Project: “Leveraging Multiple Observational Datasets to Advance Understanding and Simulation of Convection Lifecycles”
Funding Agency: NASA
Program: The Science of TASNPP and JPSS Series Satellites
Proposal Period: 2021-2024
Amount: $645,118 total ($227,026 to UVA)
Team: Gregory Elsaesser (NASA GISS, PI), Kathleen Schiro (UVA, Co-I), Remy Roca (CNRS, Collaborator), Thomas Fiolleau (CNRS, Collaborator), Piyush Garg (Argonne National Lab, Collaborator), Bill Irion (JPL, Collaborator), Christopher Barnet (STC, Collaborator)
Deep convective systems produce expansive high cloud shields that have large impacts on global radiation budgets. Their heavily raining regions and overall long durations combine to yield substantial rainfall accumulation across many locations, with the majority of rainfall in the tropics being attributed to such systems. Global climate models, in order to provide reliable projections of 21st century climate and rainfall extremes, must accurately simulate the spectrum of cloud feedbacks and hydrological processes associated with deep convective systems, which requires accurate simulation of convective initiation, evolution and termination as well as cloud area production as a function of their lifecycle. Preliminary work, largely informed by Aqua/AIRS retrievals, suggests that increased moisture in the lower-middle troposphere favors system occurrence (and enhanced rainfall), with lifecycle characteristics (e.g., system sizes, duration) being strongly impacted by lower-troposphere stability. Composite preliminary work suggests varying timescales for moistening and stabilization (as short as 1-hr, to as long as 6-12 hours), with regional differences noted. We hypothesize some regional differences may be the result of evaluating system-environment characteristics independent of lifecycle stage, since moving convective systems statistically cross some locations at systematically different lifecycle stages than others. All results suggest a more process-oriented “convective-systems” scale approach that entails investigating the cloud, rainfall, and environmental characteristics as a function of convective system lifecycle stages.
To this end, we propose a project to improve our understanding of convective system lifecycles, where convective system lifecycle stages are provided by a Geostationary Infrared (IR) system tracking database, environmental thermodynamic data are provided by multiple satellites (Aqua, Suomi-NPP, JPSS-1 [a.k.a. NOAA-20]), and supplementary observations of the lower-troposphere are provided by RapidScat cold pool retrievals and in situ (e.g., buoys) observational sources. We initially focus on the entirety of the tropical (30S-30N) oceanic domain, where convective diurnal cycles are less pronounced and controls on convective lifecycles are not well understood, yet GCM rainfall, convection, and cloud biases are still pervasive.
Hypotheses are posed and a framework is laid out for testing the relationship between convective system longevity, system sizes, and the timescale for thermodynamic stabilization of the lower-troposphere. We propose a unique leveraging of time-lagged sampling of temperature and water vapor profiles from Aqua, SNPP and JPSS-1 to assess short term changes in the environment driven by convection as part of understanding the large-scale vs local control on environments surrounding convection and timescales for stabilization. This process-oriented analysis has a potential feedback onto the sounder retrieval community that aims to understand how quickly changing environments affect validation efforts using radiosondes launched at times lagged relative to satellite overpass times. We extend aspects of our work to land environments in order to make more expansive conclusions about convective system duration, size and the environment.
The mapping of Level 2 sounder data to system cloud shields and lifecycle stages allows for a novel process-oriented analysis aiming to understand convective system sizes which closely tie to anvil cloud area sizes, an important endeavor considering the role of anvil cloud area in high cloud feedbacks (Sherwood et al., 2020). Our results overall will inform the development of improved convective system size representation in climate models, an effort PI Elsaesser is involved in with the NASA-GISS climate model parameterization team.
Project: “Using Polarimetric signatures of GNSS signals for the remote sensing characterization of the vertical structures of heavy precipitation and water vapor in clouds”
Funding Agency: NASA
Program: Global Navigation Satellite System Research (NNH19ZDA001N-GNSS)
Proposal Period: 2020-2023
Amount: $591,531 total ($61,179 to UVA)
Team: Manuel de la Torre Juarez (JPL, PI), Kathleen Schiro (UVA, Co-I), Joe Turk (JPL, Co-I), Kuo-Nung Wang (JPL, Co-I), Estel Cardellach (ICE-CSIC, Co-I), Chi Ao (JPL, Collaborator), Ramon Padulles (ICE-CSIC, Collaborator)
Organized convective systems are responsible for a majority of tropical precipitation. However, the feedbacks, mechanisms, and interactions between convection and its environment permitting the organization of convection are poorly understood. The propagation of the circularly polarized GNSS signal through the atmosphere has been shown recently to be altered by precipitating hydrometeors. Theoretical analyses, radio occultation (RO) from space, and mountain top experiments have shown the potential to characterize the vertical structure of heavy precipitation. When combined with the coincident more standard RO products of water vapor, temperature, and neutral stability to convection inside thick clouds, Polarimetric RO (PRO) can clarify the role of the vertical distributions of water vapor, temperature and associated buoyancy in controlling the transition to heavy precipitation. This work focuses on the observations simultaneously of the heights at which the transition to heavy precipitation occurs and the thermodynamic conditions associated with this transition.
The role of the University of Virginia team in their collaboration with the Jet Propulsion Laboratory team, is to define science requirements that guide the priorities of the GNSS PRO retrieval products.
To that effect the U of Virginia team’s work will carry out analyses linking variability in the thermodynamic structure of the troposphere to precipitation intensity, deep convection onset, and the convective lifecycle by:
-Collocating GNSS and GNSS PRO retrievals with TRMM/GPM radar data and mesoscale convective tracking databases (which use IR geostationary imagery and IMERG precipitation)
-Preparing composites of Thermodynamic profiles derived from GNSS retrievals as a function of the convective lifecycle over both continental and oceanic regimes in the tropics.
-Comparing characteristics of the thermodynamic environment preceding convection organization to study the associations between variability in moisture vertical structure and favorability of organization/clustering.
-Studying the variability of the thermodynamic structure of the atmosphere in response to deep convection, as deep convection-environment interactions are two-way interactions.
-Proposing retrieval product priorities based on the results of the science analyses described above.
-Training students in this area of research.
-Reporting the results each 6 months to JPL and at scientific meetings, conferences, or refereed publications.
-These convection-environment interactions underpin variability in tropical weather and climate across scales and are critical to our improved understanding and modeling of the global climate system.
Project: “Thermodynamic and Non-thermodynamic Controls on Deep Convection in ARM Observations”
Funding Agency: DOE
Program: Atmospheric Systems Research (ASR)
Proposal Period: 2022-2026
Amount: $739,851 total ($179,916 to UVA)
Team: Fiaz Ahmed (UCLA, PI), Kathleen Schiro (UVA, Co-PI), David Neelin (UCLA, Co-PI), Rong Fu (UCLA, Co-I), Scott Giangrande (BNL, Collaborator), Shaocheng Xie (LLNL, Collaborator)
Deep convection remains one of the most challenging processes to represent in weather and climate models, partly because of multiple controlling factors. We propose to create a framework based on Atmospheric Radiation Measurement Program (ARM) observations, with which to assess the relative influence of thermodynamic, dynamic and aerosol effects on deep convection. This framework will expand upon a previously identified empirical buoyancy measure that constrains the thermodynamic influence on deep convective precipitation in the tropics. We also propose to integrate this precipitation-buoyancy framework into the ARM model diagnostics package (ARM-DIAGS).
Prior work with observations from DOE ARM sites from the Tropical Western Pacific (TWP) and Green Ocean Amazon (GoAmazon2014/5) helped establish the empirical precipitation- buoyancy framework, which constrains the thermodynamic influences on deep convection. This project will expand the buoyancy framework using ARM site observations across a wider range of environments (tropical and sub-tropical; oceanic and continental). We will examine data from recent ARM field campaigns: Cloud, Aerosol, and Complex Terrain Interactions (CACTI), GoAmazon2014/5, and Tracking Aerosol Convection Interactions Experiment (TRACER). We will also use long-term measurements from the Southern Great Plains (SGP) and TWP sites. We will extend the buoyancy framework by accounting for non-thermodynamic controls on convection, which include dynamical (e.g., wind shear, orography, sea-breeze convergence) and microphysical (aerosol) effects. By controlling for thermodynamic factors, we propose to use the precipitation-buoyancy framework to more precisely evaluate the dynamical and aerosol effects on convection. We will employ multi-instrument ARM observations, including radiosondes, surface meteorological instruments, precipitation and cloud radars, radar wind profilers, and aerosol observing systems. We will also quantify how the environmental influence on convection changes as a function of the cloud-lifecycle and convective organization. These efforts will allow us to construct a broader framework for representing deep convection dependence on its environment. To aid climate model development, we will also integrate the observed precipitation-buoyancy relationship into the ARM model diagnostics package (ARM- DIAGS). We also propose to use the buoyancy framework to identify optimal parameter regimes for development versions of DOE’s Energy Exascale Earth System Model (E3SM). These efforts will identify convection-related process errors in climate models. Our team has the required expertise in ARM instrumentation, convective physics, aerosol-cloud interactions and climate model diagnostics to achieve the proposed targets.
Our proposed work targets Atmospheric System Research (ASR) focus areas on convective processes and aerosol processes, and is strongly aligned with ASR’s overarching goal to “improve understanding of key cloud, aerosol, precipitation, and radiation processes that affect the Earth’s radiative balance and hydrological cycle.”
Project: “Building an interdisciplinary and interagency collaboration between DOE BER and the University of Virginia”
Funding Agency: DOE
Program: Biological and Environmental Research (BER)
Proposal Period: 2022-2024
Amount: $30,000 (all to UVA)
Team: Xi Yang (Principal Investigator), Lawrence Band (Co-Investigator), Stephan De Wekker (Co-Investigator), Howard Epstein (Co-Investigator), Kevin Grise (Co-Investigator), Ajay B. Limaye (Co-Investigator), Stephen Macko (Co-Investigator), Todd Scanlon (Co-Investigator), Kathleen Schiro (Co-Investigator), Lauren M. Simkins (Co-Investigator)
The DOE program in Biological and Environmental Research (BER) has supported transformative and innovative research in atmospheric sciences, hydrology, geosciences, and ecology. The Department of Environment Sciences at the University of Virginia (UVA) has established itself as one of the leaders in these fields and the interdisciplinary research enabled by the synergies among its sub-disciplines within the department. UVA President Jim Ryan has announced that environmental resilience is one of the top supported areas at the university. While there is great potential for interdisciplinary and interagency collaborations between the UVA and various DOE laboratories and programs, no formal partnership has been established, nor has the Department of Environmental Sciences received DOE funding in the past few years. The interdisciplinary team within the Department of Environmental Sciences at UVA consists of ecologists, atmospheric scientists, geoscientists, and hydrologists. We propose to develop partnerships with existing DOE laboratories and programs and build capabilities to respond to future EESSD calls. The proposed activities include week-long faculty visits to various national laboratories, trips to DOE annual meetings to interact with program managers, and collaboration with DOE programs through modeling, laboratory, and field research projects. The strong interdisciplinary research of the Department of Environmental Sciences allows for us to uniquely collaborate with many DOE laboratories focused on Earth-system and planetary research. We will also invite program managers and scientists from DOE laboratories and projects to a workshop at the UVA that provides interdisciplinary synergies between UVA and DOE laboratories and allows for student engagement with DOE personnel.
Project: “Collaborative Research: Characterizing interactions between tropical deep convection and the environment using a buoyancy framework”
Funding Agency: NSF
Program: Physical and Dynamic Meteorology / Climate and Large-Scale Dynamics
Proposal Period: 2022-2026
Amount: $1.2 million total ($440,412 to UVA)
Team: Kathleen Schiro (PI), Fiaz Ahmed (Co-PI), Brandon Wolding (Co-PI), Angel Adames-Corraliza (Co-PI)
Our overarching goalis to work towards identifying a conceptual model for tropical deep convection that can be used to explain precipitation variability across scales (diurnal, seasonal, intraseasonal, and interannual), building on our knowledge of relationships between precipitation and estimates of entraining plume buoyancy (Ahmed and Neelin 2018; Schiro et al. 2018; Schiro and Neelin 2019; Ahmed et al. 2020; Adames et al. 2021; Wolding et al. 2022) hereafter referred to as the “precipitation-buoyancy (P-B) framework.” Our main research questions are (1) to what extent do “grid-scale” O(100 km) integrated measures of convective instability accurately assess the capacity of the atmosphere to support deep convection, and (2) how can we refine grid-scale average instability measures to account for variability and dynamics across scales? We will address these questions with four proposal objectives. Our first objective is to characterize how the precipitation-buoyancy (“P-B”) relationship varies as a function of convective variability across spatial scales. Our second objective is to examine how P-B thresholds change as a function of mesoscale convective system evolution, estimating the sensitivity of deep convection to its thermodynamic environment throughout different lifecycle stages. Our third objective is to characterize how dynamical interactions – mass flux/entrainment, wind shear, vorticity, cold pools – modify thermodynamic controls on deep convective evolution. Our fourth objective will be to put our new buoyancy framework to the test: to apply the refined P-B framework to study diurnal, regional, and intraseasonal precipitation variability across the tropics. Using new mesoscale convective tracking databases and cold pool gradient feature detection algorithms, long-standing radar data, field campaign data, and satellite observations, combined with novel compositing techniques, the proposal team is uniquely positioned to study thermodynamic controls on tropical deep convection in a new way and thus to refine a buoyancy framework with significant potential to improve prediction of future hydroclimatological changes and extremes.
Project: “P2PE Proposal – Climate Science: Bridging Global and Community Scales“
Internal Grant (UVA)
Amount: $5,068,030 (all to UVA)
Our vision is to dramatically advance the University of Virginia as a world leader in climate change analysis and solutions research. We propose an initiative focused on bridging global-scale climate dynamics with community-scale processes and systems to guide decision-making for equitable climate resilience and sustainability outcomes. This is a critical knowledge gap in creating actionable solutions to climate change, and one in which UVA is uniquely poised to become a preeminent leader given existing faculty particularly in Environmental Sciences, Engineering, Data Science, the Biocomplexity Institute, the Equity Center, with coordination through and recent investments in the Environmental Resilience Institute (ERI) and cluster hires in environmental resilience. We will 1) strengthen our capacity in understanding and projecting climate dynamics and impacts at scales that matter for communities (i.e. regional/local and years/decades), 2) use these enhanced projections in combination with local- scale data (e.g. real-time environmental sensing) to improve regional and global scale quantification of energy/carbon dynamics, and 3) drive actionable natural and engineered solutions to climate change (e.g. land use changes, infrastructure, decarbonization). The capacity this initiative will support is critical for answering urgent societally-relevant questions, such as how do planners in coastal Virginia use climate models to inform adaptation of their infrastructure over the coming decades; or how are national targets for decarbonization are impacted by regional constraints on land use and equity?
We propose a 5-year initiative that includes three components: 1) an end-to-end data and model support infrastructure to bridge the computational gap between global climate dynamics and community-scale impacts and action; 2) a pipeline of Postdoctoral Fellows, specifically targeting traditionally underrepresented groups in STEM, to support the development of this modeling work; and 3) three faculty positions (Assistant Professors) in cross-scale modeling (e.g., artificial intelligence and machine learning, physics-based), decision support (e.g., agent-based modeling), and geospatial analysis (e.g, data acquisition and integration). The model support infrastructure will be coordinated by a proposed staff member who will help co-create the architecture of the model integration and data structure along with the participants. The postdoctoral fellows are critical to seed methodological and application advances using the capacity made possible by this effort, bridging us from prominence to preeminence in the field of climate science. The postdocs will collaborate with faculty and graduate students to strengthen our pan-University network, and accelerate research productivity at the forefront of climate science and action. They will be trained to transition to faculty positions at UVA or elsewhere, thereby enhancing diversity nationally among the next generation of faculty addressing climate change. The appointment of three faculty members at UVA and additional enhancements in data personnel and infrastructure capacity will ensure sustainability of this initiative. The targeted research objectives of this initiative, the critical mass of postdoctoral fellows, the appointment of new faculty, and the enhancement of data processing capacity will elevate UVA from prominence to preeminence in climate resilience and sustainability. This initiative is aligned with UVA’s Environmental Resilience and Sustainability priority of the 2030 Strategic Plan; addresses climate equity, which aligns with the Democracy priority in the Plan; and supports the Plan’s goal of enhancing diversity, equity, and inclusion. We also envision major benefits through partnership with our local community and the State.
Project: “Linkage Between Deep Convection, Large-scale Circulation and Low Cloud Feedback”
Funding Agency: NOAA
Amount: $490,900 total (none to UVA)
Project: “The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity“
Funding Agency: DOE RGMA
Amount: $493,403 total (none to UVA)