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The Monte Carlo Wind Speed Probability product was tested to determine how the wind speed probabilities computed explicitly at coastal breakpoints differ from those interpolated from gridded wind speed probabilities. It was determined that wind speed probabilities interpolated to coastal points from the operational 0.5 degree latitude/longitude grid can differ by as much at 20% from those computed explicitly at the coastal points. Finer resolutions were tested and it was found that that difference can be reduced to less than 10% when the MCWSP product is run on a 0.25 degree latitude/longitude grid, as shown in the Figure below. (A. Schumacher, M. DeMaria)
Figure. Maximum and minimum errors for the 120-hr cumulative 34-kt and 64-kt Monte Carlo Wind Speed probabilities interpolated to U.S. coastal break points from the gridded product run at various resolutions. Two cases are shown; Hurricane Charley (2004) approx. 2 days before landfall along Florida’s SW coast and Hurricane Ike (2008) approx. 4 days before landfall along the TX coast.
Overshooting cloud top counts was tested as a potential predictor in the experimental NESDIS Tropical Cyclone Formation Probability product. OT data for the Atlantic from 2009 and 2010 were supplied by S. Monette at University of WI, Madison. Although the OT count parameter was chosen as an important parameter by the linear discriminant analysis, the resulting formation probabilities had slightly lower Brier Skill scores (with respect to climatology) than the version developed without the OT count parameter. More years of data are needed to see if OT counts can provide independent information for TC genesis forecasting. (A. Schumacher, M. DeMaria)
A RedGreenBlue (RGB) satellite product patterned after similar products produced by EUMETSAT is being generated using a combined GOES-E/W sounder sector for the upcoming HPC Proving Ground experiment. The Air Mass Product, which highlights atmospheric air mass difference by using two water vapor channels and an ozone channel, currently uses the EUMETSAT product recipe. Output files are now made available (via ftp) for our partners at SPoRT who are taking the 24-bit information, generating 7-bit imagery compatible with N-AWIPS, and providing it to the National Centers. This adaptation of the GOES-Sounder data allows for the display and animation of GOES-R like products to be generated over the CONUS. An example is provided below. (GOES-R Proving Ground, J. Knaff)
Figure 2: An of a GOES Sounder-based air mass product generated using the EUMETSAT product recipe and channels 12, 10, 9, and 8 of the GOES sounders with scan times starting at :46 and :01 after the hour. Image is valid at approximately 0100 UTC 30 March 2011.
A software package that ingests TPW datasets generated by NESDIS (developed at CIRA), and converts them to a standard ascii format has been installed and tested on Joint Hurricane Testbed (JHT) machines at NHC. This ingest will allow the TPW datasets to be easily posted directly to the NCEP IBM (because NHC is behind the NCEP firewall). Once on the NCEP IBM operational statistical-dynamical intensity forecasts systems (SHIPS, LGEM and RII) can access that information for JHT and GOES-R related projects. (JHT, GOES-R, J. Knaff, R. Viola)
The code that decodes AMSU-A antenna temperatures and the code that creates statistical temperature retrievals from those information was updated and provided to the NHC and NCEP Central Operations for implementation. The new code decodes and limb corrects data from NOAA-19, MetOp-A, and NASA Aqua in addition to NOAA-15, 16, and 18. Limb correction coefficients for these newer instruments were provided by K. Zhang and C. Barnett (StAR). Once tested and installed in the operational suite, six satellites will provide tropical cyclone intensity/structure as well as balanced wind fields for all active tropical cyclones – more than doubling the number of fixes available. This work, once the software is transitioned to NCEP operations, will constitute conclusion of a 2008 PSDI project. (PSDI, J. Knaff, J. Dostalek)
Significant progress has been made this quarter on software that reads, navigates and calibrates McIDAS AREA GOES GVAR files outside of the McIDAS environment. These software will allow for easier exchange of such data with collaborators who do not use or have access to the McIDAS software package. Testing will begin next quarter. (J. Knaff, R. Viola).
Methods that anticipate rapid weakening (decrease in intensity of 25 kt in 24-h) of non-landfalling tropical cyclones have been developed, tested and presented. The methods provide the probability of such an event occurring in the following 24-h. The work was presented at the Interdepartmental Hurricane Conference in Miami. The independent results based on 2009-2010 data are shown below for both the Atlantic and East Pacific Basins. (J. Knaff)
Figure 3: The Brier Skill Score, the bias, the maximum threat score and the probability associated with the maximum threat score is shown for the rapid weakening index for the Atlantic (left) and East Pacific (right). Methods use logistic regression to predict probabilities. Results are based on independent forecasts made in 2009 and 2010.
Methods that anticipate the transition of a tropical cyclone to a mid-latitude cyclone have been developed, tested and presented. The method provides the probability of such an event occurring in the following 24-h. The work was presented at the Interdepartmental Hurricane Confernce in Miami. The independent results based on 2009-2010 data are shown below for the Atlantic Basin. With the success of this method (i.e. large threat and skill scores), this method will be adapted to the full 5-day forecast in the next year. (J. Knaff)
Figure 4: The Brier Skill Score, the bias, the maximum threat score and the probability associated with the maximum threat score is shown for the extra-tropical transition index for the Atlantic using two different statistical methods linear discriminant analysis (left) and logistic regression (right). Results are based on independent forecasts made in 2009 and 2010.
As part of the GOES-R Proving Ground at the National Hurricane Center (NHC), lightning data from ground-based networks are being evaluated for utility in forecasting tropical cyclone intensity changes. Ground-based networks are being used as a proxy for the GOES-R Geostationary Lightning Mapper (GLM). An experimental version of the NHC’s operational rapid intensity index was developed and tested on independent cases from the 2009 and 2010 hurricane seasons. The figure below shows that the lightning data improved the forecast bias and the Brier Score (similar to a root mean square error for probabilistic forecasts) for both the Atlantic and eastern North Pacific. The threat score was also improved for the eastern Pacific cases. (GOES-R Proving Ground, J. Knaff, M. DeMaria)
Figure 1: Improvement in standard metrics for evaluating probabilistic forecasts due to the inclusion of lightning data in an algorithm to forecast rapid intensification of tropical cyclones.
AWG tropical cyclone datasets are being utilized for data assimilation studies of Hurricane Fred (2009). Methods have been developed to extract the location and satellite sensor information out of McIDAS AREAs created by past AWG projects (storm-centered images of all 11 MSG channels). Sample datasets have been provided to K. Apodaca and M. Zupanski (CIRA) for testing. In the near future, these data will be used for data assimilation of cloudy information near the core of Hurricane Fred. (HFIP, GOES-R, J. Knaff)
Software to calculate the Holland (1980) Model’s B parameter, and the Courtney & Knaff/Knaff & Zehr wind-pressure relationships from operational tropical cyclone data were provided to B. Sampson (NRLMRY). These software routines will be used to develop a forecaster’s interactive dialog on the Automated Tropical Cyclone Forecast system, the primary operational tropical cyclone forecasting tool used at NHC, CPHC and JTWC. It is anticipated that the forecaster dialog will be installed in the next quarter. (HFIP, PSDI, GIMPAP, J. Knaff)
Datasets generated by the Multi-platform Tropical Cyclone Surface Wind Analysis (MTCSWA) were shared with F. Zhang (Penn State Univ.) for HFIP retrospective modeling studies of the 2010 Atlantic and Western Pacific tropical cyclone seasons. Data included the input data used to generate the MTCSWA as well as the final surface wind analyses. (HFIP, J. Knaff)
Coefficients for the Statistical Typhoon Intensity Forecast Scheme (STIPS) for the western North Pacific were shared with CWB in Taiwan. CWB plans to implement a version of the model using inputs from their locally run numerical weather prediction system. Coefficients for two versions of the STIPS model were provided, one of which uses oceanic heat content (OHC) as a predictor and one that does not use OHC. (J. Knaff)
D. Lindsey, D. Hillger, and J. Knaff of the RAMM Branch were three of the 7 speakers providing brief synopses of their work at a group seminar held 24 February 2011 at the CSU Department of Atmospheric Science. These talks are modeled after similar brief introductions/talks by Department faculty. It is a way to introduce the speakers and their research areas to the large number of students and other researchers in the many different components of the Atmospheric Science and CIRA campus. (D. Lindsey, D. Hillger, J. Knaff )
Historical plots of oceanic heat content, or tropical cyclone heat potential, were created for several very intense tropical cyclones and provided to K. Hourau (Cergy-Pontoise University, France) who is examining the atmospheric and environmental characteristics associated with those events. Original data were supplied by G. Goni (NOAA/AOML). (J. Knaff)
RAMMB was informally asked by the Australian Bureau of Meteorology (BoM) to generate some of its tropical cyclone products for Tropical Cyclone (TC) Larry (2006). Products were put on the RAMMB TC real-time web page/database http://rammb.cira.colostate.edu/products/tc_realtime/. These objective products will be used by BoM to compare the TC Larry landfall in 2006 to the more recent landfall to TC Yasi in 2011. Both Larry and Yasi were very intense storms that made landfall along the Queensland coast with minimum central pressures of 940 and 929 hPa, respectively. (J. Knaff)
The cloud climatology based on marine stratus depth work with Joe Clark and Mel Nordquist from the Eureka, CA National Weather Service (NWS) office, and Becca Mazur with Cheyenne, WY NWS office is continuing. Two telecons were held to discussed the calculation of marine stratus burn off rate and what could affect it. Also discussed were future uses for climatologies in the Eureka office and a possible paper. (C. Combs)
Algorithms and procedures for producing cloud climatologies from class lists have been created and tested in preparation for results from Principle Components. In testing these procedures, general climatologies for each daylight hour during the entire season (May-September) and monthly for the 1998-2009 time period were produced. These general climatologies can be used later for comparison with the solar regime climatologies. (C. Combs)
The analysis of the new snow algorithm using MSG1 Data from March 2006 and 2007 has continued. It appears that a couple of the thresholds used for the February 2007 may need to be adjusted for the spring months. Snow data over Europe was found online from the National Ice Center. Comparisons with the 24 km gif images have been favorable, though the snow data is at a resolution much lower than the test data sets. (C. Combs)
Aid was given to Louie Grasso in converting Fortran code for reading McIDAS files to work with the new GOES 13 data files and with files from various sources. (C. Combs)
A new experimental version of the GOES Hail Probability Product is currently being generated and sent to the Storm Prediction Center for evaluation. It will be evaluated more formally as part of the 2011 Spring Experiment. Changes include adding the CIMSS Overshooting Tops algorithm as a predictor and switching to a new statistical scheme. (D. Lindsey)
Figure. Example of the GOES Hail Probability Product. The colors represent probability (%) of severe hail (>=1″ diameter) within 25 km of a point between 23 UTC on 29 March and 02 UTC on 30 March, 2011.
Continued work on the Gulfstream Project: The attached figure shows the 700 mb linear balance streamfunction and linear balance wind vectors which were computed using the February 2007 average temperature from runs of the COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) model. The winds are derived by first computing the geopotential field from the temperature observation assuming hydrostatic balance. The geopotential field is then used in the linear balance equation to get the streamfunction. Eventually the code will be expanded to include the solving of the omega equation associated with linear balance. This work is being done as part of a joint project with Dudley Chelton of CIOSS, in which the effect of the gulfstream on the tropopause is being explored. The COAMPS model calculations are being used as a check on the results of similar calculations of linear balance winds and omega using AMSU temperature profiles as input. (J. Dostalek)
700 mb linear balance streamfunction (x107 m2s-1) and linear balance wind vectors derived from the February 2007 average temperatures from the COAMPS model.
Some wintertime midlatitude cyclones display the classic “comma” pattern in satellite imagery. Others show a separation between the comma head and the clouds associated with the cold and the warm fronts (see images below). Work is being done with former CSU Master’s student Darren Van Cleave, now with the NSW in Rapid City, SD, on how to explain this difference. This quarter two new cases were saved on the local AWIPS, and HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) of NOAA’s Air Resources Laboratory is now being used for analyzing the trajectories of the principal airflows of the midlatitude cyclones being studied. (J. Dostalek)
Figure 1. Midlatitude cyclone with classic comma shape.
Figure 2. Midlatitude cyclone with comma head separated from clouds along the warm and cold fronts.
Simulated True-Color Imagery with Aerosols: Simulated-ABI true-color imagery has been created for an aerosol case provided by S. Kondragunta. That case is presented in the attached Figure. Some of the aerosols for this case can be seen in an animated version of this RGB/true-color image. However, the un-realistic coloring of the land surfaces in the image is being investigated. Using MODIS imagery for the same date and time, a comparison of the true-color images reveals strong biases in the components of the RGB image over land in particular. The source of the problem is suspected to be the surface/boundary that was used to create the RGB components of the simulated ABI data. An improved surface boundary might not only produce a more realistic true-color image, but might also help visualize the aerosols for this case study. (D. Hillger)
Figure: True-color (RGB) image created from simulated-ABI data provided by S. Kondragunta, for an aerosol case on 24 August 2006. Although hints of the embedded aerosols can be seen when animated, this image has land surface colors that are both un-characteristic for the western U.S. and unlike those captured by MODIS imagery for the same date and time.
True-color (RGB) Image Processing: D. Hillger and S. Miller resolved some of the remaining issues with the Green-LUT and Rayleigh-correction steps in the generation of true-color/RGB imagery from simulated ABI data. MODIS imagery was used for testing, since it contains a Green band, and a synthetic-Green band can be generated from the MODIS Red, Blue, and Near-IR bands, as would be done for GOES-R ABI. The order of the steps in the processing of RGB, with the Green-LUT before the Rayleigh-correction is currently producing the best results. Examples of Rayleigh-corrected images are presented in the top panels of the accompanying figure. The lower two panels use an additional log-enhancement, to create images that are typical of RGB products produced by NASA. As a measure of success, the mean difference between the reflectances in the Green and synthetic-Green components ranges from about 1% (for clouds, where the absolute reflectances are high) to about 5% (for land, where the absolute reflectances are much lower). (D. Hillger)
Figure: True-color (RGB) images from MODIS data on 24 August 2006 over Montana with heavy smoke from western wildfires: Left-side RGB images use actual MODIS Green band; right-side RGB images use a synthetic-Green band, as would be generated for ABI. Top images are Rayleigh-corrected; bottom images are Rayleigh-corrected and log enhanced, as would be typical of NASA true-color/RGB images.
Revised RGB Imagery: Several of the true-color/RGB cases used as examples or test cases were rerun with the updated Green LUT, Rayleigh-correction, and log- enhancement. The attached figure is a revised version of the true-color/RGB image created from WRF-simulated ABI data provided by CIMSS. This case was previously shown, but is now log-enhanced in addition to the Rayleigh-correction.
Figure: True-color (RGB) image created by the Green LUT process on WRF-simulated ABI data provided by CIMSS. Image is both Rayleigh-corrected and log-enhanced.
AWIPS Proving Ground: Installation instructions to add NSSL WRF-ARW data on to the AWIPS systems have been sent to Cheyenne and Rapid City Forecast offices, and the data is now flowing to both offices. (H. Gosden, D. Lindsey, L. Grasso, D. Molenar)
GOES-R Proving Ground: Data from the NSSL WRF-ARW is now being converted into AWIPS format and provided via LDM to the NWS Central Region. NWS offices in Boulder, Riverton, Pueblo, Cheyenne, and Rapid City are currently pulling in the data and displaying it on their AWIPS systems. Two GOES-R ABI bands are being provided to the NWS, from 12Z of Day 1 to 12Z of Day 2, hourly. The Boulder office has mentioned this product in their Area Forecast Discussions quite a few times already. We are providing this data, along with some additional bands and channel differences, to the SPC for the 2011 Spring Experiment in May and June 2011. (D. Lindsey, L. Grasso, H. Gosden, D. Molenar)
Figure. Example of how the simulated 6.95 µm band looks in AWIPS.
GOES-R Proposal: A proposal was accepted for funding by the GOES-R Risk Reduction program entitled “Convective Storm Forecasting 1-6 Hours Prior to Initiation.” It is a joint proposal with individuals from CIRA, CIMSS, Alabama-Huntsville, NSSL, and CREST. (D. Lindsey, L. Grasso)
Collaboration continues with M. Fromm (Naval Reseach Lab, Washington, DC) and folks from the Czech Hydrometeorological Institute studying fire-induced thuderstorms, or PyroCbs, including looking closely at the fires in Russia during the summer of 2010. (D. Lindsey)
D. Lindsey assisted in the contribution of a EUMETSAT Image of the Month on an intense pyrocumulonimbus event that occurred in Russia during their heat wave in summer 2010. It can be viewed here: http://oiswww.eumetsat.org/WEBOPS/iotm/iotm/20100804_pyrocb/20100804_pyrocb.html (D. Lindsey)
Training metrics for the quarter:
18 VISIT teletraining sessions have been delivered. There were 22 teletraining signups, 69 students participated.
Registrations: 293
Completions: 205
LMS totals from January 2005 through March 28, 2011:
Registrations: 5496
Completions: 3607
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 sessions:
The “Utilizing Synthetic Imagery from the NSSL 4 km WRF-ARW model in Forecasting Severe Thunderstorms” training session was delivered to the entire staff of the Storm Prediction Center (27 participants) in preparation for the upcoming severe weather season. This was accomplished via 5 teletraining sessions in February through early March. The feedback was primarily positive:
Ongoing development of new VISIT training sessions:
Research:
Collaboration:
J. Braun finished recent collaboration with the NWS Alaskan Region Environmental and Scientific Services Division (ESSD) as well as the NWS Alaskan Aviation Unit and NWS Center Weather Service Unit upon completion of the second of a two part series to be used in the VISIT and SHyMet programs titled “Volcanoes and Volcanic Ash. Volcanic Ash Part 2.”
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 29, 2011. 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 | 1564 | 6648 | 17791 | 23481 |
| 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 | 77 | 324 | 1051 | 1242 |
| 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 | 36 | 149 | 368 | 540 |
| 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 | 40 | 166 | 435 | 564 |
| AWIPS Cloud Height / Sounder | 11 | 55 | 128 | 178 |
| QuikSCAT winds | 10 | 37 | 107 | 110 |
| Convective Downbursts | 61 | 214 | 460 | 758 |
| DGEX | 27 | 215 | 562 | 785 |
| Severe Parameters | 16 | 136 | 324 | 431 |
| Winter Weather (Parts 1 AND 2) | 52 | 259 | 267 | 909 |
| 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 | 24 | 37 | 47 | 102 |
| Orographic Effects | 26 | 63 | 122 | 208 |
| NAM-WRF | 14 | 52 | 59 | 144 |
| Basic Satellite Principles | 21 | 34 | 61 | 83 |
| 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 | 20 | 33 | 34 | 95 |
| Utility of GOES for Severe Wx | 20 | 46 | 84 | 144 |
| NHC Track Models | 4 | 15 | 28 | 55 |
| NHC Intensity Models | 4 | 12 | 31 | 48 |
| Basic Sat Interp in the Tropics | 3 | 4 | 9 | 11 |
| POES and AVHRR in AWIPS | 6 | 10 | 13 | 112 |
| UW Convective Initiation Product | 11 | 18 | 34 | 64 |
| Water Vapor imagery for severe wx | 5 | 9 | 3 | 38 |
| UW Nearcasting product | 5 | 6 | 1 | 9 |
| Atmospheric Rivers | 2 | 7 | 26 | 26 |
| MIMIC TPW | 2 | 4 | 0 | 9 |
| Synthetic Severe | 6 | 2 | 0 | 28 |
Meetings and Calls
VISIT/SHyMet had conference calls on February 2 and March 7.
A member of the VISIT/SHyMet team from CIRA is now participating in the NWS Satellite Requirements and Solution Steering Team (SST) monthly teleconference meetings as a subject matter expert.
A member of the VISIT/SHyMet team from CIRA participates in the COMET monthly satellite call to keep informed of training efforts there. (Bikos, Braun)
New course debuted in March 2011: SHyMet Severe Thunderstorm Forecasting.
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:
31 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2011) for the SHyMet Severe Development Plan.
SHyMet Severe Thunderstorm – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Severe Thunderstorm individual class/session breakdown through March 30, 2011 (for “online” training only).
Tropical SHyMet training course. Began August 2010.
Consists of 7 courses: http://rammb.cira.colostate.edu/training/shymet/tropical_intro.asp
SHyMet Tropical Metrics: CIRA/VISIT Registered:
2 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2011) for the SHyMet Tropical Development Plan (13 total for August 2010 through Mar. 30, 2011) 1 Participants have completed the course this quarter, with 4 having completed since its inception.
SHyMet Tropical – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Tropical individual class/session breakdown through Mar. 30, 2011 (for “online” training only).
SHyMet For Forecasters training course: 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:
3 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2011) for the SHyMet Forecasters Course Development Plan (31total for January 2010 through Mar. 30, 2011) 1 Participants have completed the course this quarter, with 13 having completed since its inception.
3 Non-NOAA participants (International) have registered here at CIRA for the SHyMet Forecasters Course between January 2010 –Mar. 30, 2011, including 1 this quarter. There were no completions this quarter.
SHyMet For Forecasters – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Forecasters individual class/session breakdown through Mar. 30, 2011 (for “online” training only).
SHyMet Intern course (Development Plan)
The SHyMet Intern course continues to be offered online. It consists of 9 modules
(http://rammb.cira.colostate.edu/training/shymet/intern_intro.asp ).
SHyMet Intern Metrics: CIRA/VISIT Registered:
13 NOAA/NWS employees/participants have registered here at CIRA this quarter (Jan. – Mar. 2011) for the SHyMet Intern Course – 272 total for April 2006 through Mar. 30, 2011. 4 Participants completed the course this quarter for a total of 126 registered completions.
1 Non-NOAA participants (International) have registered here at CIRA this quarter for the SHyMet Intern Course. (33 total for April 2006 – Mar. 30, 2011) There were no completions this quarter.
SHyMet Intern – NOAA-Learning Management System (LMS) Registered:
Overall NOAA LMS – SHyMet Intern individual class/session breakdown through
Mar. 30, 2011 (for “online” training only).
ALL SHYMET: Total Registered through LMS since inception: 4351
Total Completed in LMS Since Inception: 2842
Progress on new SHyMet for Hydrologists training course:
As of the December 13 meeting, the SHyMet team out of Boulder has taken the lead in developing the content of the course. For content development, we will assist when requested. When the content has been developed, we will assist with the logistics of adding materials to the web and the LMS
New directions for SHyMet:
In light of the recent developments for SHyMet for Hydrologists, we will refocus efforts to look at training with a focus on Aviation Weather Hazards. (B. Connell, D. Bikos, J. Braun)
Training material on the pressure-wind relationships developed at CIRA/RAMMB and the Australian Bureau of Meteorology was provided to the organizers of the WMO International Workshop on Satellite Analysis of Tropical Cyclones. A. Burton (BoM) will present the training. A presentation of this training material will be constructed for the VISIT program in the next quarter. (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 (for January, February, and March 2010) through VISITview using GOES and POES satellite Imagery from CIRA (http://rammb.cira.colostate.edu/training/rmtc/focusgroup.asp ) and voice via Yahoo Messenger. There were participants from the U.S.: CIRA, NWS Training Division, the International Desk at NCEP, JOSS UCAR, as well as outside the U.S.: Antigua, Barbados, Bahamas, Bolivia, Colombia, Costa Rica, Dominican Republic, El Salvador, Guatemala, Guyana, Honduras, Panamá, and Venezuela. The participants include researchers and students as well as forecasters. The discussions were well attended with a peak of 53 participants during the January session. Francisco Argeñal, from the Meteorological Service in Honduras joined in with a group of 20 people that were attending an intermediate meteorology course. February’s session had 35 participants, and March’s session had 43 participants. M. Davison at NCEP International Desk led the discussions. During the sessions, participants provided comments on local and regional current weather phenomena. One of the topics of discussion in March was the circulation off the Brazilian coast near Rio de Janeiro. Everyone was encouraged to check on development of a warm core cyclone over the weekend. Participants were also engaged in detecting the location of the ITCZ from total precipitable water and cloud imagery. (B.Connell)
Figure: Screen grab during the January 2011 session of water vapor imagery over South America with annotation depicting conditions leading to heavy rains in southern Brazil.
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 new 2-week archive feature (thanks Kevin!): (http://rammb.cira.colostate.edu/ramsdis/online/rmtc.asp).
Look for information on our activities on the Regional Training Center web page. http://rammb.cira.colostate.edu/training/rmtc/ (B. Connell, D. Coleman, D. Watson,
K. Micke)
GOES-15 Sounder Noise Level Analysis: Using special data collected during the GOES-15 Science Test, which took place in August and September 2010, D. Hillger computed the noise levels for the 18 Sounder IR bands. The noise levels were computed on 32 hours of special limb-view Sounder data, from 4 through 6 September 2010. This type of analysis has been done for each GOES back to GOES-8, now a total of 8 satellites, showing a general trend toward lower noise as spacecraft bus and instrument improvements have been implemented. See the attached table for the grand summary of Sounder noise. (The Imager noise levels were reported in a previous weekly item.) In summary, the GOES-15 Sounder noise levels appear similar to those computed for previous GOES, and are well below the specifications (last column). Exceptions include some of the GOES-15 shortwave infrared bands (bands 13 through 15), where the noise levels appear to be close to specifications. The large noise values in noise for those bands is likely due to detector-to-detector striping that is quite apparent in some of the images. A separate analysis was done to determine the detector-to-detector striping for both the GOES-15 Imager and Sounder, the results of which are not shown here, but will appear in the NOAA Technical Report that is being compiled on the GOES-15 Science Test. (D. Hillger)
Table 1: Summary of the Noise for GOES-8 through GOES-15 Sounder Bands
(In radiance units; the Specification (SPEC) values are also listed).
| Sounder Band | Central Wavelength (μm) | GOES-15 | GOES-14 | GOES-13 | GOES-12 | GOES-11 | GOES-10 | GOES-9 | GOES-8 | SPEC |
| mW/(m2·sr·cm-1) | ||||||||||
| 1 | 14.71 | 0.23 | 0.29 | 0.32 | 0.77 | 0.67 | 0.71 | 1.16 | 1.76 | 0.66 |
| 2 | 14.37 | 0.21 | 0.24 | 0.25 | 0.61 | 0.51 | 0.51 | 0.80 | 1.21 | 0.58 |
| 3 | 14.06 | 0.22 | 0.21 | 0.23 | 0.45 | 0.37 | 0.41 | 0.56 | 0.98 | 0.54 |
| 4 | 13.64 | 0.17 | 0.16 | 0.18 | 0.39 | 0.36 | 0.41 | 0.46 | 0.74 | 0.45 |
| 5 | 13.37 | 0.15 | 0.15 | 0.18 | 0.34 | 0.34 | 0.36 | 0.45 | 0.68 | 0.44 |
| 6 | 12.66 | 0.068 | 0.073 | 0.095 | 0.14 | 0.17 | 0.16 | 0.19 | 0.32 | 0.25 |
| 7 | 12.02 | 0.046 | 0.053 | 0.086 | 0.11 | 0.11 | 0.09 | 0.13 | 0.20 | 0.16 |
| 8 | 11.03 | 0.057 | 0.076 | 0.10 | 0.11 | 0.14 | 0.12 | 0.09 | 0.13 | 0.16 |
| 9 | 9.71 | 0.067 | 0.068 | 0.11 | 0.14 | 0.13 | 0.10 | 0.11 | 0.16 | 0.33 |
| 10 | 7.43 | 0.037 | 0.039 | 0.081 | 0.099 | 0.09 | 0.07 | 0.08 | 0.08 | 0.16 |
| 11 | 7.02 | 0.024 | 0.025 | 0.046 | 0.059 | 0.06 | 0.04 | 0.05 | 0.07 | 0.12 |
| 12 | 6.51 | 0.030 | 0.029 | 0.063 | 0.11 | 0.11 | 0.07 | 0.09 | 0.11 | 0.15 |
| 13 | 4.57 | 0.014 | 0.0035 | 0.0061 | 0.0062 | 0.006 | 0.007 | 0.008 | 0.012 | 0.013 |
| 14 | 4.52 | 0.016 | 0.0035 | 0.0064 | 0.0062 | 0.007 | 0.005 | 0.007 | 0.010 | 0.013 |
| 15 | 4.46 | 0.015 | 0.0033 | 0.0055 | 0.0066 | 0.006 | 0.005 | 0.006 | 0.009 | 0.013 |
| 16 | 4.13 | 0.0082 | 0.0019 | 0.0030 | 0.0024 | 0.003 | 0.003 | 0.003 | 0.004 | 0.008 |
| 17 | 3.98 | 0.0055 | 0.0016 | 0.0026 | 0.0022 | 0.003 | 0.002 | 0.003 | 0.004 | 0.008 |
| 18 | 3.74 | 0.0019 | 0.00074 | 0.0011 | 0.00094 | 0.001 | 0.001 | 0.001 | 0.002 | 0.004 |
NAS Device: Three more NAS devices has been procured and configured for various projects. (H. Gosden)
Published:
Brennan, M.J., D.P Brown, and M. DeMaria, 2011: Verification of National Weather Service tropical cyclone intensity probabilities and future plans. Connell, B.H., D. Bikos, J. Braun, A. S. Bachmeier, S. S. Lindstrom, A. Mostek, M. DeMaria, and T. J. Schmit, 2011: Training for GOES-R directed towards forecasters. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems, 23-27 January, Seattle, WA.
Connell, B.H., and L. Veeck, 2011: New forecaster training paradigm for GOES-R? AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
DeMaria, M., J.A Knaff, M J. Brennan, J.L. Beven, R T. DeMaria, A B. Schumacher, J. Kaplan, and N.W.S. Demetriades, 2011: Tropical cyclone rapid intensity change forecasting using lightning data during the 2010 GOES-R Proving Ground at the National Hurricane Center. AMS Fifth Conference on the Meteorological Applications of Lightning Data, 23-27 January, Seattle, WA.
Gurka, J.J., S.J. Goodman, T.J. Schmit, A. Mostek, S.D. Miller, A.S. Bachmeier, M. DeMaria, and B. Reed, 2011: GOES-R proving ground: plans for 2011 and beyond.AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Hamill, T., B. Brown, M. DeMaria, Z. Toth, R.L. Gall, and E. Rappaport, 2011: New ensemble-based products for tropical cyclones. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Hansen, J., C. R. Sampson, P. A. Wittmann, M. DeMaria, and J.A. Knaff, 2011: Covarying TC-forced wind speed/wave height probabilities. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Hillger, D.W., L.D. Grasso, R.L. Brummer, R.T. DeMaria, 2011: GOES-R ABI true-color capability. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Musgrave, K.D., M. DeMaria, B.D. McNoldy, and R.T. DeMaria, 2011: On the display of tropical cyclone model ensemble structure information. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA. Reed, B., C. W. Siewert, R. S. Schneider, G. L. Hufford, B. Entwhistle, M. DeMaria, D. Reynolds, and M.J. Brennan, 2011: GOES-R Proving Ground—Demonstrating GOES-R products in 2010. AMS 24th Conference on Weather and Forecasting/20th Conference on Numerical Weather Prediction, 23-27 January, Seattle, WA.
Schumacher, A.B., M. DeMaria, J.A. Knaff, L. Zhao, and T. Schott, 2011. NPP Microwave Sounder-Based Tropical Cyclone Products. 65th Interdepartmental Hurricane Conference, 28 Feb – 3 Mar, Miami, FL.
Szoke,E.J., R.L. Brummer, H. Gosden, S.D. Miller, M. DeMaria, and D.A. Molenar, 2011: An overview of CIRA’s contribution to the GOES-R Proving Ground. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Doesken, N.J., J.F. Weaver, and M. Osecky, 2011: Microscale aspects of rainfall patterns as measured by a local volunteer network. National Weather Digest.
Grasso, L.D., and D.T. Lindsey, 2011: An Example of the use of Synthetic 3.9 µm GOES-12 Imagery for Two-Moment Microphysical Evaluation. International Journal of Remote Sensing. (In press)
Hillger, D.W., L.D. Grasso, S. Miller, R. Brummer, R. DeMaria, 2011: Synthetic Advanced Baseline Imager (ABI) True-Color Imagery. Journal of Applied Remote Sensing (SPIE).
Jankov I., L.D. Grasso, M. Sengupta, P.J. Neiman, D. Zupanski, M. Zupanski, D.T. Lindsey, and R.L. Brummer, 2011: An Evaluation of Five WRF-ARW Microphysics Schemes Using Synthetic GOES Imagery for an Atmospheric River Event Affecting the California Coast. Journal of Hydrometeorology. In Press.
Knaff, J.A., and M. DeMaria, 2011: A deterministic rapid intensification aid. Wea. and Forecasting
Knaff, J.A., M. DeMaria, D.A. Molenar, C.R. Sampson and M.G. Seybold, 2011: An automated, objective, multi-satellite platform tropical cyclone surface wind analysis. J. of Applied Meteorology and Climatology.
Knaff, J.A., P. J. Fitzpatrick, C.R. Sampson, Y. Jin, and C.M. Hill, 2011:Simple Diagnosis of Tropical Cyclone Structure via Pressure Gradients. Weather and Forecasting.
Sampson, C.R., J. Kaplan, J.A. Knaff, M. DeMaria, and C. Sisko, 2011: A deterministic rapid intensification aid. Weather and Forecasting.
Setvak, M., D.T. Lindsey, R.M. Rabin, P.K. Wang, and A. Demeterova, 2011: Possible moisture plume above a deep convective storm on 28 June 2005 in MSG-1 imagery. Weather Review .
Setvák, M., M. Radová, P. Novák, D.T. Lindsey, L. Grasso, P. K. Wang, Shih-Hao Su, R. M. Rabin, J. Kerkmann, J. Šťástka, Z. Charvát, and H. Kyznarová, 2011: Convective storms with a cold-ring shaped cloud top feature. Atmos. Research.
Zupanski, D., M. Zupanski, L. Grasso, R. Brummer, I. Jankov, D. Lindsey, M. Sengupta and M. DeMaria, 2011: Assimilating synthetic GOES-R radiances in cloudy conditions using an ensemble-based method. International Journal of Remote Sensing. In Press.
Goni, G.J., J.A. Knaff, and I-I Lin, 2011: TC heat potential (TCHP) [in “State of the Climate in 2010”]. Bull. Amer. Meteor. Soc.
Grasso, L.D., D.W. Hillger, M. Sengupta, 2011: Demonstrating the Utility of the GOES-R 2.25 µm band for Fire Retrieval. Geophysical Research Letters.
Lazzara, M.A., S.A. Ackerman, and D.W. Hillger, 2011: Detecting Fog over Antarctia from Satellite. Journal of Applied Meteorology and Climatology.
Lindsey, D.T., B. McNoldy, Z. Finch, D. Henderson, D. Lerach, R. Seigel, J. Steinweg-Woods, E. Stuckmeyer, G. Williams, D. Van Cleave, and M. Woloszyn, 2011: A High Wind Statistical Prediction Model for the Northern Front Range of Colorado.. Electronic Journal of Operational Meteorology.
Miller, S., C. Schmidt, T. Schmit, and D.W. Hillger, 2011: A Case for Natural Colour Imagery from Geostationary Satellites, and an Approximation for the GOES-R ABI. International Journal of Remote Sensing.
Van Cleave, D., J.F. Dostalek, and T. Vonder Haar, 2011: The Dynamics and Snowfall Characteristics of Three Types of Extratropical Cyclone Comma Heads Categorized by Infrared Satellite Imagery. Weather and Forecasting.
Paper to be highlighted in BAMS: A soon-to-be published manuscript (in Weather and Forecasting, April 2011) has been selected to be highlighted in the April issue of the Bulletin of the American Meteorological Society. The paper discusses a technique to use the SHIPS Rapid Intensification Index developed at CIRA/RAMMB and HRD, a probabilistic forecast method, as a potential member in the tropical cyclone intensity consensus forecast used at the National Hurricane Center. The paper is a collaborative effort involving J. Knaff, M. DeMaria, B. Sampson, and J. Kaplan.
EUMETSAT Image of the Month: D. Lindsey assisted in the contribution of a EUMETSAT Image of the Month on an intense pyrocumulonimbus event that occurred in Russia during their heat wave in summer 2010. It can be viewed here: http://oiswww.eumetsat.org/WEBOPS/iotm/iotm/20100804_pyrocb/20100804_pyrocb.html
Beven, J., M. Brennan, M. DeMaria, J.A. Knaff, C. Velden, and J. Dunion, 2011: The 2010 GOES-R Proving Ground at the National Hurricane Center. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
DeMaria, M., 2011: Advanced Applications of the Monte Carlo Wind Probability Program: A Year 2 Joint Hurricane Testbed (JHT) Project Update. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
DeMaria, M., 2011: Improving Tropical Cyclone Intensity Forecast Models with Theoretically-Based Statistical Models. NOPP Review, 24 February, Miami, FL.
DeMaria, M., 2011: Tropical Cyclone Rapid Intensity Change Forecasting Using Lightning Data During the 2010 GOES-R Proving Ground at the National Hurricane Center. AMS Meteorological Applications of Lightning Data Conference. 23-27 January, Seattle, WA.
Gosden, H., 2011: CIRA Proving Ground Product Data Dissemination and Display at National Weather Service Forecast Offices. March, CIRA, Fort Collins, CO.
Kaplan, J., J. Cione, M. DeMaria, J.A. Knaff, J. Dunion, J. Solbrig, J. Hawkins, T. Lee, E. Kalina, J. Zhang, J. Dostalek, and P. Leighton, 2011: Enhancements to the SHIPS Rapid
Intensification Index. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
Knaff, J.A., M. DeMaria, J. Kaplan, C.M. Rozoff, J. Kossin, and C.S. Velden, 2011: Improvements to statistical intensity forecasts. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
Rozoff, C.M., J. Kossin, C. Velden, A. Wimmers, M. Kieper, J. Kaplan, J.A. Knaff, and M.DeMaria, 2011: Improvements in the Statistical Prediction
of Tropical Cyclone Rapid Intensification. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
Sampson, C.R., A. Schrader, E. Serra, P. Wittmann, H. Tolman, C. Sisko, C. Lauer, J. Schauer, J.A. Knaff, M. DeMaria, and A.Schumacher, 2011: ATCF Requirements, Intensity Consensus
and Sea Heights Consistent with NHC Forecasts. 65th Interdepartmental Hurricane Conference, 28 February – 3 March, Miami, FL.
Pre American Meteorological Society Dry Run Poster Presentations: D. Hillger and J. Knaff participated in a teleconference/seminar, presenting one-page slides of posters to be presented at the AMS Annual Meeting in Seattle WA the last week of January 2011. Hillger presented slides on “GOES-R ABI True-Color Capability” and “NOAA Science Test results from the GOES-14 and 15 Imager and Sounder,” J. Knaff presented a slide on “Tropical Cyclone Rapid Intensity Change Forecasting Using Lightning Data during the 2010 GOES-R Proving Ground at the National Hurricane Center.”
CIRA-Intro-Jamboree Seminar: D. Lindsey, D. Hillger, and J. Knaff of the RAMM Branch were three of the 7 speakers providing brief synopses of their work at a group seminar held 24 February 2011 at the CSU Department of Atmospheric Science. These talks were modeled after similar brief introductions/talks by Department faculty. It is a way to introduce the speakers and their research areas to the large number of students and other researchers in the many different components of the Atmospheric Science and CIRA campus.
Figure 1: CIRA Intro-Jamboree flier, listing all the speakers/presenters, including three from the RAMM Branch.
Posters:
Hillger, D.W., 2011: GOES-R ABI True-Color Capability. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.
Hillger, D.W., 2011: NOAA Science Test results from the GOES-14 and 15 Imager and Sounder. AMS Seventh Annual Symposium on Future Operational Environmental Satellite Systems. 23-27 January, Seattle, WA.Kate D. Musgrave, CIRA/Colorado State Univ., Fort Collins, CO; and M. DeMaria, B. D. McNoldy, and R. T. DeMaria On the display of tropical cyclone model ensemble structure information
Schumacher, A., S.M. Quiring, 2011: A Methodology for Incorporating Hurricane Forecast Errors into Decision-Support Systems for Energy and Utility Companies.
| Traveler Destination Purpose Funding Dates |
| M. DeMaria | Seattle, WA | AMS Annual Meeting | GOES-R3 | 23-27 January |
| B. Connell | Seattle, WA | AMS Annual Meeting | SHyMet | 23-27 January |
| K. Musgrave | Seattle, WA | AMS Annual Meeting | HFIP | 23-27 January |
| D. Hillger | Seattle, WA | AMS Annual Meeting | GOES-R3 | 23-27 January |
| L. Grasso | Norman, OK | High Impact Weather Workshop | GOES-R3 | 23-25 February |
| M. DeMaria | Miami, FL | NOPP Review | GOES-R3 | 24-26 February |
| M. DeMaria | Miami, FL | 65th Interdepartmental Hurricane Conference | GOES-R3 | 28 February to 3 March |
| J. Knaff | Miami, FL | 65th Interdepartmental Hurricane Conference | GIMPAP | 28 February to 3 March |
| A. Schumacher | Miami, FL | 65th Interdepartmental Hurricane Conference | PSDI-TC | 28 February to 3 March |
| L. Grasso | Boise, ID | IMET Workshop | GOES-R3 | 19-25 March |
Kathy-Ann Caesar, with the Caribbean Institute of Meteorology and Hydrology (CIMH), visited CIRA on Wednesday, 30 March. CIMH is one of the WMO designated Regional Meteorological Training Centers of Excellence (RMTCoE). Ms. Caesar also is a current Co-Chair of the WMO Virtual Laboratory Management Group. We reviewed developments for the Virtual International Focus Group briefings as well as collaborations on materials and content for a forecaster aviation course.(B. Connell)
Steve Goodman from the GOES-R Program Office visited CIRA and RAMMB on March 9th. An informal meeting was held with most of RAMMB and overviews of GOES-R Risk Reduction and Proving Ground projects were discussed. Each PI provided one or two slides on their topics to focus the discussion. Feedback was very positive. (M. DeMaria)
Michael Fiorino from the NOAA Earth Systems Research Laboratory in Boulder visited CIRA on Feb. 10th to discuss a joint project on hurricane intensity forecasting. (J. Knaff, M. DeMaria, K. Musgrave, B. McNoldy)
Prof. Shaima Nasiri visited CIRA and the CSU Atmospheric Science Department from Texas A&M University. She met with a number of RAMMB and CIRA employees and gave the weekly ATMOS seminar. Her research interests include detecting cloud phase using AIRS data, and some areas for potential collaboration were identified. (S. Miller, D. Lindsey)
Michael Foley and Andrew Donaldson from the BoM visited CIRA for two days to discuss adapting the operational tropical cyclone wind speed probability program developed by RAMMB for the National Hurricane Center to the Australian region. The code was modified to run in the southern hemisphere and to utilize the error distributions from their operational forecasts. Applications to provide objective guidance on hurricane watches and warnings and to generate landfall probability products were also discussed. (M. DeMaria, J. Knaff, A. Schumacher, K. Musgrave, R. DeMaria)
D. Hillger reviewed a manuscript on sea fog formation and dissipation for Pure and Applied Geophysics. The review was done well before the review deadline.
Mid-Year Review Meetings Completed with RAMMB Staff: Meetings were held with all RAMMB staff to review the progress on their performance plans. Dates of the meetings were provided to G. Taylor. (M. DeMaria)
H. Gosden will partake in the upcoming Linux Systems Administration training through Red Hat on April 18-22.
M. DeMaria participated in the Hiring Reform Training for Managers Webinar on Thursday, March 24th.
M. DeMaria visited the CSU Computer Science Department to discuss meteorological datasets that might be useful for analysis in undergraduate and graduate student projects. Two graduate students were interested in applying machine learning techniques to tropical cyclone datasets from CIRA. These include the problem of estimating tropical cyclone intensity and structure from infrared satellite imagery, and the automated recognition of tropical cyclone circulations in global model forecasts. Several Computer Science faculty members have experience in applying artificial intelligence techniques to analysis photographs, and these will be applied to the wind structure analysis of infrared imagery. For example, one student has developed a method of identifying bird species from digital photos of feathers using advanced machine learning techniques. It will be interesting to see if new ideas come from this outside perspective.
M. DeMaria participated in a conference call of the OFCM tropical cyclone research committee to discuss the current task of reviewing all U.S. tropical cyclone research activities, including NOAA, NASA, the National Science Foundation and the Office of Naval Research. This group provides bi-annual research summaries, which are used to identify research gaps and set national priorities.
Virtual Meeting of the WMO Virtual Laboratory Management Group: CIRA and the NWS Training Division participated in a virtual meeting of the VLMG on 14 March 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 meeting topics included organization of an Aviation events week, qualifications, classifications, and competencies of meteorologists, updates to the guide for running VLab training events, as well as widening the scope of the VLab. The next virtual meeting is scheduled for mid- July 2011. (B. Connell)