Development of the High-resolution Operational System for Numerical Prediction of Weather and Severe Weather Events for the Moscow Region

Rivin, G. S.; Rozinkina, I. A.; Vil’fand, R. M.; Kiktev, D. B.; Tudrii, K. O.; Blinov, D. V.; Varentsov, Mikhail; Zakharchenko, D. I.; Samsonov, Timofey; Repina, Irina; Artamonov, A. A.

doi:10.3103/s1068373920070018

Cited by 19 publications

(22 citation statements)

References 13 publications

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“…The city has experienced an increasing UHI intensity trend over the last decades [40], with a present-day annual-mean UHI intensity of 2 • peaking to more than 10 • C during calm and clear nights [41,42]. Its relevance as a test-bed for model testing and verification is shown by previous studies using COSMO model with the TERRA_URB scheme [6,39,43].…”

Section: Study Areamentioning

confidence: 99%

“…COSMO is a limited-area non-hydrostatic model developed by the COSMO consortium (Consortium for Small-scale Modelling, [44]). The model is used for numerical weather prediction in many countries including Russia [6]. The model version COSMO-CLM or CCLM [35], developed by the CLM (Climate Limited-area Modeling) community) [45], is adopted for long-term simulations and is widely used in regional climate studies.…”

Section: The Cosmo Model and Terra_urb Schemementioning

confidence: 99%

“…This version was successfully used for urban climate simulations in global cities [20,21,24,39,43,[46][47][48][49]. Recently, the TERRA_URB scheme was implemented to a newer version of COSMO (5.05urb, used in the current study) as part of the AEVUS (Analysis and evaluation of the TERRA_URB scheme) priority task of the COSMO consortium [6,50]. This newer version includes improved boundary-layer physics and is unified with the recent developments of the ICON (ICOsahedral Nonhydrostatic) modelling system [51,52].…”

Section: The Cosmo Model and Terra_urb Schemementioning

confidence: 99%

“…The annual-mean AHF is defined based on a Stewart and Kennedy (2017) [69], who suggest an annual mean value of 52 W/m 2 within the administrative borders of Moscow (excluding the "New Moscow" area). To obtain a detailed spatial pattern on a 1 km grid, this value was "weighted" by the product of H and R. Despite the evident simplicity, this approach proved itself in the previous modelling studies for Moscow [6,39,43].…”

Section: Reference Urban Canopy Parametersmentioning

confidence: 99%

“…The model options were selected based on previous modelling efforts for Moscow [6,39,43,50] as well as on a number of preliminary simulations for considered periods using the same model version and settings (results not shown). Selected model set up accounts for recent developments in the physical parameterizations, for example, so-called new ICON-based physics [71], Tegen aerosol climatology [72], exponential vertical profile of root density, and a new formulation for bare soil evaporation and vegetation-skin temperature [73].…”

Section: Model Setup and Study Periodsmentioning

confidence: 99%

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Impact of Urban Canopy Parameters on a Megacity’s Modelled Thermal Environment

2020

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Urban canopy parameters (UCPs) are essential in order to accurately model the complex interplay between urban areas and their environment. This study compares three different approaches to define the UCPs for Moscow (Russia), using the COSMO numerical weather prediction and climate model coupled to TERRA_URB urban parameterization. In addition to the default urban description based on the global datasets and hard-coded constants (1), we present a protocol to define the required UCPs based on Local Climate Zones (LCZs) (2) and further compare it with a reference UCP dataset, assembled from OpenStreetMap data, recent global land cover data and other satellite imagery (3). The test simulations are conducted for contrasting summer and winter conditions and are evaluated against a dense network of in-situ observations. For the summer period, advanced approaches (2) and (3) show almost similar performance and provide noticeable improvements with respect to default urban description (1). Additional improvements are obtained when using spatially varying urban thermal parameters instead of the hard-coded constants. The LCZ-based approach worsens model performance for winter however, due to the underestimation of the anthropogenic heat flux (AHF). These results confirm the potential of LCZs in providing internationally consistent urban data for weather and climate modelling applications, as well as supplementing more comprehensive approaches. Yet our results also underline the continued need to improve the description of built-up and impervious areas and the AHF in urban parameterizations.

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