Application of the complete CORINE land covers for modelling in WRF model

2021 ◽  
Author(s):  
Hajnalka Breuer ◽  
Zsuzsanna Zempléni ◽  
Ákos Varga
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Hungarian Academy ◽  
Substantial Effect ◽  
Convective Precipitation ◽  
Near Surface ◽  
Land Cover Types ◽  
One Year

<p>Land use information is crucial in weather modelling as it determines the energy partitioning of the land surface. Based on the partitioning heating of near surface air and moisture supply of the planetary boundary layer is determined. These processes affect the general calculation of temperature, but it also has substantial effect on precipitation formation, especially on convective precipitation.</p><p>In this study the CORINE 44 categories are integrated into the WRF model. Usually the 44 land cover types are recategorized into a standard USGS or MODIS land use types. Here we present a dataset and application with the complete integration of the 44 types.</p><p>One-year runs are created with the CORINE land cover compared to the standard USGS dataset. Along with the new land cover types vegetation parameters had be defined as well. Four runs refer to a USGS-reference, CORINE2USGS converted, CORINE-USGS parameter, CORINE-newparameters where the effect of land cover and parameter change is analyzed. The modelled area covers the whole European region with 50 km resolution using the WRF 4.2 model. Regionally, on a monthly average 5-30% difference in precipitation and around 1 °C differences occur.</p><p>The research was supported by the Hungarian National Research, Development and Innovation Office, Grant No. FK132014. Hajnalka Breuer's work was additionally financed by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.</p>

scholarly journals Continuous and consistent land use/cover change estimates using socio-ecological data

2016 ◽  
Author(s):  
Michael Marshall ◽  
Michael Norton-Griffiths ◽  
Harvey Herr ◽  
Richard Lamprey ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Natural Vegetation ◽  
Additive Models ◽  
Sub Saharan Africa ◽  
Land Cover Types ◽  
Remote Sensing Classification ◽  
Functional Relationships ◽  
Macro Scale

Abstract. A growing body of research shows the importance of land use/cover change (LULCC) on modifying the earth system. Land surface models are used to stimulate land-atmosphere dynamics at the macro- (regional to global) scale, but bias and uncertainty remain that need to be addressed, before the importance of LULCC is fully realized. In this study, we propose a method of improving LULCC estimates for land surface modelling exercises. The method yields continuous (annual) long-term (30-year) estimates of LULCC driven by socio-ecological geospatial predictors available seamlessly across sub-Saharan Africa that can be used for both retrospective and prospective analyses. The method was developed with 2252 5 × 5 km2 sample frames of the proportion of several land cover types in Kenya over multiple years. Forty-three socio-ecological predictors were evaluated for model development. Machine learning was used for data reduction and simple (functional) relationships defined by generalized additive models were constructed on a subset of the highest ranked predictors (p ≤ 10) to estimate LULCC. The predictors explained 62 % and 65 % of the variance in the proportion of agriculture and natural vegetation, respectively, but were less successful at estimating more descriptive land cover types. In each case, population density on an annual basis was the highest ranked predictor. The approach was compared to a commonly used remote sensing classification procedure, given the wide use of such techniques for macro-scale LULCC detection, and out-performed it for each land cover type. The approach was used to demonstrate significant trends in expanding (declining) agricultural (natural vegetation) land cover in Kenya from 1983–2012, with the largest increases (declines) occurring in densely populated high agricultural production zones.

scholarly journals Analysis of a Warm-Season Surface-Influenced Mesoscale Convective Boundary in Northwest Mississippi

2011 ◽  
Vol 12 (5) ◽  
pp. 1007-1023 ◽  
Author(s):  
Jamie Dyer
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Rapid Change ◽  
Convective Precipitation ◽  
Alluvial Valley ◽  
Convective Boundary ◽  
Mesoscale Convective ◽  
Lower Mississippi River

Abstract The lower Mississippi River alluvial valley in southeastern Arkansas, northeastern Louisiana, and northwestern Mississippi is characterized by widespread agriculture with few urban areas. Land use is predominantly cultivated cropland with minimal topographic variation; the eastern edge of the alluvial valley is defined by a rapid, although small, change in elevation into a heavily forested landscape, however. This change in land use/land cover has been shown to potentially enhance precipitation through generation of a weak mesoscale convective boundary. This project defines the influence of the land surface on associated precipitation processes by simulating a convective rainfall event that was influenced by regional surface features. Analysis was conducted using a high-resolution simulated dataset generated by the Weather Research and Forecasting Model (WRF). Results show that the strongest uplift coincides with an abrupt low-level thermal boundary, developed primarily by a rapid change from sensible to latent heat flux relative to the agricultural and forested areas, respectively. In addition, surface heating over the cultivated landscape appears to destabilize the boundary layer, with precipitation occurring as air is advected across the land cover boundary and the associated thermal gradient. This information can be used to define and predict surface-influenced convective precipitation along agricultural boundaries in other regions where the synoptic environment is weak.

Assess the impacts of different land cover datasets on land surface hydrological process in Community Earth System Model (CESM)

2020 ◽  
Author(s):  
Shaoqiang Ni ◽  
Hui Lu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Substantial Effect ◽  
Land Cover Changes ◽  
System Modelling ◽  
Hydrological Process ◽  
Earth System ◽  
Earth System Modelling

<p>By changing matter and energy exchange, biogeochemical process and geophysical process, land use and land cover changes have crucial effects on the earth system modelling. Previous studies have focused on reconstructing the land use and land cover change to be a continuous changing process over time considering human and natural factors. The real land cover change processes have rarely been taken into consideration in the simulation of earth system. Using Gong global land cover mapping products (1985-2015) and the Lawrence land cover dataset (default) in CESM, this study have quantitatively compared the differences in plant function types (PFT) between two products. The results show the land cover changes in default dataset are slowly changing processes with little variation from year to year. In contrast, the Gong global mapping products express a noticeable drastic change tendency between adjacent years. Driving the model with different land cover datasets, our results indicates that globally land evapotranspiration (ET) is dramatically impacted by the land cover changes, especially in areas with distinct tree changes. Also the land cover change can cause a certain proportion variation in soil water (-50%-65%) and runoff (-60%-60%, even >90% in some special grid points) in a global scale. This study estimates the substantial effect land use and land cover changes can have on the land surface hydrological process in earth system modelling.</p>

scholarly journals Continuous and consistent land use/cover change estimates using socio-ecological data

2017 ◽  
Vol 8 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Michael Marshall ◽  
Michael Norton-Griffiths ◽  
Harvey Herr ◽  
Richard Lamprey ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Natural Vegetation ◽  
Additive Models ◽  
Sub Saharan Africa ◽  
Ecological Data ◽  
Land Cover Types ◽  
Remote Sensing Classification ◽  
Functional Relationships

Abstract. A growing body of research shows the importance of land use/cover change (LULCC) on modifying the Earth system. Land surface models are used to stimulate land–atmosphere dynamics at the macroscale, but model bias and uncertainty remain that need to be addressed before the importance of LULCC is fully realized. In this study, we propose a method of improving LULCC estimates for land surface modeling exercises. The method is driven by projectable socio-ecological geospatial predictors available seamlessly across sub-Saharan Africa and yielded continuous (annual) estimates of LULCC at 5 km  ×  5 km spatial resolution. The method was developed with 2252 sample area frames of 5 km  ×  5 km consisting of the proportion of several land cover types in Kenya over multiple years. Forty-three socio-ecological predictors were evaluated for model development. Machine learning was used for data reduction, and simple (functional) relationships defined by generalized additive models were constructed on a subset of the highest-ranked predictors (p ≤ 10) to estimate LULCC. The predictors explained 62 and 65 % of the variance in the proportion of agriculture and natural vegetation, respectively, but were less successful at estimating more descriptive land cover types. In each case, population density on an annual basis was the highest-ranked predictor. The approach was compared to a commonly used remote sensing classification procedure, given the wide use of such techniques for macroscale LULCC detection, and outperformed it for each land cover type. The approach was used to demonstrate significant trends in expanding (declining) agricultural (natural vegetation) land cover in Kenya from 1983 to 2012, with the largest increases (declines) occurring in densely populated high agricultural production zones. Future work should address the improvement (development) of existing (new) geospatial predictors and issues of model scalability and transferability.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh

2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Surface Temperatures ◽  
Land Surface Temperatures
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