Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

The first non-beta release of the Weather Research and Forecast (WRF) modeling system in May, 2004 represented a key milestone in the effort to design and implement a fullyfunctioning, next-generation modeling system for the atmospheric research and operational NWP user communities. With efficiency, portability, maintainability, and extensibility as bedrock requirements, the WRF software framework has allowed incremental and reasonably rapid development while maintaining overall consistency and adherence to the architecture and its interfaces. The WRF 2.0 release supports the fullrange of functionality envisioned for the model including efficient scalable performance on a range of high-performance computing platforms, multiple dynamic cores and physics options, low-overhead two-way interactive nesting, moving nests, model coupling, and interoperability with other common model infrastructure efforts such as ESMF.

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The present study applies the WRF model involving the single-layer urban canopy model (hereafter, WRF_UCM) to urban climate simulation of the Tokyo metropolitan area for August (2004)(2005)(2006)(2007) and compare results to (a) observations, and (b) the WRF model involving the slab urban model (hereafter, WRF_SLAB). In this urban area, WRF_UCM accurately captures the observed monthly mean daytime and nocturnal UHI, whereas WRF_SLAB does not show a nocturnal UHI. Moreover, the observed diurnal variations of the surface air temperature for central Tokyo and Kumagaya, a nearby inland city, are reproduced well by WRF_UCM. However, WRF_SLAB exhibits both a 1-hr phase shift and a 6.2 C excess oscillation magnitude over observations. In addition, WRF_UCM accurately reproduces the frequency distribution of surface air temperatures, showing a maximum at 27 C, whereas WRF_SLAB produce a bimodal distribution, with double peaks at 23 and 33 C. Finally, WRF_UCM does a much better job than WRF_SLAB at modeling the relative humidity.