Identifying an Event based on a Jump in Rolling Variance in Python

I am trying to figure out a way, in Python, how to identify when an event occurs, based on a jump in the rolling standard deviation.

As shown in the plot below, around the 12000th sample, an event occurs. In my Python script, I am currently using a threshold of 0.00051 to signify when that event occurs. However, sometimes the event occurs at 0.0005 and other times the event occurs at 0.000495.

My question is - how can I algorithmically, in Python, detect this jump in the rolling standard deviation to create the event altert? Because if I have a threshold set too low, I don't want it to be triggered too early. And if I run another test, and the threshold is too high, then I don't want the event to not be triggered at all.

Any advice is greatly appreciated!

def animate(i):
data = pd.read_csv("C:\\Users\\Desktop\\data.txt", sep="$|$$|$",engine = 'python', header = None)
data = data.iloc[0, ::4]
data = data.astype(str).apply(lambda x: x.split(',')[-1]).astype(float)
data.pop(0)
xar = range(len(data))
yar = pd.DataFrame(data)
# Starting from sample 1050 to get rid of any initial noise
yar = yar[1050:12500]
xar = xar[1050:12500]
std = yar.rolling(window=2500).std()

if (np.any(std>.00051)):
choices = ["Confirm Event"]
reply = easygui.buttonbox("Event Alert!, image, choices)
if reply == "Confirm Event":
sys.exit(0)

ax1.clear()
ax1.plot(xar,std)
ax1.set_title('Rolling Standard Deviation')

fig, (ax1) = plt.subplots(1, sharex = True)
ani = animation.FuncAnimation(fig, animate, interval=.01)
plt.show()