scholarly journals Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)

2021 ◽  
Vol 14 (6) ◽  
pp. 3215-3249
Author(s):  
Timothy Glotfelty ◽  
Diana Ramírez-Mejía ◽  
Jared Bowden ◽  
Adrian Ghilardi ◽  
J. Jason West
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Sub Saharan Africa ◽  
Land Surface Models ◽  
Surface Parameters ◽  
Temperature And Precipitation ◽  
Surface Models ◽  
Sub Saharan ◽  
Land Surface Parameters

Abstract. Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and Community Land Model (CLM) LSMs in the Weather Research and Forecasting (WRF) model over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna land use and land cover (LULC) category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate responses. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near-surface temperature and precipitation. However, in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation changes. Differences in thermal changes between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.

scholarly journals Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)

2020 ◽  
Author(s):  
Timothy Glotfelty ◽  
Diana Ramírez-Mejía ◽  
Jared Bowden ◽  
Adrián Ghilardi ◽  
J. Jason West
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Sub Saharan Africa ◽  
Land Surface Models ◽  
Surface Parameters ◽  
Temperature And Precipitation ◽  
Surface Models ◽  
Climate Signals ◽  
Sub Saharan ◽  
Land Surface Parameters

Abstract. Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and CLM LSMs in the Weather Research and Forecasting Model (WRF) over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna LULC category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate signals. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near surface temperature and precipitation. However in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation climate signals. Differences in thermal climate signals between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions, and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.

A Simple Reclassification Method for Correcting Uncertainty in Land Use/Land Cover Data Sets Used with Land Surface Models

2007 ◽  
Vol 164 (8-9) ◽  
pp. 1789-1809 ◽  
Author(s):  
Joseph G. Alfieri ◽  
Dev Niyogi ◽  
Margaret A. LeMone ◽  
Fei Chen ◽  
Souleymane Fall
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Land Surface Models ◽  
Land Cover Data ◽  
Surface Models

scholarly journals Inferring past land-use induced changes in surface albedo from satellite observations: a useful tool to evaluate model simulations

2012 ◽  
Vol 9 (9) ◽  
pp. 12505-12542
Author(s):  
J. P. Boisier ◽  
N. de Noblet-Ducoudré ◽  
P. Ciais
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Type ◽  
Satellite Observations ◽  
Land Surface Models ◽  
Historical Changes ◽  
Surface Models ◽  
Past Land Use

Abstract. Cooling resulting from increases in surface albedo has been identified in several studies as the main biogeophysical effect of past land-use induced land cover changes (LCC) on climate. However, the amplitude of this effect remains quite uncertain due to, among other factors, (a) uncertainties in the magnitude of historical LCC and, (b) differences in the way various models simulate surface albedo and more specifically its dependency on vegetation type and snow cover. We have derived monthly albedo climatologies for croplands and four other land-cover types from MODIS satellite observations. We have then estimated the changes in surface albedo since preindustrial times by combining these climatologies with the land-cover maps of 1870 and 1992 used by modelers in the context of the LUCID intercomparison project. These reconstructions show surface albedo increases larger than 10% (absolute) in winter and 2% in summer between 1870 and 1992 over areas that have experienced intense deforestation in the northern temperate regions. The MODIS-based reconstructions of historical changes in surface albedo were then compared to those simulated by the various models participating to LUCID. The inter-model mean albedo response to LCC shows a similar spatial and seasonal pattern to the one resulting from the reconstructions, that is larger increases in winter than in summer driven by the presence of snow. However, individual models show significant differences with the satellite-based reconstructions, despite the fact that land-cover change maps are the same. Our analyses suggest that the primary reason for those discrepancies is how land-surface models parameterize albedo. Another reason, of secondary importance, results from differences in the simulated snowpack. Our methodology is a useful tool not only to infer observations-based historical changes in land surface variables impacted by LCC, but also to point to major deficiencies within the models; we therefore suggest that it could be more widely developed and used in conjunction with other tools in order to evaluate global land-surface models.

scholarly journals Key Challenges for Land Use Planning and Its Environmental Assessments in the Abuja City-Region, Nigeria

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 443
Author(s):  
Evidence Chinedu Enoguanbhor ◽  
Florian Gollnow ◽  
Blake Byron Walker ◽  
Jonas Ostergaard Nielsen ◽  
Tobia Lakes
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Assessment ◽  
Land Use Planning ◽  
Environmental Sustainability ◽  
Sub Saharan Africa ◽  
Environmental Assessments ◽  
City Regions ◽  
Sub Saharan ◽  
Land Cover Maps

Land use planning as strategic instruments to guide urban dynamics faces particular challenges in the Global South, including Sub-Saharan Africa, where urgent interventions are required to improve urban and environmental sustainability. This study investigated and identified key challenges of land use planning and its environmental assessments to improve the urban and environmental sustainability of city-regions. In doing so, we combined expert interviews and questionnaires with spatial analyses of urban and regional land use plans, as well as current and future urban land cover maps derived from Geographic Information Systems and remote sensing. By overlaying and contrasting land use plans and land cover maps, we investigated spatial inconsistencies between urban and regional plans and the associated urban land dynamics and used expert surveys to identify the causes of such inconsistencies. We furthermore identified and interrogated key challenges facing land use planning, including its environmental assessment procedures, and explored means for overcoming these barriers to rapid, yet environmentally sound urban growth. The results illuminated multiple inconsistencies (e.g., spatial conflicts) between urban and regional plans, most prominently stemming from conflicts in administrative boundaries and a lack of interdepartmental coordination. Key findings identified a lack of Strategic Environmental Assessment and inadequate implementation of land use plans caused by e.g., insufficient funding, lack of political will, political interference, corruption as challenges facing land use planning strategies for urban and environmental sustainability. The baseline information provided in this study is crucial to improve strategic planning and urban/environmental sustainability of city-regions in Sub-Saharan Africa and across the Global South, where land use planning faces similar challenges to address haphazard urban expansion patterns.

scholarly journals Evaluating and improving the Community Land Model's sensitivity to land cover

2018 ◽  
Vol 15 (15) ◽  
pp. 4731-4757 ◽  
Author(s):  
Ronny Meier ◽  
Edouard L. Davin ◽  
Quentin Lejeune ◽  
Mathias Hauser ◽  
Yan Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Surface ◽  
Soil Column ◽  
Plant Functional Type ◽  
Model Parameters ◽  
Functional Type ◽  
Land Surface Models ◽  
Surface Models ◽  
Open Land

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

scholarly journals Inter-comparison of two land-surface models applied at different scales and their feedbacks while coupled with a regional climate model

2012 ◽  
Vol 16 (3) ◽  
pp. 1017-1031 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser ◽  
T. Marke ◽  
A. Pfeiffer ◽  
G. Zängl ◽  
...  
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Regional Climate ◽  
Moderate Increase ◽  
Net Radiation ◽  
Land Surface Models ◽  
Near Surface ◽  
Temporal Behaviour ◽  
Surface Models ◽  
The Alps

Abstract. Downstream models are often used in order to study regional impacts of climate and climate change on the land surface. For this purpose, they are usually driven offline (i.e., 1-way) with results from regional climate models (RCMs). However, the offline approach does not allow for feedbacks between these models. Thereby, the land surface of the downstream model is usually completely different to the land surface which is used within the RCM. Thus, this study aims at investigating the inconsistencies that arise when driving a downstream model offline instead of interactively coupled with the RCM, due to different feedbacks from the use of different land surface models (LSM). Therefore, two physically based LSMs which developed from different disciplinary backgrounds are compared in our study: while the NOAH-LSM was developed for the use within RCMs, PROMET was originally developed to answer hydrological questions on the local to regional scale. Thereby, the models use different physical formulations on different spatial scales and different parameterizations of the same land surface processes that lead to inconsistencies when driving PROMET offline with RCM output. Processes that contribute to these inconsistencies are, as described in this study, net radiation due to land use related albedo and emissivity differences, the redistribution of this net radiation over sensible and latent heat, for example, due to different assumptions about land use impermeability or soil hydraulic reasons caused by different plant and soil parameterizations. As a result, simulated evapotranspiration, e.g., shows considerable differences of max. 280 mm yr−1. For a full interactive coupling (i.e., 2-way) between PROMET and the atmospheric part of the RCM, PROMET returns the land surface energy fluxes to the RCM and, thus, provides the lower boundary conditions for the RCM subsequently. Accordingly, the RCM responses to the replacement of the LSM with overall increased annual mean near surface air temperature (+1 K) and less annual precipitation (−56 mm) with different spatial and temporal behaviour. Finally, feedbacks can set up positive and negative effects on simulated evapotranspiration, resulting in a decrease of evapotranspiration South of the Alps a moderate increase North of the Alps. The inconsistencies are quantified and account for up to 30% from July to Semptember when focused to an area around Milan, Italy.

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.

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