Cities in northwestern Europe face increasingly extreme summer heat under climate change, intensifying the need for effective neighbourhood-scale heat mitigation strategies. Using hectometric (100 m) idealized Weather Research and Forecasting (WRF) simulations during three extreme heat events, this study examines how urban blue space configuration, atmospheric forcing, and physical mechanisms regulate air temperature and thermal comfort (wet-bulb globe temperature index) across coastal and inland cities. We assess how surface energy fluxes interact with horizontal advection to propagate cooling beyond waterbodies, while evaluating whether WRF-Lake produces physically realistic outputs for small, shallow urban blue spaces. Our simulations show near-surface horizontal advection as the dominant cooling mechanism, mixing cooler air from blue spaces with warmer urban air. Around midday, this provides approximately 50 W⋅ m−2 cooling potential, amplified by evaporative cooling enhanced by urban-generated turbulence. Daily mean temperature reductions ranged from −0.1◦C to −0.4◦C, with peak morning effectiveness reaching −1.0◦C in coastal areas. Wind speed emerged as the primary control: moderate winds (4.7–5.8 m⋅ s−1) propagated cooling citywide, extending up to three times the city diameter downwind, whereas light winds (1.2 m⋅ s−1) limited cooling locally. Randomly distributed waterbodies created more homogeneous cooling than canal configurations. Thermal comfort analysis revealed a critical temperature–humidity trade-off. Factor analysis (R2 = 0.93) showed air temperature cooling (50.3%) is counteracted by increased relative humidity (42.3%).We identified limitations of WRF-Lake for shallow urban blue spaces. Default roughness lengths underestimate turbulence and fluxes, likely underestimating cooling and causing unrealistic water temperature increases. This underscores the need for improved parametrizations and targeted observations to advance urban hydrometeorological modelling. ... Read more

This opinion paper reflects on the current challenges facing urban drainage systems (UDS) research, along with solutions for fostering sustainable development. Over the course of a year-long project involving 92 participants aged 24-38, including PhD candidates, post-doctoral researchers, and early-career academics, we identified critical challenges and opportunities for the sustainable development of UDS. Our exploration highlights four key challenges: limited public visibility leading to resource constraints, insufficient collaboration across subfields, issues with data scarcity and data sharing, and geographical specificities. We emphasise the importance of raising public and political awareness regarding UDS's vital role in climate adaptation and urban resilience, advocating for blue-green infrastructure and open data practices. Additionally, we address systemic academic barriers that hinder innovative research. We call for a shift away from metrics that prioritise quantity over quality. We recommend establishing stable career pathways that empower early-career researchers. This paper aims to catalyse a broader community dialogue about the future of UDS research, uniting voices from various career stages. By presenting actionable recommendations, we aim to inspire fundamental changes in research conduct, evaluation, and sustainability, ensuring the field of UDS is prepared to meet pressing urban water management challenges worldwide. ... Read more

Urban areas, characterized by dense populations and many socio-economic activities, increasingly suffer from floods, droughts, and heat stress due to land use and climate change. Traditionally, the urban thermal environment and water resources management have been studied separately, using urban land surface models (ULSMs) and urban hydrological models (UHMs). However, as our understanding deepens and the urgency to address future climate disasters grows, it becomes clear that hydrological disasters—such as floods, droughts, severe urban thermal environments, and more frequent heat waves—are actually not isolated events but compound events. This underscores the close interaction between the water cycle and the energy balance. Consequently, the existing separation between ULSMs and UHMs creates significant obstacles to better understanding urban hydrological and meteorological processes, which is crucial for addressing the high risks posed by climate change. Defining the future direction of process-based models for hydro-meteorological predictions and assessments is essential for better managing climate disasters and evaluating response measures in densely populated urban areas. Our review focuses on three critical aspects of urban hydro-meteorological simulation: similarities, differences, and gaps among different models; existing gaps in physical process implementations; and efforts, challenges, and potential for model coupling and integration. We find that ULSMs inadequately represent water surfaces and hydraulic systems, while UHMs lack explicit surface energy balance solutions and detailed building representations. Coupled models show potential for simulating urban hydro-meteorological environments, but face challenges at regional and neighborhood scales. Our review highlights the need for interdisciplinary communication between the urban climatology and urban water management communities to enhance urban hydro-meteorological simulation models. ... Read more

Accurate rainfall observations with high spatial and temporal resolutions are key for hydrological applications, in particular for reliable flood forecasts. However, rain gauge networks operated by regional or national environmental agencies are often sparse, and weather radars tend to underestimate rainfall. As a complementary source of information, rain gauges from personal weather stations (PWSs), which have a network density 100 times higher than dedicated rain gauge networks in the Netherlands, can be used. However, PWSs are prone to additional sources of error compared to dedicated gauges, because they are generally not installed and maintained according to international guidelines. A systematic long-term analysis involving PWS rainfall observations across different seasons, accumulation intervals, and rainfall intensity classes has been missing so far. Here, we quantitatively compare rainfall estimates obtained from PWSs with rainfall recorded by automatic weather stations (AWSs) from the Royal Netherlands Meteorological Institute (KNMI) over the 2018–2023 period, including a sample of 1760 individual rainfall events in the Netherlands. This sample consists of the 10 highest rainfall accumulations per season and accumulation intervals (1, 3, 6, and 24 h) over a 6-year period. It was found that the average of a cluster of PWSs severely underestimates rainfall (around 36 % and 19 % for 1 h and 24 h intervals, respectively). By adjusting the data with areal reduction factors to account for the spatial variability of rainfall extremes and applying a bias correction factor of 1.22 to compensate for instrumental bias, the average relative bias decreases to −5 % for 1 h intervals or almost zero for intervals of 3 h and longer. The highest correlations (0.85 and 0.86) and lowest coefficients of variation (0.14 and 0.18) were found for 24 h intervals during winter and autumn, respectively. We show that most PWSs are able to capture high rainfall intensities up to around 30 mm h−1, indicating that these can be utilized for applications that require rainfall data with a spatial resolution of the order of kilometres, such as for flood forecasting in small, fast-responding catchments. PWSs did not observe the most intense rainfall events, which were associated with return periods exceeding 10 or 50 years (above approximately 30 mm h−1) and occurred in spring and summer. However, the spatial distribution of rainfall likely played a large role in the observed differences rather than instrumental limitations. This emphasizes the importance of having a dense rain gauge network. In addition, the variation in undercatch is likely partly due to the disproportional underestimation of tipping bucket rain gauges with increasing intensities. Outliers during winter were likely caused by solid precipitation and can potentially be removed using a temperature module from the PWS. We recommend additional research on dynamic calibration of the tipping volumes to improve this further. ... Read more

Part of TU Delft’s Climate Action program is developing climate action pedagogies at the classroom and course levels. This contribution presents our open pedagogical language that shares evidence-informed instructional design principles and teaching practices in which students not only learn about urban climate change and sustainability but, in particular, about intervening in society or industry (action!) and its effects in everyday practice. In addition to technical system knowledge, this type of education provides students with crucial ecological and social entrepreneurship skills.

The building blocks of this language are so-called pedagogical patterns, which describe a specific (set of) instructional design principle(s) of a course or classroom setting. Each pattern is presented in a comparable way via a given template that asks for [i] a title, [ii] an illustration, [iii] a hypothesis or statement on the value this pattern brings, [iv] the evidence from teaching practice and/or the educational scientific knowledge supporting the pattern, [v] a brief description of practical implications when implementing or using the pattern, [vi] the relation to other patterns. Pedagogical patterns are not prescriptive; they show what educators could do pedagogically.

Our first pedagogical patterns are based on the teaching practices of our Delft Climate Action educators and focus on:
*citizen science approaches focusing on the adaptation of the urban area to the weather and climate of tomorrow.
*interdisciplinarity for climate adaptivity in urbanised delta regions, where students work for and with a local government or stakeholder related to urban heat, drought, air pollution, and flooding.
* entrepreneurship in the built environment, where students develop a design and entrepreneurial plan for a sustainability challenge.
* action research focusing on socio-spatial inequality, diversity, resilience, and well-being for a climate challenge in a collaborative way with practitioners and community members. ... Read more

The Urban Wind Island (UWI), a small but persistent positive mean boundary-layer wind anomaly over the city as a whole, has previously been revealed using a simplified conceptual model of the convective atmospheric boundary layer. This study extends the UWI research into less idealised cases by using the three-dimensional WRF mesoscale model for Amsterdam (The Netherlands) and its surroundings, at 500 m grid spacing. Two summers of forecast results for in total 173 days are used to identify whether the UWI persists in a three-dimensional modelling environment, and which conditions are optimal for its formation and persistence. In order to focus only on wind modified by surface processes, large-scale influences which modify wind speed, such as frontal passages, are identified and eliminated from the dataset. We then find that a positive UWI is present roughly half the time, with an order of magnitude that is similar to the previous work (∼ 0.2–0.5 ms⁻¹). In addition we find an evening UWI that is caused by the delayed onset of the transition from an unstable to a stable or a neutral boundary layer in the urban area, while the rural area is already stable and calm. ... Read more

Urban areas, characterized by dense populations and many socioeconomic activities, increasingly suffer from floods, droughts and heat stress due to land use and climate change. Traditionally, the urban thermal environment and water resource management have been studied separately, using urban land-surface models (ULSMs) and urban hydrological models (UHMs). However, as our understanding deepens and the urgency to address future climate disasters grows, it becomes clear that hydroclimatological extremes – such as floods, droughts, severe urban thermal environments and more frequent heat waves – are actually not always isolated events but can be compound events. This underscores the close interaction between the water cycle and the energy balance. Consequently, the existing separation between ULSMs and UHMs creates significant obstacles in better understanding urban hydrological and meteorological processes, which is crucial for addressing the high risks posed by climate change. Defining the future direction of process-based models for hydrometeorological predictions and assessments is essential for better managing extreme events and evaluating response measures in densely populated urban areas. Our review focuses on three critical aspects of urban hydrometeorological simulation: similarities, differences and gaps among different models; existing gaps in physical process implementations; and efforts, challenges and potential for model coupling and integration. We find that ULSMs inadequately represent water surfaces and hydraulic systems, while UHMs lack explicit surface energy balance solutions and detailed building representations. Coupled models show the potential for simulating urban hydrometeorological environments but face challenges at regional and neighbourhood scales. Our review highlights the need for interdisciplinary communication between the urban climatology and the urban water management communities to enhance urban hydrometeorological simulation models. ... Read more

The Dutch citizen science project Delft Measures (https://bit.ly/DelftMeasures) focuses on the collaboration between citizens, local institutions, and NGOs to map the weather and changing climate in the city of Delft. It has been running for 4 years, during which citizens of Delft measure long-term changes in rainfall patterns, temperature, and now also soil moisture in their private gardens. Currently, there are over 45 of the Alecto WS5500 citizen-science weather stations spread across neighborhoods in Delft, capturing rainfall variability in different urban microclimates. But in the past years, more than 100 different inhabitants have already been engaged and have helped to collect data.

The data is used by a diverse number of organizations like the National Meteorological Institute, the Delft University of Technology and the Delft Municipality, to answer different scientific, engineering, or policy questions. We collaborate with multiple NGOs in project execution. Considering the diverse interests of all stakeholders, the project addresses a variety of goals from education to improving climate adaptation to implementing open science practices.

All in all, the project grew into a successful co-creation between many different partners. Delft Measures has been growing and changing and it managed to reach a consistent base of enthusiastic citizens that support the goals of the project, engaging them in making changes in the city for climate change adaptation. For Delft, as a city below sea level, this means a better drainage network to deal with the larger showers of summer rain, while retaining water during longer periods of drought. By setting up secure collaborations with the municipality and university, the data citizens collect is used as direct input for the (future) efficiency of the municipality’s city-wide sewer and drainage network. For the university, this is valuable for education and research into how city infrastructure influences local weather patterns and the variability of rainfall, to understand better where high-intensity rainfall events will have the highest effect. Currently, such high spatial resolution on rainfall in cities is scarce. Additionally, the project functions as a case study for the university’s Open Science program, aiming to evaluate the implementation of open science practices in local citizen science projects, while NGOs invested in climate change adaptation in the city roll up their sleeves to help citizens make the practical changes needed for our new climate.

We are currently in the process of writing down the ‘recipe’ of Delft Measures, to help other cities implement similar projects and not to have to reinvent the wheel. We would like to share this recipe during this session, where we will answer questions such as how we manage to collect useful information and increase community involvement and awareness, what kind of participatory approaches we implemented to facilitate community involvement, how we tackle legitimate concerns about potential data biases, inaccuracies and how we ensure the long-term sustainability of the project. ... Read more

Monitoring, reporting, and verification frameworks for greenhouse gas emissions are being developed by countries across the world to keep track of progress towards national emission reduction targets. Data assimilation plays an important role in monitoring frameworks, combining different sources of information to achieve the best possible estimate of fossil fuel emissions and, as a consequence, better estimates for fluxes from the natural biosphere. Robust estimates for fossil fuel emissions rely on accurate estimates of uncertainties corresponding to different pieces of information. We describe prior uncertainties in CO2 and CO fossil fuel fluxes, paying special attention to spatial error correlations and the covariance structure between CO2 and CO. This represents the first time that prior uncertainties in CO2 and the important co-emitted trace gas CO are defined consistently, with error correlations included, which allows us to make use of the synergy between the two trace gases to better constrain CO2 fossil fuel fluxes. CO:CO2 error correlations differ by sector, depending on the diversity of sub-processes occurring within a sector, and also show a large range of values between pixels within the same sector. For example, for other stationary combustion, pixel correlation values range from 0.1 to 1.0, whereas for road transport, the correlation is mostly larger than 0.6. We illustrate the added value of our definition of prior uncertainties using closed-loop numerical experiments over mainland Europe and the UK, which isolate the influence of using error correlations between CO2 and CO and the influence of prescribing more detailed information about prior emission uncertainties. For the experiments, synthetic in situ observations are used, allowing us to validate the results against a “truth”. The “true” emissions are made by perturbing the prior emissions (from an emission inventory) according to the prescribed prior uncertainties. We find that using our realistic definition of prior uncertainties helps our data assimilation system to differentiate more easily between CO2 fluxes from biogenic and fossil fuel sources. Using improved prior emission uncertainties, we find fewer geographic regions with significant deviations from the prior compared to when using default prior uncertainties (32 vs. 80 grid cells of 0.25°×0.3125°, with an absolute difference of more than 1 kg s−1 between the prior and posterior), but these deviations from the prior almost consistently move closer to the prescribed true values, with 92 % showing an improvement, in contrast to the default prior uncertainties, where 61 % show an improvement. We also find that using CO provides additional information on CO2 fossil fuel fluxes, but this is only the case if the CO:CO2 error covariance structure is defined realistically. Using the default prior uncertainties, the CO2 fossil fuel fluxes move farther away from the truth in many geographical regions (with 50 % showing an improvement compared to 94 % when advanced prior uncertainties are used). With the default uncertainties, the maximum deviation of fossil fuel CO2 from the prescribed truth is about 7 % in both the prior and posterior results. With the advanced uncertainties, this is reduced to 3 % in the posterior results. ... Read more

The Delft Measures Rain Citizen-Science programme has been running for several years in the city of Delft, the Netherlands. Within this programme, interested citizens can apply to receive a low-cost Alecto WS5500 weather station, to measure local meteorological parameters in their own garden. Currently there are over 45 of these citizen-science weather stations spread across neighbourhoods in Delft, capturing rainfall variability in different urban microclimates. However, the scientific quality of these specific stations has never been tested, and from previous work we know that rigorous quality assurance is necessary in order to get meaningful (precipitation) data. Thus we have installed 8 Alecto stations in The Green Village outdoors urban climate field lab at the TU Delft. Stations have been explicitly installed in ways that a citizen might do: slightly tilted, next to a wall (simulating the limited open garden space of a Dutch urban residence), on top of a shed as well as free-standing. These different measurement setups, combined with a row of stations installed in the same way right next to one another, allow us to investigate the bias caused by less-than-ideal station installation, as well as systematic errors related to the tipping bucket mechanism and sensor drifts. Initial results show a general overestimation of the Alecto compared to reference stations and radar observations, and a discernible negative bias caused by sheltering effects of plants and, to a lesser extent by walls. ... Read more

Under the Paris Agreement, countries report their anthropogenic greenhouse gas emissions in national inventories, which are used to track progress towards mitigation goals, but they must be independently verified. Atmospheric observations of CO2, interpreted using inverse methods, can potentially provide that verification. Conventional CO2 inverse methods infer natural CO2 fluxes by subtracting a priori estimates of fuel combustion from the a posteriori net CO2 fluxes, assuming that a priori knowledge for combustion emissions is better than for natural fluxes. We describe an inverse method that uses measurements of CO2 and carbon monoxide (CO), a trace gas that is co-emitted with CO2 during combustion, to report self-consistent combustion emissions and natural fluxes of CO2. We use an ensemble Kalman filter and the GEOS-Chem atmospheric transport model to explore how satellite observations of CO and CO2 collected by the TROPOspheric Monitoring Instrument (TROPOMI) and Orbiting Carbon Observatory-2 (OCO-2), respectively, can improve understanding of combustion emissions and natural CO2 fluxes across the UK and mainland Europe in 2018–2021. We assess the value of using satellite observations of CO2, with and without CO, above what is already available from the in situ network. Using CO2 satellite observations leads to small corrections to a priori emissions that are inconsistent with in situ observations, due partly to the insensitivity of the atmospheric CO2 column to CO2 emission changes. When we introduce satellite CO observations, we find better agreement with our in situ inversion and a better model fit to atmospheric CO2 observations. Our regional mean a posteriori combustion CO2 emission ranges from 4.6–5.0 Gt a−1 (1.5 %–2.4 % relative standard deviation), with all inversions reporting an overestimate for Germany's wintertime emissions. Our national a posteriori CO2 combustion emissions are highly dependent on the assumed relationship between CO2 and CO uncertainties, as expected. Generally, we find better results when we use grid-scale-based a priori CO2:CO uncertainty estimates rather than a fixed relationship between the two species. ... Read more

Microwave backhaul links from cellular communication networks provide a valuable “opportunistic” source of high-resolution space–time rainfall information, complementing traditional in situ measurement devices (rain gauges, disdrometers) and remote sensors (weather radars, satellites). Over the past decade, a growing community of researchers has, in close collaboration with cellular communication companies, developed retrieval algorithms to convert the raw microwave link signals, stored operationally by their network management systems, to hydrometeorologically useful rainfall estimates. Operational meteorological and hydrological services as well as private consulting firms are showing an increased interest in using this complementary source of rainfall information to improve the products and services they provide to end users from different sectors, from water management and weather prediction to agriculture and traffic control. The greatest potential of these opportunistic environmental sensors lies in those geographical areas over the land surface of the Earth with few rain gauges and no weather radars: often mountainous and urban areas, but especially low- to middle-income regions, which are generally in (sub)tropical climates.

Here, the open-source R package RAINLINK is employed to retrieve CML rainfall maps covering the majority of Sri Lanka, a middle-income country having a tropical climate. This is performed for a 3.5-month period based on CML data from on average 1140 link paths. CML rainfall maps are compared locally to hourly and daily rain gauge data, as well as to rainfall maps from the Dual-frequency Precipitation Radar on board the Global Precipitation Measurement Core Observatory satellite. The results confirm the potential of CMLs for real-time tropical rainfall monitoring. This holds a promise for, e.g., ground validation of or merging with satellite precipitation products. ... Read more

Several opportunistic sensors (private weather stations, commercial microwave links and smartphones) are employed to obtain weather information and successfully monitor urban weather events. The ongoing urbanisation and climate change urges further understanding and monitoring of weather in cities. Two case studies during a 17-day period over the Amsterdam metropolitan area, the Netherlands, are used to illustrate the potential and limitations of hydrometeorological monitoring using non-traditional and opportunistic sensors. We employ three types of opportunistic sensing networks to monitor six important environmental variables: (1) air temperature estimates from smartphone batteries and personal weather stations; (2) rainfall from commercial microwave links and personal weather stations; (3) solar radiation from smartphones; (4) wind speed from personal weather stations; (5) air pressure from smartphones and personal weather stations; (6) humidity from personal weather stations. These observations are compared to dedicated, traditional observations where possible, although such networks are typically sparse in urban areas. First we show that the passage of a front can be successfully monitored using data from several types of non-traditional sensors in a complementary fashion. Also we demonstrate the added value of opportunistic measurements in quantifying the Urban Heat Island (UHI) effect during a hot episode. The UHI can be clearly determined from personal weather stations, though UHI values tend to be high compared to records from a traditional network. Overall, this study illustrates the enormous potential for hydrometeorological monitoring in urban areas using non-traditional and opportunistic sensing networks. ... Read more

The use of crowdsourcing – obtaining large quantities of data through the Internet – has been of great value in urban meteorology. Crowdsourcing has been used to obtain urban air temperature, air pressure, and precipitation data from sources such as mobile phones or personal weather stations (PWSs), but so far wind data have not been researched. Urban wind behaviour is highly variable and challenging to measure, since observations strongly depend on the location and instrumental set-up. Crowdsourcing can provide a dense network of wind observations and may give insight into the spatial pattern of urban wind. In this study, we evaluate the skill of the popular “Netatmo” PWS anemometer against a reference for a rural and an urban site. Subsequently, we use crowdsourced wind speed observations from 60 PWSs in Amsterdam, the Netherlands, to analyse wind speed distributions of different Local Climate Zones (LCZs). The Netatmo PWS anemometer appears to systematically underestimate the wind speed, and episodes with rain or high relative humidity degrade the measurement quality. Therefore, we developed a quality assurance (QA) protocol to correct PWS measurements for these errors. The applied QA protocol strongly improves PWS data to a point where they can be used to infer the probability density distribution of wind speed of a city or neighbourhood. This density distribution consists of a combination of two Weibull distributions, rather than the typical single Weibull distribution used for rural wind speed observations. The limited capability of the Netatmo PWS anemometer to measure near-zero wind speed causes the QA protocol to perform poorly for periods with very low wind speeds. However, results for a year-long wind speed climatology of the wind speed are satisfactory, as well as for a shorter period with higher wind speeds. ... Read more

Since 2012, Local Climate Zones (LCZ) have been used for numerous studies related to urban environment. In 2015, this use amplified because a method to map urban areas in LCZs was introduced by the World Urban Database and Access Portal Tools (WUDAPT). However in 2017, the first HUMan INfluence EXperiment showed that these maps often have poor or low quality. Since the maps are used in different applications such as urban modelling and land use/land cover change studies, it is of the utmost importance to improve mapping accuracies and a second experiment was launched. In HUMINEX 2.0, the focus lies on providing guidelines on the use of the mapping protocol based on the results of both HUMINEX 1.0 and 2.0. The results showed that: (1) it is important to follow the mapping protocol as strictly as possible, (2) a reasonable amount of time should be spent on the mapping procedure, (3) all users should perform a driving test, and (4) training area sets should be stored in the WUDAPT database for other users. ... Read more

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. ... Read more