Air-Temperature Response to Neighborhood-Scale Variations in Albedo and Canopy Cover in the Real World: Fine-Resolution Meteorological Modeling and Mobile Temperature Observations in the Los Angeles Climate Archipelago

Thermo-Hygrometric Variability on Waterfronts in Negative Radiation Balance: A Case Study of Balneário Camboriú/SC, Brazil

Extensive urbanization around the world has resulted in the consumption of massive vegetated areas and natural resources. To this end, one strategy for urban development is to consolidate urban areas. In Balneário Camboriú/SC, Brazil, this trend has transformed the city into a vertical built-up area on its coastal strip, accommodating a large amount of buildings both in terms of quantity and number of floors. This research aims to quantify the thermo-hygrometric fluctuation on the waterfront of Balneário Camboriú, in negative radiation balance. To acquire the data on air temperature (Ta) and relative humidity (RH), two mobile transects and measuring at two fixed points were made in a situation of negative radiation balance on 26 August 2019, in the winter period of the Southern Hemisphere. The collection work began at 06:00:00 a.m. (before sunrise, the peak of the negative radiation balance), on Atlântica Avenue (waterfront) and Brasil Avenue (parallel to the waterfront). It was verified that the Ta varied from 16.0 °C to 19.0 °C, and the RH remained over 80% during the entire route. At the meteorological shelters, the temperature presented a variation from 14.4 °C to 17.7 °C, and the RH ranged from 79.6% to 91.3% between the two points. The spatial variability in the Ta and RH along the paths travelled and at the fixed points is directly related to the land cover, represented especially by the buildings’ verticalization and data collection time.

Development of an Urban Heat Mitigation Plan for the Greater Sacramento Valley, California, a Csa Koppen Climate Type

An urban atmospheric modeling study was undertaken with the goal of informing the development of a heat-mitigation plan for the greater Sacramento Valley, California. Realistic levels of mitigation measures were characterized and ranked in terms of their effectiveness in producing urban cooling under current conditions and future climate and land use. An urban heat-island index was computed for current and future climates based on each location’s time-varying upwind temperature reference points and its hourly temperatures per coincident wind direction. For instance, the UHII for the period 16–31 July 2015, for all-hours averaged temperature equivalent (i.e., °C · h hr−1), ranged from 1.5 to 4.7 °C across the urban areas in the region. The changes in local microclimates corresponding to future conditions were then quantified by applying a modified high-resolution urban meteorology model in dynamically downscaling a climate model along with future urbanization and land use change projections for each area. It was found that the effects of urbanization were of the same magnitude as that of the local climate change. Considering the urban areas in the region and the selected emissions scenarios, the all-hours temperature equivalent of the UHII (°C · h hr−1) increased by between 0.24 and 0.80 °C, representing an increase of between 17% and 13% of their respective values in the current climate. Locally, instantaneous (e.g., hourly) temperatures could increase by up to ~3 °C because of climate effects and up to ~5 °C because of both climate and urbanization changes. The efficacies of urban heat mitigation measures were ranked both at the county level and at local project scales. It was found that urban cooling measures could help decrease or offset exceedances in the National Weather Service heat index (NWS HI) above several warning thresholds and reduce the number of heatwave or excessive heat event days. For example, measures that combine increased albedo and urban forests can reduce the exceedances above NWS HI Danger level by between 50% and 100% and the exceedances above Extreme Caution level by between 18% and 36%. UHII offsets from each mitigation measure were quantified for two situations: (1) a scenario where a community implements cooling measures and no other nearby communities take any action and (2) a scenario where both the community and its upwind neighbors implement cooling measures. In this second situation, the community benefits from cooler air transported from upwind areas in addition to the local cooling resulting from implementation of its own heat mitigation strategies. The modeling of future climates showed that except for a number of instances, the ranking of measures in each respective urban area remains unchanged into the future.

A Mobile Vehicle-Based Methodology for Dynamic Microclimate Analysis

Accurate monitoring is critical for better understanding cities' microclimate conditions and safeguard citizens' health. Previous studies have performed microclimate analyses of urbanized areas by implementing data from either stable meteorological stations or satellites, or by developing mobile stations. Here, we present a vehicle-based monitoring campaign capable of monitoring both the scalar and directionally dependent variables that regulate the canopy layer environment. Under this framework, we performed a monitoring campaign within an Italian city, and measured simultaneously air temperature (±  0.3 ∘ C @ 20 ∘ C ), relative humidity (±  2% @ 20 ∘ C ), directional shortwave radiation (calibration uncertainty: < 1.8%), CO 2 (±  50 ppm +2%) and PM10 (< 1%) concentration, wind speed (±  3% @ 40 m/s) and direction (±  3 ∘ @ 40 m/s), and specific location (latitude, longitude and elevation). The presented assessment can be carried out within almost any area that motorized vehicles are allowed to access (e.g. through public transportation vehicles). Its application together with other mobile stations that can specifically assess also pedestrian areas, such as footpaths, urban parks, sidewalks and bike paths, as well as fixed meteorological stations and remote sensing techniques can contribute to a better understanding of microclimate patterns and hence to more efficient urban planning and risk assessments.

Intra-urban microclimate investigation in urban heat island through a novel mobile monitoring system

Monitoring microclimate variables within cities with high accuracy is an ongoing challenge for a better urban resilience to climate change. Assessing the intra-urban characteristics of a city is of vital importance for ensuring fine living standards for citizens. Here, a novel mobile microclimate station is applied for monitoring the main microclimatic variables regulating urban and intra-urban environment, as well as directionally monitoring shortwave radiation and illuminance and hence systematically map for the first time the effect of urban surfaces and anthropogenic heat. We performed day-time and night-time monitoring campaigns within a historical city in Italy, characterized by substantial urban structure differentiations. We found significant intra-urban variations concerning variables such as air temperature and shortwave radiation. Moreover, the proposed experimental framework may capture, for the very first time, significant directional variations with respect to shortwave radiation and illuminance across the city at microclimate scale. The presented mobile station represents therefore the key missing piece for exhaustively identifying urban environmental quality, anthropogenic actions, and data driven modelling toward risk and resilience planning. It can be therefore used in combination with satellite data, stable weather station or other mobile stations, e.g. wearable sensing techniques, through a citizens' science approach in smart, livable, and sustainable cities in the near future.

A New Approach for Understanding Urban Microclimate by Integrating Complementary Predictors at Different Scales in Regression and Machine Learning Models

Climate change is a major contemporary phenomenon with multiple consequences. In urban areas, it exacerbates the urban heat island phenomenon. It impacts the health of the inhabitants and the sensation of thermal discomfort felt in urban areas. Thus, it is necessary to estimate as well as possible the air temperature at any point of a territory, in particular in view of the ongoing rationalization of the network of fixed meteorological stations of Météo-France. Understanding the air temperature is increasingly in demand to input quantitative models related to a wide range of fields, such as hydrology, ecology, or climate change studies. This study thus proposes to model air temperature, measured during four mobile campaigns carried out during the summer months, between 2016 and 2019, in Lyon (France), in clear sky weather, using regression models based on 33 explanatory variables from traditionally used data, data from remote sensing by LiDAR (Light Detection and Ranging), or Landsat 8 satellite acquisition. Three types of statistical regression were experimented: partial least square regression, multiple linear regression, and a machine learning method, the random forest regression. For example, for the day of 30 August 2016, multiple linear regression explained 89% of the variance for the study days, with a root mean square error (RMSE) of only 0.23 °C. Variables such as surface temperature, Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI) have a strong impact on the estimation model. This study contributes to the emergence of urban cooling systems. The solutions available vary. For example, they may include increasing the proportion of vegetation on the ground, facades, or roofs, increasing the number of basins and water bodies to promote urban cooling, choosing water-retaining materials, humidifying the pavement, increasing the number of public fountains and foggers, or creating shade with stretched canvas.

Introducing Urban Overheating—Progress on Mitigation Science and Engineering Applications

Buildings and construction is the most important economic sector in the world after agriculture [...]

Observational Evidence of Neighborhood Scale Reductions in Air Temperature Associated with Increases in Roof Albedo

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night.