Abstract

The Birmingham Urban Climate Laboratory (BUCL) is a near-real-time, high-resolution urban meteorological network (UMN) of automatic weather stations and inexpensive, nonstandard air temperature sensors. The network has recently been implemented with an initial focus on monitoring urban heat, infrastructure, and health applications. A number of UMNs exist worldwide; however, BUCL is novel in its density, the low-cost nature of the sensors, and the use of proprietary Wi-Fi networks. This paper provides an overview of the logistical aspects of implementing a UMN test bed at such a density, including selecting appropriate urban sites; testing and calibrating low-cost, nonstandard equipment; implementing strict quality-assurance/quality-control mechanisms (including metadata); and utilizing preexisting Wi-Fi networks to transmit data. Also included are visualizations of data collected by the network, including data from the July 2013 U.K. heatwave as well as highlighting potential applications. The paper is an open invitation to use the facility as a test bed for evaluating models and/or other nonstandard observation techniques such as those generated via crowdsourcing techniques.

Abstract

Recent developments to the Local-scale Urban Meteorological Parameterization Scheme (LUMPS), a simple model able to simulate the urban energy balance, are presented. The major development is the coupling of LUMPS to the Net All-Wave Radiation Parameterization (NARP). Other enhancements include that the model now accounts for the changing availability of water at the surface, seasonal variations of active vegetation, and the anthropogenic heat flux, while maintaining the need for only commonly available meteorological observations and basic surface characteristics. The incoming component of the longwave radiation (L↓) in NARP is improved through a simple relation derived using cloud cover observations from a ceilometer collected in central London, England. The new L↓ formulation is evaluated with two independent multiyear datasets (Łódź, Poland, and Baltimore, Maryland) and compared with alternatives that include the original NARP and a simpler one using the National Climatic Data Center cloud observation database as input. The performance for the surface energy balance fluxes is assessed using a 2-yr dataset (Łódź). Results have an overall RMSE < 34 W m⁻² for all surface energy balance fluxes over the 2-yr period when using L↓ as forcing, and RMSE < 43 W m⁻² for all seasons in 2002 with all other options implemented to model L↓.

Abstract

Quantitative knowledge of the water and energy exchanges in agroecosystems is vital for irrigation management and modeling crop production. In this study, the seasonal and annual variabilities of evapotranspiration (ET) and energy exchanges were investigated under two different crop environments—flooded and aerobic soil conditions—using three years (June 2014–May 2017) of eddy covariance observations over a rice–wheat rotation in eastern China. Across the whole rice–wheat rotation, the average daily ET rates in the rice paddies and wheat fields were 3.6 and 2.4 mm day⁻¹, respectively. The respective average seasonal ET rates were 473 and 387 mm for rice and wheat fields, indicating a higher water consumption for rice than for wheat. Averaging for the three cropping seasons, rice paddies had 52% more latent heat flux than wheat fields, whereas wheat had 73% more sensible heat flux than rice paddies. This resulted in a lower Bowen ratio in the rice paddies (0.14) than in the wheat fields (0.4). Because eddy covariance observations of turbulent heat fluxes are typically less than the available energy (R _n − G; i.e., net radiation minus soil heat flux), energy balance closure (EBC) therefore does not occur. For rice, EBC was greatest at the vegetative growth stages (mean: 0.90) after considering the water heat storage, whereas wheat had its best EBC at the ripening stages (mean: 0.86).

Abstract

A simple model, the Surface Temperature and Near-Surface Air Temperature (at 2 m) Model (TsT2m), is developed to downscale numerical model output (such as from ECMWF) to obtain higher-temporal- and higher-spatial-resolution surface and near-surface air temperature. It is evaluated in Shanghai, China. Surface temperature (T _s ) and near-surface air temperature (T _a ) submodels account for variations in land cover and their different thermal properties, resulting in spatial variations of surface and air temperature. The net all-wave radiation parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature submodel, the objective hysteresis model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near-surface air temperature submodel considers the horizontal and vertical energy changes for a column of well-mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land-cover types, values are more similar. Downscaled, higher-temporal- and higher-spatial-resolution air temperatures are compared to observations at 110 automatic weather stations across Shanghai. After downscaling with TsT2m, the average forecast accuracy of near-surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress.

Abstract

Radiative fluxes are key drivers of surface–atmosphere heat exchanges in cities. Here the first yearlong (December 2012–November 2013) measurements of the full radiation balance for a dense urban site in Shanghai, China, are presented, collected with a CNR4 net radiometer mounted 80 m above ground. Clear-sky incoming shortwave radiation K _↓ (median daytime maxima) ranges from 575 W m⁻² in winter to 875 W m⁻² in spring, with cloud cover reducing the daily maxima by about 160 W m⁻². The median incoming longwave radiation daytime maxima are 305 and 468 W m⁻² in winter and summer, respectively, with increases of 30 and 15 W m⁻² for cloudy conditions. The effect of air quality is evident: haze conditions decrease hourly median K _↓ by 11.3%. The midday (1100–1300 LST) clear-sky surface albedo α is 0.128, 0.141, 0.143, and 0.129 for winter, spring, summer, and autumn, respectively. The value of α varies with solar elevation and azimuth angle because of the heterogeneity of the urban surface. In winter, shadows play an important role in decreasing α in the late afternoon. For the site, the bulk α is 0.14. The Net All-Wave Radiation Parameterization Scheme/Surface Urban Energy and Water Balance Scheme (NARP/SUEWS) land surface model reproduces the radiation components at this site well, which is a promising result for applications elsewhere. These observations help to fill the gap of long-term radiation measurements in East Asian and low-latitude cities, quantifying the effects of season, cloud cover, and air quality.

Abstract

To investigate the boundary layer dynamics of the coastal megacity Shanghai, China, backscatter data measured by a Vaisala CL51 ceilometer are analyzed with a modified ideal curve fitting algorithm. The boundary layer height z _i retrieved by this method and from radiosondes compare reasonably overall. Analyses of mobile and stationary ceilometer data provide spatial and temporal characteristics of Shanghai’s boundary layer height. The consistency between when the ceilometer is moving and stationary highlights the potential of mobile observations of transects across cities. An analysis of 16 months of z _i measured at the Fengxian site in Shanghai reveals that the diurnal variation of z _i in the four seasons follows the expected pattern; for all seasons z _i starts to increase at sunrise, reflecting the influence of solar radiation. However, the boundary layer height is generally higher in autumn and winter than in summer and spring (mean hourly averaged z _i for days with low cloud fraction at 1100–1200 local time are 900, 654, 934, and 768 m for spring, summer, autumn, and winter, respectively). This is attributed to seasonal differences in the dominant meteorological conditions, including the effects of a sea breeze at the near-coastal Fengxian site. Given the success of the retrieval method, other ceilometers installed across Shanghai are now being analyzed to understand more about the spatial dynamics of z _i and to investigate in more detail the effects of prevailing mesoscale circulations and their seasonal dynamics.

Abstract

Observations of atmospheric conditions and processes in cities are fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality, and climate models, and providing key information for city end users (e.g., decision makers, stakeholders, public). In this paper, Shanghai’s Urban Integrated Meteorological Observation Network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being multipurpose (e.g., forecast, research, service), multifunction (e.g., high-impact weather, city climate, special end users), multiscale (e.g., macro/meso, urban, neighborhood, street canyon), multivariable (e.g., thermal, dynamic, chemical, biometeorological, ecological), and multiplatform (e.g., radar, wind profiler, ground based, satellite based, in situ observation/sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments, to identify data gaps based on science- and user-driven requirements, and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

Abstract

The Surface Urban Energy and Water Balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux Q _F and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of Q _F are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data, and dynamic population density. The Q _F is estimated to be largest in summer (mean daily peak 236 W m⁻²). When Q _F is omitted, the SUEWS sensible heat flux Q _H reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When Q _F is included, the Q _H estimates are improved in spring, summer, and autumn but are poorer in winter, indicating winter Q _F is overestimated. Inclusion of Q _F has little influence on the simulated latent heat flux Q _E but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on Q _E . When irrigation is not considered, the simulated Q _E is underestimated for all seasons. The mean summer daytime Q _E is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly outdoor water use. This study highlights the importance of appropriately including Q _F and irrigation in urban land surface models—terms not generally considered in many previous studies.

Abstract

Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.

Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

Abstract

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no comparison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling approaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.