Regional and Mesoscale Meteorology Branch

VIIRS Tropical Cyclones Storm-Relative Real-Time Imagery: Two storm-relative Visible Infrared Imaging Radiometer Suite (VIIRS) products created for tropical cyclones.  VIIRS data are collected for each SNPP pass over tropical cyclone center. Each image is centered at the storm center interpolated from latest available ATCF data, and shows 6 by 6 latitude/longitude degrees box around the center. The first product, the Enhanced Infrared (IR) VIIRS, displays storm relative imagery for VIIRS longwave IR band M15 (750 m resolution at nadir), remapped to a Mercator  projection. The image is color enhanced to emphasize the coldest temperature/highest clouds. The second product, Day/Night Visible Imagery VIIRS, displays storm-relative loop composed of two VIIRS bands.  For the day-time images it uses the high resolution visible band (I01, 375 m resolution at nadir). For the night images it uses the unique VIIRS Day Night Band (DNB, 742 m resolution across the swath). Both images are remapped to Mercator  projection. Both products are available in real time on RAMMB/CIRA TC Real-Time web page http://rammb.cira.colostate.edu/products/tc_realtime/. (G. Chirokova, J. Knaff, K. Micke, S. Finley, R. DeMaria)

Figure 1.  VIIRS real-time tropical cyclones storm-relative imagery. Left panel: Day/Night Visible Imagery, showing high-resolution visible VIIRS band IO1 for daytime image and DNB VIIRS band for nighttime image. Right panel: Enhanced Infrared (IR)VIIRS imagery, band M15. The latest images for both products are from 19 Mar, 2014, 05:43UTC. 

NOAA/NESDIS/PSDI/NDE/S-NPP Tropical Cyclone Algorithm: One major release and four upgrade releases (NPP_TC v1.2.3, 1.3.0-3) were developed, tested and migrated to the NDE development and test servers along with an additional 12 ATMS test cases. Release highlights include a python netCDF output conversion and a Process Control File data input validation program. The S-NPP TC Products algorithm has very little opportunity for real-time testing due to the take down and rebuilding of the test system (TEST) in late March.  TEST is expected to be back up in May or June 2014.  The S-NPP TC Products will be tested in real-time at that time and will be briefed to the SPSRB shortly thereafter (est. June 2014).  Users at NHC have indicated this delay will not impact use of the product on their end as long as it is operational by July 2014. (S. Longmore, A. Schumacher, J. Dostalek)

NOAA/NESDIS/PSDI/AMSU Tropical Cyclone Algorithm: Two upgrade releases (AMSU_TC v1.1.0, v.1.1.1) were developed, tested and migrated to the NESDIS tropics server for testing. Release highlights include an upgrade of the AMSU_TC scripts to the latest versions used in NPP_TC, python netCDF output conversion and data input (ATCF, GFS, and AMSU) retrieval programs. (S. Longmore, J. Dostalek)

Multi-satellite-platform Tropical Cyclone Surface Wind Analysis (MTCSWA) V2.0:  The MTCSWA has been running since 2011 in NESDIS operations.  Since that time several aspects of the system have been revisited including how the IR-based flight-level wind proxies are created, how the analysis winds (done at 700 or 850 hPa) is reduced to the surface, and surface inflow angle representation.  The IR-based aircraft wind proxy now uses an algorithm that accounts for the 2-dimensional IR image and was developed using a higher-resolution aircraft-based wind analysis.  That work is being prepared for publication.  The flight-level to surface wind reductions are based on methods developed at NHC and leverage a recently finished Joint Hurricane Testbed project to automate aircraft-based wind analyses in NHC operations (approval pending).  The inflow angles are adopted from a parameterization developed at AOML (Zhang and Uhlhorn 2012) and is based on GPS dropsondes.  The new V2.0 analyses are being tested in the CIRA environment and being disseminated via the TC-realtime web page.  The resulting analyses generally have larger and more physically-based wind asymmetries and provide better estimates of winds at radii beyond 300 km of the TC center.  The MTCSWA (V1.0 and V2.0) for Tropical Cyclone Ian are provided below in Figure 1. The top panel shows how the IR and large-scale analyses compare, and the bottom panel compares the current MTCSWA with MTCSWA V2.0. We wish to seek funding for operational transition in FY2014 or 2015. (J. Knaff)

Figure 1:  MTCSWAs for Tropical Cyclone Ian (SE Pacific) valid 12 UTC 9 January 2014.  Scaled IR image and MTCSWA V2.0 (top panels) and a comparison of MTCSWA V1.0 (bottom left) and MTCSWA V2.0 at smaller scales (bottom right).

Updgrading Tropical Cyclone Products at NESDIS: Collaboration with NESDIS employees at the Office of Satellite and Product Operations (OSPO) and with the NPP Data Exploitation (NDE) program has continued in order to prepare for the operational implementation of the processing of tropical cyclone analysis products from the Advanced Microwave Sounding Unit (AMSU) and from the Advanced Technology Microwave Sounder (ATMS).  OSPO has processed AMSU data for tropical cyclone analysis for many years, but the temperature soundings come from a statistical technique that is over 10 years old.  AMSU temperature and moisture retrievals are now being produced by the Microwave Integrated Retrieval System (MIRS) algorithm, and thus an update of the code implementing the processing is necessary.  Also, with the launch of Suomi-NPP, data from the ATMS will be available for operational use.  For this project, code similar to the set sent to OSPO was sent to NDE for implementation.  Emails and telephone calls have continued as adjustments to the suite of programs are being made at both OSPO and NDE. (J. Dostalek)

AMSU Temperature Retrievals in Tropical Cyclones: The RAMM Branch creates tropical cyclone products which use winds computed from temperature profiles generated from microwave satellite retrievals from the Advanced Microwave Sounding Unit (AMSU).  Up to this point a statistical retrieval scheme over 10 years old has been used.  In preparation for switching the retrieval scheme to NESDIS’ current operational algorithm, the 1DVAR Microwave Integrated Retrieval System (MIRS), a comparison of the two techniques is being performed.  Data from Hurricanes Ernesto, Isaac, and Sandy of the 2012 Atlantic season were used to compare the two techniques, using collocated dropsondes as ground truth.  Figure 1 presents the results of the temperature profile comparison.  The retrievals are within 50 km and 1 hour of the dropsondes, and the number of collocations at each level is noted on the right-hand side of the figure.  Both algorithms show a bias of less than 2 K in magnitude, with the MIRS algorithm showing a generally smaller bias, except at 1000 hPa and at the upper two levels.  The root mean square error (rmse) for both algorithms is around 2 K, with higher values near the surface.  The rmse of the MIRS retrieval is equal to or better than the statistical retrieval, except at 700 hPa and 600 hPa.  For this comparison, an available low-level temperature correction was not applied to the statistical technique, likely resulting in the maximum rmse seen at 850 hPa and 925 hPa.  Work on this project is ongoing.  In particular, research into how these temperature differences affect the quality of the tropical cyclone wind field products is underway. (J. Dostalek)

Figure 1. Bias (dashed) and root mean square error (solid) of the statistical AMSU retrieval technique (red) and the AMSU MIRS (green). 
The number of collocations (within 50 km and 1 hour) at each level for each retrieval technique is given on the right.

Fixes for AMSU Data Issue:  Many tropical cyclone products developed at CIRA which run operationally at NCEP rely on AMSU brightness temperatures.  These brightness temperatures are converted from their original BUFR format to a text format for further processing.  It was discovered that occasionally extra data was getting through the BUFR conversion step and into the subsequent processing.  Figure 2 presents the problem.  The left panel shows the correct input data for the NOAA-18, 12 UTC analysis of 21 November 2013 over Tropical Storm Melissa — two descending passes.  The right panel shows the incorrect data — the two NOAA-18 passes seen on the left, with the addition of brightness temperatures from an ascending NOAA-18 pass, and data from MetOp-B.  In collaboration with the NOAA staff at the National Hurricane Center and the Office of Science and Technology, the sources of the two problems were determined last quarter.  Fixes for the two problems have now been delivered to the National Hurricane Center for implementation.  (J. Dostalek)

Figure 2.  NOAA-18 data locations over Tropical Storm Melissa for 12 UTC 21 November 2013.  Left: correct data input consisting of two descending passes.  Right: input data with additional, unwanted brightness temperatures from NOAA-18 and MetOp-B.  The location of Tropical Storm Melissa is given by the red asterisk.

A time-integrated parameter using Goerss Predicted Consensus Error (GPCE) information from the Monte Carlo wind speed probability model has been developed as part of a project supported by the Joint Hurricane Testbed.  This parameter is an average of the normalized GPCE values from the 12h – 120h forecasts, and represents the average uncertainty of a 12h – 120h tropical cyclone track forecast.  When the time-integrated GPCE parameter is split into 3 terciles (low, normal, high), it was found that the corresponding integrated forecast error distributions for the low (high) GPCE tercile have smaller (larger) standard deviations (Figure below).  This result suggests that lower (higher) time-integrated GPCE values are related to smaller (larger) forecast uncertainty.  This information will provide forecasters with a 3-category measure of confidence of track forecast that may be relayed to users in the forecast discussion product or used to modify the cone of uncertainty.  Although this initial version of the time-integrated GPCE parameter already shows promise, further testing will be done to determine if differential weighting of GPCE at different forecast times yields better separation of forecast errors.  (A. Schumacher, M. DeMaria)

Figure.  Time-integrated forecast error frequency for the lowest (IGPCE_LOW), middle (IGPCE_MED) and highest (IGPCE_HIGH) time-integrated GPCE parameter values for 2013 NHC Atlantic tropical cyclone forecasts.

HWRF Synthetic IR Imagery: HWRF synthetic satellite infrared brightness temperatures  (Figure 3) on the innermost (3 km) nest is being collected to support both HFIP and GOES-R research and for the comparison between HWRF results and GOES-13 observations. (J. Knaff, K. Musgrave, L. Grasso)

Figure 1. HWRF synthetic IR channel 4 brightness temperatures of Hurricane Humberto from run initialized 0000 UTC 11 September 2013,
displaying the 48 hour forecast.  Left panel shows combined domain on 9 km grid, right panel shows innermost nest on 3 km grid.

NCAR/NOAA/CSU Tropical Cyclone Workshop:  Another semi-yearly TC workshop was held 8 January 2014 at NCAR in Boulder.  These workshops provide an opportunity for TC researchers at NOAA labs, CIRA, CSU and NCAR to share details of their present work and have been occurring for approximately 5 years.  An agenda from the last meeting is shown below. (J. Knaff)

MTCSWA data for West Pacific shared:  Multi-platform Tropical Cyclone Surface Wind Analyses (MTCSWA) for western North Pacific TCs, 2007-2013 were shared with L. Wu, Professor/Associate Dean of Atmospheric Science at Nanjing University of Information Science and Technology (NUIST) and the director of Pacific Typhoon Research Center (PTRC).  He is using these to “examine the interaction between typhoons and the environment (e.g., monsoon gyres).” (J. Knaff)

Images provided to JTWC:  Storm-relative water vapor images of Tropical Cyclone Ian (SH07, 2014) were provided to the Joint Typhoon Warning Center for training on interaction of TCs subtle upper level features and their usefulness for forecasting rapid intensity changes. This interaction has since led to JTWC using different water vapor enhancement curves (i.e., those developed here at CIRA). (J. Knaff)

Potential to work with NRLMRY:  Meetings were held  to discuss a collaboration opportunity with NRLMRY.  NRLMRY under US Air Force funding is developing an SSMI/S surface wind product as WindSat Risk Reduction.  The current product, however, does not produce wind vectors in the vicinity of tropical cyclones.  CIRA/RAMMB can help by using existing code to estimate the 2-D winds using SSMI/S sounder retrievals (MIRS) and solving the non-linear balance.  The level of funding/effort has been communicated with NRLMRY. (J. Knaff)

HFIP Annual Meeting: K. Musgrave traveled to College Park, MD for the Hurricane Forecast Improvement Program (HFIP) Annual Meeting 19-20 February 2014.  The meeting addressed the strategic plan for the next five years of HFIP, with several follow-on teleconferences already planned to expand on areas discussed.  (K. Musgrave)

The Monte Carlo wind speed probability model rerun: The Monte Carlo wind speed probability model was rerun for 3 Hurricane Isaac (2012) advisories and delivered the realization data files to M. Brennan at the NHC for use in a FEMA training course. (A. Schumacher, M. DeMaria)

The Monte Carlo wind speed probability model rerun: The Monte Carlo wind speed probability model was rerun for 2 sample tropical cyclone advisories and delivered data files to P. Santos at NWS Miami for use in training. (A. Schumacher, M. DeMaria)

Probabilistic Forecasting of Severe Convection: D. Lindsey is working with researchers from CIMSS on a project to develop an automated system using data from GOES, NEXRAD, and model output to provide probabilities that individual storms will reach severe limits.  Our role is to use statistical methods to determine which near storm environmental predictors provide the best a priori estimate for severe storm probabilitity.  This is a GIMPAP-funded project. (D. Lindsey)

Cross Sections to Complement Synthetic Imagery:  Vertical cross sections of potential temperature and vertical velocity are now available for viewing on RAMSDIS online under “GOES-R Proving Ground.”  The hourly forecasts are valid at 9-36 hours from the 00 UTC run of the 4 km NSSL WRF.  These times match the loops of the GOES-R synthetic imagery displayed on the same page, so the atmospheric structure displayed in the cross section can be compared to the associated synthetic satellite image loops.  The location of the cross section is displayed in the upper-left corner of the image, and will be placed in areas of interest such as across fronts or waves in the lee of topography.  An example image is given below — the 24 hour forecast of the 00 UTC 27 February 2014 run of the 4 km NSSL WRF (Figure 3).  A notable feature is the packing of the potential temperature lines (black) near the surface at the northern portion of the cross section.  This feature is the edge of a cold air mass forecast to be over the Great Lakes.  The blue contours show vertical velocity, with upward vertical motion in the solid contours and the downward vertical motion in the dashed contours. (J. Dostalek)

Figure 3. Vertical cross section along line shown in upper left corner.  Black contours are potential temperature and blue contours are vertical velocity, with upward motion solid and downward motion dashed.  The values are from the 24-hour forecast of the 00 UTC run of the 4 km NSSL-WRF.

ORI Product Validation: The Orographic Rain Index (ORI) product is being validated with the objective of including this information in a paper for publication as well as a conference presentation in the summer.  Data was collected for several cases across more than 40 sites in California for total of 170 times series (5362 observations of ORI vs precip).  The Pearson product-moment correlation coefficient (R) was calculated for each time series to assess how well the ORI data (average value within 15 km of the precipitation site) correlates with precipitation.  A histogram of each time series binned by R values (Fig. 1)

Figure 1. Histogram of R values for each time series of ORI vs precipitation.

shows the majority of events have a R value greater than 0.5, and the average R value for all events is 0.57.  This supports the hypothesis that utilizing ORI for atmospheric river events in California does demonstrate utility in forecasting orographic enhancement of precipitation.  Next, we will analyze gage height data from rivers to assess ORI, we expect this to be more representative of rainfall occuring over complex terrain since it is more of an areal measurement than a point observation that is typically not located on the highest local terrain.  (D. Bikos)

Joint VIIRS Imagery/Arctic Applications Blog Posts Capture Major Glacial Calving Event in Antarctica:  To demonstrate the quality and utility of VIIRS Near Constant Contrast (NCC) imagery, NCC images of the Pine Island Glacier in Antarctica were collected over a period of 50 days from 7 November to 26 December 2013. During this time period, the iceberg known as B-31 calved from Pine Island Glacier. Iceberg B-31 has been estimated to have a size nearly equal to the land area of Singapore (~700 km2). Animations of NCC imagery over this period have been produced that show in detail the calving of B-31 and the breakup of the Antarctic ice sheet to the west of Pine Island Bay. Example images are shown in the figure below. The advantages of using visible wavelength information over infrared information to detect sea ice both day and night is discussed. NCC imagery, the Imagery EDR product produced from the VIIRS Day/Night Band, offers the ability to detect sea ice even at night in the presence of optically thin clouds, which is difficult or impossible to do using only infrared imagery. Additional imagery (including the full 50 day animation video) may be found on the JPSS Imagery and Visualization Team Blog at http://rammb.cira.colostate.edu/projects/npp/blog/index.php/uncategorized/b-31-and-the-pine-island-glacier/ or on the Seeing the Light: VIIRS in the Arctic Blog at http://rammb.cira.colostate.edu/projects/alaska/blog/?p=96  (C. Seaman)

Figure: VIIRS Near Constant Contrast images of Pine Island Bay and the Pine Island Glacier, Antarctica. The 7 November image (left) shows the crack where the B-31 iceberg is beginning to calve from the glacier in the lower right corner of the bay. The image from 18 November (right) shows the B-31 iceberg after the calving event, which occurred on or about 11 November 2013.

GRAVITE User Guide Feedback:  D. Hillger provided technical feedback on a User Guide for the Government Resources for Algorithm Verification, Independent Testing and Evaluation (GRAVITE) system for the JPSS Ground Project.  The User Guide will be formalized as a NASA document.  (D. Hillger)

Additions to VIIRS Direct Broadcast Imagery Display:  New VIIRS imagery and imagery products have been added to the VIIRS imagery displayed online over CONUS at http://rammb.cira.colostate.edu/ramsdis/online/npp_viirs.asp. The three new products are the remapped longwave and shortwave IR bands of VIIRS and a combination product of those two bands called the Shortwave Albedo.  The Shortwave Albedo is a shortwave and longwave band combination that subtracts the emissive component from the shortwave band by using the longwave band, creating a reflective-only shortwave component product.  This product is an indication of the reflective properties of land and cloud surfaces, often used to detect low/stratus clouds and fog.  The SW Albedo is a product that has been in long term use with GOES imagery.  The figure below shows a composite of direct broadcast imagery over CONUS.  Such images are available twice daily.  More VIIRS images and products will be created displayed in the future.  All of these are being used in VIIRS imagery validation efforts.  (D. Hillger, K. Micke)

Figure 1: Composite of direct-broadcast Shortwave Albedo imagery produced from VIIRS Imagery captured from the University of Wisconsin and displayed on CIRA’s “Suomi NPP VIIRS Online”.  Low clouds and fog are white, middle-level clouds are darker, and the highest/coldest clouds are color enhanced from the longwave IR band.

Additional VIIRS Direct Broadcast Imagery Display:  Another new VIIRS imagery product has been added to the VIIRS imagery displayed online over CONUS at http://rammb.cira.colostate.edu/ramsdis/online/npp_viirs.asp.  The newest product is a RGB combination of the Day Night Band (DNB), the Shortwave Albedo, and the Longwave Infrared as the Red, Green, and Blue components, respectively.  This combination allows the discrimination of various types of cloud, low/water vs. high/ice, as well as clear land and ocean surfaces, as well as snow cover.  This RGB image is a product that has been in long term use with the equivalent bands/images of GOES.  The figure below shows the coverage of CONUS that occurs twice daily.  All of these image products are being used in VIIRS imagery validation efforts.  (D. Hillger)

Figure 1a: RGB composite (DNB/Shortwave Albedo/Longwave IR) produced from daytime VIIRS direct-broadcast imagery captured from the University of Wisconsin and displayed on CIRA’s “Suomi NPP VIIRS Online”.  Land surfaces are basically green, ocean surfaces are blue, and low clouds are white or off-white.  The magenta-based colors for snow (more red) and ice cloud (more purple) are similar, but users can easily learn to distinguish between the two.

Figure 1b: Same RGB combination as in Figure 1a, but for the nighttime passes over CONUS.  Note that the product includes lights from cities that can be confused with snow cover, being they are the same magenta-red color.

VIIRS Imagery EDR Users’ Guide:  C. Seaman has prepared a VIIRS Imagery EDR Users’ Guide, based on his Beginners’ Guide to VIIRS Imagery PowerPoint presentation.  The document will take the form of a NOAA Technical Report when complete.  The Users’ Guide is a required part of the EDR Imagery Validation 1 Review scheduled for 7 January 2014.  (D. Hillger, C. Seaman)

Figure 1: Cover of the first draft of the new VIIRS Imagery EDR Users’ Guide

Imagery Team Presentation for the Validation 1 Review: D. Hillger (StAR) and T. Kopp (Aerospace) represented the VIIRS EDR Imagery Team (via teleconference and WebEx) at the EDR Validation 1 Review on 7 January 2014.  That was followed by an Imagery User presentation given by J. Solbrig of Naval Research Laboratory (NRL).  This was the first EDR Imagery review where both non-NCC and NCC imagery reached a maturity stage at the same time.  In previous reviews the non-NCC and NCC Imagery were separated due to more and harder-to-solve issues with NCC Imagery, causing a lag in maturity compared to non-NCC Imagery.  Feedback from the Review Board came 1 day later, on 8 January 2013, recommending that Imagery has already reached the Validation 3 stage (a jump ahead by 2 stages).  However, the only caveat is that the Imagery Team provide recommended requirements for VIIRS Imagery as a result of our pointing out that the JPSS Imagery requirement are currently very lax and inadequate to move into the JPSS era.  (D. Hillger)

GOES-R ABI Split Window Difference: D. Lindsey and L. Grasso are continuing to study the utility of the GOES-R Split Window Difference in helping with convective initiation forecasting.  A paper on this topic was submitted to the Journal of Applied Meteorology and Climatology, and it has been accepted pending minor revisions.  The figure below is based on a model simulation of 20 May 2013, and shows a comparison of the 10.35 µm band (left) and the split window difference (right).  Note that a signal can be seen in the split window difference in central Texas before any convective clouds begin to form.  (D. Lindsey, L. Grasso)

Figure.  Simulated 10.35 µm (a, c, e, and g) and SWD (BT(10.35 µm ) – BT(12.3 µm), b, d, f, and h) imagery based on the 18-hour (a and b), 19-hour (c and d), 20-hour (e and f), and 21-hour (g and h) forecast of the NSSL WRF initialized at 00 UTC on 20 May 2013, valid at 18-21 UTC on 20 May 2013.  The brightness temperature and SWD units are °C.

GOES-R True Color Imagery Product (TCIP) Document Revised: D. Hillger provided an update to the Algorithm Theoretical Basis Document (ATBD) developed for true-color imagery from the GOES-R Advanced Baseline Imager (ABI).  The document was last revised in 2011, but another revision was considered necessary to avoid the use of “natural-color” terminology, as natural-color imagery is a standard and well-known product developed from Meteosat bands.  Rather, the use of “true-color” has been substituted, even though there could be some argument that what is seen is not strictly true color but synthetic true color.  The overriding consideration, however, is that the TCIP is derived from what are considered to be true-color visible/reflective bands.  The document gives the theoretical basis for generating true-color imagery from the ABI, which lacks the Green band.  That Green band is synthesized from other ABI bands in order to make up for its absence.  This ATBD will eventually be found online along with the ATBDs for other GOES-R products.  (D. Hillger)

Synthetic GOES-13 image of hurricane Sandy: In preparation for running HWRF for the new funded project entitled, “Assimilation of Moisture and Precipitation Observations in Cloudy Regions of Hurricane Inner Core Environments to Improve Hurricane Intensity, Structure, and Precipitation”, L. Grasso generated synthetic GOES-13 image at 10.7 µm from Grids 1, 2, and 3 of a simulation of hurricane Sandy (Figure 1). All images are from an hwrf_3.5a simulation and have been remapped onto a rectilinear grid. Further, these images were produced using the CRTM_v2.0.5 on grids 1, 2, and 3 of the simulation. Note: the CRTM_v2.0.5 was used as a standalone piece of code as opposed to using the post processing routines that are part of hwrf_3.5a. (L. Grasso)

Figure 1: Synthetic GOES-13 10.7 µm Tb from (A) Grid 1, (B) Grid 2, and (C) Grid 3 of a simulation of hurricane Sandy using hwrf_3.5a. These images have been remapped onto a rectilinear grid.

Manuscript Accepted with Revision: L. Grasso’s manuscript entitled, “Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF-ARW Using Synthetic and Observed GOES-13 Imagery” has been accepted with revisions to Monthly Weather Review.  Figure 2 below indicates the main result of the study: Our goal was to demonstrate that when a particular microphysical process is reduced by 50%, upper level ice clouds increase towards realistic coverage. Figure 2a shows a synthetic GOES-13 image at 10.7 µm from a “control” simulation of the 4 km NSSL WRF-ARW. Figure 2b shows results from a re-run of the “control” simulation with a 50% reduction in a microphysical process. Note the enhanced cold cloud coverage in Figure 2b. This work is in collaboration with the following external scientist: Kyo-Sun Lim (PPNL), Adam Clark (NSSL), and Scott Dembek (CIMMS) and the following internal scientists: Dan Lindsey (NESDIS), and Dan Bikos (CIRA).

  
Figure 2: Synthetic GOES-13 10.7 µm images from the real-time 4 km NSSL WRF-ARW. Results from a “control” run are displayed in (A). At issue is the consistent lack of upper level ice clouds. A new simulation was run with a 50 % reduction in a microphysical process; results are displayed in (B). Note the increase in cold cloud coverage.

Synthetic imagery of Dust: L. Grasso generated plots of optical properties at 0.56 µm of four idealized dust plumes. Each plume assumes an idealized Gaussian concentration following Sutton (1935; Sutton O. G., A theory of eddy diffusion in the atmosphere. Proc. Roy. Soc. London, A, 135, 1932, pp. 143-165). Optical properties—single scattering albedo, asymmetry factor, and extinction—have been computed from a predefined mixture of minerals for each plume. Figure 3 shows the optical properties of the plumes over the Texas Panhandle at 0.56 µm.

Figure 3. Optical properties of idealized dust plumes at 0.56 µm over portions of the Texas panhandle.

OWLeS Experiment:  D. Lindsey called several GOES-13 SRSO for the Ontario Winter Lake-effect Systems (OWLeS) experiment.  This 1-minute data was made available in real time on the web for OWLeS forecasters, was provided to the Storm Prediction Center and the Aviation Weather Center in NAWIPS format for display in their operational systems, and was archived and provided to OWLeS PIs for future research. (D. Lindsey)

Training metrics for the quarter:

•  Teletraining:

9 VISIT teletraining sessions have been delivered.  There were 10 teletraining signups, 23 students participated.

• Learning Management System (LMS) audio / video playback modules:
  Registrations:  101
  Completions:  65

LMS totals from January 2005 through 17 March 2014:
Registrations:  6827
Completions: 4648

Definitions used in LMS metrics:
Registrations:  The number of students who either clicked on the course, or actually took the course, but did not complete the quiz or achieve a passing grade upon taking the quiz.  A student may have registered for multiple courses.
Completions:  The number of students that achieved a passing grade on a quiz for a course.  A student may have completed multiple courses this way.

New training that debuted this quarter:

• “Identifying Snow with Daytime RGB Satellite Products” by Bernie Connell (CIRA).

New training forum:

• VISIT Satellite Chat – Virtual interactive training sessions that are intended to:

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).

Chat sessions during this quarter included a mixture: South Dakota blizzard, Northeast Severe Weather, Super Typhoon Haiyan, Lake-effect snow, and orographic cirrus. 

As of 17 March 2014 there have been 25 VISIT Satellite Chat sessions for a total of 68 NWS forecast office signups.  We started in February 2012 with one morning chat session and in September went to two chat sessions: one in the morning and one in the afternoon.  This allowed for more flexibility in participation from NWS offices, as well as other researchers and trainers.

Recorded versions of past satellite chat sessions are available here:
http://rammb.cira.colostate.edu/training/visit/satellite_chat/

Ongoing development of new VISIT training sessions:

• Utilizing Synthetic Imagery from the NSSL 4-km WRF-ARW model in temperature forecasting related to sky cover.

VISIT web-page traffic:

• The following is a summary of VISIT web-page traffic for the quarter (from Google Analytics), there were 19,057 page visits for the quarter:

Collaboration:

D. Bikos will be collaborating with many different training offices (including COMET) and local, regional and national operational offices of the National Weather Service. 

VISIT Meteorological Interpretation Blog – (http://rammb.cira.colostate.edu/training/visit/blog/) – Continue to build and administer the VISIT Blog – a web-log program intended to initiate increased communication between the operational, academic, and training communities.  The blog averages about 400 pageviews per month.

The following table shows a breakdown of the metrics for each VISIT teletraining session valid April 1999 – March17, 2014.  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.

Meetings and Calls

VISIT/SHyMet had conference calls on 23 January and 21 February.

E. Szoke, D. Bikos and B. Connell attended the GOES-R Proving Ground conference calls.

E. Szoke attended the American Meteorological Society annual meeting in Atlanta, GA in January.  The following presentation was delivered by E. Szoke:

• Szoke, E., D. Bikos, R. Brummer, H. Gosden, S. Miller, M. DeMaria, D. Lindsey, D. Hillger, C. Seaman, D. Molenar, 2014: More opportunities for forecaster interaction for future operational satellite products – CIRA’s activities in the GOES-R and JPSS Proving Grounds, 94th AMS Annual Meeting, Atlanta, Georgia, 2-6 February, 2014, 4th Conference on Transition of Research to Operations. 

A satellite training meeting was held at COMET in Boulder, CO on 3 March 3 2014.  D. Bikos, B. Connell and E. Szoke attended in person.  The main topic of the discussion was GOES-R related training and collaboration between VISIT/SHyMet, COMET and WDTB.  The GROW (GOES-R Operational Warning) course being developed by WDTB will be leveraging training materials and subject matter experts of VISIT / SHyMet as well as COMET.  Future training capabilities were discussed including in person training for GOES-R, an online “hotline” staffed by VISIT staff available for forecasters to ask questions once GOES-R becomes available and frequent “storm of the month” online discussions.

The NOAA satellite science week virtual meeting was held the week of 10 March 2014.  E. Szoke and B. Connell attended remotely.  Training was one of the topics of discussion but higher emphasis will be on training during the meeting in Kansas City in early June.
(D. Bikos, E. Szoke, B. Connell)

1. Preparations for proposed SHyMet course:  GOES-R Instruments and Products

Highlights:
At the COMET meeting on 3 March 2014 there was positive discussion on the materials that the various training groups offer to various user groups that GOES-R and JPSS would like to reach.  This GOES-R course draws directly on expertise from the Cooperative Institutes and will meet forecaster user needs.  It will be complementary to GOES-R material offered through COMET.  This course will also likely be leveraged to some extent for the GROW course being developed by WDTB.

Ray Hoff (University of Maryland, Baltimore County) was contacted to enquire about GOES-R Air Quality materials that can be included in this SHyMet course.  We will review 2 videos to see if they relate to the new course, and if so the need for quiz will be addressed with Dr. Hoff.

Four sessions of the new 30-minute teletraining:  “Identifying Snow with Daytime RGB Satellite Products” were given during January and February 2014.
http://rammb.cira.colostate.edu/training/visit/training_sessions/identifying_snow_with_daytime_rgb_satellite_products
A recording will be made incorporating feedback and then posted on the web page and linked to the LMS.

Background information and related updates:
A preliminary organizational call was held between the SHyMet teams at CIRA and CIMSS 19 November 2012 to discuss how the course should be structured and executed, what in-house training modules were candidates for the new course, and how do we decide which external training modules to include in the course.  A second call was held on 30 November and invited Satellite Champions, COMET, SPoRT, and other researchers to provide input on training that they have that would be relevant for the new SHyMet course.  More recently, a conference call was held on 22 April 2013 to consider what training modules could be included, as well as identification of potential training material.

Course structure:  A customized / personalized training experience with training needs assessed during signup.

Course execution:  Assign the individual modules at the time of registration.  The web-pages will group the various topics but we will ask the student at the time of registration their training needs, then determine which modules to assign.
Current list of in-house modules (containing 70% or more GOES-R PG product content):

• Introduction to GOES-R (abbreviated version of GOES-R 101)
• Forecaster Training for the GOES-R Fog/low stratus (FLS) Products.
• GOES-R severe weather applications demonstrated with synthetic imagery (new module to be developed by D. Bikos based primarily on existing training content).
• Objective Satellite-Based Overshooting Top and Enhanced-V Anvil Thermal Couplet Signature Detection.
• The UW NearCasting Product.
• Convective Cloud-top Cooling and UW Convective Initiation.

Potential External Modules:

A. GOES-R Satellite Liaisons (Amanda Terborg, Michael Folmer, and Chad Gravelle):

• Cloud Top Cooling
• RGB air mass / dust product
• CIMSS ABI WES case content
• Fog / low stratus (already included above)
• 4 synthetic imagery VISIT training sessions (severe weather, cyclogenesis, orographic cirrus, and low cloud/fog).

B. COMET (Patrick Dills and Wendy Abshire)

• GOES-R Benefits of next generation monitoring (multiple parts).
• ABI module.
• Companion module for GLM (future release).

There will be training modules that cover Air Quality (collaboration with Ray Hoff) and Space Weather (collaboration with Steve Hill) included.

Potential reference material containing less than 70% GOES-R content:
RGB products explained, Atmospheric dust, Forecasting dust storms, Volcanic ash observation tools and dispersion models, GOES channel selection (version 2), GOES channel selection (version 2),  Satellite monitoring of atmospheric composition, and Multispectral applications: monitoring the wildland fire cycle.

We will need introductory modules to briefly give an overview of how GOES-R preparations got to where they are now. We will include why there might be more than one product, as well as what to expect before and after launch.

2. The following 4 courses continue to be administered:

1. SHyMet Severe Thunderstorm Forecasting.  Released March 2011. Consists of 7 core courses and 4 optional courses: http://rammb.cira.colostate.edu/training/shymet/severe_topics.asp

      Core courses:

• Mesoscale Analysis of Convective Weather Using RSO Imagery.
• Use of GOES RSO Imagery with other Remote Sensor Data for Diagnosing Severe Weather across the CONUS.
• GOES Imagery for Forecasting and Nowcasting Severe Weather.
• Water Vapor Imagery Analysis for Severe Weather Forecasting.
• Synthetic Imagery in Forecasting Severe Weather.
• Predicting Supercell Motion in Operations.
• Objective Satellite-Based Overshooting Top and Enhanced-V Anvil Thermal Couplet Signature Detection.

Optional courses:

• Monitoring Gulf Moisture Return.
• The UW Convective Initiation Product.
• Coastal Severe Convective Weather.
• Topographically Induced Convergence Zones and Severe Convective Weather.

2. Tropical SHyMet.  Released August 2010.
Consists of 7 courses:  http://rammb.cira.colostate.edu/training/shymet/tropical_intro.asp

• Basic Satellite Interpretation in the Tropics.
• Ensemble Tropical Rainfall Potential (eTRaP)
• An Overview of Tropical Cyclone Track Guidance Models used by NHC
• An Overview of Tropical Cyclone Intensity Guidance Models used by NHC
• Satellite Applications for Tropical Cyclones : Dvorak Technique
• ASCAT Winds
• AWIPS OB9 Blended TPW Products

3. SHyMet For Forecasters Learning Plan:  Released January 2010.  It consists of 6 core courses and 3 optional courses.
http://rammb.cira.colostate.edu/training/shymet/forecaster_intro.asp :

This Development Plan includes:

1. Introduction to remote sensing for hydrology (NWS FDTB)
2. Interpreting Satellite Signatures (CIMSS)
3. Satellite Applications for Tropical Cyclones: Dvorak Technique (RAMMB/CIRA)
4. Aviation Hazards (CIRA)
5. Water vapor channels (CIMSS)
6. GOES-R 101 (CIRA)

Optional modules

7. Regional Satellite Cloud Composites from GOES (CIRA)
8. Volcanic Ash Hazards (Part 1)  (CIRA)
9. Volcanic Ash Hazards (Part 2) (CIRA)

4. SHyMet Intern Learning Plan: Released April 2006
The SHyMet Intern course consists of 9 modules.
(http://rammb.cira.colostate.edu/training/shymet/intern_intro.asp ). 

Metrics for the 4 SHyMet courses:

Non-NOAA:
Intern:  44 Registrations; 14 known completions

The numbers we have listed here for total completions since debut have doubled from what were reported at the end of 2012.  This is mainly due to taking a closer look at the completion numbers that come out of NOAA’s learning management system.  In the past we have asked for participants to send an email to the SHyMet group to register for the course and send another email when they have completed the course.  NOAA’s LMS currently does not have an ideal way to track completion of a whole course.  We retrieve individual module registrations and completions and then sort on those by course and participant.  We check this list of course completions against our email registration list.  By comparing the two lists, we have found that those that register with CIRA by email account for roughly 66% of those that have completed the course.  Of those that register for the course with CIRA and complete it, roughly 50% tell us that they have completed the course.  Roughly 33% of those that show they have completed all the modules for a course in NOAA’s LMS have not registered with us.  It is important to keep this in mind in planning for future courses.

3. International training that builds on efforts of the VISIT and SHyMet Programs, and enhances communication and exchange of information with international training partners:

CIRA, NOAA, WMO, and the WMO Centers of Excellence in Costa Rica, Barbados, Brazil, and Argentina hosted a virtual training on GEONETCast consisting of 3 sessions on 3, 4, and 5 December 2013. The sessions were presented in both English and Spanish (for a total of 6 sessions).  The goals of the training were:  to make countries more aware of products available through GEONETCast; to expand the use of GEONETCast-Americas; and to start thinking about GOES-R.  The topics included an introduction to the capabilities of GEONETCast, disaster mitigation products, and software to view products.  Content from GOES-R 101 was used for the “Introduction to GOES-R” presentation.  McIDAS-V was one of the software packages that was highlighted.  The audience expressed interest on more GOES-R and JPSS training as well as training on McIDAS-V software. 

4. Community Outreach: 

After-school weather club: Scientists at CIRA and CSU students – all members of the local AMS chapter of Northern Colorado – FORTCAST (Fort Collins Atmospheric Scientists) volunteered for the weekly after-school weather club on Tuesdays for Putnam Elementary (K-5).  This fall session ran for 8 weeks during October through early December 2013.  There was a 90 minute session each week.  Sessions included helping with homework and leading an activity.  The topics covered included rain, wind speed, clouds, temperature, hail, frost (and ice cream!), and things that spin as well as measurements that are associated with these weather occurrences.  Volunteers included Bernie Connell, Matt Rogers, Kristi Gebhart, Erin Dagg, and James Ruppert.  Putnam has a coordinator who is responsible for matching students with clubs, assigning classrooms, providing snacks, and providing transportation – which is great!

Monthly International Weather Briefings

The WMO Virtual Laboratory Regional Focus Group of the Americas and Caribbean conducted 2 monthly English and Spanish weather briefings (23 January, and 27 February 2014) 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, NWS Training Division, UCAR/IA-NWS, and UCAR/COMET as well as outside the U.S.: Algeria, Argentina, Bahamas, Barbados, Belize, Bolivia, Colombia, Costa Rica, Dominican Republic, Haiti, Honduras, Panamá, Peru, St. Kitts and Nevis, Suriname, and Trinidad and Tobago.  The participants include researchers and students as well as forecasters and other trainers.  Both sessions were well attended as represented by 10 countries each month reaching 25 and 29 participants respectively for January, and February.  Mike Davison at NCEP International Desk led the discussions.  Typically, the sessions include a look at Water Vapor imagery for a synoptic overview of Central America and the Caribbean as well as for South America.  The IR 10.7 um imagery and Visible imagery are used to look more closely at weather features.  We look at MJO patterns and the outlook, Total Precipitable Water (TPW) patterns, Sea Surface Temperature (SST) and anomalies.  Imagery from a recent weather feature is often highlighted.  Recordings of the three sessions as well as previous sessions can be found here:  http://rammb.cira.colostate.edu/training/rmtc/fg_recording.asp (B. Connell)

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)

Figure 1.  Number of countries participating each month in the online virtual discussion sessions over the past 10 years.

Figure 2.  Number of participants joining in each month in the online virtual discussion sessions over the past 10 years.

February 2014 is a milestone month for the group leading 10 years of monthly virtual sessions.  Up to February 2014, out of a total of 120 possible monthly sessions, we have only missed 5 months: 4 due to leaders not being available and one because of technical problems.  That is pretty darn good!

Figure 1. shows the number of countries participating each month over the past 10 years and Figure 2. shows the number of participants joining in each month over the past 10 years.

Sharing of Imagery and Products
Imagery for Central and South America and the Caribbean can be viewed at one location through RAMSDIS Online – look for the 4-week archive feature:  (http://rammb.cira.colostate.edu/ramsdis/online/rmtc.asp). 
Look for information on our activities on the VLab/ Regional Training Center web page. http://rammb.cira.colostate.edu/training/rmtc/

GEONETCast Americas VLab Training Channel
B. Connell participated in a GEONETCast Americas (GNC-A) Coordination Group telecon on 6 March 2014.  The meeting focused on who should be in this newly formed group, what their roles and responsibilities should be, and how to move forward in the future. (B. Connell)

VIIRS Imagery of Alaska Added to RAMSDIS Online: A suite of VIIRS imagery products covering the Alaska Region have been added to RAMSDIS Online, including: Day/Night Band (DNB); Near-Constant Contrast (NCC); shortwave (I-4) and longwave (I-5) infrared bands; and the “Natural Color RGB” produced from bands I-1, I-2 and I-3. All, except for the DNB images, are comprised of Imagery EDR files. Images are available in low resolution (900×800 pixels) and high resolution (3850×3425 pixels) versions. The high resolution images are designed to preserve the native resolution of the DNB data. Loops of the low resolution images are available, and individual images are kept in running four week archive. These imagery products are being used in VIIRS imagery validation efforts and to demonstrate the uses of VIIRS data in high-latitude regions.  An example of the Natural Color RGB composite imagery is shown below. These imagery products are available at: http://rammb.cira.colostate.edu/ramsdis/online/npp_viirs.asp#Alaska-Centered_Image_Products (C. Seaman, K. Micke)

Figure: Example of the Natural Color RGB imagery of Alaska now available on RAMSDIS Online (from 23:08 UTC 20 February 2014)

Demonstration of the Impact of Terrain-Correction on VIIRS Imagery: Image loops have been created that demonstrate the impact of terrain-correction on images produced from VIIRS SDRs. VIIRS EDRs, which are not terrain-corrected, appear to have large shifts in the location of mountains from one orbit to the next due to parallax effects. The terrain-correction in the SDR imagery eliminates the apparent motion of mountain ranges, as expected. These image loops and discussion are available at the Suomi-NPP VIIRS Satellite Calibration and Validation website: http://rammb.cira.colostate.edu/projects/npp/calval/ (C. Seaman, D. Hillger)

RAMMB launched a new way to display the many image loops on the RAMMB website. The HTML5 Looper was built so that satellite imagery can be viewed in all modern browsers, including mobile phones and tablets. This will allow website users to seamlessly view image loops without the need for additional plugins such as Flash of Java, so matter what device they use to visit the website. (K. Micke)

Figure 1: Screenshot of the HTML5 Looper in Chrome on a Windows 7 system, displaying GeoColor GOES-East CONUS 1 km imagery.

Figure 2: Screenshot of the HTML5 Looper in Chrome Mobile on an Android phone, displaying Synthetic GOES-R Imagery
;from Real-Time NSSL 4 km WRF-ARW Band 10 (7.34 µm) imagery.

Two new high end linux systems have been procured and configured.  The systems will be used for the AWIPS II WES training and for the development of a consolidated tropical data ingest system. (D. Molenar)

Three new Windows workstations have been procured and configured for use by admin and hourly staff. (D. Molenar)

All 2013 tropical data archived has been written to DVD by a student hourly.  Efforts are underway to automate the 2014 archive to Groundsystem BluRay discs.
A new AWIPS II real-time ingest and display workstation has been installed in the CIRA Weather Lab. (D. Molenar)

Two new 64 bit RedHat AWIPS II workstations have been configured to run OB14.1.1.  The workstations will be used for software development training and test RGB software implementation. (D. Molenar)

New LDM server: the configuration of a replacement LDM server that distributes Proving Ground (PG) products was completed.  The system was configured with CentOS 5.1, the latest LDM 6.11.6 software, and the WDTB WES OB9.7 to allow running AWIPS D2D display.  After a successful LDM data distribution tests on the new server, the old server was replaced in March 2014. (H. Gosden)

Dual Display on AWIPS I: after a few failed attempts, the dual display configuration on the AWIPS I system with CentOS 5.10 was successfully enabled. (H. Gosden)

HFIP Data Transfer from Thecus NAS to Synology NAS: Worked with Kate Musgrave to transfer the model data for the HFIP project onto a more reliable Synology NAS device.  The satellite data will be next, but most of it has already been transferred as well.  The remainder of the satellite data will need to be searched from other various devices and transferred onto the new NAS device. (H. Gosden, K. Musgrave)

Published:

• Refereed

DeMaria M, J.A. Knaff, R. Zehr, 2014: Assessing hurricane intensity using satellites. Satellite-based applications to climate change. J.J. Qu, A. Powell, and M.V.K. Sivakumar, Eds, Springer, New York, 151-163. doi: http://dx.doi.org/10.1007/978-94-007-5872-8_10

Jin, Y., S. Wang, J. Nachamkin, J.D. Doyle, G. Thompson, L.D. Grasso, T. Holt, J. Moskaitis, H. Jin, R.M. Hodur, Q. Zhao, M. Liu, and M. DeMaria, 2014: Evaluation of Microphysical Parameterizations for Tropical Cyclone Prediction.Mon. Wea. Rev. 142:2, 606-625.

Johnson, R., R. Schumacher, J. Ruppert, D.T. Lindsey, J. Ruthford, and L. Kriederman, 2014: The role of convective outflow in the Waldo Canyon Fire. Mon. Wea. Rev.  142:9, 3061-3080.

Knaff, J.A., S.P. Longmore, D.A. Molenar, 2014: An Objective Satellite-Based Tropical Cyclone Size Climatology. J. Climate, 27:1, 455–476. doi: http://dx.doi.org/10.1175/JCLI-D-13-00096.1

Lang, T.J., S.A. Rutledge, B. Dolan, P. Krehbiel, W. Rison, and D.T. Lindsey, 2014: Lightning in wildfire smoke plumes observed in Colorado during summer 2012. Mon. Wea. Rev., 142:2, 489–507.  doi: http://dx.doi.org/10.1175/MWR-D-13-00184.1

Quiring, S., A. Schumacher, and S. Guikema, 2014: Incorporating Hurricane Forecast Uncertainty into Decision Support Applications, Bull. of the American Meteorological Society, 95:1, 47-58.

• Nonrefereed

Connell, B.H., D. Bikos, E. Szoke, S. Bachmeier, S. Lindstrom, A. Mostek, B. Motta, T. Schmit, M. Davison, K. Caesar, V. Castro, L. Veeck, 2014: Satellite Training Activities: VISIT, SHyMet and WMO VLab. AMS Tenth Annual Symposium on New Generation Operational Environmental Satellite Systems. 2-6 February, Atlanta, GA.

Grasso, L.D., D.T. Lindsey, and D. Bikos, 2014: Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF-ARW Using Synthetic and Observed GOES-13 Imagery. NOAA Satellite Science Week, 10-14 March.

Hillger, D.W., C. Seaman, C. Liang, S.D. Miller, D.T. Lindsey, T. Kopp, 2014: Suomi NPP VIIRS Near Constant Contrast (NCC) Imagery. AMS Tenth Annual Symposium on New Generation Operational Environmental Satellite Systems. 2-6 February, Atlanta, GA.

Lindsey, D.T., L.D. Grasso, D. Bikos, E. Szoke, 2014: Using Simulated Satellite Imagery to Visualize Model Forecasts. AMS 26th Conference on Weather Analysis and Forecasting, 2-6 February, Atlanta, GA.

Lindsey, D.T., L.D. Grasso, E. Szoke, 2014: A New Look at the GOES-R ABI Split Window Difference for Convective Initiation Forecasting. AMS 10th Annual Symposium on New Generation Operational Environmental Satellite Systems, 2-6 February, Atlanta, GA.

Schumacher, A.B., and M. DeMaria, 2014: Upgrades to the Operational Monte Carlo Wind Speed Probability Program, 68th Interdepartmental Hurricane Conference, 4-6 March, Miami, FL.

Szoke, E., R.L. Brummer, H. Gosden, C. Seaman, D. Bikos, S.D. Miller, M. DeMaria, D.T. Lindsey, D.W. Hillger, and D.A. Molenar, 2014: More opportunities for forecaster interaction for future operational satellite products – CIRA’s activities in the GOES-R and JPSS Proving Grounds. AMS 4th Conference on Transition of Research to Operations, 2-6 February, Atlanta, GA.

Accepted:

• Refereed 

Ali, M., N. Sharma, J.A. Knaff, 2014: A Soft-computing Cyclone Intensity Prediction Scheme for the Western North Pacific Ocean. Atmospheric Science Letters.

Cintineo, M. Pavolonis, J. Sieglaff, and D.T. Lindsey, 2014: An Empirical Model for Assessing the Severe Weather Potential of Developing Convection, Weather and Forecasting. 

DeMaria, M., C.R. Sampson, J.A. Knaff, K.D. Musgrave, 2014: Is Tropical Cyclone Intensity Guidance Improving? Bulletin of the American Meteorological Society.

Grasso, L.D., D.T. Lindsey, D. Bikos, 2014: Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF-ARW Using Synthetic and Observed GOES-13 Imagery, Monthly Weather Review.  

Jin, Y., S. Wang, J. Nachamkin, J.D. Doyle, G. Thompson, L.D. Grasso, T. Holt, J. Moskaitis, H. Jin, R.M. Hodur, Q. Zhao, M. Liu, and M. DeMaria, 2014: Evaluation of Microphysical Parameterizations for Tropical Cyclone Prediction. Monthly Weather Review.

Johnson, R.H, R.S. Schumacher, J.H. Ruppert, Jr., and D.T. Lindsey, 2014: Meteorology of the Waldo Canyon Fire. Monthly Weather Review.

Lang, T.J., S.A. Rutledge, B. Dolan, P. Krehbiel, W. Rison, D.T. Lindsey, 2014: Lightning in Wildfire Smoke Plumes Observed in Colorado during Summer 2012. Mon.Wea.Rev.

Lindsey, D.T., L.D. Grasso, J.F. Dostalek, J. Kerkmann, 2014: A New Look at the Split Window Difference to Diagnose Deepening Low-Level Water Vapor. Journal of Applied Meteorology and Climatology.

Tourville, N., G. Stephens, M. DeMaria, 2014: Cloudsat and A-TRAIN Observations of Tropical Cyclones. Bulletin of the American Meteorological Society.

• Nonrefereed

Beven, J.L., M. J. Brennan, H. D. Cobb III, M. DeMaria, J.A. Knaff, A.B. Schumacher, C. Velden, S.A. Monette, J.P. Dunion, G.J. Jedlovec, K.K. Fuell, and M.J. Folmer, 2014: The Satellite Proving Ground at the National Hurricane Center. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Chirokova, G., M. DeMaria, R. DeMaria, J.F. Dostalek, J.L. Beven, 2014: Improving Tropical Cyclone Track and Intensity Forecasting with JPSS imager and Sounder Data. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

DeMaria, M., A.B. Schumacher, 2014: A Quasi-Equilibrium Theory for Tropical Cyclone Potential Intensity. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Dostalek, J.F., G. Chirokova, K. Musgrave, M. DeMaria, 2014: A Comparison of Two Microwave Retrieval Schemes in the Vicinity of Tropical Storms. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Knaff, J.A., M. DeMaria, S. Longmore, R. DeMaria, 2014: Improving Tropical Cyclone Guidance Tools by Accounting for Variations in Size. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Knaff, J.A., S. Longmore, R. DeMaria, 2014: An Improved Method to Estimate Tropical Cyclone Surface Wind Fields from Routine Satellite Reconnaissance. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Musgrave, K.D., M. DeMaria, 2014: Further Development of a Statistical-Dynamical Ensemble for Tropical Cyclone Intensity Prediction. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Schumacher, A.B., M. DeMaria, J.A. Knaff, L. Ma, H. Syed, 2014: Updates to the NESDIS Tropical Cyclone Formation Probability Product. 31st Conference on Hurricanes and Tropical Meteorology. 30-March-4 April, San Diego, CA.

Submitted:

• Refereed 

Apodaca, K., M. Zupanski, M. DeMaria, J.A. Knaff, and L.D. Grasso, 2014: Lightning data assimilation into a quasi-operational numerical weather prediction model through hybrid variational-ensemble methods, Journal of Applied Meteorology and Climatology.

Grasso, L.D., D.W. Hillger, M. Sengupta, 2014:  Demonstrating the Utility of the GOES-R 2.25 µm band for Fire Retrieval. Geophysical Research Letters.

Grasso, L.D., D.T. Lindsey, C. Seaman, 2014: Satellite Observations of Plume-Like Streaks in a Cloud Field.” Journal of Atmospheric Remote Sensing.

Hillger, D., C. Seaman, C. Liang, S. Miller, D. Lindsey, and T. Kopp (2014): Suomi NPP VIIRS Imagery Evaluation. Journal of Geophysical Research.

Johnson, R., R. Schumacher, J. Ruppert, and D.T. Lindsey, 2014: Meteorology of the Waldo Canyon Fire, Monthly Weather Review.

Schmit,T.J., S.J. Goodman, D.T. Lindsey, R.M. Rabin, K.M. Bedka, M.M. Gunshor, J.L. Cintineo, C.S. Velden, A.S. Bachmeier, S.S. Lindstrom, and C.C. Schmidt, 2014: GOES-14 Super Rapid Scan Operations to Prepare for GOES-R. JARS.

Schmit, T.J., S.J. Goodman, M. Gunshor, J. Sieglaff, A. Heidinger, S. Bachmeier, S. Lindstrom, A. Terborg, J. Feltz, K. Ba, S. Sudlosky, D.T. Lindsey, R. Rabin, C. Schmidt, 2014: Rapid Refresh Information of Significant Events: Preparing Users for the Next Generation of Geostationary Operational Satellites. Bull. of the American Meteorological Society.

Van Cleave, D., J.F. Dostalek, and T. Vonder Haar, 2014: The Dynamics and Snowfall Characteristics of Three Types of Extratropical Cyclone Comma Heads Categorized by Infrared Satellite Imagery. Weather and Forecasting.

• Nonrefereed 

Brummer, R., E. Szoke, D. Bikos, D.T. Lindsey, H. Gosden, S.D. Miller, M. DeMaria, D.A. Molenar, 2014: CIRA Proving Ground Activities. EUMETSAT 2014 Meteorological Satellite Conference, 22-26 September, Geneva, Switzerland.

Brummer, R., D.T. Lindsey, L.D. Grasso, D.W. Hillger, E. Szoke, D. Bikos, 2014: Synthetic Satellite Imagery Development at CIRA. EUMETSAT 2014 Meteorological Satellite Conference, 22-26 September, Geneva, Switzerland.

Miller, S.D., W. Straka, A.S. Bachmeier, T.J. Schmit, P.T. Partain, and Y-J. Noh, 2014: Fire on High—Unique Perspectives on the Chelyabinsk Meteor from Earth-Viewing Environmental Satellites. EUMETSAT 2014 Meteorological Satellite Conference, 22-26 September, Geneva, Switzerland.

Molenar, D.A., 2014: Support and Utilization of the National Weather Service Advanced Weather Interactive Processing System II in a Research Environment. UCAR Software Engineering Assembly, 17 April 2014.

Seaman, C., D. Hillger, T. Kopp, R. Williams, S. Miller and D. Lindsey (2014): Visible Infrared Imaging Radiometer Suite (VIIRS) Imagery Environmental Data Record (EDR) User’s Guide. NOAA Technical Report, National Oceanic and Atmospheric Administration, Washington, DC.

Presentations:

Grasso, L.D., 2014: 15-minute presentation at the CIRA retreat at Tamasag entitled, “OBSERVED DUST CHARACTERISTICS FROM MODIS and IDEALIZED DUST PLUMES.”

Knaff, J.A., S. Longmore, D.A. Molenar, 2014: Improved Estimates of Tropical Cyclone Surface Wind Structure from Routine Satellite reconnaissance. NOAA Satellite Science Week.

Lindsey, D.T., 2014: Using simulated imagery to visualize model forecasts. AMS 26th Conference on Weather Analysis and Forecast/22nd Conference on Numerical Weather Prediction. 2-6 February, Atlanta, GA. (Several NWS forecasters approached following the talk on simulated imagery asking if they can get the imagery in their office, so installation instructions were sent.)

Lindsey, D.T., 2014: A new look at the GOES-R ABI split window difference for convective initiation forecasts. AMS 10th Annual Symposium on New Generation Operational Environmental Satellite Systems.  2-6 February, Atlanta, GA.

Molenar, D.A., 2014: Presentation on the use of the new real-time AWIPS II standalone workstation that was recently installed in the CIRA Weather Lab.  The presentation covered the latest information on AWIPS II deployment as well as CIRA AWIPS II project status, which includes efforts to develop RGB display capabilities in AWIPS II Display 2 Dimensions (D2D) and the National Centers Perspective (NCP).  The real-time demo of the system covered the various display perspectives available in AWIPS II and the methodology used to add experimental products to the system.  18 February 2014, CIRA, Fort Collins, CO,

Figure 1:  Screen capture of AWIPS II D2D real-time data displayed in the CIRA Weather Lab AWIPS II workstation.  Center image is the CIRA GOES-R Proving Ground GeoColor product (courtesy of Steve Miller).  Left panel, top to bottom, shows GOES 15 & 13 IR imagery with model overlay, the CIRA GOES Sounder RGB Airmass product (courtesy of John Knaff), the CIRA Orographic Rain Index product over Puerto Rico (courtesy of Stan Kidder), and the CIRA Simulated WRF imagery (courtesy of Dan Lindsey).

NOAA CREST Brown Bag Seminar: D. Hillger and J. Knaff of StAR/RAMMB listened to a NOAA CREST Brown Bag Seminar on 28 January 2014.  Title of the presentation was “Wintertime Storms in the Northeast: Wind Extremes and Ice Storms,” given by James F. Booth, Department of Earth and Atmospheric Sciences, City College of New York.  (D. Hillger, J. Knaff)

Hillger, D.W., 2014: D. Hillger gave a talk at Colorado State University’s Professional Development Institute (PDI) annual event, held 13-15 January 2014.  The PDI consists of numerous classes where various faculty and staff volunteer to share their expertise.  Hillger’s talk was titled “Whatever happened to the US adoption of the metric system?” trying to enlighten the audience to the many hidden uses of the metric system in America and explain why America has failed to adopt metric for everyday use.  The talk was well received, although attendance was light due to multiple concurrent sessions.  PDI classes given by other presenters were also attended, on topics such as “The Hidden Gems of Google.”  (D. Hillger)

Posters:

Connell, B., D. Bikos, E. Szoke, S. Bachmeier, S. Lindstrom, A. Mostek, B. Motta, T. Schmit, M. Davison, K. Caesar, V. Castro, L. Veeck, 2014: Satellite Training Activities: VISIT, SHyMet, and WMO VLab.  10th Annual Symposium on New Generation Operational Environmental Satellite Systems at the 94th AMS Annual Meeting, Atlanta, Georgia, 2-6 February, 2014. 
http://www.goes-r.gov/downloads/AMS/2014/posters/session02/692.pdf

Satellite Liaisons Visit Coordination Meeting: Participated in the remote conference meeting to discuss scheduling and activities of the visit by the satellite liaisons from NWS and National Centers.  The meeting date is to TBD and a few ideas of activities were discussed.  The main idea is for this visit is for the liaisons to understand the products that CIRA has developed and how it could benefit their forecasters, as well as to get a better understanding of their forecasting needs. (H. Gosden, R. Brummer, S. Miller, B. Connell, M. DeMaria, D. Molenar, D. Hillger)

Preparation for first data from the Advanced Baseline Imager (ABI): Dave Pogorzala, Product Operations Science Support Team (POSST) Monitoring and Analysis Software Tool (MAST) Manager, visited RAMMB and CIRA on 12 February 2014.  The purpose of the visit was in preparation for the first data that will be received from the Advanced Baseline Imager (ABI) in the checkout period following the GOES-R launch scheduled for early 2016.  Hillger and T. Schmit were instrumental in the Science Testing of GOES-10/15.  Schmit has been appointed a co-lead of the ABI/GLM Image Navigation and Registration (INR) Team.  During his visit Pogorzala learned how the Science Tests were executed for previous GOES, including the ingest and display at RAMMB/CIRA as one of the primary sites to receive the first data and imagery from each satellite.  RAMMB and CIRA hope to be heavily involved in the checkout of GOES-R in a similar manner.  Hillger is currently the Imagery Team Lead for SNPP VIIRS. (Hillger)

Visit from Sid Boukabara, acting director of JCSDA: Sid Boukabara, acting director of JCSDA, gave a seminar and visited CIRA and Atmospheric Science on 18 February 2014.  During his visit he met briefly with RAMMB.  MIRS soundings, which are being used locally for a number of products, were a topic of discussion.  We also discussed how to get more ATMS MIRS retrievals for tropical cyclone studies, how to get the MIRS code and run it locally, and who to contact at NESDIS regarding contents of the operational MIRS products.  We learned a lot about the process, what fields are good/bad and how to better interpret some of the fields.  (J. Knaff, G. Chirokova, R. DeMaria, J. Dostalek)

Going-away Party for Mark DeMaria: CIRA and RAMMB gave Mark DeMaria a going-away party on 11 February 2014.  DeMaria is leaving as RAMMB Chief after 15 years, to take the Technology and Science Branch Chief position at the National Hurricane Center in Miami FL. Speakers at the party were C. Kummerow (CIRA Director), I. Guch (CoRP Director, via telephone connection), D. Hillger (Acting Branch Chief), and R. Brummer (Assistant to RAMMB Chief).  Brummer prepared a short but humorous slide show featuring Mark’s career, and Hillger had a poster that outlined RAMMB history at CIRA since 1980.  The event included gifts for Mark and cake and other desserts for the large crowd.  DeMaria also spoke to the attendees, indicating that he would try to stay in touch and praising RAMMB and CIRA.  (D. Hillger, D. Molenar, D. Lindsey, J. Knaff, R. Brummer, K. Fryer)

Some of the attendees at M. DeMaria’s going-away party, shown from left to right are: C. Kummerow, R. Brummer, D. Molenar, R. Zehr,
D. Hillger, M. DeMaria, D. Lindsey, J. Weaver, J. Knaff, and K. Fryer.  DeMaria is holding one of his going-away gifts from RAMMB/CIRA.

Annual reviews have been completed for all CIRA IT staff. (D. Molenar)

D. Molenar participated in GSADisposal Solutions Online Training “Basics of Property Disposal” presented on 27 February 2014.  This training, along with the previous UNICOR training, has helped in the development of an efficient, cost effective local surplus plan for RAMMB federal property. (D. Molenar) 

M. DeMaria was awarded the NOAA 2014 Bronze Medal Award Career Winners For research that has led to increased understanding, observational utilization and improved hurricane forecast capabilities.

RAMMB received a “Gold Award” from the Rocky Mountain Combined Federal Campaign.  The plaque that was sent has been hung on the wall outside the RAMMB chief’s office.  D. Lindsey, M. DeMaria, D. Hillger, J. Knaff, and D. Molenar

A letter of appreciation from the Joint Typhoon Warming Center expressing appreciation for John Knaff’s “outstanding support” of the JTWC during the 2013 tropical cyclone season.