Agnodice (in ancient Greek, Aγνοδίκη) came from a wealthy family in ancient Athens. She wanted to be a doctor because she saw so many women suffering and even dying from childbirth. But Athenian law gave the death penalty to a woman who dared to be a doctor.
She cut off her hair and dressed as a man, then went to Egypt to study medicine. When she returned to Athens, she continued to pretend to be a man so she could help the women of Athens.
One day, she heard a woman crying in pain during a difficult childbirth. She went to help, but the woman refused, not wanting to be treated by a man. Agnodice revealed that she wasn’t a man, the woman accepted her help, and the treatment was successful.
Word spread among the women of Athens, who began to seek out Agnodice’s help. Before long the male doctors were put to shame. So they brought Agnodice to trial, accusing her (thinking she was a man) of actually seducing women, including their wives, who were only pretending to be sick so they could have sex with the doctor.
At the trial, Agnodice revealed that she was not a man but a woman, that she was not seducing their wives, that she was only helping them. They responded by insisting she be put to death for the crime of being a woman doctor. But by this time a large crowd of women had gathered, supporting Agnodice and pointing out that it was only because of her that so many of their children, and their wives, were still alive.
Truly shamed, they acquitted Agnodice. The law was changed.
I got another couple of subscriptions to the Climate Data Service (see the end of the post if you want to sign up), and one of them included an interesting question:
I’d also like to ask a question. I’m thinking of making a career change to data science, but am not really sure where to start. I currently work as an analyst for the Department of Defense, so I’m interested in the national security aspects of climate change as well as the human and economic changes coming. (my background is in physics so I’m not new to quantitative analysis)
How did you get your start and what would you recommend as a good path to get there? Thanks!
Regular readers know that I love to work with data. It’s what I call fun.
But this blog is about more than playing data games. It’s about global warming/climate change, and that is a serious problem, a severe threat to our future, our security, our stability, our survival. What should we do about it? By “we” I mean ordinary citizens, of the world, but especially of the U.S. I think I know the answer.
Surely some of you noticed that the area around Houston Texas suffered extreme flooding recently. At least 8 people were killed and damages ran into the billions of dollars. It was a major disaster.
People keep telling me, “You should teach!” I do seem to have a gift for explaining things in terms that can be understood. And, there are certain subjects — things people want to learn — that I know.
defendourfuture.org has some excellent videos. This one is funny:
This one’s not.
I’m glad I started the Climate Data Service, because it makes working with climate data easier. Even for me. I could access and study it before, but now it’s all in one place and one format, and the ease of use is a good motivator for closer study.
Something I’ve just been looking at is the relationship between sunspot counts and solar irradiance. I’ve used TSI (total solar irradiance) to estimate the influence of solar variations on global temperature, but reliable records don’t start until about 1976 when satellite observations began. Before that, we have to rely on proxies, of which the most common is sunspot counts. There are many reconstructions of solar irradiance which use more, but I’m not aware that any of them can be considered particularly better than the others.
The four greenhouse gases with the strongest effect on climate through their climate forcing are water vapor (H2O), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) (I’m omitting halocarbons, which come in a wide variety). We don’t control the concentration of water vapor, temperature does that. But the CO2, CH4, and N2O load is directly due to us.
I’ve just released updated data (the latter-April update) for the Climate Data service. So far, the service seems to be well-liked by subscribers.
The latest includes updates to some of the existing data fields, and new data fields have been added. The new fields are:
Field.Name Units Description
cow.way deg.C global land+ocean temperature Cowtan & Way
berk.glob deg.C global land+ocean temperature Berkeley Earth
co2.mlo ppmv CO2 Mauna Loa
co2.anom.mlo ppmv de-seasonalized CO2 Mauna Loa
co2.glob ppmv CO2 global marine surface
co2.glob.anom ppmv de-seasonalized CO2 global marine surface
co2.grim ppmv CO2 Cape Grim
ch4.grim ppbv CH4 (methane) Cape Grim
n2o.grim ppbv N2O Cape Grim
nino34 deg.C Nino 3.4 temperature
nino34.anom deg.C Nino 3.4 temperature anomaly
aod.glob global aerosol optical depth NASA
aod.nhem northern hemisphere aerosol optical depth
aod.shem southern hemisphere aerosol optical depth
pmod.tsi W/m^2 total solar irradiance PMOD
There’s not much time to get a subscription it at the low rate of $25; the price will rise in May.
So subscribe now, in two easy steps. Step 1: make a donation of $25 at donating at Peaseblossom’s Closet; Step 2: post a comment here (which I will not make public) and be sure to include your email address (so I know where to send it).