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The Department of Geosciences at Texas Tech University (https://www.depts.ttu.edu/geosciences/) seeks an early-career postdoctoral scholar to provide scientific and meteorological expertise in the areas of lidar based remote sensing of boundary layer turbulence and thermodynamical processes over arid region. The scholar will collaborate on the newly developed ABL-ROAD (Atmospheric Boundary Layer Research Over Arid Domains) program. In addition to empirical boundary layer process studies, the postdoctoral researcher will also perform weather-scale analyses of model data mismatch (MDM) experiments using archived simulations from High Resolution Rapid Refresh (HRRR) models for the broader region.

As part of this opportunity, the researcher will explore and develop new observational tools and MDM approaches for boundary layer processes focusing on the impact of dryland ecosystem on boundary layer kinematics and thermodynamics. Furthermore, the researcher will explore the potential for new and emerging boundary layer profiling systems including lidar, sodar and ceilometer to enhance our knowledge on the boundary layer parameterization schemes. The key tasks involved in the project are to (1) acquire and analyze new lidar and in-situ measurements under appropriate synoptic conditions to document boundary layer turbulence processes over an arid region; (2) synthesize observations obtained from the West Texas Mesonet for time periods > 5 years; (3) systematically investigate how model errors vary as a function of soil-vegetation-atmosphere nexus and associated meteorological conditions; (4) provide insights into the soil moisture control on land-atmosphere interactions toward help developing new parameterizations; and (5) explore the coupling between soil moisture, precipitation, and near-surface temperature in transitional regions (e.g., semiarid and semi-humid) of southwest US.

The incumbent will work with Prof. Sandip Pal and his group members of Boundary Layer Meteorology research group (https://sites.google.com/view/sandippal-ttu/). The position will be based in Lubbock, TX, a mid-sized metropolitan located in the heart of West Texas.

Required Qualifications

Specific qualifications include:

• Completion (by the time of the appointment) of a Ph.D. in meteorology/atmospheric science/physics/environmental science or related field.
• A documented record of research experience in lidar operation, data acquisition and analyses, and interpretation.
• Experience in leading peer-reviewed publications

Preferred Qualifications

In addition to the required qualifications, individuals who have one or more of the following preferred qualifications are strongly encouraged to apply:

• Experience with field work and analyses of multivariable meteorological data sets obtained via ground-based meteorological stations.
• Knowledge, and expertise in areas of ground-based remote sensing, dynamics of the boundary layer, and land atmosphere feedback processes
• Experience in the evaluation of numerical model simulations

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The selected candidate will join the BNL’s Center for Multiscale Applied Sensing team primarily as part of the new Southwest Urban Corridor Integrated Field Laboratory team. The Southwest Urban Corridor Integrated Field Laboratory is a multi-institutional project supported by the Department of Energy’s Biological Environmental Research program. The project aims to integrate a diverse suite of high-resolution observations (atmospheric, land surface, and infrastructure), diagnostic/predictive models, and civic engagement to provide new knowledge and deliver next-generation predictive tools. These tools are meant to promote equitable policy interventions targeting extreme climate events, carbon dioxide emissions, and local air pollution within and across the Arizona urban corridor.

The postdoctoral researcher will engage in field work to collect unique weather observations using the CMAS mobile observatory trucks. These observations will then be analyzed by the postdoctoral researcher and the project team to (i) create new understanding of the feedbacks among urban infrastructure, waste heat, and extreme heat/weather events; (ii) assess the spatiotemporal patterns of extreme heat and air quality impacts across the diverse urban landscape; (iii) evaluate the efficacy and social equity of mitigative actions across communities that include traditionally underrepresented groups. This position has a high level of interaction with an international and multicultural scientific community.

Essential Duties and Responsibilities

• Design field deployment strategies to evaluate and inform next-generation predictive urban climate models (e.g., using OSSEs (Observing System Simulation Experiments) or ablation studies, through extensive literature review of past field campaigns, through interactions with project stakeholders)
• Participate in summer field work
• Conduct observationally based research into the urban boundary layer using “big data” (e.g., crowd sourced data or from mobile and distributed instrument networks)
• Assess the performance of next-generation predictive urban climate models using observations
• Develop new visualization strategies of observational data useful to scientists and stakeholders
• Write and publish results in peer-reviewed journals, in coordination with team leadership
• Report on results at regular group meetings and during scheduled seminars and colloquia
• Participate in conferences and workshops, regular group meetings, and assist with notetaking

Required Knowledge, Skills, and Abilities

• PhD degree in meteorology, atmospheric sciences, data science, mathematics, or closely related fields (e.g., physics)
• Demonstrated experience with data science, especially statistical hypothesis testing, uncertainty quantification, pattern analysis
• Excellent programming skills in various platforms and languages (e.g., Matlab, Python)
• Ability to work independently and collaboratively
• Clear and concise verbal and written communication and presentation skills
• Must have a valid driver’s license accepted for driving in New York State, or the ability to attain one within 1-month of the date of hire
• Ability to drive a light-duty (“non-CDL”) truck for long durations (up to 8 hours per day)

Preferred Knowledge, Skills, and Abilities

• Experience with weather instrumentation operation (lidar, radar, weather station, radiometer, sonde, cameras)
• Experience with weather instrumentation data analysis (lidar, radar, weather station, radiometer, sonde, cameras)
• Experience with mining and cleaning “big” observational data and/or online databases
• Experience with interfacing climate observations and numerical models (including the use of instrument forward simulators)
• Experience with developing multi-dataset or multi-dimensional visualization tools
• Experience with analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM)
• Experience with machine learning and artificial intelligence techniques
• Experience with predictive modeling

Review of applications begins in April 2025. Applications will be accepted until the position is filled

Research is under the direction of Dr. Katia Lamer

FOX Weather is a 24/7 ad-supported streaming service operated by FOX News Media. Launched in October 2021, the platform builds upon FOX News Channel’s expansive newsgathering units & FOX Television Stations’ added resources with a combined 120 meteorologists for a comprehensive suite of weather products featuring local, regional and national reporting, in addition to live programming. Utilizing multiple radar systems, including an immersive mobile 3D radar, and more than 100,000 HD cameras located around the country, the service offers users an innovative approach to forecasting, including coverage surrounding all weather patterns, from immediate to long-term. FOX Weather is available via foxweather.com, the FOX Weather app on IOS and Android devices, as well as Tubi, Apple TV, Amazon, and Roku, through FOX’s Connected TV Apps.

JOB DESCRIPTION

Join the FOX Weather team as an off-air Weather Producer/Meteorologist, where you'll play a critical role in delivering accurate, engaging, and impactful weather coverage across digital and linear platforms. Collaborating closely with production and digital teams, you’ll help shape the storytelling and presentation of weather content, ensuring our audience receives the most up-to-date and compelling information—especially when it matters most.

You must be available to work on weekends and overnights. Please note that this is an off-air position.

A SNAPSHOT OF YOUR RESPONSIBILITIES:

• Work closely with the Weather Presentation team by pitching weather content ideas, producing weather segments, and providing regular meteorological guidance
• Create and update daily weather graphics using TruVu MAX software
• Monitor and analyze weather data to create graphics and content for all platforms
• Regularly provide timely and unique weather information to all of FOX Weather and its partners
• Play critical role in helping drive breaking weather coverage, providing guidance and support to FOX Weather and its partners
• Ensure accuracy and reliability by fact-checking weather-related assets before they are presented
• Work closely with the Weather Presentation team to ensure consistent look, feel, and process
• Participate in leading training on weather systems and meteorological topics for FOX Weather
• Troubleshoot issues with graphics platforms 

WHAT YOU WILL NEED:

• Bachelor’s degree in meteorology, atmospheric science, or a related field of study preferred, or equivalent experience
• 5+ years experience in a broadcast television environment with TruVu MAX
• Possess a comprehensive understanding of the underlying meteorology of impactful weather conditions
• Deep understanding of weather communication
• Excellent communication skills, a collaborative spirit, and the ability to work under intense deadline pressure
• Enthusiasm for new products and platforms, and the creative energy to ignite great ideas
• Experience with talent management
• Ability to work a flexible schedule based on the needs of a live production environment

We are seeking two highly motivated postdoctoral researchers to support model system development and forecast applications for the DAWN project, an interdisciplinary project focused on making climate research accessible to support agricultural decision-makers in the United States. Thes roles will focus on operating and evaluating coupled regional Earth system models, including climate, hydrology, and agroecosystem processes. Additionally, the postdocs will work with an interdisciplinary group to support the transfer of the resulting forecasts to our existing online decision support infrastructure. Salary is commensurate with experience and University benefits will be included.

The key responsibilities of the postdocs will be to: conduct operational runs with a regional downscaling climate model, using data from operational NOAA seasonal forecasts; 2) conduct operational simulations for county-level crop forecasts using the DSSAT crop model; 3) run scenario analyses, perform sensitivity experiments, and optimize model performance; 4) evaluate model performance, predictive skill, and uncertainty; 5) monitor system and detect/solve abnormal conditions; 6) visualize results and package data for integration into the online decision support system; 7) communicate with interdisciplinary team about the data and results, including explaining to non-experts; 8) develop technical notes, user manuals, and peer-reviewed journal articles.

Applicants should have a recent Ph.D. (within 5 years) in agricultural, hydrologic, atmospheric or climate sciences, and a strong background in model development and application. They must have experience and skill in programming (particularly Fortran), as well as analytical abilities in model evaluation and climate-hydrology-crop interactions. Applicants should also have an interest and willingness to cooperate and communicate with an interdisciplinary team, and contribute to the develop of unique solutions to support moving research to operations.

This is a one-year appointment renewable depending on performance and funding availability.

To apply:

Interested applicants should submit a cover letter, CV, and contact information for three references to Professor Xin-Zhong Liang at xliang@umd.edu. This position is available immediately, and applications will be reviewed on a rolling basis until the position is filled.