Special Issue "Modeling of Surface-Atmosphere Interactions"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Rui Salgado
E-Mail Website
Guest Editor
Institute of Earth Sciences (ICT) and Department of Physics, School of Scince and Technology, University of Évora, 7000-645 Évora, Portugal
Interests: atmospheric modeling; lake-atmosphere interactions; sea and lake breezes; interactive lakes in NWP; climate impact of dams; fire meteorology; radiation forecast; orographic precipitation
Dr. Maria José Monteiro
E-Mail Website
Guest Editor
1. Instituto Português do Mar e da Atmosfera (IPMA. I.P.), Rua C do Aeroporto, 1749-077, Lisbon, Portugal2. Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal
Interests: numerical weather prediction; limited area modeling; data assimilation; surface-atmosphere interactions
Dr. Mariana Bernardino
E-Mail Website
Guest Editor
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal
Interests: atmosphere-ocean interaction; wind and wave modeling; climate and climate change; off-shore wind and wave energy
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Dr. David Carvalho
E-Mail Website
Guest Editor
Centre for Environmental and Marine Studies (CESAM) & Department of Physics, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: numerical weather prediction;atmospheric modelling; renewable energies;climate simulation and modelling;climate variability and change;data assimilation;atmospheric motion vectors;observation system simulation experiments (OSSEs)
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Dr. Flavio T. Couto
E-Mail Website
Guest Editor
Institute of Earth Sciences (ICT) and Department of Physics, School of Scince and Technology, University of Évora, 7000-645 Évora, Portugal
Interests: fire weather and wildfires modelling; heavy orographic precipitation; mineral dust mobilization and transport
Dr. Rita M. Cardoso
E-Mail Website
Guest Editor
Instituto Dom Luiz, University of Lisbon, IDL, Campo Grande, Ed C1, 1749-016 Lisbon, Portugal
Interests: boundary layer processes; surface-atmosphere coupling; climate change; regional climate modelling
Dr. João P. A. Martins
E-Mail Website
Guest Editor
1. Instituto Português do Mar e da Atmosfera (IPMA. I.P.), Rua C do Aeroporto, 1749-077, Lisbon, Portugal2. Instituto Dom Luiz, University of Lisbon, IDL, Campo Grande, Ed C1, 1749-016 Lisbon, Portugal
Interests: thermal remote sensing; land surface temperature; land surface modelling; boundary layer processes; GNSS meteorology; cyclone tracking
Prof. Dr. Joao Carlos Andrade dos Santos
E-Mail Website
Guest Editor
Department of Physics, Centre for the Research and Technology of Agro-environmental and Biological Sciences, CITAB, Universidade de Trás-os-Montes e Alto Douro, 5000-801, Vila Real, Portugal
Interests: climate variability and extremes; climate change projections; impact and risk assessment on agriculture and forests
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleague,

Along with numerical weather prediction (NWP) progress in the past couple of decades, challenges remain as a result of the increasing complexity of today’s models. For instance, the representation of the land surface has evolved tremendously. An accurate representation of the exchanges of energy, mass (including water, desert dust, carbon, and greenhouse gases), and momentum is essential for better quality forecasts, especially for processes in the lower levels of the atmosphere. These exchanges involve a thorough description of the processes linked to turbulence, vegetation dynamics and physiological processes, precipitation and snow, surface energy balance, orographic processes, river discharge and runoff, anthropogenic forcing, etc.

Surface modeling (including land, ocean, inland water, urban areas, ice, and snow) is crucial for accurate numerical weather predictions and for the understanding and modeling of climate change. The latest Intergovernmental Panel on Climate Change (IPCC) reports are clear regarding the effects of climate change across the Mediterranean, in particular across Iberia, and consider this region a hotspot for climate change. The effects include increased risk of droughts, wildfires, extreme events (such as floods and heat waves), and coastal flooding due to increased mean sea level and storm severity.

Accurate observations (in situ, satellite, and others) are crucial to improve these models. In the 2018 Statement of Guidance for High-Resolution Numerical Weather Prediction, the World Meteorological Organization recommended that the planning of future conventional networks should focus on the boundary layer, as this is where NWP vertical resolution is highest. In particular, the density and frequency of observations available from the Mediterranean Sea should be expanded. A number of new satellite sensors and products have allowed better diagnostics of model biases. For instance, the Satellite Application Facility on Land Surface Analysis (which is part of the ground segment of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) based at the IPMA, Portugal) provides a portfolio of satellite-derived land surface variables related to the surface energy balance and vegetation state.

Data assimilation systems combine modeling and observational techniques to provide more realistic products. These techniques are in use by several international agencies, such as NASA, ECMWF, ESA, and Météo-France. For instance, the ECMWF used this capacity to produce ERA5-Land, a global reanalysis with relatively high resolution (~9 km) with data every hour, available from 1981 onward. Ocean, surface wind, and sea state information are assimilated into atmospheric and ocean models (waves, currents, sea surface temperature and height, etc.) to produce accurate forecasts and reanalysis datasets. Finally, all major global and limited area models represent surface processes using a dedicated scheme.

This Special Issue launched in the framework of the workshop on “Numerical Weather Prediction in Portugal 2020” (https://sites.google.com/view/nwpportugal) aims to collect current novel papers, whether presented at the workshop or not, on the modeling of surface–atmosphere interactions. We invite researchers to contribute original research papers dealing with all aspects of the modeling of surface–atmosphere interactions, including:

  • Modeling development, test, and validation;
  • Surface observations and data assimilation;
  • Surface reanalysis;
  • Land–atmosphere interactions and feedback;
  • Atmosphere–ocean interactions;
  • Cryosphere–atmosphere interactions;
  • Inland waters–atmosphere interactions;
  • Boundary layer processes and modeling;
  • Urban boundary layer;
  • Atmospheric circulations over complex terrain;
  • Land use and climate change;
  • Fire–weather interactions and modeling;
  • Dust mobilization;
  • Transfer of greenhouse gases at the surface–atmosphere interface;
  • Emission of pollen into the atmosphere.

Dr. Rui Salgado
Dr. Maria José Monteiro 
Dr. Mariana Bernardino
Dr. David Carvalho
Dr. Flavio T. Couto
Dr. Rita M. Cardoso
Dr. João P. A. Martins
Prof. Dr. Joao Carlos Andrade dos Santos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • modeling
  • interaction
  • surface reanalysis
  • data assimilation
  • urban boundary layer

Published Papers (4 papers)

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Research

Article
Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea
Atmosphere 2021, 12(6), 766; https://doi.org/10.3390/atmos12060766 - 14 Jun 2021
Viewed by 328
Abstract
Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this [...] Read more.
Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. The results are as follows: (1) the HRCLDAS and ERA5 near-surface wind data trend was basically the same as the observation data trend, but there was a smaller bias, smaller root-mean-square errors, and higher correlation coefficients between the near-surface wind data from HRCLDAS and the observations; (2) the quality of HRCLDAS and ERA5 near-surface wind data was better over the islands of the South China Sea than over Hainan Island land. However, over the coastal areas of Hainan Island and island stations near Sansha, the quality of the HRCLDAS near-surface wind data was better than that of ERA5; (3) the quality of HRCLDAS near-surface wind data was better than that of ERA5 over different types of landforms. The deviation of ERA5 and HRCLDAS wind speed was the largest along the coast, and the quality of the ERA5 wind direction data was poorest over the mountains, whereas that of HRCLDAS was poorest over hilly areas; (4) the accuracy of HRCLDAS at all wind levels was higher than that of ERA5. ERA5 significantly overestimated low-grade winds and underestimated high-grade winds. The accuracy of HRCLDAS wind ratings over the islands of the South China Sea was significantly higher than that over Hainan Island land, especially for the higher wind ratings; and (5) in the typhoon process, the simulation of wind by HRCLDAS was closer to the observations, and its simulation of higher wind speeds was more accurate than the ERA5 simulations. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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Article
Temperature Response to Changes in Vegetation Fraction Cover in a Regional Climate Model
Atmosphere 2021, 12(5), 599; https://doi.org/10.3390/atmos12050599 - 05 May 2021
Viewed by 314
Abstract
Vegetation plays a key role in partitioning energy at the surface. Meteorological and Climate Models, both global and regional, implement vegetation using two parameters, the vegetation fraction and the leaf area index, obtained from satellite data. In most cases, models use average values [...] Read more.
Vegetation plays a key role in partitioning energy at the surface. Meteorological and Climate Models, both global and regional, implement vegetation using two parameters, the vegetation fraction and the leaf area index, obtained from satellite data. In most cases, models use average values for a given period. However, the vegetation is subject to strong inter-annual variability. In this work, the sensitivity of the near surface air temperature to changes in the vegetation is analyzed using a regional climate model (RCM) over the Iberian Peninsula. The experiments have been designed in a way that facilitates the physical interpretation of the results. Results show that the temperature sensitivity to vegetation depends on the time of year and the time of day. Minimum temperatures are always lower when vegetation is increased; this is due to the lower availability of heat in the ground due to the reduction of thermal conductivity. Regarding maximum temperatures, the role of increasing vegetation depends on the available moisture in the soil. In the case of hydric stress, the maximum temperatures increase, and otherwise decrease. In general, increasing vegetation will lead to a higher daily temperature range, since the decrease in minimum temperature is always greater than the decrease for maximum temperature. These results show the importance of having a good estimate of the vegetation parameters as well as the implications that vegetation changes due to natural or anthropogenic causes might have in regional climate for present and climate change projections. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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Article
Lake and Land Breezes at a Mediterranean Artificial Lake: Observations in Alqueva Reservoir, Portugal
Atmosphere 2021, 12(5), 535; https://doi.org/10.3390/atmos12050535 - 22 Apr 2021
Viewed by 382
Abstract
The Alqueva reservoir, in the Southeast of Portugal, has significantly changed the landscape of the region, with impacts also on the local climate, as documented in this manuscript, namely the thermal circulation in the form of lake and land breezes. Taking advantage of [...] Read more.
The Alqueva reservoir, in the Southeast of Portugal, has significantly changed the landscape of the region, with impacts also on the local climate, as documented in this manuscript, namely the thermal circulation in the form of lake and land breezes. Taking advantage of three strategic meteorological stations, two installed at the shores and another on a floating platform located near the center of the reservoir, a detailed analysis of lake and land breeze occurrences during two years is presented in this study. The thermal gradient between the reservoir and the surroundings is the main driver for the breeze development and the meteorological stations placed in opposite sides of the reservoir allow to establish the criteria in order to detect lake and land breezes. The results showed more land breeze than lake breeze occurrences, in line with the more negative thermal gradient between shores and reservoir in the annual cycle. Lake breezes are more frequent in summer months during daytime and land breezes in turn are more frequent in winter months during night-time. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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Article
Study of Urban Heat Islands Using Different Urban Canopy Models and Identification Methods
Atmosphere 2021, 12(4), 521; https://doi.org/10.3390/atmos12040521 - 20 Apr 2021
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Abstract
This work aims to compare the performance of the single‑(SLUCM) and multilayer (BEP-Building effect parameterization) urban canopy models (UCMs) coupled with the Weather Research and Forecasting model (WRF), along with the application of two urban heat island (UHI) identification methods. The identification methods [...] Read more.
This work aims to compare the performance of the single‑(SLUCM) and multilayer (BEP-Building effect parameterization) urban canopy models (UCMs) coupled with the Weather Research and Forecasting model (WRF), along with the application of two urban heat island (UHI) identification methods. The identification methods are: (1) the “classic method”, based on the temperature difference between urban and rural areas; (2) the “local method” based on the temperature difference at each urban location when the model land use is considered urban, and when it is replaced by the dominant rural land use category of the urban surroundings. The study is performed as a case study for the city of Lisbon, Portugal, during the record-breaking August 2003 heatwave event. Two main differences were found in the UHI intensity (UHII) and spatial distribution between the identification methods: a reduction by half in the UHII during nighttime when using the local method; and a dipole signal in the daytime and nighttime UHI spatial pattern when using the classic method, associated with the sheltering effect provided by the high topography in the northern part of the city, that reduces the advective cooling in the lower areas under prevalent northern wind conditions. These results highlight the importance of using the local method in UHI modeling studies to fully isolate urban canopy and regional geographic contributions to the UHII and distribution. Considerable improvements were obtained in the near‑surface temperature representation by coupling WRF with the UCMs but better with SLUCM. The nighttime UHII over the most densely urbanized areas is lower in BEP, which can be linked to its larger nocturnal turbulent kinetic energy (TKE) near the surface and negative sensible heat (SH) fluxes. The latter may be associated with the lower surface skin temperature found in BEP, possibly owing to larger turbulent SH fluxes near the surface. Due to its higher urban TKE, BEP significantly overestimates the planetary boundary layer height compared with SLUCM and observations from soundings. The comparison with a previous study for the city of Lisbon shows that BEP model simulation results heavily rely on the number and distribution of vertical levels within the urban canopy. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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