4-9 September 2022, Bonn, Germany
Enter gather.town

OSA1.7

The Weather Research and Forecasting Model (WRF): development, research and applications

The Weather Research and Forecasting model (WRF) is a widely used high-resolution meteorological model for operational weather forecasting, fundamental and applied research in meteorology, air quality, wind energy engineering, and consultancy studies. Its user’s community consists of universities, weather forecasters, and consultancy agencies world-wide. The goal of this session is to create a European forum to discuss research results concerning all aspects of the WRF and MPAS modelling frameworks.
Papers are invited on:
• Initialization, and meteorological and land surface boundary conditions.
• Numerical and grid spacing aspects
• Studies concerning data assimilation.
• Development of physical parameterization schemes.
• Model evaluation and validation against a broad range of available observations.
• Future WRF development.
• Tailored WRF versions, e.g. polar WRF, WRF-LES, WRF-Chem, H-WRF, the WRF single-column model
• WRF applications in weather forecasting, air quality studies, wind energy engineering.
• Regional climate studies
• Mesoscale meteorological phenomena studied with WRF.
• Analogous studies using Model for Prediction Across Scales (MPAS)

Convener: Gert-Jan Steeneveld | Co-convener: Arianna Valmassoi
Orals
| Wed, 07 Sep, 14:00–17:00 (CEST)|Room HS 5-6
Posters
| Attendance Thu, 08 Sep, 11:00–13:00 (CEST) | Display Thu, 08 Sep, 08:00–Fri, 09 Sep, 14:00|b-IT poster area

Thu, 8 Sep, 11:00–13:00

Chairperson: Gert-Jan Steeneveld

EMS2022-144
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Onsite presentation
Sjoerd Barten et al.

Dry deposition is an important removal mechanism for tropospheric ozone (O3). Its deposition to oceans is generally represented in atmospheric chemistry transport models using constant surface uptake resistances. However, observations show quite large spatiotemporal variability expressing differences in solubility, waterside turbulence and O3 reacting with iodide and dissolved organic matter. We hypothesize that for the Arctic O3 deposition is overestimated with consequences for background concentrations and lifetime of O3 also due to changes in long-range transport of O3 and its precursors. These are focal points of a project on observing and modelling of Arctic climate-active trace gas exchange as a contribution to the MOSAiC observational campaign with the icebreaker Polarstern being trapped in the Arctic sea-ice for ~1 year.

We have coupled the Coupled Ocean-Atmosphere Response Experiment Gas transfer algorithm (COAREG) to the mesoscale meteorology and atmospheric chemistry model Polar-WRF-Chem (PWRF-C). This includes a further development including a two-layer scheme for O3 deposition to oceans and coupling to recently updated ocean water composition databases. We have also reduced the deposition of O3 to sea ice based on a previous study of snow-ice O3 deposition.

In this study, we evaluate the performance of PWRF-C with hourly-averaged surface O3 measurements above 60 ºN and with O3 sondes. We show that the more mechanistic representation of O3 deposition over oceans and strongly reduced deposition over snow and ice results in improved simulated Arctic O3 mixing ratios. We found that it is important to nudge PWRF-C to the ECMWF ERA-Interim wind fields which secures a fair comparison of the model with measurements regarding their footprint. Our study indicates that representation of ocean and sea-ice O3 deposition in atmospheric chemistry models must be revised to improve the representation of Arctic O3 concentrations and chemistry.

How to cite: Barten, S., Ganzeveld, L., Steeneveld, G.-J., and Krol, M.: Mechanistic Ocean-Atmosphere exchange of trace gases in Polar-WRF-Chem: Implications for Arctic tropospheric ozone, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-144, https://doi.org/10.5194/ems2022-144, 2022.

EMS2022-369
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Onsite presentation
Zsuzsanna Zempléni et al.

The CORINE land cover dataset provides a more realistic dataset for various scientific applications. In this study we incorporated almost all (38 instead of the original 44 classes, as water classes are not dividable in the WRF routines) CORINE classes to the WRF model and created 1-year long 5 km resolution simulations to check its effects. The simulated area covers the Central European region.

On a closer look, compared to the USGS dataset the first observable differences are the decreased number of non-irrigated croplands that are described as forests. The secondary difference comes in the coverage of urban areas. In some cases, a city previously covered by 2 grid points are now covered by 20, which causes a more pronounced urban heat island (UHI) effect.

Our goal is to analyse the effect of land cover differences on urban heat island intensity by only relying on the NoahMP provided heat flux calculations. For regional climate simulations the application of urban parameterisation could be more computationally demanding. Therefore, we try to assess the feasibility of UHI analysis at such a scale without urban parameterisation.

Urban areas are selected similarly to radar cell tracking, fitting a circle around the urban land cover classes and the rural regions are selected from a double size circle radius if there are no large altitude differences between the urban average altitude and the rural grid point. According to the preliminary results an annual average 1.5 °C UHI can be simulated without urban parameterisation. Principal component analysis shows that the main driver of the UHI is the annual variation of leaf area index in the rural regions. The secondary driver is either the precipitation or the snow cover, depending on the spring and wintertime weather.

How to cite: Zempléni, Z., Varga, Á. J., and Breuer, H.: The effect of the CORINE land cover class application at mid-resolution WRF simulations on urban heat island, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-369, https://doi.org/10.5194/ems2022-369, 2022.

EMS2022-259
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Onsite presentation
Ákos János Varga and Hajnalka Breuer

It has been indicated by multiple studies that the performance of a particular physical parameterization scheme in a numerical model is determined by several factors and displays high spatial and temporal variability. One factor that could potentially lead to distinctive behavior for the different schemes is the large-scale weather situation. Here we aim to answer the following questions: does the performance of the WRF regional climate model with different physical parameterizations depend on the synoptic weather situation? Can simulation results be improved with the utilization of different physics schemes depending on the synoptic weather situation?

To answer these questions, we produce 5-year (2006–2010) regional climate simulations with the WRF model. First, a 50-km simulation is performed using the ERA5 reanalysis as input data. Then, this coarse-resolution run is further downscaled to a set of 10 km simulations with daily re-initialization utilizing different planetary boundary layer (PBL), surface layer, and deep convection schemes. A simulation with the cumulus convection turned off is also included in the analysis.

The weather pattern in the 50-km run for each day is determined based on model-derived relative vorticity at the 500 and 950 hPa isobaric levels (i.e., cyclonic or anticyclonic flow in the upper and lower levels of the atmosphere). Then, we evaluate the performance of the 10-km simulations separately for periods with a specific synoptic pattern prevailing in the driving fields, using the E-OBS dataset as reference. This way, it can be deduced if a physical parameterization is superior to the other for a particular large-scale weather situation. Finally, based on the results of this sensitivity study, we produce further 10-km simulations in which we initialize the 10-km model with different physics schemes each day based on the dominant synoptic pattern in the outer domain.

How to cite: Varga, Á. J. and Breuer, H.: Does the performance of different physical parameterizations in the WRF regional climate model depend on the synoptic weather pattern in the large-scale driving fields?, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-259, https://doi.org/10.5194/ems2022-259, 2022.

EMS2022-328
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Onsite presentation
Frederik Kurzrock et al.

Numerical weather prediction (NWP) models such as the Weather Research and Forecasting (WRF) model allow to forecast cloud processes at high spatio-temporal resolutions of a few kilometres and minutes. Nevertheless, WRF is known to underestimate the presence of clouds, which has negative impacts on solar irradiance forecasts for example. Therefore, drawing the forecasts closer to observations of clouds can be an efficient means for improving hour-scale cloudiness forecasts. Determining precise initial conditions from both observations and model output in terms of clouds is a challenge. This study explores the use of four-dimensional data assimilation (FDDA) nudging to take into account cloud cover observations from an infrared all-sky imager. Experiments with two WRF domains (9 km and 3 km grid spacing), driven by Global Forecasting System (GFS) forecasts, are performed over Central Europe. The cloud cover observations are determined by the Sky InSight, an all-sky infrared imager, installed at the Lindenberg Meteorological Observatory – Richard-Assmann-Observatory (MOL-RAO) in eastern Germany. Compared to observations in the visible range, this instrument has the advantage to deliver cloud cover observations of the same quality at day and night time. The observations are compared to cloud cover values from the WRF background. Depending on the difference between the two, the WRF background humidity profile at the location of the imager is either increased, decreased or unchanged to obtain a new profile for the nudging. Cloud base height values are determined by a ceilometer and empirical values are used for the cloud top height to limit the vertical extent of the derived humidity profiles to be nudged. Reuniwatt’s custom Meteosat Second Generation (MSG) Satellite Application Facility NoWCasting (SAFNWC) cloud products are used to evaluate the impact of the nudging on WRF forecasts of cloud cover. The fast and cost-effective nudging method leads to an improvement of WRF cloud cover forecasts. It could be easily upscaled to a large amount of ground-based camera observations.

How to cite: Kurzrock, F., Hochebner, A., Millerioux, Q., Schmutz, N., Reinhardt, M., Acevedo, W., and Potthast, R.: Hour-scale cloud cover forecasting using WRF and an infrared all-sky imager, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-328, https://doi.org/10.5194/ems2022-328, 2022.

Orals

14:00–14:15
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EMS2022-199
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CC
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Onsite presentation
Carlos Román-Cascón et al.

Coastal breezes are mesoscale winds formed in mid-latitude regions under fair-weather synoptic conditions, i.e., weak surface-pressure gradient and low winds. They are characterized by a typical wind-direction reversal twice per day, with onshore winds during daytime and offshore during the night. The impacts of these winds are broad and varied: they transport humidity and pollutants (among other physical properties) in the coastal region; they can initiate convection (and even trigger the formation of storms), and they also drive some of the surface oceanic currents formed close to the coast, among others. In this sense, recent surface current observations collected by the Gulf of Cádiz radar system point at the coastal breezes as important contributors to explain the behaviour of the surface currents variability in this region. From a societal point of view, the coastal breezes are crucial for wind power industry, air-quality forecasts, maritime sports, and simply for the refreshing impact that they cause in some warm areas in summer. Hence, a correct understanding of their physical characteristics is needed to correctly forecast them and to be able to investigate their future trends.

These phenomena are formed due to the pressure gradient associated with the temperature difference between the sea and the land surfaces. Therefore, both systems (the ocean and the atmosphere) are involved on the final characteristics that specific breeze events will have, impacting on the variability observed in the strength, duration, and vertical/horizontal extension of the breezes. In this work, we use the Weather Research and Forecasting (WRF) mesoscale model to investigate how the changes in the surface affect the features of this phenomenon through the design of different sensitivity experiments. These include artificial changes in the land and sea surface temperature, but also the use of more realistic (and higher resolution) data to initialise the model. Besides, other experiments are designed to investigate the impact of different technical aspects of the model on the correct simulation of the physical processes, such as the use of different vertical and horizontal resolution, the choice of the planetary-boundary-layer scheme, or the activation or not of typical filters (smoothing) within the model.

How to cite: Román-Cascón, C., Mulero-Martínez, R., Bruno, M., Izquierdo, A., Yagüe, C., Álvarez, O., Gómez-Enri, J., Mañanes, R., and Adame, J. A.: Coastal-breeze simulation with the WRF model: analysing the sensitivity to land/sea surface temperature changes, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-199, https://doi.org/10.5194/ems2022-199, 2022.

14:15–14:30
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EMS2022-315
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CC
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Online presentation
Antonio Ricchi et al.

Heatwaves (HWs) is high-impact phenomena that may have devastating impacts on societies and ecosystems. In the context of numerical modeling, despite driving synoptic scale dynamics are generally well caught, local-scale forcing representation is still challenging, embodying a source of uncertainty and errors. In this work we study two HWs occurring in 2021 summer season (02-05 Aug and 11-14 Aug), on the Italian territory. The first event, is characterized by strong South-Westerly winds and albeit without high geopotential and 850 hPa temperature caused 2 m temperatures above 40 °C in the central Italy east cost (e.g., in the urban area of Pescara), mainly driven by katabatic winds (i.e., Fhoen dynamics). The second HW, has been triggered by a strong advection of hot air from the North African territory and with a major impact on the western coasts of the Italian territory. Here, we leverage a WRF (Weather Research and Forecasting system) numerical model at 1 km resolution over central Italy multi-physics ensemble, including various Planetary Boundary Layer (PBL), land-surface-model (LSM), radiative and surface numerical schemes. The simulations are performed using an approach that takes into account the evolution of sea surface temperature and Marine Mixed Layer Depth (at high resolution, 4.5 km), according to the OML numerical scheme, in order to represent the air-sea interactions more realistically. The preliminary results show a relevant impact exerted by numerical parameterizations, in the prediction of the maximum temperature and humidity, especially in the urban areas. A notable impact is also observed for the simulation of the minimum temperature values. The greatest modulation of HWs reproduction results from the choice of LSMand PBL schemes, and their combinations. These results highlight that the multi-physics approach is also useful to highlight most relevant processes driving local-scale modulation and related uncertainty representing a valuable tool to foster local-scale HWs-related risk mitigation.

How to cite: Ricchi, A., Sangelantoni, L., Redaelli, G., and Ferretti, R.: Multi-Physics Ensemble approach to investigate two summer 2021extreme Heat Waves over central Mediterranean basin, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-315, https://doi.org/10.5194/ems2022-315, 2022.

14:30–14:45
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EMS2022-48
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CC
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Online presentation
Stavros Solomos et al.

Dust is the most abundant aerosol worldwide with multiple implications for radiative transfer, cloud processes and air quality. The dust emissions are usually represented in atmospheric models based on static dust source maps and surface wind properties. In operational dust forecasts, the models are commonly configured in warm start mode, meaning that each simulation cycle is initialized by the forecasted dust fields of the previous run. This technique inevitably inserts certain amounts of uncertainty due to the deviation of numerical solutions. In this study we present the development and evaluation of alternative methods for the initialization of dust emissions in the Georgia Tech Goddard Global Ozone Chemistry Aerosol Radiation and Transport of the Air Force Weather Agency (GOCART-AFWA) module of WRF model. First, we implement a time-varying dust source map based on the 16-day average Normalized Difference Vegetation (NDVI) from the MODIS-Terra instrument. Replacing the static dust source map with a dynamic satellite-based emissions map, allows a physically based representation of seasonal and annual variations of initial dust-source strength in the model. Second, we demonstrate the assimilation of dust Aerosol Optical Depth (AOD) satellite retrievals from the MSG/SEVIRI sensor in the Local Analysis and Prediction System (LAPS), for use in WRF model. A 3D-Var assimilation of satellite AOD retrievals from the MSG-SEVIRI instrument is performed in LAPS, similar to the standard assimilation of atmospheric variables. The forecasted WRF dust AOD is used as first-guess field for the generation of the assimilated AOD in LAPS. Finally, the LAPS AOD is used to initialize the WRF simulations, thus nudging the model towards the observational satellite values. Model runs with different configurations of the MODIS-NDVI and MSG-SEVIRI assimilation schemes are performed for the region of North Africa and the greater Mediterranean. First results verify the successful implementation of both assimilation parameterizations in WRF-Chem.  The improvements and deviations between the original and the newly developed schemes in GOCART-AFWA are discussed in comparison with the AERONET station measurements of AOD.

Acknowledgment This work is supported by the Hellenic Foundation for Research and Innovation project MegDeth (HFRI no.703)

How to cite: Solomos, S., Spyrou, C., Bartsotas, N., and Katsafados, P.: Development of assimilation schemes for the representation of dust in LAPS and WRF modeling systems based on MODIS and MSG satellite retrievals, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-48, https://doi.org/10.5194/ems2022-48, 2022.

14:45–15:00
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EMS2022-320
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Online presentation
Michael Matějka et al.

Summer precipitation in the polar regions is important for many aspects of local environment. Examples include moss and lichens growth, snow-melt runoff, or snow accumulation on glaciers. However, precipitation observations, especially in Antarctica, are very limited due to complicated logistics and  frequent blowing-snow transport and sublimation processes. One of the novel methods how to improve the in-situ precipitation estimates is an application of a very‑high‑resolution numerical atmospheric model. A state-of-the-art, Weather Research and Forecasting (WRF) model, was run for two summer months in early 2022 over northern Antarctic Peninsula and James Ross Island, respectively. Model setup included 300 m horizontal resolution, 65 vertical levels and a new 3D TKE scheme which is especially suitable for subkilometer-scale WRF simulations. James Ross Island was selected because of availability of in-situ observations at proximity of the Johann Gregor Mendel Czech Antarctic Station. The observations were conducted by a Thies laser precipitation monitor (disdrometer) providing precipitation data at 1-minute resolution. Summer precipitation from the Thies measuring system and manual rain gauge observation was investigated in terms of duration, intensity, and phase (liquid/solid) and compared with corresponding WRF variables. In case of snow accumulation on the ground surface, snow height from the model output was compared with a sonic distance sensor data (Judd Communications). The influence of atmospheric circulation on heavy summer snowfalls was analyzed to show both the regional synoptic patterns and local (orographic) atmospheric processes. Finally, the ability of the WRF model to provide accurate and reliable precipitation records for other applications, e. g. snowpack storage and snowmelt-runoff modelling, was assessed.

How to cite: Matějka, M., Láska, K., Zbyněk, E., and Ondřej, N.: Assessment of summer precipitation on James Ross Island, Antarctic Peninsula based on the WRF model output and in-situ observations, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-320, https://doi.org/10.5194/ems2022-320, 2022.

15:00–15:15
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EMS2022-188
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Onsite presentation
Jonas Mortelmans et al.

The boreal zone has experienced more severe fires over the last years, often coinciding with years of anomalously high lightning frequencies. These lightning frequencies might increase even further with global warming. Current lightning predictions are however highly uncertain, either relying on empirical relationships derived from present climate, or coarse-scale climate scenario simulations in which the critical process of deep convection is parameterized, and the detailed representation of land-atmosphere interactions is lacking.

 

In this study, we used the NASA Unified-Weather Research and Forecasting (NU-WRF) modeling framework to simulate lightning over a 550,000 km2 domain including the Great Slave Lake in Canada. Simulations were run for the six lightning seasons (June-August; 2015-2020) at both a convection-parameterized (9 km) and convection-permitting (3 km) spatial resolution. Additionally, two microphysics (MP) schemes (Goddard 4ICE and Thompson) were compared at both resolutions. From the simulation output, we derived four diagnostic lightning indices which were evaluated against observations from the Canadian Lightning Detection Network (CLDN). This evaluation was done in terms of the capability of the indices to match the observational spatial pattern (temporally averaged), spatiotemporal frequency distribution, daily and seasonal climatology (spatially averaged), and an event-based overall skill assessment. Our results show that the Thompson MP scheme better predicts the daily climatology than the Goddard 4ICE MP scheme. The Goddard 4ICE MP scheme, on the other hand, predicts the spatial pattern best. Both MP schemes predict the seasonality equally well. Concerning the spatial resolution, a clear improvement when simulating at convection-permitting resolution is only seen for the Goddard 4ICE MP scheme. Regarding the different lightning indices, no clear superior index is found as the relative performance of each index strongly depends on the evaluation criteria. Finally, the study shows that models are in particular poor in reproducing the long-term averaged observed spatial pattern of lightning occurrence. This might be related to an insufficient representation of the land surface heterogeneity in the study area.

How to cite: Mortelmans, J., Brisson, E., Lynn, B., De Lannoy, G., Van Lipzig, N., Kumar, S., and Bechtold, M.: Lightning Simulations over the Boreal Zone: Skill Assessment for Various Land-Atmosphere Model Configurations and Lightning Indices, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-188, https://doi.org/10.5194/ems2022-188, 2022.

15:15–15:30
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EMS2022-25
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Online presentation
Ankur Prabhat Sati et al.

Managing greenhouse gas (GHG) emissions at a landscape scale requires a framework that can account for local and advected sources. TerrainAI is a funded project that is designed to provide the scientific infrastructure needed to make policy decisions at a national scale to mitigate net GHG emissions from the Irish landscape. The project has established new observation platforms over a variety of natural (e.g., grasslands, peatlands, and forests) and urbanised landscapes and uses satellite and drone technologies to capture detailed spatial and temporal data on the physical properties of land-cover. A core part of the work uses the Weather Research Forecasting (WRF) model coupled with chemistry (WRF-Chem) to simulate the net emissions and transport of GH gases. WRF-Chem has been set up for double nested domain with the entire country of Ireland as inner domain at 1 km resolution; a third nest will be established for the Dublin metropolitan area at a resolution of 250 m. The current model incorporates better resolved model input fields (e.g., land use, meteorology, and emissions) and is evaluated for two 15-day periods in 2018, representing a dry and wet periods dominated by anticyclonic and cyclonic activity respectively. The Dublin nest will employ detailed descriptions of the urban canopy layer and examine their influence on the net emission and dispersion of GHGs. Currently, a WRF-Greenhouse option is used to simulate CO2, CO and CH4 over the study region using the EDGAR emission inventory, which can capture hot-spots and general patterns. More precise emission and sequestration data based on socio-economic profiles will be generated to match the detailed land-cover database used in WRF. These data will permit us to evaluate the efficacy of mitigation policies. 

How to cite: Sati, A. P., Li, Z., Obe, B., Demuzere, M., Fealy, R., Ishola, K., and Mills, G.: Application and evaluation of the WRF-chem modelling infrastructure over Ireland to support greenhouse gas mitigation policies, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-25, https://doi.org/10.5194/ems2022-25, 2022.

16:00–16:15
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EMS2022-521
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CC
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Presentation form not yet defined
Yakob Umer et al.

Urbanization affects the initiation and intensification of convective activities by changing local meteorological variables, which alters the atmosphere's convective processes. Therefore, proper urban surface information is required to model the energy partitioning pattern and its contrast with neighboring grid cells. In this study, the mesoscale weather research and forecasting (WRF) model is configured with satellite-derived urban fraction for optimal rainfall simulation and to evaluate its impact on the simulated rainfall over Kampala, Uganda. The WRF urban parameter values associated with the considered urban fraction are adjusted based on the literature reviews. The satellite-derived urban fraction represents the more realistic extent and intensity of the urban class with a more representative urban fraction. Three different simulations are performed to distil the impact of changing urban fractions as well as of adjusting urban parameters: (1) DUF_DUP, which uses the default urban fraction and default urban parameter values, (2) DUF_AUP, which uses the default urban fraction with adjusted urban parameter values, and (3) SUF_AUP, which uses the satellite-derived urban fraction and adjusted urban parameter values. A single extreme rainfall event, which caused a flood hazard in Kampala on 25 June 2012, is used for all three simulations. The simulated peak rainfall and its spatial distribution over the Kampala catchment are evaluated using observed rainfall data from gauging stations and satellite data from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Results indicate that the simulated rainfall is overestimated compared to CHIRPS and underestimated when comparing gridcell values with gauging station records. However, the SUF_AUP simulation shows relatively better results with a lower absolute relative error score compared to the other two simulations. Compared with the default urban fraction, the satellite-derived urban fraction represents the more realistic urban extent and intensity. As a result, SUF_AUP results in a more realistic rainfall simulation compared to when using the default urban fraction. Rainfall analysis for both 24-hour and 2-hour indicates that the presence of an urban landscape alters both the structure and propagation of high-intensity rainfall over the city, mainly due to the impact of the urban landscape on the different meteorological variables leading to modifying mechanisms associated with rainfall.

Keywords: rainfall, Default urban fraction, Kampala, urban parameter, Updated urban fraction, and WRF model

How to cite: Umer, Y., Ettema, J., Jetten, V., and Steeneveld, G.-J.: Impact of the improved urban fraction on rainfall simulation using the WRF model over Kampala, Uganda, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-521, https://doi.org/10.5194/ems2022-521, 2022.

16:15–16:30
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EMS2022-613
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Online presentation
Mireia Udina et al.

The LIAISE (Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment) field campaign was designed to study the effects of irrigation on a semi-arid area in NE Spain  (Boone et al. 2019). Within the framework of LIAISE, the WISE-PreP project was conceived to examine precipitation processes, on the one hand collecting high resolution data using Parsivel disdrometers and Micro-Rain Radars complementing operational rain-gauge and C-band Doppler weather radar observations and on the other one, carrying out numerical simulations to improve our understanding of physical processes involved. In this presentation we explore the irrigation impact on precipitation in Weather Research and Forecasting (WRF) model simulations during the intensive period of the LIAISE field campaign (15-30 July 2021). We quantify the precipitation accumulation and distribution by including the irrigation parameterization (Valmassoi et al 2020) and varying its parameters (days of irrigation, amount of irrigated water, hours of irrigation, etc.). First results indicate that fractional area of precipitation is greater if the irrigation parameterization is activated and if the irrigated amount is greater as well. Finally, we explore differences in stratiform vs convective fractions of precipitation. This work was partly funded by the project “Analysis of Precipitation Processes in the Eastern Ebro Subbasin” (WISE-PreP, RTI2018-098693-B-C32, MINECO/FEDER) and the Water Research Institute (IdRA) of the University of Barcelona.

References

Boone A, Best M, Cuxart J, Polcher J, Quintana P, Bellvert J, Brooke J, Canut-Rocafort G, Price J (2019). Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment (LIAISE). Gewex News, February 2019.

Valmassoi A, Dudhia J, Sabatino SD, Pilla F (2020). Evaluation of three new surface irrigation parameterizations in the WRF-ARW v3. 8.1 model: the Po Valley (Italy) case study. Geoscientific Model Development, 13(7), 3179-3201.

How to cite: Udina, M., Bech, J., Peinó, E., and Mercader, J.: Irrigation Impact on Precipitation Forecasts During the LIAISE-2021 Field Campaign, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-613, https://doi.org/10.5194/ems2022-613, 2022.

16:30–16:45
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EMS2022-72
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Online presentation
Dorita Rostkier-Edelstein et al.

The trend of the decrease in the global average diurnal temperature range (DTR) is one of the clearest signals in twentieth century climate data. Regionally, DTR trends exhibit large variations. A factor separation analysis was conducted to investigate the impact of atmospheric moisture, synoptic‐scale winds, and their synergy on the DTR during the Israeli summer. The Weather Research and Forecasting (WRF) Single Column Model was run for summer representative days, at four locations in Israel. In almost all cases, the contribution of the factors and of their synergy to the DTR was dominated by their contribution to the diurnal minimum temperature, Tmin. The largest contribution resulted from atmospheric moisture, reducing the DTR. The contribution of synoptic‐scale winds showed more variability, with significant differences in both magnitude and sign on different days. The sign of the effect on Tmin depended on the relative direction and magnitude of the nocturnal synoptic‐scale wind with respect to the local wind, which in turn determined the effect on the low‐level jet (LLJ) and vertical mixing. The contribution from synergy between the two factors depended on the effect of moisture on the LLJ and on the effect of the synoptic‐scale winds on moisture advection in or out of the atmospheric column. All cases were classified into groups depending on the sign of contributions of the single factors and of their synergy when analyzing the DTR observed trends. These results highlight the importance of the synoptic wind, of its synergy with atmospheric moisture and of the feedback mechanisms.

How to cite: Rostkier-Edelstein, D., Rotstein, M., and Alpert, P.: A Factor Separation Study of the Effect of Synoptic‐Scale Wind, Atmospheric Moisture and of Their Synergy on the Diurnal Temperature Range During the Israeli Summer Using the WRF Single Column Model, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-72, https://doi.org/10.5194/ems2022-72, 2022.

16:45–17:00
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EMS2022-137
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CC
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Online presentation
Petros Katsafados et al.

The thought that the Earth’s spheres should be considered as a single system at short and longer spatiotemporal scales is nowadays dominant among scientific community. However, the complex interaction processes in Earth’s system are insufficiently modeled by the standalone atmospheric models. To narrow this gap, it is important to implement modeling systems that bidirectionally connect Earth’s spheres. In this context, this study presents a fully coupled multi-model system named CHAOS (Chemical Hydrological Atmospheric Ocean wave System) that bridges atmosphere, ocean and land, by representing many interaction processes. The study presents the design, the implementation and the operation of the CHAOS system, highlighting also its advantages in the simulation of severe weather events in the Mediterranean Sea and the Atlantic Ocean. The CHAOS system consists of three main components: the Advanced Weather Research Forecasting (WRF-ARW) model, the Wave model (WAM) and the Nucleus for European Modeling of the Ocean (NEMO). The three components are coupled using the OASIS Model Coupling Toolkit (OASIS3-MCT) that enables them to “online” communicate and exchange the information required. Moreover, two sub-components of the WRF-ARW model are suitably introduced in the CHAOS system to additionally simulate chemical (WRF-Chem) and hydrological (WRF-Hydro) processes, depending on the application. Regarding the hydrological processes, CHAOS is also “offline” coupled with the HEC-RAS hydraulic-hydrodynamic model to provide high-resolution flash-flood simulation and mapping. CHAOS has been applied in several high-impact cases focusing on the processes arising from the air-sea interaction. Thus, it has been implemented to study the hurricane Sandy (2012) in the Atlantic Ocean and various Mediterranean tropical-like cyclones (medicanes). It is also able to represent the sea-atmosphere-hydro-land chain processes in a severe flash flood event occurred at western Attica in Greece (2017) and to simulate the sea-salt aerosol emissions through an advanced parameterization scheme based on the sea-state conditions instead of the trivial approach that it depends exclusively on the atmospheric flow. An one-year assessment of CHAOS operation is also presented, based on the results of continuous, operational-like forecasting simulations that showcased the effects of the two-way atmosphere-wave interactions. Summarizing, in the light of the increasing high-impact weather events and the climate change, the CHAOS system and its multidisciplinary applications could be exploited not only by the scientific community as an all-in-one modeling platform able to resolve fluxes and processes across Earth’s spheres but also by decision makers for operational forecasting and civil protection applications, facilitating the safekeeping of human lives and socio-economic activities in the future.

How to cite: Katsafados, P., Varlas, G., Anastasios, P., Vassilios, V., Christos, S., Stavros, S., George, P., Evangelia, P., and Nefeli, M.: Coupling across the Spheres: the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-137, https://doi.org/10.5194/ems2022-137, 2022.

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