{"id":674,"date":"2013-04-03T14:32:13","date_gmt":"2013-04-03T21:32:13","guid":{"rendered":"http:\/\/rammb.cira.colostate.edu\/training\/visit\/blog\/?p=674"},"modified":"2026-03-06T09:06:29","modified_gmt":"2026-03-06T16:06:29","slug":"synthetic-imagery-comparison-from-2-different-models","status":"publish","type":"post","link":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/2013\/04\/03\/synthetic-imagery-comparison-from-2-different-models\/","title":{"rendered":"Synthetic imagery comparison from 2 different models"},"content":{"rendered":"\n<p>This blog entry will make a comparison between synthetic imagery generated from 2 different models, the NSSL WRF-ARW and the NAM-Nest, both with a horizontal grid spacing of 4 km.&nbsp; After comparing the synthetic imagery between the 2 models, we will compare them to the observed GOES imagery.<\/p>\n\n\n\n<p>The major differences between the 2 models when considering synthetic imagery interpretation can be summarized with an example of an extra-tropical cyclone on 23 March 2013<\/p>\n\n\n\n<p>The first thing to keep in mind is that since these are 2 different models, the forecasts will not be identical, the images in the example above are an 18 hour forecast.&nbsp; For the synthetic imagery from the NSSL WRF-ARW model, the bands being simulated are those that will be available on GOES-R, whereas the synthetic imagery from the NAM-Nest are the bands on the current GOES operational satellites.&nbsp; For the water vapor imagery, you can see that there is a substantial difference in the wavelength of the band being simulated (6.95 vs 6.5 microns).&nbsp; 6.95 microns has a weighting function that peaks lower in the atmosphere than 6.5 microns, this means the brightness temperatures will be warmer at 6.95 microns than at 6.5 microns.&nbsp; For most operational applications, (i.e., identifying troughs\/ridges, shortwaves, jet streaks etc.) this warm bias has no impact on interpretation of the signature of interest for comparison between model forecast and GOES imagery.&nbsp; For the IR imagery, the difference is much less (10.35 microns for the WRF-ARW and 10.7 microns for the NAM-Nest), therefore the warm brightness temperature bias will not be present in the IR imagery.&nbsp; The other important contribution to the difference in the appearance of clouds between the 2 models is the microphysics package being used.&nbsp; They are different, which means the appearance of the clouds can be different due to this factor.<\/p>\n\n\n\n<p>Consider the synthetic water vapor imagery from the 2 models (left is WRF-ARW, right is NAM-Nest) for a day with convection across the Plains, both initialized at 0000 UTC 29 March 2013:<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_syn_wv_comp&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_syn_wv_comp&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>Concentrate on synoptic \/ mesoscale features of interest rather than the difference in brightness temperature that is primarily due to the difference in the wavelengths of the bands being simulated.&nbsp;&nbsp; Can you see any shortwaves that appear to play a role in convective initiation?&nbsp; Are the shortwaves easier to identify in one model vs another?&nbsp; There is a difference in the appearance of the afternoon thunderstorms forecast to develop in the Plains which we will discuss in more detail when analyzing the synthetic IR imagery.<\/p>\n\n\n\n<p>Next, let&#8217;s compare the synthetic water vapor imagery from the NSSL WRF-ARW (left) with the GOES imagery (right, at the corresponding times, hourly):<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_wrf_goes_wv&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_wrf_goes_wv&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>Compare any shortwaves \/ jet streaks between the model forecast and GOES imagery.&nbsp; Note the discrepancies between the way the imagery appears from GOES versus that from the model.&nbsp; Finally, evaluate how the model did in terms of forecast location \/ timing of these features.<\/p>\n\n\n\n<p>Next, let&#8217;s compare the synthetic water vapor imagery from the NAM-Nest (left) with the GOES imagery (right, at the corresponding times, hourly):<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_nam_goes_wv&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_nam_goes_wv&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>Compare any shortwaves \/ jet streaks between the model forecast and GOES  imagery.&nbsp; Note the discrepancies between the way the imagery appears  from GOES versus that from the model.&nbsp; Finally, evaluate how the model  did in terms of forecast location \/ timing of these features.<\/p>\n\n\n\n<p>Now let&#8217;s consider the IR imagery, as before we will compare the appearance of the synthetic IR imagery between the WRF-ARW (left) and NAM-Nest (right) first:<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_syn_ir_comp&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_syn_ir_comp&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>Compare the difference in the appearance of forecast thunderstorms between the 2 models.&nbsp; Which of the models has smaller anvil cirrus?&nbsp; Compare the appearance of &#8220;non-convective&#8221; clouds (clouds that aren&#8217;t associated with thunderstorms).<\/p>\n\n\n\n<p>Now compare the GOES imagery (right) with the synthetic IR imagery from the NSSL WRF-ARW (left):<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_wrf_goes_ir&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_wrf_goes_ir&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>and the synthetic IR imagery from the NAM-Nest (left):<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_nam_goes_ir&amp;image_width=1020&amp;image_height=900\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/templates\/loop_directory.asp?data_folder=training\/visit\/loops\/29mar13_nam_goes_ir&amp;image_width=1020&amp;image_height=900<\/a><\/p>\n\n\n\n<p>For this case, which of the models represented the anvil cirrus more accurately?&nbsp; Which of the models did a better job with the timing \/ location of afternoon thunderstorms?<\/p>\n\n\n\n<p>For reference, here are the SPC storm reports for that day:<\/p>\n\n\n\n<p><a href=\"http:\/\/www.spc.noaa.gov\/climo\/reports\/130329_rpts.html\" target=\"_blank\" rel=\"noopener\">http:\/\/www.spc.noaa.gov\/climo\/reports\/130329_rpts.html<\/a><\/p>\n\n\n\n<p>Synthetic IR imagery can be quite useful in forecasting where clouds may inhibit daytime heating and thus surface temperature.&nbsp; Which of the models appeared to do a better job with the cloud cover forecast on this day?&nbsp; How early (in the loop) did you have more confidence in one model versus the other when comparing the synthetic imagery with the GOES imagery?<\/p>\n\n\n\n<p>Real-time imagery synthetic imagery from both models can be found here:<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/ramsdis\/online\/goes-r_proving_ground.asp#Synthetic_GOES-R_Imagery_from_Real-Time_NSSL_4_km_WRF-ARW\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/ramsdis\/online\/goes-r_proving_ground.asp#Synthetic_GOES-R_Imagery_from_Real-Time_NSSL_4_km_WRF-ARW<\/a><\/p>\n\n\n\n<p>Training can be found here:<\/p>\n\n\n\n<p><a href=\"http:\/\/rammb.cira.colostate.edu\/training\/visit\/training_sessions\/\" target=\"_blank\" rel=\"noopener\">http:\/\/rammb.cira.colostate.edu\/training\/visit\/training_sessions\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This blog entry will make a comparison between synthetic imagery generated from 2 different models, the NSSL WRF-ARW and the NAM-Nest, both with a horizontal grid spacing of 4 km.&nbsp; After comparing the synthetic imagery between the 2 models, we will compare them to the observed GOES imagery. The major differences between the 2 models <a href=\"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/2013\/04\/03\/synthetic-imagery-comparison-from-2-different-models\/\" class=\"more-link\">Continue Reading<\/a><\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[47,48,15,28,29],"tags":[],"class_list":["post-674","post","type-post","status-publish","format-standard","hentry","category-geostationary-satellite-discussion","category-goes-r","category-goes-r-proving-ground","category-satellites","category-severe-weather"],"_links":{"self":[{"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/posts\/674","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/comments?post=674"}],"version-history":[{"count":1,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/posts\/674\/revisions"}],"predecessor-version":[{"id":4710,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/posts\/674\/revisions\/4710"}],"wp:attachment":[{"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/media?parent=674"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/categories?post=674"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rammb2.cira.colostate.edu\/visit-blog\/wp-json\/wp\/v2\/tags?post=674"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}