Scientists developed a very high resolution dataset that goes back 6 decades: TerraClimate (Nature link). I will/may be examining their data (with model stuffing) in the next few posts.
The first thing I downloaded was the srad dataset, all 8.4GB of it, from 1958 to 2021.
srad means Shortwave Radiation (to Surface).
I was a little disappointed that it only covers land. No oceans. But let’s see what we can get out of it anyway …
These numbers suggest this is solar downwelling, not Net Solar (minus solar upwelling). Also dissapointed, but will do.
If this data with model filling is true, the ~3 W/m2 difference (~179 minus ~176) over 6 decades is WAY more than could even be hypothesized by carbon dioxide warming over the last 2 centuries.
Again we see that the solar shortwave is the dominant force in all the global warming we observed.
Sorry, times up.
Best regards, -Z
P.S. No, I have no idea what happened there in the early 1970s.
Code
# Zoe Phin, 2022/06/11
# File: srad.sh
# Run: source srad.sh; require; download; extract; plot
require() { sudo apt-get install -y gmt nco gnuplot python3-xarray python3-netcdf4; }
download() {
for y in {1958..2021}; do
wget -O $y.nc "http://thredds.northwestknowledge.net:8080/thredds/fileServer/TERRACLIMATE_ALL/data/TerraClimate_srad_$y.nc"
done
}
extract() { echo "import xarray as x; import numpy as n
a=6378.137; e=1-6356.752**2/a**2; r=n.pi/180
d = x.open_dataset('1958.nc')['srad']
by_lat=(a*r/24)**2*(1-e)*n.cos(r*d.lat)/(1-e*n.sin(r*d.lat)**2)**2/59035.372
for y in range(1958,1960):
for m in x.open_dataset(str(y)+'.nc')['srad'].weighted(by_lat).mean({'lon','lat'}).values:
print(y,m)" | sed 's/\t//1' | python3 -u | tee .srad
}
parse() { awk '{ printf "%.3f %.6f\n", 1958+NR/12-1/24,$2 }' .srad; }
annual() { awk '{S[substr($0,1,4)]+=$2/12} END {for (y in S) printf "%d %.6f\n",y,S[y]}'; }
plot() {
parse > srad.mon
parse | annual > srad.ann
parse | yoy 12 > srad.yoy
paste -d ' ' srad.mon srad.yoy > srad.csv
echo "set term png size 740,740
set key outside top center horizontal
set grid xtics ytics
set xrange [1958:2021]
set format y '%.1f'
plot 'srad.csv' u 1:3 t 'Shortwave Radiation to Surface (W/m²) - 12mo CMA' w l lw 2 lc rgb 'orange'
"| gnuplot > srad.png
}
yoy() { awk '{printf "%s ",$2}' | awk -vp=$1 '{ h=p/2;
for (i=0;i<h;i++) print ""
for (i=h;i<=NF-h;i++) { s=0
for (j=i-h+1;j<=i+h;j++) s+=$j/p
printf "%8.6f\n", s
} }'
}
Zoe's Insights 
Too many posts in a row.
Can’t keep up.
I’m exhausted.
Slow down.
ha ha
R. Greene
Professional Complainers
of America
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Please don’t spam my blog.
If you’re that curious … I sent my kids to camp and have some free time. Very simple.
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That was intended to be a joke
about your sudden burst of publishing.
I assumed it would be deleted.
I recommended your blog
on one of my blogs today,
where there have been 252
page views as of 3:15 pm.
I don’t expect a thank you,
but “spam” was unfriendly.
Richard Greene
EconomicLogic@Yahoo.com
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Interesting to see that the record warm year of 1998 was a year of rather low srad to surface. The El Niño effect sure must be strong….
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This dataset is for land only. Check out net solar in this post: https://phzoe.com/2020/03/11/40-years-of-climate-change/
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Also interesting to see that El Chichon in 1982 and Pinatubo in 1991 doesn’t seem to have affected the srad that much as the srad was already low in advance…
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As always, interesting. However, I can’t replicate your results.
The JRA-55 surface solar, both upwelling and downwelling, for the whole globe, are available from KNMI:
http://climexp.knmi.nl/selectfield_rea.cgi?id=a540b44b81b320e68a33d04c5df27b66
I fear their data looks very different from yours. No clue why.
Best regards,
w.
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You can’t replicate my results of TerraClimate or JRA-55 is different from TerraClimate?
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JRA-55 also seems to contradict CERES over the last 20 years.
Clue: TerraClimate is LAND only.
P.S. I wouldn’t be surprised if fluxes have also gotten politicized!
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It would be interesting to compare your data with those in this study…too much of a headache for me 🙂
[ Edit: _https://www.arm.gov/publications/other/P012745.pdf ]
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Ha! I also think the effort to reward ratio is low. Sorry
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