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Synthetic NSSL WRF-ARW Imagery - 10.35 minus 3.9 µm low-level cloud and fog product

Figure 1. Example of a synthetic 10.35 minus 3.9 µm (low cloud/fog product) image from 19 November 2011 at 09 UTC. The image is based on a 9-hour forecast from NSSL's 4-km WRF-ARW.

1) Product Information:

- Who is developing and distributing this product?

This product is a combined effort between the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma, and The Cooperative Institute for Research in the Atmosphere (CIRA) in Fort Collins, Colorado, together with the NOAA/NESDIS RAMM Branch.

- Who is receiving this product, and how?

Daily output from NSSL's 4-km WRF-ARW is provided to CIRA, who then generate synthetic satellite imagery, which is sent to the Storm Prediction Center (SPC) via a McIDAS ADDE server. The output is also converted to AWIPS-compatible NETCDF format and provided to the National Weather Service (NWS) Central Region, where a number of NWS offices are displaying it in real-time via AWIPS.

- What is the product size?

Each image is just under 1 MB, and every day 28 images are provided.

2) Product Description:

- Purpose of this product:

The 10.35 minus 3.9 µm difference product is known as the fog product. The product discriminates low-level clouds from high-level clouds quite well. This product will not discriminate between low-clouds and fog. Insepection of surface observations within regions of low-level clouds are needed for that purpose. The fog product is based on the fact that liquid water clouds have an emissivity at 3.9 µm that is less than that at 10.7 µm, thereby making the fog product show a positive difference (blue in this enhancement). One key difference between this product and the GOES fog product is that the reflected solar radiation is neglected in the synthetic imagery. That is, the synthetic imagery is assuming nighttime is constant. In the GOES fog product, you will notice the brightness temperature difference of low-cloud/fog transition from positive to negative between nighttime and daytime. In the synthetic imagery, the difference will remain positive due to the assumption of zero reflected solar radiation.

- Why is this a GOES-R Proving Ground Product?

The synthetic imagery is a Proving Ground Product because it replicates how actual features will appear in GOES-R ABI bands.

- How is this product created now?

Every day at 00 UTC, NSSL runs their 4-km WRF-ARW. As soon as the 12-hour forecast is completed, several variables are extracted and scp'ed to CIRA. These variables include temperature, water vapor, and other physical and microphysical parameters which are needed for the next step. When all variables have been receieved at CIRA, an observational operator is run to generate the synthetic imagery for 6 GOES-R ABI bands (3.9, 6.95, 7.34, 8.5, 10.35, and 12.0 µm). The simulated imagery is then converted to McIDAS AREA format and made avaiable for the SPC, who then makes the output viewable on their NAWIPS system. It is also converted to netcdf format and made available to the NWS to view in AWIPS. Hourly output between 12-12 UTC is processed daily. The resolution of the output is 4-km to match the input resolution of the cloud model; the real GOES-R ABI bands will have 2-km resolution.

3) Product Examples and Interpretation

The synthetic 10.35 minus 3.9 µm loop is available in real-time by around 14 UTC every day.

4) Advantages and Limitations

Advantages of the synthetic ABI imagery include: 1) Satellite imagery can be viewed before the simulated time actually occurs, so forecasters know what to expect, 2) discrimination between low-level clouds and high-level clouds displayed in a way similar to the current GOES fog product, and 3) forecasters can use this imagery to prepare themselves for what actual GOES-R ABI imagery will look like. The biggest limitation is that the forecast is only as good as the cloud model forecast; if the model does not forecast low-clouds/fog, for example, then the low-clouds/fog will also be absent from the synthetic imagery.

One of the known limitations of this product is the false cloud signature due to surface emissivities at these wavelengths. This problem is most pronounced over the southwest US. See this loop for an example. The animation shows a low-cloud signature for the duration of the loop that does not move in the vicinity of the four corners region, southwest Arizona, northwest Mexico, and slightly west of El Paso, TX. 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. The easiest way to identify a false signature is to look at the loop, and the areas that donít move at all throughout the duration of the loop are likely false emissivity signatures.