Understanding diurnal cycles

One of the simplest and most predictable patterns in meteorology is what is called the "diurnal cycle", meaning the cycle of what happens every day.  Our weather is governed by the sun, so naturally the sun's rising and setting creates a repeated cycle of events every day.  Here's a 24-hour meteogram for several important weather variables at my weather station from several days ago:

Nighttime hours (between sunset and sunrise) are shaded in light gray.  This meteogram shows a time when we had quiet synoptic-scale conditions here in Seattle--no real fronts or troughs or anything like that coming through.  Just quiet weather.  Let's look at each of these variables individually.

Temperature -- Temperature is shown in the red curve of the top panel.  You can see that the high temperature was reached at about 4:30 PM, after which the temperature began falling pretty steadily.  This steady fall continues overnight until we hit our low temperature of 51.3 degrees Fahrenheit.  Notice when this temperature occurs--right about at the time of sunrise.  It's a common misconception (or, at least I've heard it from many people) that the middle of the night is the coldest time of the night.  Not so!  If you think about the sun as our source of heat, as long as there is no sun, we'll continue to cool.  So temperatures won't warm up again until after the sun has started to come up.  In the meantime, the earth continues to radiate away energy, continuing to cool us all throughout the night.  In fact, even after the sun comes up, it still takes an hour or so for us to be receiving enough energy from the sun to outweigh the energy the earth is radiating away.  As you can see, the temperature doesn't really start increasing again until about an hour or so after sunrise.

Dewpoint--Dewpoint temperature (in green in the top panel of the chart) is one of the few variables that really doesn't have much of a diurnal cycle.  If I had to give it a diurnal effect, I'd suspect that during the day the dewpoint might increase a little because more heat means more water evaporates, increasing the moisture content of the air.  Overnight, though, unless we cool down to the dewpoint and start condensing water out of the air, there's really nothing for the dewpoint to do.  So, overall, we do see a general, gradual increase in the dewpoint throughout the period.  However, I don't see much of a diurnal cycle here.

Wind--The wind speed is shown by the shaded light blue area in the second panel down.  The wind direction is given by the little triangles (with the legend on the right side).  Now, my weather station is very poorly sited to get accurate wind measurements (more on that in another blog post).  So I don't trust these wind measurements much, particularly the wind direction.  But in looking at wind speed, we do see part of a typical diurnal cycle.  During the daylight hours, we generally do see a light breeze--in this case, between 1-2 mph.  However, notice that right after the sun sets, the wind speed drops to zero and stays there all night.  This is a very typical diurnal cycle for the wind.  In a previous blog post, I described how a low-level inversion develops overnight as the surface cools.  This stabilizes the near-surface air and inhibits vertical mixing.  While above this inversion the winds tend to increase in speed as night falls (see my previous post on the nocturnal boundary layer wind maximum), below the inversion the winds drop to near calm.  We see this above.

Another, more subtle way of seeing this nocturnal inversion developing is in the temperature curve.  Look closely at the difference between how the temperature curve looks during the day and during the night.  See how during the day the temperature curve is rather "squiggly" with little bumps going up and down?  In contrast, during the evening and overnight, the temperature curve is very, very smooth without those bumps or wiggles.  The bumps and wiggles of the temperature curve during the day show vertical mixing with the air above. Typically, during the day, the temperature cools off with height as you move away from the surface.  This makes the atmosphere more unstable.  The more unstable the air becomes, the easier it is for air to move up and down.  Little pockets of cooler air from slightly above the surface are sometimes brought down to the surface in gusts of wind.  This causes the temperature to drop a little bit before later recovering.  So those bumps and wiggles mean vertical motion is going on.

However, at night, we cool off at the surface faster than the air cools off above.  This creates a temperature profile that warms with height--a very stable profile (the nocturnal inversion).  As the air becomes more stable, it becomes much harder for there to be any vertical motion.  As such, the occasional intrusions of air from above with a different temperature basically stop.  Without these intrusions, there are no wiggles in the temperature trace--the temperature can cool evenly.  It's pretty neat that you can see this difference.

Pressure--This is another little-known diurnal cycle.  It turns out that our air pressure, which is usually considered to be a rather robust variable, also has a pronounced diurnal cycle.  It's sometimes hard to see this cycle during periods of very active weather synoptically--when a strong surface low is nearby, the falling pressure signal from the approaching surface low overwhelms this diurnal cycle.  But, it's easy to see when the weather is quiet.  It's also quite easy to see in the tropics.

So what makes the pressure diurnal cycle?  Notice that we have a minimum in pressure around 5:00 PM--slightly after we reached our high temperature during the day.  Why is this?  As air warms during the day, it expands and its density decreases.  As the air molecules get further apart and the density decreases, the pressure also tends to decrease.  So, the heating during the day causes the air to expand and the pressure to tend to fall.

During the night, the opposite happens.  As the near-surface air cools, it compresses and becomes more dense.  As you might expect, this tends to increase the pressure.  We see that in the diagram above--starting at sunset and continuing through the night, the pressure rises rather significantly.  It actually continues rising into the next day after the sun comes up.  Only after the air has started really heating up does it start falling again (at around 9:00 AM in this diagram).  So the pressure diurnal cycle kind of mirrors the temperature diurnal cycle, only lagged by a little bit.

Now when you're looking at weather patterns during the day, things should make a little more sense.  We can see how the winds calm and the pressure starts rising during the evening.  We can see how the winds start picking up and the pressure starts falling by late morning.  We can also see evidence of an increasingly unstable or stable layer near the surface by what the winds are doing or how the temperature profile looks.  Pretty good for a quiet weather day.

Fallout from the storm...and a rebuttal

It's been a week and a half since my last post, as I've been on vacation in northern California during that time.  But what a week to miss--a strong hurricane moving up the east coast with lots of media hype surrounding this storm.  I wanted to just briefly cover some highlights of the fallout from this storm by looking at what other people are saying.

1) Irene caused/is causing major flooding across much of the northeast.
As seen here:

 Much of the northeast remains under flash flood watches or warnings.  It's not completely safe to be out there just yet.  In the coming days we'll see the true extent of the damage caused by the storm.  The highest rainfall amount (so far) as reported by the NWS was in Bunyan, NC with 15.66 inches of rain.  However, greater than 10 inches of storm total precipitation was also reported in Virginia, Maryland, Delaware, New Jersey and New York.

2) Irene brought near-record storm surge to the Chesapeake Bay region.
Surge heights of 7.5 or 7.63 feet were reported near Norfolk at their peak.  This is only a few inches shy of the 7.89 foot record set by Hurricane Isabel in 2003.  Since storm surge height is often used as one proxy for the "strength" of a storm, this indicates just how significant of a hurricane this was for the east coast.

3) Radar images along the coast showed excellent detail of the storm as it passed over.
This is just a subject that I happen pay attention to.  Some of the newly-updated dual-pol NEXRAD radars got glimpses of this storm.  Since I've really only seen dual-pol products applied to severe thunderstorms and snowstorms, it will be interesting to see what dual-pol can do for hurricanes.  If you have liked my previous radar interpretation blog posts, then I recommend this post by Patrick Marsh (everybody's favorite graduate student) about interpreting wind fields in the near-hurricane environment from doppler radar.

4) The hype surrounding this storm is generating a lot of press...about the press.
I'm told that the network news coverage of this event was pretty spectacular and omnipresent.  There was no escape from it.  Being on the road most of the time, I didn't get to witness it.  But, several news outlets are wondering if the media went too far--or did just fine.  I suppose it depends on your viewpoint.  I have a feeling that had the storm been worse than predictions that we'd then get complaints that there was not enough warning, we were caught completely off guard, and so on.  Actually, based on the numbers above, I don't think that, at least for the meteorological community's part, this was over-hyped.  By the media, perhaps.  But I think the meteorological community did well.

5) Budget cuts to the weather service?
Of course, in the midst of all this, a few articles did come out both supporting and criticizing the NWS.  Some articles, like this Huffington Post article, highlight the impeding budget cuts to the National Weather Service and NOAA satellite programs.  They argue that our aging weather satellite fleet would be in danger of falling apart over the next few years if the program lost money.  We depend on weather satellites for so much of our observations in meteorology today that it's almost unthinkable that we'd let such a valuable tool disappear for budget reasons.  As the article points out, we have almost no observers taking weather readings out on the open ocean.  But that's exactly where hurricanes form and develop, and exactly where we need the observations the most.  Satellites are our greatest tool to fill that immense data void and without their observations, our hurricane models (and even our everyday global weather models) would be reduced to shots in the dark.  The GOES-R series, due to be launched in the next few years, has significant technological upgrades and much higher resolution than our current satellites.  With this GOES-R series, we have replacements for our aging satellite fleet in the works.  It would be one of the most short-sighted and foolish things I can think of to cut the program off now.

6) Fox News's "Do we need a national weather service?" editorial
This article has been receiving a lot of buzz (at least among my friends and colleagues in the meteorological community) over the past few days.The article criticises the NWS as a "relic of America's past that has outlived [its] usefulness."  The editorial writer argues that private companies provide better forecasts than the NWS and that cutting the NWS's budget by $126 million to levels of almost a decade ago wouldn't have any serious effects.

I believe this position represents an extremely limited vision of what the National Weather Service does, limiting it to just "forecasts".  It's true that private companies can often provide better forecasts on a point-by-point basis than the National Weather Service (NWS).  There is a thriving private sector in meteorology that makes serious money off of specialized and localized forecasts.  These companies can run high-resolution models and conduct internal research to improve their forecasts.  All of this is definitely doable by the private sector and I'll even admit--the forecasting aspect of the NWS is probably its most expendable feature with respect to the private sector's abilities.

But let's consider some of the other roles of the NWS.  Let's take those high resolution models that private companies run.  Let's step back to the very first step of the forecasting process.  To do any sort of model, you need to have initial conditions.  We have to know what the atmosphere is like now (and how it has been recently) to be able to look into the future.  We know this by looking at observations.  How many types of observation platforms are managed by the NWS and its parent organization NOAA?

• Weather satellites (GOES, POES, MODIS, and a suite of other specialized satellites)
• The NEXRAD doppler radar network (jointly with the FAA and the DoD)
• All upper-air sounding stations (weather balloons)
• River level gauges
• METAR observation stations at airports (jointly with the FAA)

And that's just a sample.  Almost our entire supply of upper-air observations and most of our surface observations come from the NWS or NOAA in some form or another.  Without these observations, no forecaster would be able to do predictions anywhere near as accurately as we do now.  No model would be able to get anything close to thunderstorm initiation or rain-snow dividing lines correct without this data.  We'd just maybe get the overall pattern correct over the next few days--sometimes.  All of our current weather prediction--be it public or private sector--depends on data from the NWS and NOAA.

One might argue that all of these data information services could be privatized.  We do have a couple examples that I know of where this has happened. The National Lightning Detection Network (NLDN) is administrated by the Vaisala Corporation.  Ever wonder why we don't see more lightning maps around, particularly in real-time?  Vaisala charges customers for access to lightning data in near-real-time, and those that buy it are prohibited from publicly releasing it until after a certain latency time (unless they pay more).  Another pay-for-data model has been adapted by the European Centre for Medium-Range Weather Forecasts.  I usually don't show many ECMWF model graphics and you won't find many detailed ECMWF model output images online either.  Once again--the ECMWF community charges people in non-member nations for their model output.  As such, even though they have one of the most advanced modeling systems around, we don't see much of their output online.  That is, unless you happen to belong to an organization that pays for this data.

My point is, we do have instances where private or near-private entities are controlling weather observations and model output.  In these cases, there is invariably a fee involved in accessing the data--that's how the private sector makes its money.

This is actually one of the things that worries me the most about eliminating the public sector from weather forecasting.  From the perspective of a researcher in meteorology, I enjoy and heavily rely on the plethora of free data that the NWS and NOAA provide.  You can go online and get both archived and real-time radar data whenever you need them.  You can look at output from all major weather models run by NOAA as soon as they are complete. You have access to weather observations at tens of thousands of locations through this free network.  I can see satellite images of anywhere in the country updated as frequently as every minute at times.  All of this for free.  Not only is the data free, but the mechanisms for producing, decoding or displaying the data from the NWS and NOAA are almost all open source--even the Radar Product Generator (the program that controls the doppler radars) and major weather models (like WRF) have all of their source code online, free to download and run. 

As I mentioned before, an observational network controlled by the private sector would virtually end all the free data and open source decoding.  Universities that are already cash-strapped would have to pay more money to get information that used to be free.  Cities and towns whose emergency managers relied on real-time radar and model updates to get emergency planning going would have to pay for access to this data.  Or, for a few dollars more, pay the company to have one of their expert meteorologists interpret the data for you.  Maybe we'd save some money by cutting spending for the NWS, NOAA and their programs.  But we'd probably end up paying it all right back to private companies in the end.

Which brings me to my last point--the accountability of the private sector.  While, as with any government organization, the politics will somehow find a way to infiltrate the system, I feel that the NWS really hasn't succombed to that as much.  Having worked in an NWS forecast office and for the NWS NEXRAD program, I have only seen the fringes of politics enter the business they do and never directly impacting the forecasting or warning process.  I feel that the NWS still provides an objective forecast and warning system.  The forecasters I know there are driven by their desire to get the forecast right--not by some other political or administrative agenda.

I also know several people who work for private sector meteorological companies.  They, too, possess a keen interest in getting the forecast right and that same thrill as NWS forecasters feel when things play out the way they thought they would.  I strongly support these forecasters and really respect the skill and passion they bring to their jobs.  It's not them that concerns me.

It's more the administration of these corporations that has me worried.  As any private-sector corporation, they are driven by profit.  With the way Wall Street has gone recently, we've seen that there are some darker sides of this system, even as robustly proven as it has been for our nation. We'd hope that higher profits are obtained by delivering a better product than your competitor.  But when your products can mobilize people and impact transportation or resource allocation, things get dicey.  Whole markets have developed that trade based on weather forecasts--people buy agricultural futures based on how they think the weather will impact crops.  A change in the forecast can cause the cancellation of hundreds of flights or the rerouting of dozens of container ships.  A change in the forecast can mean a change of millions of dollars.  So much of what we do depends on the weather.  Having a (hopefully) objectively-based, public-sector weather outlet that provides forecasts (and particularly warnings) without worrying about profit seems to make the most sense to me.  I'm not saying that the free-market economy would fail here--if a company makes bad forecasts, no one will trust it and it will fail.  But that strong link between the weather and our economy is something to think about when considering the role of private-sector weather companies in a country without a National Weather Service.

I usually try not to be opinionated (or voice my opinions) on these sorts of subjects, but I felt I should add my thoughts here.  After all, that's what a blog is good for, right?   If anyone else has any comments or thoughts, I'd love to hear them.

I also will do a write-up soon on my thoughts about the growing or shrinking weather-literacy of the American people.

Digging into a "simple" weather model

I often use complex, 4-dimensional weather models and show their output here as an indication of what our weather forecasts look like.  But today I wanted to show how a much simpler weather model works--and how sensitive these models can be to their parameters.

I wrote up what would be considered a small surface parameterization scheme to simply forecast the air temperature at the surface at a point over the next 24 hours.  This is based on equations from the book Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models by David Stensrud.  It's not a book for the novice meteorologist--you definitely have to have gone through at least some undergraduate meteorology to follow what's going on there.  But the first chapter basically discusses what I did.

So what is a "parameterization scheme"?  It's a way of trying to predict something that we can't explicitly measure or figure out.  When it comes down to it, a lot of features of weather models are parameterized.  We can't track every single raindrop or every single little breeze of air being tossed and turned through trees and buildings.  Yet, these processes collectively are extremely important and feed back into the larger-scale weather processes.  So, we try to estimate their net effect using parameterization schemes.

I wrote up a very basic one that looks at several radiative processes and tries to predict the surface temperature over the next 24 hours.  I started it at around 1:00 PM local time here in Seattle using my "optimal" initial conditions.  Here are the parameters:

• Latitude: 47.6928 N, Longitude 122.3038 W
• Day of year: 229
• Initial surface air temperature: 72 Fahrenheit
• Precipitable water: 1.27 cm
• Ground reservoir temperature: 12 Celsius (54 Fahrenheit)
• Cloud fraction: 0.0
• Bowen ratio: 0.9

 I'll get into what some of these mean in a minute. Here's the output:

I initialized the model at 72 degrees Fahrenheit.  You can see that the model expects us to warm up a little bit this afternoon, then cool off as the day progresses, bottoming out to around 46 degrees as a low overnight.  Then, the sun comes up at about 17 hours in and you can see the temperature starts rising again.

Is that low temperature tonight reasonable?  Here's a 24-hour meteogram showing the past 24 hours at this location (my weather station at my house, actually...):

Temperature is shown by the red curve in the top panel.  You can see that last night the low temperature reached was 48.2 Fahrenheit--not too far from our 46 Fahrenheit forecast.  So at least the model seems to be reasonable.

Now lets look at these different parameters that we can adjust.  I'm not going to change the latitude, longitude, day of year or initial surface air temperature, because those are all things we directly know and observe.  So, let's look at precipitable water.  This is something that is measurable (if you have a weather balloon, which sadly I do not...), and I recently wrote a blog post describing it.  It describes the total amount of water vapor in the air overhead.  So what happens if we adjust this a bit--say, increasing it to 2.0 cm or decreasing it to 0.5 cm?  Here's what happens:

In the graph above, the "optimal" run from before is shown in black.  The temperature results when the precipitable water is increased to 2.0 cm is in red and the temperature results when the precipitable water is decreased to 0.5 cm is in blue.  You can see that there is a pretty strong effect on the temperature path.  The temperature stays warmer when there is more water in the atmosphere, mostly because water has a higher heat capacity than air.  Therefore, moist air retains more heat, keeping it warmer longer.  Notice that with the lower precipitable water values, the temperature immediately began decreasing after the start of the model--the air was so dry that it immediately started cooling off.  However, with more precipitable water, the greater heat capacity of the water vapor keeps the air from losing heat as quickly.  This still allows the temperature to build a little before it starts cooling.

So that's the effect of precipitable water.  What about the effect of the ground reservoir temperature?  This temperature is, in simple terms, just the average temperature of the soil underfoot.  You might guess that a warmer soil temperature would help keep the temperature warmer, particularly overnight as the air cools down.  Does this actually happen?  Let's try increasing and decreasing the ground reservoir temperature by 2 degrees Celsius.  Here's the results:

Just like we might have guessed--if the ground is warmer (the run with the red curve), the air temperature also stays warmer.  Notice that same "reservoir" effect like we saw with precipitable water--the air temperature still continues to rise a bit once we start the model with a warmer ground temperature, whereas with a cooler ground temperature the model air temperature cool immediately.  Both moisture and soil temperature are important for determining how warm or cold we get and when we reach those high and low points.

The next parameter is called "cloud fraction" and it's simply an estimate of how much cloud cover there is in the sky--1.0 is completely overcast and 0.0 is completely clear.  Since it's a clear day today in Seattle, my optimal value is 0.0.  But, we can always try increasing it.  What if we had spotty cumulus clouds covering half the sky (cloud fraction = 0.5)?  Or what if it were overcast?  We might expect it to stay cooler during the day because the sun is being blocked out.  But what about at night?  Here are some results:

Well these results look a bit different.  The red line shows the temperature forecast with a cloud fraction of 0.5, and the blue line shows the temperature trace with a cloud fraction of 1.0.  We can now begin to see some of the hazards of using parameterizations and incompleteness in the model. With more clouds, we kind of expected the clouds to block out the sun and keep it cooler during the day.  That doesn't seem to have happened.  However, at night things stay much warmer with more clouds--this is definitely realistic.  Without clouds, as the earth cools at night, most of that energy would just be lost to space.  Clouds, however, can absorb much of that radiation and re-emit it back down toward the earth's surface.  Thus cloudy nights are warmer than clear nights, and the model definitely seems to capture this.

But, our intuition still tells us that more clouds should keep us cooler during the day.  So what's wrong here?  My guess is that while the model seems to be handling the impact of clouds on longwave radiation (the radiation emitted from the earth) well, it doesn't handle the potential blocking effects of clouds on shortwave radiation (radiation from the sun) well, if at all.  This gives us a clue that we may want to fix something in the model.

Let's try experimenting with the final parameter, the Bowen ratio.  This is a somewhat complex parameter that technically describes the ratio between sensible and latent heat emitted from the surface.  What this is talking about (in simpler terms) is, out of all the heat being emitted from the surface, how much of it is being lost through evaporating water (latent heat) and how much is being lost through simply radiating away the heat (sensible heat).  The AMS glossary gives typical values for this ratio:

• 5 over semi-arid regions
• 0.5 over grasslands and forests
• 0.2 over irrigated orchards or grass
• 0.1 over the ocean

These values make quite a bit of sense--over semi-arid regions (like deserts), there's not a lot of water vapor--so a Bowen ratio of 5 means that 5 times as much heat is released from the desert surface as sensible heat as opposed to heat being lost to evaporating water vapor.  Over the ocean, on the other hand, there's lots of water present--so the amount of heat released from the ocean as sensible heat is only 1/10 of the amount released through the evaporation of water from the surface.

Let's experiment with this value.  Here in Seattle there are a lot of trees and water, so maybe the Bowen ratio is closer to, say, 0.5.  But, on the other hand, this is a city with lots of pavement and buildings.  Those surfaces seem like they'd be hotter (and wouldn't have a lot of moisture).  So, maybe the Bowen ration is more like 2.0.  Let's see what happens:

Wow.  Some significant differences here.  Increasing the Bowen ratio really warms us up a lot, though we cool off to about the same temperature overnight.  Decreasing the Bowen ratio (the blue line) really cools us off--it makes us lose that reservoir of heat and we start cooling off immediately.  You can see that during the next day we start warming up really slowly.  Since the lower Bowen ratio means that more energy is going to evaporating water, there's less energy being used to increase the warmth of the air itself (the warmth we sense--hence the term: "sensible" heat).  Neither of these extreme values seem realistic--we haven't gotten up to 80 in Seattle, nor is the temperature plummeting this afternoon.  So, sticking to a middle value--0.9 to 1.0 is probably good.

This was a very simple model, a "parameterization scheme", if you will.  You can see that just by varying these parameters by a little bit, the results can change quite a lot.  We also can use our intuition and knowledge about the way temperatures typically go to both identify flaws in the model (like how it's probably not handling the effects of clouds on shortwave radiation well) and try to estimate unknown parameters (like trying to pick the right Bowen ratio). 

But I emphasize that this is a very, very simplified model over just one location.  I mean, none of these parameters change throughout the run of the model and there is no advection--this model has no idea if a cold front moves through or if the day starts clear and ends cloudy or anything like that.  And even in this simple model it's very sensitive to changes.  Imagine trying to forecast temperature AND moisture AND winds AND pressure for thousands of points across the country.  It's amazing that our models do as well as they do.

Hope you found this useful and not too boring.  If you'd like a copy of the Python script I used to run this simple model, let me know...

A strenghening cyclone brings rain to the northeast

I don't often write about the northeast in this blog.  It's probably because I've never lived there and therefore haven't really experienced their annual weather patterns firsthand.  I've lived in the upper midwest, the southern plains, and now the Pacific northwest, so that's where I tend to focus my writings.

But today I am indeed going to talk about the northeast.  As you can see in a radar mosaic from this morning, it's a very rainy day:

NEXRAD base reflectivity composite at 1858Z, August 15, 2011.

Some flood watches and warnings have already been issued for parts of the Hudson River valley and into Massachusetts.  It even looks like a heavier line has formed and is approaching New York City, though no severe warnings have been issued yet.

This low has actually been strengthening over the past 12 hours or so as it has entered the northeast.  Even so, the surface analysis from early this afternoon still shows a very broad low pressure center:

RUC surface analysis as of 15Z with temperature (colors) mean sea-level pressure (contours) and winds (barbs) on August 15, 2011.

A rather significant cold front (for this time of year) looked to have brought some cool air down south at least as far as the Appalachians.  But, notice how weak northwesterly winds continue through the Carolinas and Georgia but the boundary between the warmer and the cooler air (between the yellows and the greens) stays back behind the mountains.  I'm guessing that since the winds shift has continued over the mountains but the cooler air has not, the cold air pool behind this front was relatively shallow.  So, when it encountered the Appalachians, the cool air couldn't push through and has just gotten blocked up on the other side.  So, not the strongest low.

However, like I mentioned, there has been some strengthening in the last few hours.  This is particularly notable on the upper-air charts.  Here's the  300mb analysis from early this morning at 12Z:

300mb analysis of heights (contours) and winds (colors and barbs) at 12Z, August 15, 2011.

Notice a rather significant shortwave trough whose axis lies over Ohio and West Virginia.  This is providing the upper-level support for the surface cyclone.  There is a relatively weak jet streak analyzed around the base of the trough with a maximum wind reading of maybe 60 knots.

Compare this to the 300mb RUC analysis from 3 hours later at 15Z:

RUC 300mb analysis of heights (contours) and winds (colors and barbs) at 15Z, August 15, 2011.

The RUC analysis shows a much deeper trough with a stronger jet streak on the eastern side.  Here, the maximum winds are estimated to be around 90-100 knots!.  So why would we expect this upper-level trough to strengthen like this as it moved out over the northeast?

I suspect it has to do with the influence of the Gulf Stream current off the east coast.  Take a look at the satellite-derived sea-surface temperature over the past few days from NOAA-NESDIS:

NOAA/NESDIS 50km SST analysis from data on August 9 through August 12, 2011.

See that warm tongue of higher sea-surface temperatures that stretches northeastward from Cape Hatteras in North Carolina out away from the northeast coast?  That's the hallmark of the Gulf Stream--a current that brings very warm water northward from the tropics along the east coast.  This can set up a very strong temperature gradient between the often cooler land and the much warmer water off shore.  Remember from my discussions on jet streak theory that temperature gradients in the lower-levels drive the winds aloft through a relation known as the thermal wind relation.  So, if we have a strong temperature gradient between the cool land and the warm Gulf Stream waters, this is going to work to enhance the wind speeds aloft directly above this gradient--exactly what we're seeing.

This sort of phenomenon happens a lot in the northeast--upper-level winds increase in response to the temperature contrasts between cooler land and the warmer jet stream.  This contrast becomes particularly pronounced in early winter when the ocean is still warm but the land really starts cooling down.  This is why those great nor'easter types of storms strike during this time--they feed off of this temperature contrast to gain their strength.

Another side effect of the warm Gulf Stream current is that it provides a nice supply of warm, moist air to fuel storms and precipitation.  If the low-level winds are out of the south, they can bring that warm, moist air up and over land, creating lots of precipitation in the process.  You can see this in the infrared satellite image from early this afternoon:

GOES-E IR satellite image from 1831Z, August 15, 2011.

The classic comma-shaped cloud pattern of a developing cyclone is becoming pretty evident in this image.  To the east, you can see a broken band of clouds stretching from south to north just off the coast.  This is that warm-air advection region--where southerly winds spinning in toward the center of the cyclone are advecting warm-moist air northward.  As they approach the coast, the warm air rises over the terrain of the Appalachians and the cooler air sitting over the land surface.  This rising motion causes the moist air to cool and the moisture to condense out.  Hence, we see lots of rain and thick clouds over land in New England.

Rounds of MCSs bring cooler weather

As reports from people I know in Oklahoma keep streaming in on Facebook, it looks like today is going to be one of the cooler days in the past several weeks in that area.  For a place that has seen daily highs above 100 for much of the past month, the fact that it's only 70 degrees in Norman, OK, around noon is quite spectacular.  That's more Seattle-like in terms of the weather...

But we can see in looking at a meteogram of weather variables since the beginning of the month that the high temperatures have been getting lower over the past few days:

Meteogram from the KOUN station in Norman, Oklahoma since August 1, 2011.  Temperature is in the top panel.  From the Weather Underground site.

In fact, the highs over the past few days have actually been pretty close to normal.

So what's helping promote this cooldown?  A roughly zonal pattern aloft has storms firing on the smallest shortwave perturbations.  Here's a mosaic radar image from 17Z today:

NEXRAD radar mosaic at 17Z, Aug. 11, 2011.

You can see a nice line of storms (an MCS) that pushed through central Oklahoma today, bringing lots of rain and cooler temperatures in its wake.  However, as with most of our summer MCSs, there wasn't "strong" upper-air support.  Here's the 500mb analysis from 12Z this morning.

GFS analysis of 500mb heights and winds for 12Z, August 11, 2011.

No startling features stand out over the southern plains.  There does look to be a little perturbation in the wind field through northeastern Oklahoma, but at this resolution, it's hard to tell.  Elsewhere, a shortwave trough that moved through the Pacific Northwest has led to a cool start out here this morning.  The deeper trough over western Quebec has also brought slightly cooler weather to the Great Lakes region.

As I mentioned in an earlier post, MCSs (particularly MCCs) don't need strong upper-air support--just enough to get them going.  However, their motion is still directed by the upper-level winds.  In the pattern this morning, you can see that the flow at 500mb is generally southeastward across the southern plains.  It's no coincidence that that's the direction the storms are moving.

However, while there's a relatively flat pattern with maybe some broad troughing aloft over the southeast, at the surface it's a slightly different story. Here's the surface analysis for 16Z this morning:

RUC 16Z surface analysis of temperature (colors), winds (barbs) and mean sea-level pressure (contours) for August 11, 2011.

Notice that there's still a big ridge of high pressure over much of the Mississippi River valley.  High pressure at the surface tends to indicate low-level subsidence, which means downward air motion near the surface.  This works against thunderstorm formation by suppressing the updrafts.  As such, as this MCS moves eastward out of Oklahoma, it's probably going to encounter a slightly more hostile environment to its continued maintenance or growth.  With little upper-air support (no potent shortwave troughs or jet streaks to speak of), the MCS will probably weaken and die off before too long--just like the last one did.  The SPC has continued a slight risk down into Louisiana and Mississippi for this MCS, as it may take a little while to completely die out.

SPC day one convective outlook for August 11, 2011 as of 1630Z.

Further north, a slight risk area in the northern plains doesn't extend into the surface high pressure region at all.  This slight risk area is in response to the potential for lift and storm development as that trough from the Pacific Northwest moves in.  The persistence of the surface high pressure over the mid-Mississippi valley will tend to keep storms away from the upper midwest and Great Lakes area over the next few days.

So...enjoy the cool weather while it lasts.  The CPC still has long-term outlooks indicating above-normal temperatures in the southern plains for the next  month or so.  I guess you just have to take what breaks you can...

Some relief for the upper midwest and the northeast

Just a quick post today looking at the upper-air pattern forecast for this week.

It continues to be warm in the central part of the country.  The Climate Prediction Center outlook for the next 6-10 days continues that trend:

CPC 6-10 day outlook of temperature probability as of Aug. 7, 2011.

In the meantime, though, cooler-than-normal temperatures are expected for the Pacific Northwest and much of the upper Midwest and northeast.  It looks like the only places catching a break from the heat will be the Midwest and the mid Atlantic states.

Of course, with cooler weather also comes the rain--the same troughing that ushers in cooler temperatures also brings that colder air closer to the very warm air sitting to the south.  The tightening of the temperature gradient there promotes stronger winds aloft and more convergence at the surface.  Both of these ingredients contribute to increased chances of storms.  Therefore, the CPC's 6-10 day precipitation forecast shows a similar pattern:

CPC 6-10 day outlook of precipitation probability as of August 7, 2011.

No relief in sight for the drought-stricken areas of Texas and the southern Plains.

The storm that won't form

Looking out into the tropics today.  Last week, Tropical Storm Don failed to live up to expectations in south Texas.  The rainfall associated with the storm dissipated rather quickly, bringing little relief to that drought-stricken area.

However, we have a new disturbance in the tropical Atlantic, labeled by the National Hurricane Center (NHC) as Invest 91L.  Here's how it looked early this afternoon on visible satellite.

GOES-E visible satellite image of invest 91L, 1815Z, Aug 1, 2011.

It's definitely a somewhat-organized area of convection and the NHC says that tropical storm force winds are already being reported in the vicinity as it approaches the Lesser Antilles.

However, this storm has been on the watch list for days--since Friday, the NHC has maintained on its website that this disturbance has an 80-100% chance of developing into a tropical depression or storm in the next 24-48 hours.  Three days later, they still haven't officially upgraded it yet.  Why not?  Hurricane hunter airplanes flying through the storm failed to find a closed circulation about a clear low-pressure center.  Without that level of organization, the NHC doesn't assign storms a unique identity as a depression or as a storm, even if the winds are of tropical storm strength.  So, we continue to wait...and watch.

The tropical cyclone modeling community is ever-expanding, and they're trying to solve what is becoming one of the classic dilemmas of current numerical weather prediction.  As our computer models have become more advanced, our ability to forecast cyclone tracks has increased, while our ability to forecast cyclone strength really hasn't changed much at all.  Many, many scientists are working on that problem, and the result is many fancy model configurations that try to get it right.

Here are three examples of advanced hurricane weather models and what they are predicting will happen with this storm.  I'm going out to the end of their model run at 126 hours--that's over 5 days.  Already we're stretching the limits of predictability even in relatively quiet weather conditions.  But, I wanted to illustrate the differences in these models in both track and intensity over this time frame.

I got these images from Bob Hart's Tropical Cyclone Genesis Potential Fields page--my absolute favorite page to visit to get a nice summary of what all the models are saying with respect to possible tropical cyclones.

First, here's the Geophysical Fluid Dynamics Laboratory (GFDL) model forecast for 126 hours out from 12Z this morning:

GFDL 126 hour forecast for incest 91L at 18Z, August 6, 2011.

The left panel shows a wider view of the tropical Atlantic and eastern US.  You can see that by August 6th (Saturday), the GFDL model forecasts the storm to be well off the coast of Florida and rather small in size.  The right-hand panel shows a moving nested model grid inside the large model.  This shows the output of a second model over a small area centered about the storm at much higher resolution.  In theory, the overall synoptic pattern in the larger-scale model will help determine where the storm will go and the higher-resolution, moving nested grid will help determine the storm strength.

One thing I really like about the graphics on this particular website is that they've color-coded their wind contours to match the different levels of tropical cyclone strength.  For instance, any areas in cyan are where winds are of tropical depression strength.  Dark blue is tropical storm strength.  Green corresponds to category one hurricane strength, yellow for category two, and so on from there up.  This lets you see at a glance what the structure of the wind field is forecast to be by this model, and also what the maximum intensity would be.

In the GFDL case above, there's a significant area of green, signifying category one strength, with a few small pockets of yellow (category two) strength.  So this forecast offers the possibility of a category 1-2 hurricane well off the southeast US coast by Saturday. The minimum pressure is given as 978.9mb.

Now here's the Hurricane-WRF model (the HWRF) forecast for the same time:

HWRF 126 hour forecast for incest 91L at 18Z, August 6, 2011.

There are significant differences between this and the GFDL model.  First, the storm position is different.  The HWRF is predicting it to be much closer to the Florida coast on Saturday.  Also, in this model the storm is predicted to be much larger in area, with tropical-depression- and tropical-storm-strength winds over a much larger radius from the center.  However, in terms of strengh, I don't see any signficantly visible areas of category two strength winds in this output.  The minimum pressure is forecast to be lower--971.4 in this model as opposed to 978.9 in the GFDL model.  So lower pressure, but also weaker winds.  Still probably looking at a high-end category one hurricane in this model.

And now, another version of the HWRF, but this one with modifications from NOAA's Hurricane Forecast Improvement Plan (HFIP) initiative.  This group has modified the HWRF model somewhat and also runs their smaller nested grid at very high (3 kilometer!) horizontal resolution.  Here's their forecast for the same time:

HWRF-HFIP 126 hour forecast for incest 91L at 12Z, August 6, 2011.

This forecast is actually from 6 hours earlier, but it paints an even more sinister picture.  In this model, the storm is very close to the Florida coast by Saturday morning.  The storm also is forecast to be much stronger--there are significant areas of orange in the wind field, indicating category three strength.  That would make this a major hurricane.  The forecast minimum pressure is also much lower than the other two models at about 940mb.  If this were to happen, then south Florida would really need to watch out.

So, you can see that we still have a long way to go in our hurricane models.  Granted, these are forecasting for five days out, and even in non-hurricane situations our weather models do poorly at that range.  These only represent possible futures for this storm.  If my experience in watching these models is any indication, the end result will be something that avoids the extremes.  In fact, usually these storms turn out weaker than forecast.  But not always...  So, just be aware of this storm as it develops and moves eastward.