TS Arlene -- another kind of circular MCS

Fittingly enough, as I began this discussion on mesoscale convective systems (MCSs), our first tropical storm of the Atlantic hurricane season formed off the east coast of Mexico.  Tropical Storm Arlene made landfall this morning near Cabo Rojo, Mexico.  Here's the an IR satellite image shortly after landfall:

GOES IR satellite image of TS Arlene at 1715Z, Jun 30, 2011.

I find it fascinating comparing the satellite presence of a tropical storm with the satellite presence of a mesoscale convective complex (MCC) (or a mesoscale convective vortex--but that's another post).  In Maddox (1980)'s classification scheme, the two types of recognized "circular" MCSs were tropical cyclones and MCCs.  As odd as it might sound, I believe that the origin of the "circular" structure is actually very similar in both cases, even if the both types of storms form in vastly different ways.

One main difference between circular MCSs (like tropical cyclones and MCCs) and more linear MCS features (like squall lines) is the environment in which they form.  Remember from my previous discussion that squall lines usually form along or near frontal boundaries.  Their structure and maintenence are dictated from the surrounding environment.  In fact, a lot of their energy is derived from a baroclinic environment.  That's a fancy way of describing an environment where there are strong horizontal temperature contrasts like we see around fronts.  But, remember that a MCC tends to form away from fronts--off by itself, more or less.  Tropical cyclones, too, don't have fronts in the picture--even if they are powerful low-pressure centers, they don't have fronts associated with them.  This is because both MCCs and tropical cyclones tend to form in a barotropic environment--an environment where there are not strong horizontal temperature contrasts.

This makes sense if you think about it in a qualitative sense.  Fronts are often depicted on weather maps as long, "straight" lines.  When we consider the polar front separating the cold, arctic air in the north from the warm, subtropical air to the south, it's a long, linear boundary that's asymmetrical on either side--one side is cold and the other side is warm.  Storms that form along these boundaries between warm and cold air (or moist and dry air) are going to inherit this asymmetry--the parts of the storms in the warmer, moister air are going to behave differently than the parts of the storms in the cooler, drier air.  This works against having a circular, symemtrical structure.

In contrast, storms that form away from strong frontal boundaries (i.e. in a barotropic environment) don't have these contrasting areas of warm and cold to deal with.  This is particularly true with hurricanes--they form over the tropical oceans where everything is very warm and very moist all the time (more or less).  As such, anything that spins (or has a vorticity maximum) in such an environment should (theoretically) assume a more symmetrical, circular shape.  If all parts of the storm are experiencing similar environments, they should theoretically all look the same.  Granted, tropical cyclones do often move into areas where there is differential wind shear aloft or cooling sea-surface temperatures and this disrupts that symmetry and weakens the storm.  But still--the circular structure makes more sense.

What about MCCs?  They're not usually associated with a powerful center of low-pressure.  However, remember what I said about MCCs in my last post--MCCs tend to modify their surrounding environment more than the surrounding environment drives them.  At the heart of any MCC is an area of rising motion and a lot of latent heat release as moisture evaporates when air is lifted and cooled.  That rising motion and heating lowers the pressure in the center, creating a warm-core-like vortex.  It may be weak and subtle, but it's the same kind of mechanism that drives tropical cyclone formation and growth.  And it implies that there still is some (however weak) vorticity and circulation going on in the storm.  Is this enough to really promote a circular structure?  That's my guess for now.  Though if anyone has a better idea, I'd welcome any thoughts...

Going back to TS Arlene, it was interesting to note that our global models were forecasting a tropical cyclone to develop in the western Gulf of Mexico a full week ago--an impressive lead time for tropical cyclone genesis.  Here's the ECMWF 144 hour forecast of sea-level pressure for 00Z yesterday:

Note that the model forecasted a small, compact low in the Bay of Campeche just off the eastern Mexican coast.  It's a little further south than where the storm actually impacted the coast, but still rather impressive with such a long lead time.

Here's the same forecast from the GFS model:

The forecast low-pressure center was a significantly more pronounced, though still a little far south.

And here's the CMC model (Canadian GEM):

The CMC model was predicting a much deeper low.  For some reason the Canadian model always seems to predict tropical cyclones that are much stronger and much more frequent than actually happens.  I'm not entirely sure why this is, but it's an interesting question.

What is a mesoscale convective complex?

As I mentioned in my last post, I want to go into some detail about the definition and structure of several classes of storms.  We use the term mesoscale convective system to describe any collection of storms (or other convective activity) that is organized on a scale larger than a single storm.  Today I want to focus on one particular type of mesoscale convective system--the mesoscale convective complex.

Much of this discussion is going to follow Robert Maddox's 1980 paper "Mesoscale Convective Complexes," which is the first paper to define and describe these types of storms.  You can read the full paper here (which is actually very understandable if you can follow the kinds of things I write in my blog).

In Maddox (1980), he describes a breakdown of different types of large-end mesoscale convective phenomena using this convenient chart which follows nicely from my last blog post:

Table -- Describing a classification of meso-alpha (large mesoscale) convective phenomena, broken down by geometric shape and location.  From Maddox (1980).

The main point from this chart is that these mesoscale convective complexes are "circular" in structure and they can occur in both the tropics and the midlatitudes.  Maddox proposed a definition that still stands today (at least it still matches the American Meteorological Society's definition of a mesoscale convective complex) though there have been proposed amendments over the years:

Table -- A definition of a mesoscale convective complex from Maddox (1980).

MCCs are mostly determined by the shape and size of their infrared satellite signature.  This has always struck me as somewhat arbitrary--what's so significant about the cloud returns being more than 100,000 sq. kilometers in area?  Why does the structure have to have a near-circular shape (eccentricity greater than 0.7)?  It turns out that these parameters themselves are indeed arbitrary--they exist as a way of describing MCCs in the context of the observations that we have and in as succinct of a way as possible. 

From Maddox's paper and several subsequent descriptions, there are several key points that describe MCCs uniquely and separate them from other features such as squall lines:

1. MCCs do not require significant large-scale forcing to form.  Whereas squall lines often form along fronts and are associated with deep troughing and strong upper-air support,  MCCs can form in areas where there is relatively weak support for convection--only mild lifting motion and no significant support aloft.
2. MCCs require a very warm and moist layer that extends from the surface relatively deeply up into the atmosphere.  Because MCCs typically form in areas with weak upper-level support (as mentioned above), they need a lot of latent heat energy to sustain themselves.  Basically, with structures like squall lines along a front, you have an ambient, synoptic-scale environment that works to force and maintain thunderstorms.  With MCCs, it's more like you have storms that work to change and modify the synoptic-scale environment.
3. Because of the strong dependence on latent heat release to maintain the structure of a MCC, they tend to share many charactaristics in common with a warm-core system as opposed to a cold-core system. Typically we think of hurricanes as the strongest warm-core-type storms.  However, MCCs also exhibit this kind of structure.

Let's look at a more direct comparisons between MCCs and squall lines.  Maddox provides some examples from 1979 of both in an attempt to illustrate the difference in structure.

Figures taken from Maddox (1980).  The left side illustrates a MCC on July 12, 1979 and the right side illustrates a squall line on June 20, 1979.  The top panels show infrared satellite images, the middle panels show radar returns and the lower panels show the surface analysis.

The left-hand side of the above image shows an MCC whereas the right-hand side shows a squall line event.  In the satellite images (the top panels), the shape difference is clear--the MCC is very round in shape and covers a large, continuous area.  The squall line, in contrast, has a much more linear shape and lots of variation in the infrared satellite returns--it's not just one big blob.

In the middle panels showing the radar returns, we can see that in the squall line, the bulk of the radar return (and therefore most of the precipitation) is confined to the immediate area of the squall line (ignoring the other precipitation off to the northwest associated with the surface low).  In the MCC, however, there's a rather large area of radar returns underneath the big circular infrared satellite feature.  Furthrmore, there are embedded areas of deeper convection in the MCC--some of which do look "linear".  But, the satellite return and other radar return areas are very large and aren't just confined to that deep convective area.  This sets the MCC apart from the squall line.

Finally, in the lower panels, for the squall line case on the right we can see that the squall line is out ahead of a deep surface low to the west.  The only way you would get a deep surface low like that is to have significant upper-level support (i.e., a strong jet streak with its exit region above).  We can see a lot of pressure contours, and they're fairly close together, indicating strong pressure gradients.  The squall line itself has moved out ahead of the main cold front, but the fact that its structure so well mirrors the main cold front hints that the original storms probably formed along the cold front before strong winds aloft started moving them out ahead of the front.  This is a classic scenario that I've talked about in this blog multiple times.

However, in the MCC case, we notice a very different synoptic setup.  There's no strong surface low nearby at all.  The pressure contours are rather few and far between, indicating weak pressure gradients.  There is a cold front analyzed off to the northwest, but it doesn't appear to be very strong.  Furthermore, the shape of the convective area doesn't really match well with the shape of the cold front.  This implies that while the front may have forced initial storm development, it was not the primary mechanism for organization in these storms.  You can see that in the MCC surface analysis, they've drawn outflow boundaries on the southern and eastern edge of the complex, with a mesoscale area of high pressure underneath the middle of the complex.  This contrasts greatly with the squall line case, and gets back to the difference I mentioned earlier--

Squall lines--their forcing and maintenance--are a product of the surrounding synoptic environment whereas MCCs tend to force and change the surrounding synoptic environment.

In the surface analyses above, the MCC analysis is dominated by features (like the outflow boundaries and meso-high pressures) created by the MCC itself.  In the squall line case, the dominant features (the surface low, the strong fronts and pressure gradients) were NOT created by the squall line.  They worked to create the squall line.  This is a fundamental difference.

Let's explore some of the other features of MCCs by looking at some potential MCC candidates from the other day.  Remember this radar image from Sunday night?

NEXRAD composite base reflectivity from 0228Z, June 27, 2011.

Now--do we call these features squall lines or MCCs?  On radar the deep convection does look rather linear, but we saw even in Maddox's example MCC that we could see linear-like convective elements within an MCC.  There's also extended areas of precipitation to the north and the west of these convective lines in the radar image.  However, the technical definition revolves around the infrared satellite image, so I'll bring that back too.

GOES Infrared satellite image from 0245Z, June 27, 2011.

Immediately we can see that the shapes of these storm complexes on the satellite image is more rounded--there's no linear feature or "comma shape" like we'd expect if there was a deep surface low or a squall line. I haven't measured the area of the satellite returns explicitly, but knowing that the state of Iowa has an area of about 147,000 square kilometers seems to imply that these are large enough to qualify as MCCs (the exact definition(s) of area needed is in the first table above).  So just from these satellite images, I'd call these MCCs.

But lets look at some analyses of the surrounding environment.  Let's go back to 18Z (around the middle of the day) to when these storms were just forming.  Here was the radar image then:

NEXRAD composite radar reflectivity from 18Z, June 26, 2011.

Scattered storms were beginning to develop throughout the Dakotas and into northern Nebraska.  Other storms were beginning to fire in southeastern Nebraska.  Now, let's look at the 300mb chart for this time:

SPC mesoanalysis 300mb winds (barbs and blue colors), divergence (pink) and height (black) for 18Z, June 26, 2011.

Is there a deep trough moving in?  Not really.  Are we in the exit region of a strong jet streak?  Kind of--you can see the blue shadings highlighting the core of the jet winds off to the west.  There's some divergence aloft (shown by the pink contours) but this doesn't seem to be tied to the jet streak.  This divergence is right above the area where storms were developing on radar.  This makes sense--the rising motion in the convection implies that air above has to get out of the way, so we expect divergence aloft above the storms.  But the fact that this divergence is so localized to just the areas where the storms are seems to indicate that this is a storm-induced phenomenon--the divergence is not significantly coming from the overall synoptic pattern.  This agrees nicely with what I said about MCCs before--they modify the surrounding environment more than it forces them.

Continuing to the time when the MCCs had matured, here's the new 300mb map.

SPC mesoanalysis 300mb winds (barbs and blue colors), divergence (pink) and height (black) for 2Z, June 27, 2011.

We can see the divergence aloft (once again, the pink contours) associated with the MCCs in eastern and western Iowa--they're nowhere near any significant jet at 300mb.  There are some wiggles in the height contours, but no troughs or anything supporting these storm clusters.  Once again, the storms are modifying the environment. 

Also in this 300mb image, I find it interesting how the jet aloft has changed surrounding the storms that were developing in central South Dakota at this time.  Notice how the jet streak seems to curve up and around the top of the strong area of divergence associated with those storms in central South Dakota.  If you follow that curvature, you'd see that the jet streak is starting to become anticyclonically curved--it curves clockwise.  Interestingly, one of the features of a warm-core storm is that it promotes an area of anti-cyclonic flow (and "higher" pressure) aloft.  Is this anticyclonic curvature of the jet evidence of a warm-core structure in the storms in central South Dakota?  Remember, in my list of features of an MCC, I said that these storms often exhibited warm-core charactaristics.  So it could be...

Finally, some more interesting facts about MCCs:

1. Most MCCs develop in the afternoon hours, then strengthen through the evening and perisist overnight until the next morning.  Thus they provide a lot of nocturnal rainfall.
2. In fact, MCCs are thought to be one of the largest contributors to annual rainfall for much of the central US (several studies have looked at this, including Fritsch (1986), McAnelly and Cotton (1986, 1989) and Kane et al. (1987)).  Fritsch (1986) claims that most states in the plains and midwest receive 30-70% of their annual rainfall from MCC events.
3. Because of their heavy rainfall contribution (remember--MCCs have precipitation over a much larger area than squall lines and usually occur when there is a very deep moist layer), MCCs are responsible for many flash flood events across the central US.
4. Severe weather is definitely possible within a MCC.  Severe wind and hail are frequently found with the stronger convective elements.  If those elements can organize along one of the MCC's outflow boundaries, the wind threat can get even greater.  Tornadoes are also possible from stronger convective elements within the MCC.  Here's the SPC storm reports for that group of MCCs on Sunday night:

SPC storm reports for June 26, 2011.

And with that I'm going to wrap up my discussion of what makes a mesoscale convective complex.  It's a peculiar type of storm that is very frequent in the late spring/early summer months.  While superficially it can look like a squall line, it's a unique type of organized storm that:

• Doesn't need strong forcing aloft
• Actually works to change the synoptic pattern aloft instead of being driven by the synoptic pattern
• Usually forms with a very deep layer of moisture in the low-levels
• Has warm-core charactaristics
• Brings a lot of rainfall, usually at night, to the central part of the US
• Has a very recognizable circular-type structure on infrared satellite images.

Now you'll know what to look for the next time that the term "MCC" comes up.

The World of "Mesoscale" Convective Systems

This evening's radar composite was quite the sight.

Fig 1 -- NEXRAD composite base reflectivity from 0228Z, June 27, 2011.

There are three areas of storms moving across the northern plains and upper midwest.  The leading batch at this time was crossing the Iowa-Illinois border.  The next line was in western Iowa and southeastern Nebraska, and the furthest west group was in western Nebraska and South Dakota.  Quite the active night with line after line of storms marching through.

These are "special" types of storm systems that are called mesoscale convective complexes (or MCCs) by meteorologists.  Let me back up a minute and describe a bit more of the meteorological parlance going on here.

In meteorology we often refer to different types of weather phenomena in terms of their scale, be it spatial scale or temporal scale.  It helps to classify various weather processes and keep track of what is going on in different scopes.  Here's a quick list of some of the commonly-used scales (taken from a discussion in Stull 2000):

1. Global/Planetary Scale -- This describes phenomena that are on the order of tens of thousands of kilometers in length and usually days/months/years in time scale.  When we talk about the jet stream pattern across the planet or about the state of El Nino, these are things on the Global/Planetary scale.
2. Synoptic Scale -- This starts getting into the realm of things I usually discuss here.  The synoptic scale generally deals with phenomena on the order of 1,000-10,000 km across and is often what we focus on when looking on the scale of, say, the United States.  Features like troughs and ridges, surface lows and highs, and local jet streaks are generally considered to be on the synoptic scale.  Synoptic comes from the Greek meaning "with the eye", and originally this scale was used to describe the features on weather maps that we would easily describe by just eyeballing them--troughs, ridges, lows, highs and so on.  Sometimes I wonder with the amount of detail and layers upon layers we put on our weather maps now if "synoptic" is the best way of describing them.  But, the term persists...
3. Mesoscale -- This describes anything from the scale of 10-100 km scale ('meso' means 'middle'), and boy does it cover a lot.  Fronts are usually considered borderline between synoptic scale and mesoscale.  Think about it -- a front can be several hundred to a thousand kilometers long but only be a few dozen kilometers "across".  So, it sits right in the middle between the two scales.  On the larger side of the mesoscale, we have features like hurricanes and the types of complexes we saw in the radar image above.  But individual thunderstorms and supercell thunderstorms also fall into this scale.  Local phenomena like mountain winds or sea breezes are also considered to be in the mesoscale.
4. Microscale -- This is a somewhat looser term and generally just applies to anything less than a kilometer or so in size.  On the large end of this scale we have things like tornadoes--not quite large enough to be mesoscale phenomena (though because they come from thunderstorms that ARE large enough to be considered mesoscale, we often lump them in with the mesoscale). Turbulence is another phenomenon that is also considered to be in the microscale.

These are just terms that meteorologists use to keep track of what they're talking about.  For instance, the Storm Prediction Center (SPC) will often publish "Mesoscale Discussions" when they're talking about a region they're considering for a new watch.  The area they're talking about isn't the size of the entire country, so it's not in the synoptic scale.  It's definitely mesoscale-sized.  In the SPC's general Convective Outlooks, however, they often talk about the pattern of the jets aloft and the forecast positions of troughs and ridges in the coming days.  That's more of a synoptic-scale discussion.  Things at different scales all do interact with each other, but this just helps keep them apart.

Now let's get back to these storms.  Here is the infrared satellite image from about the same time as the radar image above.

Fig 2 -- GOES Infrared satellite image from 0245Z, June 27, 2011.

Notice that the area affected by these storms is on the scale of the size of a few states.  I still like keeping that image of the entire continental United States in my head when I think about the definition of synoptic scale.  Anything significantly smaller than that is into the mesoscale.  So, these storms are definitely in the mesoscale.  It's kind of difficult to see, but notice how that even though on radar the groups of storms formed elongated lines, the satellite image shows more circular blobs over the storms.  This shows a lot of high, thick clouds trailing the leading edge.  It also helps meteorologists to define these collections of storms in a special way. 

What do I mean by that?  It turns out that meteorologists have even more classifications for different types of phenomena.  Any time a collection of thunderstorms organizes itself on a scale larger than individual storms, it can be referred to as a mesoscale convective system (MCS).  We now know what mesoscale means, and convective just means we're referring to convective processes--meaning unstable air lifting (well, it's more complicated than that, but still...).  The term "mesoscale convective system" (or, often its acronym MCS) has become a very common term used to describe any collection of storms.  I guess it just sounds more technical to say "an MCS is moving in" as opposed to "a line of storms is moving in."  But the term MCS can describe any area of convection where multiple convective updrafts organize themselves on a scale where they work to reinforce each other.  So, individual supercell thunderstorms are NOT MCSs.

However, there are many different kinds of MCSs, including:

1. Squall Lines
2. Mesoscale Convective Complexes
3. Mesoscale Convective Vortices
4. Hurricanes
5. Lake-Effect Snow

So, I personally think it's a bit general to use the term "MCS" all the time--it can mean many things.  Particularly when you're trying to separate things like squall lines and mesoscale convective complexes.  In fact, even in the image above, one might argue that some of the groups of storms I was referring to as mesoscale convective complexes might simply be squall lines.  Specificity helps.  But, people still use the term MCS to describe just about any collection of storms.  And, technically they'd be correct.  But, not very specific.

So just what DOES separate a squall line from an MCC?  In my next few blog posts I'm going to go into some of these "technical" descriptions of these different mesoscale phenomena.  To tell you the truth, I've always been curious as to why MCCs are so special.  I was always told, "If the infrared satellite return from the storms makes a big circle, its an MCC.  If it makes a line, it's a squall line."  Why this odd distinction?  Stay tuned to my next few blog posts to find out.

Storms firing on an outflow boundary

There's a moderate risk of severe storms with a PDS (particularly dangerous situation) tornado watch out for parts of Nebraska and Kansas this afternoon.  And storms are indeed exploding across the central plains.  Here's a reflectivity image from earlier this afternoon in southern Nebraska.

Fig 1 -- 0.5 degree base reflectivity from KUEX at 2121Z, June 20, 2011.

Several powerful storms are visible in the northern part of the image, but what's also rather interesting are those two "lines" visible in the reflectivity near the radar.  These lines mark the leading edges of outflow boundaries from those powerful storms up north.  As these storms moved along, cool air sinking in the rear-flank downdraft (the back part of the storm that defines the "hook echo" in rotating storms) spreads out once it hits the ground, creating a miniature cold front along its leading edge.  This creates a boundary where air flowing out of the storm from that rear flank downdraft runs into the ambient air which is often moving in a different direction.

These boundaries and the pockets of cooler air behind them can linger around for several hours after a storm has passed.  Furthermore, since winds tend to be converging along these boundaries, they provide a focal point for new storms to fire.  Notice in the image above I circled several smaller storms that were just then forming right ahead of the eastern outflow boundary.  It's likely that convergence of the low-level winds along that boundary forced air to move upward and set the convection in motion.

We can see this convergence on the base velocity image.

Remember that the base velocity image only tells us whether air is moving toward the radar (green colors) or away from the radar (red colors).  I drew small white arrows showing the direction of motion implied by the colors in the radar velocity image above.  Notice that all the arrows should point directly toward or directly away from the radar.  In the green area, all the arrows point toward the radar.  In the red area, all the arrows point away from the radar--matching what I just said.  We can see that the arrows point toward each other on either side of the outflow boundary line.  This implies that the air is indeed converging there.

And, as an added bonus, you can see a strong velocity couplet indicating a tornado associated with one of those powerful storms to the north!

Outflow boundaries like these are often the focal point for new storms to fire, particularly on days when conditions are very unstable.  Meteorologists use the radar to see these boundaries in advance so that they know areas where storm development is increasingly likely.

But why can we see these boundaries on radar?  They're often far from where it's raining, so what's reflecting the radar beam back?  There's a lot of debate about just what makes up these radar returns, and several factors contribute.

1. The air density tends to change rapidly from the cooler air on one side of the boundary to warmer air on the other side of the boundary.  When the radar beam goes through this abrupt density change, it bends the beam somewhat--kind of like that old trick of putting a pencil in a glass of water and it looks like the pencil is broken right where it enters the water.  This bending of the beam can direct the beam into the ground, other obstacles, or even bend some of the beam back toward the radar.  This change in what is called the refractive index across the boundary is some of what makes it visible.
2. Abrupt changes in winds on either side of the boundary can kick up a lot of dust  and leaves into the air.  This puts more stuff in the air for the radar beam to bounce into.
3. A lot of people believe that insects can get "collected" on the leading edge of these boundaries.  There  can be strong winds behind the boundary that act as a short of shovel, collecting lots of insects that are flying around along the leading edge of the cooler air.  The increased concentration of insects can also increase the radar returns.

So, there are outflow boundaries.  If you're looking for places that are good for storms to start firing, outflow boundaries provide a good place to start.

More on the Nocturnal Boundary Layer Wind Maximum

Continuing from my previous post, I mentioned that there was another mechanism that helped explain why there was this maximum of winds just above the surface starting in the evening and persisting through the night.  This other mechanism would work to explain why the nocturnal boundary layer wind maximum seemed to be stronger and more frequent over the Great Plains and other selected locations around the world.

So what lies at the heart of this mechanism?  The fact that the terrain of the Great Plains has a long, gradual slope.

Let's go back to the situation I was describing in my last post during the daytime.  During the day, the sun heats the earth's surface, which in turn warms the air above it.  It stands to reason, then, that (absent other effects) the closer air is to the surface, the warmer the air will be (with respect to air at the same horizontal level elsewhere).

Let's think about how this works with respect to a gradually sloping terrain like over the Great Plains.  Say that you start sitting up in the air at a mile above sea-level over Saint Louis.  Then, start heading west along a horizontal line, staying at a mile above sea-level.  As you head west, the terrain is slowly going to rise beneath you, and you'll end up closer and closer to the ground.  You'll finally run into the ground around Denver.

But, remember what I just said about the temperature.  So along that same horizontal line, the closer you got to the surface, the warmer the air should have become.  Therefore, the further west along that horizontal level, the closer that level is to the surface and the warmer the temperature.  Therefore, there exists a temperature gradient along that level, with relatively warmer air in the west and cooler air in the east.  This is simply a function of the sloping terrain.

 Just as a side note, remember whenever we have a temperature gradient, a thermal wind is implied.  The thermal wind is the change in the actual (geostrophic) wind with height.  In this case, with cooler air to the east and warmer air to the west, the thermal wind would point from north to south.  Keep that in mind for later.

I'm going to redraw the above graphic, showing shadings to separate relatively warm air from relatively cool air--remember these are along horizontal lines, though.  Furthermore, there's a limit to this effect in the vertical.  This only makes sense in regions of the atmosphere that are directly effected by air rising from the surface.  This layer of air where warm air bubbles up from the surface and cold air sinks to compensate is called the mixed layer.  I draw a dotted line at the top of this layer in the drawing below.

This is all well and good during the day, but what happens when the sun goes down?  As soon as the radiation away from the surface becomes greater than the incoming absorbed radiation from the sun, the surface will begin to cool.  This in turn cools the air right above the surface.  Just like we saw in my last post, this surface cool layer expands in depth as slightly warmer air from above entrains in and heat continues to be radiated out by the surface.

But now, let's remember the effect of the slope of the terrain again.  Now the opposite is happening--the closer you are to the surface, the colder the air should be.  If you draw a horizontal line through this new near-surface layer, then the air to the west along that level (being closer to the ground) is cooler than the air to the east.  So, we now have the opposite temperature gradient below the level of the nocturnal inversion.

Let's go back to these thermal wind arguments.  Remember above, with the cold air to the east, the thermal wind (that is, the way (geostrophic) winds change with height) points from north to south.  Below the level of the nocturnal inversion, the temperature gradient is reversed.  Now, with colder air to the west, the thermal wind vector points in the opposite direction--from south to north.

So now we have these two thermal winds, that is two "wind shears", that are induced by these opposite temperature gradients.  What does this mean for the wind structure?

Let's assume, like in my last blog post, that the ambient (geostrophic) wind direction happens to be out of the south.  So, the wind is blowing from south to north.  What happens when we apply the thermal wind vectors to this background wind?

You can see in the diagram above that in combining these two, we have a wind that increases with height  below the nocturnal inversion, then decreases with height  above the inversion.  The result?  A maximum in the wind speed right at the level of the nocturnal inversion.  Just what we were expecting to see.

You can see now that the maximum of this low-level nocturnal wind phenomenon is indeed slightly above the surface--in fact, more specifically, at the level of the nocturnal inversion.  Furthermore, you can see the strong wind shear implied in the near-surface layer--an essential ingredient for tornadic storm development.  It's no wonder that this nocturnal low-level wind maximum is a critical phenomenon to worry about when looking for severe weather evolution late in the day.

So, after the last post and this one, we've seen a lot about the reasoning behind that statement about the "low-level winds really kick up around sunset".  We naturally expect this because of the "shutting off" of surface friction and mixing with the establishment of a cool, stable surface layer right around sunset.  This frees the wind from the forces holding it back, causing a temporary imbalance in forces that accelerates the wind just above the ground.

However, in the central US, the sloping terrain further enhances this phenomenon.  The slope of the terrain allows horizontal temperature gradients to set up during the day (and reverse near the surface at night) which alters the structure of the wind in the vertical.  This structure works to focus the wind maximum right at the level of the nocturnal inversion.

So that was a somewhat technical description of my understanding of this "nocturnal boundary-layer wind maximum" phenomenon.  Hopefully it was helpful, or at least gave you something to think about.  At least now whenever you hear someone on the Weather Channel or the news talk about the "low-level winds picking up at nightfall," you might have a better idea of just what's going on.

The Nocturnal Boundary Layer Wind Maximum...Part 1

Tonight's topic is a bit more elaborate and complex than a lot of what I usually talk about here.  However, it's a subject I enjoy a lot and I hope people will find it useful.  I've made several drawings to try to illustrate what I'm talking about, so hopefully things won't seem too complicated.  I'm also splitting my discussion over two blog posts so as not to seem too overwhelming.

So, as we can see from the title of this post, tonight I plan to talk about the nocturnal boundary layer wind maximum.  What exactly is this?  It's the phenomenon that we so often hear about when people are talking about severe weather.  There's always this worry about storms potentially becoming more severe or tornadic because the "low-level winds tend to pick up right around sunset".  I've used this expression myself many times before, including many times on this blog.  Some people refer to this as "a/the low-level jet" (though there are other kinds of "low-level jets"...).  It's true--the winds just a little ways above the ground tend to increase rather dramatically right around sunset and persist that way into the night.  Since the winds right at the surface tend to die off right around sunset, this can set up a lot of wind shear in the low-levels, where winds are rapidly changing speed with height.  The vorticity associated with this wind shear can be tilted into storms where it can enhance their rotational ability.  Furthermore, any sort of squall line complex would most likely become much stronger if suddenly the winds behind it started picking up right above the ground.  So yes...this phenomenon tends to increase the possibility of severe weather in the early evening hours when those winds start increasing.

But why?  Why do these low-level winds pick up like that?  And why does this phenomenon seem more prevalent over areas like the Great Plains?

It turns out that there are believed to be two main mechanisms at work here.  In complicated terms, they are:

1. A force imbalance that results after turbulent mixing and surface friction are "shut off" following the establishment of the nocturnal inversion.
2. Horizontal temperature gradients due to sloping terrain help enhance the low-level wind maximum.

I'll try to explain my understanding of these as simply as I can.

I'll start with the first mechanism tonight.  Let's start during the daytime. Let's also assume that whatever the weather situation, it just so happens that the winds in the low-levels are coming out of the south.  This tends to happen preceding the passage of surface low-pressure systems.   The air wants to move north.  There's some sort of pressure gradient pushing it to the north.  But it's hard for the air in the low levels to move that way.  Why?

1. With a lot of heating during the day, there's a lot of turbulent motion as air heated near the surface rises and colder air from above sinks down.  All that up and down motion is going to interfere with any horizontal wind trying to push through.
2. Near the surface, there's a lot of obstacles--trees, buildings, hills--that also block the wind.  The "roughness" of the surface due to these obstacles acts as friction slowing the wind down.

But the wind will eventually arrive at a balance.  The pressure force (and Coriolis force) directing the winds to the north eventually will balance out with the friction force and there will be a net motion northward with no acceleration.  However, this final wind velocity is not as fast as the wind could go because of all those obstacles opposing it (it will be sub-geostrophic, in technical terms).

So what happens after the sun goes down?  At some point near sunset, the earth's surface begins radiating away more energy than it's absorbing from the sun.  This makes the surface begin to cool.  As the surface cools, the air near the surface also begins to cool.  This sets up a relatively cold layer right near the surface.  Since cold air is denser than cold air, it wants to sink to the surface.  Therefore, this is a very stable arrangement--the cold air is already below the warm air above, as it should be.  Such stability inhibits a lot of vertical motion and tends to quiet the gustiness of the winds down.  You'll often see temperature profiles at night or in the early morning with an abrupt cooling right above the surface. The level that separates this cool surface air from the relatively warmer air above is known as the nocturnal inversion

But what happens now that the surface has cooled down and become more stable?  The hot surface was the source of a lot of the turbulent motion in the air above as that heated air tried to rise, so now there is much less turbulent mixing.  Furthermore, the inversion level will quickly rise above the trees, hills and buildings, separating the free atmosphere above from this friction.  As a result, with the air above separated from the surface friction and with the turbulent mixing reduced, suddenly it's like the resistance to the wind has been "shut off" above the inversion.  The once-balanced force directing the wind is no longer in balance and, with nothing to impede it, the wind rapidly starts accelerating northward.

One way to think of this is that the wind is trying to play "catch-up" since it was held back all day by the constant interference of the friction and the turbulence.  So, right after the sun sets and this surface cold layer starts developing, it reduces the obstacles to the winds progress and it moves north much more quickly.

(This actually gets more complicated, and it was shown way back in 1957 by Blackadar that this sets up an inertial oscillation with the Coriolis effect that also causes the wind direction to rotate anti-cyclonically, but that's beyond what I want to talk about here...)

So we see how these winds just above the ground might really start accelerating right after sunset.  But this could happen anywhere.  And, several studies have shown that areas like the Great Plains see this phenomenon with a greater strength and frequency than is seen elsewhere.  So something else must be contributing...but I'll save that for my next post.  We'll get to bring back our old friend, the thermal wind...

The Importance of El Nino

Switching gears a bit, I wanted to talk a bit about El Nino and why it's such a big deal for us.

When we talk about El Nino (or, as it is usually called these days, the El Nino-Southern Oscillation (ENSO)), we're talking about a periodic shift in the sea-surface temperature pattern over the eastern and central equatorial Pacific.  This in turn affects pressure patterns throughout the world, leading to swings in the weather.  It's a pretty big deal.

But why is it such a big deal?  And how can we see this?  First, sea-surface temperatures have far-reaching impacts on the overall weather pattern.  Remember from my discussion about dewpoint temperatures that water has a much higher heat capacity than air--for the same mass of water and air, it takes more energy to raise the water temperature by one degree Celsius than it takes to raise the air temperature by one degree Celsius.  Now, think of the vast quantites of water we have spread throughout the world's oceans.  If sea-surface temperatures warm or cool by just one degree Celsius, that exchanges a lot of energy with the air.  All that energy goes into reshaping our weather patterns.  So, variations in sea-surface temperatures are crucial energy sources (or sinks!) for the atmosphere.

So, let's analyze variations in sea-surface temperatures.  If we understand how sea-surface temperatures vary in space and time, we can probably get a good idea about how in general our atmosphere might vary in space and time as well.  To do this, I'm going to take a 51 year record of monthly mean sea-surface temperatures across the globe from 1950-2001 (the NCEP reanalysis, if you want to know).  I did this as part of a project with Elizabeth Maroon earlier this year, though many other scientists have used this same technique to derive modes of variability in sea-surface temperatures.  We used a technique to break down the data called Empirical Orthogonal Functions (EOF) analysis (also called Singular Value Decomposition (SVD) or Principle Component Analysis (PCA)).  This uses some matrix algebra on the sea-surface temperature patterns to tell us three things:

1. Pictures of the dominant spatial patterns (or modes) of the sea-surface temperatures.
2. How big of a contribution each of those spatial patterns has to the total variability of the sea-surface temperatures.
3. How each of these spatial patterns varies in time throughout the dataset.

I know, it may seem a bit confusing now.  Hopefully when I start showing pictures things will start making more sense.

I start by doing this analysis on the raw sea-surface temperatures.  The output of the analysis gives pictures of the four dominant spatial patterns of sea-surface temperatures during those 51 years.  These are seen below, with the most dominant pattern to the upper left.

Fig 1 -- Dominant spatial modes from an EOF analysis of SSTs from 1951-2001.  The most dominant mode is to the upper left, with the 2nd most dominant mode to the upper right, 3rd to the lower left.

So these are the patterns of sea-surface temperatures that are most dominant over time.  Let's look at the most dominant one in the upper left corner.  Notice how it indicates warm temperatures in the tropics and colder temperatures toward the poles.  Well, that makes perfect sense--we know it's warmer in the tropics and colder at the poles.  So this EOF analysis is telling us that the dominant pattern of sea-surface temperatures is just the mean state of these sea-surface temperatures--it's always warmer in the tropics and colder in the poles.  We can ask ourselves how much of our sea-surface temperature patterns over time are explained by this simple mean state.  Here's a bar chart showing what percent of the variability of sea-surface temperatures are explained by each mode:

Click on the bar chart to make it bigger if you can't read the labels.  It shows that 70% (.7) of the total variability in sea-surface temperatures can just be explained by that first mode--by knowing that it's warm in the tropics and cold in the poles.  70% of the varibility--that's an awful lot.  But then again, most of the general circulation in our atmosphere is determined by that simple heat gradient, from warm at the equator to cold at the poles. So this makes sense.

All right--so this equator-to-pole difference explains a lot.  But that's kind of easy.  We know that there's more variability than that.  So, what we can do next is take our sea-surface temperatures over 51 years at each point and then subtract the mean value at each point.  This should effectively remove that mean state and let us just look at the remaining modes.  After removing that mean and repeating the EOF analysis, we get these spatial patterns:

Hmm.  Now let's again look at the most dominant mode in the upper left.  This shows an interesting pattern.  It looks like in the northern hemisphere, there's a lot of areas where the temperature is warmer.  In contrast, in the southern hemisphere it looks like that everywhere the ocean is colder.  Remember there is one more thing that this EOF analysis gives us--how each mode varies over time.  Let's look at a plot of how the magnitude of that mode varies over the 1950-2001 period.

Wow...this mode oscillates back an forth between positive and negative values rather frequently and regularly.  If we do a Fourier analysis on this time series, we can figure out just how frequently it completes an oscillation.

Hmm--we see from the Fourier analysis that the periodicity of this mode is almost all at one year intervals.  That means that this mode goes from a positive phase to a negative phase and back again exaclty once every year.

Remember the spatial pattern we're talking about here from the plot above--it was generally warmer in the northern hemisphere and colder in the southern hemisphere.  Combined with the other evidence (like the fact that it oscillates once per year), we can conclude that this represents the seasonal cycle--during June, July and August, it's summer in the northern hemisphere and winter in the southern hemisphere.  Since it takes the ocean a while to absorb and release its large amounts of heat, there's a bit of a delay--sea-surface temperatures actually peak in the fall (which is why hurricane season peaks in the fall, among other things...) and reach a minimum in spring.  However, you can see in the spatial plot above that one hemisphere is generally warm and the other hemisphere is cold.  During the opposite season, this structure flips--it becomes the negative of that spatial pattern.  That's why when we looked at the time series, the magnitude of the pattern oscillated between positive and negative values. It's just the seasonal cycle.

How much of the total variability does the seasonal cycle explain?  Let's return to the first bar chart again before we removed the overall mean--remember here the seasonal cycle is the second most dominant mode.

If we go to the second bar in the bar chart, we can see that the seasonal cycle accounts for only about 8% (.08) of the variability of sea-surface temperatures.  That's not so much compared to the 70% explained by the mean state of warm at the tropics and cold at the poles.  But still--it's enough to strongly contribute to our seasonal differences in weather.

All right, now we've gotten rid of the mean state, so let's get rid of this seasonal cycle, too.  We can do this by subtracting the mean value at each point for each month instead of just the overall mean value.  This means we'll get a sea-surface temperature anomaly relative to the average monthly sea-surface temperature.  If we repeat the EOF analysis on this new set of numbers, we get these spatial patterns:

Now, for any of you who have seem El Nino graphics before, the dominant mode here clearly looks like El Nino.  Warmer than normal sea-surface temperatures are indicated throughout the equitorial Pacific stretching westward from the west coast of South America--the classic El Nino pattern.  However, there also seems to be a sort of anti-El Nino pattern (like a La Nina) of cool temperatures in the same area in the second most dominant mode (the upper right image).  The work I did with Elizabeth Maroon delved a bit more into examining the split in ENSO signal between those modes (and other modes).  But that's beyond what I wanted to discuss here.  The key point is--once you remove the mean state (warm in the tropics and cold in the poles) and the seasonal cycle, then the dominant mode of variability in global sea-surface temperatures is governed by ENSO. 

How much variability is explained by this ENSO signal?  I'm going to switch bar charts now to the bar chart with ENSO as the dominant mode.  Remember, 70% of the variability was explained by the mean state, and about 8% of the variability was explained by the seasonal cycle.  That leaves 22% of the variability unaccounted for.  Here's a bar chart of the strength of the remaining modes:

Remember I switched the bar chart so now mode 1 is the El Nino mode described above.  Notice that this mode only explains about 3.7% (.037) of the remaining variability in sea-surface temperatures.  Since it turns out that the second mode also strongly tracks ENSO and that explains about 2.5%, we can reasonably infer that overall the ENSO pattern explains about 6.2% of the remaining variability of ocean sea-surface temperatures.  That's 6.2% of the remaining 22%--or about 1.36% of the total variability of sea-surface temperatures.  That's really small, particularly when compared to the seasonal cycle and definitely when compared to the mean state.  Yet ENSO is so important for variations in the ocean and in our weather and climate.  Pretty incredible.

If you want further proof that this mode represents ENSO, here's a chart that compares it to an actual ENSO index.  The top graph shows the official ENSO 3.4 index from 1950-2001, which is commonly used to describe the strength of an El Nino of La Nina event over time.  Below it in bold red is the variation in the strength of the El Nino mode over time.  The two match almost exactly.  The light blue line shows the trace of the negative of that second, anti-El Nino mode over time.  It, too correlates strongly with the actual ENSO signal in the panel above.

So what's my point with all of this?  We often talk about how important the ENSO variability is for determining monthly or seasonal climate forecasts.  We hear all the time about how, "Oh, it's going to be wetter because this is a La Nina year..." or "It's going to be hot because it's an El Nino year...".  But, really, how important is ENSO?

On one hand, it's not so important--we saw that only a little over 1% of the total variability of sea-surface temperatures can be explained by ENSO modes.  That's such a small amount of the variability.

On the other hand, once we remove the mean state of sea-surface temperatures and the known, predictable seasonal cycle, the ENSO modes are the dominant mode of variability in sea-surface temperatures!  Since we can do a decent job of predicting the mean state of the sea-surface temperatures and also have a good grasp of the seasonal cycle, the next thing we need to get a handle on to increase predictability is ENSO.  But we still don't have a good idea of how to predict ENSO.  And so, even this little effect that only accounts for 1% of the variability of the system stands in the way of our being able to make better long-term predictions.  In that respect, ENSO is very, very important.

As always, email me or post a comment if you have any questions.

Arizona Wildfires and Trajectory Models

Large-scale ridging continues across the central and eastern US through the middle of this week, with some storms firing around the northern (and Gulf Coast) periphery of this sprawling surface high.  With clear skies and general subsidence, near record-high temperatures are being reported across much of the central part of the country.

But, that's not what I want to talk about tonight.  When sprawling high pressure backs up against mountain ranges, the potential exists for some strong cross-barrier pressure gradients to develop.  This in turn can lead to strong winds which is bad news for people fighting wildfires.  Here's a look at the National Weather Service warning map for this evening.  Note how much of eastern Arizona, New Mexico, and the panhandles region are under red flag warnings (the pink colors).  Strong winds combined with dry air and vegetation with no rain in sight are making ideal conditions for wildfires.

Fig 1 -- NWS watches, warnings and advisories as if 0058Z, June 8, 2011.

As you've probably heard on the news by now, large wildfires are raging across eastern Arizona.  We can see the huge smoke plumes billowing from these fires on visible satellite imagery.

Fig 2 --  GOES-W visible satellite image from 00Z, June 8, 2011.  From the HOOT website.

It's impressive just how large of an area those smoke plumes are covering.  You can see that they blow off in a northeasterly direction, giving a general indication of the wind direction over that area.  Also on this visible satellite image we can see how the subsidence across the plains and the midwest has inhibited cloud formation, leaving clear skies.  Some showers and storms were occurring over Montana, and you can see the "marine push" of low clouds off of the Pacific Ocean that has moved into western Washington today.  There's a lot going on for a "quiet" weather day.

Returning to the wildfires, you can also see the smoke plumes showing up in the infrared satellite imagery.

Fig 3 -- GOES-W IR satellite image from 00Z, June 8, 2011.  From the HOOT website.

Infrared satellite imagery is usually shown in terms of a temperature scale, with the red, yellows and greens being colder and the blues and purples being warmer (I know...it's kind of reverse from how you think it should be...).  Notice how the smoke plumes show up as bright blues, which (according to the color scale on the left) are colder than the purples and dark blues that surround them.  Those purples and dark blues are showing roughly the surface temperature--with no other clouds above, the surface is the significant contributor to the outgoing infrared radiation measured by the satellite.  What's fascinating, then, is that the smoke plumes are cooler than the temperature at the surface.  Even though the source of the smoke plumes are fires that are much, much hotter than the ambient surface temperature, like pretty much everything else in the atmosphere the smoke cools as it rises.  The fact that we're seeing returns from the smoke plume that are cooler than the surface temperatures mean that the smoke has risen very far up into the atmosphere--and cooled down a lot.

So we see that the smoke is generally blowing off to the northeast.  Where will this smoke go?  We can use the wind information from our numerical weather models to run what is called a trajectory model to determine the path the smoke will most likely take over the next 48 hours (at least, according to our weather models).  One nice model that is commonly used for doing this is the NOAA HYSPLIT model.  It's very easy to use, and in fact it has an online interface here that allows you to enter in information to their form to do your very own trajectory model runs.  It's pretty cool.

Anyhow, I started a trajectory model at the latitude and longitude of a point in the middle of where all the fires were around noon CDT today.  I started air parcels at 100m, 500m and 1000m  above the ground at that location and asked the model to show the trajectories of these air parcels over the next 48 hours.  The result is this:

 

This HYSPLIT trajectory model uses the output of the NAM weather model, specifically the wind forecasts, to predict where a blob of air at the coordinates and heights I specified will move in the future.  I ran the model for 48 hours.  In the output plot, the red line shows the path of the air that started at 100m above ground, the blue line is for 500m above the ground and the green line is for 1000m above the ground.  In the top half of the image, you can see the direction that the winds are forecast to blow the air.  So, from this, we can infer that smoke from those fires will head to the northeast (which matches up nicely with what we saw in the satellite images).  By 48 hours, the air at 500m and 1000m looks to have made it all the way up to southeastern South Dakota.  However, in the bottom part of the plot it shows the height above the ground of each parcel of air as time moves forward.  Notice that by the time the model run ends 48 hours later, the air that started at 500m has moved way up to probably over 10000m---very far above the ground.  The air that started at 1000m, though, stays much closer to the ground, even if it still rises to over 2000m.  And finally the 100m air pretty much runs into the ground and gets lost in the Texas panhandle somewhere.

So what can we take from these trajectory models?  Areas immediately to the east and northeast of the fire can expect a lot of air quality issues from smoke.  The further you go out along the path, though, the more spread out and diffuse the smoke becomes.  However, I still would not be surprised to see reports of hazy conditions in Nebraska over the next few days as the smoke from fires moves northeast. 

Sometimes it takes some effort to keep storms going...

In my last post I talked about how it looked like this weekend would be rather quiet weather-wise across the eastern half of the country due to hints at a building ridge across the region.  Well, this has turned out to be partially correct.  A surface high-pressure ridge has built across the southern US with a secondary ridge maximum further north in Canada.  There's week troughing in between these two pressure maxima, and we're seeing storms fire in that area tonight.

Fig 1 -- Sea-level pressure (contours) and composite radar at 330Z, June 5, 2011.

The strongest areas of storms is moving through the Indiana and Ohio area late this evening.  A glance at the 00Z sounding from southern Ohio shows good instability with moderately steep lapse rates and high CAPE, so the thermodynamic environment is certainly favorable for storms.

Fig 2 -- KILN sounding from 00Z, June 5, 2011.

However, like I said earlier, looking above the surface there is large-scale ridging that has built aloft across the eastern US, which we would usually think of as not conducive to storms.  The upper-level jet is rather weak, at least with how it's sampled at 300mb.  The color shading of winds on the image below shows a jet streak earlier this evening across Minnesota and the upper peninsula of Michigan at 00Z when the storms were moving through central Illinois.  Though the color shading shows a jet streak further north, I circled an area where you can see wind barbs indicating winds over 50 knots surrounded by lower-speed winds further south.  We could consider this area part of the jet streak, in which case the area where the storms were located in central Illinois would be under the right entrance region of the jet streak.  According to the four quadrant model, that would be an area of divergence aloft, supporting upward vertical motion.

Fig 3 -- Analysis of 300mb winds (colors and barbs) and heights (contours) at 00Z, June 5, 2011.

So we could construe a case for why we are seeing stronger storms there--there is weak upper-level support.  Very weak support.  But that jet has looked to be strengthening a bit, which has allowed storms to actually increase in coverage as the night has worn on.  What is causing this?

It goes back to those good old thermal wind arguments.  Remember that temperature gradients at the lower-levels influence the winds aloft through a mechanism called the thermal wind.  If we look at a surface map from 0300Z this evening, we can see that there is indeed a temperature gradient with warm air to the south and cooler air to the north between those two high pressure centers I talked about before.  In meteorologist-speak, a region like this where there are horizontal temperature gradients is called a baroclinic zone.

Fig 4 -- Surface analysis of sea-level pressure (contours), temperatures (colors) and winds (barbs)  at 0300Z, June 5, 2011.

I outlined the baroclinic zone with a red box in the map above.  You can see that in that region, temperature drops from warm in the south to cooler in the north.  Coincidentally, that's kind of where we're seeing our jet streak above--at least on the western end of the baroclinic zone.  Remember--the thermal wind relation means winds aloft are affected by temperature gradients below.

I mentioned that the jet aloft seemed to be strengthening, which continued to provide limited upper-air support (divergence aloft) and allowed storms to continue overnight.  Can we see a reason for this?  The wind barbs are kind of sparse on the surface map above, so below is a hybrid map I got from the College of DuPage website.  It has a water vapor satellite image in the background and overlaid on top in yellow are surface wind streamlines.  Think of a streamline as a continuous arrow that always follows the wind direction at a given moment in time.  They're useful to illustrate how wind is flowing.

Fig 5 -- GOES water vapor imagery at 0245Z overlaid by surface wind streamlines at 0300Z, June 5, 2011.

The red box roughly outlines the same "baroclinic zone" region in the surface map above (it's somewhat difficult to pin down just where the strongest temperature gradients are).  Notice what the streamlines are doing in that area.  In the northern half of the box, the winds are generally coming out of the north, but then they split and go east and west.  Similarly, in the southern half of the box, the winds come from the south before also splitting to go east and west.  This sort of wind pattern is known as a deformation pattern or confluent flow.

Now consider the effect of this wind pattern on the baroclinic zone.  The southerly winds in the southern half of the box are pushing the warm air to the south further north.  At the same time, the northerly winds in the northern half of the box are pushing the cooler air to the north further south.  Can you see how, with winds like that, it would work to strengthen the temperature gradient?

One fun feature of a confluent wind pattern like that is that there can be very little convergence of the winds--they don't just run straight into each other and stop.  If we had convergent winds at the surface, we know that where winds converge that tends to force air to rise--and if we had rising air we'd expect to see storms or lots of clouds or some evidence of that.  We can see that there is some wispy light white color on the water vapor image along and just north of that confluent zone where the winds are coming together out on the western end of the confluent region.  These somewhat light gray return indicating some enhanced water vapor being lifted into the upper troposphere.  So, there must be a little bit of convergence near the surface there forcing the rising motion.  But the fact that we don't see lots of storms popping up in that area indicates that the convergence is probably pretty weak (there's also a weak capping inversion on some soundings in that area which is working against rising motion).  The flow is probably mostly confluent.  To the east we can see that there's a very bright white area over Indiana and Ohio, indicating lots of water vapor in the upper troposphere.  That points to strong vertical motion lofting all that water vapor up there.  But that makes sense--that's where the storms are.  To support all that rising motion, there must be some good convergence at the surface, so the surface wind field is probably more convergent there.

Remember, confluent flow works to increase the temperature gradient.  This is a form of what is known as frontogenesis--the creation of a front.  And, because of the thermal wind relation, that increasing temperature gradient should lead to an increase in the strength of the jet above.  So--it looks like surface wind patterns are helping to keep the upper-level jet strong, which in turn is helping storms to sustain themselves over Ohio.  Pretty impressive for what otherwise would be a rather "boring" ridge...