Data & Publications

Change Hawaiʻi Project Data

Climate Data for Hawaiʻi

The Hawaiʻi Climate Data Portal (HCDP) launched on March 3, 2022, after almost a decade of development with the support of the NSF EPSCoR Track-1 ʻIke Wai project and continuing support of the current NSF EPSCoR Track-1 Change HI project.

In its first year, the HCDP, which hosts a wide range of data products, climate tools and resources, received 40,000 visits to the site from 23,000 unique visitors representing 119 different countries. The more than 45,000 unique visitors to the site have accessed more than 20 million HCDP files.

 Hawaiʻi Climate Data Portal

Near-real-time monthly rainfall and daily temperature maps, visualization tools and more.

GO to the Climate data Portal

A major enhancement to the HCDP is the integration of data from the NSF Hawaiʻi Mesonet project, which plans to establish 100 new climate stations across the state over the next two years. Similar efforts are underway in American Samoa, and funding is being sought for a mesonet in Guam.

Upcoming developments include mapping hourly wind speed and solar radiation and creating tools for wildfire risk assessment and drought forecasting.

PyForestScan

PyForestScan is a Python library for analyzing and visualizing forest structure using airborne 3D point cloud data. It facilitates the extraction of essential forest metrics—such as canopy height, plant area index (PAI), canopy cover, plant area density (PAD), and foliage height diversity (FHD)—to help researchers and land managers better understand forest composition, health, and ecological processes. By offering a streamlined workflow for processing and interpreting point cloud data, PyForestScan is a powerful and user-friendly tool for those seeking detailed insights into forest ecosystems

Go To PyForestScan

Publications

Researchers have published and presented many articles and abstracts related to the research done throughout the Change HI project. Below is a list of project publications.

Lee, C. J., Tran, G., Tabalba, R., Leigh, J., & Longman, R. (2024). Macro-Queries: An Exploration into Guided Chart Generation from High Level Prompts. arXiv. https://doi.org/10.48550/ARXIV.2408.12726 Cite
Rosam, J. R., Warman, L., Ostertag, R., Perroy, R., & Cordell, S. (2024). Light quality and spatial variability influences on seedling regeneration in Hawaiian lowland wet forests. Journal of Applied Ecology, 61(11), 2638–2652. https://doi.org/10.1111/1365-2664.14775 Cite
Westerband, A. C., & Barton, K. E. (2025). Investigating the origins and effects of intraspecific trait variation. In Plant Functional Traits (pp. 205–238). Elsevier. https://doi.org/10.1016/B978-0-443-13367-1.00010-7 Cite
Tabalba, R., Lee, C. J., Tran, G., Kirshenbaum, N., & Leigh, J. (2024). ArticulatePro: A Comparative Study on a Proactive and Non-Proactive Assistant in a Climate Data Exploration Task. arXiv. https://doi.org/10.48550/ARXIV.2409.10797 Cite
Wang, C., Stopa, J. E., Vandemark, D., Foster, R., Ayet, A., Mouche, A., Chapron, B., & Sadowski, P. (2025). A multi‐tagged SAR ocean image dataset identifying atmospheric boundary layer structure in winter tradewind conditions. Geoscience Data Journal, 12(1), e282. https://doi.org/10.1002/gdj3.282 Cite
McLean, J., & Cleveland, S. (2024). A Fast TIFF File Value Extractor For Generating Timeseries Data to Enable Virtual Climate Stations. https://doi.org/10.5281/ZENODO.13870135 Cite
Noe, K., & Kirshenbaum, N. (2024). Where Generalized Equitable Design Practice Meet Specific Indigenous Communities. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–8. https://doi.org/10.1145/3613904.3642931 Cite
Chen, C. Y., Christoffels, A., Dube, R., Enos, K., Gilbert, J. E., Koyejo, S., Leigh, J., Liquido, C., McKee, A., Noe, K., Peng, T.-Q., & Taiuru, K. (2024). Increasing the presence of BIPOC researchers in computational science. Nature Computational Science, 4(9), 646–653. https://doi.org/10.1038/s43588-024-00693-6 Cite
Stokes, A. J., Vary, N. G., & Lorshbough, E. L. (2024). Systemic biases are leading to an intersex research void. Nature, 635(8038), 290–290. https://doi.org/10.1038/d41586-024-03662-1 Cite
Rodríguez-Puerta, F., Perroy, R. L., Barrera, C., Price, J. P., & García-Pascual, B. (2024). Five-Year Evaluation of Sentinel-2 Cloud-Free Mosaic Generation Under Varied Cloud Cover Conditions in Hawai’i. Remote Sensing, 16(24), 4791. https://doi.org/10.3390/rs16244791 Cite
Bagheri, H., Mirakhorli, M., Fazelnia, M., Mujhid, I., & Hasan, M. R. (2024). Neuro-Symbolic Approach to Certified Scientific Software Synthesis. Proceedings of the 1st ACM International Conference on AI-Powered Software, 147–150. https://doi.org/10.1145/3664646.3664776 Cite
Johnson, A. E., Renambot, L., Marai, G. E., Tsoupikova, D., Papka, M. E., Long, L., Plepys, D., Talandis, J., Brown, M. D., Leigh, J., Sandin, D. J., & DeFanti, T. A. (2024). Electronic Visualization Laboratory’s 50th Anniversary Retrospective: Look to the Future, Build on the Past. PRESENCE: Virtual and Augmented Reality, 33, 77–127. https://doi.org/10.1162/pres_a_00421 Cite
Bhattacharya, A., Di Eugenio, B., Grosso, V., Johnson, A., Tabalba, R., Kirshenbaum, N., Leigh, J., & Zellner, M. (2024). A Conversational Assistant for Democratization of Data Visualization: A Comparative Study of Two Approaches of Interaction. Statistical Analysis and Data Mining: An ASA Data Science Journal, 17(6), e11714. https://doi.org/10.1002/sam.11714 Cite
Cleveland, S. B., Tanaka, S., Dumanlang, M., Stokes, A. J., Johnson, P. M., Leigh, J., Giambelluca, T. W., Turner, H., & Jacobs, G. A. (2024). Building a Cybertraining program for Climate Scientists in the Pacific to integrate Cyberinfrastructure and Open Science. Practice and Experience in Advanced Research Computing 2024: Human Powered Computing, 1–4. https://doi.org/10.1145/3626203.3670617 Cite
Takagi, Y., Tabalba, R., Kirshenbaum, N., & Leigh, J. (2024). Abstracted Trajectory Visualization for Explainability in Reinforcement Learning. 2024 IEEE Conference on Artificial Intelligence (CAI), 75–82. https://doi.org/10.1109/CAI59869.2024.00023 Cite
Longman, R. J., Lucas, M. P., Mclean, J., Cleveland, S. B., Kodama, K., Frazier, A. G., Kamelamela, K., Schriber, A., Dodge, M., Jacobs, G., & Giambelluca, T. W. (2024). The Hawai‘i Climate Data Portal (HCDP). Bulletin of the American Meteorological Society, 1(aop). https://doi.org/10.1175/BAMS-D-23-0188.1 Cite
Ware, I. M., Ostertag, R., Cordell, S., Giardina, C. P., Sack, L., Medeiros, C. D., Inman, F., Litton, C. M., Giambelluca, T., John, G. P., & Scoffoni, C. (2022). Multi-Stemmed Habit in Trees Contributes Climate Resilience in Tropical Dry Forest. Sustainability, 14(11), 6779. https://doi.org/10.3390/su14116779 Cite
Huang, Y.-F., Gayte, M., Tsang, Y., Longman, R. J., Nugent, A. D., Kodama, K., Lucas, M. P., & Giambelluca, T. W. (2022). Hourly rainfall data from rain gauge networks and weather radar up to 2020 across the Hawaiian Islands. Scientific Data, 9(1), 334. https://doi.org/10.1038/s41597-022-01430-2 Cite
Valdez, D., Bunnell, A., Lim, S. Y., Sadowski, P., & Shepherd, J. A. (2023). Performance of progressive generations of GPT on an exam designed for certifying physicians as Certified Clinical Densitometrists. https://doi.org/10.1101/2023.07.25.23293171 Cite
Mizukami, N., Newman, A. J., Littell, J. S., Giambelluca, T. W., Wood, A. W., Gutmann, E. D., Hamman, J. J., Gergel, D. R., Nijssen, B., Clark, M. P., & Arnold, J. R. (2022). New projections of 21st century climate and hydrology for Alaska and Hawaiʻi. Climate Services, 27, 100312. https://doi.org/10.1016/j.cliser.2022.100312 Cite
Belcaid, M., Leigh, J., Theriot, R., Kirshenbaum, N., Tabalba, R., Rogers, M., Johnson, A., Brown, M., Renambot, L., Long, L., Nishimoto, A., North, C., & Harden, J. (2023). Reflecting on the Scalable Adaptive Graphics Environment Team’s 20-Year Translational Research Endeavor in Digital Collaboration Tools. Computing in Science & Engineering, 25(2), 50–56. https://doi.org/10.1109/MCSE.2023.3297753 Cite
Kodama, K. M., Kourkchi, E., Longman, R. J., Lucas, M. P., Bateni, S. M., Huang, Y., Kagawa‐Viviani, A., Mclean, J., Cleveland, S. B., & Giambelluca, T. W. (2024). Mapping Daily Air Temperature Over the Hawaiian Islands From 1990 to 2021 via an Optimized Piecewise Linear Regression Technique. Earth and Space Science, 11(1), e2023EA002851. https://doi.org/10.1029/2023EA002851 Cite
Schanzenbach, D., Merrill, R., Cleveland, S., & Jacobs, G. (2023). Integrated Advanced Computing Management Interface (IACMI): A Web Portal to Democratize HPC Management. Practice and Experience in Advanced Research Computing, 328–331. https://doi.org/10.1145/3569951.3597568 Cite
Merrill, R., Schanzenbach, D., Cleveland, S. B., & Jacobs, G. A. (2023). Mana - Bringing Accessible HPC to Hawai’i. Practice and Experience in Advanced Research Computing, 86–93. https://doi.org/10.1145/3569951.3593611 Cite
Tabalba, R., Kirshenbaum, N., Leigh, J., Bhatacharya, A., Veronica, G., Johnson, A., Di Eugenio, B., & Zellner., M. (2023). An Investigation into an Always Listening Interface to Support Data Exploration. Proceedings of the 28th International Conference on Intelligent User Interfaces (IUI ’23). https://doi.org/10.3390/su141912023 Cite
Ackerman, K. L., Nugent, A. D., & Taing, C. (2023). Mechanisms controlling giant sea salt aerosol size distributions along a tropical orographic coastline. Atmospheric Chemistry and Physics, 23(21), 13735–13753. https://doi.org/10.5194/acp-23-13735-2023 Cite
DiManno, N., Ostertag, R., Uowolo, A., Durham, A., Blakemore, K., Cordell, S., & Vitousek, P. (2023). Functional trait‐based restoration alters nutrient cycling and invasion rates in \textlessspan style="font-variant:small-caps;"\textgreaterH\textless/span\textgreater awaiian lowland wet forest. Ecological Applications, 33(6), e2894. https://doi.org/10.1002/eap.2894 Cite