{"id":23,"date":"2016-02-20T15:26:16","date_gmt":"2016-02-20T20:26:16","guid":{"rendered":"https:\/\/sites.bu.edu\/efm\/?page_id=23"},"modified":"2016-02-23T16:48:28","modified_gmt":"2016-02-23T21:48:28","slug":"uc","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/efm\/uc\/","title":{"rendered":"Urban climate"},"content":{"rendered":"

Urban population has been growing fast over the past few decades and the world’s urban population has exceeded 50%. Studying\u00a0the microclimate of urban environments not only has important energy, water, and health implications, but also help understand\u00a0the broader impacts of\u00a0land-use\/land-cover changes. However, most of the current\u00a0numerical models do not have urban land use and\/or do not have urban representation. In addition, new studies have found that urban surface and hydrological processes such as vegetation dynamics might be different from those traditionally studies over other environments.<\/p>\n

We collect urban micrometeorological data including temperature, specific humidity, wind speed, radiation, turbulent fluxes and so on to\u00a0understand the unique\u00a0physical climate\u00a0of urban areas.\u00a0We are actively\u00a0working on understanding the interaction between urban heat islands and heatwaves (Fig. 1, which is taken from Li and Bou-Zeid, 2013<\/a>). A recent study from our group examined the responses of urban surface energy balance to heat waves using observational data collected in the Beijing metropolitan area (Wang et al. 2015<\/a>;\u00a0Li et al. 2015<\/a>). Currently\u00a0we are re-examining the role of wind speed changes\u00a0using the same Beijing\u00a0dataset.<\/p>\n

\"HW_UHI\"<\/a><\/p>\n

Figure 1:\u00a0<\/span>\u00a0Synergistic interaction mechanisms between the UHI and HWs, which are mainly related to the reduced moisture availability in urban areas and the reduced wind speed during heat waves.<\/p>\n

In our group, we also develop parameterizations for urban surfaces (so-called urban canopy models, see Fig. 2)\u00a0that\u00a0can be driven by or coupled to large-scale weather and climate models. Fig. 2 shows the LM3-UCM developed by us and coupled to the\u00a0Geophysical Fluid Dynamics Laboratory<\/a>\u00a0(GFDL) land model LM3, which is based on the urban canopy concept and is composed of two major components: a roof component and a canyon component. These two components do not interact with each other directly; instead, they communicate with the bottom atmospheric layer through which they interact with each other. The canyon component includes the walls, the impervious surface at the ground, the pervious surface at the ground (i.e., soil), and the vegetation above soil. These are called subcomponents of the urban canyon hereafter. All of these four subcomponents communicate with the canopy air in the urban canyon, through which they interact with each other and also the atmosphere. Currently we are using the LM3-UCM, in together with GFDL’s HiRAM, to study the impact of urbanization over the Continental United States. We are also improving many aspects of the LM3-UCM for example how it handles snow.<\/p>\n

We also use the Weather Research and Forecasting Model (WRF) extensively. We coupled the Princeton Urban Canopy Model to WRF to study urban climate in the Baltimore-Washington metropolitan area (Li and Bou-Zeid 2013<\/a>;\u00a0Li et al. 2013<\/a>;\u00a0Li and Bou-Zeid, 2014<\/a>) and the New York city (Ramamurthy<\/span>\u00a0et al. 2016<\/a>). We also developed a mosaic approach into WRF to parameterize the surface heterogeneity effect (Li et al. 2013<\/a>). In particular, we are combining\u00a0these numerical tools with other approaches to assess different urban heat\u00a0mitigation and adaptation strategies (Li et al. 2014<\/a>; Yang et al. 2015<\/a>).<\/p>\n

\"Figure1\"<\/a><\/p>\n

Figure 2: The design of LM3\u00a0urban canopy model .\u00a0 za<\/sub><\/em> is the height of the first level in the atmospheric model; H<\/em> is the averaged height of buildings; Rf<\/sub><\/em> is the roof width and Rd<\/sub><\/em> is the canyon width. Troof<\/sub><\/em> is the roof surface temperature; Twall<\/sub><\/em> is the wall surface temperature; Tbuilding<\/sub><\/em> is the temperature of the building interior; Tcanopy<\/sub><\/em> is the canopy air temperature within the urban canyon; Tveg<\/sub><\/em> is the vegetation temperature; Tsoil<\/sub><\/em> is the soil surface temperature; Timp<\/sub><\/em> is the impervious surface temperature.<\/p>\n

\"Figure1\"<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Urban population has been growing fast over the past few decades and the world’s urban population has exceeded 50%. Studying\u00a0the microclimate of urban environments not only has important energy, water, and health implications, but also help understand\u00a0the broader impacts of\u00a0land-use\/land-cover changes. However, most of the current\u00a0numerical models do not have urban land use and\/or do […]<\/p>\n","protected":false},"author":11624,"featured_media":0,"parent":0,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/pages\/23"}],"collection":[{"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/users\/11624"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/comments?post=23"}],"version-history":[{"count":16,"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/pages\/23\/revisions"}],"predecessor-version":[{"id":221,"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/pages\/23\/revisions\/221"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/efm\/wp-json\/wp\/v2\/media?parent=23"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}