Bithi De

The CI-PIVOT project, a collaboration between Indiana University, Purdue, and Mississippi State, addresses the gap between complex HPC/AI resources and domain researchers by transforming science experts into embedded Cyberinfrastructure Professionals (CIPs). Through an 18-month cohort model, this project establishes a scalable framework for professionalizing the CIP role, providing insights into training that can be generalized across the broader research ecosystem.

Cyberinfrastructure Professionals (CIPs) play a critical role in enabling scalable, data-intensive, and collaborative science by bridging domain research and advanced computational systems. However, pathways into CIP roles remain poorly defined, particularly for domain scientists transitioning into research computing careers. This study presents a conceptual framework and empirical insights from the NSF-funded CI-PIVOT initiative under the Strengthening the Cyberinfrastructure Professionals Ecosystem (SCIPE) program. We articulate a staged pathway for CIP development, describe the structure and outcomes of an 18-month cohort-based training model, and synthesize key design principles for building sustainable CI workforce pipelines. These findings contribute toward formalizing CIP career trajectories and informing institutional strategies for workforce development in cyberinfrastructure-enabled science.

A neural network (NN) surrogate of the NASA GISS ModelE atmosphere (version E3) is trained on a perturbed parameter ensemble (PPE) spanning 45 physics parameters and 36 outputs. The NN is leveraged in a Markov Chain Monte Carlo (MCMC) Bayesian parameter inference framework to generate a second posterior constrained ensemble coined a “calibrated physics ensemble,” or CPE. The CPE members are characterized by diverse parameter combinations and are, by definition, close to top‐of‐atmosphere radiative balance, and must broadly agree with numerous hydrologic, energy cycle and radiative forcing metrics simultaneously. Global observations of numerous cloud, environment, and radiation properties (provided by global satellite products) are crucial for CPE generation. The inference framework explicitly accounts for discrepancies (or biases) in satellite products during CPE generation. We demonstrate that product discrepancies strongly impact calibration of important model parameter settings (e.g., convective plume entrainment rates; fall speed for cloud ice). Structural improvements new to E3 are retained across CPE members (e.g., stratocumulus simulation). Notably, the framework improved the simulation of shallow cumulus and Amazon rainfall while not degrading radiation fields, an upgrade that neither default parameters nor Latin Hypercube parameter searching achieved. Analyses of the initial PPE suggested several parameters were unimportant for output variation. However, many “unimportant” parameters were needed for CPE generation, a result that brings to the forefront how parameter importance should be determined in PPEs. From the CPE, two diverse 45‐dimensional parameter configurations are retained to generate radiatively‐balanced, auto‐tuned atmospheres that were used in two E3 submissions to CMIP6.

A document by Gregory Elsaesser. Click on the document to view its contents.

Previous studies have documented the impact of the Arctic sea ice loss and associated warming on the midlatitude weather and climate, especially the influence of sea ice retreat over the Barents-Kara Sea on the North Atlantic and Europe regions. However, less attention has been given to other geographical locations over the Arctic, and to the linear additivity of the circulation response to regional Arctic sea ice loss and temperature anomalies. Using a simplified dry dynamical core model, we demonstrate that responses to regional Arctic temperature anomalies over the Barents-Kara Sea, Baffin Bay-Davis Strait-Labrador Sea, and East Siberia-Chukchi Sea, separately, cause similar equatorward shift of the tropospheric jet, but different stratospheric polar vortex responses. Furthermore, responses to regional Arctic temperature anomalies are not linearly additive, and the residual resembles a positive Northern Annular Mode-like structure. Additional targeted experiments highlight the stratospheric influence in the non-additivity of the midlatitude tropospheric response.

The persistent inter‐model spread in the response of global‐mean surface temperature to increased CO₂ (known as the “Equilibrium Climate Sensitivity,” or “ECS”) is a crucial problem across model generations. This work examines the influence of the models' present‐day atmospheric circulation climatologies, and the accompanying climatological cloud radiative effects, in explaining that spread. We analyze the Coupled Model Intercomparison Project Phase 6 (CMIP6) models and find that they simulate a more poleward, and thus more realistic, edge of the Hadley cell (HC) in the Southern Hemisphere than the CMIP5 models, although the climatological shortwave cloud radiative effects are similar in the two generations of models. A few CMIP5 models with extreme equatorward biases in the HC edge exhibited high ECS due to strong Southern midlatitude shortwave cloud radiative warming in response to climate change, suggesting an ECS dependence on HC position. We find that such constraint no longer holds for the CMIP6 models, due to the absence of models with extreme HC climatologies. In spite of this, however, the CMIP6 models show an increased spread in ECS, with more models in the high ECS range. In addition, an improved representation of the climatological jet dynamics does not lead to a new emergent constraint in the CMIP6 models either.

Previous studies have documented the impact of the Arctic sea ice loss and associated warming on the midlatitude weather and climate, especially the influence of sea ice retreat over the Barents‐Kara Sea on the North Atlantic and Europe regions. However, less attention has been given to other geographical locations over the Arctic, and to the linear additivity of the circulation response to regional Arctic sea ice loss and temperature anomalies. Using a simplified dry dynamical core model, we demonstrate that responses to regional Arctic temperature anomalies over the Barents‐Kara Sea, Baffin Bay‐Davis Strait‐Labrador Sea, and East Siberia‐Chukchi Sea, separately, cause similar equatorward shift of the tropospheric jet, but different stratospheric polar vortex responses. Furthermore, responses to regional Arctic temperature anomalies are not linearly additive, and the residual resembles a positive Northern Annular Mode‐like structure. Additional targeted experiments highlight the stratospheric influence in the non‐additivity of the midlatitude tropospheric response.

Recent analyses of Coupled Model Intercomparison Project phase 6 (CMIP6) models have shown higher climate sensitivities than previously reported, and this increase has been preliminary attributed to the simulation of anomalous Shortwave Cloud Radiative Effect (SWCRE) over the southern midlatitude regions. In this work, we further explore how the seasonal and annual SWCRE over different regions of the globe influence the model climate sensitivities. Our study suggests a significant contribution of SWCRE on climate sensitivities in both northern and southern midlatitudes; and the relationship remains robust across the seasons. Additionally, we assess the underlying physics of the inter-model spread to diagnose model biases. The results will contribute to quantify the severity of the Equilibrium Climate Sensitivity, as simulated by the CMIP6 models.

Stratosphere-troposphere dynamical coupling links the Siberian cold winters to sea ice loss over Barents-Kara seas.