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James M. Wilczak authored and/or contributed to the following articles/publications.
Simultaneous prediction of weather and air quality during NEAQS2004 using the WRF-chemistry model
The 2004 New England Air Quality Study (NEAQS) was an intensive effort to investigate the chemical and meteorological factors that contribute to poor air quality in the New England region. The campaign combined efforts of numerous educational institutions as well as federal, state, and local agencies. Observational data were collected from an ex...
The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign
The Second Wind Forecast Improvement Project (WFIP2) is a U.S. Department of Energy (DOE)- and National Oceanic and Atmospheric Administration (NOAA)-funded program, with private-sector and university partners, which aims to improve the accuracy of numerical weather prediction (NWP) model forecasts of wind speed in complex terrain for wind energ...
Institution National Oceanic and Atmospheric Administration - NOAA
During the first Wind Forecast Improvement Project (WFIP), new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and wind profiles by netwo...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goal of which is to improve the accuracy of short-term (0–6 hr) wind power forecasts for the wind energy industry. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that included the National Oceanic and Atmospheric Administration (NOAA)...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain
Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from di...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer
With the increasing level of offshore wind energy investment, it is correspondingly important to be able to accurately characterize the wind resource in terms of energy potential as well as operating conditions affecting wind plant performance, maintenance, and lifespan. Accurate resource assessment at a particular site supports investment decis...
Institution National Oceanic and Atmospheric Administration - NOAA
The accurate forecast of persistent orographic cold-air pools in numerical weather prediction models is essential for the optimal integration of wind energy into the electrical grid during these events. Model development efforts during the Second Wind Forecast Improvement Project (WFIP2) aimed to address the challenges also related to this. We e...
Institution National Oceanic and Atmospheric Administration - NOAA
The structure and evolution of the atmospheric boundary layer (ABL) under clear-sky fair weather conditions over mountainous terrain is dominated by the diurnal cycle of the surface energy balance and thus strongly depends on surface snow cover. We use data from three passive ground-based infrared spectrometers deployed in the East River Valley ...
Institution National Oceanic and Atmospheric Administration - NOAA