A one-year-long evaluation of a wind-farm parameterisation in HARMONIE-AROME -- Model data

This file contains supporting data for the manuscript "A one-year-long evaluation of a wind-farm parameterisation in HARMONIE-AROME" by van Stratum et al. 2022 in JAMES. - model_output: contains NetCDF files with HARMONIE-AROME for specific columns for the lidar locations, only for the WIPAFF flight comparison the full 3D hourly fields are given for one day. Files containing "DOWA_40h12tg2_fERA5_ptE" are the reference simulations and files containing "DOWA_40h12tg2_fERA5_WF2019_fix" are output from the wind farm parameterisation simulations. - input_HARMONIE_WFP: contains the input files used for the wind farm parameterisation, where wind_turbine_coordinates.tab contains the locations of all wind turbines and the turbine type, and wind_turbine_0XX.tab the cp/ct curves, radius and hub height for each turbine type. The measurements used in the manuscript are from various external sources and should be downloaded separately

A one-year-long evaluation of a wind-farm parameterisation in HARMONIE-AROME -- Model data

This file contains supporting data for the manuscript "A one-year-long evaluation of a wind-farm parameterisation in HARMONIE-AROME" by van Stratum et al. 2022 in JAMES. - model_output: contains NetCDF files with HARMONIE-AROME for specific columns for the lidar locations, only for the WIPAFF flight comparison the full 3D hourly fields are given for one day. Files containing "DOWA_40h12tg2_fERA5_ptE" are the reference simulations and files containing "DOWA_40h12tg2_fERA5_WF2019_fix" are output from the wind farm parameterisation simulations. - input_HARMONIE_WFP: contains the input files used for the wind farm parameterisation, where wind_turbine_coordinates.tab contains the locations of all wind turbines and the turbine type, and wind_turbine_0XX.tab the cp/ct curves, radius and hub height for each turbine type. The measurements used in the manuscript are from various external sources and should be downloaded separately

A One-Year-Long Evaluation of a Wind-Farm Parameterization in HARMONIE-AROME

The need to mitigate climate change will boost the demand for renewable energy and lead to more wind turbines both on- and offshore. In the near future, the effect these wind farms have on the atmosphere can no longer be neglected. In numerical weather prediction models wind-farm parameterisations (WFP) can be used to model the effect of wind farms on the atmosphere. There are different modeling approaches, but the parameterization developed by Fitch et al. (2012) is mostly used in previous studies. It models the wind farm as a momentum sink and a source of power production and turbulent kinetic energy. In this paper, we have implemented the Fitch et al. (2012) WFP into HARMONIE-AROME, the numerical weather prediction model that is currently used by at least 11 national weather services in Europe. We used HARMONIE-AROME to make year-long simulations for 2016 with and without the WFP. The results were extensively evaluated using lidar, tower and flight measurements at several locations near wind farms. Including the WFP reduces the model bias for wind speed near offshore wind farms. Wind farms not only affect wind, but also temperature and humidity, especially during stable atmospheric conditions: the enhanced mixing caused by the wind turbines reduces the stratification of temperature and humidity. Including the WFP in HARMONIE-AROME results in a more realistic representation of the atmosphere near wind farms and makes it a more future-proof model for weather forecasting

Systematic increases in the thermodynamic response of hourly precipitation extremes in an idealized warming experiment with a convection-permitting climate model

Changes in sub-daily precipitation extremes potentially lead to large impacts of climate change due to their influence on soil erosion, landslides, and flooding. However, these changes are still rather uncertain, with only limited high-resolution results available and a lack of fundamental knowledge on the processes leading to sub-daily extremes. Here, we study the response of hourly extremes in a convection-permitting regional climate model (CPRCM) for an idealized warming experiment—repeating present-day observed weather under warmer and moister conditions. Ten months of simulation covering summer and early autumn for two domains over western Central Europe and western Mediterranean are performed. In general, we obtain higher sensitivities to warming for local-scale extreme precipitation at the original grid-scale of 2.5–3 km than for aggregated analyses at a scale of 12–15 km, representative for currently conventional regional climate models. The grid-scale sensitivity over sea, and in particular over the Mediterranean Sea, approaches 12%–16% increase per degree, close to two times the Clausius–Clapeyron (CC) relation. In contrast, over the dry parts of Spain the sensitivity is close to the CC rate of 6%–7% per degree. For other land areas, sensitivities are in between these two values, with a tendency for the cooler and more humid areas to show lower scaling rates for the most intense hourly precipitation, whereas the land area surrounding the Mediterranean Sea shows the opposite behaviour with the largest increases projected for the most extreme hourly precipitation intensities. While our experimental setup only estimates the thermodynamic response of extremes due to moisture increases, and neglects a number of large-scale feedbacks that may temper future increases in precipitation extremes, some of the sensitivities reported here reflect findings from observational trends. Therefore, our results can provide guidance within which to understand recent observed trends and for future climate projections with CPRCMs

Scaling and responses of extreme hourly precipitation in three climate experiments with a convection-permitting model

It is widely recognized that future rainfall extremes will intensify. This expectation is tied to the Clausius-Clapeyron (CC) relation, stating that the maximum water vapour content in the atmosphere increases by 6-7% per degree warming. Scaling rates for the dependency of hourly precipitation extremes on near-surface (dew point) temperature derived from day-to-day variability have been found to exceed this relation (super-CC). However, both the applicability of this approach in a long-term climate change context, and the physical realism of super-CC rates have been questioned. Here, we analyse three different climate change experiments with a convection-permitting model over Western Europe: simple uniform-warming, 11-year pseudo-global warming and 11-year global climate model driven. The uniform-warming experiment results in consistent increases to the intensity of hourly rainfall extremes of approximately 11% per degree for moderate to high extremes. The other two, more realistic, experiments show smaller increases-usually at or below the CC rate-for moderate extremes, mostly resulting from significant decreases to rainfall occurrence. However, changes to the most extreme events are broadly consistent with 1.5-2 times the CC rate (10-14% per degree), as predicted from the present-day scaling rate for the highest percentiles. This result has important implications for climate adaptation. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.Atmospheric Remote Sensin

HCLIM38 : a flexible regional climate model applicable for different climate zones from coarse to convection-permitting scales

This paper presents a new version of HCLIM, a regional climate modelling system based on the ALADIN–HIRLAM numerical weather prediction (NWP) system. HCLIM uses atmospheric physics packages from three NWP model configurations, HARMONIE–AROME, ALARO and ALADIN, which are designed for use at different horizontal resolutions. The main focus of HCLIM is convection-permitting climate modelling, i.e. developing the climate version of HARMONIE–AROME. In HCLIM, the ALADIN and ALARO configurations are used for coarser resolutions at which convection needs to be parameterized. Here we describe the structure and development of the current recommended HCLIM version, cycle 38. We also present some aspects of the model performance. HCLIM38 is a new system for regional climate modelling, and it is being used in a number of national and international projects over different domains and climates ranging from equatorial to polar regions. Our initial evaluation indicates that HCLIM38 is applicable in different conditions and provides satisfactory results without additional region-specific tuning. HCLIM is developed by a consortium of national meteorological institutes in close collaboration with the ALADIN–HIRLAM NWP model development. While the current HCLIM cycle has considerable differences in model setup compared to the NWP version (primarily in the description of the surface), it is planned for the next cycle release that the two versions will use a very similar setup. This will ensure a feasible and timely climate model development as well as updates in the future and provide an evaluation of long-term model biases to both NWP and climate model developers.This research has been supported by Horizon 2020 (EUCP (grant no. 776613)) and the Maj and Tor Nessling foundation

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

The development and application of chemistry transport models has a long tradition. Within the Netherlands the LOTOS–EUROS model has been developed by a consortium of institutes, after combining its independently developed predecessors in 2005. Recently, version 2.0 of the model was released as an open-source version. This paper presents the curriculum vitae of the model system, describing the model's history, model philosophy, basic features and a validation with EMEP stations for the new benchmark year 2012, and presents cases with the model's most recent and key developments. By setting the model developments in context and providing an outlook for directions for further development, the paper goes beyond the common model description. With an origin in ozone and sulfur modelling for the models LOTOS and EUROS, the application areas were gradually extended with persistent organic pollutants, reactive nitrogen, and primary and secondary particulate matter. After the combination of the models to LOTOS–EUROS in 2005, the model was further developed to include new source parametrizations (e.g. road resuspension, desert dust, wildfires), applied for operational smog forecasts in the Netherlands and Europe, and has been used for emission scenarios, source apportionment, and long-term hindcast and climate change scenarios. LOTOS–EUROS has been a front-runner in data assimilation of ground-based and satellite observations and has participated in many model intercomparison studies. The model is no longer confined to applications over Europe but is also applied to other regions of the world, e.g. China. The increasing interaction with emission experts has also contributed to the improvement of the model's performance. The philosophy for model development has always been to use knowledge that is state of the art and proven, to keep a good balance in the level of detail of process description and accuracy of input and output, and to keep a good record on the effect of model changes using benchmarking and validation. The performance of v2.0 with respect to EMEP observations is good, with spatial correlations around 0.8 or higher for concentrations and wet deposition. Temporal correlations are around 0.5 or higher. Recent innovative applications include source apportionment and data assimilation, particle number modelling, and energy transition scenarios including corresponding land use changes as well as Saharan dust forecasting. Future developments would enable more flexibility with respect to model horizontal and vertical resolution and further detailing of model input data. This includes the use of different sources of land use characterization (roughness length and vegetation), detailing of emissions in space and time, and efficient coupling to meteorology from different meteorological models

Water table depth modulates productivity and biomass across Amazonian forests

Aim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change

Water table depth modulates productivity and biomass across Amazonian forests

Aim: Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location: Lowland Amazonian forests. Time period: 1971–2019. Methods: We used 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water and edaphic properties. Results: Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above-ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. Main conclusions: We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra-firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change