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Atmosphere
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Land Surface and its Interaction with the Atmosphere
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Land Surface and its Interaction with the Atmosphere

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 10274

Special Issue Editor

Dr. Jan-Peter Schulz

E-Mail Website
Guest Editor
Deutscher Wetterdienst, 63067 Offenbach am Main, Germany
Interests: land surface modelling; land surface-atmosphere interaction; phenology; urban processes; numerical weather prediction; climate modelling

Special Issue Information

Dear Colleagues,

Continental surfaces, including vegetation cover, represent an important component of the Earth’s climate system. On the one hand, they are the habitat of humanity, which makes it interesting to try to understand the governing processes and living conditions at the land surface and how they may evolve in the future. On the other hand, from the point of view of atmospheric sciences, the land surface and biosphere interact with the lower atmosphere, and they have a significant impact on near-surface meteorological and climatological phenomena. Atmospheric regional and global models for numerical weather prediction or climate simulations therefore require a realistic description of the land surface processes. The degree of complexity needed for these land surface schemes is not yet completely determined.

This Special Issue aims at providing an update on the general topics of land surface processes and land surface–atmosphere interactions, both in atmospheric modeling of weather and climate and in experimental studies, e.g., in field experiments or satellite remote sensing. Manuscripts on all aspects of these topics are welcome, including, e.g., studies on the processes determining surface conditions such as temperature and humidity and their interactions with the atmosphere, in natural environments but also under anthropogenic effects such as land use change.

Dr. Jan-Peter Schulz
Guest Editor

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 submissions that pass pre-check are 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 2400 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

  • land surface processes
  • land surface-atmosphere interactions
  • land use and land cover change
  • vegetation and urban modelling
  • surface biophysical processes

Published Papers (5 papers)

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Research

13 pages, 1450 KiB  
Article
Snow Representation over Siberia in Operational Seasonal Forecasting Systems
by Danny Risto, Kristina Fröhlich and Bodo Ahrens
Atmosphere 2022, 13(7), 1002; https://doi.org/10.3390/atmos13071002 - 22 Jun 2022
Viewed by 1150
Abstract
Seasonal forecasting systems still have difficulties predicting temperature over continental regions, while their performance is better over some maritime regions. On the other hand, the land surface is a substantial source of (sub-)seasonal predictability. A crucial land surface component in focus here is [...] Read more.
Seasonal forecasting systems still have difficulties predicting temperature over continental regions, while their performance is better over some maritime regions. On the other hand, the land surface is a substantial source of (sub-)seasonal predictability. A crucial land surface component in focus here is the snow cover, which stores water and modulates the surface radiation balance. This paper’s goal is to attribute snow cover seasonal forecasting biases and lack of skill to either initialization or parameterization errors. For this purpose, we compare the snow representation in five seasonal forecasting systems (from DWD, ECMWF, Météo-France, CMCC, and ECCC) and their performances in predicting snow and 2-m temperature over a Siberian region against ERA5 reanalysis and station data. Although all systems use similar atmospheric and land initialization approaches and data, their snow and temperature biases differ in sign and amplitude. Too-large initial snow biases persist over the forecast period, delaying and prolonging the melting phase. The simplest snow scheme (used in DWD’s system) shows too-early and fast melting in spring. However, systems including multi-layer snow schemes (Météo-France and CMCC) do not necessarily perform better. Both initialization and parameterization are causes of snow biases, but, depending on the system, one can be more dominant. Full article
(This article belongs to the Special Issue Land Surface and its Interaction with the Atmosphere)
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18 pages, 2362 KiB  
Article
Spatiotemporal Influences of LULC Changes on Land Surface Temperature in Rapid Urbanization Area by Using Landsat-TM and TIRS Images
by Eduardo Andre Kaiser, Silvia Beatriz Alves Rolim, Atilio Efrain Bica Grondona, Cristiano Lima Hackmann, Rodrigo de Marsillac Linn, Pâmela Suélen Käfer, Nájila Souza da Rocha and Lucas Ribeiro Diaz
Atmosphere 2022, 13(3), 460; https://doi.org/10.3390/atmos13030460 - 11 Mar 2022
Cited by 9 | Viewed by 2170
Abstract
The inverse correlation between NDVI and LST is widely known for its long time series. However, when more specific statistical tests were performed, subtle differences in the correlation behavior over time are more clearly observed. In this work, regression analyses were performed between [...] Read more.
The inverse correlation between NDVI and LST is widely known for its long time series. However, when more specific statistical tests were performed, subtle differences in the correlation behavior over time are more clearly observed. In this work, regression analyses were performed between NDVI and LST at intervals of approximately 10 years, quantifying this relationship for an area of transition from vegetation to urban occupation from 1985 to 2018. The removal of vegetation cover (reduction of 51% to 7% in grassland and 14.4% to 0.6% in forest) to occupy impermeable surfaces ( increase of 31% to 91% in urban areas) caused an average LST increase of 4.18 °C when compared to the first and last decades of the historical series. Temporal analysis allowed us to verify the increase in temperature in the four seasons. The largest difference was 6.36 °C between the first and last decade of autumn, 4.40 °C in spring, 4.09 °C in summer, and 2.41 °C in winter. The results also show that LST has a negative correlation with NDVI, especially in urban areas, with an increase in this correlation during the period (1989: R = −0.55; 1999: R = −0.58; 2008: R = −0.59; 2018: R = −0.76). Our study results will help policymakers understand the dynamics of temperature increases by adding scientifically relevant information on the sustainable organization of the urban environment. Full article
(This article belongs to the Special Issue Land Surface and its Interaction with the Atmosphere)
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14 pages, 15114 KiB  
Article
Simulation of the Scalar Transport above and within the Amazon Forest Canopy
by Edivaldo M. Serra-Neto, Hardiney S. Martins, Cléo Q. Dias-Júnior, Raoni A. Santana, Daiane V. Brondani, Antônio O. Manzi, Alessandro C. de Araújo, Paulo R. Teixeira, Matthias Sörgel and Luca Mortarini
Atmosphere 2021, 12(12), 1631; https://doi.org/10.3390/atmos12121631 - 07 Dec 2021
Cited by 2 | Viewed by 2252
Abstract
The parallelized large-eddy simulation model (PALM) was used to understand better the turbulent exchanges of a passive scalar above and within a forested region located in the central Amazon. Weak (2 ms−1) and strong (6 ms−1) wind [...] Read more.
The parallelized large-eddy simulation model (PALM) was used to understand better the turbulent exchanges of a passive scalar above and within a forested region located in the central Amazon. Weak (2 ms−1) and strong (6 ms−1) wind conditions were simulated. A passive scalar source was introduced to the forest floor for both simulations. The simulations reproduced the main characteristics of the turbulent flow and of the passive scalar transport between the forest and the atmosphere. Noteworthily, strong and weak wind conditions presented different turbulence structures that drove different patterns of scalar exchange both within and above the forest. These results show how passive scalar concentration is influenced by the wind speed at the canopy top. Additionally, higher wind speeds are related to stronger sweep and ejection regimes, generating more intense plumes that are able to reduce the passive scalar concentration inside the forest canopy. This work was the first that used PALM to investigate scalar transport between the Amazon rainforest and the atmosphere. Full article
(This article belongs to the Special Issue Land Surface and its Interaction with the Atmosphere)
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24 pages, 11484 KiB  
Article
A Sensitivity Assessment of COSMO-CLM to Different Land Cover Schemes in Convection-Permitting Climate Simulations over Europe
by Mingyue Zhang, Merja H. Tölle, Eva Hartmann, Elena Xoplaki and Jürg Luterbacher
Atmosphere 2021, 12(12), 1595; https://doi.org/10.3390/atmos12121595 - 29 Nov 2021
Cited by 2 | Viewed by 1763
Abstract
The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of [...] Read more.
The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of the atmosphere. In this study, we used three independent land cover data sets, GlobCover 2009, GLC2000 and ESACCI-LC, as the lower boundary of the regional climate model COSMO-CLM (Consortium for Small Scale Modeling in Climate Mode, v5.0-clm15) to perform convection-permitting regional climate simulations over the large part of Europe covering the years 1999 and 2000 at a 0.0275° horizontal resolution. We studied how the sensitivity of the impacts on regional and local climates is represented by different land cover maps and fractions, especially between warm (summer) and cold (winter) seasons. We show that the simulated regional climate is sensitive to different land cover maps and fractions. The simulated temperature and observational data are generally in good agreement, though with differences between the seasons. In comparison to winter, the summer simulations are more heterogeneous across the study region. The largest deviation is found for the alpine area (−3 to +3 °C), which might be among different reasons due to different classification systems in land cover maps and orographical aspects in the COSMO-CLM model. The leaf area index and plant cover also showed different responses based on various land cover types, especially over the area with high vegetation coverage. While relating the differences of land cover fractions and the COSMO-CLM simulation results (the leaf area index, and plant coverage) respectively, the differences in land cover fractions did not necessarily lead to corresponding bias in the simulation results. We finally provide a comparative analysis of how sensitive the simulation outputs (temperature, leaf area index, plant cover) are related to different land cover maps and fractions. The different regional representations of COSMO-CLM indicate that the soil moisture, atmospheric circulation, evaporative demand, elevation, and snow cover schemes need to be considered in the regional climate simulation with a high horizontal resolution. Full article
(This article belongs to the Special Issue Land Surface and its Interaction with the Atmosphere)
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10 pages, 1968 KiB  
Article
Objective Calibration of Numerical Weather Prediction Model: Application on Fine Resolution COSMO Model over Switzerland
by Antigoni Voudouri, Euripides Avgoustoglou, Izthak Carmona, Yoav Levi, Edoardo Bucchignani, Pirmin Kaufmann and Jean-Marie Bettems
Atmosphere 2021, 12(10), 1358; https://doi.org/10.3390/atmos12101358 - 18 Oct 2021
Cited by 7 | Viewed by 1818
Abstract
The objective calibration method originally performed on regional climate models is applied to a fine horizontal resolution Numerical Weather Prediction (NWP) model over a mainly continental domain covering the Alpine Arc. The method was implemented on the MeteoSwiss COSMO (consortium for a small-scale [...] Read more.
The objective calibration method originally performed on regional climate models is applied to a fine horizontal resolution Numerical Weather Prediction (NWP) model over a mainly continental domain covering the Alpine Arc. The method was implemented on the MeteoSwiss COSMO (consortium for a small-scale modeling) model with a resolution of 0.01° (approximately 1 km). For the model calibration, five tuning parameters of the parameterization schemes affecting turbulence, soil-surface exchange and radiation were chosen. A full year was simulated, with the history of the soil included (hindcast) to find the optimal parameter value. A different year has been used to give an independent assessment of the impact of the optimization process. Although the operational MeteoSwiss model is already a well-tuned configuration, the results showed that a slight model performance gain is obtained by using the Calibration of COSMO (CALMO) methodology. Full article
(This article belongs to the Special Issue Land Surface and its Interaction with the Atmosphere)
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