RAMMB: GOES-R Proving Ground Blog

As part of NOAA’s Hazardous Weather Testbed Spring Experiment at the Storm Prediction Center, CIRA is delivering 3 synthetic imagery products to be evaluated in the Experimental Warning Portion of the experiment in their AWIPS-II system: 6.95 micrometers, 10.35 micrometers, and the 10.35 – 12.3 micrometer difference product.  Chris Siewert is hosting a separate blog and regularly adding posts with details on how the products are being evaluated.  Those entries can be found here: http://goesrhwt.blogspot.com/search/label/Simulated%20Satellite%20Imagery

This example from the Boulder WFO shows the use of synthetic IR imagery generated from the 4-km horizontal grid resolution NSSL WRF model for predicting an area of fog and low clouds near the Denver International Airport (DIA) on the morning of 8 November 2011.  The WRF model is run daily at 0000 UTC, and the ultimate purpose of the synthetic imagery is to use it to replicate realistic-looking imagery that represents some of the new GOES-R channels.  Building forecaster confidence in using this new type of output from a numerical model as well as the ability of the model post-processing to generate realistic-looking satellite imagery is an important step towards ultimately using synthetic imagery to test GOES-R products.

In this case the synthetic IR imagery replicates the 10.35 micron channel, the current GOES IR channel available on AWIPS.  Boulder WFO forecaster Scott Entrekin, the local Aviation Focal Point, saved this example.  He noticed that the synthetic IR imagery predicted an area of low clouds that threatened DIA for the hours near sunrise into the morning.  DIA of course is an important Terminal Aviation Forecast (TAF) site, and this type of output is potentially useful for helping with such forecasts.

Figure 1a.  Synthetic IR image over eastern Colorado (the Boulder WFO forecast area is within the area covered by this image) valid at 1400 UTC.  The rectangle encloses some of the low cloud area and is included for reference to Figure 1b, which is at a different scale.  Aviation observations are shown from the METAR sites (key: cloud fraction shown next to ceiling height (AGL, in hundreds of feet), weather on the right side, and visibility (in miles) the bottom number), and the arrow points to DIA.

Figure 1b.  Actual visible image for 1415 UTC with aviation observations.  The rectangle shown covers approximately the same area as in Fig. 1a.  Scott noted how the low clouds seen in the visible imagery compare favorably to the low clouds indicated in the synthetic imagery shown in Figure 1a.  At 1400 UTC DIA was near the western edge of the area of low clouds and fog, and reported a 4 mile visibility in light fog, with scattered clouds at 3700 and 12000 feet.

Figure 2a.  Synthetic IR image as in Figure 1a but for 1500 UTC.

Figure 2b.  Visible image for 1500 UTC with aviation observations.  As in the comparison at 1400 UTC, the low cloud area depicted in the synthetic imagery compares favorably to low cloud and fog area seen in the visible imagery, although certainly not a perfect forecast.  Conditions at DIA had deteriorated by 1500 UTC, with 2 mile visibility in fog, scattered clouds at 300 feet, and broken clouds at 3500 feet.

This blog entry will look at an example of the synthetic fog product (from the 4-km NSSL WRF-ARW model) for an event that took place during the overnight hours of November 19 to 20, 2011.

Here is the synthetic fog product during the overnight hours:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/19nov11_syn_fog

There is southerly flow advecting moisture from the Gulf of Mexico northward.  The increasing moisture, in combination with nighttime cooling leads to the development of a large area of stratus clouds across the Plains from Texas to Nebraska and eastward across the southeast states.  This enhancement will depict regions of low-level clouds in the blue colors.  Note that the imagery from 0000-08000 UTC is based on the 0000 UTC November 18 model run, and the imagery between 0900-1200 UTC is based on the 0000 UTC November 19 model run.  There is a discontinuity between 0800 and 0900 UTC for this reason, but the trend in the low-level clouds as discussed earlier is still valid.

Let’s assess how well the model forecast was.  We’ll look at the GOES Low Cloud / Fog product (also known as the shortwave albedo product):

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/19nov11_sw_albedo

In this color table, low-level clouds / fog are depicted by the lighter / white colors.  High-level clouds are darker / black and color enhanced above a temperature threshold.  The model did a pretty good job with the development of low-level stratus across the Plains and into the southeast.  Fog can be assessed by looking at surface observations (not shown).

The key to remember here is that this product aids in visualization.  Model fields of relative humidity could have yielded the same conclusions, however by looking at a forecast model field of something you’re already familiar with for diagnosing stratus / fog (i.e., the GOES fog product), it offers a different perspective on assessing the possibility of low-level stratus / fog during the forecast period of interest.

Upon inspection of the synthetic infrared (10.35 micron) imagery from the NSSL WRF-ARW model:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/13oct11_syn_ir

your attention may be drawn to the region of southwest Colorado since we see a region of cold brightness temperatures  that does not move and persists for the duration of the loop (1600-0000 UTC).  Could these be low clouds / fog? Let’s look at the GOES visible imagery for 1630 UTC:

Skies are clear across southwest Colorado, so we are not looking at low clouds / fog.  However, note that there is snow cover over the mountains.

What we’re looking at in the synthetic imagery is a representation of  snow cover.  The snow cover data that goes into the NSSL WRF-ARW model is relatively coarse, therefore the cold ground signature is spread out over relatively large areas when there is snow cover in the model.  This signature shows up quite easily early in the cold season with the large temperature difference between snow cover and no snow cover, and will increase in coverage moving into winter as snowfall coverage increases.

Let’s analyze the following loop of the synthetic fog product, generated from the 4-km NSSL WRF-ARW model:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/10oct11_syn_fog/

In this color table, grey into light blue represents increasing confidence in liquid water clouds.  Our example from the 0000 UTC 10 October 2011 NSSL WRF-ARW model run shows a large area of liquid water clouds (most likely stratus) across Texas extending northward through the central US.  The darker shades of grey and black correspond to ice clouds (most likely cirrus) forecast by the model.

The region of blue in Arizona and Utah extending southward into northwest Mexico that does not move catches your attention.  A quick look at the visible satellite imagery:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/10oct11_goes_vis

shows that the region is mostly cloud free.  However, the lighter shade of grey extending northwest to southeast through the four corners of AZ/CO/UT/NM corresponds to the blue in the synthetic fog product; this false cloud signature is a consequence of surface emissivities at the two channels.  This is not a model error, rather, an observed feature in GOES-11.  Similarly, the other blue region in the northeast quadrant of AZ and southwest AZ into northwest Mexico are also consequences of the surface emissivity.

The easiest way to identify a false signature is to look at the loop, and the areas that don’t move at all throughout the duration of the loop are likely false emissivity signatures.

Synthetic satellite imagery can be useful in forecasting temperature.  This example from September 20-21, 2011 demonstrates the utility of synthetic imagery from the 4-km NSSL WRF-ARW model in forecasting the overnight low temperature.

Focusing on southeast Wyoming, examine the synthetic infrared imagery from late afternoon (2000 UTC) through the late night hours (0800 UTC):

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/20sept11_syn&image_width=800&image_height=600

Early in the loop, there is afternoon convective clouds in southeast Wyoming, which diminishes by 0300 UTC.  However, notice the region of clouds (indicated by the colder brightness temperatures) developing across southeast Wyoming in the 0300-0800 UTC time range.  If the forecast is correct, the cloud cover would keep temperatures from cooling down as quickly.

Now let’s analyze what actually happened by looking at the GOES IR imagery:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/20sept11_goes&image_width=800&image_height=600

Note the clouds developing into southeast Wyoming in the 0500-0745 UTC time range, similar to what was forecast by the WRF-ARW model.  This caused locations under the cloud cover to not cool off as quickly, for example, look at the temperature trace (red line) for Cheyenne, WY:

Temperatures at Cheyenne cooled off gradually to about 1000 UTC, then the cloud cover dissipated allowing temperatures to cool more rapidly to an overnight low of 36 F.

Similarly, at locations further east in the southern Nebraska panhandle, cloud cover kept Kimball, NE from cooling off too rapidly for an overnight low of  42:

And an overnight low of 40 at Sidney, NE:

Meanwhile, at Douglas (about 150 miles north of Cheyenne) in east central Wyoming:

Temperatures cooled off more rapidly as skies remained clear, and the overnight low was 25 F.

Real-time synthetic imagery from the 4-km NSSL WRF-ARW model may be viewed here:

http://rammb.cira.colostate.edu/ramsdis/online/goes-r_proving_ground.asp#Synthetic_GOES-R_Imagery_from_Real-Time_NSSL_4_km_WRF-ARW

Contributor:  Becca Mazur, NWS forecast office, Cheyenne, WY