Open AccessOn simulation improvement of the N oah_ LSM by coupling with a hydrological model using a double‐excess runoff production scheme in the GRAPES _ M eso model
Author(s) -
Wang Lili,
Chen Dehui,
Bao Hongjun,
Zhang Ke
Publication year - 2017
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1651
Subject(s) - surface runoff , environmental science , infiltration (hvac) , runoff curve number , saturation (graph theory) , routing (electronic design automation) , meteorology , wind speed , computer simulation , hydrology (agriculture) , runoff model , soil science , simulation , computer science , geology , mathematics , geotechnical engineering , physics , ecology , computer network , combinatorics , biology
Land surface models play an important role in simulating mass, energy and momentum exchanges between the atmosphere and land surface in numerical weather prediction systems. The N oah land surface model ( N oah_ LSM ) is adapted to describe the water and energy balance in the GRAPES _ M eso model ( V4 .0). However, the N oah_ LSM does not distinguish the infiltration‐excess runoff and the saturation‐excess runoff effects and does not simulate runoff routing, making its applicability limited in C hina. In this work, the N oah_ LSM was improved by incorporating double‐excess runoff production and routing schemes. The double‐excess runoff production scheme is based on the depletion of water storage coupling with the H oltan method. The M uskingum model is used for routing. To evaluate the performance of the improved model, numerical simulations were carried out using the old and improved models to investigate the feedback of changes in the land surface hydrological model to numerical simulations for meteorology. The results demonstrate that the improved land surface hydrological model affects numerical simulations for meteorology in terms of the soil temperature, soil moisture, air temperature and wind speed as well as predicting rainfall events better in terms of the rainfall regime.