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Home My WebLink Aboutbocc.con.amended.025.25 A-18/30/2021 CDD Contract Information Contract Number Project Name Contractor Budget Line Item 40451100.531000 Procurement Method: Type: Contract Start Date Contract End Date Contract Type Retainage If this is a new contractor, please enter the New Vendor information into Munis for workflow approval. Contact Information: Department County Representative Diane Jackson County Representative Phone (970) 429-1880 Provide a brief description of the Contract or Change Order: Contract Value Summary: $ 125,000.00 $ - $ - $ 125,000.00 025.25 A-1 Pitkin County Procurement Cover Sheet Please complete the Contract Cover Sheet when the contract/task order is complete and fully executed. Return all Contract Cover Sheets and Contracts/Change Orders/Amendments/Task Orders to Procurement No ASE Wind Study University Corporation for Atmpospheric Research $125,000.00 Additional Budget Line Item(s) (Please fully allocate New Contract Total) $- $- $- $125,000.00 Formal Services/Maintenance 10/13/2025 10/12/2026 Task Order Airport Task Order to perform a wind study and analysis at the airport. Original Contract Amount Previous Change Order/Amendment Amount This Change order/Amendment amount Contract Total Master Service Agreement #: 025.25 Rev: 2018-10-10 btf 1 TASK ORDER Task Order/Project Name: Aspen/Pitkin County Airport Winds Project Study Task Order Number: 025.25 A-1 Task Order Budget Line Item: 40451100.531000 OWNER: CONTRACTOR: Pitkin County University Corporation for Atmospheric Research Diane Jackson – Airport Arnaud Dumont and Larry Cornman 0233 E Airport Road 3090 Center Green St. Aspen, CO 81611 Boulder, CO 80301-2252 Phone: (970) 429-1880 Phone: (303) 497-8434 diane.jackson@aspenairport.com dumont@ucar.edu, cornman@ucar.edu, cc: fedaward@ucar.edu PROJECT NAME: ASPEN/PITKIN COUNTY AIRPORT WINDS PROJECT STUDY START DATE: October 13, 2025 END DATE: October 12, 2026 The Aspen/Pitkin County Airport Winds Project (the “Agreement”) dated August 1, 2025 between the Board of County Commissioners of Pitkin County (the “County”) and University Corporation for Atmospheric Research 3090 Center Green St. Boulder, CO 80301 (the “Contractor”), shall include the following services. 1.Contractor’s Obligations. Contractor shall provide the services described in the attached Statement of Work (“Attachment A”) dated 8/1/2025. The services provided pursuant to this Task Order are not subject to Section XXVII of the Agreement. 2.Compensation and Expenses, Invoicing, Payment and Offset. The County shall compensateContractor for its services in accordance with the Project Budget and Schedule set out in Paragraph 1 of this Task Order. It is expressly understood and agreed that in no event will the total compensation and reimbursement to be paid hereunder exceed the sum of One HundredTwenty-Five Thousand dollars and Zero cents ($125,000.00) for all services rendered. By TaskOrder or Task Order Amendment, the County and Contractor may reallocate the budget amongproject tasks if the total budget amount remains unchanged. Contractor shall invoice for the project monthly based on hours worked, with payment expected within thirty (30) days of invoice, but any payment by the County may be offset by any amount the Contractor owes theCounty for any reason. Master Service Agreement #: 025.25 Rev: 2018-10-10 btf 2 Any invoices not sent in the following manner may have payment delayed. All invoices for this Task Order shall reference Task Order 025.25 A-1 and Aspen/Pitkin County Airport Winds Project Study. Invoices shall be sent electronically in PDF format to ap@aspenairport.com. 3.Pitkin County’s Obligations. Pitkin County shall administer this contract through a CountyRepresentative. Diane Jackson, Airport Director will manage the project as the County’sRepresentative. The services provided and products delivered by the Contractor under thiscontract will be subject to review by the County’s Representatives, or a designee, for compliance with Contractor’s obligations prior to final payment. 4.Formation of Task Order. This Task Order is issued in accordance with the provisions of theAgreement. Contractor agrees to provide services subject to the terms of this Task Order andfor the avoidance of doubt this Task Order consists of the terms set out in the Agreement. In all other respects the Agreement is in full force and effect and remains unchanged by this TaskOrder. UNIVERSITY CORPORATION FOR ATMOSPHERIC RESEARCH ________________________________________________ !Kathie Sharp, Contract Admi#VENDOR SIGNATURE#! Date 10/13/2025 PITKIN COUNTY, COLORADO DIRECTOR APPROVAL: ________________________________________________ !#SECTION LEADER#! Date COUNTY MANAGER APPROVAL: ________________________________________________ !#COUNTY MANAGER#! Date Oct-14-2025 Airport Director Diane Jackson Oct-14-2025 Ryan Mahoney Deputy County Manager RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 1 PROPOSALS FORM Response Time: 2:00 PM MT Response Date: February 7, 2025 Pursuant to a request by the Pitkin County Commissioners, the undersigned Proposer, having examined this Request for Proposals (RFP), including the site of the proposed Service and being familiar with existing conditions including the availability of materials and labor, hereby proposes to furnish all labor, materials, supplies, applicable permits, services and supervision required to perform the Services as detailed in this RFP. Description: Proposer proposes to 1.Assess and Address Instantaneous Winds From: Anna Thomas UCAR Office of Contracts PO Box 3000 Boulder, CO 80307-3000 Phone (303) 497-2005 E-mail Address: althomas@ucar.edu To: ASPEN/PITKIN COUNTY AIRPORT WINDS PROJECT 0233 E Airport Road Aspen, CO 81611 Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 Attachment A RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 2 2. Propose Advanced Wind Shear and Turbulence Detection Technologies 3. Deploy Additional Wind Sensors Statement and Approach to Service: See detailed content in the Proposal Response document. The National Center for Atmospheric Research, Research Application Laboratory (NCAR/RAL) will provide technical support to the sponsors to help address the concerns about wind hazards at Aspen/Pitkin County Airport (ASE) and associated airspace. To produce actionable recommendations, NCAR/RAL intends to investigate the meteorological conditions – specifically wind regimes and the subsequent terrain interaction – that may result in the hazardous wind conditions. Due to the limited nature of this first phase, we plan on performing this investigation via a case study approach – as opposed to a more comprehensive climatological study. The cases will be selected by identifying potentially hazardous wind conditions encountered along the runway and the short departure and approach paths, via a combination of archived pilot reports indicating significant windshear and turbulence, surface meteorological data from the ASE ASOS (Automated Surface Observing System), and as available, known accident/incident scenarios. To support the case studies, data from the NOAA High Resolution Rapid Refresh (HRRR) model archives will be used. These data are available at a 3-km spatial and hourly resolution. Another set of supporting data will be lightning data from a ground based and/or space borne lightning detection system, to help ascertain whether convection was present. These data sets will then be used to generate an understanding of the general, and to some extent, local meteorological conditions associated with known wind-impact scenarios. An adjunct to the case study analyses will be assessing the application of Automatic Dependent Surveillance (ADS-B Out) reports. Given a better understanding of the meteorological regimes associated with wind hazards in the vicinity of the airport, NCAR/RAL will then investigate potential operational solutions. Three potential approaches come to mind: (1) a “wind information” system, which provides sensor data from which users can make operational decisions. This type of system does not “interpret” the weather for users but provides the data from which the users would make those decisions. (2) A “warning system” which provides users with actionable warnings specific to a given runway operation. Such a warning system could come in three sub-types, (a) a diagnostic system that uses sensor information along with “look-up tables” that have been pre-computed to connect sensor measurements to wind hazards; (b) a detection system that uses sensor measurements to calculate hazardous windshear and/or turbulence conditions and produce appropriate warning information; and (c) a hybrid detection-diagnostic system. The purpose of this task is to investigate which of these options might be best suited to the wind hazard situation at and around ASE, from a scientific and engineering perspective. An additional task of installing temporary wind sensors on and near the airport, and performing data analysis on those data, is also included. This effort will be highly beneficial, Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 3 as it addresses a recommendation from Section (2B) of the Aspen/Pitkin County Airport FlightOps Safety Task Force’s Spring 2023 report, “At a minimum, additional exploratory wind sensors should be installed as soon as possible to help us understand the conditions throughout the length of the runway even if these reports are not yet integrated into FAA displays and procedures.” This deployment also will generate essential data for the other tasks. NCAR/RAL has an in-house capability to deploy self-contained, all-weather, research- quality anemometers. We envision three possible locations, one at the north end of the runway (perhaps coincident with the existing ASOS site), one at the south end, and one at the radar site on top of Shale Bluffs. Data will be collected at a minimum of one sample per second, transferred to, and archived at NCAR in near real time. NCAR will work with local entities to site and deploy the sensors, and then operate, collect, and perform an analysis of the data. Qualifications of Proposer See detailed content in the Proposal Response document. The NCAR Research Applications Laboratory (RAL) has significant experience with developing and deploying wind hazard systems for airports and investigating aircraft incidents. Our capabilities include knowledge of the relevant atmospheric aspects, sensor systems, and algorithm development. Furthermore, RAL has wide-ranging experience working with the aviation user community, including pilots, airline and airport operators, air traffic controllers (control tower, TRACON, enroute, and traffic management), regulators, and aircraft manufacturers. Low-Altitude Convective Windshear Starting back in the early 1980’s RAL worked with the FAA to investigate adverse low altitude convective wind shears and their impact on aviation. RAL scientists and engineers developed the operational algorithms for the Low-Level Windshear Alert System (LLWAS), an anemometer-based system that is still used operationally in the US as well as at numerous airports around the world. RAL staff also worked closely with the FAA in the development and deployment of the Terminal Doppler Weather Radar (TDWR) system. RAL scientists also developed and fielded the first TDWR/LLWAS integration algorithms. A critical part of the success in solving the convective wind shear problem came from the work of a Wind Shear Users Group. This group, set up by the FAA, had members from all aspects of the user community (pilots, airlines, ATC, aircraft manufacturers, and regulator), as well as from the scientific and engineering community (NCAR/RAL, MIT-LL, NASA, NOAA, and university researchers). From those initial forays into aviation weather in the 1980s, RAL has maintained strong, ongoing relations with the broader user and research communities. Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 4 Low-Altitude Windshear and Turbulence Detection System: Hong Kong International Airport From 1993-1997, NCAR/RAL developed and deployed a low-altitude, terrain-induced wind shear detection and turbulence diagnostic system for the (at-the-time new) Hong Kong International airport. Based on the understanding of the windshear and turbulence conditions obtained during the feasibility and field deployment periods, and coordination with the relevant user community, RAL developed a diagnostic-based detection algorithm and warning system, the Operational Windshear Warning System (OWWS). The diagnostic algorithm was based on correlating the inflow conditions – as measured by the mountain-top anemometers and winds above the terrain provided by the wind profilers – with turbulence as measured by the research aircraft. The warning system integrated the diagnostic algorithm output with the outputs from the TDWR and LLWAS systems. The outputs from the warning system were provided on alphanumeric and graphical displays. The warning system and the display systems were developed in close coordination with the sponsor (at the time, the Royal Observatory) and the local user community. Low-Altitude Windshear and Turbulence Detection System: Juneau International Airport Following on with the success of the Hong Kong system, in the late 1990’s the FAA sponsored NSF-NCAR/RAL to consider a similar system for the Juneau International Airport. In a parallel fashion to the Hong Kong methodology, RAL performed a feasibility study for Juneau, including the deployment of airport and mountain-top anemometers, three Doppler wind profilers, a Doppler lidar, and an x-band Doppler weather radar. Three aircraft measurement field programs were also undertaken: two with research aircraft, and one with Alaska Airlines 737s flown in non-revenue (Part 91) mode. The Juneau Airport Winds (JAWS) system development was significantly more extensive than that for the Hong Kong system. This was due to the more complicated terrain and flight patterns. On the other hand, the approach taken in devising the warning system was similar, i.e., it is a diagnostic system. As with Hong Kong, turbulence measured by the research and Alaska Airlines aircraft was correlated with wind speeds, directions, and variations taken from the mountain-top anemometers and wind profilers. From these correlations, a system of regression equations was developed and used to drive the diagnostic system. Furthermore, as Juneau is a challenging weather environment for remote sensors, extensive work was done to harden the equipment and data (via qc algorithms). As in Hong Kong, a comprehensive effort was made to engage and coordinate with the user community – including at the local level (ATC, NWS, Part 121 and 135 operators), and at the national level (the FAA and congress). Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 5 Surface Wind Measurements NCAR scientists have been involved extensively in field deployments, particularly in regard to deploying surface-based sensors. Wind sensors are one of the most common sensors deployed as they are needed to help assess the general meteorological conditions at a given site. These sensor deployments have happened around the world, both domestically and internationally and include locations in Antarctica. Incident/Accident Investigations NCAR scientists also have a lengthy history investigating terrain-generated meteorological hazards, such as mountain waves, lee-waves, and low-level erratic winds. They have investigated the meteorological conditions surrounding a number of aviation accidents associated with terrain induced hazards, have evaluated weather conditions at airports located near precipitous terrain, and provided alert systems to aid in airport operations. Examples of situations analyzed include:  A large amplitude mountain lee wave above the Denver International Airport (DIA) likely generated the strong and unexpected crosswind gust that resulted in a departing commercial airliner deviating off the runway and crashing on 20 December 2008. This is discussed below,  The unmanned experimental aircraft, Helios, crashed into the ocean shortly after take- off from Kauai’s Pacific Missile Range Facility, likely due to turbulence associated with a terrain generated island wake,  Extreme clear air turbulence over the Rocky Mountains associated with a downslope windstorm resulted in structural damage, including the loss of an engine and part of a wing, of a DC-8 cargo jet. Because of NCARs extensive experience with mountain-induced aviation hazards, the FAA requested NCAR’s assistance in evaluating the potential benefit of incorporating weather information into FAA’s Precipitous Terrain classification, currently based solely on static terrain characteristics, which provides guidance over regions characterized by steep terrain or abrupt slopes. The resulting study focused on Aspen/Pitkin County, Eagle County Regional, and Leadville-Lake County airports in Colorado. During this project, NCAR/RAL scientists investigated atmospheric turbulence occurrences around the three mountain airports using PIREPs to identify their link to complex terrains, and analyzed METAR wind, temperature, and humidity data to characterize meteorological conditions in these regions that can adversely impact the performance of the current Precipitous Terrain classification based on static terrain information. Case studies using kilometer-scale numerical weather modeling were conducted to compare meteorological conditions between calm and turbulent cases in the airport regions. Diagnosing turbulence utilizing numerical model output NCAR/RAL scientists have extensive experience with diagnosing turbulence from numerical weather simulations/forecasts meteorological fields (wind, temperature, moisture, etc.) and Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 6 providing atmospheric measures of turbulence on a grid point by grid point basis. The approach NCAR/RAL scientists have developed and used is to compute a suite of indicators of turbulence (or diagnostics), e.g., vertical wind shear, horizontal wind shear, Richardson number (Ri) etc., and use these diagnostics to infer turbulence location and intensity, and also a likelihood of a certain turbulence intensity to occur. Various turbulence diagnostics have been developed that represent various sources of turbulence, including clear-air turbulence (CAT), mountain wave turbulence (MWT), convectively induced turbulence (CIT), and low- level boundary layer turbulence (LLT). Turbulence estimates using ADS-B Out reports In previous efforts related to low-altitude windshear and turbulence – the Juneau and Hong Kong Airport projects (described above) – data collected from research aircraft flights along the operational routes were used to correlate with ambient wind conditions. Unfortunately, the cost for fielding research aircraft is steep, and so alternate data collection approaches are preferable. One such approach is to use ADS-B Out reports. Over the past five years, the FAA has sponsored RAL to look into the feasibility of using ADS-B Out aircraft reports to estimate turbulence. Specifically, we are using the vertical rate parameter to estimate the energy dissipation rate (EDR), an aircraft-independent measure of turbulence intensity. The FAA efforts have been focused on aircraft-to-ground-station communication links. More recently, RAL has been contracted by Aireon, a private company that provides global access to ADS-B data using satellite data links. We refer to these data as spaced-based ADS-B, or SBA for short. Both efforts have been quite successful and both entities are moving towards operational demonstrations of the turbulence product. The advantage of ADS-B reports is that they are required for all aircraft in controlled airspace (at least for CONUS). This means that the data should be available from all aircraft flying in and out of ASE. Please insert names address, phone numbers and description of similar Service for Reference Checks. 1. Gary Pokodner – Weather Technology in the Cockpit (WTIC) Program Manager at FAA (202) 267-2786 Project Manager for Precipitous Terrain Classification and Mobile Met Adverse Winds 2. Stephanie DiVito - Program Manager in FAA Aircraft Icing (609) 485-7152 Project/Program Lead for Terminal Area Icing research and field campaigns requiring sensor deployments Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 7 3. QUALIFICATIONS OF PERSONNEL See detailed content in the Proposal Response document as well as full resumes (supplied as a separate document). Personnel #1. Larry Cornman - Project Scientist III Qualifications: Larry is a Project Scientist at the National Center for Atmospheric Research. His educational background includes undergraduate degrees in Mathematics and Physics from the University of California and a graduate degree in Physics from the University of Colorado. He started working at NCAR in 1983 in support of the FAA's Low Level Windshear Alert System (LLWAS). From 1983 to 1990, Larry was involved in the development of the Phase II and Phase III LLWAS algorithms and the Terminal Doppler Weather Radar (TDWR) algorithms. In 1989, he developed the TDWR/LLWAS Integration algorithms, for which he holds numerous U.S. and International patents. Since 1990, Larry's research focus has been on atmospheric turbulence. He has developed turbulence detection algorithms for remote sensors including ground-based and airborne Doppler radars, lidars and wind profilers; as well as developing a methodology for making in situ measurements of turbulence from commercial aircraft. Larry also has a significant amount of expertise in the aerodynamic impact of wind fields and turbulence on aircraft, as well in the development of signal and image processing algorithms. He holds four U.S. patents in this latter area. He has twice been the recipient of an Aviation Week and Space Technology magazine Laurel Award, a recipient of a NASA Turning Goals into Reality award, and was named to the 2003 Scientific American 50 list as Research Leader in Aerospace. See attached resume for more details List of similar Service performed:  Head of the algorithm development group for the Hong Kong OWWS project.  Original project manager and scientific lead for the FAA Juneau Windshear and turbulence project.  Project lead for the FAA’s ADS-B Turbulence Project.  Project lead for NASA’s Airborne Radar Turbulence detection project.  Original project lead for the FAA’s in situ Turbulence Measuring and Reporting project. Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 8 Reference Name, & Phone Number: Dr. Robert Goodrich, Professor Emeritus of Mathematics, University of Colorado, Boulder 720-438-0490 Personnel #2. Arnaud Dumont DitVoitel – Engineering Deputy Qualifications: Designer and developer of decision support systems and visualization tools for meteorological forecasting in aviation, surface transportation, energy, epidemiology, and riverbasin management. 30 years experience working directly with end users in various domains to understand operational requirements and develop software tools which address their analytical needs. Extensive experience designing and implementing data dissemination systems, including data processing, persistence, web services, and data exchange protocols. See attached resume for more details. List of similar Service performed:  Developed visualization and alert notification systems for the Juneau Airport Winds System (JAWS) 2002-2004  Led the Aviation Digital Data Service (ADDS) aviation weather website and application development 2007-2015  Led the MobileMet Minimum Weather Service Recommendations, Enhanced Depiction of Runway Winds, and Adapting Weather Information for Cockpits for the FAA’s Weather Technology in the Cockpit (WTIC) Program 2012-2020 Reference Name, & Phone Number: Gary Pokodner - Program Manager of FAA Weather Technology in the Cockpit (WTIC) (202)267-2786 Personnel #3. Dr. Wiebke Deierling - Project Scientist II Qualifications: Atmospheric scientist with over 20 years of experience on a variety of topics around aviation weather including turbulence and convection, and the development of operational weather support tools. Significant experience in research on aviation turbulence and enhancing turbulence diagnosis and prognosis algorithms as well as convection. See attached resume for more details. Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 9 List of similar Service performed:  Leading team to develop/improve turbulence forecasting and nowcasting capabilities as well as improve turbulence observations for the FAA’s Aviation Weather Research Program (AWRP). The team also serves as subject matter experts to the NTSB on turbulence incident investigations  Serves as a subject matter expert for the FAA on turbulence and lightning Reference Name, & Phone Number: Dr. Matthias Steiner - Director Aviation Applications Program in Research Applications Laboratory, NSF National Center for Atmospheric Research (303) 497-2720 Personnel #4. Dr. Scott Landolt - Project Scientist II Qualifications: Atmospheric scientist with nearly 30 years of experience deploying a variety of sensors, including anemometers, at federal, state and private locations, including airports. Extensive experience with sensor siting, deployment, and maintenance, and analysis of sensor data from all seasons. See attached resume for more details. List of similar Service performed:  Deployed sensors in Juneau, AK to develop correction factor for optical precipitation accumulation sensors, including wind as a component  Oversee the NCAR Marshall Instrument Field Site, where nearly a dozen wind sensors are deployed and have been operational for over 20 years  Serves as a subject matter expert for the FAA on weather observations and sensor capabilities Reference Name, & Phone Number: Stephanie DiVito - Program Manager in FAA Aircraft Icing (609) 485-7152 Personnel #5. Dr. Hailey Shin – Project Scientist II Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 10 Qualifications: Atmospheric scientist with over 15 years of research experience investigating atmospheric turbulence in the atmospheric boundary layer and in the upper atmosphere using high- resolution numerical simulations and various in-situ and remote sensing observations. Extensive experience in research and development of turbulence transport modules in multiple numerical weather models including the community Weather Research and Forecasting. See attached resume for more details. List of similar Service performed:  Performed analysis of the FAA’s precipitous terrain classification algorithm and characterization of weather conditions over complex terrains in Colorado for the FAA’s Weather Technology in the Cockpit (WTIC) Program 2019-2020  Performed research and development of probabilistic turbulence forecasting capabilities based on NOAA’s operational numerical weather forecasts in support of the FAA’s Aviation Weather Research Program (AWRP) 2020-2025  Performed turbulence forecasting and nowcasting as part of turbulence case studies in support of the FAA’s Aviation Weather Research Program (AWRP) 2024-2025 Reference Name, & Phone Number: Dr. Matthias Steiner - Director Aviation Applications Program in Research Applications Laboratory, NSF National Center for Atmospheric Research (303) 497-2720 Personnel #6. Dr. Teddie Keller – Associate Scientist IV Qualifications: Atmospheric scientist with over 30 years of research experience investigating mountain generated meteorological hazards and aviation turbulence. This includes analyzing observations, aircraft data, and high-resolution numerical model output. See attached resume for more details. List of similar Service performed:  Investigated the atmospheric conditions contributing to the crash of a Boeing 737 at Denver International Airport (DIA) on Dec. 20, 2008, at the request of the NTSB. Analyzed observations, pilot reports, and a high resolution, three-dimensional numerical simulation of the event to understand the surrounding meteorological conditions. Determined that the amplification of partially trapped gravity waves in the Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 RFP #: 025.25 Budget Line Item #: FAA & Airport General Funding 11 stable layer above DIA likely contributed to the cross-wind gustiness associated with the crash.  Identified days with significant aviation turbulence both for rigorous case study analysis and to assist the development and testing of turbulence diagnostics for use in operational turbulence prediction models. Performed meteorological analysis of numerous aviation turbulence encounters. Reference Name, & Phone Number: Dr. Matthias Steiner, Director Aviation Applications Program, NSF National Center for Atmospheric Research (303) 497-2720 It is further understood that the right is reserved by the County to reject any and all Proposals. The Proposer acknowledges receipt of Addenda Nos. . The right is reserved to waive any informalities and to reject any Proposal received for any reason. Dated this day of , 2025 (Corporate seal) PROPOSER: SIGNATURES: If the Response is being submitted by a Corporation, the Proposer should be signed by an officer, i.e. President or vice-president. The signature of the officer signing shall be attested to by the secretary and properly sealed. If the Response is being submitted by an individual or a partnership, the Response shall so indicate and be properly signed. Docusign Envelope ID: 79A138CA-CE55-41DA-8496-A0329B27C349 Anna L Thomas 2/5/2025 Manager, UCAR Contracts Aspen/Pitkin County Airport Winds Project Response to Request for Proposals NCAR Research Applications Laboratory (RAL) February 7, 2025 Proposed Approach and Task Descriptions From the Aspen/Pitkin County Airport FlightOps Safety Task Force’s Spring 2023 report, “Initial Report and Recommendations of the Aspen/Pitkin County Airport FlightOps Safety Task Force,” their stated mission is “to maximize safety and reduce aviation accidents and incidents at the Aspen/Pitkin County Airport (ASE) and associated airspace”. The purpose of this project is for the National Science Foundation’s National Center for Atmospheric Research, Research Application Laboratory (NSF NCAR/RAL) to provide technical support to the sponsors to help address these concerns. NCAR/RAL has the technical expertise and experience in providing practical solutions to a wide variety of aviation hazard scenarios. Specific to this project, we have a proven track record of investigating airport wind, wind shear, and turbulence problems due to complex terrain and convection, as well as devising, developing, and deploying user-centric information and warning systems. This project is considered as a first step in providing solutions for the ASE wind hazard problems. It would be unrealistic to propose a solution without understanding the meteorological and operational aspects which have contributed to past wind-related accidents and incidents. To produce actionable recommendations, NCAR/RAL intends to investigate the meteorological conditions – specifically wind regimes and the subsequent terrain interaction – that may result in the hazardous wind conditions. Due to the limited nature of this first phase, we plan on performing this investigation via a case study approach – as opposed to a more comprehensive climatological study. The cases will be selected by identifying potentially hazardous wind conditions encountered along the runway and the short departure and approach paths, via a combination of archived pilot reports indicating significant windshear and turbulence, surface meteorological data from the ASE ASOS (Automated Surface Observing System), and as available, known accident/incident scenarios. To support the case studies, data from the NOAA High Resolution Rapid Refresh (HRRR) model archives will be used. These data are available at a 3-km spatial and hourly resolution. Another set of supporting data will be lightning data from a ground based and/or space borne lightning detection system, to help ascertain whether convection was present. These data sets will then be used to generate an understanding of the general, and to some extent, local meteorological conditions associated with known wind-impact scenarios. An adjunct to the case study analyses will be assessing the application of Automatic Dependent Surveillance (ADS-B Out) reports. These reports can provide high-resolution observations of aircraft motion, without the need to install additional instrumentation on-board. NCAR/RAL has been sponsored by the FAA to develop turbulence detection algorithms from these data. That effort has been focused on enroute turbulence detection from Part 121 aircraft, but there is a strong interest and intention by the FAA to also consider GA and Part 135 aircraft. Given a better understanding of the meteorological regimes associated with wind hazards in the vicinity of the airport, NCAR/RAL will then investigate potential operational solutions. Three potential approaches come to mind: (1) a “wind information” system, which provides sensor data from which users can make operational decisions. This type of system does not “interpret” the weather for users but provides the data from which the users would make those decisions. (2) A “warning system” which provides users with actionable warnings specific to a given runway operation. Such a warning system could come in three sub-types, (a) a diagnostic system that uses sensor information along with “look-up tables” that have been pre-computed to connect sensor measurements to wind hazards. An example of this type is the Juneau Airport Wind System (JAWS) system in Juneau, AK, developed by NCAR/RAL, which uses anemometers and wind profilers along with regression algorithms to diagnose the turbulence along the approach and departure corridors; (b) a detection system that uses sensor measurements to calculate hazardous windshear and/or turbulence conditions, and produce appropriate warning information. Examples of this type are the RAL-developed FAA Low-Level Windshear Alert System (LLWAS; an anemometer-based network) and TDWR (Doppler radar) systems, or a Doppler lidar approach – such as used in Hong Kong; and (c) a hybrid detection-diagnostic system. The rationale behind such an approach is that each separate system has strengths and weaknesses, and a combined system can leverage those aspects to produce more comprehensive and accurate results. The purpose of this task is to investigate which of these options might be best suited to the wind hazard situation at and around ASE, from a scientific and engineering perspective. NCAR/RAL will provide a report detailing the results of the efforts described below. A set of recommended follow-on activities will also be provided. These activities could include further meteorological analysis (e.g. a more comprehensive climatology), fine-scale numerical turbulence and/or wind modeling, more case studies, and/or further data collection exercises. Furthermore, the recommendations will include guidance on viable approaches for operational implementation of wind information and/or wind hazard warning systems. It is anticipated that a follow-on effort, targeted at Aspen Airport’s prioritized hazard mitigation strategy, will be necessary to further refine the solution and implement an operational system. Throughout the project, NCAR/RAL will ensure that communication between the parties is maintained via telecons, status briefings, etc. NCAR/RAL will also work with the sponsor to investigate and participate in developing funding opportunities for follow-on efforts. An additional task of installing temporary wind sensors on and near the airport, and performing data analysis on those data, is also included. This effort will be highly beneficial, as it addresses a recommendation from Section (2B) of the Task Force report, “At a minimum, additional exploratory wind sensors should be installed as soon as possible to help us understand the conditions throughout the length of the runway even if these reports are not yet integrated into FAA displays and procedures.” This deployment also will generate essential data for the other tasks described below. NCAR/RAL has an in-house capability to deploy self-contained, all-weather, research-quality anemometers. We envision three possible locations, one at the north end of the runway (perhaps coincident with the existing ASOS site), one at the south end, and one at the radar site on top of Shale Bluffs. Data will be collected at a minimum of one sample per second, transferred to, and archived at NCAR in near real time. NCAR will work with local entities to site and deploy the sensors, and then operate, collect, and perform an analysis of the data. In the following subsections, a more detailed description of the three tasks mentioned above, is provided. Task 1. Assessing and Addressing Instantaneous Winds It is well known that airports located in mountainous areas are subject to a number of terrain- generated meteorological hazards, such as mountain waves, low-level erratic winds and turbulence, and strong downslope windstorms. The goal of this task is to gain a better understanding of the specific meteorological conditions influenced by the unique topography around the Aspen airport, which occasionally result in erratic winds and hazardous flying conditions along the arrival and departure paths at ASE. The approach is to perform case studies, i.e. identify and investigate specific days with particularly hazardous wind conditions. These days will be selected using a combination of pilot reports (PIREPs) of wind, wind shear, and/or turbulence for flights into and out of ASE, analysis of airport wind sensor data, and aviation accident reports. In parallel to the case studies, we will also hold informal discussions with a variety of airport users (e.g., pilots and ATC personnel) to augment our knowledge base with anecdotal information regarding the perceived wind related issues. These additional data could influence the focus of our study and the follow-on recommendations. Finally, we will investigate previous NTSB accident/incident cases, and if the appropriate data is available, perform case studies similar to those discussed above. Specific Work Elements for Task 1: 1. Select specific days with hazardous flying conditions for intense case study analysis using: a. NCAR’s archived pilot reports of wind hazards encountered during take-off and landings, as well as short final and departure, at ASE. In addition to turbulence intensity estimates, the added remarks in some of these reports add significant meteorological information, including identifying encounters of low-level wind shear (LLWS) and rapid speed changes. Example Pireps include: i. “ASE /TB MOD /RM LLWS +20 -15 KT SHORT FINAL RWY 15”, and “ASE /TB SEV /RM +-15KTS, 400FT AGL” b. Analyzing wind gustiness at ASE using NCAR’s archived high rate ASOS data, as well as data collected with the added anemometers deployed for this project (Task 3). c. Analyze cases based on past accident/incident scenarios in conjunction with wind and pirep data. 2. Analyze the meteorological conditions surrounding the specific case study days identified above, using: a. Local wind sensor data to identify days with significant gustiness. b. Hourly HRRR weather model with 3 km grid spacing, and model derived turbulence diagnostics, to assess larger scale wind patterns and sources. c. Pireps and in situ turbulence data at both lower and upper levels to assess the presence of deep atmospheric disturbances, such as mountain waves. d. Sounding data, satellite, and radar data. 3. Explore the feasibility of using archived ADS-B vertical data to calculate aircraft- independent turbulence information at low-altitudes. 4. Hold discussions with ASE users to gain a better understanding of the meteorological conditions that result in hazardous wind conditions. Deliverables for Task 1: • Perform an in-depth analysis of existing accident and incident reports, interviews with stakeholders of the airfield, review weather models and flight data from aircraft. • Provide a method to investigate airport wind, wind shear, and turbulence problems due to complex terrain and convection. • Produce data sets used to generate an understanding of the general and local meteorological conditions associated with known wind-impact scenarios. • Produce a set of case studies that incorporates all the data collected and informs the conclusions. • Identify existing operational procedures that may exacerbate wind related safety conditions at the facility and propose possible enhancements and implementable best practices. Task 2. Advanced Wind Shear and Turbulence Detection Technologies Considering wind hazards from an aircraft performance perspective, it is persistent airspeed variations that are of the most concern. That is, longitudinal changes in the wind (i.e. windshears) that occur over single-digit kilometer scales (say, 1-5 km, depending on the airspeed). Loss of lift due to a significant decrease in the headwind can lead to the inability to maintain a safe altitude during takeoff or landing. Alternatively, with an excessive headwind increase during landing, the inability to bleed off enough airspeed so as to maintain the glide slope, can result in a hard landing or an overshoot of the runway. From the aircraft stability and control perspective, small-scale, transverse wind variations (relative to the aircraft track) are the most pertinent. Specifically, vertical wind variations along the flight track, in the tens of meters to single-digit kilometer scales (<2 km, depending on airspeed) are most suited to inducing large aircraft responses (vertical displacements and accelerations, as well as pitch angle displacements). Variations in the vertical wind transverse to the flight track (e.g., variations of the vertical wind along the wing) can induce strong rolling motions. Based on the criteria presented above, one can see that an optimal system for real-time detection of windshear and turbulence along the approach and departure flight paths would require an all- weather sensor system (or multiple sensors) that can accurately measure 3-d winds along those flight paths; at a spatial resolution suited to aircraft response, and at a temporal resolution commensurate to the variability in the winds. Since a single, (or even multiple) sensor system does not exist that can completely satisfy these criteria, we look for single or multiple systems, perhaps combined with a diagnostic algorithm (driven by sensor data), that, while not perfect, are adequate for the operational needs. In previous R&D efforts, NCAR/RAL has investigated the utility of a number of sensors for low- altitude windshear and turbulence detection. A short list is provided below. • Anemometers Pros: (mostly) all weather; 2-d horizontal winds; rapid updates Cons: point measurements • Boundary layer Doppler wind profilers Pros: (mostly) all weather; vertical profile of 3-d wind; reasonable update rate Cons: susceptible to contamination (e.g., ground clutter, aircraft flying nearby); volumetric average (not point) measurements; only senses the airspace above the sensor • Doppler wind lidar Pros: clear-air capability; rapid scanning ability; good spatial resolution Cons: radial-only measurement; can have significant attenuation in precipitation conditions • Doppler weather radar Pros: rapid scanning ability; relatively good spatial resolution Cons: limited clear-air capability (depending on transmit frequency); radial-only measurement As mentioned above, another alternative to a sensor-based detection system is a sensor-based diagnostic system. In the sensor-based detection approach, direct measurements of the hazardous wind conditions are made along the flight path (e.g., Doppler lidar/radar), or close enough to the flight path to interpolate/extrapolate to the flight path (e.g., using anemometer or Doppler wind profiler). In a sensor-based diagnostic system, a correlation-based algorithm would be developed to connect ambient wind conditions (e.g., upstream conditions) to reported (pireps) or measured (aircraft-based) windshear/turbulence conditions. A concise list of the pros/cons of these two approaches is provided below. Sensor-based detection systems – direct measurements of wind/turbulence • Pros: accurate; less ambiguity (location/magnitude) • Cons: sensors may give inaccurate information (due to noise, viewing location, viewing angles, and/or low SNR/attenuation) Sensor-driven diagnostic systems – indirect use of measurements of wind/turbulence • Pros: Less costly to implement; reasonable accuracy • Cons: Requires significant database of scenarios and verification. NCAR plans to use the results of the Task 1 efforts to get a better understanding of the specific scenarios under which hazardous wind conditions may exist at and near ASE. Based on this analysis, we will consider appropriate, and cost-effective options, e.g., a wind information system, a sensor-based detection warning system, a sensor-based diagnostic warning system, or a hybrid detection/diagnostic wind information/warning system. Furthermore, we will consider methods for providing the output of such systems to the appropriate users. NCAR will also work closely with the user community to ensure that the output of these systems meets their operational needs. NCAR will provide a report detailing the results of the efforts described above. This will include guidance on viable approaches for operational implementation of wind information and/or wind hazard warning systems, along with a cost/benefit analysis of each system for further evaluation and possible implementation. NCAR will also work closely with the sponsor to indicate the need and rationale for additional efforts associated with this task. These could include augmentation of the data collection beyond the anemometers proposed in Task 3. For example, additional anemometers, a temporary deployment of other sensors (e.g., a Doppler lidar), or the temporary deployment of a research aircraft. Additionally, NCAR may see the utility of performing high-resolution numerical model runs that could be used to further understand the spatial and temporal conditions during hazardous wind events, as well as providing a dataset for simulating sensor and/or algorithm performance under such conditions. As with augmenting the data collection, NCAR will communicate with the sponsor on potential needs and associated costs. NCAR will also work closely with the sponsor to pursue additional and/or alternative sources of funding to continue the R&D activities, as well as to fund future algorithm development and potential sensor deployments. The intent of this task is to consider practical, tangible, and specific steps forward. This task will build on the case study task described above and consider sensor types appropriate for ASE (given expected weather scenarios), sensor locations, deployment costs, and user aspects (e.g., displays and information content). The outcome of this task will be recommendations as to potential solutions for the ASE wind hazards. Specific Work Elements for Task 2: 1. Investigate sensor systems (e.g., on-airport and off-airport anemometers, Doppler lidars, Doppler radars, Doppler wind profilers). 2. Describe a notional “Wind information” system (e.g., display of sensor data – no interpretation – just QC). 3. Describe a notional “Warning” system (actionable, user-friendly information. Could be graphical display). 4. Present user aspects for consideration (e.g., information content, useability, access, information display, communications, airline/FAA rules). Deliverables for Task 2: • Provide a report detailing the results of the efforts described above. • Include guidance on viable approaches for operational implementation of wind information and/or wind hazard warning systems. • Cost/Benefit analysis of each system for further evaluation and possible implementation. Task 3. Deployment of Additional Wind Sensors The purpose of this task is to collect high quality, temporal information on localized winds impacting the Aspen airport. NCAR/RAL has had extensive experience over the past several decades in deploying sensors at and around airport locations to collect unique data used to tailor solutions to problems specific to that airport. For this project, a R. M. Young aerovane and associated temperature/humidity probe (Figure 1) will be used. While the aerovane will provide measurements of wind speed and direction, the addition of the temperature/humidity probe will help provide information on causes of various wind regimes, including examining cold air drainage and vertical stability. Figure 1. R. M. Young Aerovane (left) and Temperature/Humidity sensor (right). These sensors will be deployed at three locations at or near the Aspen airport. The proposed locations include the north end of the runway (co-located near the ASOS), the south end of the runway, and on radar ridge above Shale Bluffs. Figure 2 shows the approximate locations of the anemometers. The orange star in the figure indicates the approximate location of the ASOS. Determination of the final installation sites will first require site visits by NCAR/RAL personnel to assess power and communication availability, airport requirements for sensors installed on airport grounds and location feasibility, and approvals from landowners to install sensors at the finalized locations. Figure 2. Aspen airport with proposed anemometer locations. The orange star indicates the approximate location of the ASOS. Deployment of the sensors will occur approximately two months after contract start. This will give us time to coordinate with the appropriate local entities regarding siting, access to power and communications. Data will be collected at one second intervals and transmitted back to NCAR/RAL in near real-time via LTE/5G modems and archived for later analysis. Data can also be made available to Aspen airport staff via a webpage in both text and graphical format if requested. Sensors will operate through period of performance and data will be regularly monitored to ensure a high-quality dataset. NCAR/RAL staff will be available to troubleshoot any issues that may arise while the sensors are deployed and visit the sites as needed if repairs are necessary. Data analysis will be performed to support the efforts in Task 1. With a focus on comparisons between the Shale Bluffs anemometer and airport conditions as measured by airport sensors and other sources (e.g., PIREPS or ADS-B data), to help with understanding conditions that might lead to hazardous winds for aircraft operations. Specific Work Elements for Task 3: 1. Determine locations for three anemometer sites (e.g., N-end runway, S-end runway, radar ridge site above Shale Bluffs) and deploy sensors. 2. Collect data during the contract period of performance. 3. Perform initial data analyses. Deliverables for Task 3: 1. Provide cost estimates for additional equipment, including infrastructure requirements and operational costs for budgetary purposes. 2. Work with local entities to site and deploy self-contained, all-weather, research-quality anemometers. 3. Operate, collect, and perform an analysis of the data. The data will be collected at a minimum of one sample per second, transferred to, and archived at NCAR in near real time. Report and Project Management NCAR will provide project management support for the proposed efforts, including personnel and administrative, and contractual support. Specific Tasks: 1. Summarize/describe work performed in tasks listed above. 2. Produce a report including recommendations regarding next steps. 3. Coordinate with the sponsor, provide briefings, and participate in telecons, as needed. Disadvantaged Business Entity (DBE) Participation Based on the United States Executive Order dated January 20, 2025 and titled "Initial Rescissions of Harmful Executive Orders and Actions," which repeals Executive Order 14035, Diversity, Equity, Inclusion and Accessibility in the Federal Workforce, UCAR/NCAR cannot submit a DBE plan with this proposal. While NCAR has had a long history of successful DEI programs in the past, we are now precluded from engaging in all such activities. Schedule Period of performance (POP): 12 months from contract start. Task 1: Assessing and Addressing Instantaneous Winds Work on Task 1 will commence after contract start and be completed at the end of the POP. It is anticipated that this task will have two phases. The first phase will consist of the collection of relevant archival data (e.g., pireps, model data) and subsequent case studies performed relative to those data. A briefing on the initial results of this phase will be provided six months after the contract start. The second phase is predicated on having useful case study data available from the anemometer deployment described in Task 3. We anticipate that there may only be a limited number of non-convective cases until the Fall season, so most of the work for this phase will be performed towards the latter stages of the POP. Besides the mid-term briefing, NCAR staff will provide briefings to the sponsor as needed, as work progresses. Task 2: Advanced Wind Shear and Turbulence Detection Technologies As Task 2 is designed to leverage the results of Task 1, we intend to ramp up the effort on this task parallel to, but with a time-delay, relative to Task 1. The final report will be completed by the end of the POP, but NCAR staff will provide briefings to the sponsor as needed, as work progresses. Task 3: Deployment of Additional Wind Sensors Work on this task will commence at contract signing. NCAR staff will work with the sponsor and local entities as needed, to coordinate issues related to anemometer siting, power, and communications. Assuming those efforts proceed without significant impediments, we anticipate that data collection from the anemometers will begin approximately two months after contract signing. NCAR has budgeted support costs for operating the anemometers throughout the POP. Preliminary data analysis – mainly for QC/verification – will begin once the data are available. Ongoing data monitoring and quick-look data analysis will be ongoing, and data analysis to support case study efforts (Task 1) will occur as interesting cases arise. Budget The project budget is attached as a separate document. Qualifications of Proposer: The NCAR Research Applications Laboratory (RAL) has significant experience with developing and deploying wind hazard systems for airports and investigating aircraft incidents. Our capabilities include knowledge of the relevant atmospheric aspects, sensor systems, and algorithm development. Furthermore, RAL has wide-ranging experience working with the aviation user community, including pilots, airline and airport operators, air traffic controllers (control tower, TRACON, enroute, and traffic management), regulators, and aircraft manufacturers. Low-Altitude Convective Windshear Starting back in the early 1980’s RAL worked with the FAA to investigate adverse low altitude convective wind shears and their impact on aviation. RAL scientists and engineers developed the operational algorithms for the Low-Level Windshear Alert System (LLWAS), an anemometer- based system that is still used operationally in the US as well as at numerous airports around the world. RAL staff also worked closely with the FAA in the development and deployment of the Terminal Doppler Weather Radar (TDWR) system. RAL scientists also developed and fielded the first TDWR/LLWAS integration algorithms. In developing these windshear systems, RAL scientists and engineers helped to pioneer the use of meteorological sensor systems for real-time aviation hazard detection and warning. As part of the feasibility studies into using in situ and remote sensors for wind shear detection, RAL also led extensive field programs to help understand and characterize the phenomena. A critical part of the success in solving the convective wind shear problem came from the work of a Wind Shear Users Group. This group, set up by the FAA, had members from all aspects of the user community (pilots, airlines, ATC, aircraft manufacturers, and regulator), as well as from the scientific and engineering community (NCAR/RAL, MIT-LL, NASA, NOAA, and university researchers). From those initial forays into aviation weather in the 1980s, RAL has maintained strong, ongoing relations with the broader user and research communities. Low-Altitude Windshear and Turbulence Detection System: Hong Kong International Airport From 1993-1997, NCAR/RAL developed and deployed a low-altitude, terrain-induced wind shear detection and turbulence diagnostic system for the (at-the-time new) Hong Kong International airport. In the initial phases, RAL performed a feasibility study to investigate the conditions under which prevailing winds, interacting with the local topography (Lantau Island) generated significant windshear and turbulence downstream of the terrain. Anemometers were deployed on mountain tops, three vertically pointing Doppler wind profilers were placed in the lee of the terrain, a TDWR radar was sited (and eventually deployed) across the bay from the airport, an LLWAS network was sited (and eventually deployed) on the airport itself, and a Doppler lidar was deployed on the airport site. Furthermore, a research aircraft was brought in from the US to provide high-quality measurements along simulated approach and departure paths. An example data case is shown in Figure 3. Wind barbs are sub-sampled values taken along the simulated approach path. One can see the laminar flow as the aircraft approaches the airport area from the Southwest (and above the terrain), transitioning to disturbed flow in the lee of, and below the peaks of the terrain. Figure 3. Example flight path from research aircraft flights, showing sub-sampled wind barbs. Disturbed flow is seen in the lee of the terrain. Based on the understanding of the windshear and turbulence conditions obtained during the feasibility and field deployment periods, and coordination with the relevant user community, RAL developed a diagnostic-based detection algorithm and warning system, the Operational Windshear Warning System (OWWS). The diagnostic algorithm was based on correlating the inflow conditions – as measured by the mountain-top anemometers and winds above the terrain provided by the wind profilers – with turbulence as measured by the research aircraft. The warning system integrated the diagnostic algorithm output with the outputs from the TDWR and LLWAS systems. The outputs from the warning system were provided on alphanumeric and graphical displays. The warning system and the display systems were developed in close coordination with the sponsor (at the time, the Royal Observatory) and the local user community. After the airport opened, Doppler lidars were deployed at the airport and integrated into the warning system. As of 2024, there are four such installations, covering the two parallel runways. (Note that RAL’s involvement in Hong Kong occurred prior to the airport being opened for operational use.) Low-Altitude Windshear and Turbulence Detection System: Juneau International Airport Following on with the success of the Hong Kong system, in the late 1990’s the FAA sponsored NSF-NCAR/RAL to consider a similar system for the Juneau International Airport. In a parallel fashion to the Hong Kong methodology, RAL performed a feasibility study for Juneau, including the deployment of airport and mountain-top anemometers, three Doppler wind profilers, a Doppler lidar, and an x-band Doppler weather radar. Three aircraft measurement field programs were also undertaken: two with research aircraft, and one with Alaska Airlines 737s flown in non-revenue (Part 91) mode. The Juneau Airport Winds (JAWS) system development was significantly more extensive than that for the Hong Kong system. This was due to the more complicated terrain and flight patterns (see Figure 4). On the other hand, the approach taken in devising the warning system was similar, i.e., it is a diagnostic system. As with Hong Kong, turbulence measured by the research and (here) Alaska Airlines aircraft was correlated with wind speeds, directions, and variations taken from the mountain-top anemometers and wind profilers. From these correlations, a system of regression equations was developed and used to drive the diagnostic system. Furthermore, as Juneau is a challenging weather environment for remote sensors, extensive work was done to harden the equipment and data (via qc algorithms). As in Hong Kong, a comprehensive effort was made to engage and coordinate with the user community – including at the local level (ATC, NWS, Part 121 and 135 operators), and at the national level (the FAA and congress). Figure 4. Left-hand panel: prevailing winds and flight tracks (black) overlaying the Juneau terrain. Right-hand panel: heatmap of turbulence intensity measured by research aircraft. Surface Wind Measurements NCAR scientists have been involved extensively in field deployments, particularly in regard to deploying surface-based sensors. Wind sensors are one of the most common sensors deployed as they are needed to help assess the general meteorological conditions at a given site. These sensor deployments have happened around the world, both domestically and internationally and include locations in Antarctica. NCAR scientists are well-versed in the methods for siting and deploying the sensors. This is accomplished by conducting site surveys to determine 1) feasibility of a given location, including ability of the landowner to support the installation for the time the sensors will be deployed, 2) power availability, and 3) potential communication capabilities for transferring the data. Airport locations can sometimes require more discussion due to FAA rules for structures on the airfield, but these can be addressed. While the site locations are being finalized, the sensors are installed at the NCAR Marshall Instrument Field Site, where they are tested and made ready for the final deployment. Once the site locations have been confirmed and the sensors fully tested, they are deployed to each of the sites, with additional troubleshooting time reserved to confirm proper operations. Incident/Accident Investigations NCAR scientists also have a lengthy history investigating terrain-generated meteorological hazards, such as mountain waves, lee-waves, and low-level erratic winds. They have investigated the meteorological conditions surrounding a number of aviation accidents associated with terrain induced hazards, have evaluated weather conditions at airports located near precipitous terrain, and provided alert systems to aid in airport operations. Examples of situations analyzed include: • A large amplitude mountain lee wave above the Denver International Airport (DIA) likely generated the strong and unexpected crosswind gust that resulted in a departing commercial airliner deviating off the runway and crashing on 20 December 2008. This is discussed below, • The unmanned experimental aircraft, Helios, crashed into the ocean shortly after take-off from Kauai’s Pacific Missile Range Facility, likely due to turbulence associated with a terrain generated island wake, • Extreme clear air turbulence over the Rocky Mountains associated with a downslope windstorm resulted in structural damage, including the loss of an engine and part of a wing, of a DC-8 cargo jet. Because of NCARs extensive experience with mountain-induced aviation hazards, the FAA requested NCAR’s assistance in evaluating the potential benefit of incorporating weather information into FAA’s Precipitous Terrain classification, currently based solely on static terrain characteristics, which provides guidance over regions characterized by steep terrain or abrupt slopes. The resulting study focused on Aspen/Pitkin County, Eagle County Regional, and Leadville-Lake County airports in Colorado. During this project, NCAR/RAL scientists investigated atmospheric turbulence occurrences around the three mountain airports using PIREPs to identify their link to complex terrains, and analyzed METAR wind, temperature, and humidity data to characterize meteorological conditions in these regions that can adversely impact the performance of the current Precipitous Terrain classification based on static terrain information. Case studies using kilometer-scale numerical weather modeling were conducted to compare meteorological conditions between calm and turbulent cases in the airport regions. The approach NCAR/RAL scientists will use in evaluating hazardous meteorological conditions for cases at the Aspen airport is illustrated by their analysis of conditions surrounding the Boeing 737 jetliner crash at the Denver International airport on December 20, 2008. In this case the NTSB requested RAL’s help in determining the probable cause of strong surface crosswinds that contributed to the departing aircraft running off the side of the runway and bursting into flames. Fortunately, no one was killed. Further analysis by NCAR scientists using aircraft turbulence reports, upper air sounding data, the larger scale meteorological environment, as well as visible and IR satellite data, indicated the atmosphere was conducive to a large amplitude mountain wave, with a lee wave extending downstream over the Denver airport. Pilot reports indicated both mountain waves and turbulence, including severe to extreme turbulence, throughout the day over a deep region of the atmosphere. Satellite imagery clearly showed distinctive cloud patterns associated with both large amplitude mountain waves and downwind propagating lee waves. Sounding data indicated upstream atmospheric conditions conducive to mountain wave formation. A high-resolution numerical simulation conducted by NCAR confirmed these results, clearly showing a large mountain wave over the foothills and an oscillating large amplitude lee wave extending downwind over the airport. Associated with the lee wave were regions of strong westerly winds penetrating down to the surface, resulting in strong westerly gusts propagating across the DIA property, many ranging from 20-30 ms-1. Diagnosing turbulence utilizing numerical model output NCAR/RAL scientists have extensive experience with diagnosing turbulence from numerical weather simulations/forecasts meteorological fields (wind, temperature, moisture, etc.) and providing atmospheric measures of turbulence on a grid point by grid point basis. The approach NCAR/RAL scientists have developed and used is to compute a suite of indicators of turbulence (or diagnostics), e.g., vertical wind shear, horizontal wind shear, Richardson number (Ri) etc., and use these diagnostics to infer turbulence location and intensity, and also a likelihood of a certain turbulence intensity to occur. Various turbulence diagnostics have been developed that represent various sources of turbulence, including clear-air turbulence (CAT), mountain wave turbulence (MWT), convectively induced turbulence (CIT), and low-level boundary layer turbulence (LLT). Turbulence estimates using ADS-B Out reports In previous efforts related to low-altitude windshear and turbulence – the Juneau and Hong Kong Airport projects (described above) – data collected from research aircraft flights along the operational routes were used to correlate with ambient wind conditions. Unfortunately, the cost for fielding research aircraft is steep, and so alternate data collection approaches are preferable. One such approach is to use ADS-B Out reports. Over the past five years, the FAA has sponsored RAL to look into the feasibility of using ADS-B Out aircraft reports to estimate turbulence. Specifically, we are using the vertical rate parameter to estimate the energy dissipation rate (EDR), an aircraft-independent measure of turbulence intensity. The FAA efforts have been focused on aircraft-to-ground-station communication links. More recently, RAL has been contracted by Aireon, a private company that provides global access to ADS-B data using satellite data links. We refer to these data as spaced-based ADS-B, or SBA for short. Both efforts have been quite successful and both entities are moving towards operational demonstrations of the turbulence product. The advantage of ADS-B reports is that they are required for all aircraft in controlled airspace (at least for CONUS). This means that the data should be available from all aircraft flying in and out of ASE. During the above-mentioned feasibility studies, certain factors have arisen that can limit the usefulness and/or quality of the ADS-B data. Two of these aspects that are pertinent to this project are the contamination due to maneuvering and data gaps. The latter of these two items is much more prominent with the SBA data, so if we can access the ground-based ADS-B reports, this should not be a problem. The maneuver contamination is more significant, and the initial efforts to ascertain the utility of these data for this project will focus on this aspect. The issue with maneuvers is that the estimation of EDR from the ADS-B vertical rates assumes that the source of vertical rate disturbances is solely from atmospheric inputs (i.e., wind/turbulence) to the aircraft response. If a given maneuver occurs slowly and steadily over a time period much longer than the variations in the aircraft response to the wind/turbulence, then signal processing methods are effective in separating the two combined effects. For example, with an altitude change during cruise, the effect that the maneuver has on the vertical rate can be removed. However, during the take-off/initial climb phase (say, below one thousand feet AGL), this may not always be the case. Most of our efforts regarding turbulence estimation from ADS-B data have been focused on those portions of the flight excluding the take-off/initial climb and final approach/landing periods. Nevertheless, we are confident that we have the experience and algorithmic tools to address these flight segments. Qualifications of Staff Personnel #1. Larry Cornman – Project Scientist III. PI Qualifications: Larry is a Project Scientist at the National Center for Atmospheric Research. His educational background includes undergraduate degrees in Mathematics and Physics from the University of California and a graduate degree in Physics from the University of Colorado. He started working at NCAR in 1983 in support of the FAA's Low Level Windshear Alert System (LLWAS). From 1983 to 1990, Larry was involved in the development of the Phase II and Phase III LLWAS algorithms and the Terminal Doppler Weather Radar (TDWR) algorithms. In 1989, he developed the TDWR/LLWAS Integration algorithms, for which he holds numerous U.S. and International patents. Since 1990, Larry's research focus has been on atmospheric turbulence. He has developed turbulence detection algorithms for remote sensors including ground-based and airborne Doppler radars, lidars and wind profilers; as well as developing a methodology for making in situ measurements of turbulence from commercial aircraft. Larry also has a significant amount of expertise in the aerodynamic impact of wind fields and turbulence on aircraft, as well in the development of signal and image processing algorithms. He holds four U.S. patents in this latter area. He has twice been the recipient of an Aviation Week and Space Technology magazine Laurel Award, a recipient of a NASA Turning Goals into Reality award, and was named to the 2003 Scientific American 50 list as Research Leader in Aerospace. See attached resume for more details List of similar Service performed: • Head of the algorithm development group for the Hong Kong OWWS project. • Original project manager and scientific lead for the FAA Juneau Windshear and turbulence project. • Project lead for the FAA’s ADS-B Turbulence Project. • Project lead for NASA’s Airborne Radar Turbulence detection project. • Original project lead for the FAA’s in situ Turbulence Measuring and Reporting project. Personnel #2. Arnaud Dumont DitVoitel – Engineering Lead, RAL’s Aviation Applications Program. Co-PI Qualifications: Designer and developer of decision support systems and visualization tools for meteorological forecasting in aviation, surface transportation, energy, epidemiology, and river basin management. 30 years’ experience working directly with end users in various domains to understand operational requirements and develop software tools which address their analytical needs. Extensive experience designing and implementing data dissemination systems, including data processing, persistence, web services, and data exchange protocols. See attached resume for more details. List of similar Service performed: • Developed visualization and alert notification systems for the Juneau Airport Winds System (JAWS) 2002-2004 • Led the Aviation Digital Data Service (ADDS) aviation weather website and application development 2007-2015 • Led the MobileMet Minimum Weather Service Recommendations, Enhanced Depiction of Runway Winds, and Adapting Weather Information for Cockpits for the FAA’s Weather Technology in the Cockpit (WTIC) Program 2012-2020 Personnel #3. Dr. Wiebke Deierling - Project Scientist II Qualifications: Atmospheric scientist with over 20 years of experience on a variety of topics around aviation weather including turbulence and convection, and the development of operational weather support tools. Significant experience in research on aviation turbulence and enhancing turbulence diagnosis and prognosis algorithms as well as convection. See attached resume for more details. List of similar Service performed: • Leading team to develop/improve turbulence forecasting and nowcasting capabilities as well as improve turbulence observations for the FAA’s Aviation Weather Research Program (AWRP). The team also serves as subject matter experts to the NTSB on turbulence incident investigations • Serves as a subject matter expert for the FAA on turbulence and lightning Personnel #4. Dr. Scott Landolt - Project Scientist II Qualifications: Atmospheric scientist with nearly 30 years of experience deploying a variety of sensors, including anemometers, at federal, state and private locations, including airports. Extensive experience with sensor siting, deployment, and maintenance, and analysis of sensor data from all seasons. See attached resume for more details. List of similar Service performed: • Deployed sensors in Juneau, AK to develop correction factor for optical precipitation accumulation sensors, including wind as a component • Oversee the NCAR Marshall Instrument Field Site, where nearly a dozen wind sensors are deployed and have been operational for over 20 years • Serves as a subject matter expert for the FAA on weather observations and sensor capabilities Personnel #5. Dr. Hailey Shin – Project Scientist II Qualifications: Atmospheric scientist with over 15 years of research experience investigating atmospheric turbulence in the atmospheric boundary layer and in the upper atmosphere using high-resolution numerical simulations and various in-situ and remote sensing observations. Extensive experience in research and development of turbulence transport modules in multiple numerical weather models including the community Weather Research and Forecasting. See attached resume for more details. List of similar Service performed: • Performed analysis of the FAA’s precipitous terrain classification algorithm and characterization of weather conditions over complex terrains in Colorado for the FAA’s Weather Technology in the Cockpit (WTIC) Program 2019-2020 • Performed research and development of probabilistic turbulence forecasting capabilities based on NOAA’s operational numerical weather forecasts in support of the FAA’s Aviation Weather Research Program (AWRP) 2020-2025 • Performed turbulence forecasting and nowcasting as part of turbulence case studies in support of the FAA’s Aviation Weather Research Program (AWRP) 2024-2025 Office of Compliance & Pre-Award Administration NSF NCAR Directorate NSF National Center for Atmospheric Research P. O. Box 3000, Boulder, CO 80307-3000 USA • Fax: 303-497-1194 • ww.ncar.ucar.edu February 26, 2025 Chris Davis Procurement Manager Pitkin County 530 E. Main Street Aspen, CO 81611 RE: Pitkin County RFP 025.25 – DBE Participation Dear Mr. Davis: UCAR/NCAR acknowledges and supports the objectives of the DBE program as defined in 49 CFR Part 26, aiming to promote equal opportunities for disadvantaged business enterprises. Self-Performance Justification After a thorough assessment of the project requirements and our internal capabilities, we have determined that UCAR/NCAR possesses the necessary resources and expertise to execute the entire contract with our in-house team. Consequently, we do not anticipate the need for subcontractors for this project. Procurement of Materials and Supplies The project necessitates the procurement of materials and supplies totaling $2,000. In alignment with DBE program objectives, we are committed to sourcing these materials from certified DBE suppliers whenever feasible. We will conduct market research to identify potential DBE vendors and evaluate their offerings to ensure compliance with project specifications and quality standards. Good Faith Efforts Should we identify suitable DBE suppliers, we will document our selection process and include them in our procurement plan. If DBE suppliers are not available or do not meet project requirements, we will provide documentation of our good faith efforts to engage such enterprises. Assurances and Compliance UCAR/NCAR affirms that, in the event subcontracting becomes necessary or additional procurement opportunities arise, we will: • Adhere to DBE Requirements: Proactively seek DBE-certified partners and ensure their participation aligns with the commercially useful function criteria as stipulated in 49 CFR Part 26. • Obtain Necessary Approvals: Secure all requisite consents from Pitkin County prior to engaging any subcontractors or suppliers, in full compliance with DBE program regulations. Should you have questions regarding the proposal, please contact the NCAR Office of Compliance & Pre-Award Administration, Ms. Valerie Koch at valeriek@ucar.edu. Sincerely, Valerie Koch Asst. Director of PreAward Administration Certificate Of Completion Envelope Id: 8C6BDBDA-E30E-44EA-8496-0B5053EDC523 Status: Completed Subject: UCAR | Pitkin County Task Order 025.25 A-1 for Review & Signature Source Envelope: Document Pages: 35 Signatures: 2 Envelope Originator: Certificate Pages: 6 Initials: 1 Pitkin County Procurement AutoNav: Enabled EnvelopeId Stamping: Disabled Time Zone: (UTC-07:00) Mountain Time (US & Canada) 530 East Main Street Suite 203 Aspen, CO 81611 Procurement@PitkinCounty.com IP Address: 65.38.144.66 Record Tracking Status: Original 10/14/2025 8:44:19 AM Holder: Pitkin County Procurement Procurement@PitkinCounty.com Location: DocuSign Signer Events Signature Timestamp Connie Baker connie.baker@pitkincounty.com Budget Director Pitkin County Security Level: Email, Account Authentication (None) Signature Adoption: Pre-selected Style Using IP Address: 65.38.144.66 Sent: 10/14/2025 8:48:04 AM Viewed: 10/14/2025 9:45:46 AM Signed: 10/14/2025 9:52:27 AM Electronic Record and Signature Disclosure: Not Offered via Docusign Diane Jackson diane.jackson@aspenairport.com Airport Director Security Level: Email, Account Authentication (None)Signature Adoption: Pre-selected Style Using IP Address: 65.38.144.66 Sent: 10/14/2025 9:52:29 AM Viewed: 10/14/2025 9:56:11 AM Signed: 10/14/2025 10:05:15 AM Electronic Record and Signature Disclosure: Accepted: 10/14/2025 9:56:11 AM ID: 939fd27e-c859-42d7-b159-96e2b049d41e Company Name: Pitkin County, Colorado Ryan Mahoney ryan.mahoney@pitkincounty.com Deputy County Manager Signing Group: County Manager Group Security Level: Email, Account Authentication (None) Signature Adoption: Pre-selected Style Using IP Address: 65.38.144.66 Sent: 10/14/2025 10:05:17 AM Viewed: 10/14/2025 10:16:38 AM Signed: 10/14/2025 10:17:08 AM Electronic Record and Signature Disclosure: Not Offered via Docusign In Person Signer Events Signature Timestamp Editor Delivery Events Status Timestamp Agent Delivery Events Status Timestamp Intermediary Delivery Events Status Timestamp Certified Delivery Events Status Timestamp Carbon Copy Events Status Timestamp Pitkin County Procurement procurement@pitkincounty.com Ruslana Ivanova, Procurement Specialist Pitkin County Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:09 AM Resent: 10/14/2025 10:17:17 AM Electronic Record and Signature Disclosure: Not Offered via Docusign Accounts Payable AP@pitkincounty.com Accounts Payable Pitkin County Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:10 AM Electronic Record and Signature Disclosure: Not Offered via Docusign Kathie Sharp ksharp@ucar.edu Lead Contract Administrator University Corporation for Atmospheric Research Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:11 AM Electronic Record and Signature Disclosure: Accepted: 9/4/2025 4:02:29 AM ID: 0894829c-5d09-4569-b176-b71ee95c2009 Company Name: Pitkin County, Colorado UCAR fedaward@ucar.edu Susan M Loyd, Lead Contract Administrator Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:11 AM Viewed: 10/14/2025 11:11:41 AM Electronic Record and Signature Disclosure: Accepted: 9/3/2025 9:51:42 AM ID: bc7d70b3-055b-4428-9ddf-44cf8a40e084 Company Name: Pitkin County, Colorado Larry Cornman cornman@ucar.edu Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:12 AM Electronic Record and Signature Disclosure: Not Offered via Docusign Arnaud Dumont dumont@ucar.edu Security Level: Email, Account Authentication (None) Sent: 10/14/2025 10:17:13 AM Electronic Record and Signature Disclosure: Not Offered via Docusign Witness Events Signature Timestamp Notary Events Signature Timestamp Envelope Summary Events Status Timestamps Envelope Sent Hashed/Encrypted 10/14/2025 8:48:04 AM Certified Delivered Security Checked 10/14/2025 10:16:38 AM Signing Complete Security Checked 10/14/2025 10:17:08 AM Envelope Summary Events Status Timestamps Completed Security Checked 10/14/2025 10:17:13 AM Payment Events Status Timestamps Electronic Record and Signature Disclosure ELECTRONIC RECORD AND SIGNATURE DISCLOSURE From time to time, Pitkin County (we, us or Pitkin County) may be required by law to provide you with certain written notices or disclosures. Described below are the terms and conditions for providing to you such notices and disclosures electronically when we send you documents for electronic signature. Acknowledging your Access, Intent, and Consent to Receive and Sign Materials Electronically To confirm that you can access this information electronically, which will be similar to other electronic notices and disclosures that we will provide to you, please verify that you were able to read this electronic disclosure and that you also were able to print on paper or electronically save this page for your future reference and access or that you were able to e-mail this disclosure and consent to an address where you will be able to print on paper or save it for your future reference and access. Further, if you consent to receive notices and disclosures exclusively in electronic format on the terms and conditions described above, please let us know by clicking the 'I agree' button below. By checking the 'I Agree' box, I confirm that:  I am establishing my intent to be bound to the transaction, and indicating that I am fully aware of the purpose for which the signature is being provided.  I can access and read this Electronic CONSENT TO ELECTRONIC RECEIPT OF ELECTRONIC RECORD AND SIGNATURE DISCLOSURES document; and  I can print on paper the disclosure or save or send the disclosure to a place where I can print it, for future reference and access; and  Until or unless I notify Pitkin County as described above, I consent to receive from exclusively through electronic means all notices, disclosures, authorizations, acknowledgments, and other documents that are required to be provided or made available to me by Pitkin County during the course of my relationship with you. Signing Documents without a Pitkin County DocuSign Account: Pitkin County may not require all document signers to be authorized users of the Pitkin County DocuSign Account. Please read the information below carefully and thoroughly, and if you can access this information electronically to your satisfaction and agree to these terms and conditions, please confirm your agreement by clicking the 'I agree' button at the bottom of this document. When you don't have a DocuSign account, you will be provided the opportunity to agree to the Legal Disclosure each time you open an "envelope" for signing, at this time, you can download and retain this disclosure. Pitkin County will forward completed documents that you've reviewed, processed or signed via email. Should you require copies of these signed documents (e.g., if they get deleted from your email account) you should request those documents from Pitkin County under the Colorado Open Records Act by contacting the Pitkin County custodian who sent you the document for signature. Signing Documents with a Pitkin County DocuSign Account: Electronic Record and Signature Disclosure created on: 3/20/2020 3:28:13 PM Parties agreed to: Diane Jackson, Kathie Sharp, UCAR Please read the information below carefully and thoroughly, and if you can access this information electronically to your satisfaction and agree to these terms and conditions, please confirm your agreement by clicking the 'I agree' button at the bottom of this document. Getting paper or electronic copies At any time, you may request from us a paper or electronic copy of any record provided or made available electronically to you by us. For such copies, as long as you are an authorized user of the DocuSign system you will have the ability to download and print any documents we send to you through your DocuSign user account for a limited period of time (usually 30 days) after such documents are first sent to you. 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Consequences of changing your mind If you elect to receive required notices and disclosures only in paper format, it will slow the speed at which we can complete certain steps in transactions with you and delivering services to you because we will need first to send the required notices or disclosures to you in paper format, and then wait until we receive back from you your acknowledgment of your receipt of such paper notices or disclosures. To indicate to us that you are changing your mind, you must withdraw your consent using the DocuSign 'Withdraw Consent' form on the signing page of your DocuSign account. This will indicate to us that you have withdrawn your consent to receive required notices and disclosures electronically from us and you will no longer be able to use your DocuSign user account to receive required notices and consents electronically from us or to sign electronically documents from us. All notices and disclosures will be sent to you electronically Unless you tell us otherwise in accordance with the procedures described herein, we will provide electronically to you through your DocuSign user account all required notices, disclosures, authorizations, acknowledgments, and other documents that are required to be provided or made available to you during the course of our relationship with you. To reduce the chance of you inadvertently not receiving any notice or disclosure, we prefer to provide all of the required notices and disclosures to you by the same method and to the same address that you have given us. Thus, you can receive all the disclosures and notices electronically or in paper format through the paper mail delivery system. If you do not agree with this process, please let us know as described below. Please also see the paragraph immediately above that describes the consequences of your electing not to receive delivery of the notices and disclosures electronically from us. How to contact Pitkin County: You may contact us to let us know of your changes as to how we may contact you electronically, to request paper copies of certain information from us, and to withdraw your prior consent to receive notices and disclosures electronically as follows: To contact us by email send messages to Helpdesk@provelocity.com To advise Pitkin County of your new e-mail address To let us know of a change in your e-mail address where we should send notices and disclosures electronically to you, you must send an email message to us at Helpdesk@provelocity.com and in the body of such request you must state: your previous e-mail address, your new e-mail address . 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