scholarly journals Combined impacts of land cover changes and large‐scale forcing on Southern California summer daily maximum temperatures

2015 ◽  
Vol 120 (18) ◽  
pp. 9208-9219 ◽  
Author(s):  
Pedro Sequera ◽  
Jorge E. González ◽  
Kyle McDonald ◽  
Robert Bornstein ◽  
Daniel Comarazamy
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Southern California ◽  
Daily Maximum ◽  
Land Cover Changes ◽  
Maximum Temperatures

Unmixing the regional climate response to recent historical land cover changes in Europe

2020 ◽  
Author(s):  
Bo Huang ◽  
Xiangping Hu ◽  
Geir-Arne Fuglstad ◽  
Xu Zhou ◽  
Wenwu Zhao ◽  
...  
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Agricultural Land ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Energy Budget ◽  
Land Cover Changes ◽  
Climate Response ◽  
Statistical Regression ◽  
Cooling Effects

<p>Land cover changes (LCCs) influence the regional climate because they alter biophysical mechanisms like evapotranspiration, albedo, and surface roughness. Previous research mainly assessed the regional climate implications of individual land cover transitions, such as the effects of historical forest clearance or idealized large-scale scenarios of deforestation/afforestation, but the combined effects from the mix of recent historical land cover changes in Europe have not been explored. In this study, we use a combination of high resolution land cover data with a regional climate model (the Weather Research and Forecasting model, WRF, v3.9.1) to quantify the effects on surface temperature of land cover changes between 1992 and 2015. Unlike many previous studies that had to use one unrealistic large-scale simulation for each LCC to single out its climate effects, our analysis simultaneously considers the effects of the mix of historical land cover changes in Europe and introduces a new method to disentangle the individual contributions. This approach, based on a ridge statistical regression, does not require an explicit consideration of the different components of the surface energy budget, and directly shows the temperature changes from each land transition.</p><p>            From 1992 to 2015, around 70 Mha of land transitions occurred in Europe. Approximately 25 Mha of agricultural land was left abandoned, which was only partially compensated by cropland expansion (about 20 Mha). Declines in agricultural land mostly occurred in favor of forests (15 Mha) and urban settlements (8 Mha). Relative to 1992, we find that the land covers of 2015 are associated with an average temperature cooling of -0.12±0.20 °C, with seasonal and spatial variations. At a continental level, the mean cooling is mainly driven by agriculture abandonment (cropland-to-forest transitions). Idealized simulations where cropland transitions to other land classes are excluded result in a mean warming of +0.10±0.19 °C, especially during summer. Conversions to urban land always resulted in warming effects, whereas the local temperature response to forest gains and losses shows opposite signs from the western and central part of the domain (where forests have cooling effects) to the eastern part (where forests are associated to warming). Gradients in soil moisture and local climate conditions are the main drivers of these differences. Our findings are a first attempt to quantify the regional climate response to historical LCC in Europe, and our method allows to unmix the temperature signal of a grid cell to the underlying LCCs (i.e., temperature impact per land transition). Further developing biophysical implications from LCCs for their ultimate consideration in land use planning can improve synergies for climate change adaptation and mitigation.</p><p> </p>

scholarly journals Understanding the mechanism of land-cover related climate change in the low latitudes

MAUSAM ◽  
2021 ◽  
Vol 59 (3) ◽  
pp. 297-312
Author(s):  
HEIKO PAETH
Keyword(s):  
Land Cover ◽  
West Africa ◽  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
Rainfall Amount ◽  
Congo Basin ◽  
Convective Precipitation ◽  
Land Cover Changes ◽  
Low Latitudes

Rainfall variability in the low latitudes in general and over tropical and sub-tropical Africa in particular, is largely affected by land surface characteristics like, vegetation cover, albedo and soil moisture. Understanding the local and dynamical effects of land-cover changes is crucial to future climate prediction, given ongoing population growth and increasing agricultural needs in Africa. Here, a set of sensitivity studies with a synoptic-scale regional climate model is presented, prescribing idealized scenarios of reduced vegetation cover over Africa. Beside the vegetation ratio itself, the leaf area index, forest ratio, surface albedo and roughness length are changed as well, in order to obtain a consistent scenario of land surface degradation. In addition, a second set of experiments is realized with altered soil parameters as expected to be coming alongwith a reduction in vegetation cover.   Seasonal rainfall amount decreases substantially when the present-day vegetation continuously disappears. The strongest changes are found over the Congo Basin and subsaharan West Africa, where the summer monsoon precipitation diminishes by up to 2000 mm and 600 mm, respectively. The rainfall response to vegetation changes is non-linear and statistically significant over large parts of subsaharan Africa. Convective precipitation is more sensitive than large-scale precipitation.   The most prominent effect of land degradation is a decrease (increase) of latent (sensible) heat fluxes. As a consequence, the large-scale thermal gradients, as a key factor in the monsoonal flow over Africa, are modified leading to a southward shift of the intertropical convergence zone and enhanced moisture advection over the southernmost part of West Africa and the central Congo Basin. The mid-tropospheric jet and wave dynamics are barely affected by land-cover changes. Although the large-scale dynamical response is favourable to increasing rainfall amount, the moisture budget is predominantly governed by reduced evapotranspiration, overcompensating the positive dynamical effect and inducing a weakening of the regional-scale water recycling. The related changes in the soil properties may additionally contribute to a reduction in rainfall amount, albeit of lower amplitude.

Impact of Abrupt Land Cover Changes by Tropical Deforestation on Southeast Asian Climate and Agriculture

2017 ◽  
Vol 30 (7) ◽  
pp. 2587-2600 ◽  
Author(s):  
Merja H. Tölle ◽  
Steven Engler ◽  
Hans-Jürgen Panitz
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Layer Structure ◽  
Surface Fluxes ◽  
Maximum Temperature ◽  
Natural Mode ◽  
Land Cover Changes ◽  
Strong Impact ◽  
Se Asia ◽  
The Impact

Southeast Asia (SE Asia) undergoes major and rapid land cover changes as a result of agricultural expansion. Landscape conversion results in alterations to surface fluxes of moisture, heat, and momentum and sequentially impact the boundary layer structure, cloud-cover regime, and all other aspects of local and regional weather and climate occurring also in regimes remote from the original landscape disturbance. The extent and magnitude of the anthropogenic modification effect is still uncertain. This study investigates the biogeophysical effects of large-scale deforestation on monsoon regions using an idealized deforestation simulation. The simulations are performed using the regional climate model COSMO-CLM forced with ERA-Interim data during the period 1984–2004. In the deforestation experiment, grasses in SE Asia, between 20°S and 20°N, replace areas covered by trees. Using principal component analysis, it is found that abrupt conversion from forest to grassland cover leads to major climate variability in the year of disturbance, which is 1990, over SE Asia. The persistent land modification leads to a decline in evapotranspiration and precipitation and a significant warming due to reduced latent heat flux during 1990–2004. The strongest effects are seen in the lowlands of SE Asia. Daily precipitation extremes increase during the monsoon period and ENSO, differing from the result of mean precipitation changes. Maximum temperature also increases by 2°C. The impacts of land cover change are more intense than the effects of El Niño and La Niña. In addition, results show that these land clearings can amplify the impact of the natural mode ENSO, which has a strong impact on climate conditions in SE Asia. This will likely have consequences for the agricultural output.

scholarly journals V2Karst V1.1: a parsimonious large-scale integrated vegetation–recharge model to simulate the impact of climate and land cover change in karst regions

2018 ◽  
Vol 11 (12) ◽  
pp. 4933-4964 ◽  
Author(s):  
Fanny Sarrazin ◽  
Andreas Hartmann ◽  
Francesca Pianosi ◽  
Rafael Rosolem ◽  
Thorsten Wagener
Keyword(s):  
Land Cover ◽  
Groundwater Recharge ◽  
Large Scale ◽  
Temporal Distribution ◽  
Land Cover Changes ◽  
Depth Analysis ◽  
Karst Areas ◽  
Large Scale Land ◽  
Evapotranspiration Estimation ◽  
The Impact

Abstract. Karst aquifers are an important source of drinking water in many regions of the world. Karst areas are highly permeable and produce large amounts of groundwater recharge, while surface runoff is often negligible. As a result, recharge in these systems may have a different sensitivity to climate and land cover changes than in other less permeable systems. However, little is known about the combined impact of climate and land cover changes in karst areas at large scales. In particular, the representation of land cover, and its controls on evapotranspiration, has been very limited in previous karst hydrological models. In this study, we address this gap (1) by introducing the first large-scale hydrological model including an explicit representation of both karst and land cover properties, and (2) by providing an in-depth analysis of the model's recharge production behaviour. To achieve these aims, we replace the empirical approach to evapotranspiration estimation of a previous large-scale karst recharge model (VarKarst) with an explicit, mechanistic and parsimonious approach in the new model (V2Karst V1.1). We demonstrate the plausibility of V2Karst simulations at four carbonate rock FLUXNET sites by assessing the model's ability to reproduce observed evapotranspiration and soil moisture patterns and by showing that the controlling modelled processes are in line with expectations. Additional virtual experiments with synthetic input data systematically explore the sensitivities of recharge to precipitation characteristics (overall amount and temporal distribution) and land cover properties. This approach confirms that these sensitivities agree with expectations and provides first insights into the potential impacts of future change. V2Karst is the first model that enables the study of the joint impacts of large-scale land cover and climate changes on groundwater recharge in karst regions.

scholarly journals Global climate forcing driven by altered BVOC fluxes from 1990–2010 land cover change in maritime Southeast Asia

2018 ◽  
Author(s):  
Kandice L. Harper ◽  
Nadine Unger
Keyword(s):  
Land Cover ◽  
Southeast Asia ◽  
Land Cover Change ◽  
Radiative Forcing ◽  
Large Scale ◽  
Lower Troposphere ◽  
Convective Transport ◽  
Atmospheric Composition ◽  
Land Cover Changes ◽  
Upper Troposphere

Abstract. Over the period 1990–2010, maritime Southeast Asia experienced large-scale land cover changes, including expansion of high-isoprene-emitting oil palm plantations and contraction of low-isoprene-emitting natural forests. The ModelE2-Yale Interactive Terrestrial Biosphere global chemistry–climate model is used to quantify the atmospheric composition changes and, for the first time, the associated radiative forcing induced by the land-cover-change-driven biogenic volatile organic compound (BVOC) emission changes (+6.5 TgC y−1 isoprene, −0.5 TgC y−1 monoterpenes). Regionally, surface-level ozone concentrations largely decreased (−3.8 to +0.8 ppbv). The tropical land cover changes occurred in a region of strong convective transport, providing a mechanism for the BVOC perturbations to affect the composition of the upper troposphere. Enhanced concentrations of isoprene and its degradation products are simulated in the upper troposphere, and, on a global-mean basis, land cover change had a stronger impact on ozone in the upper troposphere (+0.6 ppbv) than in the lower troposphere (

Spatio-temporal comparison of different approaches to derive land use and land cover change emissions by models

2021 ◽  
Author(s):  
Wolfgang Obermeier ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Agricultural Land ◽  
Land Cover Changes ◽  
Legacy Effects ◽  
Equatorial Africa ◽  
The Usa ◽  
Spatio Temporal ◽  
Global Carbon

<p>The quantification of the net carbon flux from land use and land cover changes (f<sub>LULCC</sub>) is essential to understand the global carbon cycle, and consequently, to support climate change mitigation. However, large-scale f<sub>LULCC</sub> is not directly measurable, and can only be inferred by models, such as semi-empirical bookkeeping models, and process-based dynamic global vegetation models (DGVMs). By definition, f<sub>LULCC</sub> estimates between these two model types are not directly comparable. For example, transient DGVM-based f<sub>LULCC</sub> of the annual global carbon budget includes the so-called Loss of Additional Sink Capacity (LASC). The latter accounts for environmental impacts on the land carbon storage capacities of managed land compared to potential vegetation which is not included in bookkeeping models. Additionally, estimates of transient DGVM-based f<sub>LULCC</sub> differ from bookkeeping model estimates, since they depend on arbitrarily chosen simulation time periods and the timing of land use and land cover changes within the historic period (which includes different accumulation periods for legacy effects). However, DGVMs enable a f<sub>LULCC</sub> approximation independent of the timing of land use and land cover changes and their legacy effects by simulations run under constant pre-industrial or present-day environmental forcings.</p><p>In this study, we analyze these different DGVM-derived f<sub>LULCC</sub> definitions, under transiently changing environmental conditions and fixed pre-industrial and fixed present-day conditions, within 18 regions for twelve DGVMs and quantify their differences as well as climate- and CO<sub>2</sub>-induced components. The multi model mean under transient conditions reveals a global f<sub>LULCC</sub> of 2.0±0.6 PgC yr<sup>-1</sup> for 2009-2018, with ~40% stemming from the LASC (0.8±0.3 PgC yr<sup>-1</sup>). Within the industrial period (1850 onward), cumulative f<sub>LULCC</sub> reached 189±56 PgC with 40±15 PgC from the LASC.</p><p>Regional hotspots of high LASC values exist in the USA, China, Brazil, Equatorial Africa and Southeast Asia, which we mainly relate to deforestation for cropland. Distinct negative LASC estimates were observed in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land). Negative LASC estimates indicate that fLULCC estimates in these regions are lower in transient DGVM simulations compared to bookkeeping-approaches. By unraveling the spatio-temporal variability of the different DGVM-derived f<sub>LULCC</sub> estimates, our study calls for a harmonized attribution of model-derived f<sub>LULCC</sub>. We propose an approach that bridges bookkeeping and DGVM approaches for f<sub>LULCC</sub> estimation by adopting a mean DGVM-ensemble LASC for a defined reference period.</p>

Observation-constrained Radiative Forcing from historical land-cover changes in CMIP5 models

2020 ◽  
Author(s):  
Quentin Lejeune ◽  
Edouard Davin ◽  
Grégory Duveiller ◽  
Bas Crezee ◽  
Ronny Meier ◽  
...  
Keyword(s):  
Land Cover ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Mean Value ◽  
Cmip5 Models ◽  
Land Cover Changes ◽  
Conversion Rates ◽  
The One ◽  
Derived Data

<p>The albedo of trees is lower than the one of crops and grasses, especially in the presence of snow. It is therefore understood that the replacement of forests by croplands and grasslands used for agricultural purposes that has occurred since pre-industrial times led to large-scale albedo increases. This is reflected by the estimate of the Radiative Forcing (RF) from historical Land-Cover Changes (LCC) of the Fifth Assessment Report (AR5) of the IPCC, which amounts to -0.15 +/- 0.10 W/m<sup>2</sup>. However, this expert judgment was intended to both account for a few studies using single climate models which put forward values close to 0.2W/m<sup>2</sup>, and the finding that climate models usually overestimate the albedo difference between natural vegetation and croplands in comparison to satellite-derived observational evidence. Further uncertainties around this number have also been suggested by studies revealing a substantial model spread in the albedo response to historical LCC. This points at the need to revisit the IPCC AR5 conclusions in light of recent model intercomparison efforts and observational data.</p><p>In this study, we reconstructed the local albedo changes induced by conversions between trees and crops/grasses since 1860 for 15 CMIP5 models. We evaluated the employed methodology using factorial experiments isolating the historical LCC forcing in four models for which the required simulations are available, and obtained very similar results. Using an empirical parameterisation of the radiative kernel, we then derived estimates of the associated RF ranging between 0 and -0.22 W/m<sup>2</sup>, with a multi-model mean value of -0.07 W/m<sup>2</sup>.</p><p>Furthermore, we constrained the RF estimates with observations by replacing the albedo response to the transition between trees and crops/grasses from the models by that provided by satellite-derived data. This led to an unexpected increase in the range between the models, due to two models having unrealistic conversion rates from trees to crops/grasses. Excluding these two models, we obtain a revised multi-model mean estimate of -0.11 W/m<sup>2</sup> (with individual model results between -0.04 and -0.16 W/m<sup>2</sup>). We were also able to link the differences between the unconstrained and constrained RF estimates to some of the model biases in the albedo sensitivity to deforestation.</p><p>Since the conversions between trees and crops/grasses are responsible for almost the totality of historical albedo changes in CMIP5 models, our findings are comparable to previous estimates of the RF from all LCC. They point at values that are at the lower end of the range provided by the IPCC AR5. The approach described in this study can be applied on other model simulations, such as those from CMIP6.</p>

scholarly journals Thermal Anomalies Detect Critical Global Land Surface Changes

2018 ◽  
Vol 57 (2) ◽  
pp. 391-411 ◽  
Author(s):  
D. J. Mildrexler ◽  
M. Zhao ◽  
W. B. Cohen ◽  
S. W. Running ◽  
X. P. Song ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Large Scale ◽  
Heat Waves ◽  
Land Cover Changes ◽  
Land Area ◽  
Thermal Anomalies ◽  
Extreme Climatic Events ◽  
Global Land ◽  
Surface Changes

AbstractMeasurements that link surface conditions and climate can provide critical information on important biospheric changes occurring in the Earth system. As the direct driving force of energy and water fluxes at the surface–atmosphere interface, land surface temperature (LST) provides information on physical processes of land-cover change and energy-balance changes that air temperature cannot provide. Annual maximum LST (LSTmax) is especially powerful at minimizing synoptic and seasonal variability and highlighting changes associated with extreme climatic events and significant land-cover changes. The authors investigate whether maximum thermal anomalies from satellite observations could detect heat waves and droughts, a melting cryosphere, and disturbances in the tropical forest from 2003 to 2014. The 1-km2 LSTmax anomalies peaked in 2010 when 20% of the global land area experienced anomalies of greater than 1 standard deviation and over 4% of the global land area was subject to positive anomalies exceeding 2 standard deviations. Positive LSTmax anomalies display complex spatial patterns associated with heat waves and droughts across the global land area. The findings presented herein show that entire biomes are experiencing shifts in their LSTmax distributions driven by extreme climatic events and large-scale land surface changes, such as melting of ice sheets, severe droughts, and the incremental effects of forest loss in tropical forests. As climate warming and land-cover changes continue, it is likely that Earth’s maximum surface temperatures will experience greater and more frequent directional shifts, increasing the possibility that critical thresholds in Earth’s ecosystems and climate system will be surpassed, resulting in profound and irreversible changes.

scholarly journals A Non-Stationary Heat Spell Frequency, Intensity, and Duration Model for France, Integrating Teleconnection Patterns and Climate Change

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1387
Author(s):  
Yasser Hamdi ◽  
Christian Charron ◽  
Taha B. M. J. Ouarda
Keyword(s):  
Large Scale ◽  
Value Theory ◽  
Climate Indices ◽  
Daily Maximum ◽  
Teleconnection Patterns ◽  
Duration Magnitude ◽  
Change Context ◽  
Maximum Temperatures

The warming observed over the past summers since 2000 is unprecedented in climate records in Europe and especially in France. Extreme temperatures and heat spells were often analyzed in the literature by applying extreme value theory but rarely in a non-stationary (NS) framework and duration modeling is often excluded. For a modern risk-based approach, it is important to have knowledge of the duration, magnitude, and frequency of occurrence of heat spells in a climate variability and change context. Yet, despite their obvious importance, teleconnections and associated climate indices (CIs) have often been excluded from heat spell modelling. The notion of duration is also not easily interpretable in a frequency analysis and can even be subtle, especially in a NS context. In this study, we used time-varying statistical distributions with parameters conditional on covariates representing the time and CIs. The daily maximum temperatures (DMTs) observed at the Orange and Dijon stations in France were used as a case study. This paper highlights a possible relationship between some large-scale climate patterns and the heat spells in France. Overall, the results suggest that considering the combined effect of global warming and these patterns in NS models is useful for a more appropriate characterization of the hazard heat spells in France.

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