• No se han encontrado resultados

The National Research Council (2012) identified the urban boundary layer as “the most understudied and undersampled layer in the urban atmosphere” due to difficulty of access. Unmanned aircraft systems (UAS) are capable of collecting meteorological data to characterize the evolution of temperature, humidity, and winds within the boundary layer, as well as estimate the turbulent sensible, latent, and momentum fluxes, longwave and shortwave radiation, and skin temperature (Knuth et al. 2013). Provided they are safely integrated into the national airspace over the next several years, UAS could serve a new method to collect data to characterize both the

urban and surrounding rural boundary layer and surface characteristics without installing several large towers across a metropolitan area.

Grimmond et al. (2010) found that urban energy balance models have the least capability to model latent heat fluxes. Given that humid heat waves have a stronger impact on human health (Guirguis et al. 2014), future research in urban canopy model development should focus on improving the modeling of latent heat fluxes through better integration of urban vegetation. While a tile approach works for cities where irrigation is not a significant source of moisture, it does not allow direct interaction of built and vegetated surfaces or the capability to account for external water sources such as street cleaning.

Future research should also focus on creating urban canopy parameter datasets. The lack of information on some urban canopy parameters has resulted in tuning the parameter to minimize differences between predicted and observed variables. The National Urban Database with Access Portal’s gridded urban parameter datasets for 44 cities was included in the recent release of the WRF model version 3.5 for use with both the single-layer and multi-layer urban canopy models. However, limitations exist with respect to urban fraction.

A significant need exists for two-way interactions between urban meteorologists and end user communities (e.g., emergency managers, public utilities, and urban planners) to better understand user information needs and steer the direction of urban meteorological research. Coordination with state programs experienced in extension, education, and outreach at the local level, such as Land Grant and Sea Grant Extension

or OK-First, could help identify user groups and initiate and facilitate ongoing dialogue. To sustain this effort in the long term and ensure research is socially relevant to end users will require an interdisciplinary team of both physical and social scientists that speak the same language.

REFERENCES

Ackerman, B., 1985: Temporal march of the Chicago heat island. J. Climate Appl.

Meteor., 24, 547-554.

——, 1987: Climatology of Chicago area urban-rural differences in humidity. J.

Climate Appl. Meteor., 26, 427-430.

Aida, M., 1982: Urban albedo as a function of the urban structure – a model experiment. Bound.-Layer Meteor., 23, 405-413.

——, and M. Yaji, 1979: Observations of downward atmospheric radiation in the Tokyo area. Bound.-Layer Meteor., 16, 453-465.

——, and K. Gotoh, 1982: Urban albedo as a function of the urban structure – a two- dimensional numerical simulation. Bound.-Layer Meteor., 23, 415-424.

Allwine, K. J., and J. E. Flaherty, 2006: Joint Urban 2003: Study overview and instrument locations. PNNL Tech. Rep. PNNL-15967, 92 pp.

——, J. H. Shinn, G. E. Streit, K. L. Clawson, and M. Brown, 2002: Overview of URBAN 2000: A multiscale field study of dispersion through an urban environment. Bull. Amer. Meteor. Soc., 83, 521-536.

Arnfield, A. J., 1982: An approach to the estimation of the surface radiative properties and radiation budgets of cities. Phys. Geogr., 3, 97–122.

——, 1988: Validation of an estimation model for urban surface albedo. Phys. Geog., 9, 361-372.

——, 2003: Two decades of urban climate research: A review of turbulence, exchange of energy and water, and the urban heat island. Int. J. Climatol., 23, 1-26.

——, and C. S. B. Grimmond, 1998: An urban canyon energy budget model and its application to urban storage heat flux modeling. Energy and Buildings, 27, 61-68.

ASHRAE, 2009: Material properties. 2009 ASHRAE Handbook: Fundamentals. American Society of Heating, Refrigerating and Air-Conditioning Engineers, 26.1–26.22.

Atkinson, B. W., 2003: Numerical modeling of urban heat-island intensity. Bound.-

Layer Meteor., 109, 285-310.

Au, S. K., and J. L. Beck, 2001: Estimation of small failure probabilities in high dimensions by subset simulation. Probab. Eng. Mech., 16, 263-277.

Baker, L. A., A. J. Brazel, N. Selover, C. Martin, N. McIntyre, R. S. Steiner, A. Nelson, and L. Musacchio, 2002: Urbanization and warming of Phoenix (Arizona, USA): Impacts, feedbacks and mitigation. Urban Ecosyst., 6, 183-203.

Barlow, J. F., and S. E. Belcher, 2002: A wind tunnel model for quantifying fluxes in the urban boundary layer. Bound.-Layer Meteor., 104, 131-150.

——, I. N. Harman, and S. E. Belcher, 2004: Scalar fluxes from urban street canyons. Part I: Laboratory simulation. Bound.-Layer Meteor., 113, 369-385.

Basara, J. B., 2001: The value of point-scale measurements of soil moisture in planetary boundary layer simulations. Ph. D. dissertation, School of Meteorology, University of Oklahoma.

——, and K. C. Crawford, 2002: Linear relationships between root-zone soil moisture and atmospheric processes in the planetary boundary layer. J. Geophys. Res., 107, 10, 1-18.

——, P. K. Hall Jr., A. J. Schroeder, B. G. Illston, and K. L. Nemunaitis, 2008: Diurnal cycle of the Oklahoma City urban heat island. J. Geophys. Res., 113, D20109, doi:10.1029/2008JD010311.

——, H. G. Basara, B. G. Illston, and K. C. Crawford, 2010: The impact of the urban heat island during an intense heat wave in Oklahoma City. Adv. Meteor., 2010, doi:10.1155/2010/230365.

——, and Coauthors, 2011: The Oklahoma City Micronet. Meteor. Appl., 18, 252-261. Beljaars, A. C. M., 1994: The parameterization of surface fluxes in large-scale models

under free convection. Quart. J. Roy. Meteor. Soc., 121, 255-270.

Bergstrom, R. W., and J. T. Peterson, 1977: Comparison of predicted and observed solar radiation in an urban area. J. Appl. Meteor., 16, 1107-1115.

Best, M. J., 1998: A model to predict surface temperatures. Bound.-Layer Meteor., 88, 279-306.

——, 2005: Representing urban areas within operational numerical weather prediction models. Bound.-Layer Meteor., 114, 91-109.

Betts, A. K., F. Chen, K. Mitchell, and Z. Janjic, 1997: Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta model using FIFE data. Mon. Wea. Rev., 125, 2896-2916.

Betts, R., and M. J. Best, 2004: Changes in urban temperature and humidity due to radiative forcing, landscape effects and local heat sources. BETWIXT Tech. Briefing Note 6, Version 1, 14 pp.

Bornstein, R. D., 1968: Observations of the urban heat island effect in New York City.

Documento similar