Persistent cloud cover over mega-cities linked to surface heat release

Theeuwes, Natalie; Barlow, Janet F.; Teuling, Adriaan J.; Grimmond, Sue; Kotthaus, Simone

doi:10.1038/s41612-019-0072-x

Cited by 69 publications

(70 citation statements)

References 50 publications

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“…A similar conclusion was e.g. found with respect to clouds over metropolitan areas (Theeuwes et al, 2019). In future, urban scale resolving models (e.g., Maronga et al, 2020) will help to investigate the role of particle transport on the distribution of aerosols in the mixing layer and thus their heterogeneity.…”

Section: Discussionsupporting

confidence: 80%

On the spatial variability of the regional aerosol distribution as determined from ceilometers

Wiegner

Geiß

Mattis

et al. 2020

Preprint

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Abstract. Measurements of the vertical distribution of aerosol particles are typically only available at selected sites leaving the question of their representativeness for urban and regional scales unanswered. As a contribution to solve this problem we have investigated ceilometer signals from two testbeds in Munich and Berlin, Germany. For each testbed measurements of 24 months from 6 ceilometers were available. This constitutes a unique data set, in particular as the same type of instruments are deployed and the same data evaluation schemes applied. Two parameters are discussed: the mixing layer height (MLH) as an indicator for the vertical distribution and the integrated backscatter as a proxy for the amount of aerosols in the mixing layer. The MLH was determined by the COBOLT algorithm, the integrated backscatter from the Klett (backward and forward) inversion scheme. It was found that the mean difference of the MLH at two sites within a testbed typically only varies by less than 50&#8201;m, slightly increasing with the distance of the corresponding sites. Almost 60&#8201;% of all intercomparisons agree within &#177;100&#8201;m. MLHs are typically correlated with R > 0.9 in particular for the Berlin-testbed. With respect to the integrated backscatter the correlation is in the range of 0.7 < R < 0.9. This is expected from the diversity of local aerosol sources within a given testbed. We conclude from our data that the MLH determined from a single ceilometer is applicable for a whole metropolitan area. However, the integrated backscatter of particles within the mixing layer exhibits a variability of 15&#8211;25&#8201;% suggesting that one ceilometer is not representative, especially if atmospheric processes shall be investigated.

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Section: Discussionsupporting

confidence: 80%

On the spatial variability of the regional aerosol distribution as determined from ceilometers

Wiegner

Geiß

Mattis

et al. 2020

Preprint

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“…Impact of cities on the cloud fraction (Fig. 11) is well documented also by Theeuwes et al (2019), who investigated cloud cover and its differences in Paris and London and their surroundings during the warm season. They also found a cloud cover urban increase during afternoon and evening, despite drier atmosphere above cities that leads to a cloud base located higher by approximately 250 m. Higher temperatures in cities probably result in partial dissolution of non-precipitation stratiform clouds and fog in winter, with statistically significant cloud cover reduction during morning hours, because urban precipitation is not reduced (but rather increased, Fig.…”

Section: Discussionsupporting

confidence: 54%

“…Huszar et al, 2014;Trusilova et al, 2016;Göndöcs et al, 2017;Karlický et al, 2018;Huszár et al, 2018;Huszar et al, 2018Huszar et al, , 2020. Also the moisture flux decrease in cities is a well-known phenomenon as shown already by Oke (1987), or more recently by Theeuwes et al (2019) from latent heat flux comparison. In terms of wind speed changes in urban areas, no statistically significant differences occur during summer evening hours, when the cross-model average is nearly zero.…”

Section: Discussionmentioning

confidence: 87%

“…E.g. Theeuwes et al (2019) describe the observed cloud cover enhancement over Paris and London during summer as a consequence of increased convection caused by UHI. Manola et al (2020) show increased summer precipitation intensities and also overall precipitation increase in the city of Amsterdam in comparison to rural surroundings, also as a result of enhanced convection over the urban area.…”

Section: Introductionmentioning

confidence: 99%

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The `urban meteorology island': a multi-model ensemble analysis

Karlický¹,

Huszár²,

Nováková³

et al. 2020

Preprint

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Abstract. Cities and urban areas are well-known for their impact on meteorological variables and thereby modification of the local climate. Our study aims to generalize the urban-induced changes of specific meteorological variables by introducing a single phenomenon – the urban meteorology island (UMI). A wide ensemble of 24 model simulations with the WRF and RegCM regional climate models on European domain was performed to investigate various urban-induced modifications as individual components of the UMI. The results show that such an approach is meaningful, because nearly in all meteorological variables considered, statistically significant changes occur in cities. Besides previously documented urban-induced changes of temperature, wind speed and boundary-layer height, the study is focused also on changes of cloud cover, precipitation and humidity. An increase of cloud cover in cities, together with a higher amount of sub-grid scale precipitation is detected in summer afternoons. Specific humidity is significantly lower in cities. Further, the study shows that different models and parameterizations can have a strong impact on discussed components of UMI. Multi-layer urban scheme with anthropogenic heat considered increases winter temperatures by more than 2 °C and reduces wind speed more strongly than other urban models. Also the selection of planetary boundary-layer scheme influences the urban wind speed reduction, as well as boundary-layer height with the greatest extent. Finally, urban changes in cloud cover and precipitation are mostly sensitive to the parameterization of convection.

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“…variance, skewness, kurtosis. The vertical velocity variance is used as a measure for the turbulent mixing in the boundary layer and a simple threshold is used to determine the top of the mixed layer following previous studies (Barlow et al, 2015;Theeuwes et al, 2019). Data where the signal to noise ratio was low (SNR + 1 < 1.01) are filtered out.…”

Section: Model Description: High-resolution Uk Model (Ukv)mentioning

confidence: 99%

Understanding physical processes and feedback mechanisms between the urban surface and the overlying atmosphere

Tsiringakis

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Chapter 2 On-and off-line evaluation of the single-layer urban canopy model in London summertime conditions Chapter 3 Surface and atmospheric driven variability of the single-layer urban canopy model under clear sky conditions over London Chapter 4 Interactions between the nocturnal low-level jets and the urban boundary layer: a case study over London Chapter 5 On the role of turbulence and momentum advection in the formation of nocturnal low-level jets over urban areas Chapter 6 Synthesis 117 Appendix 125 List of Publications 171 Education Certificate 172 1.4 Modelling the urban surface 7 Atmospheric level Urban surface SLAB UCM Single-layer UCM Multi-layer UCM1.4 Modelling the urban surface 91.5 The coupling between the urban surface, urban boundary layer and meso-scale flows 13Chapter 2 On-and off-line evaluation of the single-layer urban canopy

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Persistent cloud cover over mega-cities linked to surface heat release

Cited by 69 publications

References 50 publications

On the spatial variability of the regional aerosol distribution as determined from ceilometers

On the spatial variability of the regional aerosol distribution as determined from ceilometers

The `urban meteorology island': a multi-model ensemble analysis

Understanding physical processes and feedback mechanisms between the urban surface and the overlying atmosphere

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