Historical Land-Cover Change Impacts on Climate: Comparative Assessment of LUCID and CMIP5 Multimodel Experiments

2017 ◽  
Vol 30 (4) ◽  
pp. 1439-1459 ◽  
Author(s):  
Quentin Lejeune ◽  
Sonia I. Seneviratne ◽  
Edouard L. Davin

Abstract During the industrial period, many regions experienced a reduction in forest cover and an expansion of agricultural areas, in particular North America, northern Eurasia, and South Asia. Here, results from the Land-Use and Climate, Identification of Robust Impacts (LUCID) and CMIP5 model intercomparison projects are compared in order to investigate how land-cover changes (LCC) in these regions have locally impacted the biophysical land surface properties, like albedo and evapotranspiration, and how this has affected seasonal mean temperature as well as its diurnal cycle. The impact of LCC is extracted from climate simulations, including all historical forcings, using a method that is shown to capture well the sign and the seasonal cycle of the impacts diagnosed from single-forcing experiments in most cases. The model comparison reveals that both the LUCID and CMIP5 models agree on the albedo-induced reduction of mean winter temperatures over midlatitudes. In contrast, there is less agreement concerning the response of the latent heat flux and, subsequently, mean temperature during summer, when evaporative cooling plays a more important role. Overall, a majority of models exhibit a local warming effect of LCC during this season, contrasting with results from the LUCID studies. A striking result is that none of the analyzed models reproduce well the changes in the diurnal cycle identified in present-day observations of the effect of deforestation. However, overall the CMIP5 models better simulate the observed summer daytime warming effect compared to the LUCID models, as well as the winter nighttime cooling effect.

2013 ◽  
Vol 17 (7) ◽  
pp. 2613-2635 ◽  
Author(s):  
H. E. Beck ◽  
L. A. Bruijnzeel ◽  
A. I. J. M. van Dijk ◽  
T. R. McVicar ◽  
F. N. Scatena ◽  
...  

Abstract. Although regenerating forests make up an increasingly large portion of humid tropical landscapes, little is known of their water use and effects on streamflow (Q). Since the 1950s the island of Puerto Rico has experienced widespread abandonment of pastures and agricultural lands, followed by forest regeneration. This paper examines the possible impacts of these secondary forests on several Q characteristics for 12 mesoscale catchments (23–346 km2; mean precipitation 1720–3422 mm yr−1) with long (33–51 yr) and simultaneous records for Q, precipitation (P), potential evaporation (PET), and land cover. A simple spatially-lumped, conceptual rainfall–runoff model that uses daily P and PET time series as inputs (HBV-light) was used to simulate Q for each catchment. Annual time series of observed and simulated values of four Q characteristics were calculated. A least-squares trend was fitted through annual time series of the residual difference between observed and simulated time series of each Q characteristic. From this the total cumulative change (Â) was calculated, representing the change in each Q characteristic after controlling for climate variability and water storage carry-over effects between years. Negative values of  were found for most catchments and Q characteristics, suggesting enhanced actual evaporation overall following forest regeneration. However, correlations between changes in urban or forest area and values of  were insignificant (p ≥ 0.389) for all Q characteristics. This suggests there is no convincing evidence that changes in the chosen Q characteristics in these Puerto Rican catchments can be ascribed to changes in urban or forest area. The present results are in line with previous studies of meso- and macro-scale (sub-)tropical catchments, which generally found no significant change in Q that can be attributed to changes in forest cover. Possible explanations for the lack of a clear signal may include errors in the land cover, climate, Q, and/or catchment boundary data; changes in forest area occurring mainly in the less rainy lowlands; and heterogeneity in catchment response. Different results were obtained for different catchments, and using a smaller subset of catchments could have led to very different conclusions. This highlights the importance of including multiple catchments in land-cover impact analysis at the mesoscale.


2021 ◽  
Author(s):  
Kazi Jihadur Rashid ◽  
Sumaia Islam ◽  
Mohammad Atiqur Rahman

Abstract Urban heat island (UHI) is one of the major causes for deteriorating ecology of the rapidly expanding Dhaka city in the changing climatic conditions. Although researchers have identified, characterized and modeled UHI in the study area, the ecological evaluation of UHI effect has not yet been focused. This study uses land surface normalization techniques such as urban thermal field variance (UTFVI) to quantify the impact of UHI and also identifies vulnerable UHI areas compared to land cover types. Landsat imageries from 1990 to 2020 were used at decadal intervals. Results of the study primarily show that intensified UHI areas have increased spatially from 33.1–40.9% in response to urban growth throughout the period of 1990 to 2020. Extreme surface temperature values above 31°C have also been shown in open soils in under-construction sites for future developmental purposes. UTFVI is categorized into six categories representing UHI intensity in relation to ecological conditions. Finally, comparative analysis between land use/land cover (LULC) with UTFVI shows that the ecological conditions deteriorate as the intensity of UHI increases in the area. The developed areas facing ecological threat have increased from 9.3–19.8% throughout the period. Effective mitigating measures such as increasing green surfaces and planned urbanization practices are crucial in this regard. This study would help policymakers to concentrate on controlling thermal exposure and on preserving sustainable urban life.


2021 ◽  
Vol 10 (12) ◽  
pp. 809
Author(s):  
Jing Sun ◽  
Suwit Ongsomwang

Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature.


2021 ◽  
Author(s):  
Jaime Gaona ◽  
Pere Quintana-Seguí ◽  
Maria José Escorihuela

<p>Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.</p><p>The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the Köppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.</p><p>The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.</p><p>The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.</p>


2019 ◽  
Vol 12 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Chantelle Burton ◽  
Richard Betts ◽  
Manoel Cardoso ◽  
Ted R. Feldpausch ◽  
Anna Harper ◽  
...  

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.


2010 ◽  
Vol 14 (10) ◽  
pp. 2073-2084 ◽  
Author(s):  
F. Zabel ◽  
T. B. Hank ◽  
W. Mauser

Abstract. Regionalization of physical land surface models requires the supply of detailed land cover information. Numerous global and regional land cover maps already exist but generally, they do not resolve arable land into different crop types. However, arable land comprises a huge variety of different crops with characteristic phenological behaviour, demonstrated in this paper with Leaf Area Index (LAI) measurements exemplarily for maize and winter wheat. This affects the mass and energy fluxes on the land surface and thus its hydrology. The objective of this study is the generation of a land cover map for central Europe based on CORINE Land Cover (CLC) 2000, merged with CORINE Switzerland, but distinguishing different crop types. Accordingly, an approach was developed, subdividing the land cover class arable land into the regionally most relevant subclasses for central Europe using multiseasonal MERIS Normalized Difference Vegetation Index (NDVI) data. The satellite data were used for the separation of spring and summer crops due to their different phenological behaviour. Subsequently, the generated phenological classes were subdivided following statistical data from EUROSTAT. This database was analysed concerning the acreage of different crop types. The impact of the improved land use/cover map on evapotranspiration was modelled exemplarily for the Upper Danube catchment with the hydrological model PROMET. Simulations based on the newly developed land cover approach showed a more detailed evapotranspiration pattern compared to model results using the traditional CLC map, which is ignorant of most arable subdivisions. Due to the improved temporal behaviour and spatial allocation of evapotranspiration processes in the new land cover approach, the simulated water balance more closely matches the measured gauge.


2014 ◽  
Vol 10 (4) ◽  
pp. 3127-3161 ◽  
Author(s):  
A. J. Coletti ◽  
R. M. DeConto ◽  
J. Brigham-Grette ◽  
M. Melles

Abstract. Until now, the lack of time-continuous, terrestrial paleoenvironmental data from the Pleistocene Arctic has made model simulations of past interglacials difficult to assess. Here, we compare climate simulations of four warm interglacials at Marine Isotope Stage (MIS) 1 (9 ka), 5e (127 ka), 11c (409 ka), and 31 (1072 ka) with new proxy climate data recovered from Lake El'gygytgyn, NE Russia. Climate reconstructions of the Mean Temperature of the Warmest Month (MTWM) indicate conditions 2.1, 0.5 and 3.1 °C warmer than today during MIS 5e, 11c, and 31, respectively. While the climate model captures much of the observed warming during each interglacial, largely in response to boreal summer orbital forcing, the extraordinary warmth of MIS 11c relative to the other interglacials in the proxy records remain difficult to explain. To deconvolve the contribution of multiple influences on interglacial warming at Lake El'gygytgyn, we isolated the influence of vegetation, sea ice, and circum-Arctic land ice feedbacks on the climate of the Beringian interior. Simulations accounting for climate-vegetation-land surface feedbacks during all four interglacials show expanding boreal forest cover with increasing summer insolation intensity. A deglaciated Greenland is shown to have a minimal effect on Northeast Asian temperature during the warmth of stage 11c and 31 (Melles et al., 2012). A prescribed enhancement of oceanic heat transport into the Arctic ocean has some effect on Beringian climate, suggesting intrahemispheric coupling seen in comparisons between Lake El'gygytgyn and Antarctic sediment records might be related to linkages between Antarctic ice volume and ocean circulation. The exceptional warmth of MIS 11c remains enigmatic however, relative to the modest orbital and greenhouse gas forcing during that interglacial. Large Northern Hemisphere ice sheets during Plio-Pleistocene glaciation causes a substantial decrease in Mean Temperature of the Coldest Month (MTCM) and Mean Annual Precipitation (PANN) causing significant Arctic aridification. Aridification and cooling can be linked to a combination of mechanical forcing from the Laurentide and Fennoscandian ice sheets on mid-tropospheric westerly flow and expanded sea ice cover causing albedo-enhanced feedback.


2017 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Aurore Brut ◽  
...  

Abstract. Agricultural landscapes often include a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes as simulated by land surface and distributed hydrological models. Sentinel-2 mission satellite remote sensing products allow for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy flux via the ISBA-SURFEX land surface model. The study area is a 24 km by 24 km agricultural zone in southwestern France. An initial reference simulation was conducted from 2006–2010 using the ECOCLIMAP-II database. This global numerical land ecosystem database was created at a 1 km resolution and includes an ecosystem classification with a consistent set of land surface parameters required for the model, such as the Leaf Area Index (LAI) and albedo measures. The LAI of ECOCLIMAP is climatologic and derived from a 2000–2005 analysis of MODIS satellite products. This low resolution induces that several vegetation covers can be mixed in a model cell. The climatic construction of LAI dynamics also suggests that there is no interannual variability in the vegetation cycle. A second simulation was performed by forcing the same model with annual land cover maps and monthly LAI values derived from a series of 105 8 m-resolution Formosat-2 images for the same period. Both simulations were conducted at the parcel scale, i.e., a computation unit covers an area of connected pixels of the same vegetation type (a crop field, forest patch, etc.). To evaluate our simulations, we used in situ measurements of evapotranspiration and latent and sensible heat flux from two eddy covariance stations in the study area. Our results show that the use of Formosat-2 high-resolution products significantly improves simulated evapotranspiration results with respect to ECOCLIMAP-II, especially when a surface is covered with summer crops (the correlation coefficient with monthly measurements is increased by roughly 0.3 and the root mean square error is decreased by roughly 31 %). This finding is attributable to a better description of LAI evolution processes reflected by Formosat-2 data, which further modify soil water content and drainage levels of deep soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels from Formosat-2 data in comparison to reference values. In smaller proportions, runoff is also increased by roughly 1 % of annual precipitation when using Formosat-2 data. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.


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