R.J. Ronda

The Challenge of Forecasting the Onset and Development of Radiation Fog Using Mesoscale Atmospheric Models

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.

Cool city mornings by urban heat

The urban heat island effect is a phenomenon observed worldwide, i.e. evening and nocturnal temperatures in cities are usually several degrees higher than in the surrounding countryside. In contrast, cities are sometimes found to be cooler than their rural surroundings in the morning and early afternoon. Here, a general physical explanation for this so-called daytime urban cool island (UCI) effect is presented and validated for the cloud-free days in the BUBBLE campaign in Basel, Switzerland. Simulations with a widely evaluated conceptual atmospheric boundary-layer model coupled to a land-surface model, reveal that the UCI can form due to differences between the early morning mixed-layer depth over the city (deeper) and over the countryside (shallower). The magnitude of the UCI is estimated for various types of urban morphology, categorized by their respective local climate zones.

Land Surface Feedbacks on Spring Precipitation in the Netherlands

AbstractIn this paper, the Weather Research and Forecasting (WRF) Model is used to investigate the sensitivity of precipitation to soil moisture and urban areas in the Netherlands. The average output of a 4-day event during 10–13 May 1999 for which the individual days had similar synoptical forcing is analyzed. Four simulations are conducted to test the impact of soil moisture changes on precipitation. A positive soil moisture–precipitation feedback is found, that is, wet (dry) soils increase (decrease) the amount of precipitation. Three additional experiments are executed, two in which urban areas in the Netherlands are expanded and one where urban areas are completely removed. Expansion of urban areas results in an increase of the sensible heat flux and a deeper planetary boundary layer, similar to reducing soil moisture. Expanding urban areas reduces precipitation over the Netherlands as a whole, but the local response is not clear. Within existing urban areas, mean and maximum temperature increases of...

Urban fine-scale forecasting reveals weather conditions with unprecedented detail

CapsuleFeasibility of Numerical Weather Prediction at urban neighborhood and street scales demonstrated for summer conditions in the Amsterdam metropolitan region (Netherlands). As the number of urban dwellers increases from an estimated 4 billion in 2014 to an expected 6.5 billion by 2050 (UN 2014), urbanization is putting an increasing strain on human comfort, productivity and health in cities worldwide.

Urban station data for the city of Amsterdam for the summer of 2015

Urban landscapes impact the lives of urban dwellers by influencing local weather conditions. However, weather forecasting down to the street and neighborhood scale has been beyond the capabilities of Numerical Weather Prediction (NWP) despite that observational systems are now able to monitor urban climate at these scales. In this study, weather forecasts at intra-urban scales were achieved by exploiting recent advances in topographic element mapping and aerial photography as well as looking at detailed mappings of soil characteristics and urban morphological properties, which were subsequently incorporated into a specifically adapted Weather Research and Forecasting model. The urban weather forecasting system was applied to the Amsterdam metropolitan area during the summer of 2015, where it produced forecasts for the city down to the neighborhood level (a few hundred meters). Comparing these forecasts to the dense network of urban weather station observations within the Amsterdam metropolitan region showed that the forecasting system successfully determined the impact of urban morphological characteristics and urban spatial structure on local temperatures including the cooling effect of large water bodies on local urban temperatures. The forecasting system has important practical applications for end-users such as public health agencies, local governments and energy companies. It appears that the forecasting system enables forecasts of events on a neighborhood level where human thermal comfort indices exceeded risk thresholds during warm weather episodes. These results prove that worldwide urban weather forecasting is within reach of NWP, provided that appropriate data and computing resources become available to ensure timely and efficient forecasts

Smartphone App brings human thermal comfort forecast in your hands

DECEMBER 2017 AMERICAN METEOROLOGICAL SOCIETY | W hat activity would you consider doing tomorrow if the weather forecast predicts a temperature of 27°C? Taking your kids or grandparents for a walk, or maybe a good opportunity to visit that new art museum? That walk may become stressful if it is sunny and the path offers little shade along the way. However, on a windy day, or on a route shaded from direct sunlight, such as a narrow street canyon, thermal conditions may be just fine. By utilizing expert knowledge of the combined effects of temperature, humidity, wind speed, and radiation on the human thermal energy balance, it is possible to refine the general forecast to be more site specific about human comfort while outdoors. Climate change (McCarthy et al. 2010, Coumou and Rahmstorf 2012, Coumou and Robinson 2013), urbanization-related heating [the urban heat island effect (UHI)], and recorded excess mortality during recent European heat waves generated an acute awareness for heat-related health risks. The elderly, people with cardiovascular diseases, and outdoor workers are particularly vulnerable (Zander et al. 2015). Accordingly, the need for easily accessible and local forecasting of human thermal comfort is growing. This paper presents a new smartphone app that communicates a location-specific human thermal comfort forecast based on the latest innovations in urban climate and biometeorology, computer science, communication technology, and land-use mapping. The forecasts were evaluated against four years of observations in the Netherlands. Humans are relatively limited in physiological thermoregulation strategies to cope with heat or cold and must rely on choice of clothing, shelter, or behavioral thermoregulation. Such strategies may also affect the choice of outdoor activities. A person’s interpretation of a standard weather forecast is subjective, and various empirical thermal indices to enhance weather forecasts have been introduced. These include the wind chill factor (Osczevski and Bluestein 2005) to quantify wind speed effects on the severity of cold weather conditions and the heat index (Steadman 1979) for hot conditions coupled with the effect of humidity on a perceived temperature scale. Unfortunately, none of these empirical indices build upon a physically sound human thermal energy balance model, and site-specific information, as introduced by urban morphology, has been neglected. Human thermal energy balance modeling has resulted in an “apparent” temperature that combines weather conditions, such as temperature, humidity, wind speed, and radiation. The latest insights are represented in the universal thermal climate index (UTCI) (Blzejczyk et al. 2012, Bröde et al. 2012). The UTCI is favored because it marries a dynamic clothing model and a state-of-the-art thermophysiological model of human heat transfer and temperature regulation (Fiala et al. 2012). The dynamic clothing model is based on what a person would wear according to the outdoor temperature (Havenith et al. 2012). The total human radiation load as part of the human thermal energy balance is expressed by a single temperature known as the mean radiant temperature Tmrt [Fanger 1970; see also sidebar “UTCI and mean radiant temperature Tmrt”]. The UTCI covers the full thermal exposure range Smartphone App Brings Human Thermal Comfort Forecast in Your Hands

Summer in the City: Forecasting and Mapping Human Thermal Comfort in Urban Areas

Urbanization affects human thermal comfort and health, especially for vulnerable groups such as the elderly and people with established health issues. To mitigate adverse thermal comfort and accompanying excess mortality there is an urgent need of tools for forecasting urban thermal comfort on short to medium-ranged time scales. In this use-case, we present the setup of a prototype of a high-resolution forecasting system at a neighborhood scale spatial resolution. The system builds on both traditional data sources, such as height-and terrain maps, and aerial photographs, as innovative datasources like the Dutch cadastre and the Dutch Statistics office. Additionally, crowd sourced temperature observations, special measuring campaigns, and a dense network of meteo stations will be used for validation.