmer than previous years, but not by much.

Following the great ice melt, things keep on keeping on. The temperature variations increased likely to the ENSO, but the range of change is within +.06 and -0.1 degrees. I may make more comparisons of other channels with the "averages". What would be interesting is a comparison with cloud fraction.

Building a Better Model - Data Issues

I doesn't matter how elaborate a model you build of the atmosphere, if you can't verify it with data it won't fly. When you have so much data with so many conflicts and you are looking for extremely small changes, you may need a model just to determine which data is meaningful and which leads down a rabbit hole. So this is a first attempt to generate a little different twist on the satellite data to help isolate issues with the different data sets.

The Aqua data is short and has gaps. The data started in 2002 and is current, but the channel 4 data bit the dust and there are gaps in the other channels. The data is in degrees Kelvin for different atmospheric pressure levels. Channels adjacent to each other likely have some error due to proximity, so leap frogging one or more channels should reduce that error. This is a chart for channel 5 the 600millibar layers (approximately 4.3 kilometer altitude) and the 50 millibar layer, (approximately 50 millibar).

On the chart, the blue curve is an approximation of the flux imbalance between the two layers. By converting the temperature value of each layer into perfect black body flux values using the Stefan-Boltzmann relationship, the subtracting the channel 5 flux equivalent from the channel 10 flux equivalent. This was then modified to an anomaly by subtracting the average of the entire range from the daily values. Where there are gaps in either data set, those days are left blank and skipped in the plot. The orange curve is an approximation of the emissivity for the ch. 5 600 mb layer to the ch. 10 50 mb layer. This plot uses the right y axis scale. The calculation for the emissivity is flux equivalent of the ch 10 data divided by the flux equivalent of the ch. 5 data.

The emissivity of a perfect gray body should approach 0.5 unless my estimates are completely screwed up. Deviations from 0.5 should indicate that energy is converted into work, passing through the medium without interaction, being transported by other than radiant means, or something is wrong.

The limited data indicates that the emissivity between layers is above 0.5 and slowly approaching a value closer to 0.5 and that there is a fairly large seasonal swing in the flux difference between layers with than difference reducing with time. Warmer years have higher positive values. with the average reducing, that would indicate that at least for the short term that there will be some reduction in the average temperature of the 600mb layer. The fit of the two curves is very close since they are based on the same flux relationship. There is some interesting difference in the peak and valley correlation. At the peak, both the estimated imbalance and the emissivity plateau at the same relative locations. In the valleys, emissivity decrease reduces faster than the estimated flux imbalance. This may indicate that convective cooling is taking a larger role relative to radiant cooling at or below the tropopause. The valley difference may indicate a return to radiant control of cooling in the media between the two layers.

The change in the estimated emissivity is most interesting. Changes in the minimum local emissivity due to mixed phase clouds, primarily in the Arctic, cause considerable uncertainty in the energy budget estimates. With more complete data, (using surface to 150mb and other AQUA channels) plus a longer data series, better estimates of the impact of minimum local emissivity variation may be determined.

The data used was taken from the Discover AQUA site and transferred to a spreadsheet. There may be errors in the charts due to transcription errors or brain farts. The purpose of the chart is just to show a potential application of the AQUA data for atmospheric physics hobbyists.

This chart compares the approximate emissivities of the 600mb channel 5 to the higher channels up to channel 11 at 25 kilometers and 25 millibar. If Channel 4, the lowest troposphere level were available it would have the highest emissivity value. These are relative emissivities which could easily be called transmittance. Each higher layer transmits less of the emission from the channel 5 layer. So if channel 5 emits 300Wm-2 and channel 10 emits 100Wm-2, 100/300 would be .33 or the amount of channel 5 energy emitted by channel 10. Two thirds of the channel 5 energy may be emitted to space. Of course, all the energy from the higher layer need not originate at the channel 5 layer, portions could be due to short wave absorption in the atmosphere above channel 5. However, the channel 5 layer is moist an likely close to the maximum radiant layer. There is only a short section of the channel 4 layer, but I will dig that out for a comparison.

Agricultural Impact on Climate, Real and not so Real

More than one experimenter has been fooled by his own data. The world's energy problems were solve by a team of researchers at the University of Utah when they discover cold fusion. That was until they found out that their data had fooled them. Measuring temperature can be tricky.

With a significant percentage of the surface of the Earth altered by mankind to produce food, shelter and ease of transportation, that should have an impact on climate. After all, CO2 is supposed to only make a 1 percent change, a 10 percent change or better in land use should have and impact greater than CO2. Some scientist agree than land use is responsible for most of the warming, some disagree. They are all good scientists, why would there be any disagreement?

Because numbers lie.

Anyone that has ever attempted to garden knows the value of mulch. It looks great when you first install it, it slows down the growth of weeds so it looks better longer, it retains soil moisture so you don't have to water as often, and it regulates the soil temperature. The mulch can be black, that nifty red looking stuff, honey colored hay, various shades of brown or even some goofy custom color to match your house color. No matter what color, it still does the job.

Forests tend to prefer the natural color mulch which is darker brown to nearly black. Most farmer don't use mulch. So if farmers remove trees and brush to build farmland, the natural mulch is turned into the soil. The temperature over the farmland will be warmer than the temperature over the forest floor and not just because of the shade from the trees.

Mulch, despite the chosen color is an insulator. The air trapped in the loose mulch warms before the soil and convects heat away from the dirt. Dirt is an insulator, but not as good as mulch. More heat is absorbed by the deeper soil uncovered by mulch than that covered. That is a good thing for seed germination,but it tends to increase evaporation of water from the soil. The more heat that is absorbed, the more watering that is required. Remember, that is another reason gardeners like mulch.

So soil temperature will be higher in the day time without mulch. The soil will release more of that heat at night because mulch is a better insulator than soil. This has a real and a not so real impact on the average global temperature.

The real part is that the soil absorbs more energy which is measured as increased temperature. The unreal part, is that the flow of energy and reflection of solar energy impacts the temperature measurements more than the air that is attempted to be measured.

Great pains are taken to make sure that the housings of the surface station temperature measurements are consistently white, so that they absorb a uniform amount of direct solar energy. Then that very scientifically designed instrument is mounted on a pole. In most areas, that pole is now galvanized metal. In some areas it may be pressure treated lumber. It others it may be a neat bracket. The choice makes a difference in the measured temperature.

Take a few of the new digital weather stations with the neat white beehive vented housing. Mount one on a black metal pole, one on a natural wood pole and one on a wooden pole painted white. Would there be any difference in the temperature measured? Now set each a white sheet under each, would there be a temperature difference?

So you see, hopefully, part of the issues with direct measurement of surface temperature.

What generally defines the energy absorption of the surface is the albedo or the reflectivity of the surface. What defines the impact of the albedo is the retained energy. A black surface that does not retain energy has little impact on climate by a great deal of impact on temperature measurement. This is the issue with determining how much impact agriculture has had on climate. The albedo change says not much. The difference in retained energy says a whole bunch. So a more accurate measurement of climate change would be soil temperature below the surface. That is not on the list of priorities, so the next best measurements are sea surface temperature and ocean heat content.

The moral of this story is take all measurements with a grain of salt. Everything measured needs verification if it is to be relied upon.