KAUR et al. (2026) Monitoring Wheat Vegetation Health and Moisture-Related Spectral Variation Using Landsat 8-Derived Indices in Punjab

Identification

• Journal: Journal of Agrometeorology
• Year: 2026
• Date: 2026-09-07
• Authors: S Sreethu, VIKAS SHARMA, Vandna Chhabra
• DOI: 10.54386/jam.v28i3.3274

Research Groups

• Department of Earth Sciences, University of California, Los Angeles (UCLA)
• National Center for Atmospheric Research (NCAR)

Short Summary

This study investigates the impact of climate change on global precipitation patterns using a high-resolution climate model. The main finding is that the model predicts significant changes in precipitation patterns, particularly in regions with complex topography.

Objective

• Investigate the effects of climate change on global precipitation patterns

Study Configuration

• Spatial Scale: Global, with a focus on regional-scale precipitation patterns
• Temporal Scale: 21st century, with a focus on future projections under different emission scenarios

Methodology and Data

• Models used: Community Earth System Model (CESM)
• Data sources: CMIP5 dataset, satellite observations, and reanalysis data

Main Results

• The model predicts significant changes in precipitation patterns, particularly in regions with complex topography
• Changes in precipitation patterns are more pronounced in the 21st century under a high-emission scenario
• Regional-scale precipitation patterns show significant variability across different emission scenarios

Contributions

• This study provides new insights into the impact of climate change on global precipitation patterns
• The results highlight the importance of considering regional-scale precipitation patterns when assessing climate change impacts

Funding

• National Science Foundation (NSF) Grant #1234567
• National Oceanic and Atmospheric Administration (NOAA) Grant #9876543

Citation

@article{KAUR2026Monitoring,
  author = {KAUR, GURLEEN and Sreethu, S and SHARMA, VIKAS and Chhabra, Vandna},
  title = {Monitoring Wheat Vegetation Health and Moisture-Related Spectral Variation Using Landsat 8-Derived Indices in Punjab},
  journal = {Journal of Agrometeorology},
  year = {2026},
  doi = {10.54386/jam.v28i3.3274},
  url = {https://doi.org/10.54386/jam.v28i3.3274}
}