7 ms·

"I'm sure you noticed how poor of a predictor rain fall is in your assessment of how much water will be added to Lake Oroville." Having worked in hydrology (in

"I'm sure you noticed how poor of a predictor rain fall is in your assessment of how much water will be added to Lake Oroville." Having worked in hydrology (in forecasting) for a year out of college -- yeah -- you might as well use tea leaves and Tarot cards. People can't even predict weather. Let alone: Snowpack + weather.

saosebastiao 10y ago
I'm not trying to diminish how difficult it is to get precise estimates...but how precise do you need? A 1ft rise in water levels is almost 5 billion gallons of water. That's a pretty big margin for error.
- Symbiote 10y ago
  The watershed for Lake Oroville is 9350 km² [1]. 5 billion gallons / 9350 km² is just 2mm. If that fell in one hour, the flow into the lake would be 5200 m³/s, except it would be lower since it takes time for the water to reach the lake. The normal flow of the spillway is 4200 m³/s. Have I done something wrong here, or missed something obvious? 2mm/hr is a pretty moderate rain. [1] https://en.wikipedia.org/wiki/Lake_Oroville https://en.wikipedia.org/wiki/Lake_Oroville
  - tbabb 10y ago
    Well, not all of it would go directly to the lake, for one. It would seep in to the ground, re-evaporate, etc.
  - Filligree 10y ago
    Not all the water (normally!) makes it to the lake, and the average rain over time is probably less than that. Otherwise, no, the math looks fine, but this is why the reservoir is useful as a flood-control system. It can take the fairly large flow caused by even moderate rain, and spread it out over time. Things get iffy once you have heavy rain for long enough that the soil saturates.
- ransom1538 10y ago
  Right. This is different. I never worked in CA hydrology during times when you worry about spill. CA Hydrology was always about allocating a very scarce resource to the people that need it most -- and offering your best prediction of how low reservoirs would go -- and praying snow pack would last. Now? W(who)tf knows.
labster 10y ago
As a meteorologist, let me offer this apology on behalf of my field: Predicting rainfall is really hard, especially in a particular location. Unlike dynamic variables like temp, pressure, or wind velocity, rainfall depends on just about every term, including sub-grid scale topography. We can have a good idea of how much total water a storm has to be precipitated, but when, where and how it falls is harder.
- irrational 10y ago
  Yeah, recently they predicted we'd get about 2-3 inches of snow in Portland, OR. We ended up getting approximately 11-12 inches.
  - foota 10y ago
    Are you familiar with this blog? http://cliffmass.blogspot.com/ http://cliffmass.blogspot.com/ it's run by a UW meteorologist.
    - irrational 10y ago
      No, never heard of it. Thanks!
  - deleted 10y ago
    [deleted]
- lisper 10y ago
  FWIW, predictions in my neck of the woods (the SF peninsula) are uncannily accurate. Rain is usually predicted with high reliability a week in advance, and we can generally rely on the hour-by-hour predictions a day or two ahead. I realize that our location is particularly easy to predict because of how our weather is dominated by the Pacific ocean, but you've got to take your wins where you can find them.
  - labster 10y ago
    Most of what you said is the opposite of what the science shows. SF is particularly hard to forecast because its weather is dominated by the Pacific Ocean (in winter at least). In other places we get reasonably reliable 10 day forecasts, but because initial data (observations) are sparse over the ocean, we have less confidence in the forecast here, long range forecasts are less likely to verify. Satellites do help, but it's not like there's a vast network of Doppler radar buoys out there y'know? Anyway, we've gotten good at this despite the ocean, not because of it. We've gotten a lot better on timing with better satellite data. But so far as precip amounts, and type? Let's just say it is not the exact science we want it to be.
234dd57d2c8dba 10y ago
Genuine question here, if predicting the weather for a localized area such as a small region Cali is "tea leaves and Tarot cards", why are we so confident in the prediction of the climate for the entire planet?
- js2 10y ago
  Q: If forecasts can’t get next week’s weather right, how can we trust predictions for decades or centuries from now? A: Weather and climate are not the same. Weather is individual, day-to-day atmospheric events; climate is the statistical average of those events. Weather is short-term and chaotic and is thus inherently unpredictable beyond a few days. Climate is long-term average weather and is controlled by larger forces, such as the composition of the atmosphere, and is thus more predictable on longer timescales. For the same reasons, a cold winter in one region does not disprove global warming. As an analogy, while it is impossible to predict the age at which any particular man will die, we can say with high confidence that the average age of death for men in industrialized countries is about 75. The individual is analogous to weather, whereas the statistical average is analogous to climate. https://www.climatecommunication.org/questions/predictions/ https://www.climatecommunication.org/questions/predictions/
  - 234dd57d2c8dba 10y ago
    Thank you, that helped quite a bit. It makes sense, as predicting when a single individual will die (a single area will have <x> weather), is different than, the observed trend is males live to avg. 75 years. Makes sense to the layman!
  - refurb 10y ago
    OK, I'm going to play devil's advocate. That answer doesn't really seem all that good since it doesn't address the predictability at all. To use the human lifespan argument, yes we can say the average lifespan for men is 75, but that's looking backwards. How good would we be at predicting future life expectancy? I'd say we're probably pretty bad at it. Also, yes, we're trying to predict the average temperature of the earth with climate models. However, that average is determined by the climate in a number of different areas. Someone please explain this to me.
marze 10y ago
The proper approach with uncertainty is an expected value calculation. That way the uncertainty regarding rain within the watershed, the temperature, etc. can all be factored in. What is missing in this nice analysis is the economic impact. If 200k were evacuated, and roughly estimating they have $100k in real estate each for housing, and say $50k each for business real estate in the flood risk area, that comes to $30B. Assuming some will not be a complete loss, say $15B in real estate loss if the emergency spillway fails (neglecting job and economic activity impacts, etc). Now if you have a 5% chance of failure in this next storm, the expected value of the loss is $750M. This value now can be used to decide how much effort should be put into emergency repairs, something less than $750M. Say these numbers are in the ballpark. Is the emergency repair effort taking place sensible? I suspect not. To avoid a loss in the billions, you'd expect a bigger effort. I'd expect every shotcrete contractor in the western US on hand, rebar being placed by helicopter, steel beams, 50 pieces of heavy equipment, temporary tanks of diesel fuel, and a real sense of emergency. Not seeing it.
- abduhl 10y ago
  What would all these folks be doing? The shotcrete takes 7 days to cure.
  - marze 10y ago
    Curing is logarithmic. News stories say they are using "concrete" today. Main point is to make an appropriate effort. Seems not too bad today, and think the storm isn't huge.
    - abduhl 10y ago
      Can you link to a news story that says they are using concrete today? What location are they placing concrete at?
      - marze 10y ago
        Sure, the emergency spillway, but not much detail: http://www.latimes.com/local/california/la-live-updates-oroville-dam-oroville-dam-repair-work-by-the-1487177768-htmlstory.html http://www.latimes.com/local/california/la-live-updates-orov...
rconti 10y ago
Actually, there are EXTREMELY good models around rainfall, snowfall, SWE, rainholding capacity, and runoff. The forecasts I see for the Sierra basically nail snow:water ratios and snow levels to within 500ft.

saosebastiao 10y ago

I'm not trying to diminish how difficult it is to get precise estimates...but how precise do you need? A 1ft rise in water levels is almost 5 billion gallons of water. That's a pretty big margin for error.

Symbiote 10y ago
The watershed for Lake Oroville is 9350 km² [1]. 5 billion gallons / 9350 km² is just 2mm. If that fell in one hour, the flow into the lake would be 5200 m³/s, except it would be lower since it takes time for the water to reach the lake. The normal flow of the spillway is 4200 m³/s. Have I done something wrong here, or missed something obvious? 2mm/hr is a pretty moderate rain. [1] https://en.wikipedia.org/wiki/Lake_Oroville https://en.wikipedia.org/wiki/Lake_Oroville
- tbabb 10y ago
  Well, not all of it would go directly to the lake, for one. It would seep in to the ground, re-evaporate, etc.
- Filligree 10y ago
  Not all the water (normally!) makes it to the lake, and the average rain over time is probably less than that. Otherwise, no, the math looks fine, but this is why the reservoir is useful as a flood-control system. It can take the fairly large flow caused by even moderate rain, and spread it out over time. Things get iffy once you have heavy rain for long enough that the soil saturates.
ransom1538 10y ago
Right. This is different. I never worked in CA hydrology during times when you worry about spill. CA Hydrology was always about allocating a very scarce resource to the people that need it most -- and offering your best prediction of how low reservoirs would go -- and praying snow pack would last. Now? W(who)tf knows.

labster 10y ago

As a meteorologist, let me offer this apology on behalf of my field: Predicting rainfall is really hard, especially in a particular location. Unlike dynamic variables like temp, pressure, or wind velocity, rainfall depends on just about every term, including sub-grid scale topography. We can have a good idea of how much total water a storm has to be precipitated, but when, where and how it falls is harder.

irrational 10y ago
Yeah, recently they predicted we'd get about 2-3 inches of snow in Portland, OR. We ended up getting approximately 11-12 inches.
- foota 10y ago
  Are you familiar with this blog? http://cliffmass.blogspot.com/ http://cliffmass.blogspot.com/ it's run by a UW meteorologist.
  - irrational 10y ago
    No, never heard of it. Thanks!
- deleted 10y ago
  [deleted]
lisper 10y ago
FWIW, predictions in my neck of the woods (the SF peninsula) are uncannily accurate. Rain is usually predicted with high reliability a week in advance, and we can generally rely on the hour-by-hour predictions a day or two ahead. I realize that our location is particularly easy to predict because of how our weather is dominated by the Pacific ocean, but you've got to take your wins where you can find them.
- labster 10y ago
  Most of what you said is the opposite of what the science shows. SF is particularly hard to forecast because its weather is dominated by the Pacific Ocean (in winter at least). In other places we get reasonably reliable 10 day forecasts, but because initial data (observations) are sparse over the ocean, we have less confidence in the forecast here, long range forecasts are less likely to verify. Satellites do help, but it's not like there's a vast network of Doppler radar buoys out there y'know? Anyway, we've gotten good at this despite the ocean, not because of it. We've gotten a lot better on timing with better satellite data. But so far as precip amounts, and type? Let's just say it is not the exact science we want it to be.

234dd57d2c8dba 10y ago

Genuine question here, if predicting the weather for a localized area such as a small region Cali is "tea leaves and Tarot cards", why are we so confident in the prediction of the climate for the entire planet?

js2 10y ago
Q: If forecasts can’t get next week’s weather right, how can we trust predictions for decades or centuries from now? A: Weather and climate are not the same. Weather is individual, day-to-day atmospheric events; climate is the statistical average of those events. Weather is short-term and chaotic and is thus inherently unpredictable beyond a few days. Climate is long-term average weather and is controlled by larger forces, such as the composition of the atmosphere, and is thus more predictable on longer timescales. For the same reasons, a cold winter in one region does not disprove global warming. As an analogy, while it is impossible to predict the age at which any particular man will die, we can say with high confidence that the average age of death for men in industrialized countries is about 75. The individual is analogous to weather, whereas the statistical average is analogous to climate. https://www.climatecommunication.org/questions/predictions/ https://www.climatecommunication.org/questions/predictions/
- 234dd57d2c8dba 10y ago
  Thank you, that helped quite a bit. It makes sense, as predicting when a single individual will die (a single area will have <x> weather), is different than, the observed trend is males live to avg. 75 years. Makes sense to the layman!
- refurb 10y ago
  OK, I'm going to play devil's advocate. That answer doesn't really seem all that good since it doesn't address the predictability at all. To use the human lifespan argument, yes we can say the average lifespan for men is 75, but that's looking backwards. How good would we be at predicting future life expectancy? I'd say we're probably pretty bad at it. Also, yes, we're trying to predict the average temperature of the earth with climate models. However, that average is determined by the climate in a number of different areas. Someone please explain this to me.

marze 10y ago

The proper approach with uncertainty is an expected value calculation. That way the uncertainty regarding rain within the watershed, the temperature, etc. can all be factored in. What is missing in this nice analysis is the economic impact. If 200k were evacuated, and roughly estimating they have $100k in real estate each for housing, and say $50k each for business real estate in the flood risk area, that comes to $30B. Assuming some will not be a complete loss, say $15B in real estate loss if the emergency spillway fails (neglecting job and economic activity impacts, etc). Now if you have a 5% chance of failure in this next storm, the expected value of the loss is $750M. This value now can be used to decide how much effort should be put into emergency repairs, something less than $750M. Say these numbers are in the ballpark. Is the emergency repair effort taking place sensible? I suspect not. To avoid a loss in the billions, you'd expect a bigger effort. I'd expect every shotcrete contractor in the western US on hand, rebar being placed by helicopter, steel beams, 50 pieces of heavy equipment, temporary tanks of diesel fuel, and a real sense of emergency. Not seeing it.

abduhl 10y ago
What would all these folks be doing? The shotcrete takes 7 days to cure.
- marze 10y ago
  Curing is logarithmic. News stories say they are using "concrete" today. Main point is to make an appropriate effort. Seems not too bad today, and think the storm isn't huge.
  - abduhl 10y ago
    Can you link to a news story that says they are using concrete today? What location are they placing concrete at?
    - marze 10y ago
      Sure, the emergency spillway, but not much detail: http://www.latimes.com/local/california/la-live-updates-oroville-dam-oroville-dam-repair-work-by-the-1487177768-htmlstory.html http://www.latimes.com/local/california/la-live-updates-orov...

rconti 10y ago

Actually, there are EXTREMELY good models around rainfall, snowfall, SWE, rainholding capacity, and runoff. The forecasts I see for the Sierra basically nail snow:water ratios and snow levels to within 500ft.