Changes in wind speed under heat waves enhance urban heat islands in the Beijing Metropolitan Area

The interaction between urban heat islands (UHIs) and heat waves (HWs) is studied using measurements collected at two towers in the Beijing, China, metropolitan area and an analytical model. Measurements show that 1) the positive interaction between UHIs and HWs not only exists at the surface but also persists to higher levels (up to ~70 m) and 2) the urban wind speed is enhanced by HWs during daytime but reduced during nighttime as compared with its rural counterpart. A steady-state advection–diffusion model coupled to the surface energy balance equation is then employed to understand the implication of changes in wind speed on UHIs, which reveals that the observed changes in wind speed positively contribute to the interaction between UHIs and HWs in both daytime and nighttime. The vertical structure of the positive interaction between UHIs and HWs is thus likely an outcome resulting from a combination of changes in the surface energy balance and wind profile

An Empirical Model for Estimating Soil Thermal Conductivity from Soil Water Content and Porosity

Soil thermal conductivity l is a vital parameter for soil temperature and soil heat flux forecasting in hydrological models. In this study, an empirical model is developed to relate l only to soil volumetric water content u and soil porosity us. Measured l values for eight soils are used to establish the empirical model, and data from four other soils are used to evaluate the model. The new model is also evaluated by its performance in the Simple Biosphere Model 2 (SiB2). Results show that the root-mean-square errors (RMSEs; ranging from 0.097 to 0.266 W m21 K21 ) of the new model estimates of l are lower than those (ranging from 0.416 to 1.006 W m21 K21 ) for an empirical model of similar complexity reported in the literature earlier. Further, with simple inputs and equations, the new model almost has the accuracy of other more complex models (RMSE of l ranging from 0.040 to 0.354 W m21 K21 ) that require additional detailed soil information. The new model can be readily incorporated in large-scale models because of its simplicity as compared to the more complex models. The new model is tested for its effectiveness by incorporating it into SiB2. Compared to the original SiB2 l model, the new l model provides better estimates of surface effective radiative temperature and soil wetness. Owing to the newly presented empirical model’s requirement for simple, available inputs and its accuracy, its usage is recommended within large-scale models for applications where detailed information about soil composition is lacking

Improving Soil Heat Flux Accuracy with the Philip Correction Technique

Soil heat flux Gs is an important component of the surface energy balance. Soil heat flux plates (SHFPs) are widely used to measure Gs, although several errors are known to occur. The Philip correction has been applied to minimize errors in Gs measured by SHFPs (Gp) if the soil thermal conductivity λs, SHFP thermal conductivity λp, and plate geometry function H are known. The objective of this study is to evaluate the effectiveness of the Philip correction for a variety of SHFPs. The λp were determined without thermal contact resistance and differed from the manufacturer-specified λp. A simplified H formulation was similar to or less than the full H equation for different SHFP shapes. The G ratio (Gp/Gs) was sensitive to λs/λp and H when they were relatively small. Compared with the Gs determined by a gradient method (Gs_grad), the Gpmeasured under a full corn (Zea mays, L.) canopy in the field underestimated Gs by 38%–62%. After applying the Philip correction, almost all Gp agreed better with Gs_grad. Generally, the Gp corrected with measured plate parameters agreed better with Gs_grad than those corrected with manufacturer-specified values. The Gp corrected with the simplified and full H expression differed for different SHFPs. These results indicate that SHFPs always underestimate Gs and that the performance of the Philip correction is affected by λp, plate dimensions, and H. An alternative method to measure Gs by a three-needle heat-pulse sensor or a gradient method, in which soil temperature and water content are measured at several depths, is recommended

Quality Assessment of YUNYAO GNSS-RO Refractivity Data in the Neutral Atmosphere

GNSS (Global Navigation Satellite System) Radio Occultation (RO) data is an important component of numerical weather prediction (NWP) systems. To incorporate more GNSS RO data into NWP systems, commercial RO data has become an excellent option. Tianjin Yunyao Aerospace Technology Co., Ltd. (YUNYAO) plans to launch a meteorological constellation of 90 satellites equipped with GNSS-RO instruments, which will significantly increase the amount of GNSS-RO data in NWP systems. This study evaluates the quality of neutral atmosphere refractivity profiles from YUNYAO satellites Y003 to Y010 during the period from May 1 to July 31, 2023. Compared with the refractivity calculated from ERA5, the absolute value of the mean bias (MB) for YUNYAO refractivity data is generally less than 1.5 % between 0 and 40 km, and close to 0 between 4 and 40 km. The standard deviation (SD) is less than 3.4 %, and there are differences in the SDs for different GNSS satellites, especially in the lower troposphere and the stratosphere. Second, the refractivity error SD of YUNYAO RO data is estimated using the "three-cornered hat" (3CH) method and multiple data sets. In the pressure range of 1000–10 hPa, the refractivity error SD of YUNYAO RO data is below 2.6 %, and the differences in refractivity error SD among different GNSS satellites do not exceed 0.5 %. Finally, compared to COSMIC-2 and Metop-C RO data, YUNYAO RO data exhibit consistent refractivity error SD and are smaller within 300–50 hPa

An Analytical Solution to the One-Dimensional Heat Conduction–Convection Equation in Soil

Soil heat transfer occurs by conduction and convection. Soil temperatures below infiltrating water can provide a signal for water flux. In earlier work, analysis of field measurements with a sine wave model indicated that convection heat transfer made significant contributions to the subsurface temperature oscillations. In this work, we used a Fourier series to describe soil surface temperature variations with time. The conduction and convection heat transfer equation with a multi-sinusoidal wave boundary condition was solved analytically using a Fourier transformation. Soil temperature values calculated by the single sine wave model and by the Fourier series model were compared with field soil temperature values measured at depths of 0.1 and 0.3 m below an infiltrating ponded surface. The Fourier series model provided better estimates of observed field temperatures than the sine wave model. The new model provides a general way to describe soil temperature under an infiltrating water source

Attribution and mitigation of heat wave-induced urban heat storage change

When the urban heat island (UHI) effect coincides with a heat wave (HW), thermal comfort conditions in cities are exacerbated. Understanding the surface energy balance (SEB) responses to HWs is critical for improving predictions of the synergies between UHIs and HWs. This study evaluates observed SEB characteristics in four cities (Beijing, Łódź, London and Swindon), along with their ambient meteorological conditions, for both HW and background summer climate (BC) scenarios. Using the Analytical Objective Hysteresis Model (AnOHM), particular emphasis is on the heat storage. The results demonstrate that in London and Swindon not only the amount of daytime heat storage but also its portion relative to the net all-wave radiation increase under HWs. Results further demonstrate that such increases are strongly tied to lower wind speeds. The effects of different UHI mitigation measures on heat storage are assessed using AnOHM. Results reveal that using reflective materials and maintaining higher soil moisture availability may offset the adverse effects of increased heat storage

Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset

To compare the impact of surface–atmosphere exchanges from rural and urban areas, fully vegetated areas (e.g. deciduous trees, evergreen trees and grass) commonly found adjacent to cities need to be modelled. Here we provide a general workflow to derive parameters for SUEWS (Surface Urban Energy and Water Balance Scheme), including those associated with vegetation phenology (via leaf area index, LAI), heat storage and surface conductance. As expected, attribution analysis of bias in SUEWS-modelled QE finds that surface conductance (gs) plays the dominant role; hence there is a need for more estimates of surface conductance parameters. The workflow is applied at 38 FLUXNET sites. The derived parameters vary between sites with the same plant functional type (PFT), demonstrating the challenge of using a single set of parameters for a PFT. SUEWS skill at simulating monthly and hourly latent heat flux (QE) is examined using the site-specific derived parameters, with the default NOAH surface conductance parameters (Chen et al., 1996). Overall evaluation for 2 years has similar metrics for both configurations: median hit rate between 0.6 and 0.7, median mean absolute error less than 25Wm-2, and median mean bias error ~5Wm-2. Performance differences are more evident at monthly and hourly scales, with larger mean bias error (monthly: ~40Wm-2; hourly ~30Wm-2) results using the NOAH-surface conductance parameters, suggesting that they should be used with caution. Assessment of sites with contrasting QE performance demonstrates how critical capturing the LAI dynamics is to the SUEWS prediction skills of gs and QE. Generally gs is poorest in cooler periods (more pronounced at night, when underestimated by ~3mms-1). Given the global LAI data availability and the workflow provided in this study, any site to be simulated should benefit

Contrasting responses of urban and rural surface energy budgets to heat waves explain synergies between urban heat islands and heat waves

Heat waves (HWs) are projected to become more frequent and last longer over most land areas in the late 21st century, which raises serious public health concerns. Urban residents face higher health risks due to synergies between HWs and urban heat islands (UHIs) (i.e., UHIs are higher under HW conditions). However, the responses of urban and rural surface energy budgets to HWs are still largely unknown. This study analyzes observations from two flux towers in Beijing, China and reveals significant differences between the responses of urban and rural (cropland) ecosystems to HWs. It is found that UHIs increase significantly during HWs, especially during the nighttime, implying synergies between HWs and UHIs. Results indicate that the urban site receives more incoming shortwave radiation and longwave radiation due to HWs as compared to the rural site, resulting in a larger radiative energy input into the urban surface energy budget. Changes in turbulent heat fluxes also diverge strongly for the urban site and the rural site: latent heat fluxes increase more significantly at the rural site due to abundant available water, while sensible heat fluxes and possibly heat storage increase more at the urban site. These comparisons suggest that the contrasting responses of urban and rural surface energy budgets to HWs are responsible for the synergies between HWs and UHIs. As a result, urban mitigation and adaption strategies such as the use of green roofs and white roofs are needed in order to mitigate the impact of these synergies

Thermal property values of a central Iowa soil as functions of soil water content and bulk density or of soil air content

Soil thermal properties play important roles in dynamic heat and mass transfer processes, and they vary with soil water content (θ) and bulk density (ρ b). Both θ and ρ bchange with time, particularly in recently tilled soil. However, few studies have addressed the full extent of soil thermal property changes with θ and ρ b. The objective of this study is to examine how changes in ρ b with time after tillage impact soil thermal properties (volumetric heat capacity, C v, thermal diffusivity, k, and thermal conductivity, λ). The study provides thermal property values as functions of θ and ρ b and of air content (n air) on undisturbed soil cores obtained at selected times following tillage. Heat pulse probe measurements of thermal properties were obtained on each soil core at saturated, partially saturated (θ at pressure head of −50 kPa) and oven‐dry conditions. Generally, kand λ increased with increasing ρ b at the three water conditions. The C v increased as ρ bincreased in the oven‐dry and unsaturated conditions and decreased as ρ b increased in the saturated condition. For a given θ, a larger ρ b was associated with larger thermal property values, especially for λ. The figures of C v, k and λ versus θ and ρ b, as well as C v, k and λ versus n air, represented the range of soil conditions following tillage. Trends in the relationships of thermal property values with θ and ρ b were described by 3‐D surfaces, whereas each thermal property had a linear relationship with n air. Clearly, recently tilled soil thermal property values were quite dynamic temporally due to varying θ and ρ b. The dynamic soil thermal property values should be considered in soil heat and mass transfer models either as 3‐D functions of θ and ρ b or as linear functions of n air