Implementation of a new urban energy budget scheme into MetUM. Part II: Validation against observations and model intercomparison

In the first part of this article, we introduced a new urban surface scheme, the Met Office – Reading Urban Surface Exchange Scheme (MORUSES), into the Met Office Unified Model (MetUM) and compared its impact on the surface fluxes with respect to the current urban scheme. In this second part, we aim to analyze further the reasons behind the differences. This analysis is conducted by a comparison of the performance of the two schemes against observations and against a third model, the Single Column Reading Urban model (SCRUM). The key differences between the three models lie in how each model incorporates the heat stored in the urban fabric and how the surface-energy balance is coupled to the underlying substrate. The comparison of the models with observations from Mexico City reveals that the performance of MORUSES is improved if roof insulation is included by minimizing the roof thickness. A comparison of MORUSES and SCRUM reveals that, once insulation is included within MORUSES, these two models perform equally well against the observations overall, but that there are differences in the details of the simulations at the roof and canyon level. These differences are attributed to the different representations of the heat-storage term, specifically differences in the dominant frequencies captured by the urban canopy and substrate, between the models. These results strongly suggest a need for an urban model intercomparison exercise. Copyright © 2010 Royal Meteorological Society and Crown Copyrigh

Implementation of a new urban energy budget scheme in the MetUM. Part I: Description and idealized simulations

This paper describes the formulation of a new urban scheme, MORUSES (Met Office–Reading Urban Surface Exchange Scheme) for use in the Met Office Unified Model. The implementation of the new scheme ensures that (1) the new scheme offers more flexibility in the parametrization of the building properties, and hence provides a more realistic representation of the fluxes; (2) the bulk outputs are in satisfactory agreement with previous observational studies; and (3) the impact of the new scheme on the energy balance fluxes is similar to the impact of the current urban scheme when set up to mimic it. As well as having a better physical basis, MORUSES also gains in flexibility in applications and adaptations to different urban materials as well as urban planning. The new scheme represents the urban area as a composition of two tiles, a canyon and a roof, using a simple 2D geometry. Sensitivity analysis to canyon geometry and thickness of the roof canopy emphasizes the gain in flexibility captured by the new scheme. Copyright © 2010 Royal Meteorological Society and Crown Copyrigh

Importance of initial state and atmospheric conditions for urban land surface models' performance

Urban land surface models (LSM) are commonly evaluated for short periods (a few weeks to months) because of limited observational data. This makes it difficult to distinguish the impact of initial conditions on model performance or to consider the response of a model to a range of possible atmospheric conditions. Drawing on results from the first urban LSM comparison, these two issues are considered. Assessment shows that the initial soil moisture has a substantial impact on the performance. Models initialised with soils that are too dry are not able to adjust their surface sensible and latent heat fluxes to realistic values until there is sufficient rainfall. Models initialised with too wet soils are not able to restrict their evaporation appropriately for periods in excess of a year. This has implications for short term evaluation studies and implies the need for soil moisture measurements to improve data assimilation and model initialisation. In contrast, initial conditions influencing the thermal storage have a much shorter adjustment timescale compared to soil moisture. Most models partition too much of the radiative energy at the surface into the sensible heat flux at the probable expense of the net storage heat flux

The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

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 com- parison 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 ap- proaches 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

Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF

Adaptive selection of members for convective-permitting regional ensemble prediction over the western Maritime Continent

A common issue faced by the downscaled regional ensemble prediction systems is the under-dispersiveness of the ensemble forecasts, often attributed to the lack of spread under the initial conditions from the global ensemble. In this study, a novel method that adopts an adaptive approach to selecting global ensemble members for regional downscaling has been developed. Instead of using a fixed set of pre-selected global ensemble members, the adaptive selection performs a sampling algorithm and selects the global ensemble members, which maximizes a fractions skill score (FSS)-based displacement between ensemble members. The method is applied to a convective-permitting ensemble prediction system over the western Maritime Continent, referred to as SINGV-EPS. SINGV-EPS has a grid spacing of 4.5 km and is a 12-member ensemble that is driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) 51-member global ensemble. Month-long trials were conducted in June 2020 to assess the impact of adaptive selection on the ensemble forecast spread and rainfall verification scores. In both fixed pre-selection and adaptive selection experiments, SINGV-EPS was still under-dispersive. However, adaptive selection improved the ensemble spread and reduced the root-mean-square error (RMSE) of the ensemble mean in wind, temperature, and precipitation fields. Further verification of the rainfall forecasts showed that there was a reduction in the Brier score and a higher hit rate in the relative operating characteristic (ROC) curve for all rainfall thresholds when adaptive selection was applied. Additionally, the ensemble mean forecasts from adaptive selection experiments are more accurate beyond 24 h, with a higher FSS for all rainfall thresholds and neighborhood lengths. These results suggest that the adaptive selection is superior to the fixed pre-selection of global ensemble members for downscaled regional ensemble prediction

How do green roofs mitigate urban thermal stress under heat waves?

As the climate warms, heat waves (HW) are projected to be more intense and to last longer, with serious implications for public health. Urban residents face higher health risks because urban heat islands (UHIs) exacerbate HW conditions. One strategy to mitigate negative impacts of urban thermal stress is the installation of green roofs (GRs) given their evaporative cooling effect. However, the effectiveness of GRs and the mechanisms by which they have an effect at the scale of entire cities are still largely unknown. The Greater Beijing Region (GBR) is modeled for a HW scenario with the Weather Research and Forecasting (WRF) model coupled with a state-of-the-art urban canopy model (PUCM) to examine the effectiveness of GRs. The results suggest GR would decrease near-surface air temperature (ΔT2max = 2.5 K) and wind speed (ΔUV10max = 1.0 m s-1) but increase atmospheric humidity (ΔQ2max = 1.3 g kg-1). GRs are simulated to lessen the overall thermal stress as indicated by apparent temperature (ΔAT2max = 1.7 °C). The modifications by GRs scale almost linearly with the fraction of the surface they cover. Investigation of the surface-atmosphere interactions indicate that GRs with plentiful soil moisture dissipate more of the surface energy as latent heat flux and subsequently inhibit the development of the daytime planetary boundary layer (PBL). This causes the atmospheric heating through entrainment at the PBL top to be decreased. Additionally, urban GRs modify regional circulation regimes leading to decreased advective heating under HW

Initial results from Phase 2 of the international urban energy balance model comparison

Urban land surface schemes have been developed to model the distinct features of the urban surface and the associated energy exchange processes. These models have been developed for a range of purposes and make different assumptions related to the inclusion and representation of the relevant processes. Here, the first results of Phase 2 from an international comparison project to evaluate 32 urban land surface schemes are presented. This is the first large-scale systematic evaluation of these models. In four stages, participants were given increasingly detailed information about an urban site for which urban fluxes were directly observed. At each stage, each group returned their models' calculated surface energy balance fluxes. Wide variations are evident in the performance of the models for individual fluxes. No individual model performs best for all fluxes. Providing additional information about the surface generally results in better performance. However, there is clear evidence that poor choice of parameter values can cause a large drop in performance for models that otherwise perform well. As many models do not perform well across all fluxes, there is need for caution in their application, and users should be aware of the implications for applications and decision making

Introducing standardized field methods for fracture-focused surface process research

Rock fractures are a key contributor to a broad array of Earth surface processes due to their direct control on rock strength as well as rock porosity and permeability. However, to date, there has been no standardization for the quantification of rock fractures in surface process research. In this work, the case is made for standardization within fracture-focused research, and prior work is reviewed to identify various key datasets and methodologies. Then, a suite of standardized methods is presented as a starting “baseline” for fracture-based research in surface process studies. These methods have been shown in pre-existing work from structural geology, geotechnical engineering, and surface process disciplines to comprise best practices for the characterization of fractures in clasts and outcrops. This practical, accessible, and detailed guide can be readily employed across all fracture-focused weathering and geomorphology applications. The wide adoption of a baseline of data collected using the same methods will enable comparison and compilation of datasets among studies globally and will ultimately lead to a better understanding of the links and feedbacks between rock fracture and landscape evolution.</p

U.K. climate projections: Summer daytime and nighttime urban heat island changes in England’s major cities

In the United Kingdom, where 90% of residents are projected to live in urban areas by 2050, projecting changes in urban heat islands (UHIs) is essential to municipal adaptation. Increased summer temperatures are linked to increased mortality. Using the new regional U.K. Climate Projections, UKCP18-regional, we estimate the 1981–2079 trends in summer urban and rural near-surface air temperatures and in UHI intensities during day and at night in the 10 most populous built-up areas in England. Summer temperatures increase by 0.45°–0.81°C per decade under RCP8.5, depending on the time of day and location. Nighttime temperatures increase more in urban than rural areas, enhancing the nighttime UHI by 0.01°–0.05°C per decade in all cities. When these upward UHI signals emerge from 2008–18 variability, positive summer nighttime UHI intensities of up to 1.8°C are projected in most cities. However, we can prevent most of these upward nighttime UHI signals from emerging by stabilizing climate to the Paris Agreement target of 2°C above preindustrial levels. In contrast, daytime UHI intensities decrease in nine cities, at rates between −0.004° and −0.05°C per decade, indicating a trend toward a reduced daytime UHI effect. These changes reflect different feedbacks over urban and rural areas and are specific to UKCP18-regional. Future research is important to better understand the drivers of these UHI intensity changes