William I. Gustafson

NOx emission reduction and its effects on ozone during the 2008 Olympic Games.

We applied a daily assimilated inversion method to estimate NO(x) (NO + NO(2)) emissions for June-September 2007 and 2008 on the basis of the Aura Ozone Monitoring Instrument (OMI) observations of nitrogen dioxide (NO(2)) and model simulations using the Regional chEmistry and trAnsport Model (REAM). This method allows for estimating emission changes with a finer temporal resolution than previous studies and shows that the progression of the emission reduction corresponds roughly to the scheduled implementation of emission controls over Beijing. OMI column NO(2) reductions are approximately 45%, 33%, and 14% over urban Beijing, rural Beijing, and the Huabei Plain, respectively, while the corresponding anthropogenic NO(x) emission reductions are only 28%, 24%, and 6%, during the full emission control period (July 20-Sep 20, 2008). Meteorological changes from summer 2007 to 2008 are the main factor contributing to the column NO(2) decreases not accounted for by the emission reduction. The surface ozone changes due to NO(x) emission reduction are negligible using a standard VOC emission inventory. When using enhanced VOC (particularly aromatics) emissions derived from in situ observations, urban Beijing shifted O(3) production from the VOC-limited regime toward the NO(x)-limited regime resulting in a more substantial ozone decrease (up to 10 ppbv).

The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol–cloud interactions in multiscale modeling framework models: tracer transport results

All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM’s cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization.

How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions?

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25°, with the meteorology nudged toward the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the Northern Hemisphere midlatitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m−2 (−30%) compared to the 2° model, leading to a 0.26 W m−2 reduction (−15%) in the global annual average AIF.

Coupling between the University of California, Davis, Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) and MM5: Preliminary Results for July 1998 for Western North America

Abstract The University of California, Davis, Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) is coupled to the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) as a land surface scheme. Simulations for July 1998 over western North America show that this coupling, the first between a mesoscale model and a land surface model of this complexity, is successful. Comparisons among model output, National Centers for Environmental Prediction–NCAR reanalysis fields, and station data show that MM5–ACASA generally reproduces near-surface temperature in a realistic fashion, but with a stronger diurnal cycle than observations suggest. A control run using the existing Louis/European Centre for Medium-Range Weather Forecasts land surface formulation produces unrealistically low temperatures associated with high latent heating and precipitation amounts over much of the model domain. Simulations of heat and moisture fluxes using the Biosphere–Atmospher...

Precipitation characteristics of CAM5 physics at mesoscale resolution during MC3E and the impact of convective timescale choice

The physics suite of the Community Atmosphere Model version 5 (CAM5) has recently been implemented in the Weather Research and Forecasting (WRF) model to explore the behavior of the parameterization suite at high resolution and within the controlled setting of a limited area model. The initial paper documenting this capability characterized the behavior for a northern high-latitude region. This paper characterizes the precipitation characteristics for continental, midlatitude, springtime conditions during the Midlatitude Continental Convective Clouds Experiment (MC3E) over the central United States. This period exhibited a range of convective conditions from those driven strongly by large-scale synoptic regimes to more locally driven convection. The study focuses on the precipitation behavior at 32 km grid spacing to better anticipate how the physics will behave in a global model when used at similar grid spacing in the coming years. Importantly, one change to the Zhang-McFarlane deep convective parameterization when implemented in WRF was to make the convective timescale parameter an explicit function of grid spacing. This study examines the sensitivity of the precipitation to the default value of the convective timescale in WRF, which is 600 s for 32 km grid spacing, to the value of 3600 s used for 2° grid spacing in CAM5. For comparison, a 1200 s and an infinite convective timescale are also used. The results show that the 600 s timescale gives the most accurate precipitation amount over the central United States. However, this setting has the worst precipitation diurnal cycle, with the convection too tightly linked to the daytime surface heating. Longer timescales greatly improve the diurnal cycle but result in less precipitation and produce a low bias. An analysis of rain rates shows the accurate precipitation amount with the shorter timescale is assembled from an over abundance of drizzle combined with too few heavy rain events. With longer timescales, one can improve the frequency distribution, particularly for the extreme rain rates. Ultimately, without changing other aspects of the physics, one must decide between accurate diurnal timing and rain amount when choosing an appropriate convective timescale.

On-Line Chemistry Within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

In this chapter we describe the Weather Research and Forecasting (WRF) model as it is coupled to online chemistry. This model now includes many atmospheric chemistry routines covering biogenic emissions, deposition, photolysis, chemical mechanisms. In addition, several atmospheric aerosol routines and a biomass burning model were added to WRF. The chemistry and aerosol routines are solved in an “online” fashion with the meteorology forecast model. In other words, the interaction and transport of meteorological, chemical, and aerosol species are calculated using the same physical parameterizations with no need to interpolate in time and/or space. Interactions include the aerosol direct and indirect effect. This chapter gives an overview of some of the most important features of this modeling system. Some evaluation results are also discussed.

Eddy fluxes and sensitivity of the water cycle to spatial resolution in idealized regional aquaplanet model simulations

A multi-scale moisture budget analysis is used to identify the mechanisms responsible for the sensitivity of the water cycle to spatial resolution using idealized regional aquaplanet simulations. In the higher resolution simulations, moisture transport by eddy fluxes dry the boundary layer enhancing evaporation and precipitation. This effect of eddies, which is underestimated by the physics parameterizations in the low-resolution simulations, is found to be responsible for the sensitivity of the water cycle both directly, and through its upscale effects on the transport of mean moisture by the mean circulation. Correlations among moisture transport by eddies at adjacent ranges of scales provides a potential for reducing this sensitivity by representing the unresolved eddies by their marginally resolved counterparts.

Implementing the data center energy productivity metric

As data centers proliferate in size and number, the endeavor to improve their energy efficiency and productivity is becoming increasingly important. We discuss the properties of a number of the proposed metrics of energy efficiency and productivity. In particular, we focus on the Data Center Energy Productivity (DCeP) metric, which is the ratio of useful work produced by the data center to the energy consumed performing that work. We describe our approach for using DCeP as the principal outcome of a designed experiment using a highly instrumented, high-performance computing data center. We found that DCeP was successful in clearly distinguishing different operational states in the data center, thereby validating its utility as a metric for identifying configurations of hardware and software that would improve (or even maximize) energy productivity. We also discuss some of the challenges and benefits associated with implementing the DCeP metric, and we examine the efficacy of the metric in making comparisons within a data center and among data centers.

Resolution‐dependent behavior of subgrid‐scale vertical transport in the Zhang‐McFarlane convection parameterization

With this study, to better understand the behavior of quasi-equilibrium-based convection parameterizations at higher resolution, we use a diagnostic framework to examine the resolution-dependence of subgrid-scale vertical transport of moist static energy as parameterized by the Zhang-McFarlane convection parameterization (ZM). Grid-scale input to ZM is supplied by coarsening output from cloud-resolving model (CRM) simulations onto subdomains ranging in size from 8 × 8 to 256 × 256 km2s.

Impact of subgrid‐scale radiative heating variability on the stratocumulus‐to‐trade cumulus transition in climate models

Subgrid-scale interactions between turbulence and radiation are potentially important for accurately simulating marine low clouds in climate models. To better understand the impact of these interactions, the Weather Research and Forecasting model is configured for large eddy simulation to study the stratocumulus to trade cumulus (Sc-to-Cu) transition. Using the Global Energy and Water Cycle Experiment Atmospheric System Studies composite Lagrangian transition case and the Atlantic Trade Wind Experiment case, it is shown that the lack of subgrid-scale turbulence-radiation interaction, as is the case in current generation climate models, accelerates the Sc-to-Cu transition. Our analysis suggests that subgrid-scale turbulence-radiation interactions in cloud-topped boundary layers contribute to stronger production of temperature variance, which in turn leads to stronger buoyancy production of turbulent kinetic energy and helps to maintain the Sc cover.