Noah-MP-CROP: an integrated atmosphere-crop-soil modeling system for regional agro-climatic assessments.

Tuesday, 16 December 2014: 11:35 AM
Xing Liu1, Michael J Barlage2, Fei Chen2, Dev S Niyogi1 and Guangsheng Zhou3, (1)Purdue University, West Lafayette, IN, United States, (2)NCAR/RAL, Boulder, CO, United States, (3)CMA China Meteorological Administration, Beijing, China
Cropland plays an important role in land-atmosphere interactions. Integrating advanced regional-scale crop-growth modeling capabilities into a land surface model (LSM) is not only crucial for assessing potential impacts of climate change and climate variability on crop yields, but also can help to improve the representation of crop-atmosphere interactions in the Weather Research and Forecasting (WRFModel. Therefore, the objectives of developing Noah-MP-CROP are: 1) provide high-spatial and high-temporal resolution regional agro-climatic related products; 2) enhance the simulations of cropland surface-fluxes in the WRF model for numerical weather prediction and regional climate modeling. Noah-MP is a new-generation of LSM that uses multiple parameterizations for land hydrology and energy processes. In this study, we couple species-specific crop phenology and carbon allocation schemes with Noah-MP-based complex simulations of canopy photosynthesis and soil moisture. The Noah-MP-CROP can be executed at field-scales or grid-scales of different spatial resolution and it also can be applied at multiple temporal scales. The major agriculture-related outputs include: grain mass, leaf mass, leaf area index, crop yield, growth primary production, growing degree days, soil temperature, soil moisture, and evapotranspiration. The model also allows us to conduct different assessments by using either historical, real-time, short-term forecast or future projected weather input data. In this study, we focus on evaluating the Noah-MP-CROP for the regional agro-climatic assessments in the U.S. Corn Belt. Model simulations are conducted at both field-scale (Bondville, IL and Mead, NE) and grid-scale (4km-resolution). At both field sites, model outputs of crop yield (grain mass), leaf area index and surface fluxes show strong agreement with observations. Also incorporating crop-growth models in Noah-MP improves the simulated latent heat and sensible heat fluxes during the crop growing season.