气候变化领域集成服务门户(CCPortal): Impacts of Tiled Land Cover Characterization on Global Meteorological Predictions Using the MPAS-A

CCPortal

DOI	10.1029/2019JD032093
	Impacts of Tiled Land Cover Characterization on Global Meteorological Predictions Using the MPAS-A
	Campbell P.C.; Bash J.O.; Herwehe J.A.; Gilliam R.C.; Li D.
发表日期	2020
ISSN	2169897X
卷号	125 期号:15
英文摘要	Parameterization of subgrid-scale variability of land cover characterization (LCC) is an active area of research and can improve model performance compared to the dominant (i.e., most abundant tile) approach. The “Noah” land surface model implementation in the global Model for Prediction Across Scales-Atmosphere (MPAS-A), however, only uses the dominant LCC approach that leads to oversimplification in regions of highly heterogeneous LCC (e.g., urban/suburban settings). Thus, in this work we implement a subgrid tiled approach as an option in MPAS-A, version 6.0, and assess the impacts of tiled LCC on meteorological predictions for two gradually refining meshes (92–25 and 46–12 km) focused on the conterminous United States for January and July 2016. Compared to the dominant approach, results show that using the tiled LCC leads to pronounced global changes in 2-m temperature (July global average change approximately −0.4 K), 2-m moisture, and 10-m wind speed for the 92–25 km mesh. The tiled LCC reduces mean biases in 2-m temperature (July U.S. average bias reduction approximately factor of 4) and specific humidity in the central and western United States for the 92–25 km mesh and improves the agreement of vertical profiles (e.g., temperature, humidity, and wind speed) with observed radiosondes; however, there is increased bias and error for incoming solar radiation at the surface. The inclusion of subgrid LCC has implications for reducing systematic temperature biases found in numerical weather prediction models, particularly those that employ a dominant LCC approach. Published 2020. This article is a US Government work and is in the public domain in the USA.
英文关键词	evaluation; land cover characterization; model simulations; MPAS-A; Noah land surface model; subgrid
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185855
作者单位	National Academies/National Research Council (NRC) Fellowship Participant at National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States; Now at Center for Spatial Information Science and Systems/Cooperative Institute for Satellite Earth System Studies, George Mason University, Fairfax, VA, United States; Office of Air and Radiation, Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, United States; Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States; Department of Earth and Environment, Boston University, Boston, MA, United States
推荐引用方式 GB/T 7714	Campbell P.C.,Bash J.O.,Herwehe J.A.,et al. Impacts of Tiled Land Cover Characterization on Global Meteorological Predictions Using the MPAS-A[J],2020,125(15).
APA	Campbell P.C.,Bash J.O.,Herwehe J.A.,Gilliam R.C.,&Li D..(2020).Impacts of Tiled Land Cover Characterization on Global Meteorological Predictions Using the MPAS-A.Journal of Geophysical Research: Atmospheres,125(15).
MLA	Campbell P.C.,et al."Impacts of Tiled Land Cover Characterization on Global Meteorological Predictions Using the MPAS-A".Journal of Geophysical Research: Atmospheres 125.15(2020).