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Eric Wendoloski, a NOAA Hollings Scholar from Millersville University in Pennsylvania, completed his research at CIRA. During his nine week visit he performed a study of lightning activity and tropical cyclone formation. His results showed significant differences between lightning strikes around developing and non-developing tropical disturbances. Eric gave a seminar in Silver Spring describing his results, which is a requirement of the Hollings interns. An abstract was also submitted for presentation at the upcoming AMS annual meeting on these results. (J. Dostalek, M. DeMaria)
As part of the CIRA cal/val project, coding is well underway to collect microwave-based satellite retrievals, the associated GFS analyses, and dropsonde profiles to be used in a validation study pertaining to the analysis of tropical cyclones. To be compared are two retrieval schemes, the statistical technique which is currently being used in CIRA’s wind retrieval system, and MIRS NESDIS operational microwave retrieval method. Temperature (and moisture for MIRS) retrievals will be used in CIRA’s wind retrieval system, with the resultant winds being compared to collocated dropsondes. It is expected that the MIRS retrievals will produce more accurate results, but if issues with the MIRS soundings arise, suggestions to the MIRS development team will be made to improve the retrieval system. In addition, the two retrieval schemes will be used as input to programs that estimate maximum potential intensity (MPI) from a theoretical relationship derived by Kerry Emanuel and the vertical velocity profile of an air parcel from an entraining plume model. The code is being written such that it may be used in a real-time as well as in a case study mode. (J. Dostalek)
An experimental hybrid statistical-dynamical wind speed probability algorithm has been running in real-time since Aug 1 2012. In this version of the product, the statistically derived realization tracks are replaced with objectively identified TC tracks from the GFS, ECMWF, CMC, FNMOC, and UKMET global models. The hybrid wind speed probabilities will continue to be displayed in near real-time on the Hurricane Forecast Improvement Project (HFIP) demonstrations page (http://www.hfip.org/data_prob/) for the remainder of 2012. (A. Schumacher, M. DeMaria, K. Musgrave)
A disturbance-following tropical cyclone (TC) genesis index (TCGI) is being developed to provide forecasters with an objective tool for identifying the 0-48hr and 0-120hr probability of TC genesis in the North Atlantic basin. This project is being supported by the Joint Hurricane Testbed (JHT). This new scheme will utilize Dvorak T-number / CI value estimates, environmental and convective parameters currently used in the NESDIS TC Formation Probability (TCFP) product (fixed grid scheme), environmental parameters from SHIPS that are relevant to TC genesis, and total precipitable water (TPW) retrievals from microwave satellites. Recently, work on developing a training dataset for the algorithm has been completed, with a total of 54 potential predictors having been identified. Work continues to develop the disturbance-centric algorithm, with a plan to test the algorithm in real-time starting in June 2013. (A. Schumacher, M. DeMaria)
Initial work is underway in developing a product that incorporates satellite data and model wind information to forecast tropical cyclone recurvature. The satellite data is based on a technique by Dvorak (1995) which identifies the distance between the tropical cyclone center and a curved moisture boundary as seen in the GOES water vapor imagery. An example illustrating this technique is depicted in Figure 1. The contours are the gradient of brightness temperatures within a specified range from the water vapor imagery, while the yellow line illustrates the distance between the gradient associated with the curved moisture boundary and the storm center just before recurvature took place. The model wind information is based on a technique by Hodanish and Gray (1993) which considers the mid- and upper-level zonal winds at a distance and direction relative to the tropical cyclone center. Analysis of the u-component of the wind at mid-levels for Atlantic tropical cyclones has yielded encouraging results for thresholding wind values that relate to probability of recurvature (Fig. 2). (D. Bikos)
Fig. 1: Tropical cyclone Fabian at 17:45 UTC 5 September 2003 just prior to recurvature. The contours are the gradient of a specified range of brightness temperatures from the water vapor imagery, while the yellow line shows the distance between the gradient associated with the curved moisture boundary and the cyclone center.
Fig. 2. 350-500 mb u component of the wind (m s-1) averaged west,northwest, and north octants at 6 and 8 degrees from the tropical cyclone center between -24 and +12 hours from the time of recurvature.
A. Schumacher and M. DeMaria visited the Hurricane Research Division in Miami, FL to collaborate with NOAA scientists J. Dunion and J. Kaplan on a Joint Hurricane Testbed (JHT) project entitled “Development of a Probabilistic Tropical Cyclone Genesis Prediction Scheme.” (A. Schumacher, M. DeMaria)
GOES-14 data in SPC Operations: GOES-14, centered near 105 W in August, resumed collecting data in late summer. It was used primarily to collect 1-minute data over various domains until late September, when it became the operational GOES-East upon the failure of GOES-13. On Thursday 8/16, the domain was centered over Norman, OK, and CIRA worked with the Storm Prediction Center to set up a data feed so the 1-minute data could be displayed in real time in their NAWIPS systems. The image below is a screen capture from the SPC’s NAWIPS system showing a Visible GOES-14 image. CIRA continued to provide the GOES-14 data to the SPC in real time, and it was used regularly by operations. (D. Lindsey)
Figure. Screen capture from the Storm Prediction Center’s NAWIPS system from Thursday, Aug. 16 showing a visible GOES-14 image from 1529 UTC over the 1-minute scan domain.
VIIRS Day-Night Band – Examples are being collected of the new VIIRS Day-Night Band. It allows clouds, city lights, and lightning to be seen, thanks in part to lunar reflection. The example below is from the landfall of Hurricane Isaac. (D. Lindsey)
Figure. A nighttime DNB image of Hurricane Isaac at landfall on 29 August 2012.
High Wind Prediction: In collaboration with Tony Wimmers (CIMSS), a new GIMPAP project is underway in which satellite information will be combined with model forecast fields to predict downslope windstorms at several wind-prone locations in the western U.S. NWS forecasters from Boulder, Salt Lake City, and Las Vegas will also be involved. Forecasters at each office have been contacted about obtaining observed wind data at multiple locations. The first location to be analyzed is Hill Air Force Base, near Salt Lake City, UT. (D. Lindsey, D. Bikos, S. Longmore)
Work continues on a GOES-R Risk Reduction Project whose goal is to improve 1-6 hour forecasts of convective initiation. This is a collaborative effort between CIRA, CIMSS, UAH, NSSL, and CREST. Data collection from the summer of 2012 has ended, and work has begun analyzing this output. The NSSL WRF model output is being used as proxy data, so Convective Initiation events from the model are will be used as the verifying points. (D. Lindsey, L. Grasso)
Work continues on developing simulated satellite imagery products for evaluation as part of the GOES-R Proving Ground. The simulated 10.35-3.9 fog product is currently being evaluated by a number of Central Region offices, in coordination with Chad Gravelle (CIMSS/AWC). Some very useful feedback has been obtained. (D. Lindsey, D. Bikos)
We have been invited to return to the IMET satellite training to present our GOES-R fire work. Unluckily, the workshop was cancelled due to fiscal shortfalls. As a result, we suggested to Dan Borsum, Heath Hockenbery, Larry Vanbussum, and Robyn Heffernan that we would be willing to give an our presentation remotely. They agreed and suggested a presentation length and format. With the help of Dan Bikos, an approximately thirty-minute presentation was recorded and passed on to Dan Borsum and Robyn Heffernan. (L. Grasso, J. Braun, D. Bikos)
A few years ago, I gave a few presentations at the Great Divide Workshop. Due to fiscal shortfalls, the workshop was nearly cancelled this year. Organizers decided to make the workshop virtual by taking advantage of webinar capabilities. I was asked by Dan Borsum and Robyn Heffernan to give a one hour presentation about our AWG synthetic fire imagery project. As a result, I’ll be giving a one hour presentation on 3 October 2012. (L. Grasso, D. Hillger, R. Brummer, R. DeMaria)
We continue our collaboration with Paul van Delst (NCEP/EMC) and recently Brad Ferrier (EMC). Our interaction with Paul focuses on the speed of the CRTM_v2.0.5 on S4 located at SSEC in Madison, WI. Our interaction with Brad focuses on the so-called Ferrier microphysics used in the 4km nested NAM. We will be producing synthetic GOES-13 imagery at 10.7 µm from this model. (L. Grasso, Y-J. Noh, D. Lindsey)
Suomi NPP VIIRS Imagery Blog: The CIRA NPP VIIRS blog continues to be updated with interesting images that highlight the capabilities of VIIRS. Blog posts for this quarter have focused on fire detection, flood detection, the Greenland ice melt event of July 2012 and several new RGB composites, some of which are highlighted in more depth elsewhere in this section. The blog may be found here: http://rammb.cira.colostate.edu/projects/npp/blog/. (C. Seaman)
VIIRS RGB composites for fire detection: A new RGB composite, the “Fire Power RGB”, made from VIIRS M-10 (1.61 µm, blue), M-11 (2.25 µm, green) and M-12 (3.70 µm, red) has been proposed and was presented at the EUMETSAT RGB Workshop in Seeheim, Germany (17-19 September 2012). This product can also be produced from equivalent spectral bands on GOES-R ABI. See the example image below of fires in the Australian Outback. The land surface appears purple, liquid clouds appear blue, ice clouds appear dark green and fires appear white, yellow, orange or red, depending on apparent temperature.
Figure 1: False-color RGB composite of VIIRS channels M-10, M-11 and M-12, taken 04:34 UTC 19 September 2012. Areas of active fires are highlighted.
Another useful RGB composite for fire detection uses M-05 (0.67 µm, blue), M-07 (0.87 µm, green) and M-11 (2.25 µm, red). This composite has the appearance of a “natural color” image, except fires are easier to detect and appear as bright red pixels. See example below. Examples of these RGB composites were presented at the EUMETSAT RGB workshop by R. Brummer, and were well received by the RGB community. More examples are found at the CIRA NPP VIIRS blog: http://rammb.cira.colostate.edu/projects/npp/blog/index.php/uncategorized/the-outback-on-fire/ (C. Seaman, D. Hillger, R. Brummer)
Figure 2: False-color RGB composite of VIIRS channels M-05, M-07 and M-11, taken 04:34 UTC 19 September 2012. Areas of active fires are highlighted.
Using VIIRS for flood detection: The VIIRS band M-06 (0.75 µm) was designed for atmospheric correction. The M-06 detectors saturate at a low radiance, so any reflection of solar radiation off of clouds, aerosols, land or due to sun glint will easily be detected. Sea surface temperature retrievals, for example, are not to be performed for those pixels that are at/near saturation in M-06. As a result, M-06 identifies pixels with surface water and clear skies. This makes identification of large-scale flooding possible, as evidenced by before and after images of flooding caused by Hurricane Isaac.
Figure 1. VIIRS M-06 images of southern Florida before and after the passage of Hurricane Isaac (2012). The Everglades and other areas appear darker after the hurricane due to flooding.
Dry ground, clouds and sun glint appear white, water surfaces appear black. Flooding reduces the M-06 reflectance over land making the surface appear dark.
The “natural color” RGB composite of VIIRS bands I-01 (0.64 µm, blue), I-02 (0.865 µm, green) and I-03 (1.61 µm, red) also detected flooding along the Louisiana Gulf Coast. In the before and after images below, notice the disappearance of the isthmus between Lake Pontchartrain and Lake Maurepas after the passage of Hurricane Isaac. Additional flooding is evident along the Mississippi River delta region, and along the Mississippi coastline.
This and more examples may be found on the CIRA NPP VIIRS blog: http://rammb.cira.colostate.edu/projects/npp/blog/index.php/uncategorized/hurricane-isaac-before-during-and-after/ (C. Seaman)
Figure 2. VIIRS “natural color” RGB composites of the Louisiana Gulf Coast from before and after the passage of Hurricane Isaac (2012). As in M-06, flooded areas appear darker due to low water reflectance in each channel of the composite.
Imagery EDR filled values: There is some difficulty with the display of EDR imagery caused by fill values on the edges of the EDR granule. If these fill values are taken into account, then the granules can be displayed contiguously. This is an issue of which users need to be aware. See the zoomed-in example in the figure below. (D. Hillger, C. Seaman)
Figure 1: Zoomed-in example of an Imagery EDR granule will fill values along the edge between granules and at the edge of scan. (Image courtesy of C. Seaman, CIRA)
Suomi NPP VIIRS Online: Automated processing of VIIRS granules is underway. The attached figure shows the main page for NPP VIIRS imagery. The left side shows the center half of a VIIRS granule, and the right side shows a map of the Earth with the location of that granule. Currently, two VIIRS M bands are being displayed, one visible and one infrared window band. Individual images can be viewed as well as loops of images. A 4 week archive of images is also available, as well as a link to product information on what is shown. NPP VIIRS online can be found at http://rammb.cira.colostate.edu/ramsdis/online/npp_viirs.asp Future additions to the page include image products or RGB image combinations such as true-color imagery. (D. Hillger, D. Watson, K. Micke)
Figure 1: Suomi NPP VIIRS Online page at CIRA/RAMMB.
Comparison of VIIRS with current GOES for Hurricane Isaac: The GOES image is from Imager channel 4 taken at 18:45 UTC on 27 August 2012. The VIIRS image is from channel I-05 taken 18:50 UTC, 27 August 2012. Both are longwave IR window channels, however a lot more structure to Isaac can be seen at 375 m resolution than at 4 km! See also Figure 2, a nighttime DNB image of Hurricane Isaac at time of landfall. (D. Hillger, D. Lindsey, C. Seaman)
Figure 1: Current GOES Imagery vs. VIIRS imagery of Hurricane Isaac on 27 August 2012. (Images courtesy of C. Seaman, CIRA)
Figure 2: A nighttime DNB image of Hurricane Isaac at landfall on 29 August 2012. (Image courtesy of D. Lindsey, NOAA/StAR)
Automated VIIRS imagery processing: Automatic processing of VIIRS imagery by granule is now underway at CIRA. While not every image is captured and displayed, samples of both visible and IR bands are now being displayed on one of the computers dedicated to the VIIRS project. Figure 1 is an example of a visible band M5 (0.672 µm) image off the northern coast of Russia on the Arctic Ocean. Besides clouds, glaciers are seen on an elongated island. Even though (faint) latitude and longitude lines and land/ocean boundaries are provided on the image, a second image (Figure 2) is also provided for each granule, a Mollweide projection of the entire Earth showing where the displayed granule is located. This automated processing allows checking of the quality of the imagery. While only selected VIIRS bands are currently being displayed, additional bands and band combinations will be part of this processing in the future, as well as an online display of these images. Many other imagery examples are found at the NPP VIIRS Imagery blog (http://rammb.cira.colostate.edu/projects/npp/). (D. Hillger)
Figure 1: An example of a Suomi NPP VIIRS visible band M5 (0.672 µm) granule (center portion only) over the northern reaches of Russia. Besides clouds, an island in the Arctic Ocean, mostly covered by glaciers, is also seen. To locate this granule on the Earth see Figure 2.
Figure 2: Mollweide projection of the entire Earth, showing the location of the VIIRS granule shown in Figure 1. Note that the granule is at far northern latitudes and is seen in two parts in this projection.
Automated VIIRS imagery processing (continued): Automatic processing of VIIRS imagery by granule continues at CIRA. While not every image is captured and displayed, samples of both visible and IR bands are now being displayed on one of the computers dedicated to the VIIRS project. This automated processing allows for qualitative checking of the quality of the imagery. While only selected VIIRS bands are currently being downloaded and displayed, additional bands and band combinations will be part of this processing in the future, as well as an online display of these images (coming soon). Figure 1 is an example of a true-color band M5/M4/M3 image over the Strait of Gibraltar. Note the high-resolution details (both spatial and spectral), but with some evidence of detector-to-detector striping. (D. Hillger)
Figure 1: VIIRS true-color image from bands M5/M4/M3 (750 m) on 13 August 2012 at 1312 UTC Strait of Gibraltar
The information below is a new entry in the Suomi NPP VIIRS Imagery Blog. Thanks to C. Seaman, CIRA, who maintains the blog, for this material, which is a current hot topic in scientific circles. Many other imagery examples are found at the NPP VIIRS Imagery blog (http://rammb.cira.colostate.edu/projects/npp/blog/).
You may have heard on the news a story about the rapid ice melt that occurred in Greenland a couple weeks ago. Over a period of four days, the percentage of the surface of Greenland’s ice sheet that showed evidence that the ice was melting went from 40% to 97%. NASA’s Thomas Wagner does a good job explaining it in this interview. You’ll notice in the first link (from the Earth Times) that the rapid melt was first noticed by someone analyzing data from Oceansat-2. The ice melt was detected by its microwave scatterometer and was later confirmed by MODIS. Well, if MODIS can see this ice melt, surely VIIRS can see it, too. Let’s see.
First, let’s look at the false color RGB composite made from channels I-01 (0.64 µm, blue), I-02 (0.865 µm, green) and I-03 (1.61 µm, red). These images are comprised of 5 VIIRS granules stitched together and cropped slightly to get them in under the 15 MB limit for attachments to this blog. You really need to see them zoomed in to full resolution to see the kind of detail that the VIIRS bands provide. This isn’t even the full resolution of the satellite – these two images have been shrunk by a factor of 2 to get in under the file size limit, so it’s actually more like the resolution of the M-bands.
Figure 1 is what VIIRS saw on 8 July 2012, at 14:35 UTC. Figure 2 is what VIIRS saw on 8 July 2012, at 14:35 UTC.
For more information and images for this case, see the Blog link already mentioned. (D. Hillger, C. Seaman)
Figure 1: False color RGB composite of VIIRS channels I-01, I-02 and I-03, taken 14:35 UTC 8 July 2012
Figure 2: False color RGB composite of VIIRS channels I-01, I-02 and I-03, taken 14:42 UTC, 13 July 2012
VIIRS M-band True-Color Imagery after Rayleigh-Correction: Rayleigh-correction code previously used on MODIS and simulated GOES-R ABI has been modified to work for VIIRS reflectances, to create true-color imagery such as the upside-down example over the High Park Fire in northern Colorado in Figure 1. The plan is to work towards implementing this code and producing true-color imagery on the fly, to facilitate finding imagery issues. Algorithms to rotate the image and fill in the bow-tie deletions are also available. The same processing is applicable to VIIRS EDRs, except that by default not all of the M band components for true color are available as EDRs. Image processing was done with McIDAS-X. (D. Hillger)
Figure 1: The center portion of a single VIIRS SDR granule of Rayleigh-corrected true-color imagery created from bands M5/M4/M3 at 750 m resolution. Note the bow-tie deletions at the sides of the granule, and note that the image is upside-down due to the ascending pass over Colorado. This example includes a smoke plume from the early stages of the High Park fire on 10 June 2012.
D. Lindsey provided GOES loops to assist in the assessment of the Long Draw Fire (southeast Oregon) that burned over 582,000 acres. On July 9-10, it made a very impressive eastward run, and the GOES 3.9 µm loop at the link below captured that well. A web page is maintained at RAMMB that includes (among other things) links to several worldwide geostationary satellite floaters for monitoring wildfires. These real-time loops are used by a variety of groups. Webpage with the floater links: http://rammb.cira.colostate.edu/dev/lindsey/loops/ Loop of the Long Draw Fire’s eastward run: http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=dev/lindsey/loops/10jul12_oregon_pyrocb_ch2&image_width=1020&image_height=720 (D. Lindsey)
On Sept. 12, D. Lindsey provided a short remote lecture, via Skype, to an undergraduate seminar class at the Univ. of Georgia called “Observing the Earth from Space.” The class is taught by Dr. Marshall Shepherd, who is the current AMS President Elect. (D. Lindsey)
Training metrics for the quarter:
16 VISIT teletraining sessions have been delivered. There were 25 teletraining signups, 64 students participated.
Registrations: 245
Completions: 173
LMS totals from January 2005 through September 28, 2012:
Registrations: 6054
Completions: 3943
Definitions used in LMS metrics:
Registrations: The number of students who either clicked on the course, or actually took the course, but did not complete the quiz or achieve a passing grade upon taking the quiz. A student may have registered for multiple courses.
Completions: The number of students that achieved a passing grade on a quiz for a course. A student may have completed multiple courses this way.
New training that debuted this quarter:
New training forum:
a) be brief, target length of 30 minutes.
b) demonstrate satellite products that can be applied to operational forecasting.
c) exchange ideas across both operational and academic sides.
d) identify new training topics based on specific participant needs.
e) incorporate seasonal examples that are timely, and use real-time data (where applicable).
As of September 28, 2012, there have been 7 VISIT Satellite Chat sessions for a total of 28 NWS forecast office signups.
Recorded versions of past satellite chat sessions are available here:
http://rammb.cira.colostate.edu/training/visit/satellite_chat/
Ongoing development of new VISIT training sessions:
Research:
Additional Training:
New VISIT employee:
Increase in web-page traffic:
There were around 800 pageviews on these 2 days, which was nearly 30% of all VISIT web-page traffic for August.
Collaboration:
D. Bikos will be collaborating with many different training offices (including COMET) and local, regional and national operational offices of the National Weather Service.
VISIT Meteorological Interpretation Blog – (http://rammb.cira.colostate.edu/training/visit/blog/) – Continue to build and administer the VISIT Blog – a web-log program intended to initiate increased communication between the operational, academic, and training communities. The blog averages about 300 pageviews per month (926 this quarter).
The following table shows a breakdown of the metrics for each VISIT teletraining session valid April 1999 – September 28, 2012. The participant count is collected after each teletraining session, the student is mailed a certificate of completion if they reply to an evaluation email with names. For a complete list and description of each VISIT session see this web-page.
Sessions | Number of offices attending (signups) | Certificates Issued | Participants | |
Total | 1642 | 6774 | 17851 | 23873 |
Enhanced-V | 69 | 211 | 540 | 540 |
Detecting Boundaries | 12 | 62 | 226 | 226 |
Detecting LTO boundaries at night | 17 | 67 | 186 | 186 |
CONUS CG Lightning Activity | 16 | 86 | 285 | 285 |
Using GOES RSO | 26 | 83 | 263 | 263 |
Tropical Satellite Imagery | 8 | 48 | 138 | 138 |
GOES Enhancements in AWIPS | 9 | 47 | 109 | 109 |
Diagnosing Mesoscale Ascent | 21 | 83 | 252 | 252 |
Applying Mesoscale Tools | 5 | 54 | 202 | 202 |
Diagnosing Surface Boundaries | 24 | 106 | 307 | 307 |
QuikSCAT | 11 | 42 | 135 | 161 |
Lake-Effect Snow | 15 | 64 | 210 | 262 |
NDIC | 19 | 40 | 105 | 107 |
Lightning Met 1 | 63 | 331 | 1129 | 1377 |
Precip Type | 5 | 44 | 186 | 195 |
Pattern Recognition to MRF | 10 | 70 | 277 | 277 |
HPC Medium Range Forecasting | 15 | 101 | 335 | 335 |
Ingredients based Approach | 36 | 198 | 626 | 626 |
Model Initializations | 20 | 124 | 440 | 569 |
NWP Top 10 Misconceptions | 27 | 148 | 532 | 681 |
GOES Sounder | 29 | 122 | 262 | 350 |
GOES High Density winds | 21 | 71 | 161 | 161 |
Forecasting MCS’s | 12 | 84 | 232 | 287 |
Mesoanalysis using RSO | 52 | 181 | 565 | 702 |
Near-Storm data in WDM | 14 | 91 | 340 | 379 |
POES | 6 | 27 | 63 | 84 |
Lightning Met 2 | 43 | 261 | 731 | 941 |
Ensemble Prediction Systems | 17 | 93 | 303 | 377 |
Eta12 | 14 | 57 | 194 | 241 |
Tornado Warning Guidance 2002 | 13 | 91 | 355 | 409 |
Fog Detection | 11 | 80 | 264 | 331 |
ACARS | 13 | 73 | 204 | 264 |
Cyclogenesis | 78 | 325 | 1051 | 1243 |
TRAP | 5 | 20 | 66 | 70 |
Subtropical | 2 | 15 | 54 | 65 |
Mesoscale Banding | 8 | 78 | 302 | 356 |
Lake-Effect Snow II | 15 | 52 | 128 | 179 |
TROWAL | 41 | 155 | 370 | 558 |
Hydro-Estimator | 15 | 58 | 171 | 221 |
GOES Fire Detection | 17 | 69 | 205 | 234 |
GOES-12 | 21 | 76 | 248 | 299 |
RSO 3 (Parts 1 AND 2) | 60 | 228 | 310 | 861 |
Water Vapor Imagery | 52 | 219 | 475 | 699 |
Mesoscale Convective Vortices | 47 | 173 | 440 | 581 |
AWIPS Cloud Height / Sounder | 11 | 55 | 128 | 178 |
QuikSCAT winds | 10 | 37 | 107 | 110 |
Convective Downbursts | 65 | 219 | 461 | 768 |
DGEX | 27 | 215 | 562 | 785 |
Severe Parameters | 16 | 136 | 324 | 431 |
Winter Weather (Parts 1 AND 2) | 54 | 261 | 267 | 911 |
Predicting Supercell Motion | 9 | 103 | 197 | 274 |
Monitoring Moisture Return | 14 | 49 | 127 | 190 |
Pulse Thunderstorms | 3 | 48 | 116 | 190 |
GOES 3.9 um Channel | 5 | 17 | 56 | 77 |
Gridded MOS | 18 | 97 | 147 | 335 |
MODIS Products in AWIPS | 40 | 81 | 213 | 240 |
CRAS Forecast Imagery in AWIPS | 25 | 38 | 47 | 103 |
Orographic Effects | 27 | 64 | 123 | 209 |
NAM-WRF | 14 | 52 | 59 | 144 |
Basic Satellite Principles | 26 | 39 | 63 | 97 |
Warm Season Ensembles | 24 | 60 | 87 | 166 |
Potential Vorticity + Water Vapor | 34 | 98 | 191 | 258 |
Cold Season Ensembles | 20 | 64 | 129 | 233 |
GOES Low Cloud Base Product | 14 | 36 | 57 | 109 |
Coastal Effects | 8 | 15 | 46 | 53 |
NHC Hurricane Models | 4 | 18 | 55 | 55 |
Interpreting Satellite Signatures | 24 | 37 | 34 | 107 |
Utility of GOES for Severe Wx | 24 | 50 | 93 | 159 |
NHC Track Models | 6 | 25 | 36 | 86 |
NHC Intensity Models | 6 | 19 | 35 | 75 |
Basic Sat Interp in the Tropics | 6 | 7 | 16 | 18 |
POES and AVHRR in AWIPS | 7 | 12 | 13 | 117 |
UW Convective Initiation Product | 16 | 24 | 42 | 89 |
Water Vapor imagery for severe wx | 8 | 15 | 6 | 60 |
UW Nearcasting product | 9 | 10 | 1 | 26 |
Atmospheric Rivers | 2 | 7 | 26 | 26 |
MIMIC TPW | 3 | 5 | 0 | 14 |
Synthetic Severe | 13 | 14 | 4 | 62 |
OST and Thermal Couplet | 6 | 7 | 5 | 29 |
Synthetic Orographic Cirrus | 1 | 1 | 1 | 1 |
GOES-15 to GOES-West | 3 | 15 | 0 | 54 |
Cloud Top Cooling | 3 | 4 | 0 | 17 |
Synthetic Low Cloud and Fog | 3 | 12 | 0 | 27 |
Meetings and Calls
VISIT/SHyMet had conference calls on July 20, August 22 and September 21.
A member of the VISIT/SHyMet team from CIRA participated in the COMET monthly satellite training calls.
The following 4 courses continue to be administered:
1. SHyMet Severe Thunderstorm Forecasting. Released March 2011. Consists of 7 core courses and 4 optional courses: http://rammb.cira.colostate.edu/training/shymet/severe_topics.asp
Core courses:
Optional courses:
2. Tropical SHyMet. Released August 2010.
Consists of 7 courses: http://rammb.cira.colostate.edu/training/shymet/tropical_intro.asp
3. SHyMet For Forecasters Learning Plan: Released January 2010. It consists of 6 core courses and 3 optional courses.
http://rammb.cira.colostate.edu/training/shymet/forecaster_intro.asp :
This Development Plan includes:
Optional modules
4. SHyMet Intern Learning Plan: Released April 2006
The SHyMet Intern course consists of 9 modules.
(http://rammb.cira.colostate.edu/training/shymet/intern_intro.asp ).
Metrics for the 4 SHyMet courses:
SHyMet Course | Total since debut | Quarter (July-Sept. 28, 2012) | Course Debut | ||
Completions | Registrations | Completions | Registrations | ||
Intern | 148 | 345 | 1 | 6 | April 2006 |
Forecaster | 22 | 54 | 0 | 1 | January 2010 |
Tropical | 6 | 17 | 1 | 0 | August 2010 |
Severe | 11 | 51 | 1 | 5 | March 2011 |
Monthly International Weather Briefings
The WMO Virtual Laboratory Regional Focus Group of the Americas and Caribbean conducted 3 monthly English and Spanish weather briefings (25 July, 15 August, and 19 September 2012) through VISITview using GOES and POES satellite Imagery from CIRA (http://rammb.cira.colostate.edu/training/rmtc/focusgroup.asp ). We used GoToWebinar for voice over the Internet. There were participants from the U.S.: CIRA, the International Desk at NCEP, CSU, NWS Training Division, as well as outside the continental U.S.: Bahamas, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, El Salvador, Guyana, Haiti, Honduras, Mexico, Panamá, Peru, St. Kitts and Nevis, Suriname, Trinidad and Tobago, and Uruguay. The participants include researchers and students as well as forecasters. All sessions were well attended as represented by 10, 9, and 11 countries reaching 40, 52, and 38 participants respectively for July, August, and September. During the August session, a group from the WMO Regional Training Seminar for National Instructors of RA III and RA IV in Peru participated. Mike Davison at NCEP International Desk led the discussions. Typically, the sessions include a look at Water Vapor imagery for a synoptic overview of Central America and the Caribbean as well as for South America. The IR 10.7 um imagery and Visible imagery are used to look more closely at weather features. We look at MJO patterns and the outlook, Total Precipitable Water (TPW) patterns, Sea Surface Temperature (SST) and anomalies. Imagery from a recent weather feature is often highlighted. Participants provided comments and questions related to the local weather in their regions. Recordings of the session can be found here: http://rammb.cira.colostate.edu/training/rmtc/fg_recording.asp
During the last three months, Barbados has also been conducting monthly briefings for the Eastern Caribbean to introduce forecasters in training to the operational forecasters from the region. CIRA has been assisting with the logistics of the sessions and providing imagery through the rammb server listed above.
Other activities included collection and summary of satellite climatology for Costa Rica and Barbados through 2011. The updated composites can be viewed for Costa Rica (1997-2011)(http://rammb.cira.colostate.edu/research/satellite_climatologies/costa_rica/ )
and Barbados (1998-2011) (http://rammb.cira.colostate.edu/research/satellite_climatologies/barbados/ ).
Sharing of Imagery and Products
Imagery for Central and South America and the Caribbean can now be viewed at one location through RAMSDIS Online – look for the 2-week archive feature: (http://rammb.cira.colostate.edu/ramsdis/online/rmtc.asp).
Look for information on our activities on the VLab/ Regional Training Center web page. http://rammb.cira.colostate.edu/training/rmtc/
GEONETCast Americas VLab Training Channel established
CIRA in collaboration with Paul Seymour of NOAA’s Direct Readout Service have initiated and started sending training materials through a GEONETCast Americas channel called “VLab Training”. In August and September, 3 video segments from the Focus group recordings were transmitted through the VLab Training channel. We will continue to do this on a monthly basis and start evaluating what other training can be sent through GEONETCast. (B. Connell, D. Coleman, D. Watson, K. Micke)
TravelerDestinationPurposeFundingDates |
Fryer,K. | Santa Fe, NM | JCSDA Satellite Data Assimilatiion Meeting | Task 1 | July 23-27 |
DeMaria, M. | Washington, DC | GIMPAP and PSDI Annual Reviews | HFIP | August 6-10 |
Musgrave, K. | Boulder, CO | NCAR GSI Tutorial | HFIP | August 21-23 |
Grasso, L. | Norman, OK | SPC, NSSL, CATS Visits | GOESR | September 9-12 |
DeMaria, M. | Miami, FL | NHC, HRD JHT TC Genesis Collaboration | HFIP HJ | September 10-18 |
Schumacher, A. | Miami, FL | NHC, HRD JHT TC Genesis Collaboration | JHT TC Genesis | September 10-14 |
Brummer, R. | Seeheim, Germany | EUMETSAT RGB Workshop | Proving Ground | September 12-20 |
J. Knaff | Monterey, CA | Naval Research Lab Interaction | HFIP | September 17-20 |
To Accepted and Submitted Publications To Awards and Citations To Presentations and Posters
Published:
Azorin-Molina, C., R. Baena-Calatrava, I. Echave-Calvo, B.H. Connell, S.M. Vicente-Serrano, J.I. Lopez-Moreno, 2012: A daytime over land algorithm for computing AVHRR convective cloud climatologies for the Iberian Peninsula and the Balearic Islands. International Journal of Climatology, August, DOI: 10.1002/joc.3572 .
Finch, J., and D. Bikos, 2012: Russian Tornado Outbreak of 9 June 1984. Electronic J. Severe Storms Meteor., 7:4, 1–28.
Sampson, C.R., A.B. Schumacher, J.A. Knaff, M. DeMaria, E.M. Fukada, C.A. Sisko, D.P. Roberts, K.A. Winters, H.M. Wilson, 2012: Objective guidance for use in setting tropical cyclone conditions of readiness. Wea. Forecasting, 27:4, 1052–1060.
Miller, S.D, S. Mills, C. Elvidge, D.T. Lindsey, T. Lee, and J. Hawkins, 2012: Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities, Proceedings of the National Academy of Sciences. http://www.pnas.org/content/early/2012/09/05/1207034109.full.pdf+html?with-ds=yes.
Musgrave, K.D., R.K. Taft, J.L. Vigh, B.D. McNoldy, and W.H. Schubert, 2012: Time evolution of the intensity and size of tropical cyclones. Journal of Advances in Modeling Earth Systems, 4: M08001, doi:10.1029/2011MS000104.
Lin, I-I, G.J. Goni, J.A. Knaff, C. Forbes, M.M. Ali, 2012: Tropical Cyclone Heat Potential for Tropical Cyclone Intensity Forecasting and Its Impact on Storm Surge. Journal of Natural Hazards.
Lindsey D.T, T. Schmit, W. MacKenzie, C. Jewett, M. Gunshor, L.D. Grasso, 2012: 10.35 µm: An atmospheric window with less moisture attenuation. J. Appl. Remote Sens.
Sitkowski, M., J. Kossin, C. Rozoff, and J.A. Knaff, 2012: Hurricane eyewall replacement cycles and the relict inner eyewall circulation. Mon. Wea. Rev.
Schumacher, A.B., M. DeMaria, R. Berg, E. Gibney, R. Knabb, 2013: Recent Advancements in the TC Wind Speed Probability Program. Special Symposium on the Next Level of Predictions in Tropical Meteorology: Techniques, Usage, Support, and Impacts, 6-10 January, Austin, TX.
DeMaria, M., K.D. Musgrave, R. Gall, F. Toepfer, 2013: Statistical Post-Processing Techniques to Improve Hurricane Forecast Improvement Project (HFIP) Model Guidance. Symposium on the Role of Statistical Methods in Weather and Climate Prediction. 6-10 January, Austin, TX.
Hillger, D.W., T. Thomas Kopp, S.D. Miller, D.T. Lindsey, C. Seaman, 2013: Suomi NPP VIIRS Imagery after 1 Year. Symposium on Future Operational Environmental Satellite Systems, 6-10 January, Austin, TX.
Wendoloski, E., M. DeMaria, J.F. Dostalek, 2013: Lightning Observations and Tropical Cyclogenesis. Conference on the Meteorological Applications of Lightning Data, 6-10 January, Austin, TX.
Knaff, J.A., M. DeMaria, S. Longmore, C. Sampson, 2013: Examination of Global Satellite-Based Tropical Cyclone Size Variations. Conference on Applied Climatology, 6-10 January, Austin, TX.
Knaff, J.A., M. DeMaria, S. Longmore, J.F. Dostalek, C. Sampson, J. Hawkins, 2013: Understanding and Diagnosing Tropical Cyclone Structure Variations. Symposium on Future Operational Environmental Satellite Systems, 6-10 January, Austin, TX.
Grasso, L.D., R.L. Brummer, R. DeMaria, D.T. Lindsey, D.W. Hillger, 2013: :Observed and Synthetic Satellite Imagery of Aerosol Influences on Thunderstorm Anvils. Symposium on Aerosol-Cloud-Climate Interactions, 6-10 January, Austin, TX.
Longmore, S., J.A Knaff, M. DeMaria, 2013: A Pseudo Object Oriented netCDF Application Interface Layer to “Simplify” Access to Satellite and Future Atmospheric Datasets. Conference on Environmental Information Processing Technologies, 6-10 January, Austin, TX.
Knaff, J.A., M. DeMaria, C.R. Sampson, J.E. Peak, J. Cummings, W.H. Schubert, 2012: Upper Oceanic Energy Response to Tropical Cyclone Passage. Journal of Climate
Grasso, L.D., D.W. Hillger, M. Sengupta, 2012: Demonstrating the Utility of the GOES-R 2.25 µm band for Fire Retrieval. Geophysical Research Letters.
Grasso L.D, D.W. Hillger, C. Schaaf, Z. Wang, R.L. Brummer, and R. DeMaria, 2012: Use of MODIS 16 Day Albedos in Generating GOES-R Advanced Baseline Imager (ABI) Imagery. J. Appl. Remote Sens.
Quiring, S., A. Schumacher, and S. Guikema (2012): Incorporating Hurricane Forecast Uncertainty into Decision Support Applications, Bull. of the American Meteorological Society.
Van Cleave, D., J.F. Dostalek, and T. Vonder Haar, 2012: The Dynamics and Snowfall Characteristics of Three Types of Extratropical Cyclone Comma Heads Categorized by Infrared Satellite Imagery. Weather and Forecasting.
CO-LABS, the non-profit that informs the public about breakthroughs and impacts from Colorado’s 24 federally funded labs, will honor the team of Mark DeMaria, a NOAA research meteorologist with Colorado State University’s Cooperative Institute for Research in the Atmosphere (CIRA), with the 2012 Governor’s Award for High-Impact Research on Oct. 25. Tteam members are: John Knaff, Andrea Schumacher, Kate Musgrave, Dan Bikos, and Debra Molenar
L.D. Grasso, R.L Brummer, D.T Lindsey, D.W. Hillger, and R. DeMaria, 2012 : GOES-R ABI AS A WARNING AID, SPC/CAPS/NSSL 10-11 September, This one-hour presentation was givn by L. Grasso at the Storm Prediction Center, Norman, OK.
L.D. Grasso, D.W. Hillger, R.L. Brummer, and R. DeMaria, 2012: Synthetic GOES-R Imagery of Canopy Wildfires and Agricultural Burning, SPC/CAPS/NSSL, 10-11 September. This one-hour presentation was given by L. Grasso to the NWC.
The Colorado State University Department of Atmospheric Science is having its 50th anniversary celebration on 13-14 July 2012. The first day’s events include invited speakers/graduates of the Department, as well as a poster session and an evening banquet. For the poster session, a poster showing RAMMB history at CSU was presented, an updated version of a poster first presented at the 7th CoRP Science Symposium held at CSU in 2010. The second day’s events include an Open House at the Atmospheric Science/CIRA campus. (D. Hillger)
Notes:
The manuscript “A daytime over land algorithm for computing AVHRR convective cloud climatologies for the Iberian Peninsula and the Balearic Islands” by Cesar Azorin-Molina, Rafael Baena-Calatrava, Imanol Echave-Calvo, Bernadette Connell, Sergio M. Vicente-Serrano, and Juan I. López-Moreno appeared in the International Journal of Climatology in August 2012. Dr. Azorin-Molina visited CIRA during the summer of 2006 to collaborate with scientists on the use of NOAA-16 and 17 imagery in creating stratified cloud climatologies for regions in Spain. Collaborations have continued since then.
Day-Night Band Paper: A paper entitled “Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities,” by S. Miller, S. Mills, C. Elvidge, D. Lindsey, T. Lee, and J. Hawkins was published in Proceedings of the National Academy of Sciences. The paper can be viewed here: http://www.pnas.org/content/early/2012/09/05/1207034109.full.pdf+html?with-ds=yes . PNAS is a high profile journal, and several articles appeared in the press announcing this publication, including here: http://www.sciencedaily.com/releases/2012/09/120910155613.htm .(S. Miller and D. Lindsey)
Virtual Meeting of the WMO Virtual Laboratory Management Group: CIRA and the NWS Training Division participated in a virtual meeting of the VLMG on 2 July for the Virtual Laboratory for Training and Education in Satellite Meteorology (VLab) (http://vlab.wmo.int). The VLab was established under the WMO Coordination Group for Meteorological Satellites (CGMS) to promote effective use of satellite meteorology throughout the WMO member countries. The VLab consists of members from major satellite operators across the globe collaborating with WMO centres of excellence. The topics of the meeting included the Caribbean Aviation Week during the first week of May, updates to the document for user readiness for new generation satellites and using a maturity model to assess progress in meeting training goals. Preparations for the VLMG meeting in October in Brazil were also discussed. (B. Connell)
Three new potential collaborations were identified during my trip to Norman. One is with Youngsun Jung of CAPS. She is working on data assimilation of satellite imagery. I asked if she would be willing to visit CIRA to meet Milija Zupanski. A second potential collaboration is with Yang Hong, adjunct professor at the school of meteorology. We discussed the idea of moving a sub-pixel fire beneath a point spread function to demonstrate the brightness temperature dependency on the location of the fire. In addition, he included the idea of using a fire model that explicitly simulates a fire front that moves through a numerical domain. Output from this model can also be used to move around beneath a point spread function. Results would help understand how brightness temperatures depend on the location of a fire. Lastly, Steve Koch has a group at NSSL that is working on diagnosing hydrometeor characterizations along a radar beam. In particular, he is receptive to the idea of exploring how satellite data may be used in this project. (L. Grasso)
Bob Rabin (National Severe Storms Lab) visited CIRA on Tuesday July 3, and on September 7 and 10. He is collaborating with D. Lindsey and L. Grasso on several GOES-R Risk Reduction projects. (D. Lindsey)
M. DeMaria and K. Musgrave provided interviews to Ty Brennan of CBS 4 Denver, which aired on the 6pm news on August 29th and can be viewed at http://denver.cbslocal.com/2012/08/29/csu-hurricane-researchers-play-important-role-during-big-storms/. M. DeMaria also provided an interview to ABC 7 Denver, which aired on the 5pm news on August 29th. These interviews discussed current efforts of CIRA in tropical cyclone research and forecasting, as well as the impacts of Hurricane Isaac. (M. DeMaria, K. Musgrave)
M. DeMaria gave an interview with Discovery News on what limits hurricane maximum winds and if there will ever be a need for a category 6 hurricane on the Saffir-Simpson wind scale (probably not). The story is available from http://news.discovery.com/earth/is-a-category-6-possible-120828.html. (M. DeMaria)
M. DeMaria provided a phone interview to Jack Williams, a freelance writer for the Washington Post, on new capabilities of GOES for tropical cyclones. Mr. Williams may use a recent publication on tropical cyclone lightning in a book he is preparing for the AMS. M. DeMaria also gave a phone interview to Steve Clark from Spaceflightnow.com on a story he is working on regarding how satellite remote sensing capabilities have improved since Hurricane Andrew in 1992. (M. DeMaria)
J. Knaff was interviewed by T. Lewis of Wired Magazine on the topic of why tropical cyclones look similar in satellite imagery. (J. Knaff)
M. DeMaria held annual review meetings with all RAMMB Staff. (M. DeMaria)
The five RAMMB employees viewed “Through a Dog’s Eyes,” a program featuring service dogs and how they help people with various disabilities, and “Sitting Bull, Chief of the Lakota Nation,” a documentary on the great Sioux Chief. These movies fulfill the yearly EEO and Diversity requirements. (M. DeMaria, J. Knaff, D. Hillger, D. Molenar, and D. Lindsey)
M. DeMaria attended the CIRA Fellows meeting on Friday, July 20th, 2012. An overview of CIRA activities was provided, including the NESDIS and OAR projects. Training and outreach activities were also described. About 15 CIRA Fellows attended the meeting and each was asked to provide feedback to CIRA on the presentations. My feedback suggested ways that NESDIS/STAR might increase support for graduate student research through collaborative grants, for CIRA to start thinking about methods for obtaining real time GOES-R data and maintain its AWIPS capabilities to stay relevant in the satellite Proving Ground, and endorsed the idea proposed by CIRA to coordinate training on wildfire detection and response to federal and state agencies, based on recent experience in the Colorado High Park fire. (M. DeMaria)