Why So Hot, So Soon?

It happens every spring. Early in the season, before the trees have grown leaves and the flowers in bloom, there is always a hot dry day. Temperatures push 90 in the New York Metro region, perhaps a week or two after a cool, damp day where the temperatures don’t get out of the 40’s. For us this year, it was yesterday Wednesday April 7. The map below shows temperatures at 4pm yesterday:



Newark and Hartford have exceeded 90 and unofficial reports from Orange County suggested temperatures of 94! But why and how? Well it has to do with trees, or in this case a lack there of.

Trees do two things that tend to reduce surface temperatures, first they reflect radiation and shade the surface and secondly they are a driver in evapo-transpiration. Let me explain.

Trees, when they have leaves and are photosynthesizing, draw moisture out of the soil and release it to the atmosphere when their stomata are open and they are pulling in CO2 (go-go introduction to biology!). In effect they act to moisten atmosphere when the sun is up. In much of the solar radiation (sunlight) that would go into heating the surface instead heats the water in the atmosphere. This is the same reason that the deserts in northern Africa are hotter than the rainforests at the equator, even though the rainforests receive more sunlight. Overall trees keep temperatures down, and increase the humidity.

So if we had had Tuesday’s weather, sometime in May when the trees were fully deployed – temperatures would have been much milder, perhaps with highs in the lower 80’s - even the sun being higher and stronger in the sky!

Another interesting effect to note on the above temperature map is the influence of the cold ocean on air temperatures. With water temperatures still below 50 in many places, when the wind blows off the ocean it acts to cool costal locations. That is why Long Island showed temperatures in the 60’s and 70’s while Newark burned up in the 90’s.

Interesting weather day in the New York Metro Region.

New Yankee Stadium Home Runs Not Necessarily Related to Weather

Yesterday AccuWeather via their blog put forth a hypothesis that the well documented increase in home runs at the new Yankee Stadium was due to a change in the stadium’s shape, allowing for west winds to enter and exit the stadium at a high speed and the proper angle to turn lazy fly balls into home runs. More specifically:

The wind on Saturday during the Yankees' 22-4 loss against the Cleveland Indians was mostly from the west at 15-20 mph. Given the layout of the stadium, the wind could have had an effect on fly balls in right field. Six home runs were hit by the Indians in the second inning alone.

Although the field dimensions of the new stadium are exactly that of the old stadium, the shell of the new stadium is shaped differently. AccuWeather.com meteorologists also estimate that the angle of the seating tiers in the new stadium could have a different effect on wind motion across the field.

Note the lack of scientific explanation for the statements in the article. Notice how many times words like mostly, could, estimate are used in the paragraphs. No modeling, or observational studies were used. Let me translate that for you into plain English, “hey we watched the game on Fox on Saturday and it sure looked like the wind was blowing the ball hard, maybe it’s the new stadium?” Look it seems like a reasonable hypothesis and all, especially watching some of those pop flies end up as home runs on Saturday, but it’s just a theory and the accuweather story struck me as being less science and more guessing. I was frustrated that a weather company would present this theory with only one games worth of wind data as as motivating observation.

So I wanted to test their theory with a bit of weather data to see if it holds any water. The methods are explained below and the study includes only six games the four versus the Indians this past weekend and two exhibition games versus the Cubs in early April. The chart shows the number of home runs hit each game, the mean direction of the wind and the wind speed. First note, only three of the six games hosted at Yankee Stadium so far had a west wind. So three of the games played so far had winds not out of the west, and often out of the opposite direction (east), which would by the accuweather theory suppress home runs. In each of these games where the wind was not out of the west, 3 home runs were hit.


Table 1. The above table shows the average wind direction, and speed for games at Yankee Stadium so far in 2009. See the methods section below for details.

During games with a west wind, 8, 6 and 5 home runs were hit, each a significant amount of home runs for a MLB game. But might these home runs be due to the players involved in the game and not the weather? I’m not a saberatician so excuse my clumsy attempt to convince you that there is just as good a chance that the HR’s were due to good offences hitting against struggling pitching as there is a chance that the wind was directly responsible for the home runs. Cleveland lead the American League in runs scored after the all-star break last year and is #2 in runs scored in this young season. During the west wind games this high powered offense was coupled with some exceptionally poor pitching. Of those three games with a west wind, two of them were started by Chien Ming Wang who has for a lack of a better word been awful both at Yankee Stadium and away so far this year. Other pitchers starting in these high home run games were Fausto Carmona (5.85 ERA in 2008, 7.87 ERA in 2009) served up 4 HR, Anthony Reyes (5.73 ERA in 2009, was lights out in second half of 2009) served up 3 HR while Joba Chamberlain (5.60 ERA in 2009 and 2.60 ERA in 2008 and arguably the best pitcher of the crew) only allowed 1 HR. Relievers who served up home runs include minor league pitcher Anthony Claggett who appeared to be overmatched, Jose Veras, Edward Ramirez, Zack Jackson and Jenson Lewis whos ERA’s range from 5.79 to 43.20 this year. Johan Santana, Tim Lincecum, Brandon Webb and Mariano Rivera these pitchers are not.

It’s too early to draw any conclusions from the weather data presented above. But it’s clear that a number of factors not related to the weather may have resulted in the home run deluge, and we can’t say for sure if the west wind is the cause of the HR deluge:

• The accuweather hypothesis appears to be at best an untested guess, not based on modeling studies or scientific observation.


• Winds have been equally out of the west as other directions, thus they can’t directly explain the deluge of runs and home runs scored over the weekend.


• More home runs have been hit when there is a west wind at Yankee Stadium than when the wind has been from the east or south.


• In the games with west winds the pitching has been poor, pitched either by pitchers who do not have demonstrated long term records of being above league average or are who are clearly struggling so far this season.


• Cleveland and the Yankees are amongst the two best offensive teams in the American League


• At this point there is not sufficient data to prove whether or not wind direction is statistically tied to home runs.

As Peter Abraham pointed out in his blog today, it’s too early to rush to judgment, the Yankees and opponents hit 20 HR in a four game series last year as well! It’s a neat theory to tie wind direction to HR production, but I think it’s irresponsible for accuweather to claim that the west wind is leading to these home runs. We’ll have to see what the numbers bare out this summer, and draw conclusions after a sufficient sample size has been drawn.

Methods. I calculated the mean wind direction, wind speed and air temperature at LaGuardia Airport from raw METAR code taken from the Plymouth State Weather Data Archive. LaGuardia Aiport was chosen to represent conditions in the Bronx due to the well documented problems with the Central Park observation site. The averages were calculated for the hours of the game, based on data taken from box scores, except during the exhibition games vs. the Cubs where length was estimated to be 4 hours.


Table 2. As per table 1, but includes standard deviation and temperature data as well.

Could a Long Island Offshore Windfarm Disrupt Weather Radars?

Above, A marks the spot of a wind farm in central Wisconsin that is disrupting weather radars, making forecasting all the more challenging. Image source: Google Maps.

Saw a great article in the Milwaukee Journal Sentinel recently about a large wind farm disrupting weather radar capabilities in central Wisconsin. We’ve talked a lot about the benefits of wind power, especially in rural areas, to generating clean electricity. Here is a demonstrated negative consequence of large wind farm installations.

The National Weather Service has issued a new kind of warning because of a Dodge County wind farm that is disrupting the agency's ability to monitor storms in southeastern Wisconsin.

The wind farm's giant turbines - each as wide as a football field and as tall as a 20-story building - are sending false storm signals to the government's weather radar system.

Weather service officials say they see no significant public safety threat, although they say the wind farm has caused radar interference and could confuse some storm watchers.

Meteorologist Marc Kavinsky said the approaching summer storm season will be the federal agency's first opportunity to gauge the wind farm's full impact.
"It'll be interesting," he said. "I'm hoping the effects will be minimal."
Located just outside the Dodge County community of Iron Ridge, the wind farm includes 36 turbines that began operating over the past few months, generating electricity for several surrounding communities.

The farm is about 30 miles north of the National Weather Service office in Sullivan, which provides radar coverage and severe weather alerts across a 125-mile radius that includes all of southeastern Wisconsin.

The meteorologist, Marc Kavinsky, who was quoted in the article has a great website demonstrating the effects of these tremendous blades on Doppler radar returns.

His key implications of the wind farms on radar returns were:

• Thunderstorm or winter storm characteristics could be masked or misinterpreted, reducing warning effectiveness in the vicinity of the wind farm.

• False signatures contaminating Doppler velocity data in the vicinity of the wind energy facility could reduce forecaster's situational awareness, particularly
during hazardous/severe weather events.

• False precipitation estimates could negatively impact flash-flood warning effectiveness.

To summarize the above, the false returns negatively affect the weather services’ ability to forecast for severe events, like thunderstorms, tornadoes and flooding rains. While this would be a major concern in the Midwest where severe weather associated with thunderstorms is common, how important would it be here in the New York region? Let’s try to anticipate the effects of a wind farm 10 miles off of the south coast of Long Island, as has previously been proposed.


The figure above shows how topography coupled with an extremely high wind farm affects weather radards. Source: National Weather Service.

The figure above shows why the wind farm in Wisconsin is so effective in disrupting the radar signals. The radar beam is tilted up, generally in the neighborhood of 0.5 to 3.5 degrees, and in this case the beam intersects the windfarm because the terrain is sloping upward along the beam path. If the ground was flat, the windfarm would go undetected by radar. How would this work in the New York region?

The NWS Doppler radar that serves the New York region is sited on Brookhaven National Lab on Long Island. A conservative estimate of the height of the Doppler radar is 250 feet above mean sea level. Using Google earth software I calculated the distance from the radar to Fire Island on the south shore of Long Island to be about 8.6 miles. Plan for the windfarm had it to be placed about 12 miles off shore, so let’s estimate the closest possible distance between windfarms and the Doppler radar to be 20 miles (even though in the planning stage the windfarm was located futher west, increasing the distance between radar and windfarm). Next step, figure out the height of the proposed windfarm. Taking the extreme of a 20 story windfarm at 15 feet a story, we come up with a height of 300 feet. With the lowest angle (0.5) of the radar, 20 miles away the beam would be about 528’ above where it started and with the highest angle (3.5) it would be 3696’ above the ground where it started. If you ignore radar beam broadening and throw in a ground elevation of somewhere near 250’ the beam would be 775’ to 4000’ above sea level by the time it reached the windfarm.

Bottom line, a wind farm 20 miles away from the Doppler Radar would require a height of at least 775’ to interfere with Doppler radars offshore in the New York region. While wind farm interference is a problem given the complicated topography of central Wisconsin, it will likely be not be an issue with an offshore farm in the New York region.

Forecasting Isn't Easy

MLB Drops the Ball, Blames Meteorologists

Don’t like the result of your decision? Blame science!

Major league baseball made a very poor decision and attempted to play a baseball game during a strengthening coastal storm and is now blaming faulty forecasts from weathermen for their poor decision.

(Last night at the World Series, Jason Werth couldn't quite make this catch at the wall, and Bud Selig couldn't quite read a radar. Image to right from yahoo, Photo by Brad Mangin/MLB via Getty Images)



Last night Game 5 of the World Series between the Tampa Bay Devil Rays and the Philadelphia Phillies was suspended in the sixth inning due to rain. This was a noteworthy moment as never before in the history of major league baseball had a world series baseball game been suspended in progress. Rapidly strengthening nor’easters are not to be trifled with, so it’s not surprise that the game wasn’t completed. Except to perhaps running major league baseball, who blamed the game suspension on poor weather forecasting. (Aside: Now you can see that I’ll take any excuse to write about baseball, as in realitly, I spend the majority of my days checking various excellent baseball blogs.)

Though Monday opened as an overcast but dry day in Philadelphia, the forecast grew progressively worse. The three meteorological agencies used by Major League Baseball all recommended to Selig at approximately 7:45 p.m. ET that there would be 1/10th of an inch of precipitation until midnight, and all parties involved voted to play.

"Given the weather forecast we had, and we had monitored it over and over again, it was a decision that we made," Selig said. "And obviously I made it with some significant trepidation, but had the forecast held, we would have been OK."

Rain began falling significantly in the fourth inning, and Selig met with the groundskeeper in the fifth inning. The sand-based field of Citizens Bank Park absorbs water well, but the condition deteriorated over the next 1 1/2 innings, prompting Welke to wave the teams off after the top of the sixth.

The only problem with mlb’s position is that the forecast was actually RIGHT, as reported by national weather online:

Commissioner, Bud Selig, cited faulty forecasts for the unfortunate premature halt of the game. He mentioned that the clearly erroneous forecasts had only called for a tenth of an inch of rain between 8 PM and midnight. For most who won't check their facts, this sounds like an atrocious error by meteorologists! But, a check of the numbers yields .13" of rain by the time the game was called. Though this means there was an error of three hundredths of an inch of rain at that time - and ten hundredths of an inch of rain by midnight when the official amount was .23" of rain, many would agree that's a pretty darn good precipitation forecast.

The weather forecast for last night called for a strengthening nor’easter to start blowing up the East Coast. Anyone who lives along the Atlantic knows that when a nor’easter is getting going, it’s a good night to stay inside with a warm drink and a nice book. Needless to say I was shocked when the game started last night. I was actually tuned into Monday night football instead of the world series because I assumed that the game was canceled. And so did Joe Posnanski:

They never should have started the game. That was obvious from early Monday evening, when a light rain began to mist in Philadelphia. The weather radars, at least according to a local weatherman who was on television in the press box, showed that a hard and cold rain was gonna fall. The TV meteorologist said that rain would start falling right around 10 p.m. Eastern time. That figured to be right around the fourth or fifth inning.

Let’s take a look at those radar images to see if we can notice anything ominous looming.



Here is the radar at 7pm, when Bud and crew were sitting around chatting about whether or not to play the game. An expansive region of light to moderate rain sits just off to the west moving slowly towards the east. Only 5 to 10 miles west of Philadelphia, a narrow filament of moderate rain appears to be building. And according to surface observations, it’s already raining in Philadelphia.



Now it’s 8pm. It’s raining lightly. Just about time for the game to start. The narrow filament of moderate rain sits just to the west of Philadephia. This filament continues to grow slowly. The large swath of light rain has moved a bit further east, now almost connecting with the narrow filament. It’s clear now that this rain will reach Philadelphia in the next hour or so. The area of rain is large, and slowly growing more intense. There is no reason to expect the rain will end anytime soon. Why start the baseball game?



Now it’s 9pm. It’s raining lightly, with a temperature of 45 F. The heavier filament of rain has pulled off to the north, which is good news. However, now the entire Philadelphia region is encompassed in the light rain shield that has moved in from the west, with heavier rain off to the southwest, slowly moving towards the ballpark. It’s not going to get any better from this point out.



Now it’s 10pm. The rain has picked up a bit in intensity, and the temperature is down to 43. The metro region is encompassed in a band of moderate rain, with more off to the southwest to come. Shortly after this Bud and company cancel the game.

You don’t need a weatherman to know which way the wind is blowing, and you don’t need three weather forecasting firms to tell you that it was going to rain more and more in Philadelphia last night. It was obvious to anyone paying attention that it was a lousy night in Philadelphia for baseball. Give us a break here. The game should not have been played.

The talking heads, baseball’s apologists on ESPN, had a slightly different take on the events:

“There’s nothing they could have done any different.” – Peter Gammons

“Are we going to see some snow on Tuesday?” – Karl Ravech
“We might!” – Tim Kurkjian

Is there hope for the rest of the world series? Here’s what mlb has to say about today (Tuesday’s forecast):

Bob DuPuy, Major League Baseball's chief operating officer, made comments after tonight's game: "The weather tomorrow is supposed to be worse."

Where are you getting that from Bob? As of 9am this morning the worst was over in Philadelphia and all that remained was a bit of light rain on the west side of the storm, that should pull out by noon or so.

Sorry Bud! This one is on you Bud, just like with the '94 strike, and the '02 all star game. You made a poor decision, accept it and don't blame weathermen.

The file drawer effect

So why post this summers climate report? Well for one, I am a meteorologist and old habits die hard. But the thing I wanted to stress was how poor our memories are when it comes to recalling previously encountered environmental conditions. When it comes down to it we often remember only the events that concur with what we expect or hope for. This preferential recollection occurs so often that psychologists have a name for it, the file-drawer effect*.

(*- I'm more impressed with myself for remembering this from Psychology 101 class in Fall 2002 in Bailey Hall, than I am with psychologist for coming up with the effect. Of course, the reason I remember this class so vividly isn't for the class itself but rather the instructor, Dr. Jim Maas. I have never in my entire life attended a series of lectures by someone who thought so highly of himself and felt the need to share this opinion with his subjects on such a regular basis. The class was practically a shrine to his achievements, including the mandatory reading of his own book. My favorie Jim Maas story however has nothing to do with the class. My friend and former roommate Bhargav had sprained his ankle at one point, and needed a ride onto campus. So we piled into my saturn and stopped outside of his building. Mass pulls up behind us, and while we are helping the obviously injured and on crutches Bhargav out of the car Maas lays on the horn, flailing his arms about wildly. The kicker was that there was room for him to drive around us. The amazing thing is that as much as I envy Mass' academic success (I mean who wouldn't, he teaches the largest undergraduate lecture in the US, has multiple books read and is a successful researcher at an Ivy League school), I would never want to be like him in a million years.)



File drawer effect, gets its name from file drawer cabinets, where in years passed researchers would dutifully file interesting research papers on topics related to their research. Researchers would pick out papers that agree with their hypothesis, and ignore or file away deeply in their drawers papers that disagreed with their hypothesis. Thus, you create a large cache of supportive papers and ignore (the occasionally massive) the collection of papers that contradict your research.

This premise materializes itself with tales of the supernatural. You may walk up a flight of stairs in your home over 10,000 times in your life. In all likelihood nothing odd will happen 9,999 times. However if one time by chance, a ball suddenly bounces down the stairs in the middle of the night, and out observe it, you will remember that freak occurrence. In fact you will almost certainly not recall the other 9,999 times when nothing out of the ordinary occurred, but then point to that one time as proof that a ghost lives in your staircase and haunts you late at night.

Perhaps this explains why the more educated you are the more likely you are to believe in the supernatural.

The 2006 study of college students, done by Bryan Farha at Oklahoma City University and Gary Steward Jr. of the University of Central Oklahoma, reached a similar conclusion. Belief in the paranormal — from astrology to communicating with the dead — increases during college, rising from 23 percent among freshmen to 31 percent in seniors and 34 percent among graduate students.

I hypothesize that as you progress in education you are trained in the art of observation, and learn to draw hypothesis and inferences from these observation. In the case of extremely unlikely occurrences, rather than attribute things to chance (which trained scientists often never do), we attribute this to the supernatural.

Well my point to all of this is don’t believe what you remember when it comes to the environment. What you remember is likely to be biased to what you want to remember. When grandpa tells you he had to walk up hill in snow up to his knees to get to school he’s probably right, that did happen. However, it probably only happened once, and he has since selectively recalled this event, ignoring all the other days that he did not walk to school in snow up to his knees.

Climate vs. Weather

I apologize for today’s short post. Today is the Stony Brook University Intramural Softball championship game, and I have to leave the office early to hold down 3rd base. Tomorrow we’ll pick back up with “serious” environmental dialogue and address the insight that this blogs only reader, Mikey P brought to the table.

Weather versus Climate
The most difficult lecture for me to give to the students in my Environmental Problems and Solutions class at Stony Brook Southampton is the lecture on Global Climate. Specifically, trying to explain to the students what the major difference is between weather and climate. Here then are the definitions of climate and weather respectively from the American Heritage Dictionary.

cli•mate n.

1. The meteorological conditions, including temperature, precipitation, and wind, that characteristically prevail in a particular region.
2. A region of the earth having particular meteorological conditions: lives in a cold climate.
3. A prevailing condition or set of attitudes in human affairs: a climate of unrest.

Climate implies a long term series of conditions, the average of which we consider to be the “climate of a region.” It’s also important to consider the expected variability associated with a region, for example in April one could expect a day with a high of 30 or a day with a high of 70, both of which are within normal bounds, neither of which alone truly describe the climate of April.

weath•er n.

1. The state of the atmosphere at a given time and place, with respect to variables such as temperature, moisture, wind velocity, and barometric pressure.
2.
1. Adverse or destructive atmospheric conditions, such as high winds or heavy rain: encountered weather five miles out to sea.
2. The unpleasant or destructive effects of such atmospheric conditions: protected the house from the weather.
3. weathers Changes of fortune: had known him in many weathers.

Weather, the definition implies atmospheric conditions at one time. The weather can vary greatly from one day to the next, whereas the climate should vary only slightly from day to day or even week to week for a region.

Anyway I bring this up because today is a good example of why we need to include a degree of variability when ascribing climate to any region. The weather map below, taken from http://www-frd.fsl.noaa.gov/mesonet/ shows the wide range of temperatures in the Northeastern US today.



Today temperatures range from a very autumnal upper 50’s in the Adirondacks, Green, and White Mountains, to the 60’s across most of Western New York and the Catskills, to the 70’s throughout most of southern New England and the Hudson Valley to more a more “seasonable” lower 80’s in New York City and Long Island. However just to the south in New Jersey and Pennsylvania temperatures are in the 90’s with high humidity – the epitome of an August day along the Eastern US coastline. And of course far to the south Tropical Storm Fay continues to subsume Florida with rain and wind.

Any way, the point of all of this is just to say that when we define climate we need to be careful to include variability in our description. Today’s cool temperatures are part of a “normal” climate for the Northeast – although one may consider this to be somewhat extreme weather. This is a good example that one could use to explain the difference between climate and weather.