|First Name||Last Name||Affiliation||Abstract Title:||Abstract:|
|Jared||Allen||NWS Austin/San Antonio, TX||Increasing Situational Awareness of River Flooding by Applying a GIS Extent Mapping Approach||Situational awareness of river flooding events and their evolution is critical for emergency management resource allocation, decision making, and overall public alertness. Currently, however, National Weather Service (NWS) mapping efforts for flood extents per gage site can equate to $10,000-50,000 and six months to 24 months of resource expenditures before finalization. To offset these high costs, an experimental GIS method for deriving river flood extents has been developed in partnership with the Corps of Engineers. Through a GIS protocol and the use of the Flood Estimation Simulation Model (FESM), early results indicate near 70-95% accuracy and completion times on the order of days, if not hours. Spatial correlations using the kappa coefficient statistic show quality-controlled flood extents to have substantial to near perfect agreement with NWS Advanced Hydrologic Prediction Service (AHPS) standards (0.70 – 0.99). Furthermore, in testing this technique, we have shown that flaws exist within the existing AHPS flood extent libraries. This technique has proven to save resources in an operational setting, and through the use of dynamic web maps, has increased internal and NWS core partner situational awareness during river flooding episodes.|
|Brian||Ancell||Texas Tech University||The Use of Forecast Sensitivity to Improve High-Impact Ensemble Forecasts|| Ensemble-based sensitivity analysis can reveal important weather features early in a forecast window relevant to the predictability of high-impact events later in a forecast. This leads to a number of sensitivity-based applications that might improve operational forecasts of specific events such as observation targeting and ensemble subsetting. Here we examine ensemble subsetting, which compares all ensemble members to observations early in the forecast window in regions of large forecast sensitivity. The hypothesis tested here is that ensemble members that possess the smallest errors in sensitive regions should be more skillful than the full ensemble. Operationally, this procedure can typically be performed prior to the next assimilation cycle that incorporates observations to initialize extended forecasts, adding valuable lead time to predictions of high-impact weather.|
The ensemble subsetting technique is tested on land-falling midlatitude cyclones over a full winter season using simulated observations. Subsets of 8-15 members produces the smallest errors, and results are sensitive to the threshold used to define large sensitivity (e.g. whether the largest 50% or largest 90% of sensitivity values are used in comparisons with observations). The subsetting approach is also explored within a severe convective case in the Great Plains to understand whether large nonlinearity reduces the technique's usefulness. Based on these results, plans for integrating ensemble sensitivity analysis into the 2016 HWT Spring Experiment are discussed.
|Andrew||Arnold||NWS Midland||Tropical Cyclone Odile: Historic Flooding within a Long-Term Drought||A significant, high–impact flood and flash flood event took place in late September 2014 across much of West Texas and southeast New Mexico. Tropical Cyclone Odile made landfall on the Pacific coast of Mexico and moved slowly across the Southwestern U.S. This system brought repeated rounds of heavy rainfall to the Permian Basin and Trans Pecos of Texas producing a year’s worth of rainfall in a short period of time. Heavy rain led to several hydrologic milestones including record river crests on the Colorado and Pecos Rivers and substantial water rises on area reservoirs. This event helped put a considerable dent, but did not end, a multi–year drought across the region. This study will examine the impact of historic, heavy rains on an area in a long–term drought, the unusual track of Tropical Cyclone Odile through New Mexico and Texas, and summarize the challenges that came with such a rare event.|
|Andrew||Arnold||NWS Midland||Finding a Needle in a Haystack: Utilization of a West Texas VOST for Social Media Monitoring During Hazardous Weather||Social media has become an important part of National Weather Service (NWS) operations, but data mining can be an overwhelming task given a large forecast area, inconsistent volumes of unfiltered reports during an event, or emergent/colloquial descriptors that can “hide” ground truth reports from NWS social media operations. Virtual Operations Support Teams (VOST) can be one way to utilize social media in National Weather Service offices and are designed to incorporate emerging communication tools to collect and filter pre-, during, and post-incident information, especially in regions where forecast area size, population, or both create challenging conditions for data mining.|
In Fall 2014, the National Weather Service offices in Midland and Lubbock began a partnership with Texas Tech University to create a VOST. The West Texas Virtual Operations Support Team (WTXVOST) utilizes the social media expertise of atmospheric science and mass communications students at Texas Tech University to provide additional situational awareness to local National Weather Service offices during hazardous weather. Training and a practice VOST activation were held in March 2015, with the WTXVOST’s first real-time event occurring in April 2015. Active promotion of the #WTXSpotter hashtag to provide additional visibility for reports has also been conducted by the NWS Midland and Lubbock offices. In addition to providing hazardous weather support to the National Weather Service, the model for the WTXVOST is designed to demonstrate the availability of ground truth information on social media to assist with NWS warning operations, especially in regions that may be considered “data sparse”.
|Mark||Benoit||Texas A&M University||Sensitivity of High-Resolution WRF Forecasts to Radiosonde Observations over Central TX||The contiguous USA has around 70 upper-air sites, where weather balloon launches are done twice every day. Often, the separation between radiosonde observations (RAOBs) can be several hundred kilometers, which presents a problem to forecasters, who rely not only on modeled fields, but on Skew-T Log-P diagrams from a model to accurately predict the weather, especially in high impact situations. At Texas A&M, the Student Operational Upper-air (SOUP) program launches balloons when the Houston, Dallas/Ft. Worth, Austin/San Antonio NWS, or even the Storm Prediction Center (SPC) requests a launch. These supplementary RAOBs have proven useful to forecasters, as the closest upper-air site is more than 250km away. Would they, however, provide forecast value to a model since they are one of the main sources of assimilated data? Upper-air observations, especially midlevel moisture, are not perfectly known, which presents uncertainty in forecasts. Assimilation of these single sounding located at Texas A&M may improve a high-resolution forecast. About thirty RAOBs from different dates will be assimilated, and high-resolution WRF simulations will be done using WRFDA. A simulated reflectivity comparison with real data is one way that differences in model fields are seen most readily, but other fields, such as mid-level humidity and winds will also be helpful in this assessment. If a single point in this upper-air hole proves beneficial, realtime assimilation of these infrequent data points into the Texas A&M WRF could be implemented for use to forecasters.|
|Chris||Birchfield||Social Media Program Manager, National Weather Service Brownsville/Rio Grande Valley||Going Viral: NWS Brownsville/Rio Grande Valley Social Media Partnerships Prepare Tens of Thousands of Residents for Hazardous Weather||Many communities of the Rio Grande Valley are vulnerable to weather hazards, often which fall short of National Weather Service (NWS) warning thresholds. NWS Brownsville/Rio Grande Valley fills the gap effectively by providing plain-language information on impending weather threats and potential impacts with frequent notifications through social media. NWS Brownsville supplements weather hazard information on social media with a mix of fun and educational posts on weather-related topics that often focus on the region’s unique culture, where storytelling and family conversation is treasured. We often post in English and Spanish to increase audience reach, and have developed strong relationships with traditional media partners who help amplify critical weather information through their heavily followed pages. Crowdsourcing techniques are also used to increase information sharing from the community; these techniques provide a trove of hazardous weather verification that until recently required time and diligence to retrieve, often well after the threat had passed.|
Our presentation will describe these and other successful techniques that have increased our followers, particularly on Facebook, to become an office with some of the highest number of followers, by population, along the Gulf and Atlantic coasts - and how other government offices with public safety missions can apply similar techniques with their communities to rapidly grow their social media presence.
|David||Bonnette||Texas A&M University||Clear Lake Texas Extreme Rain Event Case Study||On May 12th 2015 between 7-12 inches of rain fell in 3-5 hours between 9PM-2AM CDT in a localized area of Clear Lake City, Texas, a suburb 15NM southwest of Houston, Texas. This 100-year rainfall led to flash flooding resulting in one fatality, property damage, major traffic delays and over 20 water rescues during the morning commute into the city of Houston. A supercell developed earlier in the day along the Galveston Bay which then moved only ~20 NM in 10 hours. This case is unique in that several additional precipitation bands developed just off the Gulf Coast with a NE movement of ~15 kt, overtaking the existing supercell, seemingly without diminishing its intensity. This begs the question; why did storms in a similar environment have such different characteristics? This study explores this question using observed and model soundings as well radar data from surrounding radars. Radar data indicated the Clear Lake supercell's heights extended roughly twice as high as the precipitation bands from the Gulf of Mexico. This likely allowed the supercell to experience a deeper mean layer shear thus exhibiting a different storm motion as it was affected by the increased vertical shear. A combination of linear updraft-in-shear effects on new updraft growth and a slower storm motion over the deeper cloud depth are hypothesized to have contributed to the supercell's longevity and slower motion. The resulting near-stationary movement combined with the rainfall from the more transient shallow precipitation bands to cause historically high rainfall amounts to fall in such a short period of time.|
|Trevor||Boucher||NWS EWX||The Supplemental Assistance Volunteer Initiative (SAVI) Team||Additional co-authors: Aaron Treadway, WFO EWX; Morgan Barry, WFO MOB|
The Virtual Operations Support (VOS) concept provides virtual aid through social media and other communication technologies to support operations that may be overwhelmed by the high volume of data generated in a disaster. While originating in the Emergency Management (EM) community, straightforward application can be made to operational meteorology during high impact weather events.
When faced with information overload, it becomes extremely difficult for a Weather Forecast Office (WFO) to efficiently extract information and simultaneously handle clear, consistent messaging, disseminate short-fuse products, and address EM, Media, and public concerns. In fact, a common need for improvement is clear and concise messaging through social media. However, the most common barrier to improvement is a lack of available staff to dedicate to these services.
The National Weather Service consists of 122 WFOs. On any given day, WFOs could be busy handling the workload associated with high impact weather threats. However, other WFOs across the country are not, and could potentially be available to monitor the situation and assist with communications. In fact, these meteorologists at other WFOs, also savvy with social media interactions, not only offer an untapped source of assistance, but of expertise.
The obvious connection of need with capability is the inspiration for the NWS Supplemental Assistance Volunteer Initiative (SAVI) Team. The team is comprised of social media savvy, meteorologists from across the country, that can be activated by request from a WFO anticipating high impact weather operations. The SAVI team leverages the expertise of the national workforce, by having remote WFOs supporting each other and lightening the social media workload of the affected WFO. This allows the affected WFO to concentrate on other aspects of the NWS mission including outgoing messaging, decision support services, or other areas where manpower is needed.
|Armani||Cassel||Texas A&M University||Comparison of Texas A&M WRF convection-allowing forecasts with other high-resolution models||The Weather Research and Forecast Model running at Texas A&M University was established in the 2015 Summer Student-Operational ADRAD Project (SOAP) and operates with a 3-km resolution from 12-km North American model initial conditions. As a new implementation of WRF, comparisons must be made to add perspective to its abilities. Within TAMU WRF model runs, qualitative and quantitative comparisons are made between itself and computer models like the High-Resolution Rapid Refresh (HRRR) model for notable types of weather events in Texas. The relative performance of each model will be assessed through comparisons to local observations. Storm modes for record flooding rains in Houston and storm track for Tropical Storm Bill are examples of cases used to assess the model forecasts of high-impact events. Additional visualization methods will be employed for a three-dimensional display of model comparisons with surface observations.|
|Nick||Fang||The University of Texas at Arlington||An Application of Dynamic Moving Storms (DMS) Generator on Flood Risk Analysis for the Brays Bayou Watershed in Houston, Texas||Challenges of fully considering the complexity among spatially and temporally varied rainfall always exist in flood frequency analysis. Conventional approaches that simplify the complexity of spatiotemporal interactions generally undermine their impacts on flood risks. A previously developed stochastic storm generator called Dynamic Moving Storms (DMS) aims to address the highly-dependent nature of precipitation field: spatial variability, temporal variability, and movement of the storm. The authors utilize a multivariate statistical approach based on DMS to estimate the occurrence probability or frequency of extreme storm events. Fifteen years of radar rainfall data is used to generate a large number of synthetic storms as basis for statistical assessment. Two parametric retrieval algorithms are developed to recognize rain cells and track storm motions respectively. The resulted parameters are then used to establish probability density functions (PDFs), which are fitted to parametric distribution functions for further Monte Carlo simulations. Consequently, over 1,000,000 synthetic storms are generated based on twelve retrieved parameters for integrated risk assessment and ensemble forecasts. Furthermore, PDFs for parameters are used to calculate joint probabilities based on 2-dimensional Archimedean-Copula functions to determine the occurrence probabilities of extreme events. The approach is applied to the Brays Bayou watershed in Houston Texas for the 2015 Memorial Flood and the generated results are compared with those from traditional rainfall frequency studies (i.e. Intensity-Duration-Frequency curves, and Areal Reduction Factors).|
|Nick||Hampshire||NWS WFO Austin/San Antonio||Environmental Conditions Conducive for South-Central Texas Heavy Rainfall Events||Heavy rainfall in South Central Texas causes numerous flash floods, which makes this weather hazard the leading cause of weather-related deaths in this area. A number of atmospheric parameters were examined to better understand the atmospheric ingredients that precede heavy rain events. Fifty days with at least one report of six inches or greater rainfall within the National Weather Service Austin/San Antonio County Warning Area were identified between 2005 – 2015. Statistical results found distinct seasonal patterns for several environmental conditions. For example, in the fall and spring, precipitable water values appear to be correlated with the occurrence of heavy rain events when those values are two standard deviations or greater above climatological averages. In contrast, a threshold of precipitable water of two inches (50.8 mm) or greater was a better discriminator of heavy rain events in the summer. Other parameters, including the 500 hPa synoptic pattern, 850 hPa flow, diurnal characteristics, upwind propagation vectors, and the presence of surface boundaries will also be discussed and assessed for correlation.|
|Mike||Hardiman||NOAA/NWS El Paso, TX||“EPZwxNet” – Using the Raspberry Pi and Davis Vantage Pro2 Weather Stations to Fill Critical Observation Gaps|
The state of Texas shares a boundary with Mexico that is over 1,200 miles (1,931 km) in length, with several large bi-national population centers and smaller communities straddling the border. With respect to traditional surface-based in-situ meteorological observations (e.g., METAR and Synoptic observations), Mexico remains a “data sparse” region. However, several entities within the Mexican government operate various networks of weather stations. Several of these networks utilize GOES satellites for data transmission and are available for wider dissemination through the U.S. National Weather Service Hydrometeorological Automated Data System (HADS).
The most reliable network, known as EMAS (Estaciones Meteorológicas AutomáticaS), is operated by Mexico’s national weather service, Servicio Meteorológico Nacional (SMN). The network features 189 stations nationwide, including 29 in Mexican States which border Texas.
Other networks utilizing GOES data transmission include meteorological and hydrological stations operated by the Mexican Section of the bi-national International Boundary and Water Commission (IBWC/CILA) and the Comisión Nacional del Agua (CONAGUA). These stations measure streamflow along the Rio Grande and its Mexican tributaries, as well as precipitation within the Rio Grande Basin. Data from these stations is of high value for river stage forecasts along the Rio Grande.
Recently, the National Weather Service in El Paso, TX and the West Gulf River Forecast Center in Fort Worth, TX collaborated to identify hydrologic stations within northern Mexico and add them to the HADS stream. This effort then expanded to include all SMN EMAS stations in Mexican border states, and in states within the North American Monsoon region.
In addition, several Mexican border states now operate reliably, high-quality agricultural mesonets, including over 80 stations in the state of Chihuahua.
This presentation will describe the networks in more detail, along with their potential utility in meteorological analysis and forecasting.
|Kyungtae||Lee||Texas A&M University||Future Climate Change Impacts on Hydrological Droughts,|
Heatwaves, and Irrigation Water Demand in Texas
|With the changing climate, hydrologic extremes (such as floods, droughts, and heat waves) are becoming more frequent and intensified. Such changes in extreme events are expected to affect agricultural production and food supplies. This study focuses on the State of Texas, which has the largest farm area and the highest value of livestock production in the U.S. The objectives are two-fold: First, to investigate the climatic impact on the occurrence of future hydrologic extreme events; and second, to evaluate the effects of the future extremes on agricultural production. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over Texas river basins during the historical period, is employed for this study. The VIC model is forced by the statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four different scenarios in terms of Representative Concentration Pathway (RCP) (i.e. 2.6, 4.5, 6.0 and 8.5 w/m2). Analyses are carried out to identify how the frequency and the extent of the extreme events will be altered in the future. Heatwave frequency and extent are quantified using CMIP5 air temperature projections, while drought severity and areal extent calculated using VIC soil moisture outputs. The results suggest that a significant increase in the number of heatwaves and droughts will occur starting in the second half of the 21st century in Texas. In addition, the seasonal drought frequency will be shifted. Then, the effects of the predicted hydrologic extreme events on the irrigation water demand are investigated. It is found that future irrigation water demand over agricultural land will increase, especially along the Gulf coast. The results are expected to contribute to future water management and planning in Texas.|
|Peirong||Lin||University of Texas at Austin||WRF-Hydro-RAPID Performance in Predicting Recent Texas Hill Country Flash Floods||The WRF-Hydro-RAPID modeling framework is currently adopted by the National Flood Interoperability Experiment (NFIE) for national-scale flood forecasting at 2.67 million river reaches across the continental United States. However, model validation and improvements are still necessary before meeting operational flood forecasting goals. In this study, we will perform historical WRF-Hydro-RAPID simulations and evaluate the model’s performance in terms of predicting 20 selected flooding events from 2002 to 2015 in the Texas Hill Country and Balcones Escarpment, including the Austin and San Antonio metropolitan areas. This region is featured by complex terrain, soil characteristics, and increased urbanization of the Austin-San Antonio corridor, and it experienced high-frequency of flash floods in the past 15 years. |
Aiming to comprehensively assess the model capabilities and limitations, a variety of flood event types will be used, categorized as (1) slow rate of rise, (2) moderate rate of rise, and (3) rapid rate of rise. The flooding events cover a range of antecedent rainfall conditions and basin characteristics, from low to highly sloped, rural to urban, and with varying soil characteristics. In order to test precipitation uncertainties, the model will be tested with three precipitation datasets: (1) StageIV quantitative precipitation estimates (QPE), (2) Multi-Radar/Multi-Sensor (MRMS) native data, and (3) MRMS gauge-adjusted data. The overall model performances will be evaluated against several skill metrics. This current one-year project focuses on using historical model simulations in offline mode, but the results are extendable to the current collaborative NFIE efforts, which provides flood forecasting for the entire US at real time.
|Michael||Lyttle||Austin, TX VOST Group||Implementing the VOST Concept: The Austin and |
Travis County Experimental Model
|Austin and Travis County contain some of the highest percentages per capita of persons using social media, and following multiple severe weather events in 2015, it became apparent that additional social media support would benefit NWSFO San Antonio (EWX-New Braunfels) given the increased amount of severe weather-related social media traffic. Thus, an initiative was created between NWSFO San Antonio and @TravisCOSW to utilize the social media expertise of trained volunteers to provide the NWS office with an additional level of situational awareness during the warning decision process. This presentation will go over the experimental plan to utilize the VOST concept in the Austin metro and Travis County areas.|
|Jamison||McCarthy||Texas A&M University||Non-internet meteorological data reception for emergency and remote applications||It is almost assumed that high-speed internet protocol communications are available for the retrieval of meteorological data and charts. However, some situations still exist where this is not the case, such as smaller maritime vessels, remote expeditions, and after a significant disaster. We explore two technologies, the decades-old High-Frequency (HF) radio facsimile, and the very new aviation technology known as ADS-B (Automatic Dependent Surveillance-Broadcast). Both of these capabilities are free after an investment in receiving equipment, but are applicable in very different circumstances. In the case of HF Facsimile (HF-FAX), modern laptop/phone/tablet and digital radio technology has made reception much easier and less expensive than in the past. Necessary equipment is assembled and reception tests are performed for each, updating the community on the status of the utility of these technologies for operational or even recreational meteorological applications.|
|Andy||Patrick||NWS Lake Charles, La.||The Enhanced Hazardous Weather Outlook: A Texas Perspective||Authors: Andy Foster, NWS Springfield, Mo. ; Jason Schaumann, NWS Springfield, Mo.; Jim Maczko, NWS Grand Rapids, Mi.; Corey King, NWS Bismarck ND; Derek Deroche, NWS Central Region; Brian Walawender NWS Central Region; Jim Keeney NWS Central Region; Joohn Margraf NWS Twin Cities, Mn.; Ryan Cutter NWS Kansas City Mo, ; Andy Patrick, NWS Lake Charles, La.; Mark Mitchell NWS Kansas City, Mo, Tabitha Huntemann NWS MDL|
The Enhanced Hazardous Weather Outlook: A Texas Perspective
The National Weather Service has begun an initiative to graphically display web-based hazardous weather information to a diverse customer base. The Enhanced Hazardous Weather Outlook (EHWO) is a graphical decision support service that supports preparedness and response efforts prior to and during hazardous weather. The EHWO provides decision makers with convenient access to potential weather hazard information by graphically depicting the risk of weather hazards utilizing a tiered risk and awareness level scheme.
The national graphical EHWO goes beyond the traditional text Hazardous Weather Outlook by packaging risk-based, color-coded alert levels within an interactive geospatial interface and utilizing buttons. EHWO weather hazard types and risks are derived directly from the National Digital Forecast Database (NDFD) as well as national centers which conserve workload and promote office-to-office continuity. The EHWO also serves internal NWS operations by enhancing situational awareness and ensuring service consistency.
This presentation will first provide an overview of the prototype graphical EHWO. An explanation will be given on the generation and utility of the EHWO for weather hazards that frequently occur in Texas. The presentation will then conclude with future considerations to further expand on the utility of the EHWO as a decision support service.
Using the Bering Sea and Typhoon Rules to Generate Long-Range forecasts II: Predictability of Severe Weather
|The Bering Sea Rule (BSR) has been shown to be an effective long range forecasting tool. One can find 8-14 day and monthly forecasts of temperature and precipitation through the Climate Prediction Center. However, there are no forecast tools for looking at the possibility of severe weather past mid-range forecasts, or about eight days courtesy of the Storm Prediction Center. Computer models are also not able to forecast effectively beyond the seven to 15 day range in the PNA region, as dynamic predictability diminishes severely. Utilizing three important data collection points in the Pacific and over the continental United States, and the Bering Sea Rule, forecasts that perform better than climatology can be obtained. Using autocorrelation and fourier analysis of the PNA Index, we find a strong 20 to 30 day oscillation that would correspond to the BSR. These statistical techniques also show some promise for the identification of potential severe weather events beyond the dynamic forecasting range. Thus these forecasts would be of interest to the government, energy, agriculture, and other sectors in identifying the potential for severe weather. |
|Edmar||Ruano||Texas A&M University||Aerosol Optical Depth Measurements Using a Handheld Sun Photometer||As part of the Texas A&M Student Operational Aggie Doppler Radar Project (SOAP), photometry measurements were taken throughout the summer to measure aerosol optical depth (AOD), using handheld sun photometers. This study will explore the value of these measurements from relatively cost efficient instruments. During the observations, there was an interesting Saharan dust event from which data were collected. Results will be presented analyzing this case using this photometer data in addition to measurements from satellites and backwards trajectories of air parcels. Direct comparisons of AOD data during non-dust events from the sun photometer and satellite derived AOD products from the MODIS sensors on the NASA satellites Terra and Aqua will also be presented.|
|Michelle||Serino||Texas A&M University||Radar-detected Mesocyclone Tilt in Tornadic and Nontornadic Supercells||While supercell thunderstorms are the storms with the greatest potential of producing tornadoes, the majority of supercells do not produce tornadoes. This study builds a climatology of radar data to distinguish between tornadic and nontornadic supercells that will complement an idealized modeling study. Level- II Weather Surveillance Radar-1988 Doppler data were collected for isolated supercells in the contiguous United States from 2009 to 2014. This period was selected to overlap with the additional research data collected during the Second Verification on the Origins of Rotation in Tornadoes Experiment.|
From this initial climatology, low-level (LL) and mid-level (ML) azimuthal wind shear maxima are located (representing the LL and ML mesocyclones), and the horizontal distance between each maximum is calculated during the evolution of each supercell. It is expected that as the horizontal distance between the LL and ML mesocyclones increases, the likelihood and intensity of a tornado both decrease. Statistical analysis of the climatology and results from individual cases, including the dependence of separation between LL and ML mesocyclones on the environmental vertical wind shear from proximity soundings, will be presented.
|Nicholas||Smith||Atmospheric Science Group-Texas Tech University||Meteorological Impacts on Texas Wind Energy|| Wind energy is an increasingly important part of Texas’ energy portfolio as the amount of installed wind power production grows each year. A major challenge to the efficient integration and utilization of increased wind power production is accurately forecasting day-ahead power production. Rapid changes in wind speed, known as wind ramps, produce fluctuations in wind power generation that pose a challenge to grid operators, who must ensure that sufficient power is on the grid to satisfy demand, and to individual wind farms, which need to anticipate the amount of power that they can sell. Variations in wind speed are therefore a primary concern throughout the wind energy industry and an improved understanding of wind ramps and their predictability is essential for increasing wind energy’s presence on the grid. Icing events are another meteorological phenomenon that can impact wind power production, as turbines are shutdown when ice accumulates on the blades.|
This study will discus the impact of wind ramps and icing events upon wind power production and will present results from a study that used ensemble sensitivity analysis (ESA) was used to investigate synoptically forced wind ramp events in the Texas Panhandle. ESA calculates the linear regression of a scalar forecast metric with respect to a model variable at an earlier forecast time and can be used to identify atmospheric features that are relevant to wind ramp forecasting.
|Trenton||Spencer||Texas A&M University Department of Atmospheric Sciences||Low-level Wind Comparisons Using Multiple Sensing Technologies||Low-level winds were observed simultaneously by multiple technologies as a part of the Texas A&M Summer Student Operational ADRAD Project (Summer SOAP) hands-on research program. These include remotely-sensed winds from a Sonic Detection and Ranging (SODAR) instrument provided by Atmospheric Sciences Corporation and the Velocity Azimuth Display (VAD) profiles from an NSF Center for Severe Weather Research (CSWR) Doppler on Wheels (DOW) as well as VAD profiles from the fixed ADRAD. The wind profiles are matched to launches of radiosondes by SOAP to complete the comparison. The resultant time-matched datasets are compared for similarities and differences, and strengths and weaknesses of the technologies are explored.|
|Brittany||Toy||Texas A&M University||Comparison of the TAMU-WRF Simulated Reflectivity to Radar Observations||High-resolution, convection-allowing forecast models are able to provide realistic representations of precipitation, but verification of such forecasts are needed to determine their usefulness. This poster will present research comparing Texas A&M University's Aggie Doppler Radar (ADRAD) reflectivity to the Texas A&M University's Weather Research and Forecasting model's (TAMU-WRF) simulated reflectivity. In order to find similarities and differences, the authors will use multiple weather events that occurred within ADRAD's range and compare both products. TAMU- WRF was recently launched this summer and produces real time, 3-km resolution daily forecasts. ADRAD, which is located on top of the Eller Oceanography & Meteorology Building on the main campus of Texas A&M University, is an S-Band radar with a 1.5 degree beam width.|
A series of case studies comparing modeled and observed reflectivity will be presented for a variety of local meteorological events. Results verifying structure, location, and intensity of precipitation simulated by TAMU-WRF will be shown.
|Aaron||Treadway||National Weather Service||Southern Region Severe Thunderstorm Impact Based Warning Tag Verification|| On April 1, 2015, nineteen Southern Region NWS Forecast Offices, as well as 48 other NWS offices across the country, began issuing impact based warnings (IBW) for tornadoes and severe thunderstorms. In addition to new impact statements within the warning product itself, warning tags indicating the magnitudes of hail and wind as well as the tornado threat were added to the footer of the warning. For overall verification purposes, a severe thunderstorm warning is verified if there is at least one local storm report that meets or exceeds the criteria for a severe thunderstorm (57 mph wind or 1 inch hail). The severe thunderstorm tags now present a new potential for verification, comparing the listed wind and hail magnitudes with that observed based on the local storm reports. This means that probability of detection and false alarm ratio now have two lenses to be examined with: overall verification and IBW verification. Other trends are important to note as well, for example, how tags in a warning change with each successive severe weather statement for an event, based either on radar or storm reports. In addition, the frequency of various tags could be an indication of an office’s severe weather climatology. These various statistics and measures of success are summarized over the first six months of the IBW program for the participating Southern Region offices. The results are valuable to social scientists and forecasters alike as more offices, including the remaining Southern Region offices, are now issuing impact based warnings. As the National Weather Service as a whole works to better inform the public about severe weather hazards, verification of the impact based warnings tags will become key as the program continues.|
|Gang||Zhao||Texas A&M University||Survivability of Megacities Under the Impacts of Future |
Drought and Population Growth
|Located at the transitional boundary between the humid east and semiarid west, Texas is extremely vulnerable to drought events. To mitigate drought impacts, and to meet the needs from the increasing water demand due to a fast growing population, a number of reservoirs have been constructed during the past 60 years. However, due to global warming, the climate in Texas is expected to become more variable - which can dramatically exacerbate the losses under drought conditions. This presents a great challenge to urban areas, especially megacities with large populations. Using the City of Dallas as a pilot study, the combined effects of future droughts and water demand on water supply reliability were evaluated. An ensemble of downscaled General Circulation Models (GCMs) outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were utilized to quantify future meteorological droughts. The Palmer Drought Severity Index (PDSI) was employed to evaluate the drought patterns, and to select possible severe meteorological droughts in the future. These droughts were then simulated with a fully distributed hydrologic model, which has a multi-purpose reservoir module. Results show worsened drought conditions in the future, especially in the second half of the 21st century. Meanwhile, using Monte-Carlo simulations, water demand is projected to continuously increase from 430 million gallon per day (MGD) in 2010 to 820 MGD by 2090 (uncertainty ranges from 580 MGD to 1200 MGD). Together, there is a significant decline of reservoir storage during drought events, which substantially reduces the water reliability of the city’s water supply system.|
|Long||Zhao||Department of Geological Sciences, University of Texas at Austin||Global Soil Moisture Estimation by Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4–DART System||Initial conditions with accurate soil moisture are expected to improve weather forecast. Land data assimilation is proven to produce superior soil moisture estimates. However, very few frameworks exist that estimate global-scale soil moisture through microwave land data assimilation (DA). Toward this goal, we have developed such a framework by linking the Community Land Model version 4 (CLM4) and an empirical radiative transfer model (RTM) with the Data Assimilation Research Testbed (DART). The deterministic Ensemble Adjustment Kalman Filter (EAKF) within the DART is utilized to estimate global multi-layer soil moisture by assimilating Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature observations. A 40-member CAM4 (Community Atmosphere Model version 4) reanalysis is adopted to drive the same number of CLM4 simulations and space-specific time-invariant microwave parameters are pre-calibrated to minimize uncertainties in RTM. Evaluations against global in-situ soil moisture measurements including the West Texas Mesonet dataset suggest that the newly established framework improves over the open-loop CLM4 simulations. While constant refinement will be applied to the CLM4-DART DA system, this framework is flexible with input observations and can be easily configured to assimilate multi-platform obtained satellite data including SMAP, GRACE, and MODIS, etc.|