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Taylor's Frozen Turbulence Hypothesis (TH) is a critical assumption in turbulent theory and practice which allows time series of point measurements of turbulent variables to be translated to the spatial domain via the mean wind. Using a 3D array of fibre-optic distributed temperature sensing in the atmospheric surface layer over an idealized desert site we present a systematic investigation of the applicability of Taylor's Hypothesis to atmospheric surface layer flows over a variety of conditions: unstable, near-neutral, and stable atmospheric stabilities; and multiple measurement heights between the surface and 3 m above ground level. Both spatially integrated and spatially scale-dependent eddy velocities are investigated by means of time-lagged streamwise two-point correlations and compared to the mean Eulerian wind. We find that eddies travel slower than predicted by TH at small spatial separations, as predicted by TH at separations typically between 5 and 16 m, and faster than predicted by TH at larger spatial separations. In unstable atmospheric conditions the spatial separation at which eddy velocity is larger than Eulerian velocity decreases with height. [ABSTRACT FROM AUTHOR]

Climate models predict meteorological variables for outdoor spaces. Nevertheless, most people work indoors and are affected by heat indoors. We present an approach to transfer climate projections from outdoors to climate projections of indoor air temperature (Ti) and thermal comfort based on a combination of indoor sensors, artificial neural networks (ANNs), and 22 regional climate projections. Human thermal comfort and Ti measured by indoor sensors at 90 different workplaces in the Upper Rhine Valley were used as training data for ANN models predicting indoor conditions as a function of outdoor weather. Workplace-specific climate projections were modeled for the time period 2070–2099 and compared to the historical period 1970–1999 using the same ANNs, but ERA5-Land reanalysis data as input. It is shown that heat stress indoors will increase in intensity, frequency, and duration at almost all investigated workplaces. The rate of increase depends on building and room properties, the workplace purpose, and the representative concentration pathway (RCP2.6, RCP4.5, or RCP8.5). The projected increase of the mean air temperature in the summer (JJA) outdoors, by + 1.6 to + 5.1 K for the different RCPs, is higher than the increase in Ti at all 90 workplaces, which experience on average an increase of + 0.8 to + 2.5 K. The overall frequency of heat stress is higher at most workplaces than outdoors for the historical and the future period. The projected hours of indoor heat stress will increase on average by + 379 h, + 654 h, and + 1209 h under RCP2.6, RCP4.5, and RCP8.5, respectively. [ABSTRACT FROM AUTHOR]

Climate models predict meteorological variables for outdoor spaces. Nevertheless, most people work indoors and are affected by heat indoors. We present an approach to transfer climate projections from outdoors to climate projections of indoor air temperature (Ti) and thermal comfort based on a combination of indoor sensors, artificial neural networks (ANNs), and 22 regional climate projections. Human thermal comfort and Ti measured by indoor sensors at 90 different workplaces in the Upper Rhine Valley were used as training data for ANN models predicting indoor conditions as a function of outdoor weather. Workplace-specific climate projections were modeled for the time period 2070–2099 and compared to the historical period 1970–1999 using the same ANNs, but ERA5-Land reanalysis data as input. It is shown that heat stress indoors will increase in intensity, frequency, and duration at almost all investigated workplaces. The rate of increase depends on building and room properties, the workplace purpose, and the representative concentration pathway (RCP2.6, RCP4.5, or RCP8.5). The projected increase of the mean air temperature in the summer (JJA) outdoors, by + 1.6 to + 5.1 K for the different RCPs, is higher than the increase in Ti at all 90 workplaces, which experience on average an increase of + 0.8 to + 2.5 K. The overall frequency of heat stress is higher at most workplaces than outdoors for the historical and the future period. The projected hours of indoor heat stress will increase on average by + 379 h, + 654 h, and + 1209 h under RCP2.6, RCP4.5, and RCP8.5, respectively. [ABSTRACT FROM AUTHOR]

A method for directly measuring carbon dioxide (CO2) emissions using a mobile sensor network in cities at fine spatial resolution was developed and tested. First, a compact, mobile system was built using an infrared gas analyzer combined with open-source hardware to control, georeference, and log measurements of CO2 mixing ratios on vehicles (car, bicycles). Second, two measurement campaigns, one in summer and one in winter (heating season) were carried out. Five mobile sensors were deployed within a 1 x 12:7 km transect across the city of Vancouver, BC, Canada. The sensors were operated for 3.5 h on pre-defined routes to map CO2 mixing ratios at street level, which were then averaged to 100 x 100m grid cells. The averaged CO2 mixing ratios of all grids in the study area were 417.9 ppm in summer and 442.5 ppm in winter. In both campaigns, mixing ratios were highest in the grid cells of the downtown core and along arterial roads and lowest in parks and well vegetated residential areas. Third, an aerodynamic resistance approach to calculating emissions was used to derive CO2 emissions from the gridded CO2 mixing ratio measurements in conjunction with mixing ratios and fluxes collected from a 28m tall eddycovariance tower located within the study area. These measured emissions showed a range of -12 to 226CO2 h-1 h-1 in summer and of -14 to 163 kgCO2 h-1 h-1 in winter, with an average of 35.1 kgCO2 h-1 h-1 (summer) and 25.9 kgCO2 h-1 h-1 (winter). Fourth, an independent emissions inventory was developed for the study area using buildings energy simulations from a previous study and routinely available traffic counts. The emissions inventory for the same area averaged to 22.06 kgCO2 h-1 h-1 (summer) and 28.76 kgCO2 h-1 h-1 (winter) and was used to compare against the measured emissions from the mobile sensor network. The comparison on a grid-by-grid basis showed linearity between CO2 mixing ratios and the emissions inventory (R² = 0:53 in summer and R² = 0:47 in winter). Also, 87% (summer) and 94% (winter) of measured grid cells show a difference within ±1 order of magnitude, and 49% (summer) and 69% (winter) show an error of less than a factor 2. Although associated with considerable errors at the individual grid cell level, the study demonstrates a promising method of using a network of mobile sensors and an aerodynamic resistance approach to rapidly map greenhouse gases at high spatial resolution across cities. The method could be improved by longer measurements and a refined calculation of the aerodynamic resistance. [ABSTRACT FROM AUTHOR]

A method for directly measuring carbon dioxide (CO2) emissions using a mobile sensor network in cities at fine spatial resolution was developed and tested. First, a compact, mobile system was built using an infrared gas analyzer combined with open-source hardware to control, georeference and log measurements of CO2 mixing ratios on vehicles (car, bikes). Second, two measurement campaigns, one in summer and one in winter (heating-season) were carried out. Five mobile sensors were deployed within a 1 x 12.7 km transect across the City of Vancouver, BC, Canada. The sensors were operated for 3.5 hours on pre-defined routes to map CO2 mixing ratios at street level, which was then averaged to 100 x 100 m grids. The grid-averaged CO2 mixing ratios were 417.9 ppm in summer and 442.5 ppm in winter. In both campaigns, mixing ratios were highest in the downtown core and along arterial roads and lowest in parks and well vegetated residential areas. Third, an aerodynamic resistance approach to calculating emissions was used to derive CO2 emissions from the gridded CO2 mixing ratio measurements in conjunction with mixing ratios and fluxes collected from a 28-m tall eddy-covariance tower located within the study area. These measured emissions showed a range of -12 to 226 kg CO2 ha-1 hr-1 in summer and of -14 to 163 kg CO2 ha-1 hr-1 in winter, with an average of 35.1 kg CO2 ha-1 hr-1 (summer) and 25.9 kg CO2 ha-1 hr-1 (winter). Fourth, an independent emissions inventory was developed for the study area using buildings energy simulations from a previous study and routinely available traffic counts. The emissions inventory for the same area averaged to 22.06 kg CO2 ha-1 hr-1 (summer) and 28.76 kg CO2 ha-1 hr-1 (winter) and was used to compare against the measured emissions from the mobile sensor network. The comparison on a grid-by-grid basis showed linearity between CO2 mixing ratios and the emissions inventory (R2 = 0.53 in summer and R2 = 0.47 in winter). 87 % (summer) and 94 % (winter) of measured grid cells show a difference within ±1 order, and 49 % (summer) and 69 % (winter) show an error of less than a factor 2. Although associated with considerable errors at the individual grid cell level, the study demonstrates a promising method of using a network of mobile sensors and an aerodynamic resistance approach to rapidly map greenhouse gases at high spatial resolution across cities. The method could be improved by longer measurements and a refined calculation of the aerodynamic resistance. [ABSTRACT FROM AUTHOR]

The MoBiMet (Mobile Biometeorology System) is a low-cost device for thermal comfort monitoring, designed for long-term deployment in indoor or semi-outdoor occupational contexts. It measures air temperature, humidity, globe temperature, brightness temperature, light intensity, and wind, and is capable of calculating thermal indices (e.g., physiologically equivalent temperature (PET)) on site. It visualizes its data on an integrated display and sends them continuously to a server, where web-based visualizations are available in real-time. Data from many MoBiMets deployed in real occupational settings were used to demonstrate their suitability for large-scale and continued monitoring of thermal comfort in various contexts (industrial, commercial, offices, agricultural). This article describes the design and the performance of the MoBiMet. Alternative methods to determine mean radiant temperature (Tmrt) using a light intensity sensor and a contactless infrared thermopile were tested next to a custom-made black globe thermometer. Performance was assessed by comparing the MoBiMet to an independent mid-cost thermal comfort sensor. It was demonstrated that networked MoBiMets can detect differences of thermal comfort at different workplaces within the same building, and between workplaces in different companies in the same city. The MoBiMets can capture spatial and temporal differences of thermal comfort over the diurnal cycle, as demonstrated in offices with different stories and with different solar irradiances in a single high-rise building. The strongest sustained heat stress was recorded at industrial workplaces with heavy machinery. [ABSTRACT FROM AUTHOR]

This study presents an attempt to resolve fluctuations in surface temperatures at scales of a few seconds to several minutes using time-sequential thermography (TST) from a ground-based platform. A scheme is presented to decompose a TST dataset into fluctuating, high-frequency, and long-term mean parts. To demonstrate the scheme's application, a set of four TST runs (day/night, leaves-on/leaves-off) recorded from a 125-m-high platform above a complex urban environment in Berlin, Germany is used. Fluctuations in surface temperatures of different urban facets are measured and related to surface properties (material and form) and possible error sources. A number of relationships were found: (1) Surfaces with surface temperatures that were significantly different from air temperature experienced the highest fluctuations. (2) With increasing surface temperature above (below) air temperature, surface temperature fluctuations experienced a stronger negative (positive) skewness. (3) Surface materials with lower thermal admittance (lawns, leaves) showed higher fluctuations than surfaces with high thermal admittance (walls, roads). (4) Surface temperatures of emerged leaves fluctuate more compared to trees in a leaves-off situation. (5) In many cases, observed fluctuations were coherent across several neighboring pixels. The evidence from (1) to (5) suggests that atmospheric turbulence is a significant contributor to fluctuations. The study underlines the potential of using high-frequency thermal remote sensing in energy balance and turbulence studies at complex land-atmosphere interfaces. [ABSTRACT FROM AUTHOR]

Full-scale observations from two urban sites in Basel, Switzerland were analysed to identify the magnitude of different processes that create, relocate, and dissipate turbulent kinetic energy (TKE) in the urban atmosphere. Two towers equipped with a profile of six ultrasonic anemometers each sampled the flow in the urban roughness sublayer, i.e. from street canyon base up to roughly 2.5 times the mean building height. This observational study suggests a conceptual division of the urban roughness sublayer into three layers: (1) the layer above the highest roofs, where local buoyancy production and local shear production of TKE are counterbalanced by local viscous dissipation rate and scaled turbulence statistics are close to to surface-layer values; (2) the layer around mean building height with a distinct inflexional mean wind profile, a strong shear and wake production of TKE, a more efficient turbulent exchange of momentum, and a notable export of TKE by transport processes; (3) the lower street canyon with imported TKE by transport processes and negligible local production. Averaged integral velocity variances vary significantly with height in the urban roughness sublayer and reflect the driving processes that create or relocate TKE at a particular height. The observed profiles of the terms of the TKE budget and the velocity variances show many similarities to observations within and above vegetation canopies. [ABSTRACT FROM AUTHOR]

The article offers information about a study which aims to determine the importance of coherent structures in turbulent transfer. It is stated that data measured within, and above an urban street canyon has been used to analyze the significance of coherent structures in turbulent transfer. On the other hand, a quadrant analysis indicates that turbulent momentum and sensible heat fluxes are strongly sweep-dominated in large parts of the street canyon and close to the roofs. Detailed information regarding the methods and analysis used in the study is discussed, as well as the results.

• A flux variance similarity partitioning method was developed as a gap-filling model. • Results were compared with three established gap-filling models. • Gap-filled 18-year mean NEP values were similar among the four models. • There were large differences in annual photosynthesis and respiration values among the four models. • Accounting for light inhibition of daytime respiration in ecosystem models is critical. We propose a gap-filling model for carbon dioxide fluxes measured by eddy covariance (EC) that combines the flux variance similarity (FVS) partitioning approach with the artificial neural network (ANN) technique (FVS–ANN). 18 years of EC-measured net ecosystem production (NEP) of a Douglas-fir (Pseudotsuga menziesii) stand in British Columbia, Canada were used. FVS-partitioned fluxes were used as a training dataset for ANNs based on the environmental variables to model missing respiration and photosynthesis values. Results from the FVS–ANN model were compared with three established models using different partitioning and gap-filling approaches, namely the nighttime relationship, the daytime intercept, and an ANN-based model informed by the nighttime relationship (ANN–nighttime). In the gap-filled long-term NEP record, the 18-year mean NEP values were similar (between 225 and 239 gC m−2 year−1) and individual years showed small differences in annual NEP among the four models, demonstrating the reliability of estimated NEP when any of the models were used for gap-filling. However, the largest differences in annual gap-filled photosynthesis and respiration estimates among the four models in a given year were as large as 813 and 835 gC m−2 year−1, respectively. The FVS–ANN model consistently resulted in the smallest annual photosynthesis and respiration estimates, while the nighttime-based models resulted in the highest photosynthesis and respiration. The differences between the FVS–ANN and any of the other three models are explained by the different definitions of partitioned fluxes (i.e., values from the FVS–ANN are smaller than the other three models by leaf respiration). However, the differences may also be partly due to light inhibition of daytime respiration, which is known as the Kok effect that is believed to be adequately considered in the new FVS–ANN combination and partially in the daytime intercept model, but not in the other two models. The results suggest that previous EC-based estimates of global photosynthesis and respiration obtained by using nighttime relationships are potentially biased high. [ABSTRACT FROM AUTHOR]

To adapt forest ecosystems and forest management to climate change, it is essential to know which forest regions and which tree species are resilient to climate variability and which ones are possibly affected most by past and anticipated future changes. In this contribution, for the main forest regions of Türkiye and six tree species, recent climate variability and trends were quantified and statistically correlated to record tree defoliation and vitality. Climate variables considered are maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean), and total precipitation (Prcp), which are compared to forest health responses recorded as part of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) on 277 plots across forests along the Black Sea and Mediterranean regions. In addition, long-term data on satellite measurements of the normalized difference vegetation index (NDVI) were extracted for the same 277 plots for the period 2008–2020. Firstly, 30 years (1991–2020) of reanalysis of climate variables from ECMWF were extracted for all plots; secondly, individual correlations and cross-correlations of climate variables and tree health and vitality were computed for the period 2008–2020 (significance level of 95%) for the four most dominant species from the Black Sea forests (F. orientalis, Q. cerris, P. sylvestris, P. orientalis) and two species from Mediterranean forests (P. brutia and C. libani). Temperature showed a stronger effect on most species than precipitation. Finally, time-lagged correlations were analyzed for seven-time lags (significance level of 95%) to evaluate legacy effect. The analysis revealed that different tree species from the two regions show different responses to climate variables. Species in the Mediterranean region are more resistant to droughts and climatic variations. Legacy effects of defoliation and NDVI have lasted for at least 2 years. [ABSTRACT FROM AUTHOR]

• Stable c isotopes used to partition NEE into photosynthesis and respiration. • Light-inhibition effect on daily ecosystem respiration was 35%. • Average light-inhibition effect on daytime ecosystem respiration was 56%. • Nighttime relationship partitioning overestimated gross primary production by 23%. • Daytime intercept partitioning method partly accounted for light inhibition effects. Partitioning measured net ecosystem exchange of CO 2 (NEE) into ecosystem respiration (R e) and gross primary production (GPP) is essential for understanding the biophysical controls on forest ecosystem carbon (C) dynamics. Obtaining R e and GPP accurately from NEE remains a challenge. In this study, we measured stable CO 2 isotopologue signatures at ecosystem scale simultaneously with eddy-covariance measurements of NEE above a Douglas-fir stand on Vancouver Island, Canada. This allowed us to analyze three partitioning methods (the traditional nighttime relationship, daytime intercept, and stable C isotope methods). In all three methods, nighttime R e values were obtained from nighttime EC-measured NEE values. Over a 29-day summertime period, daily (24-h) R e and GPP obtained using the daytime intercept method were 11±4% and 6 ± 5%, respectively, lower than those estimated using the nighttime relationship method. Stable-C-isotope-partitioned daily R e and GPP were 35±13% and 19±10%, respectively, lower than when using the nighttime relationship method to obtain daytime R e. That mean daytime R e obtained using the stable C isotope method was 56% less than that estimated using the nighttime relationship method suggests that light inhibition of foliage respiration (i.e., the Kok effect) had a major effect on daytime R e in this Douglas-fir stand. The mean daytime R e obtained using the stable C isotope method was 49% lower than the value estimated using the daytime intercept method, which indicates that the daytime intercept method accounted only for a small proportion of the light inhibition effect during the most active period of the growing season. [ABSTRACT FROM AUTHOR]

As the frequency and intensity of heatwaves will continue to increase in the future, accurate and high-resolution mapping and forecasting of human outdoor thermal comfort in urban environments are of great importance. This study presents a machine-learning-based outdoor thermal comfort model with a good trade-off between computational cost, complexity, and accuracy compared to common numerical urban climate models. The machine learning approach is basically an emulation of different numerical urban climate models. The final model consists of four submodels that predict air temperature, relative humidity, wind speed, and mean radiant temperature based on meteorological forcing and geospatial data on building forms, land cover, and vegetation. These variables are then combined into a thermal index (universal thermal climate index – UTCI). All four submodel predictions and the final model output are evaluated using street-level measurements from a dense urban sensor network in Freiburg, Germany. The final model has a mean absolute error of 2.3 K. Based on a city-wide simulation for Freiburg, we demonstrate that the model is fast and versatile enough to simulate multiple years at hourly time steps to predict street-level UTCI at 1 m spatial resolution for an entire city. Simulations indicate that neighbourhood-averaged thermal comfort conditions vary widely between neighbourhoods, even if they are attributed to the same local climate zones, for example, due to differences in age and degree of urban vegetation. Simulations also show contrasting differences in the location of hotspots during the day and at night. [ABSTRACT FROM AUTHOR]

High-frequency measurements are available at five heights within and above a row-gap trellised vineyard located on a 7 ∘ slope in the Southern Okanagan Valley, British Columbia, Canada. During a 3-week campaign in July 2016, approximately 17% of the nocturnal conditions exhibit drainage flow along the local slope. Drainage conditions are characterized by temperature inversions beginning around z / h c = 0.39 , where z is the height above ground level (a.g.l.) and h c is the canopy height (2.3 m a.g.l.), and near-surface lapses. Changes in the sign of the streamwise momentum flux suggest the presence of a jet maximum around z / h c = 1.65 , while a weak inflection point is observed near the canopy top, suggesting dynamical influences from both the drainage layer and canopy layer on the turbulent flow field. The largest observed fluxes in both the streamwise momentum flux and the turbulent sensible heat flux are near the top of the canopy, consistent with the location of the inflection point. Calculated two-point length scales from along-slope distributed temperature measurements reveal that turbulent structures are smallest near the canopy top. Conditional sampling of the three-dimensional velocity components and temperature indicate that a large fraction of canopy-layer transport is driven by canopy top turbulence, with sweeps dominating over ejections, particularly at z / h c = 0.65 . [ABSTRACT FROM AUTHOR]

As the frequency and intensity of heat waves will continue to increase in the future, accurate and high-resolution mapping and forecasting of human outdoor thermal comfort in urban environments is of great importance. This study presents a machine learning based outdoor thermal comfort model with a good trade-off between computational cost, complexity, and accuracy compared to common numerical urban climate models. The machine learning approach is basically an emulation of different numerical urban climate models. The final model consists of four sub-models that predict air temperature, relative humidity, wind speed, and mean radiant temperature based on meteorological forcing and geospatial data on building form, land cover, and vegetation. These variables are then combined into a thermal index (Universal Thermal Climate Index - UTCI). All four sub-model predictions and the final model output are evaluated using street-level measurements from a dense urban sensor network in Freiburg, Germany. The final model has a mean absolute error of 2.3 K. Based on a city-wide simulation for the city of Freiburg we demonstrate that the model is fast and versatile enough to simulate multiple years at hourly timesteps to predict street-level UTCI at 1 m spatial resolution for an entire city. Simulations indicate that neighborhood-averaged thermal comfort conditions vary widely between neighborhoods, even if they are attributed to the same local climate zones, e.g. due to differences in age and degree of urban vegetation. Simulations also show contrasting differences in the location of hot spots during the day and at night. [ABSTRACT FROM AUTHOR]

Traditional methods for remote sensing of urban surface temperatures (Tsurf) are subject to a suite of temporal and geometric biases. The effect of these biases on our ability to characterize the true geometric and temporal nature of urban Tsurf is currently unknown, but is certainly nontrivial. To quantify and overcome these biases, we present a method to retrieve time-continuous hemispherical radiometric urban Tsurf (Them,r) from broadband upwelling longwave radiation measured via pyrgeometer. By sampling the surface hemispherically, this measure is postulated to be more representative of the complex, three-dimensional structure of the urban surface than those from traditional remote sensors that usually have a narrow nadir or oblique viewing angle. The method uses a sensor view model in conjunction with a radiative transfer code to correct for atmospheric effects in three-dimensions using in situ profiles of air temperature and humidity along with information about surface structure. A practical parameterization is also included. Using the method, an eight-month climatology of Them,r is retrieved for Basel, Switzerland. Results show the importance of a robust, geometrically representative atmospheric correction routine to remove confounding atmospheric effects and to foster inter-site, inter-method, and inter-instrument comparison. In addition, over a month-long summertime intensive observation period, Them,r was compared to Tsurf retrieved from nadir (Tplan) and complete (Tcomp) perspectives of the surface. Large differences were observed between Tcomp, Them,r, and Tplan, with differences between Tplan and Tcomp of up to 8 K under clear-sky viewing conditions, which are the cases when satellite-based observations are available. In general, Them,r provides a better approximation to Tcomp than Tplan, particularly under clear-sky conditions. The magnitude of differences in remote sensed Tsurf based on sensor-surface-sun geometry varies significantly based on time of day and synoptic conditions and prompts further investigation of methodological and instrument bias in remote sensed urban surface temperature records. [ABSTRACT FROM AUTHOR]

A total of 20 urban neighbourhood-scale eddy covariance flux tower datasets are made openly available after being harmonized to create a 50 site–year collection with broad diversity in climate and urban surface characteristics. Variables needed as inputs for land surface models (incoming radiation, temperature, humidity, air pressure, wind and precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to equilibrate models with local climate conditions. For both gap filling and spin up, ERA5 reanalysis meteorological data are bias corrected using tower-based observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015). Other variables (turbulent and upwelling radiation fluxes) are harmonized and quality controlled without gap filling. Site description metadata include local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. This open collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. These data can be accessed from https://doi.org/10.5281/zenodo.7104984 (Lipson et al., 2022). [ABSTRACT FROM AUTHOR]

Twenty urban neighbourhood-scale eddy covariance flux tower datasets have been harmonized and quality controlled, producing a 50 site-year collection with broad diversity in climate and urban surface characteristics. Observations are gap-filled and prepended with 10 years of reanalysis-derived local data to enable use as spin up and forcing for land surface model evaluation. For both gap filling and spin-up, ERA5 reanalysis meteorological data are bias corrected using tower observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015 linear regression). Site description metadata includes local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. Together, this collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. [ABSTRACT FROM AUTHOR]

The Namib Turbulence Experiment (NamTEX) was a multinational micrometeorological campaign conducted in the central Namib Desert to investigate three-dimensional surface layer turbulence and the spatiotemporal patterns of heat transfer between the subsurface, surface, and atmosphere. The Namib provides an ideal location for fundamental research that revisits some key assumptions in micrometeorology that are implicitly included in the parameterizations describing energy exchange in weather forecasting and climate models: homogenous flat surfaces, no vegetation, little moisture, and cloud-free skies create a strong and consistent diurnal forcing, resulting in a wide range of atmospheric stabilities. A novel combination of instruments was used to simultaneously measure variables and processes relevant to heat transfer: a 3-km fiber-optic distributed temperature sensor (DTS) was suspended in a pseudo-three-dimensional array within a 300 m × 300 m domain to provide vertical cross sections of air temperature fluctuations. Aerial and ground-based thermal imagers recorded high-resolution surface temperature fluctuations within the domain and revealed the spatial thermal imprint of atmospheric structures responsible for heat exchange. High-resolution soil temperature and moisture profiles together with heat flux plates provided information on near-surface soil dynamics. Turbulent heat exchange was measured with a vertical array of five eddy-covariance point measurements on a 21-m mast, as well as by collocated small- and large-aperture scintillometers. This contribution first details the scientific goals and experimental setup of the NamTEX campaign. Then, using a typical day, we demonstrate (i) the coupling of surface layer, surface, and soil temperatures using high-frequency temperature measurements, (ii) differences in spatial and temporal standard deviations of the horizontal temperature field using spatially distributed measurements, and (iii) horizontal anisotropy of the turbulent temperature field. [ABSTRACT FROM AUTHOR]

Urban surface albedo is an essential biophysical variable in the surface energy balance across all scales, from micro-scale (materials) to the globe, changing with land covers and three-dimensional structures over urban areas. Urban albedos are dynamic over space and time but have not yet been quantified over global scales due to the lack of high-resolution albedo datasets. Here, we combined the direct estimation approach and Landsat surface reflectance product to generate a 30-m-resolution annual surface albedo dataset for 3037 large cities (area > 50 km2) worldwide for the period from 1986 to 2020, allowing spatial patterns and long-term temporal trends to be explored with possible causal drivers, and quantification of the surface radiative forcing from these albedo changes. Evaluation of this new albedo dataset using global urban flux tower-based measurements demonstrates its high accuracy with an overall bias and root-mean-square-error (RMSE) of 0.005 and 0.025, respectively. Analysis of the dataset reveals an overall decreasing trend of albedo during the 35-year evaluation period (1986–2020), which is robust accounting for uncertainties from training sample representativeness, Landsat data uncertainty, seasonal variation, and snow-cover contamination. Our results reveal that urban greening (measured by the positive Normalized Difference Vegetation Index (NDVI) trend) can well explain the total variances in the albedo trend for the 35-year period through two different pathways of tree planting and urban warming-enhanced vegetation growth. The decrease in urban albedo caused a warming effect indicated by positive surface radiative forcing, with a global city-level average surface radiative forcing of 2.76 W·m−2. These findings enhance our understanding of urbanization's impacts on albedo-related biophysical processes and can provide information to quantify urban surface radiation energy and design effective mitigation strategies to reduce urban warming. • High-resolution surface albedo dataset is generated from Landsat for 3037 global major cities. • Most cities have a decreasing albedo trend during the past three decades. • Urban greening explains decreasing albedo trend through two different ways. • Decreased urban albedo incudes a positive surface radiative forcing. [ABSTRACT FROM AUTHOR]

Abstract: The complexity of built form and land cover has often limited detailed model estimates of solar irradiance in the urban canopy. These limitations arise largely from difficulties in generating contiguous detailed spatial representations of solar obstructing features such as buildings and trees. This study presents a method that integrates remotely sensed datasets across spatial scales for estimating irradiance in urban areas. The method draws largely on airborne Light Detection and Ranging (LiDAR) technology with specific focus on estimating radiation transmission through urban vegetation. The incoming irradiance above the urban canopy is determined using atmospheric transmission derived from geostationary satellite imagery to provide a long-term record of seasonal fluctuations in cloud cover, and the associated direct and diffuse irradiance. Individual model components are analyzed for three urban study areas to assess the interactions between input model parameters and patterns of different urban form. Results indicate that representations of trees as opaque objects substantially underestimate solar irradiance across urban form types, demonstrating up to a 18% underestimate of direct irradiance in treed residential areas. Both atmospheric transmittance and urban form are also shown to be critical model parameters, and are discussed with reference to unique considerations for generating estimates of urban irradiance. [Copyright &y& Elsevier]

Abstract: Suburban areas continue to grow rapidly and are potentially an important land-use category for anthropogenic carbon-dioxide (CO2) emissions. Here eddy covariance techniques are used to obtain ecosystem-scale measurements of CO2 fluxes (F C) from a suburban area of Baltimore, Maryland, USA (2002–2006). These are among the first multi-year measurements of F C in a suburban area. The study area is characterized by low population density (1500inhabitants km−2) and abundant vegetation (67.4% vegetation land-cover). F C is correlated with photosynthetic active radiation (PAR), soil temperature, and wind direction. Missing hourly F C is gap-filled using empirical relations between F C, PAR, and soil temperature. Diurnal patterns show net CO2 emissions to the atmosphere during winter and net CO2 uptake by the surface during summer daytime hours (summer daily total is −1.25gCm−2 d−1). Despite the large amount of vegetation the suburban area is a net CO2 source of 361gCm−2 y−1 on average. [ABSTRACT FROM AUTHOR]

To quantify the ecosystem services of trees in urban environments, it is necessary to assess received direct solar radiation of each tree. While the Sky View Factor (SVF) is suitable for assessing the total incoming short- and longwave radiation fluxes, its information is limited to specific points in space. For a spatial analysis, it is necessary to sample the area for SVF. A new geometrical method, Area View Factor (AVF), for the calculation of sunlit areas is proposed. AVF is the ratio of the unhidden, projected surface of an object to the whole projected surface of an object in a complex environment. Hereby, a virtual, orthographic camera is oriented in accordance to the sun's position in the 3D model domain. The method is implemented in the microscale model SkyHelios, utilizing efficient rendering techniques to assess AVF of all urban trees in parallel. The method was applied to Rieselfeld in Freiburg, Germany. The assessed sunlit area is compared to the SVF at the top of each tree and solar altitude angle, revealing a strong relationship between sunlit areas to solar altitude angles. This study shows that AVF is an efficient methodology to assess received direct radiation of urban trees. Based on AVF, it is possible to identify urban areas with shaded and sunlit trees, but it can also be applied to other objects in complex environments. Therefore, AVF is applicable for urban architecture or energetic research questions. [ABSTRACT FROM AUTHOR]

• On average, the bog site was near carbon neutral 8–13 years after rewetting. • The site alternated between being an annual C sink and source over the years. • Climatic variability and functional change drive interannual variability in c fluxes. • Excluding CH 4 would result in an overestimation of the net C sink. Peatland rewetting, a management effort to restore water levels in previously drained peatlands, is important for re-establishing the role of these peatlands as carbon (C) sinks. Since rewetted peatlands have a highly variable response to interannual variations in climatic conditions and functional changes, long term studies of C fluxes in these ecosystems are needed. Here, we evaluated the impact of climate variability and functional change on the interannual variability of CO 2 and CH 4 fluxes at Burns Bog, a rewetted temperate bog on the Pacific Coast in Canada, based on five years of eddy covariance measurements. We found that the site alternated between being an annual-scale net CO 2 sink or source, ranging from -32.6 ± 21.5 (±95% CI) to 11.9 ± 15.1 g CO 2 C m-2 yr-1, respectively, while consistently being a CH 4 source, ranging from 11.6 ± 0.7 to 18.0 ± 1.6 g CH 4 C m-2 yr-1. Over the five-year period, mean annual CH 4 emissions (13.7 ± 2.5 g CH 4 C m-2 yr-1; ±SD across years) entirely offset the CO 2 sink (-12.3 ± 20.4 g CO 2 C m-2 yr-1), resulting in the site being near-carbon neutral over this period (1.3 ± 23.9 g C m-2 yr-1). This finding indicates that excluding CH 4 fluxes from the net C balance results in an overestimation of the net C uptake at this site. Annual CO 2 emissions from the bog were greatest in the year with a dry and warm summer, emphasizing the importance of temperature and water table depth at the bog. Regardless of the greenhouse gas (GHG) metrics (i.e., global warming potential or sustained global warming potential) used in calculating the annual CO 2 -eq balance, the site consistently had a positive GHG balance across the study period. Despite mainly acting as a GHG source, the rewetted site will likely have a cooling effect on the climate system over long timescales compared to drained bogs that are large CO 2 sources. [ABSTRACT FROM AUTHOR]

Tower-based measurements from within and above the urban canopy in two cities are used to evaluate several existing approaches that parametrize the vertical profiles of wind speed and temperature within the urban roughness sublayer (RSL). It is shown that current use of Monin–Obukhov similarity theory (MOST) in numerical weather prediction models can be improved upon by using RSL corrections when modelling the vertical profiles of wind speed and friction velocity in the urban RSL using MOST. Using anisotropic building morphological information improves the agreement between observed and parametrized profiles of wind speed and momentum fluxes for selected methods. The largest improvement is found when using dynamically-varying aerodynamic roughness length and displacement height. Adding a RSL correction to MOST, however, does not improve the parametrization of the vertical profiles of temperature and heat fluxes. This is expected since sources and sinks of heat are assumed uniformly distributed through a simple flux boundary condition in all RSL formulations, yet are highly patchy and anisotropic in a real urban context. Our results can be used to inform the choice of surface-layer representations for air quality, dispersion, and numerical weather prediction applications in the urban environment. [ABSTRACT FROM AUTHOR]

This work explores the feasibility of real-time large-eddy simulations of flow over urban canopies at the neighborhood scale. The cumulant lattice Boltzmann method is employed using a single General Purpose Graphic Processing Unit (GPGPU). In order to demonstrate the validity and efficiency of this approach we simulate wind flow in a neighborhood of Basel. Simulation results are validated against measurements from the Basel Urban Boundary Layer Experiment (BUBBLE) and are compared to previous CFD simulations. Turbulence statistics are found to be in agreement with corresponding tower measurements according to several validation metrics. While quantitative comparisons are limited to the six measurement locations of the field measurements, the available data supports the conjecture that real-time simulation of urban air flow is feasible at the neighborhood scale with the proposed numerical technique. • LES of urban air flow of a neighborhood of Basel, Switzerland. • Simulation results are validated against tower measurements. • First application of cumulant LBM with quartic parametrization to real world problem. • It is shown, that LBM on GPGPUs can offer real-time simulations for urban air flows. [ABSTRACT FROM AUTHOR]

Insect outbreaks can significantly influence carbon (C) and water balances of forests. Forest tent caterpillars (FTC) ( Malacosoma disstria Hübner) are one of the most prominent insects found in aspen forests in Canada and have the potential to considerably influence regional C and water fluxes. In the summer of 2016, an FTC infestation occurred in a ca. 100 -year-old trembling aspen ( Populus tremuloides ) stand in the southern boreal forest where the longterm research site known as Old Aspen (OA) is located. The infestation led to nearly complete defoliation of the canopy during the leafing out period when photosynthesis, and thus C uptake, is progressing towards maximum levels. We used 21 years of eddy-covariance (EC) and climate measurements covering pre-infestation and infestation periods to estimate the impact of the FTC infestation on net ecosystem production (NEP), gross ecosystem production (GEP) and evapotranspiration (E). Defoliation in 2016 reduced annual NEP to −130 g C m −2  y −1 and GEP to 798 g C m −2  y −1 , respectively, which were much less than their 20-year means (NEP = 118 ± 53 g C m −2  y −1 , GEP = 1057 ± 74 g C m −2  y −1 ), and resulted in the most negative annual NEP value of the 21 years of measurements at the OA site. NEP for 2016 was even lower than values observed during three drought years (2001–2003). However, FTC infestation caused little effect on annual E. FTC infestation reduced the near-surface remotely-measured greenness index, green chromatic coordinate (GCC), to ∼0.32 on June 10 in comparison to ∼0.40 in other years. The defoliation, observable from space as reductions in normalized difference vegetation index (NDVI) values, also showed a negligible effect on E but a large effect on the C fluxes. [ABSTRACT FROM AUTHOR]

The article focuses on Natural Environment Research Council Joint Weather and Climate Research Programme workshop regarding an integration of urban atmospheric process that held on November 16-18, 2016 at the University of Reading. It states observation of changes in atmospheric models associated with urban regions along with pressure. It mentions consideration of research project with collaboration of social sciences and environmental sciences.

Large-scale insect outbreaks can substantially alter the carbon exchange of forests. Currently, British Columbia, Canada, is experiencing the largest mountain pine beetle (MPB, Dendroctonus ponderosae) outbreak ever registered, leaving large areas of forest killed or partially killed. It has been found that some unharvested attacked stands have returned to being a carbon sink within a relatively short time. A three-week field campaign was conducted during the summer of 2010 in one of these MPB-attacked stands, to determine the contributions of different vegetation layers to the overall net ecosystem exchange (NEE) of the stand. Almost all of the mature pine trees in this stand were dead, while there was a relatively rich secondary structure (younger conifer trees not killed by the beetle) and a broadleaf dominated understory. Two independent approaches, the eddy-covariance (EC) approach using seven EC systems distributed vertically on a tower of which six were installed within the canopy and one above the canopy and an ecophysiological (EP) approach based on carbon dioxide (CO2) chamber measurements on foliage and boles were employed in this study. Air-column storage corrected CO2 flux below each measurement level was partitioned into photosynthesis and respiration components. The climatic conditions during the field campaign were dry, and water use efficiency was analyzed while going from moderate to dry conditions. Due to the open-stand structure, approximately 60% of the photosynthetically active radiation reached the 1-m height. The photosynthesis of the living vegetation exceeded the respiration in this stand. The understory was found to have the largest CO2 sink strength in the canopy, while the secondary structure also contributed substantially to the overall CO2 uptake. The overstory, consisting of mainly dead trees, was a weak CO2 source. The EC and EP approaches agreed regarding the vertical distribution of sources and sinks of CO2 in the canopy; however, the magnitude varied between the two approaches. Water use efficiency was relatively high with the daytime average value between 2.3g C kg-1 H2O close to the ground where the broadleaf vegetation was dominant and 6.5g C kg-1 H2O where the conifer trees of the secondary structure were located. The secondary structure exhibited greater adjustment to increasingly dry conditions than the broadleaf vegetation. [ABSTRACT FROM AUTHOR]

The current outbreak of mountain pine beetle (MPB) that started in the late 1990s in British Columbia, Canada, is the largest ever recorded in the north American native habitat of the beetle. The killing of trees is expected to change the vertical distribution of net radiation ( $$Q^*$$ ) and the partitioning of latent ( $$Q_\mathrm{E}$$ ) and sensible ( $$Q_\mathrm{H}$$ ) heat fluxes in the different layers of an attacked forest canopy. During an intensive observation period in the summer of 2010, eddy-covariance flux and radiation measurements were made at seven heights from ground level up to 1.34 times the canopy height in an MPB-attacked open-canopy forest stand $$(\hbox {leaf area index} = 0.55~\mathrm{{m}}^{2}\ \mathrm{{m}}^{-2})$$ in the interior of British Columbia, Canada. The lodgepole pine dominated stand with a rich secondary structure (trees and understorey not killed by the beetle) was first attacked by the MPB in 2003 and received no management. In this study, the vertical distribution of the energy balance components and their sources and sinks were analyzed and energy balance closure (EBC) was determined for various levels within the canopy. The low stand density resulted in approximately 60 % of the shortwave irradiance and 50 % of the daily total $$Q^*$$ reaching the ground. Flux divergence calculations indicated relatively strong sources of latent heat at the ground and where the secondary structure was located. Only very weak sources of latent heat were found in the upper part of the canopy, which was mainly occupied by dead lodgepole pine trees. $$Q_\mathrm{H}$$ was the dominant term throughout the canopy, and the Bowen ratio ( $$Q_\mathrm{H}/Q_\mathrm{E}$$ ) increased with height in the canopy. Soil heat flux ( $$Q_\mathrm{G}$$ ) accounted for approximately 4 % of $$Q^*$$ . Sensible heat storage in the air ( $$\Delta Q_\mathrm{S,H}$$ ) was the largest of the energy balance storage components in the upper canopy during daytime, while in the lower canopy sensible heat storage in the boles ( $$\Delta Q_\mathrm{S,B}$$ ) and biochemical energy storage ( $$\Delta Q_\mathrm{S,C}$$ ) were the largest terms. $$\Delta Q_\mathrm{S,H}$$ was almost constant from the bottom to above the canopy. $$\Delta Q_\mathrm{S,C}$$ , $$\Delta Q_\mathrm{S,B}$$ and latent heat storage in the air ( $$\Delta Q_\mathrm{S,E}$$ ) varied more than $$\Delta Q_\mathrm{S,H}$$ throughout the canopy. During daytime, energy balance closure was high in and above the upper canopy, and in the lowest canopy level. However, where the secondary structure was most abundant, $${\textit{EBC}} \le 66\,\%$$ . During nighttime, the storage terms together with $$Q_\mathrm{G}$$ made up the largest part of the energy balance, while $$Q_\mathrm{H}$$ and $$Q_\mathrm{E}$$ were relatively small. These radiation and energy balance measurements in an insect-attacked forest highlight the role of secondary structure in the recovery of attacked stands. [ABSTRACT FROM AUTHOR]

The specific problems of determining and simulating the surface energy balance (SEB) and the mixing height (MH) over urban areas are examined. The SEB and MH are critical components of algorithms and numerical models for the urban boundary layer, though the constituent parts of the SEB and the MH are not routinely measured by national weather services. Parameterisations are thus needed in applications. In this investigation, several recently developed algorithms and models for estimating the SEB and MH were applied to new datasets and assessed. Results are discussed in terms of the need for spatial resolution and the parameters needed to describe the urban atmosphere. Limitations of models are identified and recommendations for further development and observations are given. Having identified gaps in knowledge, key findings from new urban experiments and numerical modelling for the SEB and MH are given. The diurnal cycle for the SEB is significantly different from rural conditions—urban heat storage is needed in urban parameterisations. The urban MH is increased over the rural MH, as shown by several numerical schemes and careful sodar analyses. This work has been carried out within the COST-715 Action “Meteorology applied to urban air pollution problems (1998–2004). COST 715 reached a consensus proposing representatively sited measurements of meteorological parameters and turbulent fluxes above roof-tops, and recognised that such data are needed to improve numerical models of the urban surface processes. [ABSTRACT FROM AUTHOR]

An overview of the Energy Balance Experiment (EBEX-2000) is given. This experiment studied the ability of state-of-the-art measurements to close the surface energy balance over a surface (a vegetative canopy with large evapotranspiration) where closure has been difficult to obtain. A flood-irrigated cotton field over uniform terrain was used, though aerial imagery and direct flux measurements showed that the surface still was inhomogeneous. All major terms of the surface energy balance were measured at nine sites to characterize the spatial variability across the field. Included in these observations was an estimate of heat storage in the plant canopy. The resultant imbalance still was 10%, which exceeds the estimated measurement error. We speculate that horizontal advection in the layer between the canopy top and our flux measurement height may cause this imbalance, though our estimates of this term using our measurements resulted in values less than what would be required to balance the budget. [ABSTRACT FROM AUTHOR]

During a special observing period (SOP) of the Mesoscale Alpine Programme (MAP), boundary layer processes in highly complex topography were investigated in the Riviera Valley in southern Switzerland. The main focus was on the turbulence structure and turbulent exchange processes near the valley surfaces and free troposphere. Due to the anticipated spatial inhomogeneity, a number of different turbulence probes were deployed on a cross section through the valley. Together with a suite of more conventional instrumentation, to observe mean meteorological structure in the valley, this effort yielded a highly valuable dataset. The latter is presently being exploited to yield insight into the turbulence structure in very complex terrain, and its relation to flow regimes and associated mean flow characteristics. Specific questions, such as a detailed investigation of turbulent exchange processes over complex topography and the validity of surface exchange parameterizations in numerical models for such surfaces, the closure of the surface energy balance, or the definition and meaning of the “boundary layer height,” are investigated using the MAP-Riviera dataset. In the present paper, we provide details on sites and their characteristics, on measurements and observational strategies, and on efforts to guarantee comparability between different instrumentation at different sites, and we include an overview of the available instrumentation. On the basis of preliminary data and first results, the main research goals of the project are outlined. [ABSTRACT FROM AUTHOR]

• Identified drivers controlling 15 years of measured NEE over a Douglas-fir forest. • Artificial neural networks partitioned NEE into respiration and gross primary production. • Bayesian optimization of hyperparameters and predictor analysis applied. • Soil moisture identified as most important driver of respiration in late summer. • Spring / summer precipitation and temperature more important for NEE than annual values. It is critical to have long-term carbon dioxide (CO 2) flux observations in forest ecosystems to understand how changing climate can affect forest carbon (C) stocks and CO 2 exchange between forests and the atmosphere. In this study, fifteen years (2002–2016) of continuous eddy-covariance flux and climate measurements in an intermediate-aged Douglas-fir stand on the east coast of Vancouver Island, Canada, were analyzed. First, the eddy covariance-measured CO 2 fluxes were partitioned into gross primary production and ecosystem respiration using two artificial neural networks. Second, the responses of net ecosystem production, gross primary production and ecosystem respiration to interannual climate variability, including five El Niño-Southern Oscillation events, were determined. Three hyper-parameters (number of layers, hidden units, and batch size) of each artificial neural network were set by Bayesian optimization using sequential model-based optimization while the remaining hyper-parameters were taken from the literature. The first artificial neural network was fitted using only nighttime CO 2 flux data and applied to estimate nighttime and daytime ecosystem respiration values, and the second one was used to gap-fill gross primary production values. In addition, a predictor analysis was done to investigate the most influential predictors (i.e., environmental variables) within seasons and years. When applied to half-hourly data, the ecosystem respiration model had an R2 of 0.43, whereas the gross primary production model had an R2 of 0.80. The stand was a moderate C sink (average net ecosystem production of 118 ± 404 g C m−2 year−1) during the entire study period, except for the years 2002–2006 when the stand was a moderate C source. The mean annual values of gross primary production and ecosystem respiration were 1649 ± 157 g C m−2 year−1 and 1531 ± 410 g C m−2 year−1, respectively. Our analysis showed that soil temperature was the most important predictor for the ecosystem respiration model, and photosynthetically active irradiance was the most important predictor for the gross primary production model. However, during dry periods in late summer, soil moisture became the most important predictor. Interannual variability of net ecosystem production was only slightly affected by annual total precipitation, mean soil temperature and mean air temperature. Instead, it depended on spring mean air temperature (start of the growing season), summer total precipitation (indicative of water deficiency) and mean summer air temperature. El Niño and La Niña events generally resulted in lower and higher annual net ecosystem production, respectively. [ABSTRACT FROM AUTHOR]