Fog events and local atmospheric features simulated by regional climate model for the metropolitan area of São Paulo, Brazil

Rocha, Rosmeri Porfírio da; Gonçalves, Fábio Luiz Teixeira; Segalin, Bruna

doi:10.1016/j.atmosres.2014.06.010

Cited by 17 publications

(7 citation statements)

References 17 publications

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“…Therefore, there is no clear sign for these variables as well as for total/net radiation, since solar radiation did not change in future for most of the models. Concerning wind, [36] future climate simulations show that model outputs present poor results for surface values.…”

Section: Weather Datamentioning

confidence: 95%

Residential buildings’ thermal performance and comfort for the elderly under climate changes context in the city of São Paulo, Brazil

Alves

Duarte

Gonçalves

2016

Energy and Buildings

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Section: Weather Datamentioning

confidence: 95%

Residential buildings’ thermal performance and comfort for the elderly under climate changes context in the city of São Paulo, Brazil

Alves

Duarte

Gonçalves

2016

Energy and Buildings

Self Cite

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“…At this point, it is not unequivocally clear why the logistic regression does not confirm this picture. We speculate that the SO 2 concentration is, in the MASP, more closely related to the formation of haze situations (visibility 1-5 km) with lower humidity associated with radiative processes, while situations of even lower visibility (< 1 km) are mostly associated with humidity advected from the Atlantic Ocean (Da Rocha et al 2015). Also, there may be a temporal and spatial mismatch between the observation of fog (one location, often one point in time during a day) and the SO 2 data (daily medians over the entire MASP).…”

Section: Discussionmentioning

confidence: 86%

“…Gonçalves et al (2008) suggested that regional warming led to the observed decrease of fog. Similarly, Da Rocha et al (2015) also argue that regional processes account for the occurrence of fog in the MASP, but they suspect radiative rather than advective processes. However, other studies have suggested that both global warming and an increase in air quality have been driving observed decreases in fog at various sites worldwide, including the MASP (Vautard et al 2009;Klemm and Lin 2016).…”

Section: Introductionmentioning

confidence: 99%

Fog, Temperature and Air Quality Over the Metropolitan Area of São Paulo: a Trend Analysis from 1998 to 2018

Mühlig

Klemm

Gonçalves

2020

Water Air Soil Pollut

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This study investigates the long-term development of fog occurrences in the Metropolitan Area of São Paulo (MASP). Specifically, it analyzes the roles of meteorological and air quality parameters as potential drivers for fog formation. A dataset reaching back to the year 1933 shows that the overall trends of the annual fog occurrences (AFO) coincide with those of the annual mean temperature. Air quality data have been available since 1998, allowing us to perform a statistical analysis of the contributions of meteorology and air quality to AFO for the period from 1998 to 2018. The logistic regression model shows that the binary dependent variable (daily fog occurrence, FO) is explained by its independent predictors PM10, relative humidity (rH), and daily minimum temperature (Tmin), in that order. FO was not found to be significantly influenced by atmospheric pressure (aP) and nitrogen oxides (NOx). While the influence of SO2 was minor and associated with less confidence, it was negative. Potential causes for these surprising results are discussed. We conclude that the parameters PM10, rH, and Tmin are significant drivers of fog formation in the MASP, whereby the total explanatory power of the drivers for the dichotomous variable FO is 16%.

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“…Gridded CRU temperature and precipitation data are based on interpolated monthly data collected at 4,800 stations around the world. Although CRU data have been previously used as the observed data set of comparison in regional climate studies over Brazil (Da Rocha et al, ; Lee & Berbery, ), because there exists poor station data coverage in the interior of South America our “observed” data set may be biased and underestimate spatial and interannual variability (Malhi & Wright, ; New et al, ). In an analysis comparing various gridded precipitation data sets, including CRU, to Agencia Nacional de Aguas streamflow data, Levy et al () demonstrated that over the Brazilian rainforest‐savanna transition zone, which overlaps with our study region, the Precipitation Estimate from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) data set is the best observational data set for the region.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Agricultural Land Cover Representations on Regional Climate Model Simulations in the Brazilian Cerrado

2018

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Examining interactions between large‐scale land cover and land use change and regional climate in areas undergoing dynamic land transformations, like the Brazilian Cerrado, is crucial for understanding tradeoffs between human needs and ecosystem services. Yet regional climate models often do not include accurate land cover data of these complex landscapes. We use National Center for Atmospheric Research's Weather Research and Forecasting (WRF) model coupled to the Noah‐Multiparameterization (Noah‐MP) land surface model to run 10‐year climate simulations across Brazil to assess (1) whether an accurate, regionally validated land cover data set with two, new agricultural land cover classifications improves model simulation results; (2) the ability of Noah‐MP's dynamic vegetation option to model vegetation growth; and (3) the sensitivity of the model output to scale. The results of the simulations with the updated land surface perform better over intensive agricultural areas for precipitation, evapotranspiration, and temperature, especially during the wet‐to‐dry season transition months. Evapotranspiration is overestimated during the start of the rainy season across all model simulations, which is likely due to the soil moisture model. We also find that using the Noah‐MP dynamic vegetation significantly degrades agricultural leaf area index phenology simulations in Brazilian agricultural regions. Lastly, improving the model's resolution did not improve model output when compared to observational data. Incorporating more accurate representations of the landscape into regional climate models is essential for quantifying potential changes in climatological seasonality in dynamic, human‐modified regions and making informed land use decisions.

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Fog events and local atmospheric features simulated by regional climate model for the metropolitan area of São Paulo, Brazil

Cited by 17 publications

References 17 publications

Residential buildings’ thermal performance and comfort for the elderly under climate changes context in the city of São Paulo, Brazil

Residential buildings’ thermal performance and comfort for the elderly under climate changes context in the city of São Paulo, Brazil

Fog, Temperature and Air Quality Over the Metropolitan Area of São Paulo: a Trend Analysis from 1998 to 2018

Evaluation of Agricultural Land Cover Representations on Regional Climate Model Simulations in the Brazilian Cerrado

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