We are all familiar with the fact that cities are generally warmer than the surrounding, more rural areas. We see it referenced most nights in our television weather reports. It is especially significant on nights with clear skies and light winds which favor radiational cooling. This is most significant in the rural areas but in the city, the excess heat absorbed during the day and the local heat sources maintain higher nighttime readings. During the days or nights with strong winds and clouds the differences are minimzed due to mixing and the advective cooling of the city by the winds.

The urban heat island

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.城市环境位于社会、文化和经济活动的结合点,城市下垫面具有独特的生物物理特征。在城市化过程中持续的基础设施建设导致自然景观被建筑物替代。在过去很长时间,绝大部分城市影响天气气候的研究和城市热岛效应(城市及上空温度高于周边地区)有关。除了城市热岛效应,城市化也影响大气湿度、风、边界层结构、云的形成、污染物扩散、降水和暴雨。在这篇综述文章中,我们阅览了超过五百篇文献,从观测和模拟两个方面,首先介绍了用于城市化及影响研究的数据资料和方法,总结了城市化影响区域气候和极端天气的各个领域的科学要点。我们也例举了在理解城市化影响方面目前存在的主要问题和挑战,提出了相应的未来研究重点和方向。. 

/pdf/urbanization-impact-on-regional-climate-and-extreme-weather-1v8dakqv.pdf

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Abstract The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water bodies—from the spatial distribution to the long-term trend—is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km 3 year −1 and it has increased at a rate of 3.12 km 3 year −1 . The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems. 

/pdf/evaporative-water-loss-of-1-42-million-global-lakes-1ojxufmc.pdf

Evaporative water loss of 1.42 million global lakes

/pdf/evaporative-water-loss-of-1-42-million-global-lakes-2qajvj6r.pdf

In times of urbanization and climate change, urban green spaces and their ecosystem services are pivotal for adapting to extreme weather events such as heat and drought. But what happens to the provision of ecosystem services when green spaces themselves are compromised by heat and drought? In this study, we assessed the air temperature regulation by two structurally distinct inner-city parks in Leipzig, Germany, that were strongly affected by the heat and drought periods in 2018 and 2019. We used a dense network of in-situ measurements and machine learning to create spatially explicit maps of air temperature distribution at a fine-scale neighborhood level for a 24 h period during the summer heat wave in 2019. The results showed that the larger, tree-dominated park could maintain spaces of relative coolness at any time, whereas the other rather open, grass-dominated park was strongly heated during the daytime but provided relatively cool air during the night and early morning. We found a maximum spatially averaged cooling effect of green spaces versus the built-up surroundings of 1.1°C in the morning. In the afternoon, however, when air temperatures peaked at nearly 40°C, cooling was limited to shaded areas, leading to average differences between green spaces and built-up surroundings below 1°C. Our spatially explicit maps indicated that the “cooling distances” of green spaces, i.e., cooling effects that extend beyond the boundaries of a park, are negligible during dry and hot conditions. We conclude that vegetation structure, particularly the configuration of trees, is key to designing heat and drought-resilient green spaces and thus maintaining ecosystem service provision under the challenges of climate change. Urban planning needs to account for larger green spaces that are complemented by decentralized, well-distributed small-scale green infrastructure that intersperses the built infrastructure such as roadside greenery and vegetated backyards.

/pdf/parks-under-stress-air-temperature-regulation-of-urban-green-2gp0qned.pdf

Parks Under Stress: Air Temperature Regulation of Urban Green Spaces Under Conditions of Drought and Summer Heat

Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobilemeasurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist’s smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.038–0.058C for temperature and of 0.18%–0.33% for relative humidity (one standard deviation of variation amongmultiple units). The time constant with a complete radiation shelter andmoving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70m.Measurements weremadewith the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect.

Performance Evaluation of a Smart Mobile Air Temperature and Humidity Sensor for Characterizing Intracity Thermal Environment

. Eddy covariance data are widely used for the investigation of surface–air
interactions. Although numerous datasets exist in public depositories for
land ecosystems, few research groups have released eddy covariance data
collected over lakes. In this paper, we describe a dataset from the Lake
Taihu eddy flux network, a network consisting of seven lake sites and one
land site. Lake Taihu is the third-largest freshwater lake (area of 2400 km 2 ) in China, under the influence of subtropical climate. The dataset
spans the period from June 2010 to December 2018. Data variables are saved
as half-hourly averages and include micrometeorology (air temperature,
humidity, wind speed, wind direction, rainfall, and water or soil temperature
profile), the four components of surface radiation balance, friction
velocity, and sensible and latent heat fluxes. Except for rainfall and wind
direction, all other variables are gap-filled, with each data point marked by
a quality flag. Several areas of research can potentially benefit from the
publication of this dataset, including evaluation of mesoscale weather
forecast models, development of lake–air flux parameterizations,
investigation of climatic controls on lake evaporation, validation of remote-sensing surface data products and global synthesis on lake–air
interactions. The dataset is publicly available at https://yncenter.sites.yale.edu/data-access (last access: 24 October 2020) and from the Harvard Dataverse
( https://doi.org/10.7910/DVN/HEWCWM ; Zhang et al., 2020).

/pdf/a-dataset-of-microclimate-and-radiation-and-energy-fluxes-zslddmd5gp.pdf

A dataset of microclimate and radiation and energy fluxes from the Lake Taihu eddy flux network

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Performance Evaluation of a Smart Mobile Air Temperature and Humidity Sensor for Characterizing Intracity Thermal Environment

A dataset of microclimate and radiation and energy fluxes from the Lake Taihu eddy flux network