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Ongoing urbanization highlights the need for a better understanding and high resolution modelling of the urban climate. In this study, we combine rural observations by WMO surface stations, weather radar data and urban crowd-sourced observations with very fine-scale modelling efforts for Amsterdam, The Netherlands. As a model, we use the Weather Research and Forecasting (WRF) mesoscale model with 3D variational data assimilation at a 100-m resolution in the innermost model domain. In order to enable the assimilation of observations within the urban canopy, we develop a scheme to reduce urban temperature biases by adjusting urban fabric temperatures. The scheme is tested against independent urban observations for the summer month of July 2014 and specifically for a hot period and an extreme precipitation event. We find data assimilation reduces biases in temperature and wind speed. Within the city, the most significant improvement is the reduction of negative temperature biases during clear nights, which implies a better prediction of the Urban Heat Island (UHI). Concerning precipitation, the fractional skill score improves incrementally when additional observations are assimilated, and the largest impact is seen from the assimilation of weather radar observations.

The funding agency information in the Acknowledgements was not complete in the original publication of the article. The revised Acknowledgments is provided in this erratum.

In this study, the stability dependence of turbulent Prandtl number ($$Pr_t$$ P r t ) is quantified via a novel and simple analytical approach. Based on the variance and flux budget equations, a hybrid length scale formulation is first proposed and its functional relationships to well-known length scales are established. Next, the ratios of these length scales are utilized to derive an explicit relationship between $$Pr_t$$ P r t and gradient Richardson number. In addition, theoretical predictions are made for several key turbulence variables (e.g., dissipation rates, normalized fluxes). The results from our proposed approach are compared against other competing formulations as well as published datasets. Overall, the agreement between the different approaches is rather good despite their different theoretical foundations and assumptions.

The Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models. In ISOBAR ground-based flux and profile observations are combined with boundary layer remote sensing methods and the extensive usage of different unmanned aircraft systems (UAS). During February 2017 and 2018 we carried out two major field campaigns over the sea ice of the northern Baltic Sea, close to the Finnish island of Hailuoto at 65°N. In total 14 intensive observational periods (IOPs) resulted in extensive SBL datasets with unprecedented spatiotemporal resolution, which will form the basis for various numerical modeling experiments. First results from the campaigns indicate numerous very stable boundary layer (VSBL) cases, characterized by strong stratification, weak winds, and clear skies, and give detailed insight in the temporal evolution and vertical structure of the entire SBL. The SBL is subject to rapid changes in its vertical structure, responding to a variety of different processes. In particular, we study cases involving a shear instability associated with a low-level jet, a rapid strong cooling event observed a few meters above ground, and a strong wave-breaking event that triggers intensive near-surface turbulence. Furthermore, we use observations from one IOP to validate three different atmospheric models. The unique finescale observations resulting from the ISOBAR observational approach will aid future research activities, focusing on a better understanding of the SBL and its implementation in numerical models.

We report about a new third-party observation, namely, wind measurements derived from hot-air balloon (HAB) tracks. We first compare the HAB winds with wind measurements from a meteorological tower and a radio acoustic wind profiler, both situated at the topographically flat observatory near Cabauw, the Netherlands. To explore the potential of this new type of wind observation in other topographies, we present an intriguing HAB flight in Austria with a spectacular mountain–valley circulation. Subsequently, we compare the HAB data with a numerical weather prediction (NWP) model during 2011–13 and the standard deviation of the wind speed is 2.3 m s−1. Finally, we show results from a data assimilation feasibility experiment that reveals that HAB wind information can have a positive impact on a hindcasted NWP trajectory.

In this paper, we revisit a well-known formulation of temperature structure parameter ($$C_T^2$$ C T 2 ), originally proposed by V. I. Tatarskii. We point out its limitations and propose a revised formulation based on turbulence variance and flux budget equations. Our formulation includes a novel physically-based outer length scale which can be estimated from routine meteorological data.

In this study, we utilize a novel approach to solve the Ekman equations for eddy-viscosity profiles in the stable boundary-layer. By doing so, a well-known expression for the stable boundary-layer height by Zilitinkevich (Boundary-Layer Meteorology, 1972, Vol. 3, 141–145) is rediscovered.

An overview is given of 50-year Cabauw observations and research on the structure and dynamics of the atmospheric boundary layer. It is shown that over time this research site with its 200-m meteorological tower has grown into an atmospheric observatory with a comprehensive observational program encompassing almost all aspects of the atmospheric column including its boundary conditions. This is accomplished by the Cabauw Experimental Site for Atmospheric Research (CESAR) a consortium of research institutes. CESAR plays an important role in the educational programs of the CESAR universities. The current boundary-layer observational program is described in detail, and other parts of the CESAR observational program discussed more briefly. Due to an open data policy the CESAR datasets are used by researchers all over the world. Examples are given of the use of the long time series for model evaluation, satellite validation, and process studies. The role of tall towers is discussed in relation to the development of more and better ground-based remote sensing techniques. CESAR is now incorporated into the Ruisdael observatory, the large-scale atmospheric research infrastructure in the Netherlands. With Ruisdael the embedding of the Dutch atmospheric community in national policy landscape, and in the European atmospheric research infrastructures is assured for the coming decade.

To reduce the vulnerability of urban areas facing high temperatures, it is useful to develop methods to obtain the urban heat island (UHI) intensity. However, it is hard to equip all cities with extensive measurement networks and alternative UHI diagnostic methods are needed. Accordingly, in this paper we evaluate and revise the diagnostic equation designed by Theeuwes et al. (2017) and analyze its application for Xi'an (China), based on long-term summer meteorology data. The evaluation of the default diagnostic equation shows that limited accuracy for Xi'an is caused by the sum of morphological parameters being used outside the original range of calibration. Subsequently, we propose an extended equation, which adds the building fraction to express the morphology of additional spatial categories. This new equation is calibrated against a 3-year dataset and independently validated with data from another year. In addition, a class prediction with three spatial categories is proposed, and verified by independent data of 20 stations in Xi'an in 2018, which enables this formula to be applied in more cities. Altogether, the extended diagnostic equation is an effective method to evaluate the daily maximum UHI intensity (UHImax) on neighborhood-scale, which can be generalized for a whole city area and presents internal intensity differences with multi-points.

15 year re-analysis of the urban climate of Amsterdam using WRF Sytse Koopmans1 (Sytse.koopmans@wur.nl), Gert-Jan Steeneveld1, Ronald van Haren2, Albert A.M. Holtslag1. 1 Wageningen University and Research, the Netherlands:2 Netherlands eScience Center, the Netherlands: Ongoing world-wide climate change and urbanization illustrate the need to understand urban hydrometeorology and its implications for human thermal comfort and water management. Numerical weather prediction models can assist to understand these issues, as they progress increasingly towards finer scales. With high model resolutions (grid spacing of 100m), effective representation of cities becomes crucial. The complex structures of cities, configuration of buildings, streets and scattered vegetation, require a different modelling approach than the homogeneous rural surroundings. The current urban canopy-layer schemes account for these city specific characteristics, but differ substantially amongst each other due to uncertainty in land use parameters and incomplete physical understanding. Therefore, the hindcasting of the urban environment needs improvement.In this study, we improve the WRF (Weather Research and Forecasting) mesoscale model performance by incorporating observations of a variety of sources using data assimilation (WRF-3DVAR) and nudging techniques on a resolution up to 167 meter. Data assimilation aims to accurately describe the most probable atmospheric state by steering the model fields in the direction of the observations. Specific to urban boundary layers, a novel approach has been developed to nudge modelled urban canyon temperatures with quality controlled urban weather observations. Adjusting the urban fabric accordingly is crucial, because of the large heat storage within urban canopies. The road and wall layers of the urban canopy are adjusted depending on the bulk heat transfer coefficient and urban geometry. Other data assimilation sources consists of WMO synoptic weather observations and volume radar data.The results of the 15-year climatological urban re-analysis are here presented and it is subdivided in three key questions. First, we attempt to answer how large the trends are in human thermal comfort over the 15 year period. Second, we investigate if there are seasonality’s detected in maximum urban heat island intensities. Earlier found hysteresis-like curves were reproduced to a large extent for for pedestrian level air temperatures. Lastly, we analyse trends in extreme precipitation using simulated precipitation data on one second interval.

Height of the stable boundary layer (SBL) presents an important diagnostic used to describe the relevant processes governing the evolution and characteristics of SBL, and the extent to which the surface is communicating with the free atmosphere. Here we investigate the SBL height over a gentle (1°) mesoscale slope on which relatively deep mid-latitude katabatic flows (with jet maxima between 20 and 50 m) develop during clear nights. We show that detecting the SBL top depends on the method used (Richardson number, flux- and anisotropy-profiles). The detected SBL depth, mostly deviates from the jet maximum height or the top of the near-surface inversion. The flat terrain formulations for the SBL height correlate well with the detected top of the SBL if instead of background stratification, near-surface stratification is used in their formulations, however, they mostly largely overestimate the SBL height. The difference to flat-terrain SBL is also shown through the dependence of size of the dominant eddy with height. In katabatic flows the eddy size is semi-constant with height throughout the SBL, whereas in flat terrain eddy size varies significantly with height.

Many wind energy applications rely on engineering models that simulate the interaction between the wind and the turbine(s). These models often represent the wind in an idealised fashion, which introduces uncertainties that translate into financial risk for investors.Over the past four years, we investigated these uncertainties by re-evaluating common assumptions about the (offshore) wind field, studying the physics that govern winds in coastal areas, evaluating the representation of offshore winds in weather models, and proposing alternative methods to represent the offshore wind climate in engineering models.Uncertainties in the wind climate were studied through a number of ‘anomalous wind events’. An important and illustrative example is the low-level jet, which can substantially impact power production and wind loads on the turbine. We found that low-level jets occur often over the North Sea. Moreover, numerical weather prediction models struggle to adequately represent this phenomenon. A climatology based only on observations is also biased, because the observations are limited in time and space. Thus, we combined field observations with output of reanalysis products to obtain a reliable climatology.At the 2020 general assembly, we will present a new evaluation of three recent wind atlases over the North Sea: ERA5, The New European Wind Atlas (NEWA), and the Dutch Offshore Wind Atals (DOWA). With virtually no bias, DOWA outperforms the other datasets in terms of the mean wind profile and also in the representation of wind shear. The high resolution offered by DOWA (2.5 km) and NEWA (3 km) leads to substantial improvements in the frequency and the level of detail with which low-level jets are captured. However, the timing of the events is a bit off in NEWA. By contrast, DOWA was produced using continuous three-hourly data-assimilation updates, which imposes a much stronger constraint on the simulations. Consequently, the timing of low-level jets in DOWA is much better represented. This makes for a low-level jet climatology with unprecedented accuracy and detail, facilitating resource assessment and future studies on the characteristics of the offshore wind climate.

Urban areas are vulnerable to intensive heatwave periods. In order to understand heat stress in cities, the single-layer urban canopy model (SLUCM) coupled with the weather research and forecasting model (WRF) have been widely used to quantify and forecast the urban climate. However, the model performance in WRF/SLUCM is limited by the coarse classification of urban canopy parameters (UCPs), and further improvements may require great effort. Therefore, this study was a new attempt at organizing the gridded UCPs in the ‘National Urban Database and Access Portal Tool (NUDAPT) approach’ and exploring its application in the WRF/SLUCM model in four simulations with contrasting UCP configurations. The model performances were evaluated for a heatwave period in 2018 in the typical Chinese city of Xi'an, using a near-surface observational network consisting of 39 meteorological stations in various urban spatial categories. We found that the increased accuracy in UCPs brought about gradual and overall improvements in the urban heat island effect (UHI) and air temperature (Ta), and had relatively slight effects on absolute humidity (ρν) and wind speed (WP). Furthermore, the station-to-station bias analyses indicated that optimization efficiency varied among urban spatial categories. Areas with an open form or areas densely covered with vegetation showed constant sensitivity to the increasing refinements of UCPs. Input of the gridded and multi-dimensional descriptions of urban canyon geometry contributed to more accurate results in dense urban areas and areas with mixed and inhomogeneous morphology.

High-resolution, regularly gridded air-temperature maps are frequently used in climatology, hydrology, and ecology. Within the Netherlands, 34 official automatic weather stations (AWSs) are operated by the National Met Service according to World Meteorological Organization (WMO) standards. Although the measurements are of high quality, the spatial density of the AWSs is not sufficient to reconstruct the temperature on a 1-km-resolution grid. Therefore, a new methodology for daily temperature reconstruction from 1990 to 2017 is proposed, using linear regression and multiple adaptive regression splines. The daily 34 AWS measurements are interpolated using eight different predictors: diurnal temperature range, population density, elevation, albedo, solar irradiance, roughness, precipitation, and vegetation index. Results are cross-validated for the AWS locations and compared with independent citizen weather observations. The RMSE of the reference method ordinary kriging amounts to 2.6 °C whereas using the new methods the RMSE drops below 1.0 °C. Especially for cities, a substantial improvement of the predictions is found. Independent predictions are on average 0.3 °C less biased than ordinary kriging at 40 high-quality citizen measurement sites. With this new method, we have improved the representation of local temperature variations within the Netherlands. The temperature maps presented here can have applications in urban heat island studies, local trend analysis, and model evaluation.

In this article an analysis of urban rainfall from hourly to seasonal scales is conducted for the Netherlands, with a focus on its capital, Amsterdam. In addition, the potential of synoptic weather types and local wind directions to categorize extreme rainfall in Amsterdam is assessed. An analysis of gauge-adjusted daily radar rainfall retrievals with 1 km spatial resolution for 10 years shows that rainfall is enhanced over Dutch cities compared to their rural surroundings, with a maximum of a 14.2% increase over the largest cities in winter. The annual cumulative rainfall in Amsterdam appears to be significantly higher compared to its surroundings. This is due both to the higher frequency of occurrence of urban rainfall and to the higher hourly mean intensities. Extreme hourly rainfall rates appear to be affected by urban areas only in summer. Diurnal and weekly rainfall cycles do not reveal any significant urban influence. A wind direction analysis reveals that extreme rainfall events can primarily be attributed to westerly and next to southerly air masses. An analysis of the Jenkinson and Collinson (JC) and the German Weather Service (Deutscher Wetterdienst, DWD) weather types with rainfall and extreme rainfall events reveals that the JC weather types are more indicative of situations associated with rainfall extremes, whereas the DWD weather types are more indicative of situations resulting in higher accumulated rainfall amounts.

Numerical weather prediction models play an important role in the field of wind energy, for example, in power forecasting, resource assessment, wind farm (wake) simulations, and load assessment. Continuous evaluation of their performance is crucial for successful operations and further understanding of meteorology for wind energy purposes. However, extensive offshore observations are rarely available. In this paper, we use unique met mast and Lidar observations up to 315 m from met mast “IJmuiden,” located in the North Sea 85 km off the Dutch coast, to evaluate the representation of wind and other relevant variables in three mainstream meteorological models: ECMWF-IFS, HARMONIE-AROME, and WRF-ARW, for a wide range of weather conditions. Overall performance for hub-height wind speed is found to be comparable between the models, with a systematic wind speed bias

Meteorology and air quality are key aspects for city life and urban metabolism. Both aspects build upon urban and natural processes, involve stocks and flows of heat and pollution, with in the end consequences for stocks and flows concerning other urban entities and processes such as human outdoor activities, leisure, transport modes, as well as for urban design and planning. During hot summer days cities experience an urban heat island effect mainly at the start of the evening and at night. As a result inhabitants might be subject to a reduced human thermal comfort. Hot summer days often also coincide with relatively poor air quality conditions. Both short-term effects are known to increase the mortality rates, and it is challenging to distinguish their impacts on health effects. Moreover, climate change scenarios indicate an enhancement of future heat wave frequency and intensity and a further deterioration of human thermal comfort. These issues raise the need and the urgency for city adaptation, but an integrated method for the assessment is still missing. Effective city adaptation is hampered by the complexity of the urban climate (induced by both meteorology and urban morphological characteristics) and its potential health risks, combined with the complex spatial interaction of stakeholders and economical functions. To warn the general public, and to effectively perform urban planning interventions, straightforward environmental indicators are required. Indicators have been developed for the individual aspects before, but indices that combine both air quality and urban heat are rather scarce (Rainham and Smoyer-Tomic, 2003). This study develops a novel metric that combines the impact of thermal comfort and air quality by accounting for the relative health risk for both aspects. A straightforward quantification method for this metric has been developed to provide an objective, rational assessment. The application of this new Urban Climate assessment tool is then applied to a case study for a heat wave in the Northwestern Europe, and applied for a sample intervention in the city center of Ghent (Belgium).

At present atmospheric models for weather and climate use enhanced turbulent drag under stable conditions, because these empirically provide the necessary momentum drag for accurate forecast of synoptic systems. The enhanced mixing (also known as the "long-tail"), introduces drag that can not be physically justified and deteriorates the score for near surface temperature, wind and boundary-layer height, and deteriorates fog and frost forecasting. This study hypothesises that the insufficient representation of small-scale orographic gravity wave drag in the stable boundary layer may explain the need for the enhanced drag formulation. Hence, we introduce a new scheme in the WRF model that accounts for this drag as a superposition on the turbulent drag induced by a so-called short-tail mixing function. The latter is consistent with boundary-layer observations and large eddy simulations. We evaluate this scheme, against a short-tail and a long-tail scheme for sixteen 8-day forecasts over the Atlantic Ocean and Europe in winter. The new scheme outperforms the short and long tail schemes on sea level pressure, height of the 500 hPa field, 10 m wind and the cyclonic core pressure. Cyclonic core pressure bias is reduced by approximately 45% to 80% compared to the short-tail scheme. Sea level pressure bias is reduced by up to 0.48 hPa (50%) over the whole domain compared to the short-tail run. The new scheme has even smaller biases than the long-tail scheme, supporting our hypothesis that small-scale gravity wave drag may explain the need for a long-tail function. Near surface wind bias is reduced by up to 40% compared to the long-tail and up to 32% compared to the short-tail scheme, while the 2 m temperature bias is only slightly increased (19%).

A comprehensive analysis of the turbulence structure of relatively deep midlatitude katabatic flows (with jet maxima between 20 and 50 m) developing over a gentle (1°) mesoscale slope with a long fetch upstream of the Meteor Crater in Arizona is presented. The turbulence structure of flow below the katabatic jet maximum shows many similarities with the turbulence structure of shallower katabatic flows, with decreasing turbulence fluxes with height and almost constant turbulent Prandtl number. Still stark differences occur above the jet maximum where turbulence is suppressed by strong stability, is anisotropic and there is a large sub‐mesoscale contribution to the flux. Detecting the stable boundary‐layer top depends on the method used (flux‐ vs. anisotropy‐profiles) but both methods are highly correlated. The top of the stable boundary layer, however, mostly deviates from the jet maximum height or the top of the near‐surface inversion. The flat‐terrain formulations for the boundary‐layer height correlate well with the detected top of the stable boundary layer if the near‐surface and not the background stratification is used in their formulations; however, they mostly largely overestimate this boundary‐layer height. The difference from flat‐terrain boundary layers is also shown through the dependence of size of the dominant eddy with height. In katabatic flows the eddy size is semi‐constant with height throughout the stable boundary‐layer depth, whereas in flat terrain, eddy size varies significantly with height. Flux‐gradient and flux‐variance relationships show that turbulence data from different stable boundary‐layer scaling regimes collapse on top of each other showing that the dominant dependence is not on the scaling regime but on the local stability., Persistent relatively deep katabatic flows develop over a shallow mesoscale slope outside the Meteor Crater, Arizona. Their turbulent structure deviates from the structure of shallow katabatic flows in that the small‐scale turbulence is strongly attenuated already at heights below the jet maximum. The height of the stable katabatic boundary layer is significantly lower than over flat terrain for the same forcing. The change of turbulence anisotropy below and above the boundary layer provides a new diagnostic of boundary‐layer height.

Urban canopy models are essential tools for forecasting weather and air quality in cities. However, they require many surface parameters, which are uncertain and can reduce model performance if inappropriately prescribed. Here, we evaluate the model sensitivity of the single-layer urban canopy model (SLUCM) in the Weather Research and Forecasting (WRF) model to surface parameters in two different configurations, one coupled to the overlying atmosphere (on-line) in a 1D configuration and one without coupling (off-line). A two-day summertime period in London is used as a case study, with clear skies and low wind speeds. Our sensitivity tests indicate that the SLUCM reacts differently when coupled to the atmosphere. For certain surface parameters, atmospheric feedback effects can outweigh the variations caused by surface parameter settings. Hence, in order to fully understand the model sensitivity, atmospheric feedback should be considered.

Ten years of ERA5 reanalysis data are combined with met-mast and lidar observations from 10 offshore platforms to investigate low-level jet characteristics over the Dutch North Sea. The objective of this study is to combine the best of two worlds: (1) ERA5 data with a large spatiotemporal extent but inherent accuracy limitations due to a relatively coarse grid and an incomplete representation of physical processes and (2) observations that provide more reliable estimates of the measured quantity but are limited in both space and time. We demonstrate the effect of time and range limitations on the reconstructed wind climate, with special attention paid to the impact on low-level jets. For both measurement and model data, the representation of wind speed is biased. The limited temporal extent of observations leads to a wind speed bias on the order of ±1 m s−1 as compared to the long-term mean. In part due to data-assimilation strategies that cause abrupt discontinuities in the diurnal cycle, ERA5 also exhibits a wind speed bias of approximately 0.5 m s−1. The representation of low-level jets in ERA5 is poor in terms of a one-to-one correspondence, and the jets appear vertically displaced (“smeared out”). However, climatological characteristics such as the shape of the seasonal cycle and the affinity with certain circulation patterns are represented quite well, albeit with different magnitudes. We therefore experiment with various methods to adjust the modelled low-level jet rate to the observations or, vice versa, to correct for the erratic nature of the short observation periods using long-term ERA5 information. While quantitative uncertainty is still quite large, the presented results provide valuable insight into North Sea low-level jet characteristics. These jets occur predominantly for circulation types with an easterly component, with a clear peak in spring, and are concentrated along the coasts at heights between 50 and 200 m. Further, it is demonstrated that these characteristics can be used as predictors to infer the observed low-level jet rate from ERA5 data with reasonable accuracy.

The urban heat island (UHI) effect, defined as the air temperature difference between the urban canyon and the nearby rural area, is investigated. Because not all cities around the world are equipped with an extensive measurement network, a need exists for a relatively straightforward equation for the UHI effect. Here, we derive a simple, diagnostic equation for the UHI using dimensional analysis. This equation provides a first-order estimation of the daily maximum UHI based on routine meteorological observations and straightforward urban morphological properties. The equation is tested for 14 cities across northwestern Europe and appears to be robust. The comprehensiveness of this analytical equation allows for applications beyond urban meteorological studies.

High-resolution upper-air wind observations are sparse, and additional observations are a welcome source of meteorological information. In this paper the potential of applying balloon flights for upper-air wind measurements is explored, and the meteorological content of this information is investigated. The displacement of a hot-air balloon is a measure for the wind speed and direction and thus a potential source for wind observations in the lower part of the troposphere. The response time of the balloon on the changing wind is fast in the beginning and levels off for smaller relative wind speeds. Four case studies are presented, and the balloon-derived winds are compared with other wind observations and with results from the HIRLAM–ALADIN Research on Mesoscale Operational NWP in Europe (HARMONIE) model. It turns out that hot-air balloon tracks can indeed produce useful wind observations just above and in the atmospheric boundary layer (ABL).

This study evaluates the relative impact of snow-surface coupling, long-wave radiation, and turbulent mixing on the development of the stable boundary layer over snow. Observations at three sites are compared to WRF single-column model (SCM) simulations. All three sites have snow-covered surfaces but are otherwise contrasting: Cabauw (Netherlands, grass), Sodankyla (Finland, needle-leaf forest) and Halley (Antarctica, ice shelf). All cases are characterized by stable, clear-sky, and calm conditions. Part 1 of this study determined the optimal SCM forcing strategy. In this study, the process intensities from that reference are perturbed to study their relative significance and to assess which process could be responsible for the most optimal agreement between model and observation. The analysis reveals a large variability in the modelled atmospheric state and surface parameters. Overall, the modelled gradients of temperature and moisture are under-estimated but decreasing the process intensities improves this. The impact is strongest with reduced mixing, though this then causes the model to overestimate the near-surface wind speed. To study the surface energy balance terms, we use so-called ‘process diagrams’. The achieved variation between the sensitivity runs indicates the model sensitivity to each process. The overall sensitivity is similar for the three sites but the relative offsets in the position of the sensitivity runs with respect to the observations differ, hampering general recommendations for model improvement. Furthermore, sometimes a meaningful interpretation of observations is troublesome, which hampers the comparison with model results. Radiation is relatively more important at Cabauw and Sodankyla, whilst coupling plays a more important role at Halley. The sensitivity analysis is performed with two boundary-layer schemes (MYJ, YSU). YSU generates larger, more accurate gradients of atmospheric temperature and humidity, while wind speeds are predicted better with MYJ. The behaviour of an increase in 2?m temperature with decreased mixing is most obvious with YSU.

In the Netherlands, there will be an urgent need for additional housing by the year 2040, which mainly has to be realized within the existing built environment rather than in the spatial extension of cities. In this data-driven study, we investigated the effects of different urban planning strategies on heat stress for the current climate and future climate scenarios (year 2050) for the urban agglomeration of The Hague. Heat stress is here expressed as the number of days exceeding minimum temperatures of 20 &deg, C in a year. Thereto, we applied a diagnostic equation to determine the daily maximum urban heat island based on routine meteorological observations and straightforward urban morphological properties including the sky-view factor and the vegetation fraction. Moreover, we utilized the Royal Netherlands Meteorological Institute&rsquo, s (KNMI) climate scenarios to transform present-day meteorological hourly time series into the future time series. The urban planning strategies differ in replacing low- and mid-rise buildings with high-rise buildings (which reduces the sky-view factor), and constructing buildings on green areas (which reduces the vegetation fraction). We found that, in most cases, the vegetation fraction is a more critical parameter than the sky-view factor to minimize the extra heat stress incurred when densifying the neighbourhood. This means that an urban planning strategy consisting of high-rise buildings and preserved green areas is often the best solution. Still, climate change will have a larger impact on heat stress for the year 2050 than the imposed urban densification.

The aim of the research project &ldquo, Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)&rdquo, is to substantially increase the understanding of the stable atmospheric boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by models of different complexity. During three weeks in February 2017, a first field campaign was carried out over the sea ice of the Bothnian Bay in the vicinity of the Finnish island of Hailuoto. Observations were based on ground-based eddy-covariance (EC), automatic weather stations (AWS) and remote-sensing instrumentation as well as more than 150 flight missions by several different Unmanned Aerial Vehicles (UAVs) during mostly stable and very stable boundary layer conditions. The structure of the atmospheric boundary layer (ABL) and above could be resolved at a very high vertical resolution, especially close to the ground, by combining surface-based measurements with UAV observations, i.e., multicopter and fixed-wing profiles up to 200 m agl and 1800 m agl, respectively. Repeated multicopter profiles provided detailed information on the evolution of the SBL, in addition to the continuous SODAR and LIDAR wind measurements. The paper describes the campaign and the potential of the collected data set for future SBL research and focuses on both the UAV operations and the benefits of complementing established measurement methods by UAV measurements to enable SBL observations at an unprecedented spatial and temporal resolution.

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of $$\Delta x = 1.1\,\hbox {km}$$ Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.

Near-surface turbulent flux and radiation divergence field observations are analysed over a grass-covered surface located at the Wageningen observatory, the Netherlands. Net radiative flux divergence appears to be a large component of the energy budget near the surface, accounting for a cooling rate of several tens of degrees per day. Long-wave radiation divergence dominates this radiation divergence flux. We show here that long-wave flux divergence near the surface is strongly coupled to sensible heat flux, except in high relative humidity (>90%) and foggy conditions. The net long-wave radiative flux divergence exhibits a sharp gradient within the first 20 m above the surface. This flux divergence is itself strongly coupled to sensible heat flux through adjustments in surface-layer profiles. Nonetheless, no systematic effect of radiation is witnessed on the turbulent temperature spectrum so that the main effect of near-surface radiation is on the mean heat budget. As typical flux-gradient relationships are derived based on observations taken in the near-surface boundary-layer region where sharp long-wave divergence is present, we suspect that those relationships implicitly represent some of the long-wave divergence term. A modification of Monin–Obukhov Similarity Theory to include the effect of radiative divergence is proposed and discussed. This calls for independent measurements of turbulent fluxes and radiative flux divergence near the surface to re-derive turbulent flux-gradient relationships independently of radiative effects.

In this study, we improve the Weather Research and Forecasting mesoscale model (WRF) performance by incorporating observations of a variety of sources using data assimilation and nudging techniques on a resolution up to 100 meter for urban areas. Our final goal is to create a 15 year climatological urban re-analysis data archive of (hydro)meteorological variables for Amsterdam which is named ERA-urban. This will enable us to trace trends in thermal comfort and extreme precipitation.

Wind is a key component of the urban climate due to its relevance for ventilation of air pollution and urban heat, wind nuisance, as well as for urban wind energy engineering. These winds are governed by the dynamics of the atmosphere closest to the surface, the atmospheric boundary layer (ABL). Making use of a conceptual bulk model of the ABL, we find that for certain atmospheric conditions the boundary-layer mean wind speed in a city can surprisingly be higher than its rural counterpart, despite the higher roughness of cities. This urban wind island effect (UWI) prevails in the afternoon, and appears to be caused by a combination of differences in ABL growth, surface roughness and the ageostrophic wind, between city and countryside. Enhanced turbulence in the urban area deepens the ABL, and effectively mixes momentum into the ABL from aloft. Furthermore, the oscillation of the wind around the geostrophic equilibrium, caused by the rotation of the Earth, can create episodes where the urban boundary-layer mean wind speed is higher than the rural wind. By altering the surface properties within the bulk model, the sensitivity of the UWI to urban morphology is studied for the 10 urban local climate zones (LCZs). These LCZs classify neighbourhoods in terms of building height, vegetation cover etc, and represent urban morphology regardless of culture or location. The ideal circumstances for the UWI to occur are a deeper initial urban boundary-layer than in the countryside, low-rise buildings (up to 12 m) and a moderate geostrophic wind (∼5 m s−1). The UWI phenomenon challenges the commonly held perception that urban wind is usually reduced due to drag processes. Understanding the UWI can become vital to accurately model urban air pollution, quantify urban wind energy potential or create accurate background conditions for urban computational fluid dynamics models.

A Met Office/Natural Environment Research Council Joint Weather and Climate Research Programme workshop brought together 50 key international scientists from the UK and international community to formulate the key requirements for an Urban Meteorological Research strategy. The workshop was jointly organised by University of Reading and the Met Office.

Expansion of urban areas has profound effects on land surface characteristics. As such, the land surface can exert influence on atmospheric parameters that might alter precipitation amounts or patterns. In this study, precipitation observations near urban areas along the West coast of the Netherlands are investigated throughout the 1951–2010 period. An innovative analysis methodology is used to deal with the small and fragmented urban areas in the Netherlands. The results show that daily precipitation totals downwind of urban areas are, on average, about 7% higher than precipitation in the rest of the Dutch West coast. Precipitation enhancements up to 20% are found depending on wind direction and time period. These results are comparable with studies from around the globe and show that the influence of relatively small fragmented urban areas, as are present in the Netherlands, can be similar to the influence of large metropolitan areas on precipitation.

In this paper we evaluated the Weather Research and Forecasting (WRF) mesoscale meteorological model for stable conditions at clear skies with low wind speeds. Three contrasting terrains with snow covered surfaces are considered, namely Cabauw (Netherlands, snow over grass), Sodankyla (Finland, snow over a needle-leaf forest) and Halley (Antarctica, snow over an ice shelf). We used the full 3D model and the single-column versions of the WRF model. The SCM was driven by realistic forcings of the WRF-3D field. Several sets of SCM forcings were tested: A. no advection, B. varying geostrophic wind in time, C. momentum advection in addition to B, D. temperature and moisture advection in addition to C, and E. forcing the SCM field to the 3D field above a threshold height. The WRF-3D model produced overall good results for wind speed, but the near-surface temperatures and specific humidity were overestimated for Cabauw and Sodankyla, and underestimated for Halley. Prescribing advection for momentum, temperature and moisture gave the best results for the WRF-SCM, and simulations deviated strongly from reality without advection. Nudging the SCM field to the 3D field above a threshold height lead to an unrealistic behaviour of the variables below this height and is not recommended. Detailed prescription of the surface characteristics, e.g. adjusting the snow cover and vegetation fraction, improved the 2?m temperature simulation. For all three sites, the simulated temperature and moisture inversion was underestimated, though this improved when prescribing advection. Overall, in clear-sky conditions, the stable boundary layer over snow and ice can be modelled to a good approximation if all processes are taken into account at high resolution, and if land surface properties are carefully prescribed.

This paper reports on temporal and spatial variability of local climate and outdoor human thermal comfort within the Rotterdam agglomeration. We analyse three years of meteorological observations (2010–2012) from a monitoring network. Focus is on the atmospheric urban heat island (UHI); the difference in air temperature between urban areas and rural surroundings. In addition, we calculate the Physiologically Equivalent Temperature (PET) which is a measure of thermal comfort. Subsequently, we determine the dependency of intra-urban variability in local climate and PET on urban land-use and geometric characteristics. During a large part of the year, UHI-intensities in densely built areas can be considerable, under calm and clear (cloudless) weather conditions. The highest maximum UHI-values are found in summer, with 95-percentile values ranging from 4.3 K to more than 8 K, depending on the location. In winter, UHI-intensities are generally lower. Intra-urban variability in maximum UHI-intensity is considerable, indicating that local features have an important influence. It is found to be significantly related to building, impervious and green surface fractions, respectively, as well as to mean building height.In summer, urban areas show a larger number of discomfort hours (PET > 23 °C) compared to the reference rural area. Our results indicate that this is mainly related to the much lower wind velocities in urban areas. Also intra-urban variability in thermal comfort during daytime appears to be mainly related to differences in wind velocity. After sunset, the UHI effect plays a more prominent role and hence thermal comfort is more related with urban characteristics.

The numerical weather prediction of radiation fog is challenging, as many models typically show large biases for the timing of the onset and dispersal of the fog, as well as for its depth and liquid water content. To understand the role of physical processes, i.e. turbulence, radiation, land-surface coupling, and microphysics, we evaluate the HARMONIE and Weather Research and Forecasting (WRF) mesoscale models for two contrasting warm fog episodes at the relatively flat terrain around the Cabauw tower facility in the Netherlands. One case involves a radiation fog that arose in calm anticyclonic conditions, and the second is a radiation fog that developed just after a cold front passage. The WRF model represents the radiation fog well, while the HARMONIE model forecasts a stratus lowering fog layer in the first case and hardly any fog in the second case. Permutations of parametrization schemes for boundary-layer mixing, radiation and microphysics, each for two levels of complexity, have been evaluated within the WRF model. It appears that the boundary-layer formulation is critical for forecasting the fog onset, while for fog dispersal the choice of the microphysical scheme is a key element, where a double-moment scheme outperforms any of the single-moment schemes. Finally, the WRF model results appear to be relatively insensitive to horizontal grid spacing, but nesting deteriorates the modelled fog formation. Increasing the domain size leads to a more scattered character of the simulated fog. Model results with one-way or two-way nesting show approximately comparable results.

Uncertainty reduction in offshore wind systems heavily relies on meteorological advances. A detailed characterization of the wind climate at a given site is indispensable for site assessment, and its accurate representation in load assessment models can reduce costs of turbine design and the risk of failure. While regular wind conditions are reasonably described by established methods, some atypical wind conditions are poorly understood and represented, although they contribute substantially to load on turbines. In this study, 4 years of high-quality observations gathered up to 300 m are analyzed to characterize the wind climate at the IJmuiden tower, focusing on these ill-defined conditions. Following a systematic approach, six ‘anomalous wind events’ are identified and described: low-level jets, extreme wind speeds, shear, veer, turbulence and wind ramps. In addition, we identify typical weather conditions that favour their formation. Stable stratification in spring and summer leads to low-level jets (up to 12% of the time) for moderate wind conditions, and to extreme wind shear for stronger wind regimes. Typical wind ramps lead to a change in wind speed of 2 m s−1 in one hour. The applicability of turbulence intensity as a measure of turbulence and gusts is found to be questionable.

A great variety of similarity functions for the structure parameter of temperature ( $$C_{T}^2$$ ) have been proposed in the literature. They differ in the way they were derived from the data and in the characteristics of the dataset used for their derivation (surface type, observation level, stability range). In this study, we use one single dataset (CASES-99 experiment) and investigate the impact on the similarity functions of applying various regression approaches, and measuring at different heights and within different stability ranges. We limit ourselves to similarity functions under unstable conditions, and evaluate only the most common shape that describes the relation with two coefficients ( $$f\left( z/L\right) =c_{1} \left( 1-c_{2} {z}/{L}\right) ^{-2/3}$$ , where $$z$$ is the height, and $$L$$ is the Obukhov length and a measure of the stability, and $$c_{1}$$ and $$c_{2}$$ are the regression coefficients). The results show that applying various regression approaches has an impact on the regression coefficients $$c_{1}$$ and $$c_{2}$$ . Thus studies should always specify the regression approach when presenting similarity relations. We suggest use of an orthogonal distance regression method such that uncertainties in $$-z/L$$ are also taken into account, to apply this to the logarithmic transformation of both dimensionless groups, and to use a weighted dataset such that unreliable data points have a smaller influence on the fit. Dividing the dataset into eight height ( $$z$$ ) and eight stability ( $$-{1/L}$$ classes) classes, we show that the observation height and the stability range has an impact on the coefficients too. This implies that variations in $$c_{1}$$ and $$c_{2}$$ found in the literature may result from variations in the height and stability ranges among the datasets. Furthermore, application of the coefficients on a dataset obtained at a different height or within a different stability range has to be made with care. Finally, the variation in the coefficients between the classes indicates that the Monin–Obukhov similarity function for $$C_{T}^2$$ is not sufficiently described by the two-coefficient function used here.

Many cities have expanded during the 20th century, and consequently some weather stations are currently located closer to cities than before. Due to the urban heat island (UHI) effect, those weather stations may show a positive bias in their 2-m temperature record. In this study, we estimate the impact of urbanization on the temperature record of WMO station De Bilt (The Netherlands). This station has a long historical record, but the nearby city of Utrecht and its suburbs expanded during the 20th century. The temperature rise due to urbanization is estimated by conducting representative mesoscale model simulations for the land-use situation for the years 1900 and 2000. This is performed for 14 different episodes of a week, each representing a typical large-scale flow regime (Grosswettertypes) in both the winter and the summer season. Frequency distributions of these flow regimes are used to estimate an average temperature rise. We find that the model results with two rather different atmospheric boundary-layer schemes, robustly indicate that the urbanization during the 20th century has resulted in a temperature rise of 0.22 ± 0.06 K. This is more than a factor of 2 higher than a previously estimated temperature trend by using observed temperature records of stations close to De Bilt.

We evaluated the performance of the three-dimensional Weather Research and Forecasting (WRF) mesoscale model, specifically the performance of the planetary boundary-layer (PBL) parametrizations. For this purpose, Cabauw tower observations were used, with the study extending beyond the third GEWEX Atmospheric Boundary-Layer Study (GABLS3) one-dimensional model intercomparison. The WRF model (version 3.4.1) contains 12 different PBL parametrizations, most of which have been only partially evaluated. The GABLS3 case offers a clear opportunity to evaluate model performance, focusing on time series of near-surface weather variables, radiation and surface flux budgets, vertical structure and the nighttime inertial oscillation. The model results revealed substantial differences between the PBL schemes. Generally, non-local schemes tend to produce higher temperatures and higher wind speeds than local schemes, in particular, for nighttime. The WRF model underestimates the 2-m temperature during daytime (about $$2$$ K) and substantially underestimates it at night (about $$4$$ K), in contrast to the previous studies where modelled 2-m temperature was overestimated. Considering the 10-m wind speed, during the night turbulent kinetic energy based schemes tend to produce lower wind speeds than other schemes. In all simulations the sensible and latent heat fluxes were well reproduced. For the net radiation and the soil heat flux we found good agreement with daytime observations but underestimations at night. Concerning the vertical profiles, the selected non-local PBL schemes underestimate the PBL depth and the low-level jet altitude at night by about 50 m, although with the correct wind speed. The latter contradicts most previous studies and can be attributed to the revised stability function in the Yonsei University PBL scheme. The local, turbulent kinetic energy based PBL schemes estimated the low-level jet altitude and strength more accurately. Compared to the observations, all model simulations show a similar structure for the potential temperature, with a consistent cold bias ( $$\approx $$ 2 K) in the upper PBL. In addition to the sensitivity to the PBL schemes, we studied the sensitivity to technical features such as horizontal resolution and domain size. We found a substantial difference in the model performance for a range of 12, 18 and 24 h spin-up times, longer spin-up time decreased the modelled wind speed bias, but it strengthened the negative temperature bias. The sensitivity of the model to the vertical resolution of the input and boundary conditions on the model performance is confirmed, and its influence appeared most significant for the non-local PBL parametrizations.

In this article we study the relation between the urban heat island (UHI) in the urban canyon and street geometry, in particular the aspect ratio. Model results and observations show that two counteracting processes govern the relation between the nocturnal UHI and the building aspect ratio: i.e. trapping of long-wave radiation and shadowing effects. In general, trapping of long-wave radiation supports the UHI, whereas shadowing effects reduce the UHI. The net effect depends on the UHI definition and the amount of available short-wave radiation penetrating the canyon. In summer, autumn and spring the shadowing effects can already reduce the UHI starting at an aspect ratio between 0.5 and 1. The analysis is carried out using several methods. Firstly, the single-column model version of the Weather Research and Forecasting (WRF) model is used extensively. Two separate runs, one rural and one urban, are used to estimate the UHI. Secondly, the urban canyon temperature at the 2 m level is introduced, which allows for direct comparison between modelled and observed air temperatures within the urban canyon. Finally, the model is evaluated for all four seasons. The results of this research provide important insights for urban planning on how to use the aspect ratio to mitigate the UHI in the urban canyon.

Novel bicycle traverse meteorological measurements were made in Rotterdam to assess the spatial variation of temperature during a tropical day. Nocturnal spatial urban temperature differences of 7?K were found to be related to city morphology. The coolest residential areas were green low-density urban areas. During midday measurements the downtown was up to 1.2?K warmer than the surrounding rural area while a city park was 4.0?K cooler than downtown. A regression analysis showed that the nocturnal measured urban heat island (UHI) can be linked to land use, namely plan area fraction of vegetation, built up area water and is most significant for vegetation. The vegetated area was derived from visible and near infrared aerial images. Neighbourhoods with vegetation (within an upwind radius of 700?m) had a significantly reduced UHI during the night. From the traverse observation data a multiple linear regression model was constructed and independently validated with 3-year summertime UHI statistics derived from 4 urban fixed meteorological stations. In addition, two fixed rural stations were used; a WMO station at Rotterdam airport and a rural station further away from the city. Wind rose analysis shows that UHI is strongest from easterly directions and that the temperature signal of the WMO station is influenced by an UHI signal from both the airport runways and urban directions. A regression model reproduced the nighttime spatial variability of the UHI within a fractional bias of 4.3% and was used to derive an UHI map of Rotterdam and surroundings. This map shows that high density urban configurations lacking greenery or close to large water bodies are vulnerable to high nocturnal temperatures during heat waves. This warming effect of water bodies is also evident for an urban weather station located in the harbor area, which had a similar nocturnal UHI frequency distribution as the downtown urban weather station. The UHI map can be used as a valuable planning tool for mitigating nocturnal urban heat stress or identifying neighborhoods at risk during heat waves.

The atmospheric boundary layer (ABL) plays a dominant role in the exchange of energy, water vapour, trace gases and momentum between the earth’s surface and the overlying atmosphere. Consequently, the ABL is an important part of any numerical model in use for atmospheric and climate research, for operational weather forecasting, and for air - quality and wind - energy studies. For all these applications an overall representation is needed for boundary-layer turbulence and near-surface processes, as well as for vertical diffusion above the boundary layer. This representation is typically referred as the parametrization of vertical diffusion and turbulent mixing. It appears that models at various research groups and operational centres use rather different methods to represent turbulence and vertical diffusion and the reasons behind this diversity are not that easy to unravel. Most likely, this originates for historical reasons due to the outcome of various tuning exercises and to the num

The bulk Richardson number ( $$Ri_{Bh}$$ ; defined over the entire stable boundary layer) is commonly utilized in observational and modelling studies for the estimation of the boundary-layer height. Traditionally, $$Ri_{Bh}$$ is assumed to be a quasi-universal constant. Recently, based on large-eddy simulation and wind-tunnel data, a stability-dependent relationship has been proposed for $$Ri_{Bh}$$ . In this study, we analyze extensive observational data from several field campaigns and provide further support for this newly proposed relationship.