AAARG focuses on the dynamics and physical mechanisms of high latitude atmospheric processes. We study Arctic and Antarctic processes using high-resolution regional and global numerical models such as NCAR’s Weather Research and Forecasting (WRF) model and the Model for the Prediction Across Scales (MPAS). Since these locations are relatively data-sparse regions of the globe, we also study atmospheric predictability through ensemble data assimilation techniques using tools such as the Data Assimilation Research Testbed (DART) to better understand how to extend information provided by observations to improve numerical models.
Developing new techniques and novel methodologies for data assimilation and ensemble prediction
Applying these techniques for global scale to convective scale modeling systems assimilating a variety of observations (radar, satellite, ground based remote sensing platforms, aircraft borne observations, UAV, in-situ, etc.) to improve predictive skill
Improving the understanding of atmospheric predictability and dynamics through data assimilation and ensemble approaches from global to storm scales
Interdisciplinary research: machine learning/AI and data assimilation; machine learning/AI and forecast calibration; economic values of numerical predictions
Transitioning research and development into operations (R2O)
CCC group research falls within three topic areas of atmospheric science: Radar & Satellite Meteorology, Upper Troposphere and Lower Stratosphere (UTLS) studies, and Climate Variability and Change. Many of the topics that we work on are cross-cutting in that they require and contribute to knowledge in more than one of these areas. For example, thunderstorms are capable of reaching the tropopause: the boundary between the lowest layer of the atmosphere and that in which we live (the troposphere) and the layer immediately above (the stratosphere). If a storm overshoots the tropopause and extends into the stratosphere, it may lead to transport of air between the two layers (stratosphere-troposphere exchange or STE). STE affects the composition of the UTLS, which in turn leads to changes in the radiation budget and climate. Studying such problems enables the CCC group to broadly impact the atmospheric sciences. Additional details on our research activities and research identity can be found below.
Research in the IDEALab focuses on developing and applying data science, artificial intelligence, and machine learning techniques with a focus on high-impact real-world applications. Our research foci include the development of:
Autonomous data science techniques that can learn from real-world data
Applied data science/artificial intelligence/machine learning techniques that can be deployed in real-world settings
Intelligent autonomous agents that can successfully interact and learn while embedded in the real world
With the purpose of utilizing and developing active and passive radiation measurements for characterizing spatio-temporal distributions and radiative properties of aerosols, clouds and trace gases, the ARRS Group focuses on the development of remote sensing theory in three fundamental aspects, which include:
Remote sensing inversion
ARRS aims to establish a reliable remote sensing inversion system to improve the retrievals of aerosol and cloud properties by a) using observations that combines subsets of multi-angle, multi-spectral/hyperspectral, and/or polarimetric measurements, b) imposing multiple types of model and physical constraints, and c) using a priori aerosol and cloud information from transport model or from assimilation. The ARRS inversion system also allows for simulating new types of measurements for designing the next-generation sensors for aerosol and cloud remote sensing.
Atmospheric radiative transfer
ARRS aims to develop fast yet accurate one-dimensional (plane-parallel) and three-dimensional polarized radiative transfer models for modeling multi-angle, multi-spectral/hyperspectral, and/or polarimetric measurements. These models are for use by remote sensing inversion, climate models and data assimilation which involves a direct use of radiance.
Electromagnetic light scattering by small particles
ARRS performs research on modeling absorption and scattering properties of small particles and to understand a) the impact of aerosols and cloud particles on radiative budget of the Earth-Atmosphere system and b) various phenomena created by small particles in nature, lab and industrial processes.
The Convective Storm Dynamics Research Group seeks to better understand the two-way feedback between convective cloud systems and larger scales, often called the weather–climate interface. Cloud–radiation feedback in tropical convection is a major recent focus of our work and a prime example of this interaction: while the structure and distribution of clouds are greatly shaped by climate, clouds profoundly alter both the albedo and local greenhouse radiative trapping. The impact of this cloud–radiative forcing is not only on climate: our research is peeling back the veil on how this forcing affects convective storm behavior, including tropical cyclone formation. To study such links, we invoke knowledge and tools across a range of scales, including observations, high-resolution numerical models, and theory. Topics of special emphasis include
The McFarquhar cloud physics group focuses on the study of small-scale processes (microphysics) occurring in clouds. Some of the most fundamental and complex problems in climate and weather research today are our poor understandings of the basic properties of clouds and our inability to determine quantitatively the many effects cloud processes have on weather and climate. Current climate models indicate that Earth’s average surface temperature will warm from 1.5 to 4.5°C by 2100 due to increases in greenhouse gases, with the large uncertainty attributed to different treatments of clouds in climate models. Winter weather significantly impacts the transportation and power industries, schools and businesses, and severe thunderstorms can cause significant damage and flooding. Improved quantitative precipitation forecasts require a greater understanding of how cloud processes and the related energy release affect the structure and dynamics of storms. Research within the McFarquhar group addresses the overarching theme of clouds and their relation to climate and weather using a combination of field observations, satellite retrievals and numerical modeling studies. Prof. McFarquhar’s work at Oklahoma aims at making fundamental advances in our understanding of cloud properties and processes, and improving our ability to represent clouds in weather and climate models.
Current projects are advancing our understanding of
the microphysical structure of snow bands in winter cyclones
the role of cloud microphysical processes in mesoscale convective systems (MCSs) and storms
the properties of tropical clouds (habits, sizes and phases of cloud particles) generated by deep convection
the role of cloud microphysical processes in the rapid intensification of tropical cyclones
processes controlling the amount of supercooled water and freezing drizzle in clouds
how aerosols and other processes affect the evolution of clouds in the Arctic and over the Southern Oceans
the transmission of radiation through the cloudy atmosphere
the representation of clouds in climate and weather models, and especially the development of a stochastic framework for representing cloud processes; 9) the impact of anthropogenic aerosol particles on the water and energy bugets of clouds
the impact of biomass burning aerosols on cloud properties
the retrieval of cloud properties from space-, air- and ground-based remote sensors
the evolution of warm rain
the use of air- and ship-based instrumentation for measuring the properties of clouds. Prof. McFarquhar’s research group has led or participated in over 30 air- and ground-based field campaigns measuring the properties of clouds.
The CVC research group aims to further our knowledge of climate, climate variability and weather-climate interactions, with a focus on precipitation. This is accomplished through the use of observations and model simulations to provide a means to increase our understanding of essential mechanisms and processes across the globe, but with a focus on regions surrounding the Tropical Atlantic and the United States.
Our research interests include the following areas:
Variability of precipitation at multiple scales
Precipitation extremes, both wet and dry
Interaction of weather and climate
Representation of climate variability and change in climate models
Caribbean and African precipitation variability and change
The Salesky research group focuses on the structure and dynamics of the atmospheric boundary layer, turbulence, and interactions between Earth’s surface and the atmosphere. We use analytical methods, field experiments, and numerical simulations to address scientific questions of importance for weather and climate, air quality, water resources, and human health.
Recent topics of interest include convective boundary layers, boundary layers over complex surface topography, transport in the urban environment, and particle-laden flows. We also develop new numerical tools to study these problems using large eddy simulation.
The Applied Climate Dynamics Group is primarily focused on large-scale climate dynamics in both the atmosphere and ocean and all around the world. We focus on using observations (e.g., station data, satellite products, and reanalysis datasets) and climate models (both designed experiments and already-existing model output) for our studies. We use a variety of statistical approaches and forecasting techniques in our research with the goal of applying the results to operations in the science and in the private sector. Thus, graduate students and post-docs studying in this group have a well-rounded, application-oriented research experience.
OU-BLISS is a team of faculty and researchers with an interest in multi-faceted studies of the boundary layer. Through a variety of instrumentation and simulations, we seek to understand the dynamic nature of the lowest level of the atmosphere.
The goal of the CHEWe research group is to utilize observational and analytical tools to quantify the exchange of mass and energy between the land surface and the atmosphere from local to global scales to
increase our understanding of the complex interactions within the energy and water cycles from local to global scales and
communicate and distribute new insights to the scientific community, relevant stakeholders, and the public.
In particular, the team studies weather and climate extremes embedded within the water and energy cycles including drought, flash drought, evapotranspiration, drivers of excessive excessive precipitation, dynamics associated with precipitation extremes, and associated impacts to ecosystem function, health, and sustainability.
The HyRes group seeks is to improve weather and water prediction by better understanding the processes that govern atmospheric precipitation and its hydrologic impact at all scales. We combine state-of-the art remote sensing tools, innovative analysis of ground and satellite observations, and modeling. Our research improves the state of knowledge as well as real-world applications and operations.