scholarly journals Global biosphere–climate interaction: a causal appraisal of observations and models over multiple temporal scales

2019 ◽  
Vol 16 (24) ◽  
pp. 4851-4874 ◽  
Author(s):  
Jeroen Claessen ◽  
Annalisa Molini ◽  
Brecht Martens ◽  
Matteo Detto ◽  
Matthias Demuzere ◽  
...  
Keyword(s):  
Air Temperature ◽  
Arid Regions ◽  
Climate Impacts ◽  
Cmip5 Models ◽  
Climate Control ◽  
Temporal Scales ◽  
Local Climate ◽  
Northern Latitudes ◽  
The Impact ◽  
Semi Arid

Abstract. Improving the skill of Earth system models (ESMs) in representing climate–vegetation interactions is crucial to enhance our predictions of future climate and ecosystem functioning. Therefore, ESMs need to correctly simulate the impact of climate on vegetation, but likewise feedbacks of vegetation on climate must be adequately represented. However, model predictions at large spatial scales remain subjected to large uncertainties, mostly due to the lack of observational patterns to benchmark them. Here, the bidirectional nature of climate–vegetation interactions is explored across multiple temporal scales by adopting a spectral Granger causality framework that allows identification of potentially co-dependent variables. Results based on global and multi-decadal records of remotely sensed leaf area index (LAI) and observed atmospheric data show that the climate control on vegetation variability increases with longer temporal scales, being higher at inter-annual than multi-month scales. Globally, precipitation is the most dominant driver of vegetation at monthly scales, particularly in (semi-)arid regions. The seasonal LAI variability in energy-driven latitudes is mainly controlled by radiation, while air temperature controls vegetation growth and decay in high northern latitudes at inter-annual scales. These observational results are used as a benchmark to evaluate four ESM simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Findings indicate a tendency of ESMs to over-represent the climate control on LAI dynamics and a particular overestimation of the dominance of precipitation in arid and semi-arid regions at inter-annual scales. Analogously, CMIP5 models overestimate the control of air temperature on seasonal vegetation variability, especially in forested regions. Overall, climate impacts on LAI are found to be stronger than the feedbacks of LAI on climate in both observations and models; in other words, local climate variability leaves a larger imprint on temporal LAI dynamics than vice versa. Note however that while vegetation reacts directly to its local climate conditions, the spatially collocated character of the analysis does not allow for the identification of remote feedbacks, which might result in an underestimation of the biophysical effects of vegetation on climate. Nonetheless, the widespread effect of LAI variability on radiation, as observed over the northern latitudes due to albedo changes, is overestimated by the CMIP5 models. Overall, our experiments emphasise the potential of benchmarking the representation of particular interactions in online ESMs using causal statistics in combination with observational data, as opposed to the more conventional evaluation of the magnitude and dynamics of individual variables.

Climatic drivers and biogeophysical feedbacks: a causal inference approach over multiple temporal scales

2020 ◽  
Author(s):  
Jeroen Claessen ◽  
Annalisa Molini ◽  
Brecht Martens ◽  
Matteo Detto ◽  
Matthias Demuzere ◽  
...  
Keyword(s):  
Coupled Model ◽  
Global Scale ◽  
Cmip5 Models ◽  
Climate Control ◽  
Temporal Scales ◽  
Area Index ◽  
Local Climate ◽  
Northern Latitudes ◽  
Climatic Drivers ◽  
The Impact

<p>Earth system models (ESMs) need to correctly simulate the impact of climate on vegetation, as well as the feedback of vegetation on climate. Improving the skill of ESMs in representing climate—biosphere interactions is crucial to enhance predictions of climate and ecosystem functioning. Correlation and regression techniques are commonly used to study these interactions statistically, but these methods lack the ability to unravel the bidirectional nature of the climate–biosphere system. Here, we explore these interactions across multiple temporal scales by adopting a spectral Granger causality framework that allows identifying potentially inter-dependent variables. Multi-decadal remotely-sensed records are used to analyse the impact of key climatic drivers (precipitation, radiation and temperature) on vegetation (Leaf Area Index, LAI), as well as the biophysical feedback on local climate. These observational results are in turn used to benchmark a set of Coupled Model Intercomparison Project Phase 5 (CMIP5) members at the global scale.</p><p>Results show that the climate control on LAI variability increases with longer temporal scales, being the highest at inter-annual scales. Globally, precipitation is the most dominant driver of vegetation at monthly scales, particularly in (semi-)arid regions, as expected. The seasonal LAI variability in energy-driven latitudes is mainly controlled by radiation, while air temperature controls vegetation growth and decay in northern latitudes at inter-annual scales. ESMs have a tendency to over-represent the climate control on LAI dynamics, and especially the role of precipitation at inter-annual scales. Likewise, the widespread effect of LAI variability on radiation, as observed over the northern latitudes due to albedo changes, is also overestimated by the CMIP5 models. Overall, our experiments emphasise the potential of benchmarking the representation of climate—biosphere interactions in online ESMs using causal statistics in combination with observational data.</p>

scholarly journals Global biosphere–climate interaction: a multi-scale appraisal of observations and models

2019 ◽  
Author(s):  
Jeroen Claessen ◽  
Annalisa Molini ◽  
Brecht Martens ◽  
Matteo Detto ◽  
Matthias Demuzere ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Climate Impacts ◽  
Cmip5 Models ◽  
Wide Spread ◽  
Climate Control ◽  
Temporal Scales ◽  
Area Index ◽  
Local Character ◽  
The Impact ◽  
Semi Arid

Abstract. Improving the skill of Earth System Models (ESMs) in representing climate–vegetation interactions is crucial to enhance our predictions of future climate and ecosystem functioning. Therefore, ESMs need to correctly simulate the impact of climate on vegetation, but likewise, feedbacks of vegetation on climate must be adequately represented. However, model predictions at large spatial scales remain subjected to large uncertainties, mostly due to the lack of observational patterns to benchmark them. Here, the bi-directional nature of climate–vegetation interactions is explored across multiple temporal scales by adopting a spectral Granger causality framework that allows identifying potentially co-dependent variables. Results based on global and multi-decadal records of remotely-sensed leaf area index (LAI) and observed atmospheric data show that the climate control on vegetation variability increases with longer temporal scales, being higher at inter-annual than multi-month scales. The phenological cycle in energy-driven latitudes is mainly controlled by radiation, while in (semi-)arid regimes precipitation variability dominates at all temporal scales. However, at inter-annual scales, the control of water availability gradually becomes more wide-spread than that of energy constraints. The observational results are used as a benchmark to evaluate ESM simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Findings indicate a tendency of ESMs to over-represent the climate control on LAI dynamics, and a particular overestimation of the dominance of precipitation in arid and semi-arid regions. Analogously, CMIP5 models overestimate the control of air temperature on forest seasonal phenology. Overall, climate impacts on LAI are found to be stronger than the feedbacks of LAI on climate in both observations and models, arguably due to the local character of the analysis that does not allow for the identification of downwind or remote vegetation feedbacks. Nonetheless, wide-spread effects of LAI variability on radiation are observed over the northern latitudes, presumably related to albedo changes, which are well-captured by the CMIP5 models. Overall, our experiments emphasise the potential of benchmarking the representation of particular interactions in online ESMs using causal statistics in combination with observational data, as opposed to the more conventional evaluation of the magnitude and dynamics of individual variables.

The impact of urban policy scenarios on local climate: a multi-model intercomparison

2021 ◽  
Author(s):  
Arianna Valmassoi ◽  
Jan D. Keller ◽  
Rita Glowienka-Hense
Keyword(s):  
Urban Areas ◽  
Urban Policy ◽  
Western Europe ◽  
Model Comparison ◽  
Climate Impacts ◽  
Limited Area ◽  
Urban Greening ◽  
Local Climate ◽  
The Impact ◽  
Policy Scenarios

<p>Understanding the impact of urban environments on the local climate has been a crucial topic in recent years. Changes in the cities structure are expected due to the ongoing urbanization trends and climate-aware mitigation planning. These policy implementations are expected to affect the local urban surface and its interaction with the climate system. Here, we are interested in investigating these impacts coupled to a heatwave condition, due to its adverse impact on human health. </p> <p>In the presented work, we investigate the multi-model response to different urbanization and urban greening scenarios. We employ two NWP models at the 2.1 km convection-permitting resolution: ICON-LAM (ICOsahedral Nonhydrostatic Model in Limited Area Mode)  and WRF-ARW (Weather Research and Forecasting Model). Our one-month experiments comprise the 2019 ``record-breaking'' heatwave in Western Europe and they are all a downscaling of ICON-EU (6.5km resolution).</p> <p>The urban policy scenarios are built from the CORINE land use dataset and they include two urbanization and two urban greening settings, for each model. Urbanization is represented as a sprawl of the main urban areas within the domain towards the natural surrounding areas. To increase the urban green fraction within the main cities, we increase the number of green areas within each city.</p> <p>Our analysis shows the multi-model comparison of the effects of the mentioned urban policies on the urban heat island (UHI) under heatwave conditions. Further, we quantify the effects of urban greening as an efficient tool to mitigate expected climate impacts in terms of the Discomfort Index, and not just for the UHI.<br />Further, we evaluate the similarities and dissimilarities between the two models in terms of multiple correlation decomposition accordingly to Glowienka-Hense et al. 2020.</p>

Investigating the possible measure to protect groundwater from polluted streams in Arid and Semi-Arid Regions: the Eastern Nile Delta case study

2021 ◽  
Author(s):  
Ismail Abd-Elaty ◽  
Martina Zelenakova ◽  
Salvatore Straface ◽  
Zuzana Vranayová ◽  
Mohamed Abu-hashim ◽  
...  
Keyword(s):  
Drinking Water ◽  
Arid Regions ◽  
Nile Delta ◽  
Total Dissolved Solids ◽  
Polluted Water ◽  
Deep Aquifer ◽  
Lower Permeability ◽  
The Impact ◽  
Semi Arid

<p>Groundwater is the main source of drinking water in the Nile Delta. Unfortunately, it might be polluted by seepage from polluted streams. This study was carried out to investigate the possible measures  to  protect groundwater  in the Nile delta aquifer using a numerical model (MT3DMS - Mass Transport 3-Dimension Multi-Species). The sources of groundwater contamination were identified and the total dissolved solids (TDS) was taken as an indicator for the contamination. Different strategies were investigated for mitigating the impact of polluted water: i) allocating polluted drains and canals in lower permeability layers; ii)  installing cut-off walls in the polluted drains, and finally, iii) using lining materials in polluted drains and canals. Results indicated these measures effective to mitigate the groundwater pollution. In particular, the cut-off wall was effective for contamination reduction in shallow aquifers, whereas it had no effect in the deep aquifer, while lining materials in polluted drains and canals were able to prevent contamination and to protect the freshwater in the aquifers.  It is worth mentioning that this study was partially supported by a bilateral project between ASRT (Egypt) and CNR (Italy).</p><p> </p><p> </p>

scholarly journals An Assessment of the Accuracy of MODIS Land Surface Temperature over Egypt Using Ground-Based Measurements

2019 ◽  
Vol 11 (20) ◽  
pp. 2369 ◽  
Author(s):  
Ahmed M. El Kenawy ◽  
Mohamed E. Hereher ◽  
Sayed M. Robaa
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Arid Regions ◽  
Surface Albedo ◽  
Hydrological Modeling ◽  
Hot Spot ◽  
Near Surface ◽  
Lower Accuracy ◽  
Semi Arid ◽  
Minimum Air Temperature

Space-based data have provided important advances in understanding climate systems and processes in arid and semi-arid regions, which are hot-spot regions in terms of climate change and variability. This study assessed the performance of land surface temperatures (LSTs), retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua platform, over Egypt. Eight-day composites of daytime and nighttime LST data were aggregated and validated against near-surface seasonal and annual observational maximum and minimum air temperatures using data from 34 meteorological stations spanning the period from July 2002 to June 2015. A variety of accuracy metrics were employed to evaluate the performance of LST, including the bias, normalized root-mean-square error (nRMSE), Yule–Kendall (YK) skewness measure, and Spearman’s rho coefficient. The ability of LST to reproduce the seasonal cycle, anomalies, temporal variability, and the distribution of warm and cold tails of observational temperatures was also evaluated. Overall, the results indicate better performance of the nighttime LSTs compared to the daytime LSTs. Specifically, while nighttime LST tended to underestimate the minimum air temperature during winter, spring, and autumn on the order of −1.3, −1.2, and −1.4 °C, respectively, daytime LST markedly overestimated the maximum air temperature in all seasons, with values mostly above 5 °C. Importantly, the results indicate that the performance of LST over Egypt varies considerably as a function of season, lithology, and land use. LST performs better during transitional seasons (i.e., spring and autumn) compared to solstices (i.e., winter and summer). The varying interactions and feedbacks between the land surface and the atmosphere, especially the differences between sensible and latent heat fluxes, contribute largely to these seasonal variations. Spatially, LST performs better in areas with sandstone formations and quaternary sediments and, conversely, shows lower accuracy in regions with limestone, igneous, and metamorphic rocks. This behavior can be expected in hybrid arid and semi-arid regions like Egypt, where bare rocks contribute to the majority of the Egyptian territory, with a lack of vegetation cover. The low surface albedo of igneous and limestone rocks may explain the remarkable overestimation of daytime temperature in these regions, compared to the bright formations of higher surface albedo (i.e., sandy deserts and quaternary rocks). Overall, recalling the limited coverage of meteorological stations in Egypt, this study demonstrates that LST obtained from the MODIS product can be trustworthily employed as a surrogate for or a supplementary source to near-surface measurements, particularly for minimum air temperature. On the other hand, some bias correction techniques should be applied to daytime LSTs. In general, the fine space-based climatic information provided by MODIS LST can be used for a detailed spatial assessment of climate variability in Egypt, with important applications in several disciplines such as water resource management, hydrological modeling, agricultural management and planning, urban climate, biodiversity, and energy consumption, amongst others. Also, this study can contribute to a better understanding of the applications of remote sensing technology in assessing climatic feedbacks and interactions in arid and semi-arid regions, opening new avenues for developing innovative algorithms and applications specifically addressing issues related to these regions.

scholarly journals Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 639 ◽  
Author(s):  
Bright Freduah ◽  
Dilys MacCarthy ◽  
Myriam Adam ◽  
Mouhamed Ly ◽  
Alex Ruane ◽  
...  
Keyword(s):  
Climate Change ◽  
Arid Regions ◽  
Climate Models ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Climate Scenarios ◽  
Relative Standard ◽  
The Impact ◽  
Semi Arid ◽  
Smallholder Systems

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

scholarly journals A Review of the Impacts of Roads on Wildlife in Semi-Arid Regions

Diversity ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 81 ◽  
Author(s):  
W. Richard J. Dean ◽  
Colleen L. Seymour ◽  
Grant S. Joseph ◽  
Stefan H. Foord
Keyword(s):  
Genetic Diversity ◽  
Arid Regions ◽  
Vocal Communication ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Mitigation Measures ◽  
Obvious Effect ◽  
Long Term Impact ◽  
The Impact ◽  
Semi Arid

Roads now penetrate even the most remote parts of much of the world, but the majority of research on the effects of roads on biota has been in less remote temperate environments. The impacts of roads in semi-arid and arid areas may differ from these results in a number of ways. Here, we review the research on the impacts of roads on biodiversity patterns and ecological and evolutionary processes in semi-arid regions. The most obvious effect of roads is mortality or injury through collision. A diversity of scavengers are killed whilst feeding on roadkill, a source of easily accessed food. Noise pollution from roads and traffic interferes with vocal communication by animals, and birds and frogs living along noisy roads compensate for traffic noise by increasing the amplitude or pitch of their calls. Artificial light along roads impacts certain species’ ability to navigate, as well as attracting invertebrates. Animals are in turn attracted to invertebrates at streetlights, and vulnerable to becoming roadkill themselves. Genetics research across taxa confirms a loss of genetic diversity in small populations isolated by roads, but the long-term impact on the fitness of affected populations through a reduction in genetic diversity is not yet clear. Roads may rapidly cause genetic effects, raising conservation concerns about rare and threatened species. We assess mitigation measures and collate methods to identify the impact of roads on wildlife populations and their associated ecosystems, with a particular focus on recent advances.

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