{"id":32,"date":"2011-02-09T23:38:52","date_gmt":"2011-02-09T23:38:52","guid":{"rendered":"http:\/\/rammb.cira.colostate.edu\/research\/goes-r\/proving_ground\/blog\/?p=32"},"modified":"2026-03-06T09:05:41","modified_gmt":"2026-03-06T16:05:41","slug":"synthetic-imagery-for-severe-thunderstorm-forecasting","status":"publish","type":"post","link":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/2011\/02\/09\/synthetic-imagery-for-severe-thunderstorm-forecasting\/","title":{"rendered":"Synthetic Imagery for Severe Thunderstorm Forecasting"},"content":{"rendered":"

For this blog entry, we\u2019ll consider applications of the NSSL 4-km WRF-ARW model synthetic imagery towards a severe weather event that occurred on June 22, 2010.\u00a0 The synthetic imagery is one of the GOES-R proving ground real-time products<\/a>. \u00a0 Synthetic imagery is model output that is displayed as though it is satellite imagery.\u00a0 Analyzing synthetic imagery has an advantage over model output fields in that the feature of interest appears similar to the way it would appear in satellite imagery.\u00a0\u00a0 The primary motivation for looking at synthetic imagery is that you can see many processes in an integrated way compared with looking at numerous model fields and integrating them mentally.<\/p>\n

Figure 1<\/a> shows the WRF-ARW synthetic imagery for the 6.95 um (water vapor) band.\u00a0 The forecast times are indicated at the bottom middle portion of the image, they are from 1200 UTC to 0300 UTC so we are looking at the 12 to 27 hour forecast from the 0000 June 22, 2010 model run.\u00a0 The model shows an upper-level low over Montana and Wyoming moving eastward.\u00a0 South of this feature, we can see a region of relatively fast moving warmer brightness temperatures (the red colors moving from Arizona and Utah towards Colorado).\u00a0 This appears to be associated with an upper-level jet streak.\u00a0 Another example of a region of warmer brightness temperatures would be across Michigan moving towards Ohio, Pennsylvania and New York.\u00a0 With both features in the east and the west, there appears to be convection developing during the late afternoon hours.\u00a0 Remember, we\u2019re looking at mid to upper level features in the water vapor imagery.\u00a0 The main role of the synthetic water vapor imagery is identifying shortwaves and jet streaks that may play a role in the initiation, maintenance and intensity of convection.\u00a0 It\u2019s important to understand what you\u2019re looking at in the water vapor imagery when you see a region of warmer brightness temperatures, we\u2019ll discuss this more in future blog entries and in VISIT training sessions that address this topic.\u00a0 Next, let\u2019s look at lower levels, so we turn to the synthetic IR imagery.<\/p>\n

Figure 2<\/a> shows the WRF-ARW synthetic imagery for the 10.35 um IR band.\u00a0 We\u2019re looking at the same time period as the water vapor loop we just looked at.\u00a0 The advantage to this channel is that low-level features will show up.\u00a0 This is useful when analyzing cloud cover, to see if clouds will dissipate and allow for sufficient insolation to warm up the surface.\u00a0 At 1400 UTC we can see low-level clouds showing up as the colder brightness temperatures across western Nebraska and northeast Colorado, these are forecast to dissipate by afternoon hours, however note the higher level clouds forecast across eastern Colorado.\u00a0 A morning MCS exists across eastern Nebraska moving eastward towards Iowa.\u00a0\u00a0 We see the early afternoon convection just ahead of the upper low in Wyoming and Montana by 2000 UTC, while isolated storms develop in eastern Colorado and the Nebraska panhandle shortly thereafter, in the region of strong southwest flow aloft.\u00a0 Additional convection develops further south in Texas later.\u00a0 Upscale growth occurs during the late afternoon and evening hours, particularly over Nebraska where there is stronger flow aloft then further south in Texas.\u00a0 It appears to be an MCS over Nebraska by 0300 UTC.\u00a0 The best use of the synthetic imagery is to look at the forecast in the morning hours, follow the trends in GOES and other observational data during the day to gauge how much confidence you should have in the model forecast.<\/p>\n

Figure 3<\/a> shows the GOES 10.7 um IR band over the same time period as the forecast imagery we just looked at.\u00a0 Notice the low-level clouds in western Nebraska and northeast Colorado dissipated, as was forecast.\u00a0 The high level clouds in Colorado were well forecast, and looked to be covering a greater area than forecast.\u00a0 The early thunderstorm activity in Wyoming near the upper low is forecast well.\u00a0 Notice the later storms in western Nebraska and Kansas, they have much large anvil cirrus canopies than forecast by the synthetic imagery, this is a known bias in the model so that storms in the model will typically appear smaller than observed in GOES.\u00a0 Upscale growth into an MCS late in the loop in Nebraska seems to be handled well also, and keep in mind that the anvil cirrus canopy will always appear larger in GOES than in the synthetic imagery.<\/p>\n

Figure 4<\/a> shows the GOES 6.5 um water vapor imagery over the same time period.\u00a0 The brightness temperatures will generally appear warmer in the synthetic imagery compared to GOES imagery.\u00a0 The main role of the synthetic water vapor imagery is identifying shortwaves and jet streaks that may play a role in the initiation, maintenance and intensity of convection.\u00a0 Keep this in mind as you examine the synthetic water vapor imagery, then look at GOES visible imagery and surface observations to see where the key low-level convergence boundaries exist.<\/p>\n

The synthetic imagery has exciting potential as an additional tool in forecasting severe thunderstorms, just keep in mind we are looking at model output with its familiar limitations.<\/p>\n

For more information on severe weather applications of the synthetic imagery from the NSSL 4-km WRF-ARW model, you may take to this VISIT training session:<\/p>\n

http:\/\/rammb.cira.colostate.edu\/training\/visit\/training_sessions\/synthetic_imagery_in_forecasting_severe_weather\/ <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

For this blog entry, we\u2019ll consider applications of the NSSL 4-km WRF-ARW model synthetic imagery towards a severe weather event that occurred on June 22, 2010.\u00a0 The synthetic imagery is one of the GOES-R proving ground real-time products. \u00a0 Synthetic imagery is model output that is displayed as though it is satellite imagery.\u00a0 Analyzing synthetic […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-32","post","type-post","status-publish","format-standard","hentry","category-synthetic-nssl-wrf-arw-imagery"],"_links":{"self":[{"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/posts\/32","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/comments?post=32"}],"version-history":[{"count":6,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/posts\/32\/revisions"}],"predecessor-version":[{"id":1121,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/posts\/32\/revisions\/1121"}],"wp:attachment":[{"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/media?parent=32"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/categories?post=32"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/proving-ground-blog\/wp-json\/wp\/v2\/tags?post=32"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}