Main directions in modern research of interaction between climate and land use/land cover changes

  • L. A. Pysarenko
  • S. V. Krakovska
Keywords: climate change, natural resource management, land cover, atmospheric boundary layer, climate model, satellite monitoring, anthropogenic activity

Abstract

The purpose of the research is to analyse and assess existing approaches in investigation of interconnections between climate and underlying surface. Land use/land cover (LULC) influences climate formation via physical and chemical properties (albedo, roughness, height, chemical composition etc.). Climate in its turn affects land cover by means of meteorological parameters (air temperature and humidity, precipitation, wind etc.) and causes both cyclic and irreversible changes in land cover. In addition, anthropogenic factors exacerbate surface-climate interactions through? for example, LULC change that usually causes an additional release of chemical compounds. The paper distinguishes three main directions of the “climate - LULC” interactions research that is conducted mainly with application of satellite monitoring products, observation dataset, geographic information systems (GIS) and numerical modelling. The first direction implies monitoring and research of cyclic changes and transformation of LULC influenced by natural and anthropogenic factors, using different GIS-based satellite and surface meteorological observation databases. Despite significant technical progress and great amount of studies conducted for detecting dynamics of LULC change for different time intervals, the problems of dealing with cloudiness and shadows from orographic and other objects still remain. The second direction investigates the influence of LULC change on the chemical composition in the atmospheric boundary layer and on the regional climate. Numerous researches were dedicated to the influence of different kinds of surface such as forests, grasslands, croplands, urban areas etc. on climate characteristics and also on fluxes, for example, CO2. The effect of midlatitude forests on climate remains to be one of the challenging and urgent issues. The third direction relates to LULC change modelling and regional climate modelling. For the last decade a spatial resolution of models was considerably increased and, as a result, representation of interaction between atmosphere and land improved. Online integrated numerical atmospheric models are found as the most promising ones. They include "meteorological parameters – atmospheric chemical composition" feedbacks and can consider LULC on global and regional scales. However, some issues still need improvement, namely radiative transfer, cloud microphysics, cloud-aerosol-precipitation interactions, as well as parametrizations of some types of land and their interaction with the atmospheric boundary layer.

References

Lipinsky, V.M., Diachuk, V.A. & Babichenko, V.M. (eds). (2003). Klimat Ukrainy [Climate of Ukraine]. Kyiv: Nika-Tsentr. (in Ukr.)

Mishchenko, Z.A. & Liashenko, G.V. (2005). Mikroklimatolohiia. [Microclimatology]. Odesa (In Ukr.)

Osadchiy, V.I., Babichenko, V.M., Nabyvanets Y.B. et al. (2013). Dynamika temperatury povitria v Ukraini za period instrumentalnykh meteorolohichnykh sposterezhen [Dynamics of Air Temperature in Ukraine over Instrumental Observation Period]. Kyiv: Nika-Tsentr. (in Ukr.)

Lipinsky, V.M., Osadchyi V. & Babichenko, V.M. (eds.) (2006). Stykhiini meteorolohichni yavyshcha na terytorii Ukrainy za ostannie dvadtsiatyrichchia (1986-2005). [Natural meteorological weather phenomena in Ukraine for the last twenty years (1986-2005)]. Kyiv. (in Ukr.)

Barry, R. & Hall-McKim, E.A. (2014). Essentials of the Earth’s Climate System. Cambridge University Press.

Korhonen, H., Lehtinen, K.E.J. & Kulmala, M. (2004). Multicomponent aerosol dynamics model UHMA: model development and validation. Atmospheric Chemistry and Physics, 4, pp. 757–771. https://doi.org/10.5194/acp-4-757-2004

IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse gas fluxes in Terrestrial Ecosystems. Available at: https://www.ipcc.ch/site/assets/uploads/2019/08/Fullreport-1.pdf (Accessed: 29.10.2019).

Foteck Fonji, S. & N. Taff, G. (2014). Using satellite data to monitor land-use land-cover change in North-eastern Latvia. SpringerPlus, 61 (3). https://doi.org/10.1186/2193-1801-3-61.

Gao, Y. (2016). Interactions between land surface, forests and climate: regional modelling studies in the boreal zone. PhD thesis. University of Helsinki. Department of Physics. Available at: https://helda.helsinki.fi/handle/10138/166502 (Accessed: 27.08.2019)

de Noblet-Ducoudr´e et al. (2011). Determining robust impacts of land-use induced land-cover changes on surface climate over North America and Eurasia: Results from the first set of LUCID experiments. Journal of Climate, 25, pp. 3261-3281. https://doi.org/10.1175/JCLI-D-11-00338.1

Stysiak, A.A., Jensen, M.B. & Mahura, A. (2015). Impact of regional afforestation on climatic conditions in Copenhagen Metropolitan Area: Scientific report. Available at: https://www.dmi.dk/fileadmin/user_upload/Rapporter/SR/2015/sr15-07.pdf (Accessed: 10.09.2019)

Stocker, T. (2011). Introduction to Climate Modelling. Springer. https://doi.org/10.1007/978-3-642-00773-6

Ojima, D. (1992). Modelling the Earth System. UCAR. Office for Interdisciplinary Earth Studies.

Prusov, V.A. & Doroshenko, A.Yu. (2006). Modeliuvannia pryrodnykh i tekhnohennykh protsesiv v atmosferi [Modelling natural and technogenic processes in the atmosphere]. Kyiv: Naukova Dumka. (In Ukr.)

Stepanenko, S.M. (2013). Dynamika ta modeliuvannia klimatu [Dymamics and climate modeling]. Odesa: Ekolohiia. (In Ukr.)

Dymnikov, V.P., Lykosov V.N., Volodin E.M. et al. (2005). Modelirovanie klimata i ego izmeneniy [Modeling climate and its changes] . In: Dymnikov V.P. (eds). Sovremennye problemy vychislitel'noy matematiki i matematicheskogo modelirovaniya [Contemporary problems of numerical mathematics and mathematical modelling]. Vol. 2. Matematicheskoe modelirovanie. [Mathematical modelling]. Moscow: Nauka, pp. 38-175

Global warming of 1.5°C. Summary for Policymakers. Available at: https://report.ipcc.ch/sr15/pdf/ sr15_spm_final.pdf (Accessed: 01.09.2019)

Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the IPCC. Available at: http://www.climatechange2013.org/images/report/WG1AR5_ALL_FINAL.pdf (Accessed: 01.09.2019)

Pielke, R., et al. (2011). Land use/land cover changes and climate: modeling analysis and observational evidence.WIREs Clim Change, 2, pp. 828–850. https://doi.org/10.1002/wcc.144.

Pitman, A.J. (2003). The evolution of, and revolution in, land surface schemes designed for climate models. International Journal of Climatology, 23, pp. 479–510. https://doi.org/10.1002/joc.893.

Baklanov, A. et al. (2017). Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2). Geoscientific Model Development, 10, pp. 2971–2999. https://doi.org/10.5194/gmd-10-2971-2017

About the FLUXNET Network. Available at: https://fluxnet.fluxdata.org/about/ (Accessed: 10.09.2019)

Liu, Y. et al. (2018). Satellite-derived LAI products exhibit large discrepancies and can lead to substantial uncertainty in simulated carbon and water fluxes. Remote Sensing of Environment, 206, pp.174-188

Fangjie, M. et al. (2017). Coupled LAI assimilation and BEPS model for analyzing the spatiotemporal pattern and heterogeneity of carbon fluxes of the bamboo forest in Zhejiang Province, China. Agricultural and Forest Meteorology, 242, pp. 96-108. https://doi.org/10.1016/ j.agrformet.2017.03.022

Reichenau, T.G. et al. (2016). Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA). Plos One, 11(7), https://doi.org/10.1371/ journal.pone.0158451

Liu, J. et al. (1997). A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote sensing environment, 62 (2), pp. 158-175.

https://doi.org/10.1016/S0034-4257(97)00089-8

Duveiller, G., Hooker, J. & Cescatti, A. (2018). Data Descriptor: A dataset mapping the potential biophysical effects of vegetation cover change. Scientific Data, 5. https://doi.org/10.1038/sdata.2018.14

The Land Cover CCI Climate Research Data Package. Available at: http://maps.elie.ucl.ac.be/CCI/viewer/download.php#usertool (Accessed: 19.09.2019)

Kurbanov, E.A., Vorobyev, O.N., Gubayev, A.V. et al. (2014). Chetyre desiatiletiia issledovanyi lesov po snimkam landsat [Four decades of forest research with the use of Landsat images]. Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo universiteta. Serija: Les. Ekologiya. Prirodopol'zovanie. [Vestnik of Volga State University of Technology. Series: Forest. Ecology. Nature Management], 1(21), pp.18-32. (In Russ.)

Sivanpillai, R. et al. (2006). Estimation of managed loblolly pine stand age and density with Landsat ETM+ data. Forest Ecology and Management, 223, pp. 247–254.

Cohen, W.B. & Spies, T.A. (1992). Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and Spot imagery. Remote Sensing of Environment, 41(1), pp. 1–17.

Heikkila, J., Nevalainen, S. & Tokola, T. (2002). Estimating defoliation in boreal coniferous forests by combining Landsat TM, aerial photographs and field data. Forest ecology and Management, 158, pp. 9–23.

Kurbanov, E.A., Vorobyev, O.N., Nezamayev, S.A. et al. (2013). Tematycheskoe kartirovanie i stratifikatsiia lesov Mariiskoho Zavolzhia po sputnikovym snimkam Landsat. [Thematic mapping and stratification of forests in Middle Zavolsgie by Landsat satelite images]. Vestnik Povolzhskogo gosudarstvennogo tehnologicheskogo universiteta. Serija: Les. Ekologiya. Prirodopol'zovanie [Vestnik of Volga State University of Technology. Series: Forest. Ecology. Nature Management], 3(19), pp. 72-82. (In Russ.)

Elsakov, V.V. (2012). Sputnykovaia siemka v otsenke produktivnosti ekosistem Evropeiskoho Severa [The remote sensing data in European North productivity estimation]. Sovremennye problemy distancionnogo zondirovanija Zemli iz kosmosa [Current problems in remote sensing of the Earth from space], 1, pp.87-94. (In Russ.)

Bhagat, V.S. (2009). Use of Landsat ETM+ data for detection of potential areas for afforestation. International Journal of Remote Sensing, 30(10), pp. 2607–2617.

Levin, N. et al (2009). Mapping forest patches and scattered trees from SPOT images and testing their ecological importance for woodland birds in a fragmented agricultural landscape. International Journal of Remote Sensing, 30(12), pp. 3147–3169.

Kuemmerle, T. et al. (2016). Hotspots of land use change in Europe. Environmental Research Letters, 15, doi:10.1088/1748-9326/11/6/064020

Skakun S., Kussul N., Kussul O. et al. (2014). Quantitative estimation of drought risk in Ukraine using satellite data. Geoscience and Remote Sensing Symposium (IGARSS), IEEE International. pp. 5091-5094. https://doi.org/10.1109/IGARSS.2014.6947642

Kussul, N., Lavreniuk, M., Shelestov, A. et al. (2016). Along the season crop classification in Ukraine based on time series of optical and SAR images using ensemble of neural network classifiers. 2016 IEEE International Geoscience and Remote Sensing Symposium, Beijing, China. https://doi.org/10.1109/IGARSS.2016.7730864.

Shelestov, A., Lavreniuk, M., Kussul, N. et al. (2017). Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping. Frontiers in Earth Science, 5. https://doi.org/10.3389/feart.2017.00017

Ghazaryan, G., Dubovyk, O., Kussul, N. et al. (2016). Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013. Remote Sensing, 8, https://doi.org/doi:10.3390/rs8080617

Lesiv, M., Schepaschenko, D., Moltchanova, E., et al. (2018). Spatial distribution of arable and abandoned land across former Soviet Union countries. Scientific Data, 5, https://doi.org/10.1038/sdata.2018.56

Martazinova, V.F. & Shchehlov, O.A. (2018). [Nature of extreme precipitation over Ukraine in the 21st century]. Ukraïnsʹkij gìdrometeorologìčnij žurnal [Ukrainian hydrometeorological journal], 22. pp. 36-45. https://doi.org/10.31481/uhmj.22.2018.04 (in Russ.)

Zabolotska, T.M., Shpyg V.M. (2015). [Quantitative changes of cloud cover as indicator of global warming period]. Naukovi pratsi UkrNDHMI [Scientific Papers of UHMI], 267, pp.23-27.

Climate change 2014. Synthesis report. Available at: https://www.ipcc.ch/site/assets/uploads/2018/05/SYR_AR5_FINAL_full_wcover.pdf (Accessed: 19.06.2019)

Randerson, J.T. et al. (2006). The Impact of Boreal Forest Fire on Climate Warming. Science, 17, pp. 1130-1132.

Balabukh, V.O. & Zibtsev, S.V. (2016). [Impact of climate change on the quantity and area of forest fires in the North part of the Black sea region of Ukraine]. Ukraïnsʹkij gìdrometeorologìčnij žurnal [Ukrainian hydrometeorological journal], 18, pp. 60-71 (In Ukr.) https://doi.org/10.31481/uhmj.18.2016.07

Global Fire Emissions Database. Available at: https://www.globalfiredata.org/data.html (Accessed: 19.09.2019)

Gordon, B. Bonan. (2008). Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests. Science, 320, pp. 1444-1449.

Thom, D., Rammer, W. & Seidl, R. (2017). The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes. Ecological Monographs, 87(4), pp. 665–684. https://doi.org/ 10.1002/ecm.1272.

Sanderson, M et al. (2012). Relationships between forests and weather. EC Directorate General of the Environment 13th January 2012. Available at: http://ec.europa.eu/environment/forests/pdf/EU_Forests_annex1.pdf (Accessed: 25.09.2019)

Makhnykina, A.V., Prokushkin, A.S., Vaganova, E.A. et al. (2016). [Dynamics of the CO2 Fluxes from the Soil Surface in Pine Forests in Central Siberia]. Zhurnal Sibirskogo federal'nogo universiteta. Biologiya [Journal of Siberian Federal University. Biology], 3 (9), pp. 338-357 (In Russ.)

Lyashenko, H.V. & Kuznetsova, Yu.O. (2016). [Influence of forestry in the South of Ukraine on carbon dioxide control in the atmosphere]. Ukraïnsʹkij gìdrometeorologìčnij žurnal [Ukrainian Hydrometeorological Journal], 18, pp. 105-111. https://doi.org/10.31481/uhmj.18.2016.12

Khalaim, O.O. (2017). Otsinka potokiv CO2 u modelnykh stepovykh skosystemakh za riznoi kilkosti opadiv [Estimation of CO2 fluxes in model steppe ecosystems under altered precipitation]. Abstract of PhD in Biology. National University “Kyiv-Mohyla Academy” (In Ukr.)

Lyalko, V.I. (2015). Parnykovyi efekt i zminy klimatu v Ukraini: otsinky ta naslidky. [Greenhouse Effect and Climate Changes in Ukraine: assessments and consequences]. Kyiv: Naukova Dumka (In Ukr.)

Reducing Urban Heat Islands: Compendium of Strategies. Urban Heat Island Basics. Available at: https://www.epa.gov/sites/production/files/2014-06/documents/basicscompendium.pdf (Accessed: 25.06.2019)

Shevchenko, O. (2017). [Climate change manifestation on the territory of Kyiv and main approaches to its adaptation]. Chasopys kartohrafii [Magazine of Cartography], 1, pp. 108-122. (In Ukr.)

Mahmood, R. (2010). Impacts of Land Use/Land Cover Change on Climate and Future Research Priorities. Bulletin of the American Meteorological Society, 91, pp. 37-46.

Snizhko, S.I. & Shevchenko, O.H. (2011). Urbometeorolohichni aspekty zabrudnennia atmosfernoho povitria velykoho mista [Meteorological aspects of air pollution of Urban Areas]. Kyiv: Obrii. (In Ukr.)

Savenets, M., Nadtochii, L. & Dvoretska, I. (2018). NO2 seasonal and interannual variability in Ukrainian industrial cities. GeoScience Engineering, LXIV (4)., pp. 29–36.

Nadtochii, L.M., Savenets, M.V., Bashtannik, M.P. et al. (2019. [The features of dust air-polluiton dynamics in certain Ukrainian cities]. Ukrainskyi heohrafichnyi zhurnal [Ukrainian Geographical Journal], 1, pp. 43-50 (In Ukr.)

Palamarchuk, L.V. & Krakovska, S.V. (2018). Rehionalni zminy klimatu Ukrainy: Metodychni vkazivky do navchalnoho kursu dlia studentiv heohrafichnoho fakultetu spetsialnosti «Meteorolohiia Ta Klimatolohiia» [Regional climate change in Ukraine: training manual]. Kyiv: Print-Servis. (In Ukr.)

Khokhlov, V. & Yermolenko, N. (2015). [Future climate change and it`s impact on precipitation and temperature in Ukraine]. Ukraïnsʹkij gìdrometeorologìčnij žurnal [Ukrainian hydrometeorological journal], 16, pp.76-82. https://doi.org/10.31481/uhmj.16.2015.10

Pol’ovyi, А.M. & Bozhko, L.Yu. (2015). [Thermal resources of Ukraine in the conditions of climate change]. Ukraïnsʹkij gìdrometeorologìčnij žurnal [Ukrainian hydrometeorological journal], 16, pp.99-106. https://doi.org/10.31481/uhmj.16.2015.13

Palamarchuk, Yu.O., Ivanov, S.V. & Ruban, I.G. (2017). Tekhnologiya chislennogo opisaniya sostoyaniya atmosfery na osnove modeliruyushchey sistemy HARMONIE. [Technology of numerical description atmosphere based on modeling system HARMONIE]. Tezy dopovidei 1th Vseukrainskoho hidrometeorolohichnoho zizdu z mizhnarodnoiu uchastiu [Theses of reports of the First All-Ukrainian Hydrometeorological Congress with International Participation], 22-23 March. Odesa. Available at: http://eprints.library.odeku.edu.ua/1924/ (In Russ.)

Groisman, P.Ya. & Ivanov, S.V. (2009). Regional aspects of climate-terrestrial-hydrologic interactions in non-boreal Eastern Europe. Springer.

Galytska, E., Danylevsky, V. & Snizhko, S. (2014). [State of aerosol pollution of the atmosphere over Kyiv by means of remote studies AERONET and the impact of forest fires in the summer of 2010]. Geopolitika i ekogeodinamika regionov [Geopolitics and Ecogeodynamics of regions], 10, pp. 437-444. (In Ukr.)

Galytska, E., Danylevsky, V., Hommel, R. et al. (2018). Increased aerosol content in the atmosphere over Ukraine during summer 2010. Atmospheric Measurement Techniques, 11, pp. 2101-2118. https://doi.org/10.5194/amt-11-2101-2018

Peters, E.B. et al. (2013). Potential climate change impacts on temperate forest ecosystem processes. Canadian Journal of Forest Research, 43, pp.939-950.

Morin, X. et al. (2018). Long-term response of forest productivity to climate change is mostly driven by change in tree species composition. Scientific Reports, 8, https://doi.org/10.1038/s41598-018-23763-y

Chang, J. et al. (2017). Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance. Carbon Balance Management, 12, https://doi.org/10.1186/s13021-017-0079-8

Arneth, A. et al. (2016). Future vegetation–climate interactions in Eastern Siberia: an assessment of the competing effects of CO2 and secondary organic aerosols. Atmospheric Chemistry and Physics, 16, pp. 5243-5262

Shvidenko, A., Buksha, I. & Krakovska, S. (2018). Urazlyvist lisiv Ukrainy do zminy klimatu [Vulnerability of Ukraine’s forests to climate change]. Kyiv: Nika-Centre.

Findell, K.L. et al. (2009). Regional and global impacts of land cover change and sea surface temperature anomalies. Journal of Climate, 22, pp. 3248–3269. https://doi.org/10.1175/2008JCLI2580.1.

Rummukainen, M. et al. (2015). Twenty-first-century challenges in regional climate modeling. Bulletin of the American Meteorological Society, 96(8), pp. 135-137. https://doi.org/10.1175/BAMS-D-14-00214.1

Lawston, P.M. et al. (2017). Assessment of Irrigation Physics in a Land Surface Modeling Framework using Non-Traditional and Human-Practice Datasets. Hydrology and Earth System Sciences, 21(6), pp. 2953–2966.

https://doi.org/doi:10.5194/hess-21-2953-2017

Mahmood, R. et al. (2014). Land cover changes and their biogeophysical effects on climate. International Journal of Climatology, 34, pp. 929-953.

Published
2020-07-16
How to Cite
Pysarenko, L. A., & Krakovska, S. V. (2020). Main directions in modern research of interaction between climate and land use/land cover changes. Ukrainian Hydrometeorological Journal, (25), 38-52. https://doi.org/10.31481/uhmj.25.2020.04
Section
Meteorology and Climatology