edu.ucar.opensky::articles:26483 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T19:28:23.825982 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7j67mxc https://doi.org/10.25318/3210000201-eng https Related Dataset #1 Estimated areas, yield and production of principal field crops by Small Area Data Regions, in metric and imperial units https://doi.org/10.5065/D6V40SXP https Related Dataset #2 High Resolution WRF Simulations of the Current and Future Climate of North America https://doi.org/10.5067/MODIS/MOD15A2H.006 https Related Dataset #3 MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006 https://doi.org/10.5281/zenodo.7023831 https Related Dataset #4 Noah-MP data for modeling Canadian spring wheat study https://doi.org/10.5281/zenodo.7556046 https Related Software #1 CharlesZheZhang/noahmp: NoahMP LSM v4.4 with spring wheat https://doi.org/10.5281/zenodo.7556048 https Related Software #2 CharlesZheZhang/hrldas: HRLDAS driver for NoahMP LSM v4.4 with spring wheat Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress 2023-07-11T00:00:00Z publication https://n2t.org/ark:/85065/d7j67mxc https://doi.org/10.5194/gmd-16-3809-2023 Zhang, Z. author Li, Y. author Chen, Fei author Harder, P. author Helgason, W. author Famiglietti, J. author Valayamkunnath, Prasanth author He, Cenlin author Li, Z. author UCAR/NCAR - Library publisher The US Northern Great Plains and the Canadian Prairies are known as the world's breadbaskets for their large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model for a long time period (13 years) and fine spatial scale (4 km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at a point scale, (2) applying a dynamic planting and harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the United States Department of Agriculture(USDA). Results suggest that incorporating a dynamic planting and harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in threeCanadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications in terms of estimating crop yields, modeling the land-atmosphere interactions in agricultural areas, and predicting crop growth responses to increasing temperatures amidst climate change. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation