I like the idea of getting wind power to market. I like the idea because wind is plentiful in the US.
Can we really harvest what we need? A few issues of concern:
1. How much do the turbine networks cost?
2. How long do they last ?
3. How quickly can they be fixed and/or replaced?
The meteorology based concerns:
1. Can the turbine handle the low level jet, especially the vertical wind shear [turbine lifetime and overall "up" time]?
2. What is the probability that tornado's and/or damaging winds will occur over the lifetime of the turbine?
3. Can the turbine handle smaller scale events which may not meet severe weather criteria but may enhance the wind shear locally [outflow boundaries]?
Wind speeds need to be greater than 6.9 m/s at 80 m*. This is easily achieved in the Central US during the severe weather season. However blocking anticyclones routinely set up for spans of 1-4 weeks throughout the summer months (June, July, August). This effectively limits summer production. Turbulence in the Low level jet also affects turbine lifetime. The Plains is a turbulent hot spot. As a general rule turbines are not made to withstand strong winds. The height of the turbine and rotational and vibrational characteristics help determine the stress experienced by the entire structure*. It is possible that non-severe winds can damage a turbine. Given the data density of even surface stations it is likely that a network of turbines put upin the Plains would have difficulty being productive.
Maintenance costs are up to 3 percent and replacing blades is 15-20 percent of the initial cost of the turbine*. A German turbine had a design lifetime of 20 years ... it lasted 3 weeks*.
*some of these facts were found on the Danish Wind Industry web site.
A weather, education, and science blog run amok. Brought to you by James Correia, Jr., PhD. I have a BS from SUNYA in Atmospheric Sciences, MS from FSU in Meteorology, and a PhD from ISU in Agricultural Meteorology. I specialize in mesoscale numerical weather prediction on scales larger than 4km for both forecasting and regional climate. The views expressed here do not reflect those of NOAA, the NWS, or the University of Oklahoma.
Sunday, July 27, 2008
Sunday, July 20, 2008
math education
http://www.cnn.com/2008/LIVING/wayoflife/07/18/renegade.math.parents.ap/index.html
I am a renegade math parent. I find it difficult to grasp that the author of this article did not challenge the use of calculators in grade 4. There is a time and place for conceptual understanding and elementary school is not it. Math is nice and simple and mechanistic. There is a method for solving problems using pencil and paper. If Math is to be truly intuitive then you need a database of problems (memorizing multiplication tables). This sets the stage for learning through Algebra. The first real conceptual problems arise in geometry.
The idea that the same problem can be solved in multiple ways works only for speed. Choose the fastest method for solving. this works in the grocery store, but hardly anywhere else. Concepts are usually for applied math, like chemistry or physics, or biology.
I would argue that stopping the focus on politically correct and confusing word problems is the first step. Concentrate on real world problems if you must. But keep the focus on building the database. The key to quality education is to provide math and its applications; keep them at the same pace; make the classes build together. the more you see it, the better you learn it.
Tis is fundamentally why calculators are so bad. they just punch numbers. why have the mental database when you have a calculator. Soon enough it becomes commonplace that mechanics are learned rather than the material.
I am a renegade math parent. I find it difficult to grasp that the author of this article did not challenge the use of calculators in grade 4. There is a time and place for conceptual understanding and elementary school is not it. Math is nice and simple and mechanistic. There is a method for solving problems using pencil and paper. If Math is to be truly intuitive then you need a database of problems (memorizing multiplication tables). This sets the stage for learning through Algebra. The first real conceptual problems arise in geometry.
The idea that the same problem can be solved in multiple ways works only for speed. Choose the fastest method for solving. this works in the grocery store, but hardly anywhere else. Concepts are usually for applied math, like chemistry or physics, or biology.
I would argue that stopping the focus on politically correct and confusing word problems is the first step. Concentrate on real world problems if you must. But keep the focus on building the database. The key to quality education is to provide math and its applications; keep them at the same pace; make the classes build together. the more you see it, the better you learn it.
Tis is fundamentally why calculators are so bad. they just punch numbers. why have the mental database when you have a calculator. Soon enough it becomes commonplace that mechanics are learned rather than the material.
Reflection
Before my memory fades, I wanted to recall who got me into science fully.
1. Dad waking me up early to watch the Space Shuttle launch.
2. High school: Mr. Arpaia (sp?) demoted me to sub "college track" generalscience for the start of 9th grade. I was not pleased, but my slacker mentality landed me there and I think he knew I couldnt a swift kick to the head. Mrs. Rierra very quickly moved me back to college track where I continued to do well in her class. Mrs. Beattie in biology kept me in college prep but moved me up again for chemistrywhereIstarted to appreciate that I was indeed capable of being intelligent. It also made me believe I was smart ... something I would later need to achieve in college again.
there also were the other outstanding teacers I had: Mrs. Altieri, Mrs Ploski, Ms Nicholari, Mrs. Stellavato, Mr. Moriarty, and possibly others.
Ms Nicholari: "Jim, you have put us all to sleep with your monotone reading." her honesty made me take seriously my enrollment in the Dale Carnegie Public speaking class.
Mrs Stell: her honest, fun, inspiring classes were great. her personality really shined through,and her passion was obvious and most appreciated.
Mrs Ploski: Always happy, always proud, and very much able and willing to pass out compliments. Algebra with her was my favorite all around class.
Mrs. Altieri: funny, smart, and a great teacher.
Mr. Moriarty: A great guy. Inspiring and passionate. Someone who was animated, intelligent, and encouraging.
3. College: Dr. Vince idone, Dr. Lance Bosart, Dr. Ray Arritt, Dr. Eyad Atollah, Dr. Sheryl Honikman, Dr. H. Richter, Dr. B. Hornbuckle, Dr. S. E. Taylor, Dr. Paul Ruscher, Dr. James O'Brien, Dr. N. LaSuer.
All of these people were inspiring and motivational. They were/are dynamic, down to earth, approachable and available. They all had something encouraging to say or share, or they were able to impart some of their passion and pass on wisdom. I am lucky Ihad them as teachers. I am also lucky because having been taught by the best I have tried to acquire those same skills. Ilook forward to the day when I can teach again.
4. the storm chase. nothing better than putting your skills to the test. Its refreshing to get out and chase and put your skills to the test. A good challenge is very motivating and inspiring. Mother nature always puts on a show worthy of quantatative and qualitative analysis and enlightenment.
1. Dad waking me up early to watch the Space Shuttle launch.
2. High school: Mr. Arpaia (sp?) demoted me to sub "college track" generalscience for the start of 9th grade. I was not pleased, but my slacker mentality landed me there and I think he knew I couldnt a swift kick to the head. Mrs. Rierra very quickly moved me back to college track where I continued to do well in her class. Mrs. Beattie in biology kept me in college prep but moved me up again for chemistrywhereIstarted to appreciate that I was indeed capable of being intelligent. It also made me believe I was smart ... something I would later need to achieve in college again.
there also were the other outstanding teacers I had: Mrs. Altieri, Mrs Ploski, Ms Nicholari, Mrs. Stellavato, Mr. Moriarty, and possibly others.
Ms Nicholari: "Jim, you have put us all to sleep with your monotone reading." her honesty made me take seriously my enrollment in the Dale Carnegie Public speaking class.
Mrs Stell: her honest, fun, inspiring classes were great. her personality really shined through,and her passion was obvious and most appreciated.
Mrs Ploski: Always happy, always proud, and very much able and willing to pass out compliments. Algebra with her was my favorite all around class.
Mrs. Altieri: funny, smart, and a great teacher.
Mr. Moriarty: A great guy. Inspiring and passionate. Someone who was animated, intelligent, and encouraging.
3. College: Dr. Vince idone, Dr. Lance Bosart, Dr. Ray Arritt, Dr. Eyad Atollah, Dr. Sheryl Honikman, Dr. H. Richter, Dr. B. Hornbuckle, Dr. S. E. Taylor, Dr. Paul Ruscher, Dr. James O'Brien, Dr. N. LaSuer.
All of these people were inspiring and motivational. They were/are dynamic, down to earth, approachable and available. They all had something encouraging to say or share, or they were able to impart some of their passion and pass on wisdom. I am lucky Ihad them as teachers. I am also lucky because having been taught by the best I have tried to acquire those same skills. Ilook forward to the day when I can teach again.
4. the storm chase. nothing better than putting your skills to the test. Its refreshing to get out and chase and put your skills to the test. A good challenge is very motivating and inspiring. Mother nature always puts on a show worthy of quantatative and qualitative analysis and enlightenment.
Sunday, July 13, 2008
random thoughts
1. sometimes we give to each, expecting to get something in return
2. sometimes we give to each, hoping to receive anything (no matter how minute) in return (probably a sign of respect, a thank you)
3. sometimes we give to each other because we owe a debt which can never be repaid and even if we did try to repay it, it would refused. sometimes this is what people call "pay it forward".
its important to teach these principles and teach when to use these principles. Hopefully option 2 increases with age while option 1 decreases. option 3 needs some help. I see it sporadically. I felt like I did option 3 by teaching ... i hope to get back to that soon.
2. sometimes we give to each, hoping to receive anything (no matter how minute) in return (probably a sign of respect, a thank you)
3. sometimes we give to each other because we owe a debt which can never be repaid and even if we did try to repay it, it would refused. sometimes this is what people call "pay it forward".
its important to teach these principles and teach when to use these principles. Hopefully option 2 increases with age while option 1 decreases. option 3 needs some help. I see it sporadically. I felt like I did option 3 by teaching ... i hope to get back to that soon.
Monday, July 7, 2008
back to modeling
The return to modeling. I have worked extensively with cumulus parameterization schemes in mesoscale and now regional climate models. No matter how good they do, there are serious known limitations to the physical schemes. The problem is that most people do not do a very good analysis on the known unknowns (the things we know we don't know) or at least the characteristics that have not been examined yet.
Cumulus schemes transport heat and moisture (vapor, microphysical species, and rain) from the lower levels to the upper levels of the atmosphere. They do not typically involve momentum transfer though there are always exceptions.
Cumulus schemes do NOT have:
1. sufficient variability to handle tropical or intense midlatitude convective heating,
2. sufficient resolution to handle MCS stratiform cloud shields including the associated coupled heating-cooling vertical dipole,
3. universal trigger function that works in the topics and midlatitudes,
4. can not generate significant heavy rainfall unless numerous non-physical scheme activations occur.
Furthermore, my work clearly shows that PBL temperature and moisture biases exist depsite resolution (4 vs 8-50 km). Vertical velocity is DAMPED when a cumulus scheme is used, not because the instability is being removed but because the cumulus scheme barely counters the destabilization, thus the vertical velocity distribution does not expand.
The cumulus scheme's are heavily untested at fine grid spacing. Good simulations with a cumulus scheme do not mean the cumulus scheme was either the cause of success or failure.
I think we need to ask the following:
1. What unique properties of a cumulus scheme contribute to the succesful components of a good forecast?
2. How does the cumulus scheme interact with other physics?
3. How does a change to the cumulus scheme impact the simulation?
4. What is the tendency of a particular series of changes to a cumulus scheme?
I would also urge that anyone using a cumulus scheme that wants to nest to fine resolution: use it to drive a seperate model run. You dont want cumulus tendencies going through multiple domains in a nested two-ay or one-way feedback.
Nesting in my opinion is not a proven concept until some more work on physics is completed. Early nesting used simple CPSs on the outer coarse grid. CPSs have been known to corrupt daughter nests. User beware.
Cumulus schemes transport heat and moisture (vapor, microphysical species, and rain) from the lower levels to the upper levels of the atmosphere. They do not typically involve momentum transfer though there are always exceptions.
Cumulus schemes do NOT have:
1. sufficient variability to handle tropical or intense midlatitude convective heating,
2. sufficient resolution to handle MCS stratiform cloud shields including the associated coupled heating-cooling vertical dipole,
3. universal trigger function that works in the topics and midlatitudes,
4. can not generate significant heavy rainfall unless numerous non-physical scheme activations occur.
Furthermore, my work clearly shows that PBL temperature and moisture biases exist depsite resolution (4 vs 8-50 km). Vertical velocity is DAMPED when a cumulus scheme is used, not because the instability is being removed but because the cumulus scheme barely counters the destabilization, thus the vertical velocity distribution does not expand.
The cumulus scheme's are heavily untested at fine grid spacing. Good simulations with a cumulus scheme do not mean the cumulus scheme was either the cause of success or failure.
I think we need to ask the following:
1. What unique properties of a cumulus scheme contribute to the succesful components of a good forecast?
2. How does the cumulus scheme interact with other physics?
3. How does a change to the cumulus scheme impact the simulation?
4. What is the tendency of a particular series of changes to a cumulus scheme?
I would also urge that anyone using a cumulus scheme that wants to nest to fine resolution: use it to drive a seperate model run. You dont want cumulus tendencies going through multiple domains in a nested two-ay or one-way feedback.
Nesting in my opinion is not a proven concept until some more work on physics is completed. Early nesting used simple CPSs on the outer coarse grid. CPSs have been known to corrupt daughter nests. User beware.
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