Abstract
Abstract. The land surface plays a crucial role in regulating water and energy fluxes at the land–atmosphere (L–A) interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL) evolution, and precipitation through soil-moisture–evapotranspiration coupling. In turn, it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L–A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF) modeling system couples NASA's Land Information System (LIS) with the community WRF model and allows users to explore the L–A processes and feedbacks. Three commonly used satellite-derived land cover datasets – i.e., from the US Geological Survey (USGS) and University of Maryland (UMD), which are based on the Advanced Very High Resolution Radiometer (AVHRR), and from the Moderate Resolution Imaging Spectroradiometer (MODIS) – bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g., stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.
Highlights
(ET) to planetary boundary layer (PBL) evolution and water/energy flux entrainmHenyt,dasrowleollgasytoacnlodud/precipitation dale.v, e2l0o1p0m),enwth(ee.rge.b,ySuthneapnEhdyaBsiroctsahillocvShiacyrhas,c1tte9er9ims6t;icSsenoefvliarnatdneuseet and land cover (LULC) regulaSte cmieoinstucree sand energy exare based on the Advanced Very High Resolution Radiome- changes between the land and the atmosphere (L–A)
The NASA Unified WRF (NU-WRF) results are compared with the available observations and the results show NU-WRF does a reasonably good simulation of physical, chemical, and biological processes
The offline Land Information System (LIS) results show that large initial soil moisture (SM) difference (30–50 %) exists in the regions where woodland/closed shrubland changes to cropland or cropland is cleared for urban areas
Summary
NU-WRF was developed from the advanced research version of WRF (Michalakes et al, 2001) and WRF-Chem (Grell et al, 2005). Inheriting all the WRF features – e.g., Eulerian mass dynamic core, and 2-way nesting and physics – NUWRF incorporates NASA’s unique experience and capabilities by fully integrating the LIS, the Goddard radiation (Chou and Suares, 1999) and microphysics (Shi et al, 2010; Tao et al, 2011) schemes, and the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model (Chin et al, 2002) into a single modeling framework It links to the Goddard Satellite Data Simulator Unit (G-SDSU, Matsui et al, 2009), allowing the conversion of modeled parameters to radiance and backscattering that can directly be compared with the satellite level-1 measurements at a relevant spatial and temporal scale. LIS is a software framework that drives a suite of land surface models (LSMs) with satellite/ground-based observations and model reanalysis data It provides a flexible and satellite-based high-resolution representation of land surface physics and states (e.g., soil and vegetation), which are directly coupled to the atmosphere. Last but not the least, the LIS framework allows users to introduce new ancillary datasets (e.g., land cover, soil type, vegetation condition) into NU-WRF, which makes this study possible
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