Mikhail Varentsov
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View article: Coupling the Town Energy Balance (TEB) Scheme with the COSMO Atmospheric Model: Evaluation Against a Bulk Parameterization (TERRA_URB) for the Moscow Megacity
Coupling the Town Energy Balance (TEB) Scheme with the COSMO Atmospheric Model: Evaluation Against a Bulk Parameterization (TERRA_URB) for the Moscow Megacity Open
Numerical weather prediction (NWP) models, coupled with urban parameterizations, play a crucial role in understanding and forecasting meteorological conditions within urban environments. In the mesoscale NWP model COSMO, only one urban par…
View article: Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks
Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks Open
The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate’…
View article: Methodology for collecting and processing eddy covariance data of the Tomsk Flux Network
Methodology for collecting and processing eddy covariance data of the Tomsk Flux Network Open
Observations of turbulent heat and momentum fluxes over urban landscapes are essential for understanding urban climate processes and improving meteorological models. However, flux data remain limited for cities in continental temperate and…
View article: The use of a U-Net neural network for high-resolutionc urban climate modelling
The use of a U-Net neural network for high-resolutionc urban climate modelling Open
Urban areas cover 3 to 5% of total land area, however they contain nearly 2/3 of global population. It has been shown that cities also experience increased effects of climate change. Therefore for a sustainable future it is vital to be abl…
View article: Introducing the COSMO model with TEB urban canopy scheme: coupling strategy and comparison with simpler TERRA_URB parameterization
Introducing the COSMO model with TEB urban canopy scheme: coupling strategy and comparison with simpler TERRA_URB parameterization Open
Numerical weather prediction (NWP) models, coupled with urban parameterizations, play a crucial role in understanding and forecasting meteorological conditions within urban environments. Urban parameterizations vary in complexity, ranging …
View article: Urban Heat Islands in the Arctic: Long-Term Observations in Seven North-Eurasian Cities
Urban Heat Islands in the Arctic: Long-Term Observations in Seven North-Eurasian Cities Open
In the modern era of modeling and remote sensing, in situ urban meteorological observations still remain critically important for validating urban climate models, remote sensing products, and developing data-driven ML models. To collect su…
View article: Turbulent fluxes over a cold climate city in Siberia: insights from a new flux tower network
Turbulent fluxes over a cold climate city in Siberia: insights from a new flux tower network Open
Observations of turbulent heat and momentum fluxes over urban landscapes are crucial for understanding urban climate processes and for evaluating urban meteorological models. These observations are particularly valuable for the verificatio…
View article: Urban green infrastructure index: Assessing supply of regulating and cultural ecosystem services at a megacity scale
Urban green infrastructure index: Assessing supply of regulating and cultural ecosystem services at a megacity scale Open
Urban green infrastructures (UGI) contribute to a quality of life in cities by provisioning cultural and regulating ecosystem services (ES). Planning and management of UGI needs transparent and spatially explicit indicators of the ES suppl…
View article: The Water Balance Representation in Urban‐PLUMBER Land Surface Models
The Water Balance Representation in Urban‐PLUMBER Land Surface Models Open
Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is couple…
View article: UAV-based monitoring of the thermal structure of heterogeneous landscapes
UAV-based monitoring of the thermal structure of heterogeneous landscapes Open
The paper presents a technique for measuring the temperature of an inhomogeneous underlying surface using unmanned aerial vehicles (UAVs). To test the proposed technique, measurements over various landscapes are presented: dunes in an arid…
View article: Urban–rural differences in mortality during the 2010 heatwave in European Russia
Urban–rural differences in mortality during the 2010 heatwave in European Russia Open
The 2010 summer heatwave in European Russia led to a notable increase in mortality due to extreme heat and associated wildfires. However, the diverse settlement patterns and the uneven impact of the heatwave in European Russia have left ma…
View article: The water balance representation in Urban-PLUMBER land surface models
The water balance representation in Urban-PLUMBER land surface models Open
Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. When part of numerical weather prediction, ULSMs provide a lower boundary for the atmosphere and improve the applicability of m…
View article: Quantifying Spatial Heterogeneities of Surface Heat Budget and Methane Emissions over West-Siberian Peatland: Highlights from the Mukhrino 2022 Campaign
Quantifying Spatial Heterogeneities of Surface Heat Budget and Methane Emissions over West-Siberian Peatland: Highlights from the Mukhrino 2022 Campaign Open
The study presents the first results from the multi-platform observational campaign carried out at the Mukhrino peatland in June 2022. The focus of the study is the quantification of spatial contrasts of the surface heat budget terms and m…
View article: Arctic COSMO-CLM hindcast 2017
Arctic COSMO-CLM hindcast 2017 Open
Russian Arctic COSMO-CLM hindcast 2017
View article: Arctic COSMO-CLM hindcast 1994
Arctic COSMO-CLM hindcast 1994 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1984
Arctic COSMO-CLM hindcast 1984 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1983
Arctic COSMO-CLM hindcast 1983 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1982
Arctic COSMO-CLM hindcast 1982 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1993
Arctic COSMO-CLM hindcast 1993 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1987
Arctic COSMO-CLM hindcast 1987 Open
COSMO-CLM Russia Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1985
Arctic COSMO-CLM hindcast 1985 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1980
Arctic COSMO-CLM hindcast 1980 Open
COSMO-CLM climatological data archive
View article: Arctic COSMO-CLM hindcast 1992
Arctic COSMO-CLM hindcast 1992 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1988
Arctic COSMO-CLM hindcast 1988 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1990
Arctic COSMO-CLM hindcast 1990 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1991
Arctic COSMO-CLM hindcast 1991 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 1981
Arctic COSMO-CLM hindcast 1981 Open
COSMO-CLM Russian Arctic climate reanalysis
View article: Arctic COSMO-CLM hindcast 1989
Arctic COSMO-CLM hindcast 1989 Open
COSMO-CLM Russian Arctic climate dataset
View article: Arctic COSMO-CLM hindcast 2011
Arctic COSMO-CLM hindcast 2011 Open
COSMO-CLM Russian Arctic climate dataset
View article: Vertical profiles of air temperature, relative humidity, wind speed and direction observed using UAV over the Mukhrino peatland in June 2022
Vertical profiles of air temperature, relative humidity, wind speed and direction observed using UAV over the Mukhrino peatland in June 2022 Open
Vertical profiles of air temperature and relative humidity were measured using the iMetXQ2 sensor onboard DJI Phantom 4 quad-copter; vertical profiles of wind speed and direction were obtained from the Phantom 4 flight logs as produced by …