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A large set of matchups of MIRS AMSU temperature and moisture retrievals and ground truth soundings from the NOAA Gulfstream Jet were obtained from T. Reale of NESDIS for Hurricane Irene of 2011. There were about 150 matching soundings over a 5 day period as the storm approached the U.S. east coast. These soundings were 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. Preliminary results for the Irene environment show that MIRS soundings provide reasonable estimates of the MPI, but temperature and moisture biases in the low levels introduce fairly large errors in the vertical velocity estimates. The figure below shows that the temperature biases in the MIRS retrievals are the primary source of the vertical velocity errors. This work is part of the CIRA cal/val project and was presented at the 2012 Annual Meeting of the AMS. The results will be provided to the MIRS development team as guidance for possible future improvements of the MIRS retrievals in the tropics and subtropics. (J. Dostalek)
The average vertical velocity of an air parcel from an entraining plume model calculated using soundings in the environment of Hurricane Irene. The black line uses input from the NOAA Gulfstream Jet and is considered ground truth. The Cyan line uses input from the AMSU MIRS retrievals, and underestimates the vertical velocity in the low to mid-levels. The green and red lines show the results for the case where the moisture and temperature biases from the MIRS soundings were corrected, respectively. The largest source of error is from the temperature biases.
For years, RAMMB has produced polar plots of tropical cyclones from infrared imagery in the standard geostationary projection. Polar plots are a convenient way to analyze a tropical cyclone, as its shape lends itself to radius-azimuth projection. Programming is underway to apply this procedure to the total precipitable water (TPW) field of tropical cyclones. In this case, the TPW data comes from consecutive passes of polar-orbiting satellites combined into a single, global image. (J. Dostalek)
The effect of large-scale vertical motion on tropical cyclogenesis in the Atlantic is being investigated using an omega equation valid for the whole sphere. Work on this project continued this quarter by continuing the investigation of the differences in omega between disturbances which developed into tropical cyclones and those which dissipated. Because disturbances tend to develop differently depending on the location in the Atlantic, three different subbasins are being considered: the tropical Atlantic, the subtropical Atlantic, and the Gulf of Mexico. (J. Dostalek)
An analysis system that makes use of aircraft reconnaissance data (flight-level and SFMR surface winds) and the multi-platform tropical cyclone surface wind analysis (MTCSWA) beyond 150 km was developed for a new JHT project. This MTCSWA+Aircraft data combination allows for an analysis that extends beyond the radius of typical aircraft reconnaissance (about 180 km). Results were presented and well received at the 66th IHC. The figure below show results from the analysis for Hurricane Irene on 24 August 12 UTC (left) and the aircraft data used to derive the analysis (right). (J. Knaff)
Caption: Tropical cyclone surface wind analysis based upon 6-hour composites of aircraft reconnaissance data combined with the MTCSWA product beyond 150 km is shown on the right. Surface wind streamlines are shown with flight-level wind vectors (left) that serve as input for this product. The product will be evaluated in real-time this summer.
A manuscript entitled “objective guidance for use in setting tropical cyclone conditions of readiness” by C. Sampson (NRLMRY), A. Schumacher, J. Knaff, M. DeMaria, E. Fukada (JTWC), C. Sisko (NHC), D. Roberts (NHC), K. Winters (Patrick, AFB), and H. Wilson (Fleet Weather Center, Norfolk) was submitted to Weather and Forecasting. The paper describes a method to objective determine tropical cyclone conditions of readiness (DoD’s equivalent of Hurricane/Tropical Storm Watches/Warnings, as described below) using Monte Carlo based tropical cyclone wind probabilities. Such information will aid DoD facilities in their preparation for tropical cyclone passage in the Atlantic, and Pacific areas of operation. Additional work this quarter has concentrated on the wording of automatically generated text messages that will be part of the NHC and JTWC Monte Carlo wind Probability Text Products. (J. Knaff)
Table: Tropical cyclone conditions of readiness (TC-COR) explanation.
| TC-COR | Definition | Preparedness Examples |
| IV | 50-kt sustained winds possible within 72 hours | Obtain flashlight with extra batteries, snacks, first aid supplies, bottled water |
| III | 50-kt sustained winds possible within 48 hours | Clean up around house, pick up loose items |
| II | 50-kt sustained winds anticipated within 24 hours | Secure outdoor property including picnic table, barbeque grill |
| I | 50-kt sustained winds anticipated within 12 hours | Schools close, fill available containers with water |
| I-CAUTION | 34-49 kt occurring and are expected to reach 50 kt within 12 h | All outdoor activities except in support of urgent military missions discontinued |
| I-EMERGENCY | 50-kt sustained winds occurring | All outside activity prohibited |
| I-RECOVERY | 50-kt sustained winds no longer occurring | No outdoor activity authorized except by pre-designated emergency crews |
| STORM WATCH | Still a possibility of danger | Normal activity resumes 2 h after declaration. |
| ALL CLEAR | Local recovery operations complete | Be alert to possible damage and hazardous conditions on roads, etc. |
Upper ocean’s response to TC passage: A manuscript entitled “upper oceanic energy response to tropical cyclone passage” by J. Knaff, M. DeMaria, C. Sampson (NRLMRY), J. Peak (NRLMRY), J. Cummings (NRLMRY) and W. Schubert (CSU) was submitted to the Journal of Climate. The paper describes composite changes in upper ocean energy metrics based on a number of tropical cyclone characteristics (intensity, kinetic energy, latitude, translation speed… etc.). An example of the 10-day changes of the standard Ocean Heat Content measurement based on the depth of the 26C isotherm is shown below. (J. Knaff)
Caption: Typical OHC26C changes as a function of KE (upper left) 10 days, (upper right) 20 days, (lower left) 30 days and (lower right) 60 days following TC passage. Median values are indicated by the points and the bars indicate the quartile values from the median. Results are shown for the Atlantic (ATL, red), the east and central Pacific (EPAC, green), the northwest Pacific (WPAC, blue) and Southern Hemisphere (SHEM, magenta) TC basins as well as the global response (GLOBE, black).
National Hurricane Center (NHC) GOES-R Proving Ground Activities:
Methods to automate the collection of NPP datasets over tropical cyclones were created this quarter. Data collection is accomplished by using a combination of tropical cyclone best track and forecast track information from JTWC and NHC to locate the times when the storm will be seen by NPP. (J. Knaff)
As a follow-up to the Interdepartmental Hurricane Conference, a collaborative project with CDR Elizabeth Sanabia from the U.S Naval Academy was started to better understand the impact of the subsurface ocean structure on tropical cyclone intensification. The ocean heat content analyses from satellite altimetry are being compared with in situ ocean profiles from the 2011 hurricane season, and the impacts on statistical intensity and HWRF model forecasts are being evaluated. (M. DeMaria)
In collaboration with Tony Wimmers (CIMSS), a new GIMPAP project is just getting 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. (D. Lindsey, D. Bikos)
Cheyenne Wyoming (CYS) has successfully added the MODIS Cloud Layer/Snow Cover product. The installation instructions were sent to Rebecca Mazur, and we had a few troubleshooting sessions to get the data flowing. (H. Gosden)
On 18 January 2012, the IR cooler door was opened on VIIRS, allowing data from the infrared bands to begin flowing. The example below shows unprecedented 375-m resolution imagery in the IR over an active tropical cyclone in the Indian Ocean. This high resolution view allows for detailed examination of the convective towers surrounding the center of the storm. (D. Lindsey, D. Hillger, and J. Knaff)
Figure: VIIRS 375-m resolution I-Band-5image of Tropical Cyclone Funso off the southeast coast of Africa on 19 January 2012 at 2206 UTC. This is the highest resolution infrared imagery currently available on a space-borne instrument.
VIIRS imagery generated by RAMMB of Tropical Cyclone Funso in the southwestern Indian Ocean was featured on NASA’s NPP page. A sample image is below, and the page is located here: http://suomi.gsfc.nasa.gov/science/feature2012-0126.html (D. Lindsey, D. Hillger, and J. Knaff)
Figure: VIIRS I-band-5 375-m resolution IR image of Tropical Cyclone Funso in the southwestern Indian Ocean on 25 January 2012.
New Suomi NPP VIIRS Imagery Blog: To accompany the NPP VIIRS Imagery and Visualization Team website, a new Suomi NPP VIIRS Imagery Blog has been started (http://rammb.cira.colostate.edu/projects/npp/blog/). The site, which will host occasional interesting VIIRS Imagery and analysis, was set up by K. Micke and will be maintained by C. Seaman, newly-hired Post-Doctoral Fellow for VIIRS Imagery work at CIRA. (D. Hillger, K. Micke, and C. Seaman)
Figure 1: New Suomi NPP VIIRS Imagery Team Blog
The CIRA NPP VIIRS Blog has been updated to include a new case, in which Madagascar took a direct hit from Tropical Cyclone Giovanna, which reached “Super Cyclone” status as category 4 storm just prior to making landfall. See http://rammb.cira.colostate.edu/projects/npp/blog/index.php/uncategorized/tropical-cyclone-giovanna/ (C. Seaman and D. Lindsey)
Figure: IR-window image of Super Cyclone Giovanna taken by VIIRS channel I-5 at 0947 UTC, 13 February 2012 (Image courtesy of Dan Lindsey)
About 10 to 15% of the VIIRS Imagery “EDR” (GTM projection) granules have been discovered to have corrupted data in the triangular regions in the upper right and lower left portions of the granules. These triangular regions are associated with pixels mapped from the adjacent (+1 and -1 buffered) VIIRS Imagery “SDR” granules. The corrupted values are generally fall within the valid data range but appear to be duplicated data values or values that are suspicious (i.e. constant reflectance values of 1.6). Multiple VIIRS Imagery EDR bands are affected by the same problem. Below are some images of the “problem”. Verification of the problem (granules visually examined) occurred over New Zealand (25 Jan 2012), and over the Arabian Sea (19 Jan 2012). The VIIRS granules for the Saudi Arabia case with the “triangular issue” are available via FTP, which includes the EDRs from Robert Mahoney, the associated SDRs, and the images created from them. Go to ftp://ftp.cira.colostate.edu/ftp/Seaman/satdat/VIIRS/ (D. Hillger and C. Seaman)
Figure A: This first image is the EDR composite of channels I1, I2, and I3, with the triangular section of apparently missing data. This missing data is present in each of those band files.
Figure B: This second image is the SDR composite of the same channels, with no section of missing data.
Figure C: This third image, an outline is plotted of where the data from the SDRs lines up with the data from the EDRs. It appears that the corner of missing data in the EDRs should be coming from the next granule in time. The data in the opposite corner must be coming from the previous granule.
The CIRA NPP VIIRS Blog continues to be updated at least weekly. See http://rammb.cira.colostate.edu/projects/npp/blog/ The image below is an example from the most recent blog addition. (C. Seaman and D. Hillger)
Figure: An RGB composite of high resolution channels I-1 (blue), I-2 (green) and I-3 (red). These channels observe radiances centered on 0.64, 0.86 and 1.61 µm, respectively. As a result, differences in the optical properties of liquid droplets and ice particles at these wavelengths allow liquid and ice clouds (and snow) to be distinguished more easily. Liquid clouds appear white (or a dirty, brownish-white), while ice clouds appear blue. The snow on top of Mauna Loa and Mauna Kea stands out as a deeper blue. Vegetation still shows up as green, and barren ground as brown, producing an image that may be called “pseudo-true color.”
About 10% of the VIIRS Imagery “EDR” (GTM projection) granules have been discovered to have corrupted data in the triangular regions in the upper right and/or lower left portions of the granules. These triangular regions are associated with pixels mapped from the adjacent (+1 and -1 buffered) VIIRS Imagery “SDR” granules. All VIIRS Imagery EDR bands are affected by this problem when it occurs. Below are additional images of the “problem”. The VIIRS granules for sample cases with the “triangular issue” are available via FTP, which includes the EDRs, the associated SDRs, and the images created from them. Go to ftp://ftp.cira.colostate.edu/ftp/Seaman/satdat/VIIRS/
The examples below are three-color composites of granules with this triangular problem. The Imagery Team has been asked to find the “most recent” cases possible, which have occurred in the last 24 hours, for which data still resides on the IDPS (which has a 24 h limit). A major challenge, however, is the long delay in the data received by most Imagery Team members who receive their data through GRAVITE and/or CLASS. (D. Hillger and C. Seaman)
Figure A: A VIIRS granule over the Great Lakes from 20 February 2012, from the file “VI1BO_npp_d20120220_t1800302_e1802187_b01637_c20120221003758637275_noaa_ops.h5” has missing data in the upper-right corner.
Figure B: Another VIIRS granule from “VI1BO_npp_d20120220_t1802080_e1805077_b01637_c20120221003758637275_noaa_ops.h5” has missing data in the lower-left corner.
In the infrared (I-band 5) image below, some annotations point out the two active supercells. Note that the brightness temperatures associated with the overshooting top (OST) of the westernmost storm are colder than the easternmost storm, although both storms were quite strong at the time and the eastern storm ended up producing the deadlier tornadoes. OSTs are transitory, so it’s possible that a new cold OST formed with the eastern storm shortly after the NPP pass. These very high resolution infrared views of tornadic storms are among the first documented, given the recent launch of NPP.
Figure 1: VIIRS I-band 5 Infrared view from 2 March 2012 at 1935 UTC
The day after the tornadoes, relatively cloud-free skies in eastern Kentucky allowed VIIRS to see some of the tornado tracks. In the image below, the faint white lines circled in red in Kentucky and West Virginia denote the new tornado damage paths. When green vegetation is disrupted/destroyed, the result is typically a brighter scene at visible wavelengths.
See the NPP VIIRS Imagery Blog at http://rammb.cira.colostate.edu/projects/npp/blog/ for more details on this case. (D. LindseyandD. Hillger)
Figure 2: VIIRS I-band 1 from 3 March 2012 over eastern KY and western WV. The tornado tracks are circled and show up as faint white lines
New Suomi NPP VIIRS Blog plains wildfire case: The CIRA NPP VIIRS Blog http://rammb.cira.colostate.edu/projects/npp/blog/ has a new example, VIIRS imagery for a plains wildfire, as described in the Blog entry: On 18 March 2012, very warm, very dry and very windy conditions existed throughout eastern Colorado. Surface observations showed temperatures in the 70s and 80s °F, dew points in the teens and 20s °F, and sustained winds at 20-30 knots (gusting over 40 knots). Wind gusts up to 60 knots (~70 mph) were reported. A red flag warning was issued for nearly all of eastern Colorado. And with good reason! A grass fire started in Yuma County, CO (which borders Nebraska and Kansas) in the early afternoon, and quickly grew out of control. The media dubbed it the Heartstrong Fire. An area 14 x 16 miles had to be evacuated, although only 2400 acres actually burned. Two homes were destroyed, and three firefighters were injured battling the blaze.
Even though cirrus clouds covered the area, VIIRS observed the fire in its two 3.7 µm channels. The VIIRS images shown here, from 1934 UTC, were taken roughly 20 minutes after the fire was first reported. The moderate resolution band M-12 (centered at 3.7 µm) identifies a hot spot (which shows up as black in the image below) that is approximately 6 pixels by 3 pixels. With ~750 m resolution in this band at nadir, that corresponds to a total area of 10.2 km² of the pixels with fire signal
Image of the Heartstrong Fire from VIIRS channel M-12, 19:34 UTC 18 March 2012
The high resolution imagery band I-4 (centered at 3.74 µm) also identifies the hot spot. In this case it is approximately 11 pixels by 5 pixels in size. At ~375 m resolution at nadir, this corresponds to a total area of 7.7 km² of the pixels with radiative signal from the fire.
Image of the Heartstrong Fire from VIIRS channel I-4, 1934 UTC 18 March 2012
Thus, the difference in resolution between these two channels leads to a difference in the apparent size of the hot spot as seen by satellites. (It should be noted that this simple area estimate does not take into account distance from nadir as the spatial resolution of VIIRS degrades toward the edge of the scan in the SDR data shown). However, this apparent size is an only an estimate of the size of the hot spot visible in the satellite image, not the actual size of the fire. Fires move in narrow flame fronts that cover only a small percentage of the pixel area. From a firefighting perspective, detecting which pixels actually contain fire and where the actual burning occurs within those pixels are two different things.
Of additional importance is the difference in observed brightness temperatures between these two channels. The warmest pixel in M-12 was 327 K, while the warmest pixel in I-4 was 345 K. As the observed brightness temperature depends on the fraction of each pixel covered by fire, the higher resolution images produce higher brightness temperatures in the hot spot. This means that, to a human observer, the fire appears larger in the M-band image, while, from an automated algorithm point-of-view, the I-band image has a larger number of pixels within the hot spot, and higher brightness temperatures. These are important factors when trying to detect fires from satellites. Neither the apparent size nor the apparent temperature are the true size or temperature of the fire.
As an additional note, band M-13 (centered at 4.05 µm) is the primary band used in active fire detection as it was designed to measure the radiative signal of hot spots without sensor saturation. This band detected the hot spot as well, although the warmest pixel in this case was 306 K. This band is used by a dedicated team of researchers actively exploring fire detection from VIIRS. You can learn more about fire detection and the status of their current fire detection products by visiting viirsfire.geog.umd.edu.
Please see the Blog entry http://rammb.cira.colostate.edu/projects/npp/blog/ for additional images and information on this case. (C. Seaman, and D. Hillger)
The work on the solar regime is continuing. The difference between the clear sky and observations calculated last quarter were used again to calculate the mean and standard deviation for each three, 4 hour periods for each day. The mean data set, using each period as an individual point, was run through K-Means analysis using different numbers of clusters (6-10). The same analysis was run also on the matching standard deviation set. The K-Means clusters for each run separated out quite well, which was a good sign for this approach. The results from both sets were used as limits for various cloud classes (Clear, Haze/Cirrus, Scatter, Broken and Overcast) instead of defining the classes as was done previously. The K-Mean results for 8 clusters in both mean and standard deviation worked provide good classifications. (C. Combs)
In reviewing the resulting classes, it was decided that for solar energy, the ‘Clear’ and ‘Haze’ classes could be combined and that the ‘Overcast’ class was reasonable. It was also decided that there wasn’t a good division between ‘Scattered’ and ‘Broken’, and another method/definition should be used to separate out these two classes.
First, two thresholds using Measured/expected Clear sky values(%Clear) were set. During each period, the number of times the %Clear value was above each threshold was recorded. The Scatter/Broken cases were then divided into categories of when 50% of the period’s values were ‘above high threshold’, ‘between the two thresholds’ and ‘below both thresholds’. Different thresholds were tried, but didn’t appear to separate out the classes as well as expected.
After talking with people from within the solar industry, it was decided that the above method didn’t described their main concern, which was ramps in solar energy during the day. So to address this issue, the ‘peaks’ and ‘valleys’ in observations-clear sky were identified for each period of each day, then valleys were classified into ‘deep’ or ’shallow’ according to how low the %Clear of the valley was and whether there was a large difference between the valley and the surrounding peaks. If none of the valleys were lower than 85% of clear, the period was placed in the ‘Clear/Haze’class. If there were at least one ‘deep’ valley(below 35%), it was classified as ‘Deep Ramps’. If not classified as ‘Deep Ramps’ and there were more than one ‘shallow’ valley, it was classified as ‘Shallow Ramps’. Anything that did not fit in a category was classified as ‘Not Classified’. Periods with sharp transitions between ‘Clear’ and ‘Overcast’ appear to land in this category.
For the next quarter, these classes will be used to produced climatologies over Colorado, and climatologies covering the western US for the days previous each classification. The previous day climatologies will hopefully provide indicators of what conditions to look for in forecasts. A similar method was used looking at Cheyenne high wind events with good results. (C. Combs)
GOES-R3 Convective Initiation Project: 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. Five-minute output from the NSSL-WRF was obtained for a case study from 21 May 2011. Simulated radar reflectivity was used to define Convective Initiation (> 35 dbz at 4-km AGL), so this will be used as the validation dataset. Predictors will include data and products from the simulated GOES-R bands, along with NWP forecasts. One of the inputs is the 10.35-12.3 µm difference. We have recently developed a method to normalize this difference for the low-level temperature lapse rate in an effort to remove the diurnal signal in the difference. An example of the difference for the 21 May 2011 case study is below. (D. Lindsey, L. Grasso)
Figure. Simulated 10.35-12.3 µm data from 21 May 2011 based on a 18-hr, 30-min forecast from the NSSL WRF-ARW. The yellows and reds generally indicate regions with more water vapor, and the blue colors are clouds.
In preparation for the GOES-R Proving Ground activities at the Storm Prediction Center (as part of their annual Spring Experiment), synthetic GOES-R imagery was provided for a Weather Event Simulator case (24 May 2011). In addition, a job sheet was created that provides a walk-through for forecasters to understand how to use and interpret the synthetic imagery. This WES case will be provided to forecasters participating in the Spring Experiment prior to their arrival as a means to familiarize/train them on the products. (D. Lindsey)
A new collaboration, headed by Bill Blackwell of MIT/LL, has begun with several researchers from various organizations centered around MiniMAS (Miniature Microwave Atmospheric Sounder). This NASA project plans to launch up to 6 AMSU-like instrument on the next Iridium satellites in 2016. This configuration would result in 15-25 minute revisit time of the microwave sensor, allowing much better imaging frequency than is available with the current polar-orbiting satellites. RAMMB’s role is to apply this dataset to tropical cyclone research. At this point, weekly conference calls are held, primarily to discuss the necessary details of the proposal to be written. (J. Dostalek)
There are a number of things to report concerning GOES-R Proving Ground activities related to the HWT. First the GOES sounder-based Airmass RGB product is now available in real-time on operational systems at SPC. J. Knaff and M. Folmer (OPC/HPC) provided input detailing the creation, dissemination and training associated with the GOES sounder-based Airmass RGB product for the HWT’s Ops Plan. Finally, training material (WES jobsheet) was created for the Airmass RGB Product. All inputs provided to C. Siewert who was coordinating the Ops Plan. (J. Knaff)
L. Grasso gave an invited talk last January 2012 on our true-color imagery. The invitation was extended by Amy Huff (Battelle). Our presentation was given remotely to the Air Quality Proving Ground Workshop on January 12, 2012. (L. Grasso, D. Hillger, and R. Brummer)
We have been invited to return to the IMET satellite training to present our GOES-R fire work. Last March, CIRA trained IMET on the interpretation of synthetic GOES-R imagery that contains fire hot spots. Peter Roohr and Mike Johnson extended the invitation. Bonnie Reed has been working with Peter to find funding for this effort.
Due to funding shortages, this workshop was cancelled. (L. Grasso)
We began collaborating with Paul van Delst (NCEP/EMC) this quarter. He is helping us develop code that will read output from a numerical model and initialized specific variables that are needed by the Community Radiative Transfer Model (CRTM). I hosted his visit last January. (L. Grasso, Y-J. Noh, R. Brummer)
J. Knaff attended a workshop on 20-22 March in Hamilton, Bermuda. He was among a team of five invited scientists who interacted with various NOAA stakeholders in the insurance, re-insurance, and risk modeling communities. The goal of the workshop was to provide feedback of the relative validity of the latest RMS hurricane risk model (RiskLink v11.0) and identify/quantify uncertainties. The RMS model is widely used to establish insurance rates in the U.S and elsewhere. The invited scientists represented NOAA, Florida State University, and the London School of Economics. (J. Knaff)
Training metrics for the quarter:
15 VISIT teletraining sessions have been delivered. There were 21 teletraining signups, 49 students participated.
Registrations: 170
Completions: 104
LMS totals from January 2005 through March 30, 2012:
Registrations: 5672
Completions: 3660
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 forum debuted this quarter:
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 March 30, 2012, there have been 2 VISIT Satellite Chat sessions for a total of 30 participants from 10 NWS forecast office signups.
Ongoing development of new VISIT training sessions:
Research:
Collaboration:
J. Braun with D. Lindsey are initiating a collaborative effort between CIRA/GOES-R Proving Ground project and the Aviation Weather Center (AWC) and their Aviation Weather Testbed to access the use of forecast synthetic imagery in NAWIPS in aviation weather forecasting. Currently forecast synthetic products – 7.34um, 8.50um, and 10.35-3.9um fog product are being provided and utilized with additional real-time GOES-R products planned to be added in the future.
J. Braun and 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/) – (J. Braun) Continue to build and administer the VISIT Blog – a web-log program intended to initiate increased communication between the operational, academic, and training worlds. The blog averages about 300 views per week.
The following table shows a breakdown of the metrics for each VISIT teletraining session valid April 1999 – March 30, 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 | 1607 | 6724 | 17835 | 23726 |
| 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 | 40 | 154 | 370 | 555 |
| 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 | 43 | 169 | 435 | 569 |
| AWIPS Cloud Height / Sounder | 11 | 55 | 128 | 178 |
| QuikSCAT winds | 10 | 37 | 107 | 110 |
| Convective Downbursts | 64 | 218 | 461 | 766 |
| 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 | 23 | 36 | 63 | 89 |
| 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 | 21 | 34 | 34 | 99 |
| Utility of GOES for Severe Wx | 22 | 48 | 93 | 151 |
| NHC Track Models | 5 | 23 | 36 | 78 |
| NHC Intensity Models | 5 | 17 | 35 | 67 |
| Basic Sat Interp in the Tropics | 5 | 6 | 15 | 17 |
| POES and AVHRR in AWIPS | 7 | 12 | 13 | 117 |
| UW Convective Initiation Product | 14 | 22 | 37 | 84 |
| Water Vapor imagery for severe wx | 7 | 13 | 6 | 53 |
| UW Nearcasting product | 7 | 8 | 1 | 21 |
| Atmospheric Rivers | 2 | 7 | 26 | 26 |
| MIMIC TPW | 3 | 5 | 0 | 14 |
| Synthetic Severe | 10 | 10 | 4 | 51 |
| OST and Thermal Couplet | 2 | 2 | 0 | 12 |
| Synthetic Orographic Cirrus | 1 | 1 | 1 | 1 |
| GOES-15 to GOES-West | 3 | 15 | 0 | 54 |
Meetings and Calls
J. Braun, D. Bikos and B. Connell met with Ben Schwedler from the Aviation Weather Center in Kansas City, MO to discuss GOES-R proving ground related training.
VISIT/SHyMet had conference calls on February 1 and March 9.
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:
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:
SHyMet Severe Thunderstorm Metrics: CIRA/VISIT Registered:
1 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2012) for the SHyMet Severe Development Plan. (42 total for March 2011 through Mar. 31, 2012). 0 Participants have completed the course this quarter, with 10 having completed since its inception.
SHyMet Severe Thunderstorm – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Severe Thunderstorm individual class/session breakdown through Mar. 31, 2012 (for “online” training only).
Tropical SHyMet Learning Plan. Released August 2010.
Consists of 7 courses: http://rammb.cira.colostate.edu/training/shymet/tropical_intro.asp
SHyMet Tropical Metrics: CIRA/VISIT Registered:
3 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2012) for the SHyMet Tropical Development Plan (16 total for August 2010 through Mar. 31, 2012). 0 Participants have completed the course this quarter, with 5 having completed since its inception.
SHyMet Tropical – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Tropical individual class/session breakdown through Mar. 31, 2012 (for “online” training only).
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
SHyMet For Forecasters Metrics: CIRA/VISIT Registered:
7 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2012) for the SHyMet Forecasters Course Development Plan (46 total for January 2010 through Mar. 31, 2012) 6 Participants have completed the course this quarter, with 22 having completed since its inception.
6 Non-NOAA participants (International) have registered here at CIRA for the SHyMet Forecasters Course between January 2010 – Mar. 31, 2012. There were no known completions this quarter.
SHyMet For Forecasters – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Forecasters individual class/session breakdown through Mar. 31, 2012 (for “online” training only).
SHyMet Intern Learning Plan: Released April 2006
The SHyMet Intern consists of 9 modules.
(http://rammb.cira.colostate.edu/training/shymet/intern_intro.asp ).
SHyMet Intern Metrics: CIRA/VISIT Registered:
7 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2012) for the SHyMet Intern Course – 302 total for April 2006 through March 31, 2012. 3 Participants completed the course this quarter for a total of 146 registered completions.
1 Non-NOAA participants (International) have registered here at CIRA this quarter for the SHyMet Intern Course. (35 total for April 2006 – Mar. 31, 2012) There were no completions this quarter.
SHyMet Intern – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Intern individual class/session breakdown through
March 31, 2012.
ALL SHYMET: Total Registered through LMS since inception of SHyMet: 5532
Total Completed in LMS Since Inception: 3760
Figure SHyMet_2ndqrtfy12.png SHyMet registrations for total modules for the 4 courses as counted in the Commerce Learn Center Learning Management System. SHyMet Intern saw the highest number of registrations in its first year (2006). Registrations have been consistent for the Intern course over 2007-2011 reflecting the need of the target audience.
Collaboration:
J. Braun is currently collaborating with Jesse Sparks (interim SOO) from the Aviation Weather Center (AWC) on building a new SHyMet learning plan for Aviation Weather.
Professional Meeting:
Connell, B., Bikos, D., Braun, J., Bachmeier, S., Lindstrom, S., Mostek, A., Davison, M., Caesar, K., Castro, V., Veeck, L., DeMaria, M., and Schmitt, T., 2012: Satellite Training Activities: VISIT, SHyMet and WMO VLab Focus Group, 8th Annual Symposium on Future Operational Environmental Satellite Systems, New Orleans, LA., 22-26 January, Amer. Meteor. Soc. Poster
Connell, B. H., and Gebhart, K., 2012: Golden Words from elementary kids: Can I show you my observation! 21st Symposium on Education, New Orleans, LA, 22-26 January, Amer. Meteor. Soc. Presentation
Community outreach:
Volunteer work supporting after-school weather club: B. Connell, K. Gebhart and N. Newman ran a weekly after-school weather club on Mondays for Putnam Elementary (K-5) for 7 weeks during January through March 2012. There was a 90 minute session each week. Sessions covered snow, wind (speed and direction), clouds, temperature, and things that spin as well as measurements that are associated with these weather occurrences. Putnam has a coordinator who is responsible for matching students with clubs, assigning classrooms, providing snacks, and providing transportation – which is great!
An AWIPS “Jobsheet” describing the GOES Sounder-based Airmass product for the 24 May 2011 WES case was provided to C. Seiwert and D. Kingfeild for training related to the Hazardous Weather Testbed/Spring Experiment was provided. (J. Knaff)
Monthly International Weather Briefings
The WMO Virtual Laboratory Regional Focus Group of the Americas and Caribbean conducted 3 monthly English and Spanish weather briefings (19 October, 22 November, and 22 December 2011) 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, as well as outside the continental U.S.: Antigua, Barbados, Belize, Cayman Islands, Colombia, Costa Rica, Dominica, Dominican Republic, El Salvador, Great Britain, Grenada, Guyana, Honduras, Jamaica, Mexico, Panamá, Peru, Puerto Rico, St. Lucia, and Uruguay. The participants include researchers and students as well as forecasters. Twelve countries participated in October, ten countries logged on in November, and seven countries participated in December. The discussions were well attended with multiple participants at various sites. During the October session, Mike Davison from the NCEP International Desk commented on first major surge of cold air into Central America and participants provided comments particularly about associated rainfall in their regions. We also looked at GOES-12 sounder imagery from a case of blowing volcanic ash in Argentina, a significant event that closed the Buenos Aires airport for 12 hours on 16 October. In December, Mike engaged the participants to draw on the imagery to demonstrate flow at various levels in the atmosphere. One particular example was associated with convergent flow with resulting heavy rains in the area of Southern Caribbean Windward Islands and the North East Coast of South America (Figure BC_DEC2012.JPG). Participants provided comments about the local weather in their regions. (B. Connell)
Figure: Screen grab during the WMO VLab monthly virtual session of the Americas and Caribbean for December 2011. The participants were invited to draw on the screen of a loop of visible imagery to show cloud/wind movement and resulting convective features.
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. (B. Connell)
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/
(B. Connell, D. Coleman, D. Watson, K. Micke)
Three additional workstations and two 14 TB NAS storage devices have been purchased to support JPSS Suomi-NPP data ingest and analysis. (D. Molenar)
Published:
Hamill, T.M., M.J. Brennan, B. Brown, M. DeMaria, E.N. Rappaport, and Z. Toth, 2012: NOAA’s future ensemble-based hurricane forecast products. Bull. Amer. Meteor. Soc., 93, 209-220.
Miller, S.D., C. Schmidt, T.J. Schmit, and D.W. Hillger, 2012: A Case for natural colour imagery from geostationary satellites, and an approximation for the GOES-R ABI, Int. J. Remote Sens., 33:13, doi: 10.1080/01431161.2011.637529
Connell, B.H., D. Bikos, J. Braun, A.S. Bachmeier, S. Lindstrom, A. Mostek, M. Davison, K.A. Caesar, V. Castro, L.Veeck, M. DeMaria, and T.J. Schmit, 2012: Satellite Training Activities: VISIT, SHyMet and WMO VLab Focus Group. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
Csiszar, I., C.D. Barnet, R. Ferraro, L.E. Flynn, A.K. Heidinger, D.W. Hillger, A.Ignatov, J.Key, S.Kondragunta, I.Laszlo, and M.Wang, 2012: Overview of NPP/JPSS Environmental Data Products and Algorithm Development. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
Gurka, J.J., S. Goodman, T.J. Schmit, M. DeMaria, A. Mostek, C.W. Siewert, and B. Reed, 2012: The GOES-R Proving Ground: 2012 Update. 8th Annual Symposium on Future Operational Environmental Satellite Systems, 22-26 January 2012, New Orleans, LA.
Lindsey, D.T., and L.D. Grasso, 2012: Predicting where convective clouds will form with the GOES-R ABI. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
Lindsey, D.T., T. Schmit, W. MacKenzie, L.D. Grasso, M. Gunshor, C. Jewett, 2012: The 10.35 micrometer band: A more appropriate window band for GOES-R ABI than 11.2?. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
Mecikalski, J.R., D.T. Lindsey, C.S. Velden, B.L. Vant-Hull, and R.M. Rabin, 2012: Convective Storm Forecasting 1-6 Hours Prior to Initiation 8th Annual Symposium on Future Operational Environmental Satellite Systems, 22-26 January 2012, New Orleans, LA.
Molthan, A., K. Fuell, H. Oswald, and J.A. Knaff, 2012: Development of RGB Composite Imagery for Operational Weather Forecasting Applications. 8th Annual Symposium on Future Operational Environmental Satellite Systems, 22-26 January 2012, New Orleans, LA.
Reed, B., M. DeMaria, S.J. Goodman, J. Gurka, D. Reynolds, and C.W. Siewert, 2012: GOES-R Proving Ground – Demonstrating GOES-R Products in 2011 8th Annual Symposium on Future Operational Environmental Satellite Systems, 22-26 January 2012, New Orleans, LA.
Reynolds, D., M. DeMaria, S.J. Goodman, M.W. Johnson, and B. Reed, 2012: Data Fusion Demonstrations At the GOES-R Proving Ground Using Satellites, in-Situ Data and Weather Forecast Models. 8th Annual Symposium on Future Operational Environmental Satellite Systems, 22-26 January 2012, New Orleans, LA.
Bikos, D., D.T. Lindsey, J. Otkin, J. Sieglaff, L.D. Grasso, C. Siewert, J. Correia Jr., M. Coniglio, R. Rabin, J. Kain, S. Dembek: 2012: Synthetic Satellite Imagery for Real-Time High Resolution Model Evaluation. Weather and Forecasting.
DeMaria, M., R.T. DeMaria, J.A. Knaff, D.A. Molenar, 2012: Tropical Cyclone Lightning and Rapid Intensity Change. Mon. Wea. Rev.
Goodman, S.J., J. Gurka, M. DeMaria, G. Jedlovec, T. Schmit, C. Siewer,; A. Mostek, W. Feltz, J. Gerth, R. Brummer, S. Miller, B. Reed, R. Reynolds, 2012: The GOES-R Proving Ground: Accelerating User Readiness for the Next Generation Geostationary Environmental Satellite. Bull. Amer. Soc.
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.
Vigh, J.L, J.A. Knaff, W.H. Schubert, 2012: A climatology of hurricane eye formation. Mon. Wea. Rev.
DeMaria, M., J.A. Knaff, A.B. Schumacher, J. Kaplan, 2012: Improving Tropical Cyclone Rapid Intensity Change Forecasts from Statistical-Dynamical Models. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Dostalek, J.F., W. Schubert, M. DeMaria, 2012: Global Omega Equation: Its Derivation and Use in Tropical Cyclogenesis. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Folmer, M.J., A.L. Molthan, K.K. Fuell, J.A. Knaff, J.M. Sienkiewicz, E. Danaher, J. Kibler, D.R. Novak, B. Reed, J.L. Beven II, M. DeMaria, 2012: The Use of the RGB Airmass Product at the HPC, OPC, NHC, and SAB GOES-R Proving Grounds during the 2011 Atlantic Hurricane Season. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Kaplan, J., C.M. Rozoff, C.R. Sampson, J.P. Kossin, C.S. Velden, M. DeMaria, J.A. Knaff, 2012: Assessing the predictability of tropical cyclone rapid intensification as a function of forecast lead-time using the SHIPS rapid intensification index. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Knaff, J.A., M. DeMaria, C.R. Sampson, J. Peak, J. Cummings, W. Schubert, 2012: The Upper Ocean’s Thermal Response to Tropical Cyclones. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Knaff, J.A., M. DeMaria, D.W. Hillger, D.T. Lindsey, D.A. Molenar, J.L. Beven II, M.J. Brennan, H.D. Cobb III, R.L. Brummer. A.B. Schumacher, J.P. Dunion, K.K.Fuell, A.L. Molthan, C.S. Velden, 2012: Overview of the GOES-R Proving Ground Activities at National Hurricane Center. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Maclay, K.S., M. DeMaria, T. Vonder Haar, 2012: Tropical Cyclone Kinetic Energy and Structure Evolution in the HWRF Model. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
McNoldy, B.D., K.D. Musgrave, M. DeMaria, 2012: Diagnostics and verification of the tropical cyclone environment in regional models. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Musgrave, K.D., B.D. McNoldy, M. DeMaria, 2012: Creation of a Statistical Ensemble for Tropical Cyclone Intensity Prediction. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Peak, J.E., C.R. Sampson, J. Cummings, J.A. Knaff, M. DeMaria, W. Schubert, 2012: An Upper Ocean Thermal Field Metrics Dataset. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Sampson, C.R., A.B. Schumacher, J.A. Knaff, M. DeMaria, E.M. Fukada, C. Sisko, D.P. Roberts, K.A. Winters, H.M. Wilson, 2012: An Objective Aid for DoD Base Preparations in Advance of Tropical Cyclones. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Schumacher, A.B., M. DeMaria, J.A. Knaff, 2012: Another Look at the Use of Maximum Potential Intensity of Tropical Cyclones. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Sitkowski, M., J.P. Kossin, C.M. Rozoff, J.A. Knaff, 2012: Thermodynamic Evolution of the Hurricane Inner-Core during Eyewall Replacement Cycles and Ramifications of the Relict Wind Maximum. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Slocum, C.J., M. DeMaria, W. Schubert, 2012: Determining Tropical Cyclone Intensity Change through Balanced Vortex Model Applications. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Zhang, F., Y. Weng, X. Ge, J. Knaff, 2012: Performance of Cloud-permitting Hurricane Prediction through Assimilating High-resolution Airborne Doppler Radar and Satellite-derived Inner-core Observations. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
Knapp, K.R., J.A. Knaff, C.R. Sampson, 2012: Inter-comparison of climatological TC winds and pressures in the Western North Pacific. 30th AMS Conference on Hurricanes and Tropical Meteorology, 15-20 April, Ponte Vedra Beach, FL.
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.
Sampson, C., A. Schumacher, J.A., Knaff, M. DeMaria, E. Fukada, C. Sisko, D. Roberts, K. Winters, H. Wilson, 2012: Objective guidance for use in setting tropical cyclone conditions of readiness. Weather and Forecasting.
Setvak, M., K. Bedka, D.T. Lindsey, A. Sokol, Z. Charvat, J. Stastka, and P. K. Wang, 2012: A-Train observations of deep convective storm tops. Atmospheric Research.
Sitkowski, M., J. Kossin, C. Rozoff, and J.A. Knaff, 2012: Hurricane eyewall replacement cycles and the relict inner eyewall circulation. Mon. Wea. Rev.
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.
DeMaria, M., J.A. Knaff, J.L. Beven, M. Brennan, S. Miller, A.B. Schumacher, R. DeMaria, J.F. Dostalek, and D. Welsh. Application of Joint Polar Satellite System (JPSS) Imagers and Sounders to Tropical Cyclone Track and Intensity Forecasting. NOAA Satellite Science Week Meeting, 30 April – 4 May, Kansas City, MO.
Knaff, J.A., M. DeMaria, J.F.Dostalek, A.B. Schumacher. Improved Understanding and Diagnosis of Tropical Cyclone Structure and Structure Changes. NOAA Satellite Science Week Meeting, 30 April – 4 May, Kansas City, MO.
Lindsey, D.T., L.D. Grasso, J. Mecikalski, J. Walker, L. Schultz, C. Velden, S. Wanzong, R.Rabin, and B. Vant-Hull. Convective Storm Forecasting 1-6 Hours Prior to Initiation. NOAA Satellite Science Week Meeting, 30 April – 4 May, Kansas City, MO. Knaff, J.A., M. DeMaria, and C. Rozoff. Improved Understanding and Diagnosis of Tropical Cyclone Structure and Structure Changes. NOAA Satellite Science Week Meeting, 30 April – 4 May, Kansas City, MO.
2011 Bronze Medal Award Recipients: For providing skillful operational hurricane intensity models as demonstrated by the NHC forecast verifications for the 2009 and 2010 seasons.
Mark DeMaria
John A Knaff
John Kaplan
Beven, J., M. Brennan, H. Cobb, M. DeMaria, J.A. Knaff, C. Velden, J. Dunion, and G. Jedlovec, 2012: The 2011 GOES-R Proving Ground at the National Hurricane Center. 66th Interdepartmental Hurricane Conference, March 5-8, Charleston, SC.
Combs, C., 2012: Pacific Fog Climatologies,’ and presented satellite cloud climatologies and specifically the climatologies produced with the Eureka, CA and Monterey, CA National Weather Service offices. Online seminar to a USGS-sponsored group interested in marine stratus/fog along the California coast. A recording of the seminar can be found at: https://usgs.webex.com/usgs/lsr.php?AT=pb&SP=MC&rID=52960327&rKey=3a4133e431c5754b
DeMaria, M., 2012: The Role of Satellite Observations in Forecasting Landfalling Tropical Cyclones. AMS 10th Symposium on the Coastal Environment. 22-26 January, New Orleans, LA.
DeMaria, M., J.A. Knaff, A. Schumacher, J.F. Dostalek and R. DeMaria, 2012: Applications of ATMS/CrIS Soundings to Tropical Cyclone Analysis and Forecasting. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
DeMaria, M., A.B, Schumacher, J. A. Knaff, and R.L. Brummer, 2012: Improvements in Statistical Tropical Cyclone Forecast Models: A Year 1 Joint Hurricane Testbed Project Update. 66th Interdepartmental Hurricane Conference, March 5-8, Charleston, SC.
Grasso, L.D., 2012: True-color imagery. Air Quality Proving Ground Workshop (given remotely), January 12 (L. Grasso, D. Hillger, R. Brummer)
Grasso, L.D., R.L. Brummer, R. DeMaria, D.T. Lindsey, and D.W. Hillger, 2012: GOES-R activities at CIRA. Second Hazardous Weather Workshop, 7-9 February, Norman, OK.
Hillger, D.W., 2012: The hidden role of the metric system in the U.S.: What you may not know! 9-11 January, Colorado State University’s Professional Development Institute (PDI) Fort Collins, CO.
Hillger, D.W., T.J. Kopp, 2012: First Images and Products From VIIRS on NPP. AMS Eighth Annual Symposium on Future Operational Environmental Satellite Systems. 22-26 January, New Orleans, LA.
Hillger, D.W., and T. Schmit, 2012: GOES Science Tests: Results for the Last Two of the Current GOES Series. 18th Conference on Satellite Meteorology, Oceanography and Climatology / First Joint AMS-Asia Satellite Meteorology Conference. 22-26 January, New Orleans, LA.
Lindsey, D.T., 2012: Using Synthetic Satellite Data to Prepare for GOES-R. Seminar at EUMETSAT, March 22, 2012.
Musgrave, K.D., M. DeMaria, B.D. McNoldy, Y. Jin, and M. Fiorino, 2012: Creation of a Statistical Ensemble for Tropical Cyclone Intensity Prediction. 66th Interdepartmental Hurricane Conference, March 5-8, Charleston, SC.
Knaff, J.A., R.L. Brummer, M. DeMaria, C. Landsea, and J. Franklin, 2012: Development of a Real-Time Automated Tropical Cyclone Surface Wind Analysis: A Year 1 Joint Hurricane Testbed Project Update. 66th Interdepartmental Hurricane Conference, March 5-8, Charleston, SC.
Schumacher, A., M. DeMaria, M. Brennan, K. Musgrave, T. Marchok and J. Moskaitis, 2012: Applications of Ensemble Tropical Cyclone Products to National Hurricane Center Forecasts and Warnings. Warn on Forecast and High Impact Weather Workshop, 8-9 February, Norman, OK.
Schumacher, A.B., M. DeMaria, K.D. Musgrave and J.A. Knaff, 2012: Development of a Hybrid Statistical-Dynamical Wind Speed Probability Model. 66th Interdepartmental Hurricane Conference, March 5-8, Charleston, SC.
Zhang, M., M. Zupanski, M.-J. Kim, and J. Knaff, 2012: All-sky radiance assimilation using NOAA operational HWRF and a regional hybrid ensemble-variational data assimilation system. Warn-on-Forecast and High Impact Weather Workshop, 8-9 February 2012, Norman, OK.
Zupanski, M., M. Zhang, and K. Apodaca, 2012: Challenges of assimilating all-sky satellite radiances. Warn-on-Forecast and High Impact Weather Workshop, 8-9 February 2012, Norman, OK.
Notes: Visit to EUMETSAT and Prague: D. Lindsey traveled Europe March 21-30, 2012. The first stop was Darmstadt, Germany, to visit EUMETSAT. There, I gave a seminar titled “Using Synthetic Satellite Data to Prepare for GOES-R.” We also had some valuable discussions regarding preparations for new satellites, as EUMETSAT will be launching Meteosat Third Generation in 2018 and has begun their preparation activities. Next, I traveled to Prague to attend a EUMETSAT-sponsored Convection Working Group Workshop hosted by the Czech Hydrometeorological Institute, and provided a few short lectures on some of the GOES-R Risk Reduction work I’m currently involved in and some storm top radiative transfer model simulations we’ve completed. Multiple opportunities for collaboration were realized during this visit. (D. Lindsey)
Figure. Photo of the participants at the Convection Working Group Workshop in Prague, Czech Republic 27-30 March, 2012.
Virtual Meeting of the WMO Virtual Laboratory Management Group: CIRA and the NWS Training Division participated in a virtual meeting of the VLMG on 22 February 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 upcoming Caribbean Aviation Week during the first week of May, and organization of a Satellite Direct Readout week as well as Precipitation Event week to coincide with other face to face trainings and conferences in the fall. Preparations for the VLMG meeting in October in Brazil were also discussed. (B. Connell)
| Traveler Destination Purpose Funding Dates |
| Wendoloski, E. | Fort Collins, CO | CIRA Internship | NOAA | January 9-11 |
| DeMaria, M. | New Orleans, LA | AMS Conferences | GOES-R | January 22-26 |
| Hillger, D. | New Orleans, LA | AMS Conferences | PDRA | January 22-26 |
| Connell, B. | New Orleans, LA | AMS Conferences | SHyMet | January 22-26 |
| Musgrave, K. | New Orleans, LA | AMS Conferences | HFIP | January 22-26 |
| van Delst, P. | Fort Collins, CO | Collaboration | GOES-R | January 31-February 3 |
| Grasso, L. | Norman, OK | WoF High Impact Workshop | GOES-R | February 7-9 |
| Schumacher, A. | Norman, OK | WoF High Impact Workshop | GOES-R | February 7-9 |
| Maclay, K. | Fort Collins, CO | Collaboration | C/Gar & HFIP | February 27-March 2 |
| Schumacher, A. | Charleston, SC | Interdepartmental Hurricane Conf | PSDI | March 4-8 |
| Musgrave, K. | Charleston, SC | Interdepartmental Hurricane Conf | PSDI | March 4-8 |
| DeMaria, M. | Charleston, SC | Interdepartmental Hurricane Conf | GOES-R | March 4-8 |
| Knaff, J. | Charleston, SC | Interdepartmental Hurricane Conf | GOES-R | March 4-8 |
| Szoke, E. | Fort Collins, CO | Proving Ground Meeting | Proving Ground | March 6 |
| Szoke, E. | Pueblo, CO | Proving Ground Demonstration | Proving Ground | March 13 |
| Hillger, D. | Cheyenne, WY | CAC Renewal | CoRP Base | March 14 |
| Knaff, J. | Bermuda | RPI Workshop | CoRP/RPI | March 20-23 |
| Lindsey, D. | Darmstadt/Prague | EUMETSAT |
Paul van Delst Visit: Paul van Delst (NWS/EMC/JCSDA) visited CIRA and RAMMB Jan 30th through February 2nd. Paul worked with CIRA’s radiative transfer team on using the Community Radiative Transfer Model (CRTM) to create synthetic imagery from WRF-ARW output. He also met with CIRA’s Data Assimilation team. Paul gave a seminar on the recent developments in the CRTM to improve the use of satellite radiances in data assimilation systems.
CIRA IT staff annual reviews and 2013 work plans have been completed. (D. Molenar)
D. Molenar has completed the latest versions of AWIPS II training available via LMS. Training has also been completed on the new NWS Software Collaboration Portal for Local Application development and collaboration. AWIPS II ESA and ITO training are also in progress. (D. Molenar)