CIMSS/ASPB PG April 2010MeetingsVisits involving NWSAWIPS MigrationGRIB2Norman Haz Wx TestbedLocal Area Haz Wx TestbedReal-time ABI simulations using NSSL WRFWES ABI statusWorking with AK PG effort

Related topicsGOES-R and FogForecast Sky Cover Product Provided to NWSNear-casting examplesVISITview TrainingCIMSS Satellite blogGOES-15 First visible imagesGOES-13 cut-overGOES-11

MeetingsOn March 22, 2010, J. Gerth gave a presentation at the Great Lakes Operational Meteorology Workshop in Toronto, Canada, titled Enhancing Local Model Studies with Initial Conditions from Satellites for Great Lakes Research.The presentation focused on how current operational and experimental satellite data is of use to the Great Lakes operational meteorology community and the kind of changes that can be expected with the GOES-R series satellites as well as what it means for operational meteorology and numerical weather prediction.During the meeting, forecasters underscored the need for detection and tracking capability of gravity wave features in satellite imagery.

Visits involving NWSOn Friday, January 29, 2010, J. Gerth visited NWS Sullivan to assess the current state of the research to operations products provided.On Monday, March 15, 2010, CIMSS hosted forecaster Marcia Cronce, senior forecaster Steve Hentz, and Information Technology Officer Jerry Wiedenfeld from NWS Sullivan.Discussed plans for the upcoming GOES-R simulated product demonstration and evaluation testbed which will occur this summer.An overview was given of the convective initiation and nearcasting products that are currently in use at NWS Sullivan.There was also discussion about the progression of the AWIPS migration.

AWIPS MigrationJ. Gerth continues to serve as the CIMSS representative on the AWIPS II teleconference call for the GOES-R Proving Ground partners, as well as the AWIPS II Governance Tiger Team. Additional time will be required shortly with NWS/NCEP and the NESDIS AWIPS focal point to pursue our GOES-R PG product transition approach.Currently assessing operating system and hardware requirements to run AWIPS II outside of a NWS forecast office. Our development equipment is adequately handling the software.Continue to receive and install new builds of the software, most recently TO11 DR9.

POES data in local AWIPS2

GRIB2Convective initiation products now available in GRIB2 format. The GRIB2 format is compliant with WMO and NCEP standards. AWIPS netCDF delivery will be phased out at our beta test sites. NWS Sullivan, SPC, and Spaceflight Met Group will be first users of GRIB2 format.Intend to launch GRIB2 to all interested field offices in the coming weeks. Web site will be available.S. Lindstrom is currently preparing training via the VISIT program.GRIB2 products do not work with N-AWIPS due to irregular initial times and memory allocations in the software.

Norman Haz Wx TestbedW. Feltz and J. Gerth will visit C. Siewert in Norman, OK, on April 26, 27 to finalize data flow and functionality of products that will be demonstrated as part of the spring experiment at the Storm Prediction Center.Deadline for delivery of products for evaluation as established in the plan was April 1.Currently working with Greg Stumpf to assure access to the convective initiation products in AWIPS for the Experimental Warning Program.The methodology for providing data to N-AWIPS will continue similar to last year. Loop back delivery allows CIMSS to remotely detect when delivery to the SPC has failed in this approach.

GOES Proxy Overshooting Top (OT) and Decision Support DetectionProvided to SPC HWT for GOES-R PG Spring 2010

OT Validation

Local Area Haz Wx TestbedThe local area HWT with NWS Sullivan will run predominantly Tuesday and Thursday of each week from the middle of May through the end of August.NWS Sullivan forecaster will be dedicated to working with CIMSS scientist in consistently assessing the functionality of the GOES-R PG demonstration products during the upcoming convective season.J. Craven, M. Cronce, (NWS Sullivan) and J. Gerth (CIMSS) are working to prepare questions which will be provided to NWS Sullivan forecasters on each assessment shift as they find use for the convective initiation and nearcasting products.We are looking to quantify not only lead time against radar and lightning data, but compared to the forecasters subjective assessment of when convective initiation is imminent.

ABI Band 10(7.34 m)ABI Band 13(10.35 m)UW/CIMSS is generating simulated ABI Bands 8-16 using NSSL-WRF once daily

Resolving timing issue related to file transfer from NSSL to CIMSS; causing unnecessary lag.

Currently in test mode, webpage is updated by 11am for 7 timesteps. After timing issue hope to process 19 timesteps [12-06 UTC] by 8 am (central).http://cimss.ssec.wisc.edu/goes_r/proving-ground/nssl_abi/nssl_abi_rt.html

GOES-R ABI WES CaseReviewing feedback and making changes as necessary.Adding simulated data over the Pacific Ocean.Updating WES guideHave inquired about eventual steps for converting case into AWIPS II compliant format.

ABI WES case: Added a set of ABI simulated images from 21Z on Jun 26, 2008

GOES-R AWG Fog/Low Cloud Detection AlgorithmThe official GOES-R fog/low cloud detection product is designed to quantitatively identify clouds that produce Instrument Flight Rules (IFR) or Low Instrument Flight Rules (LIFR) conditions (ceiling < 1000 ft (305 m)).The GOES-R fog detection is expressed as a probability, which is derived from textual and spectral information, as well as the difference between the cloud radiative temperature and surface temperature. Cloud object processing is also used to improve algorithm skill.Fog cannot be accurately detected if there are higher cloud layers overlapping the fog layer. The accuracy specifications account for this.Since the properties of the cloud base are not directly measured, variations in cloud base due to local boundary layer effects (e.g. local moisture sources/sinks and local turbulent mixing processes) generally will not be captured. As such, not every surface observation underneath a GOES-R detected low cloud will necessarily indicate a ceiling of 1000 ft or lower, but those surface observations that do not indicate LIFR or IFR will generally indicate Marginal Visual Flight Rules (MVFR) conditions.The GOES-R AWG fog product is included in the High Latitude and Winter Testbed and Alaska Experiment Operations Plan.Examples are shown in the subsequent slides.

GOES-R Fog Detection Algorithm (night)RGB image (R = 3.9 m emissivity, G = 11 m BT, B = 11 m BT) of the US on December 13, 2009 at 7:45 UTC (1:45 am CST) with surface observations showing visibility in miles.

GOES-R Fog Detection Algorithm (night)The fog probability determined from the GOES-R fog detection algorithm is contoured over the false color image.

GOES-R Fog Detection Algorithm (night)

GOES-R Fog Detection Algorithm (day)RGB image (R=0.65m reflectance, G=3.9m reflectance, B=11m BT) of the US on December 13, 2009 at 15:45 UTC (9:45 am CST) with surface observations showing visibility in miles

GOES-R Fog Detection Algorithm (day)The fog probability determined from the GOES-R fog detection algorithm is contoured over the false color image.

GOES-R Fog Detection Algorithm (day)

GOES-R AWG Volcanic Ash ProductsThe official GOES-R volcanic ash products are: ash cloud height and ash mass loading (ash effective radius is also produced).Recently, we have updated Geocat to allow for MODIS processing. MODIS direct broadcast data can be used to test and evaluate the GOES-R algorithm in the Alaska Region.We are in the process of transitioning a scaled down, AVHRR based, version of the GOES-R ash products to the University of Alaska - Fairbanks. UAF is well positioned to provide products to the Anchorage VAAC with low time latency.AVHRR Transition status: we are working through some data format issues.

Soufriere Hills - Aqua MODIS 2/12/2010 05:30 UTC

Redoubt - Aqua MODIS 3/26/2009 22:40 UTC

NEW VISIT TELETRAINING MODULESNow on Visit Training Calendar!

Some recent CIMSS Satellite Blog posts relevant to GOES-Rhttp://cimss.ssec.wisc.edu/goes/blog/archives/5092 (SRSO OPERATIONS FROM GOES-13)http://cimss.ssec.wisc.edu/goes/blog/archives/4831 (USE OF NEAR-IR ABI CHANNELS)http://cimss.ssec.wisc.edu/goes/blog/archives/4716 (CIRRUS DETECTION ABI CHANNEL)http://cimss.ssec.wisc.edu/goes/blog/archives/4777 (NEARCAST CONVECTION W/ SOUNDER WV DATA, ECLIPSE ISSUES)http://cimss.ssec.wisc.edu/goes/blog/archives/4624 (CONVECTIVE INITIATION)http://cimss.ssec.wisc.edu/goes/blog/archives/4920 (DETECT BLOWING DUST WITH 12-MICROMETER DATA)

Forecast Sky Cover Product Provided to National Weather Service AWIPS24-hour forecast sky cover (%) from CRAS valid 00UTC April 5, 2010. The Graphical Forecast Editor (GFE) used by NWS forecasters requires forecast sky cover grids which are not generated by NWS models at this time.(Courtesy of Robert Aune)The Cooperative Institute for Meteorological Satellite Studies (CIMSS) is using the the CIMSS Regional Assimilation System (CRAS) to generate a forecast sky cover product in real-time for the National Weather Service (NWS) AWIPS.

Sky cover is computed using a combination of CRAS forecast cloud mixing ratio, forward calculated radiative transfer and spherical geometry. Accuracy of the product is dependent on the use of GOES sounder cloud and water vapor products to initialize clouds in the CRAS.

Forecast satellite imagery and sky cover (shown at right), are transmitted every 12 hours to a website (http://cimss.ssec.wisc.edu/cras/) and to NWS AWIPS for evaluation.24-hour forecast 11 micron image from CRAS valid 00UTC April 5, 2010. Validating IR image from GOES-13 valid 00UTC April 5, 2010.

6-hour NearCast for 2100 UTCLow to Mid level Theta-E Differences6-hour NearCast for 2100 UTCLow level Theta-ERapid Development of Convection over NW Iowa between 2000 and 2100 UTC 9 July 2009Using the GOES-12 Sounder to Nearcast Severe WeatherThe CIMSS Near-casting Model uses hourly GOES Sounder retrievals of layered precipitable water (PW) and equivalent potential temperature (Theta-E) to predict severe weather outbreaks up to 6 hours in advance!

Hourly, multi-layered observations from the GOES Sounder are projected forward in time along Lagrangian trajectories forced by gradient winds. Trajectory observations from the previous six hours are retained in the analysis. Destabilization is indicated when theta-E decreases with height.

Limitations: - Sounder channels support only two layers for near-casting - Only useful for elevated convection Sounder cant detect low-level moisture - Frequent false alarms Sounder cant detect inversionsVertical Theta-E Differences predict complete convective instability by 2100 UTC. Severe thunderstorms occurs as predicted!Robert Aune (NESDIS) and Ralph Petersen (CIMSS)Low-level Theta-E NearCasts shows warm moist air band moving into far NW Iowa by 2100 UTC.One Example of a Successful Near-cast

A Hyper-Spectral Geo-Sounder Will Near-cast Severe Weather An Observing System Simulation ExperimentA WRF model simulation of the June 12, 2002 IHOP case was used to generate simulated radiances from a GOES-R Advanced Baseline Imager (ABI) and a geostationary Hyper-spectral Environmental Sounder (HES). Simulated radar reflectivity was also generated

Temperature and moisture profiles were retrieved from the simulated radiance datasets and assimilated by the CIMSS Near-casting Model and compared.Robert Aune (NOAA/NESDIS)5-hour NearCast for 2000 UTCLow level Theta-E5-hour NearCast for 2000 UTCLow to Mid level Theta-E DifferencesNegative vertical Theta-E differences indicate where convection is likely. Rapid Development of Convection over Texas and Nebraska between 2000 and 2100 UTC 12 June 2002Strong low-level Theta-E gradients are indicated by HES which has the ability to detect low-level moisture.5-hour NearCast for 2000 UTCLow to Mid level Theta-E DifferencesNegative vertical Theta-E differences indicate where convection is likely. 5-hour NearCast for 2000 UTCLow level Theta-EWeak gradients of low-level Theta-E are indicated by ABI which has only two water vapor channels.Simulated ABISimulated HESSimulated composite reflectivity indication the formation of convection.

GOES-15 First Visible imageshttp://www.ssec.wisc.edu/media/spotlight/goes15/http://cimss.ssec.wisc.edu/goes/blog/archives/5005http://www.noaanews.noaa.gov/stories2010/20100407_goes15.html http://www.nasa.gov/mission_pages/GOES-P/news/first-image.htmlhttp://cimss.ssec.wisc.edu/goes/blog/archives/5045http://rammb.cira.colostate.edu/projects/goes-p/ SounderImager

GOES-13 Operational East!http://cimss.ssec.wisc.edu/goes/blog/archives/5116

GOES-11 sees a Meteor?http://cimss.ssec.wisc.edu/goes/blog/archives/5167

*1. Storm Reports (top right) from the Storm Prediction Center indicate severe storms that were observed on February 10, 2009.2. The image below shows a 4-hour nearcast of de-stabilization forming in Central Oklahoma. Larger values of instability (mm differences) indicate a greaster potential for severe weather. Precipitation products from NWP models tend to show patterns that are quite board and much smoother than observed. In addition, the source of moisture for the precipitation is often misrepresented i.e., the precipitation forms for the wrong reason and/or the precipitation patterns become driven by the convective parameterizations themselves, not by details in the observed local moisture and wind fields.

In the case shown, the rapid convection developed only in the area where the 6 hour NearCasts showed strong signatures of Convective Instability in far NW IA a fact that was lost to forecasters using the NWP guidance lone. It should also be noted that no GOES observations were available here after the convection began, although the destabilization shown in the NearCasts proper predicted the subsequent movement of the MCS.

It should also be noted that NWP models typically limit the amount of convective instability that can be present in the models. In fact, the role of the convective parameterizations is not be produce realistic thunderstorms, but rather to remove excessive thermal instabilities and vertically misplaced latent heating which could adversely affect the model during an extended prediction. For example, the ECMWF readily recognizes the its convective schemes cause rainfall to occur too early during daytime over land in the tropics (they detect instability and try to remove it to quickly) and that the rainfall is unrealistic in that it starts and stops much to often during the afternoon (due to repeated cycles of stabilization, followed by surface heating and destabilization). In addition, once the convective parameterization has been active for a period of time (even if incorrectly), boundary layer flows produced as a result of the parameterization often become dominant in the area around the storms, leading to further forecast errors.Precipitation products from NWP models tend to show patterns that are quite board and much smoother than observed. In addition, the source of moisture for the precipitation is often misrepresented i.e., the precipitation forms for the wrong reason and/or the precipitation patterns become driven by the convective parameterizations themselves, not by details in the observed local moisture and wind fields.

In the case shown, the rapid convection developed only in the area where the 6 hour NearCasts showed strong signatures of Convective Instability in far NW IA a fact that was lost to forecasters using the NWP guidance lone. It should also be noted that no GOES observations were available here after the convection began, although the destabilization shown in the NearCasts proper predicted the subsequent movement of the MCS.

It should also be noted that NWP models typically limit the amount of convective instability that can be present in the models. In fact, the role of the convective parameterizations is not be produce realistic thunderstorms, but rather to remove excessive thermal instabilities and vertically misplaced latent heating which could adversely affect the model during an extended prediction. For example, the ECMWF readily recognizes the its convective schemes cause rainfall to occur too early during daytime over land in the tropics (they detect instability and try to remove it to quickly) and that the rainfall is unrealistic in that it starts and stops much to often during the afternoon (due to repeated cycles of stabilization, followed by surface heating and destabilization). In addition, once the convective parameterization has been active for a period of time (even if incorrectly), boundary layer flows produced as a result of the parameterization often become dominant in the area around the storms, leading to further forecast errors.