Detection of Urban-Induced Rainfall Anomalies in a Major Coastal City

Shepherd, J. Marshall; Burian, Steven J.

doi:10.1175/1087-3562(2003)007<0001:douira>2.0.co;2

Cited by 234 publications

(146 citation statements)

References 37 publications

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“…This temperature differential was first referred to as the Urban Heat Island by Manley (1958) and since then a large effort has been devoted to the study of this important urban phenomenon using both air temperature and surface temperature (e.g. Grimmond & Oke, 2002;Quattrochi & Ridd, 1994;Shepherd & Burian, 2003;Rosenzweig et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Remote sensing of the urban heat island effect across biomes in the continental USA

Imhoff

Zhang

Wolfe

et al. 2010

Remote Sensing of Environment

1,131

686

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Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003)(2004)(2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the nonurban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban-rural temperature difference) the largest (8°C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9°C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3°C temperature difference in summer and only 1.3°C in winter. In desert environments, the LST's response to ISA presents an uncharacteristic "U-shaped" horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI's calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.Published by Elsevier Inc.

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Section: Introductionmentioning

confidence: 99%

Remote sensing of the urban heat island effect across biomes in the continental USA

Imhoff

Zhang

Wolfe

et al. 2010

Remote Sensing of Environment

1,131

686

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“…Results from METROMEX suggest that the urban effects lead to 5-25% increased precipitation, particularly 50-75 km downwind of the urban center during the summer months (Changnon et al, 1991). There is increasing evidence that urbanization and changes in urban-rural boundaries can have a significant feedback on the spatiotemporal patterns of precipitation (Shepherd et al, 2002;Shepherd and Burian, 2003;Niyogi et al, 2006;Mote et al, 2007;Lei et al, 2008). Cotton and Pielke (2007, Chapter 5;Pielke et al, 2007, Section 7) summarize numerous studies as to how urbanization alters rainfall patterns as a result of mesoscale circulations and through changes in convective available potential energy (CAPE).…”

Section: Introductionmentioning

confidence: 99%

Urbanization signature in the observed heavy rainfall climatology over India

Kishtawal

Niyogi

Tewari

et al. 2009

Intl Journal of Climatology

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295

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ABSTRACT:We assess the urbanization impacts on the heavy rainfall climatology during the Indian summer monsoon. While a number of studies have identified the impact of urbanization on local precipitation, a large-scale assessment has been lacking. This relation between urbanization and Indian monsoon rainfall changes is investigated by analyzing in situ and satellite-based precipitation and population datasets. Using a long-term daily rainfall dataset and high-resolution gridded analysis of human population, this study showed a significantly increasing trend in the frequency of heavy rainfall climatology over urban regions of India during the monsoon season. Urban regions experience less occurrences of light rainfall and significantly higher occurrences of intense precipitation compared to nonurban regions. Very heavy and extreme rainfall events showed increased trends over both urban and rural areas, but the trends over urban areas were larger and statistically more significant. Our analysis suggests that there is adequate statistical basis to conclude that the observed increasing trend in the frequency of heavy rainfall events over Indian monsoon region is more likely to be over regions where the pace of urbanization is faster. Moreover, rainfall measurements from satellites also indicate that urban areas are more (less) likely to experience heavier (lighter) precipitation rates compared to those in nonurban areas. While the mechanisms causing this enhancement in rainfall remain to be studied, the results provide the evidence that the increase in the heavy rainfall climatology over the Indian monsoon region is a signature of urban-induced rainfall anomaly.

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“…In recent years urban boundary layer research has received more attention, as people have realized that urbanization has impacts on weather and climate (Changnon, 1992;Martilli, 2002;Kalnay and Cai, 2003;Shepherd and Burian, 2003;Lim et al, 2005;Best, 2006). Studies on the urban boundary layer have been carried out through various approaches including observational experiment, physical modelling and numerical simulation.…”

Section: Introductionmentioning

confidence: 99%

Observational verification of urban surface roughness parameters derived from morphological models

Liu¹,

Sun²,

Jiang³

2008

Meteorological Applications

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This study focuses on how to verify the aerodynamic roughness parameters in an urban area by using observational data collected in the roughness sub-layer. Anemometrical observations were made in the downtown area of Nanjing, China, in summer and winter. Data were collected using both slow and fast response anemometers mounted on a 36 m tower. The friction velocity was observed just above the top of the urban canopy layer, which is at the height of 19.7 m, while the mean wind speed was observed at a relatively low level that is generally thought to be in the roughness sub-layer, of which the top usually ranges from 2 to 5 times the height of the urban canopy layer. The results of the measurements show that the dimensionless friction velocities (normalized by the mean wind speed at an upper level) maintain approximately a constant (0.20) and the fluctuations are small (±0.02) in a period of 21 days. The results imply that the similarity relation for the mean wind profile is still valid and that the effect of stratification is negligibly small in the urban roughness sub-layer.Based on the measurement results, the logarithmic wind profile was applied to verify the aerodynamic roughness parameters empirically derived from four morphological models: the rule of thumb (Rt) method, the Bottema (Ba) method, the Macdonald (Ma) method and the Raupach (Ra) method. The results show that they are not very different from each other. The good performance of the Rt method may be due to the fact that the distribution of buildings in the study area is regular. The Ba and Ra methods are likely to be better since they can give reasonable estimates of roughness parameters. Evidence indicates that the Ma method underestimates the roughness length.

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Detection of Urban-Induced Rainfall Anomalies in a Major Coastal City

Cited by 234 publications

References 37 publications

Remote sensing of the urban heat island effect across biomes in the continental USA

Remote sensing of the urban heat island effect across biomes in the continental USA

Urbanization signature in the observed heavy rainfall climatology over India

Observational verification of urban surface roughness parameters derived from morphological models

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