Understanding Land-Atmosphere Interactions: Knowledge from Monitoring to Modelling

A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: closed (30 April 2019) | Viewed by 6675

Special Issue Editors


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Guest Editor
Department of Civil Engineering, National Chung Hsing University, Taichung City 402, Taiwan
Interests: hydro-climatic modeling and forecasting; regional catastrophe modeling and risk assessments; integrated and interdisciplinary climate risk assessments; GIS and remote sensing applications; sustainability and environmental management
Special Issues, Collections and Topics in MDPI journals
National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
Interests: land-atmosphere interactions; applications of remote sensing on global and terrestrial hydrology; anthropogenic effects on the water cycle

Special Issue Information

Dear Colleagues,

Land–atmosphere interactions are complex physical processes subject to classical thermodynamics, local-to-regional specifications, as well as human activity. Among many research opportunities, one imperative issue is to assess how land use/cover changes (LUCC) may influence climate variability owing to massive alteration of landscapes (e.g., rapid urbanization and deforestation) that have been occurring in many regions of the world. This Special Issue invites diverse contributions related to better understanding of land-atmosphere interactions. Studies of this kind should be rooted in diagnostics of observed data linking climate variations with signs of LUCC. We are particularly interested in receiving contributions from peers using statistical and numerical methods to assess how LUCC can exert influence over regional climates and how land-atmosphere interactions can trigger extreme weather and climate events. Contributions of crossing scales and disciplines are also welcome; for instance, investigating teleconnections between LUCC and large-scale circulations and coupling climate, land surface, with land use models for specific purposes.

This Special Issue will select works from Global Land Project (GLP) 2018 Asia Conference. Each submission to this Special Issue should contain at least 50% of new material, e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases. These extended submissions will undergo a peer-review process according to the journal’s rules of action. At least two technical committees will act as reviewers for each extended article submitted to this Special Issue; if needed, additional external reviewers will be invited to guarantee a high-quality reviewing process. Participants of this conference will receive a 20% discount on the Article Processing Charges.

Dr. Chia-Jeng Chen
Dr. Min-Hui Lo
Guest Editors

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Keywords

  • climate variability and dynamics
  • land surface processes
  • land management
  • land use/cover changes
  • land-atmosphere interaction

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Published Papers (1 paper)

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Review

27 pages, 7930 KiB  
Review
Understanding Land–Atmosphere–Climate Coupling from the Canadian Prairie Dataset
by Alan K. Betts and Raymond L. Desjardins
Environments 2018, 5(12), 129; https://doi.org/10.3390/environments5120129 - 4 Dec 2018
Cited by 2 | Viewed by 6207
Abstract
Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land–atmosphere–cloud coupling. The key reason is that trained observers made hourly estimates of the opaque cloud fraction that obscures the sun, moon, or stars, following [...] Read more.
Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land–atmosphere–cloud coupling. The key reason is that trained observers made hourly estimates of the opaque cloud fraction that obscures the sun, moon, or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality such that they can be calibrated against Baseline Surface Radiation Network data to yield the climatology of the daily short-wave, long-wave, and total cloud forcing (SWCF, LWCF and CF, respectively). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing changes sign from negative in the warm season, to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10 °C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud, and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature, and the pressure height of the lifting condensation level are all tightly coupled to the opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between the cloud forcing and the warm season imbalance of the diurnal cycle, which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forcing, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer, goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of the mixing ratio, which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season, and its dependence on reflective cloud. Full article
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