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This is what I was talking about in this mornings post. (http://www.drroyspencer.com/)


NASA AIRS: 80% of U.S. Warming has been at Night

April 30th, 2019 by Roy W. Spencer, Ph. D.

I have previously addressed the NASA study that concluded the AIRS satellite temperatures “verified global warming trends“. The AIRS is an infrared temperature sounding instrument on the NASA Aqua satellite, providing data since late 2002 (over 16 years). All results in that study, and presented here, are based upon infrared measurements alone, with no microwave temperature sounder data being used in these products.

That reported study addressed only the surface “skin” temperature measurements, but the AIRS is also used to retrieve temperature profiles throughout the troposphere and stratosphere — that’s 99.9% of the total mass of the atmosphere.

Since AIRS data are also used to retrieve a 2 meter temperature (the traditional surface air temperature measurement height), I was curious why that wasn’t used instead of the surface skin temperature. Also, AIRS allows me to compare to our UAH tropospheric deep-layer temperature products.

So, I downloaded the entire archive of monthly average AIRS temperature retrievals on a 1 deg. lat/lon grid (85 GB of data). I’ve been analyzing those data over various regions (global, tropical, land, ocean). While there are a lot of interesting results I could show, today I’m going to focus just on the United States.

Because the Aqua satellite observes at nominal local times of 1:30 a.m. and 1:30 p.m., this allows separation of data into “day” and “night”. It is well known that recent warming of surface air temperatures (both in the U.S. and globally) has been stronger at night than during the day, but the AIRS data shows just how dramatic the day-night difference is… keeping in mind this is only the most recent 16.6 years (since September 2002):


AIRS temperature trend profiles averaged over the contiguous United States, Sept. 2002 through March 2019. Gray represents an average of day and night. Trends are based upon monthly departures from the average seasonal cycle during 2003-2018. The UAH LT temperature trend (and it’s approximate vertical extent) is in violet, and NOAA surface air temperature trends (Tmax, Tmin, Tavg) are indicated by triangles. The open circles are the T2m retrievals, which appear to be less trustworthy than the Tskin retrievals.

The AIRS surface skin temperature trend at night (1:30 a.m.) is a whopping +0.57 C/decade, while the daytime (1:30 p.m.) trend is only +0.15 C/decade. This is a bigger diurnal difference than indicated by the NOAA Tmax and Tmin trends (triangles in the above plot). Admittedly, 1:30 a.m. and 1:30 pm are not when the lowest and highest temperatures of the day occur, but I wouldn’t expect as large a difference in trends as is seen here, at least at night.

Furthermore, these day-night differences extend up through the lowertroposphere, to higher than 850 mb (about 5,000 ft altitude), even showing up at 700 mb (about 12,000 ft. altitude).

This behavior also shows up in globally-averaged land areas, and reverses over the ocean (but with a much weaker day-night difference). I will report on this at some point in the future.

If real, these large day-night differences in temperature trends is fascinating behavior. My first suspicion is that it has something to do with a change in moist convection and cloud activity during warming. For instance more clouds would reduce daytime warming but increase nighttime warming. But I looked at the seasonal variations in these signatures and (unexpectedly) the day-night difference is greatest in winter (DJF) when there is the least convective activity and weakest in summer (JJA) when there is the most convective activity.

One possibility is that there is a problem with the AIRS temperature retrievals (now at Version 6). But it seems unlikely that this problem would extend through such a large depth of the lower troposphere. I can’t think of any reason why there would be such a large bias between day and night retrievals when it can be seen in the above figure that there is essentially no difference from the 500 mb level upward.

It should be kept in mind that the lower tropospheric and surface temperatures can only be measured by AIRS in the absence of clouds (or in between clouds). I have no idea how much of an effect this sampling bias would have on the results.

Finally, note how well the AIRS low- to mid-troposphere temperature trends match the bulk trend in our UAH LT product. I will be examining this further for larger areas as well.


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Sounds like the NWS has fixed the new GFS issues and are ready to proceed into the testing phase.


In October 2018, the NCEP Office of the Director (OD) approved
proceeding with plans to implement FV3-based GFS V15 in the
winter of 2019. See the OD briefing here:

In the summer of 2018, during the evaluation phase, two bugs
were identified and addressed:
1. Snow was not adequately melting under warm conditions.
A change to model parameters associated with communicating snow
amounts to the land surface was introduced in July 2018 to
address this.
2. The calculation of the solar zenith angle was incorrect. A
fix was introduced in September 2018.

During the fall of 2018, EMC identified excessively cold
temperature increments in the data assimilation system in polar
regions. This was the result of an incorrect parameter
associated with supersaturation over ice.

As the real-time parallel run and model evaluation by the
community entered the winter of 2018, it became clear the change
made to the snow accounting (Item 1 above) inadvertently caused
excessive accumulating snow in marginally cold environments in
mid-latitude storms, The fix to the solar zenith angle (Item 2
above) inadvertently exacerbated an existing cold bias at lower
levels in the atmosphere. The increased cold bias in the lower
atmosphere compounded the excessive accumulated snow issue noted
above in Item 1.

On February 26, 2019, NWS paused the implementation plans for
GFS V15. See scn19-12 below:

EMC began exploring corrective actions to alleviate the
excessive snow and cold bias that resulted in the following:
1. EMC changed the way snow amounts were calculated and
communicated to the land surface model, basing it on the
fraction of frozen precipitation falling on the ground rather
than basing it on the total precipitation in cold conditions.
2. EMC refined the interaction of radiation with cloud
particles, allowing for each type of hydrometeor (convective
rain, stratiform rain, snow, graupel, and ice) to assume its own
physical characteristics as calculated by the Geophysical Fluid
Dynamics Laboratory (GFDL) microphysics scheme (like particle
radius) and interact accordingly with the radiation scheme.
3. EMC updated the supersaturation parameter over ice in the
data assimilation system.

All three of these modifications were introduced into a new
model configuration with fully cycled data assimilation. This
simulates the full prediction system starting from mid-December
2018; it is now running in real time. In addition, a portion of
the last hurricane season (from August 26, 2018, through October
31, 2018) was also simulated in a fully-cycled data assimilation
configuration with these three modifications.

The results are promising and give NWS confidence to proceed.
The three new modifications are significantly mitigating the
cold bias and excessive snow in GFS V15.1, especially in the
shorter lead times (0-96 hrs), while retaining the benefits of
the new FV3 dynamical core documented in the brief to the NCEP
Director in October 2018. These benefits include:
- (Significantly) Improved 500-hPa anomaly correlation (NH and
- Intense tropical cyclone deepening in GFSv14 not observed in
- GFS V15.1 tropical cyclone track forecasts improved (within 5
- Warm season diurnal cycle of precipitation improved
- Multiple tropical cyclone centers generated by GFS V14 not
seen in GFS V15.1 forecasts or analyses
- General improvement in HWRF runs
- New simulated composite reflectivity output is a nice addition
- Some indication that GFS V15.1 can generate modest surface
cold pools from significant convection
- Improved ozone and water vapor physics and products
- Improved precipitation ETS score (hit/miss/false alarm)

Several individual case studies illustrate the model still
exhibits a cold bias and may produce excessive snow in the
medium range. Nonetheless, the aforementioned significant model
improvements over GFS V14 are compelling and we are exiting the
implementation pause outlined in Service Change Notice (SCN) 19-
12. EMC will continue to explore ways to address these issues.

Additional material relevant to the performance of the new model
configuration is documented here:

The experiment that includes the three modifications and other
results from our recent explorations were incorporated into the
real-time parallel experiment that started on April 19, 2019.
Details on the availability of data from this experiment are
documented here:

For questions regarding products from GFS Version 15.1, please
 Brian Gross, EMC Director


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Joe seems to think there could be some tropical activity coming up.


With cooler air getting into the southeast next week and also across the rest of the south, and the MJO coming into favorable phases, I am concerned we get a development between May 15 and 30 this year.

We shall see.

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