Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates

Branch, Oliver; Schwitalla, Thomas; Temimi, M.; Fonseca, Ricardo; Temimi, Marouane; Weston, Michael; Milovac, Josipa; Wulfmeyer, Volker

doi:10.5194/gmd-14-1615-2021

Cited by 16 publications

(22 citation statements)

References 74 publications

(111 reference statements)

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“…Similar results are obtained at the location of the other stations (not shown), with the biases having a slightly higher magnitude for the higher elevation sites in line with the findings of Branch et al. (2021) and Temimi et al. (2020).…”

Section: Performance Of the Wrf Modelsupporting

confidence: 89%

“…Figure 7a shows the WRF and observed data at the location of the eight stations that comprise the bulk of the rainy region on this day. Similar results are obtained at the location of the other stations (not shown), with the biases having a slightly higher magnitude for the higher elevation sites in line with the findings of Branch et al (2021) and Temimi et al (2020).…”

Section: Local-scale: Weather Station Datasupporting

confidence: 86%

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Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates

Fonseca

Francis

Temimi

et al. 2022

Earth and Space Science

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With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this study, the usefulness of the Weather Research and Forecasting (WRF) model forecasts for guidance into seeding operations in the United Arab Emirates, where seeding activities have been conducted for more than two decades, is assessed. The WRF predictions are compared with ground‐based, satellite‐derived and radar reflectivity data, and in‐situ observations onboard the airplanes used to perform the seeding operations. WRF is found to have higher skill in simulating the observed cloud top pressure/temperature than the cloud fraction, with the model vertical velocity predictions also more skillful than those of the radar reflectivity. A stronger Arabian Heat Low (AHL) in the model leads to drier conditions which, together with a surface cold bias, limits the spatial extent and vertical depth of the simulated convective clouds. Development of convective rolls in the boundary layer is reported in both observations and simulations and their interaction with cold pools from convective clouds promote the development of secondary convection. Sensitivity to the choice of the Planetary Boundary Layer (PBL) scheme is also noticed, with the Yonsei University PBL scheme giving the best performance. When considering the two factors needed for a successful seeding operation that is, the presence of an updraft and clouds, the model‐predicted seeding regions largely match the areas where precipitation was observed. As the proposed WRF set up can be used operationally, the model forecasts will bring added value to the seeding activities in the country.

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Section: Performance Of the Wrf Modelsupporting

confidence: 89%

Section: Local-scale: Weather Station Datasupporting

confidence: 86%

Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates

Fonseca

Francis

Temimi

et al. 2022

Earth and Space Science

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“…We noted the presence of a short reversal to a cold bias that occurred around 4 a.m. This switch usually occurred roughly around the twice-daily transition times of the boundary layer between stable and convective states [66].…”

Section: Air Temperature and Relative Humiditymentioning

confidence: 79%

“…Aerosol load and associated radiative impact [9] are known to exhibit an annual maximum during summer over the UAE [65]. This cold bias was also highlighted in the study carried out by Branch et al [66] to assess the seasonal and daytime performance of daily forecasts with WRF in the United Arab Emirates. Note that the observed diurnal cycle was well simulated by EXP01, EXP08, and EXP13 than in the other model simulations, particularly during daytime.…”

Section: Air Temperature and Relative Humiditymentioning

confidence: 82%

Evaluation of the Performance of the WRF Model in a Hyper-Arid Environment: A Sensitivity Study

et al. 2022

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Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved.

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“…Boutle et al (2022) evaluated results from large eddy simulation (LES) and single column models (SCMs) for a radiation fog case in the United Kingdom and recommend having a first vertical level of less than 10 m and six or more levels below 150 m. An increase in the vertical resolution is expected to better simulate strong moisture and temperature gradients in the lower troposphere (e.g. Branch et al, 2021). However, Ajjaji et al (2008) reported that an increase in the vertical resolution can have the opposite effect and inhibit cloud formation for fog events over the United Arab Emirates, an arid region similar to Namibia, during a WRF real-case (i.e.…”

Section: Model Configurationmentioning

confidence: 99%

Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

et al. 2022

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Abstract. Aerosol-aware microphysics parameterisation schemes are increasingly being introduced into numerical weather prediction models, allowing for regional and case-specific parameterisation of cloud condensation nuclei (CCN) and cloud droplet interactions. In this paper, the Thompson aerosol-aware microphysics scheme, within the Weather Research and Forecasting (WRF) model, is used for two fog cases during September 2017 over Namibia. Measurements of CCN and fog microphysics were undertaken during the AErosols, RadiatiOn and CLOuds in southern Africa (AEROCLO-sA) field campaign at Henties Bay on the coast of Namibia during September 2017. A key concept of the microphysics scheme is the conversion of water-friendly aerosols to cloud droplets (hereafter referred to as CCN activation), which could be estimated from the observations. A fog monitor 100 (FM-100) provided cloud droplet size distribution, number concentration (Nt), liquid water content (LWC), and mean volumetric diameter (MVD). These measurements are used to evaluate and parameterise WRF model simulations of Nt, LWC, and MVD. A sensitivity analysis was conducted through variations to the initial CCN concentration, CCN radius, and the minimum updraft speed, which are important factors that influence droplet activation in the microphysics scheme of the model. The first model scenario made use of the default settings with a constant initial CCN number concentration of 300 cm−3 and underestimated the cloud droplet number concentration, while the LWC was in good agreement with the observations. This resulted in droplet size being larger than the observations. Another scenario used modelled data as CCN initial conditions, which were an order of magnitude higher than other scenarios. However, these provided the most realistic values of Nt, LWC, MVD, and droplet size distribution. From this, it was concluded that CCN activation of around 10 % in the simulations is too low, while the observed appears to be higher reaching between 20 % and 80 %, with a mean (median) of 0.55 (0.56) during fog events. To achieve this level of activation in the model, the minimum updraft speed for CCN activation was increased from 0.01 to 0.1 m s−1. This scenario provided Nt, LWC, MVD, and droplet size distribution in the range of the observations, with the added benefit of a realistic initial CCN concentration. These results demonstrate the benefits of a dynamic aerosol-aware scheme when parameterised with observations.

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Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates

Cited by 16 publications

References 74 publications

Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates

Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates

Evaluation of the Performance of the WRF Model in a Hyper-Arid Environment: A Sensitivity Study

Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

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