Examining WRF's Sensitivity to Contemporary Land-Use Datasets across the Contiguous United States Using Dynamical Downscaling

An Analysis of CMAQ Gas Phase Dry Deposition over North America Through Grid-Scale and Land-Use Specific Diagnostics in the Context of AQMEII4

The fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4) is conducting a diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality models over North America and Europe. In this study, we analyze annual AQMEII4 simulations performed with the Community Multiscale Air Quality Model (CMAQ) version 5.3.1 over North America. These simulations were configured with both the M3Dry and Surface Tiled Aerosol and Gas Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of observed and modeled concentrations and wet deposition fluxes shows that the AQMEII4 CMAQ simulations perform similarly to other contemporary regional-scale modeling studies. During summer, M3Dry has higher ozone (O3) deposition velocities (Vd) and lower mixing ratios than STAGE for much of the eastern U.S. while the reverse is the case over eastern Canada and along the West Coast. In contrast, during winter STAGE has higher O3 Vd and lower mixing ratios than M3Dry over most of the southern half of the modeling domain while the reverse is the case for much of the northern U.S. and southern Canada. Analysis of the diagnostic variables defined for the AQMEII4 project, i.e. grid-scale and land-use (LU) specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and wintertime cuticular grid-scale effective conductances for M3Dry and generally higher soil grid-scale effective conductances (for both vegetated and bare soil) for STAGE in both summer and winter. On a domain-wide basis, the stomatal grid-scale effective conductances account for about half of the total O3 Vd during daytime hours in summer for both schemes. Employing LU-specific diagnostics, results show that daytime Vd varies by a factor of 2 between LU categories. Furthermore, M3Dry vs. STAGE differences are most pronounced for the stomatal and vegetated soil pathway for the forest LU categories, with M3Dry estimating larger effective conductances for the stomatal pathway and STAGE estimating larger effective conductances for the vegetated soil pathway for these LU categories. Annual domain total O3 deposition fluxes differ only slightly between M3Dry (74.4 Tg/year) and STAGE (76.2 Tg/yr), but pathway-specific fluxes to individual LU types can vary more substantially on both annual and seasonal scales which would affect estimates of O3 damages to sensitive vegetation. A comparison of two simulations differing only in their LU classification scheme shows that the differences in LU cause seasonal mean O3 mixing ratio differences on the order of 1 ppb across large portions of the domain, with the differences generally largest during summer and in areas characterized by the largest differences in the fractional coverages of the forest, planted/cultivated, and grassland LU categories. These differences are generally smaller than the M3Dry vs. STAGE differences outside the summer season but have a similar magnitude during summer. Results indicate that the deposition impacts of LU differences are caused both by differences in the fractional coverages and spatial distributions of different LU categories as well as the characterization of these categories through variables like surface roughness and vegetation fraction in look-up tables used in the land-surface model and deposition schemes. Overall, the analyses and results presented in this study illustrate how the diagnostic grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can provide insights into similarities and differences between the CMAQ M3Dry and STAGE dry deposition schemes that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.

Assessment of a Coastal Offshore Wind Climate by Means of Mesoscale Model Simulations Considering High-Resolution Land Use and Sea Surface Temperature Data Sets

In this study, offshore wind climate assessments are carried out by using mesoscale model Weather Research and Forecasting (WRF) and validated by measurement at a demonstration site located 3.1 km offshore of Choshi. An optimal nudging method is investigated by using offshore and meteorological observations. The land-use datasets are then created from a higher-resolution land-use data by using a maximum area sampling scheme according to the horizontal resolution of the mesoscale model. Finally, the sea surface temperature datasets are corrected by observation data. It is found that the relative error of annual wind speed is reduced from 7.3% to 2.2% and the correlation coefficient between predicted and measured wind speed is improved from 0.80 to 0.84 by considering the effects of land-use and sea surface temperature.

Effects of Mosaic Land Use on Dynamically Downscaled WRF Simulations of the Contiguous U.S

The representation of land use (LU) in meteorological modeling strongly influences the simulation of fluxes of heat, moisture, and momentum; affecting the accuracy of 2-m temperature and precipitation. Here, the Weather Research and Forecasting (WRF) model is used with the Noah land surface model to compare a mosaic approach, which accounts for subgrid scale variability of LU types, to the default option which only considers the dominant category in each grid cell. Three-year historical dynamically downscaled WRF simulations are generated using a 12-km domain over the contiguous U.S. to assess the sensitivities to using mosaic LU and to changes to parameters associated with LU and soil categories. Compared to dominant LU, mosaic LU features decreased coverage of forest and agricultural types and increased low-density urban LU throughout much of the eastern and central U.S. However, highly urbanized areas show the opposite trend, as mosaic LU represents partial greenspace within areas that are exclusively urban within dominant LU. Mosaic LU results in widespread increases in sensible heat fluxes and 2-m temperatures, with reductions in latent heat flux, 2-m mixing ratio, and monthly precipitation across the central and eastern U.S. These changes exacerbate an existing warm bias found with dominant LU but reduce overestimations of precipitation. Highly urbanized areas in the eastern U.S. tend to have cooler, more realistic temperatures with mosaic LU relative to dominant LU. A pair of runs with updated surface parameters corroborates these results. Overall, differences between the simulations are largely attributable to their representations of urban LU.