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: closed (31 December 2021) | Viewed by 28509

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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

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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

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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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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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Instituto de Ciências da Terra—ICT (Polo de Évora), Universidade de Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
Interests: fire weather and wildfires modelling; heavy orographic precipitation; mineral dust mobilization and transport
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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
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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

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Centre for the Research and Technology of Agro-Environmental and Biological Sciences, CITAB, Universidade de Trás-os-Montes e Alto Douro, UTAD, 5000-801 Vila Real, Portugal
Interests: climate modeling; climate impact research; climate change adaptation; meteorology; crop model simulations
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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

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Keywords

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

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Published Papers (8 papers)

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17 pages, 7119 KiB  
Article
Variability of the Southwestern Patagonia (51°S) Winds in the Recent (1980–2020) Period: Implications for Past Wind Reconstructions
by Carolina Gómez-Fontealba, Valentina Flores-Aqueveque and Stéphane Christophe Alfaro
Atmosphere 2022, 13(2), 206; https://doi.org/10.3390/atmos13020206 - 27 Jan 2022
Cited by 4 | Viewed by 3159
Abstract
The Southern Hemisphere Westerly Winds (SWW) control the amount and latitudinal distribution of rainfall in southwestern Patagonia. Recent studies have shown that SWW has intensified in the last decades, but their past behavior is not yet well understood. To understand this behavior, it [...] Read more.
The Southern Hemisphere Westerly Winds (SWW) control the amount and latitudinal distribution of rainfall in southwestern Patagonia. Recent studies have shown that SWW has intensified in the last decades, but their past behavior is not yet well understood. To understand this behavior, it is necessary to analyze climatic data from meteorological stations and reconstruct their variability through paleoclimatic evidence, such as lake cores. Nevertheless, Patagonia is an austral region characterized by its complex topography and quasi lack of a meteorological network. In this work, three reanalyses are studied (MERRA-2, ERA5, and GLDAS) and compared with the Cerro Castillo and Teniente Gallardo stations (~51°S), with the aim of simulating the winds in the past. The results indicate that ERA5 and MERRA-2 simulate well the wind variability in the study region, while GLDAS is less reliable. Therefore, the first two reanalyses could be used to extend the time series of the meteorological station and calibrate a new wind proxy based on the abundance and size of the aeolian particles, reconstructing in a direct way the intensity of the SWW in the past over southwestern Patagonia. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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20 pages, 2908 KiB  
Article
Toward the Estimation of All-Weather Daytime Downward Longwave Radiation over the Tibetan Plateau
by Zhiyong Long, Lirong Ding, Ji Zhou and Tianhao Zhou
Atmosphere 2021, 12(12), 1692; https://doi.org/10.3390/atmos12121692 - 17 Dec 2021
Cited by 2 | Viewed by 2409
Abstract
Downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. Accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation [...] Read more.
Downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. Accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tests eight methods for clear-sky conditions and six methods for cloudy conditions based on ground-measured data. It is found that the Dilley and O’Brien model and the Lhomme model are most suitable for clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of DLR under clear-sky conditions is approximately 22.5 W/m2 for nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m2. Based on the estimated cloud fraction and meteorological data provided by the China Land Surface Data Assimilation System (CLDAS), hourly all-weather daytime DLR with a 0.0625° resolution over the Tibetan Plateau is estimated. Results demonstrate that the average RMSE of the estimated hourly all-weather DLR is approximately 26.4 W/m2. With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau is generated. This dataset can contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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22 pages, 11157 KiB  
Article
Forest Fires in Madeira Island and the Fire Weather Created by Orographic Effects
by Flavio T. Couto, Rui Salgado and Nuno Guiomar
Atmosphere 2021, 12(7), 827; https://doi.org/10.3390/atmos12070827 - 28 Jun 2021
Cited by 15 | Viewed by 5021
Abstract
Understanding the effects of weather and topography on fire spread in specific contexts, such as oceanic islands, is critical for supporting fire prevention and suppression strategies. In this study, we analyse the atmospheric conditions associated with historical forest fires that have occurred over [...] Read more.
Understanding the effects of weather and topography on fire spread in specific contexts, such as oceanic islands, is critical for supporting fire prevention and suppression strategies. In this study, we analyse the atmospheric conditions associated with historical forest fires that have occurred over complex terrain in Madeira Island, Portugal. The atmospheric Meso-NH model was used to identify the mesoscale environment during three forest fires events. The model was configured into two nested horizontal domains, the outer domain at 2.5 km resolution and the inner domain at 500 m. The paper brings a comprehensive analysis on the factors favouring the evolution of significant large fires occurring in Madeira Island in August 2010, July 2012 and August 2016. These fire events were selected because they are characterized by their large size (between 324.99 ha and 7691.67 ha) that expanded in a short-time period, threatening people and property in the wildland-urban interfaces. The study highlights that local terrain produce orographic effects that enhance the fire danger over the southern slope during typical summer atmospheric conditions. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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21 pages, 6020 KiB  
Article
Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea
by Yi Jiang, Shuai Han, Chunxiang Shi, Tao Gao, Honghui Zhen and Xiaoyan Liu
Atmosphere 2021, 12(6), 766; https://doi.org/10.3390/atmos12060766 - 14 Jun 2021
Cited by 27 | Viewed by 4123
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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15 pages, 7830 KiB  
Article
Temperature Response to Changes in Vegetation Fraction Cover in a Regional Climate Model
by Jose Manuel Jiménez-Gutiérrez, Francisco Valero, Jesús Ruiz-Martínez and Juan Pedro Montávez
Atmosphere 2021, 12(5), 599; https://doi.org/10.3390/atmos12050599 - 5 May 2021
Cited by 1 | Viewed by 1926
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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18 pages, 9927 KiB  
Article
Lake and Land Breezes at a Mediterranean Artificial Lake: Observations in Alqueva Reservoir, Portugal
by Carolina Purificação, Miguel Potes, Gonçalo Rodrigues, Rui Salgado and Maria João Costa
Atmosphere 2021, 12(5), 535; https://doi.org/10.3390/atmos12050535 - 22 Apr 2021
Cited by 6 | Viewed by 2424
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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23 pages, 4035 KiB  
Article
Study of Urban Heat Islands Using Different Urban Canopy Models and Identification Methods
by Rui Silva, Ana Cristina Carvalho, David Carvalho and Alfredo Rocha
Atmosphere 2021, 12(4), 521; https://doi.org/10.3390/atmos12040521 - 20 Apr 2021
Cited by 10 | Viewed by 3904
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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21 pages, 578 KiB  
Conference Report
A Review on the Current Status of Numerical Weather Prediction in Portugal 2021: Surface–Atmosphere Interactions
by Maria José Monteiro, Flavio T. Couto, Mariana Bernardino, Rita M. Cardoso, David Carvalho, João P. A. Martins, João A. Santos, José Luís Argain and Rui Salgado
Atmosphere 2022, 13(9), 1356; https://doi.org/10.3390/atmos13091356 - 25 Aug 2022
Cited by 7 | Viewed by 2547
Abstract
Earth system modelling is currently playing an increasing role in weather forecasting and understanding climate change, however, the operation, deployment and development of numerical Earth system models are extremely demanding in terms of computational resources and human effort. Merging synergies has become a [...] Read more.
Earth system modelling is currently playing an increasing role in weather forecasting and understanding climate change, however, the operation, deployment and development of numerical Earth system models are extremely demanding in terms of computational resources and human effort. Merging synergies has become a natural process by which national meteorological services assess and contribute to the development of such systems. With the advent of joining synergies at the national level, the second edition of the workshop on Numerical Weather Prediction in Portugal was promoted by the Portuguese Institute for the Sea and Atmosphere, I.P. (IPMA), in cooperation with several Portuguese Universities. The event was hosted by the University of Évora, during the period of 11–12 of November 2021. It was dedicated to surface–atmosphere interactions and allowed the exchange of experiences between experts, students and newcomers. The workshop provided a refreshed overview of ongoing research and development topics in Portugal on surface–atmosphere interaction modelling and its applications and an opportunity to revisit some of the concepts associated with this area of atmospheric sciences. This article reports on the main aspects discussed and offers guidance on the many technical and scientific modelling platforms currently under study. Full article
(This article belongs to the Special Issue Modeling of Surface-Atmosphere Interactions)
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