Our Research
Climate and Weather Processes
Global and regional climate sensitivity is defined primarily by feedbacks to the planets’ hydrological cycle that in turn alter the planet’s energy balance. These feedbacks involve processes that are ‘fast’ such as cloud and precipitation processes, evolving within the ‘weather envelope’, or slow such as changes related to land cover, carbon exchanges or ice sheet extent that evolve within the ‘climate envelope’. Research within CIRA and in conjunction with the ATS faculty has made important contributions to the observing, understanding and modeling of important processes key to improving numerical weather/climate prediction. The severe decrease in Arctic sea ice in 2007 underscores the delicate connections between changing weather and climate trends (e.g. Kay et al., 2008). Shifts in weather processes, such as the drying of the atmosphere and the clearing of Arctic clouds (perhaps associated with decadal oscillations), accelerated the sea ice loss and amplified the slower climate forcing effects of sea ice. As another example, predictions of long-term trends in air quality must consider not only emissions projections but also the affect that climate change will have on regional to-global scale weather patterns (e.g., impacting transport, trapping inversions, etc.). In acknowledgement of the importance of the weather-climate connection, the Department of Energy’s Atmospheric Radiation Measurement and Climate Change Prediction Programs now run a climate model in NWP mode. Research conducted under this theme employs a combination of numerical models and environmental data to understand processes that dictate changes on weather and climate timescales (minutes to months to years) and the two-way interactions between weather systems and regional and global climate. Research related to the hydrologic cycle, carbon exchanges and turbulent flux exchanges all have the ability to influence both weather and climate and thus form the basis of this research theme. Also included are those studies that look at weather systems from a process perspective and the development of data sets intended for climate trend analysis.
Data Assimilation
The future state of a dynamical system is typically calculated by integrating a numerical model, and depends on parameters such as initial conditions, model errors, empirical parameters of the model, and possibly on lateral boundary conditions. Observations add new information that can be combined with model prediction to produce optimal values of dynamical system parameters and reduce their uncertainty. A mathematical methodology that can accomplish this is called data assimilation. Data assimilation is fundamentally probabilistic since the uncertainty of dynamical system parameters can be described by a probability density function. Since dynamical models add valuable prior information, data assimilation is commonly based on Bayes theorem and thus represents a Bayesian inference. Data assimilation is also nonlinear since dynamical prediction models and observation operators can be highly nonlinear. CIRA data assimilation research has the following goals: Since we are primarily interested in geosciences applications to high-dimensional dynamical systems, the high-performance computational component of data assimilation is also of great importance to our research. Typical data assimilation methodologies developed and improved at CIRA are variational, ensemble, and hybrid ensemble-variational methodologies, but we are also exploring other avenues. Our research is encompassing a wide range of applications including carbon cycle, hydrology, climate, and cloud-resolving processes. We are also actively supporting NOAA research and development by conducting data assimilation research using NOAA operational systems and observations.
Modeling Systems Research
Much of the Regional to Global-scale Modeling work done at CIRA is performed by approximately 20 CIRA researchers who are integrated into various collaborative research activities within the Global Systems Division (GSD) at the NOAA Earth System Research Laboratory (ESRL) in Boulder. They conduct research and development to provide NOAA and the nation with observing, prediction, computer, and information systems that deliver environmental products ranging from local to global predictions of short-range, high impact weather and air quality events to longer-term intra-seasonal climate forecasts. CIRA researchers and scientists, in partnership with GSD, Global Monitoring Division (GMD), and Physical Sciences Division (PSD) scientists, conceive, design, and test the forecast impact of meteorological observing systems, with an emphasis on integrated observing systems employing a large range of measurement systems. They develop modeling and assimilation techniques and information systems to improve the short-range weather forecasting necessary for severe weather watches and warnings, heavy precipitation events, water management, air quality forecasting, and fire weather prediction. They develop the global Earth system modeling and assimilation techniques needed for global chemical transport and regional climate simulations. Together with our partners at the NOAA ESRL, CIRA scientists and researchers investigate high-performance computer architectures to handle the enormous computational demands of environmental models and develop environmental information systems to support commerce, transportation, emergency management, and other societal needs. They support NOAA in high-performance computing through new computing technology and improved software engineering practices while investigating advanced computer architecture to handle the enormous computational demands of environmental models. In other research, our scientists use models to improve the representation of clouds and land surface processes and to investigate the response of regional hydrology to global climate change. These impact studies help facilitate the development and enhancement of models for both operational forecasting and research applications. They help create tools that allow scientists to obtain more information from observations and simulated observations and conduct weather analysis, numerical forecasting, and ensemble forecasting.
Education and Outreach
Education and Outreach at CIRA is designed to support the research performed at CIRA, improve the visibility of CIRA research and researchers to the University, within NOAA, and to the community, and to inspire the next generation of research scientists. To support these goals, programs administered by the Education and Outreach (E&O) program are organized along four tiers of involvement, all of which are targeted to a specific audience, and are directly related to the research performed at CIRA. Wherever possible, outreach activities are designed to facilitate evaluation and assessment of the activity to obtain quantitative feedback on the success of the activity. The CIRA E&O program is led by a committee composed of researchers and other CIRA personnel who have training and an interest in science education and outreach. As mentioned previously, outreach activities at CIRA are organized through four tiers of involvement. The first, most basic, tiered activity encompasses public relations, media releases, and community involvement – increasing CIRA’s visibility in the public sphere to all audiences. The second tier of activities represent ‘pilot programs’ developed in-house at CIRA – short-term projects targeted at a specific audience with a focus on relevance to CIRA research or capabilities. Tier 2 projects are developed using in-house funding from CIRA with the intent of using preliminary results from the project to compete for and obtain external funding sources. The third tier of projects at CIRA represent ongoing outreach projects that are externally supported, either as part of a funded research project or as a standalone education or outreach project, including Tier 2 projects that successfully competed for external funds. A fourth tier for CIRA education and outreach projects envisions leveraging unique CIRA capabilities to provide national-caliber education opportunities: providing complete education and public outreach capabilities for an earth science mission, for example, or hosting a nationally-known training and professional development program for emergency managers. Development of the tiered system of outreach and education at CIRA was implemented in mid-2011, incorporating existing Tier 1 and Tier 2 activities; continued development of CIRA’s Tier 2 and Tier 3 activities is underway. Outreach and Education activities at CIRA operate under the auspices of the Education and Outreach committee who represent areas of research at CIRA and act as principal points-of-contact or principal investigators for CIRA activities. The committee is chaired by the education and outreach coordinator for CIRA, who operates with the oversight of the Directors of CIRA, and who reports to the CIRA Board and Fellows as required. The Education and Outreach Coordinator also acts on CIRA’s behalf for education and outreach activities between Cooperative Institutes and within NOAA at large.
Societal and Economic Impact Studies
At CIRA, we recognize the importance of developing meaningful interdisciplinary partnerships to help us apply our research in ways that directly benefit society. As such, the Societal Impacts of Weather and Climate (SIWC) research group was established to address NOAA’s social science research priorities. Through our partnership with CSU, we’ve been able to collaborate with experts in areas such as risk communication, impacts of extreme weather on human health, and economic impacts of weather and climate. In addition, our participation in the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) Risk Communication group has allowed us to develop strong working relationships with social scientists at NCAR and the University of Washington. We also have two employees embedded within the National Weather Service’s Social, Behavioral, and Economic Sciences (SBES) program.
Satellite Algorithm Development, Training and Education
Satellite information improves our ability to observe current environmental conditions (relevant, e.g., to increase warning lead times) and advance the representation of physics in numerical weather and climate prediction models. NOAA geostationary and polar orbiting satellites are an integral part of the international global space-based observing system, providing a ‘global spectral shell’ of information with varying spatial, spectral, and temporal characteristics. Satellite Algorithm Development, Training, and Education is a core thematic area of research for CIRA, and we hold over 30 years of experience in developing, demonstrating, transitioning, and training operational users on satellite meteorological products. This expertise spans both national and international operational satellite systems and extends to operational risk-reduction and research-grade systems. We apply this expertise to the development of new satellite algorithms, anticipating future system capabilities, and training forecasters on the capabilities and limitations of satellite-derived information. Meeting the mission-critical needs of NOAA in satellite research and development requires close working partnerships and full immersion within NOAA’s program planning, budget, and execution cycle. This level of involvement is best facilitated by regular, face-to-face interactions. The Cooperative Institute program accomplishes this interaction in a unique way – allowing Federal scientists to physically sit at academic institutions and vice versa. For example, CIRA hosts the Regional and Mesoscale Meteorology Branch (RAMMB) of NOAA/NESDIS/STAR, who interact closely with CIRA scientists at Colorado State University in Fort Collins. Our co-location with CSU’s Department of Atmospheric Science enables direct linkages to faculty and their students in the discipline areas of Satellite Meteorology, Radiative Transfer and Remote Sensing Theory, Thermodynamics and Cloud Physics, Atmospheric Chemistry and Air Quality, and Tropical Meteorology and Dynamics. In addition, the NOAA Weather and Climate Center in College Park, MD serves as host to a group of CIRA scientists who are fully entrained within the research activities of Satellite Oceans Sensors Branch as well as the Marine Ecosystems & Climate Branch as part of the NESDIS Environmental Applications Team (NEAT). In both on-site and remote arrangements, Federal scientists serve as technical advisors to ensure that our research follows in lockstep with NOAA mission needs.
Data Distribution
The Data Distribution theme area involves research focusing on identifying effective and efficient methods of quickly distributing and displaying very large sets of environmental and model data using data networks, using web map services, data compression algorithms, and other techniques. CIRA is engaged in a number of notable activities under this thematic research area at both the Fort Collins campus and the NOAA Earth System Research Lab in Boulder. In Fort Collins, CIRA maintains the Data Processing Center (DPC) for NASA’s CloudSat satellite mission. Launched in 2006, CloudSat carries a nadir-looking 94 GHz cloud profiling radar that gathers information about the microphysical properties and vertical structure of clouds for climate and weather research. CloudSat flies in formation with the A-Train constellation of satellites which allows collocated and nearly-simultaneous observations of the atmosphere by the suite of instruments on each platform. The DPC is responsible for acquiring CloudSat data from the U. S. Air Force and selected data sets from the other missions to generate multi-sensor data products and distributing them to the scientific community. Success in this endeavour has allowed the DPC to take on other data distribution projects. In addition to observing, assimilation, modelling, and high-performance/advanced computing capabilities, information systems are necessary and required to deliver environmental products ranging from local to global predictions of short-range, high impact weather and air quality events to longer-term intra-seasonal climate forecasts. This research challenge includes identifying and developing new web visualization capability amidst the diversity of the types of data, information resources, and multiple standards that exist and the need for integrating these separate infrastructures to enable collaborative research across the various disciplines. Alongside ESRL/GSD scientists, approximately 25 CIRA researchers are striving to develop various state-of-the-art information systems and advanced workstation concepts, including an initial network-enabled Weather Information Database (WIDB) that will synthesize important NWS data repositories into a seamless virtual weather database that will support the ‘Common Weather Picture‘. The WIDB will be based on standard services and formats that will enable effective and efficient populating of the WIDB, exposure of information, and access to users. Our researchers are also developing the capability for NWS IT infrastructure to effectively and efficiently interface with FAA IT infrastructure. Another major effort in support of the NWS and FAA involves the development of a 4-dimensional Weather Cube to house standardized weather information for integration into air traffic decision-support tools to improve the quality of weather products for the aviation community. In addition to our collaboration with ESRL/GSD, CIRA has recently begun collaborating with the NWS Aviation Weather Center (AWC) in Kansas City with an on-site research team to support the NextGen weather initiative via the Aviation Weather Testbed (AWT) in building the 4-D Cube, in addition to transitioning experimental FAA Aviation Weather Research Program algorithms to the AWC operational environment. A third research thrust is to improve weather information for fire weather prediction; one component is the development and enhancement of an interactive, integrated GIS, weather, and fire information platform that would be available to… Read more »