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Wang, Dali

Publications and source records attributed to Wang, Dali.

Enabling kilometer-scale E3SM land model simulation over North America: A new integrated framework solution

This study introduces a novel framework designed to enhance the performance, scalability, and portability of the kilometer-scale E3SM Land Model (km-ELM) within the E3SM modeling infrastructure. By seamlessly integrating cutting-edge data tools, we address existing challenges such as slow performance, limited scalability, and difficulties in software integration in current data-driven ELM simulation over large geographic areas. Our innovative approach leverages the KiloCraft data toolkit to generate unified inputs for simulations ranging from a single-cite case, to a 72,083-cell regional case to a continental configuration encompassing 21.6 million land grid cells at a 1 km × 1 km resolution. We conduct extensive strong- and weak-scaling experiments on three state-of-the-art supercomputers, utilizing up to 100,800 CPU cores across 2400 compute nodes to evaluate end-to-end metrics including wall-clock time, simulation-years-per-day (SYPD), initialization costs, and I/O throughput. Our results reveal the land (LND) component’s efficient scaling, demonstrating near-ideal weak scaling and strong-scaling parallel efficiencies reaching up to 87% at 50,400 cores. We confirm portability and reproducibility through bitwise-equivalent outputs across different machines using identical inputs over supported machines. Notably, at extreme scales, we identify I/O as a critical bottleneck and that leads to effective solution with the SCORPIO/ADIOS stack. Collectively, these findings validate the deployment of km-ELM at a continental scale with high parallel efficiency and provide essential guidance on configuration, decomposition, and I/O settings for optimized kilometer-scale land simulations in E3SM. This work emphasizes the innovative design and practical solutions that enhance the operational capabilities of km-ELM, focusing on software performance and scalability while leaving detailed scientific evaluations of simulated land processes for future investigations.

E3SM land model (ELM), km-ELM, scalability, perfor↗

A Summary of Proposed Changes to the Current ICARTT Format Standards and their Implications to Future Airborne Studies

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public.

Northup, Emily↗

Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public.

Early, Amanda Benson↗

An Overview of the Challenges With and Proposed Solutions for the Ingest and Distribution Processes for Airborne Data Management

The current data management practices for NASA airborne field projects have successfully served science team data needs over the past 30 years to achieve project science objectives, however, users have discovered a number of issues in terms of data reporting and format. The ICARTT format, a NASA standard since 2010, is currently the most popular among the airborne measurement community. Although easy for humans to use, the format standard is not sufficiently rigorous to be machine-readable. This makes data use and management tedious and resource intensive, and also create problems in Distributed Active Archive Center (DAAC) data ingest procedures and distribution. Further, most DAACs use metadata models that concentrate on satellite data observations, making them less prepared to deal with airborne data.

Beach, Aubrey↗

Processing of ICARTT Data Files Using Fuzzy Matching and Parser Combinators

In this paper, the task of parsing and matching inconsistent, poorly formed text data through the use of parser combinators and fuzzy matching is discussed. An object-oriented implementation of the parser combinator technique is used to allow for a relatively simple interface for adapting base parsers. For matching tasks, a fuzzy matching algorithm with Levenshtein distance calculations is implemented to match string pair, which are otherwise difficult to match due to the aforementioned irregularities and errors in one or both pair members. Used in concert, the two techniques allow parsing and matching operations to be performed which had previously only been done manually.

Rutherford, Matthew T.↗