Thursday, March 23, 2017

When is the air aloft the coldest and driest on average? Now!

Strange enough that one might think is belongs in some kind of Ripley's Weather Believe or Not.

What part of the year is the air above the Pacific Northwest typically the driest (least amount of water vapor)?

What part of the year is the above the Pacific Northwest typically the coldest?

The answers to these two questions are the same:  right around now!  But why?

Let's start with a measure of the total water vapor in a vertical column (called precipitable water) for Quillayute, WA (UIL), on the NW Washington coast (see below).   The black line is the average and the red line is the extreme high values. Lowest values (driest air)  in late March/early April.  Interestingly, the driest air is not when our precipitation is the least (late July/early August).  The amount of moist is highest during our driest period.  Very strange.

Next, let's go to a specific level (850 hPa--about 5000 ft).  The mixing ratio (the amount of water vapor-in grams- per kilogram of dry air) shows a similar pattern, with driest conditions in early spring.

How do we explain this weird situation?  The answer is found with temperature.

The amount of water vapor that can be held (or contained) in a volume of air depends on temperature, with warm air able to hold more water vapor.  Here is the temperature at 850 hPa (again about 5000 ft).  Ah ha!  It looks like the moisture!   The warmest temperatures aloft are in early August and the coolest average temperatures are in late winter (March).

So in late winter/early spring when the atmosphere aloft is coolest, the moisture content is less since cold air can hold less moisture than warm air.

But that leaves another question.  Why are air temperatures aloft coolest in March? Why aren't the temperatures aloft coolest when the sun is weakest (late December)?   

The reason is that there is substantial thermal inertia of the atmosphere--it takes a while to warm it up.   Like a giant flywheel.   And remember that the atmosphere cools as along as long as the amount of energy leaving the atmosphere (by radiation and other processes) exceeds what is coming in (solar radiation, heat provided by the condensation of water vapor)

The surface of the earth has less thermal inertia and tend to respond more rapidly to heating/cooling at the earth's surface then the atmosphere above.  Thus, the lowest surface air temperatures tend to be in middle to late January in our region, not the spring.

There is an interesting meteorological implication of the different rate of heating between air near the surface and aloft:  the atmosphere over our region tends to be most unstable (tendency to convect) during spring compared to any other time of the year.

The atmosphere becomes less stable when the rate of cooling with height (called the lapse rate) is greatest.  If in late winter or early spring, the ground warms up faster than the air aloft, then the lapse rate becomes larger during that period.   This is particularly true in spring when the sun (and thus heating near the ground) is getting large.

This figure shows the lapse rate in the lowest 10,000 ft above Quilluyate across the year (black is average, red line is extreme max, blue line extreme min).  The lapse rate is largest in April.

Large lapse rates promote instability, which produces cumulus and cumulonimbus clouds, which in turn bring the famous convective rain showers of NW spring.  So spring is a showery period in our region because of the surface warms more quickly than the atmosphere above.

Tuesday, March 21, 2017

A Good Winter for Northwest Potholes: Why?

This has been a big year for Northwest potholes, feared by drivers and bicyclists alike.  And should not be a surprise, considering the weather has been "ideal" for producing potholes:  more cold (sub-freezing) temperatures than the past few years and lots of precipitation.

There has been plenty of media coverage of the pothole epidemic  (see below from KING5 and KIRO)

One well-covered pothole in Spokane took out 8 cars in a few minutes!  In Spokane, the pothole problem became so crippling for cyclists and cars, that anarchists (Portland Anarchist Road Care) started filling them in!  When anarchist are fixing roads instead of tearing stuff down, you know you have a problem.

Now, Seattle is well organized in the pothole business and the city even has a pothole map.  The figure below shows the potholes that have are either pending to be fixed (blue) or repaired during the past 90 days.  Road dangers lurk in much of the city.  Be careful out there.

 So why has this been such a bountiful year for axle-breaking, tire-destroying, potholes in our region?

 Because it has been much colder than the past few years, with lots of sub-freezing weather and loads of precipitation.

Why is subfreezing weather important?   To understand why you need to know how water density (and volume) changes with temperature.   The figure below shows how the volume of a gram of water varies with temperature.  Starting above freezing, as water cools down it reaches maximum density (minimum volume) around 4C, and then the volume increases slowly towards freezing.  But then things get exciting:  the volume increases substantially as water freezes.  To put it another way, water expands substantially as it transitions from liquid water to ice.

Such expansion can produce tremendous force--cracking rocks or bursting pipes.

Water can get below a roadbed, either through small cracks or from the side.  If temperatures drop below freezing, the water can expand, push up upon and breaking the roadway (see schematic below)  When the temperature warms, the ice contracts leaving a void below the roadway, which can result in the road collapsing  due to the weight of cars.  The more times this process is repeated, the more the road can be undermined.

So below-freezing temperatures are helpful to produce potholes, as is plentiful precipitation to supply the water that freezes.  

Let's take a look at temperatures this and previous winters.  At Seattle (see below), lots of surface air temperatures (yellow line) that dropped below the normal lows (blue line) and freezing this winter.  Much more that the previous two years.
At Spokane, it was an amazingly cold year, with several days dropping to 0F or below!
Portland had many days below freezing this winter, producing lots of ice and snow.

The figure below shows that all the urban areas were substantially wetter than normal, supplying lots of water to invade the sub-surface between the roadways

The bottom line of all this.  A wet year with lots of moisture invaded roadway subsurfaces.   With the coldest winter in years, with lots of subfreezing temperatures, there were excellent conditions for the production of tire-bursting potholes in Seattle, Portland and Spokane.

One positive thing:  it could have been worse:

Monday, March 20, 2017

Might Bipartisan Actions Revolutionize U.S. Weather Prediction?

 There is now a major opportunity to lay the basis for far better weather prediction in the U.S.  

And the effort could be completely bipartisan.    It would also provide an example of how both sides of the aisle can work together to make major improvements in a key national capability--weather prediction-- saving lives, protecting property, and substantially enhancing the economic vitality of the U.S.

There are two bipartisan bills before Congress right now that are worthy of support:

1. The Weather Research and Forecasting Innovation Act of 2017:  H.R. 353 sponsored by Rep. Frank Lucas (R OK), Suzanne Bonamici (D OR), Lamar Smith ( TX), and others. And its carbon-copy version in the Senate.

2.  Radar Gap Study Act.  Text is here.  Sponsored by Senator Maria Cantwell (D WA),  Senator Richard Burr and Tom Tillis (R NC). Representative Robert Pittenger (R-NC) introduced companion legislation in the House of Representatives.

The Weather Research and Forecasting Innovation Act is extraordinarily forward leaning.  Its goal is to:

To improve the National Oceanic and Atmospheric Administration’s weather research through a focused program of investment on affordable and attainable advances in observational, computing, and modeling capabilities to support substantial improvement in weather forecasting and prediction of high impact weather events, to expand commercial opportunities for the provision of weather data, and for other purposes.

The specifics of the bill are enough to warm the heart of any American concerned about the quality  and future U.S. weather prediction, including:

1.  Organization of a coherent research program for improving U.S. weather science and prediction, including extramural (outside of the U.S. government) research.
2.  Develop rational methods for designing and supporting the U.S. weather observation system (amazingly this had really not been done).
3.  Organized efforts to improve U.S. tornado, hurricane, and subseasonal (less than a few months) forecasting.
4.  Requirement that the US Air Force explain their problematic selection of a non-U.S. weather modeling system for their operational requirements (big mistake by the way)
5.  Calls for the evaluation of more private sector weather observation assets.
6.  Annual reviews of the computer resources available for U.S. weather prediction.

..and much more.  The bill includes the financial resources needed for the above.    

Basically Congress is telling the NOAA/National Weather Service that is expect U.S. should be state-of-the-science and that the time for excuses are over.  Some in NOAA might be discomfited that Congress is providing a lot of guidance about what needs to be done.  But quite frankly, progress has been too slow and it is going to take Congress to move the U.S. weather prediction effort into higher gear.

The radar act sponsored by Senator Cantwell and her Republican colleagues from North Carolina?

It directs the National Weather Service (NWS) to determine which areas of the country have inadequate weather radar and develop a plan to improve radar coverage.  And there are major gaps in the radar coverage such the coastal zone west of Oregon, the eastern slopes of the Cascades, and much of eastern Oregon.  The National Weather Service radar coverage below 4, 6, and 10K feet ABOVE GROUND LEVEL (shown below for country and the NW) shows major gaps in the west, but the situation is MUCH worse than presented here.  Many of the radars start out high and thus the radar beams can miss the critical lower atmosphere. Radar coverage is very much needed along the eastern slopes of the Cascades for wildfire management and localized flash flood prediction.

I think we can be very hopeful that these important legislative measures will have a decent chance of passage.   Weather prediction is important for the entire country irrespective of one's political bent. Red states suffer from hurricanes and severe thunderstorms.  Blue states from atmospheric rivers and coastal storms.  Both endure drought, floods, wildfires, and windstorms.  Both Red and Blue state economies are highly vulnerable to weather for agriculture, transportation and more.

And yes, weather prediction (ranging from hourly to seasonal prediction) is not climate prediction, so it lacks the controversy of decadal to century-long forecast of greenhouse gas impacts.  So the current administration can support it.

Saturday, March 18, 2017

A Year's Worth of Water in 5 Months

Meteorologists and hydrologists call it the water year, the period between October 1 and September 30.  Each year the cumulative precipitation for the water year is totalled starting October 1.

The water year is a natural precipitation measure along the U.S. West Coast because we typically get very little precipitation over the summer and precipitation generally is not significant until October.

Thus, there is a hydrological reset each summer, with the soils dried, the snowpack melted, and the rivers dropping to low early fall levels. So October 1 is a good date to start the new water season.

Now the amazing thing.  Five and one-half months into the 2016-2017 water year, many Northwest stations have ALREADY received their total water year amounts.   You got that right....if there was not another drop of rain or flake of snow for the next 6.5 months, these stations would have their full normal precipitation for the water year.

By late September there is generally very little snowpack left in the Cascades

Want proof?  No problem.   The National Weather Service has some wonderful water year plots, with dark green showing actual accumulated precipitation this water year and light green indicating normal values (shown below).

Here is the plot for Seattle-Tacoma Airport for water year total precipitation and snow.    Amazing... Sea-Tac passed the normal water year amount during the past week...and the show is not over yet. The late winter has been very wet--particularly early February and the last few weeks.  More snow than normal too...mainly from a crazy local snowfall in early February.  Note how the light green curve (normal year) plateaus out after May 1.  And in normal year, the bulk of our precipitation falls between Nov 1 and April 1---our wet season.

Seattle Tacoma Airport Water Year Plot

But let's not stop there.  Let's head to the Washington coast at Hoquiam, where the total amount (63.25 inches) is just behind the normal water year.  They will cross the line this coming week.

 Hoquiam Water Year

But why only look west of the Cascade crest?  Consider Spokane, where the total (17.66 inches) is already well past the normal water year.

Spokane Water Year

Another way to look at the water year situation is in map form.  Here is the percent of average precipitation precipitation for the current water year (again, since October 1) for the entire West (courtesy of the Western Region Climate Center). Virtually the entire West Coast has higher than normal precipitation, with California, Montana, and eastern WA being particularly wet.

Now, a question many of you are asking is whether this anomalous year is an indication of a trend towards wetter winters and thus might be the sign of some cause (like global warming).   To answer, here is a plot of the long-term trend of water year precipitation (from the NOAA/NWS ESRL website).  Bottom line:  no significant trend since 1948.  Thus, what we are experiencing is probably just natural variability.

This plot is consistent with our best climate models, which suggest that global warming will have only a small impact (slight increase) in regional annual precipitation by the end of this century. Climate models project that Northwest will not lose our substantial precipitation as the earth warms, but more of it will fall as rain rather than snow.

Thursday, March 16, 2017

The Nor'Easter of March 14: What are its Lessons for the Weather Community?

On March 14th, a storm rapidly developed off the Carolina Coast, quickly moved northward, crossing eastern Long Island and SE New England before exiting the region.  It produced very strong winds (gusts reaching 40-60 mph over the region), heavy snow (1-2 feet) in the interior, and a nasty slushy mix over the coastal zone. (see snow total map from WeatherBell, Inc.)

In some ways this storm was a great success, a a major event predicted nearly a week out, with verifying strong winds, and snow for many.  But in major coastal areas, blizzard warnings and predictions of 1-2 feet did not pan out.   As a result, some in the media and a few major politicians were critical of the National Weather Service, who they claimed suppressed changing information on Monday that suggested a lesser coastal event.

In this blog, I will examine this storm and note that it reveals some major issues with modern weather prediction.  Issues that are general and reflect problems we had with the Northwest windstorm bust of October 2016.

As noted note above, this forecast could be considered a great success for modern weather prediction, with a real heads up 4-5 days ahead of time.  Here are the NWS official surface analyses at 5 AM and 1 PM on Tuesday, March 14th (sea level pressure shown).  The low (central pressure of 986 hPa) rapidly intensified (to 978 hPa) as it moved to the tip of Long Island)

The NOAA/NWS GFS forecast valid 5 AM on Tuesday made Friday (4AM), 96 hours before the event, had the right idea and stuck to it (shading is lower atmosphere temperatures).   Based on these forecasts, airlines and others started taking pre-emptive action, including suggesting that travelers change their reservations.

Virtually all the major modeling systems (NOAA GFS, European Center, UKMET office, Canadian CMC) honed into a similar solution, with minor (but important) differences in track and intensity.

The implications for the Northeast U.S. were serious.  Such a strong storm, with attendant large pressure gradients, would certainly produce strong winds over the Northeast.  With cool air over the continent, substantial snow was in the offering for many folks.  Where heavy snow and winds came together, blizzard conditions (heavy snow, greater than 35 mph winds, low visibility) would occur.

Blizzard conditions

But there was in issue.  A big one.  The storm was sweeping warm air into it (see red colors above) aloft and the water temperatures are relatively warm.  Thus, there would be a transition zone between snow inland and rain offshore, where a wintry mix of snow, sleet, freezing rain, and rain would occur. The fabled rain-snow line.   And clearly the line would be somewhere along or near the coast.   If it was just offshore, the NY Metro area would have an historic and crippling blizzard.  If it was just along the coast, NY could get a slush storm or rain.

And predicting this line is not easy.  It is dependent on the movement of different temperature air around the storm.  It is dependent on the intensity of vertical air motions (which can influence temperature).  It is dependent on the amount of precipitation (since the evaporation and melting of precipitation can change the temperature profile).  It is dependent on coastal effects (where temperature and surface variations are large).  Bottom line: the rain-snow line can be a real challenge for even the best models and forecasters. And in a coastal area, it is critically dependent on the exact track and intensity of a storm.  And an inability to diagnose and prediction physical details like cloud processes.

On Friday and early in the weekend, most of the model guidance suggested that the rain-snow line would be just offshore, indicated New York and Boston would have mainly a snow event, with the most probable amounts being 1-2 feet.  This guidance included high resolution deterministic forecasts and lower-resolution ensembles of many forecasts (used to define uncertainty).

On Sunday, the NWS SREF (Short-Range Ensemble Forecasting System) showed some uncertainty for the total snow forecast at New York's JFK airport (see below), with an ensemble average of around 12 inches and a range from an inch to 29 inches.

The ensemble-based probabilities of precipitation type (below), were dominated by snow (blue lines)

But by Monday morning, the situation had changed substantially.  The morning (8 AM) run of the NWS SREF ensemble had decreased the snow to about 10 inches, with more of the ensembles going for lower amounts.

The probability of rain (green) was gaining on snow (blue) and was higher than snow at 11 AM (18 UTC) Tuesday.

The 2 PM run of the SREF went much further, suggesting an event that would start as snow and then transition to rain (see below)

But on Monday, we were closer to the event and forecasters had powerful, more modern tools available.

The future of forecasting such events is high-resolution ensembles, using convection-allowing grid spacing (like 3-km).   The National Weather Service does not have such an ensemble system (and it should!), but the National Center for Atmospheric Research (NCAR) does (but a small one with only 10 members).   And NCAR ran such an ensemble starting 5 AM on Monday.  The average of the ensemble (the ensemble mean) showed a huge coastal snow gradient, with 6-10 inches over Long Island, with heaviest amounts to the west and north.  But a slight shift would have huge impacts on NY snow.   This kind of situation suggest large uncertainty.

The NCAR ensemble showed lot of uncertain for JFK airport, with a mean of around 8 inches (see below) and a spread from 2-17 inches.   It also indicated a change from snow to rain (not shown)

And now the problem.   Here is the National Weather Service forecast released 4 AM Monday, one that uses their new approach to presenting uncertainty.  The suggested a most probable value for JFK airport of 17 inches and a range from 8 to 22.     This was the forecast that was in place for most of Monday morning when a lot decisions were being made.   And in addition, there was a winter storm warning and blizzard warning in place over New York on Monday.  Nothing like a blizzard warning to get media juices going.

And as uncertainties in the forecast were increasing, the NWS doubled down on the blizzard warning:

By late on Monday, the models shown above were clearly edging towards a lesser event and shorter-range rapid refresh models like HRRR was becoming available (HRRR is initialized every hour and run out for 18 hr).   HRRR uses very high resolution (3-km grid spacing), is initialized with lots of regional assets, and the snow output makes use of variable density snow, which gives more accurate totals.

Here is the 18h HRRR snow total starting 5 PM Monday, March 14th, which encompasses pretty much the whole storm in NY.  3-6 inches over the eastern end of LI and the immediate south shore of LI, increasing to the NW, with perhaps 12-15 inches would be expected over the NW side of NY city.  Roughly 10-11 inches around JFK.

Still too much, but the pattern is very good.  A new version of HRRR, called HRRRx, does even better, with the suggestion that better physics descriptions helps with the overprediction of snow.

Now I have been fixated about snow in the above discussion.  Winds were important as well, and the models and the NWS forecasts were very realistic about their strength and duration.

So what is the bottom line of all this?   In many ways this was a very successful forecast that shows how far weather forecasting technology has come.

1.  The threat of a major Nor'Easter was identified 5-7 days in advance.
2.  The large scale prediction was quite accurate, but there were minor but important track and structural errors.
3.  The winds were forecast quite well.
4.  The general structure of the snowfall was handled reasonably, but the rain-snow line was displaced too far to the southeast by the models, resulting in an overprediction of snow over NY and Boston.
5.   There was considerable evidence of forecast uncertainty in the days before, with the possibility of less snow becoming more evident on Monday, March 14.  In particular, it become clear by Monday afternoon that a transition from snow to rain was probable over LI and much of NY City.
6.   Forecasters held on to the heavy snow/blizzard forecasts on Monday and probably should have backed off that forecast by Monday afternoon, highlighting the change to rain more.

So what are take home messages?

1.  The NWS must continue to improve its forecast technology, including high-resolution ensembles that provide uncertainty and probabilistic guidance.  The NWS has been delaying too long in building a convection-allowing operational ensemble system.  Congress needs to intervene if necessary.

2.  NWS forecasts have to transition to a probabilistic framework, where probabilities are given for various outcomes.  The old style watch-warning system is really not effective in a new world of uncertainty and probabilistic prediction.

3.   Forecasts much continuously evolve as more or better information comes in.  Forecasters should not try to second guess users or keep intense forecasts in place to encourage "right" decision making.