scholarly journals Terrestrial ecosystems response to future changes in climate and atmospheric CO<sub>2</sub> concentration

2014 ◽  
Vol 11 (15) ◽  
pp. 4157-4171 ◽  
Author(s):  
V. K. Arora ◽  
G. J. Boer
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
High Latitude ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Terrestrial Carbon ◽  
Simulated Precipitation ◽  
Atmospheric Carbon ◽  
Amazonian Region

Abstract. The response of the terrestrial carbon cycle to future changes in climate and atmospheric CO2 is assessed by analysing simulation results for the 2006–2100 period made with the second generation Canadian Earth system model (CanESM2) for the RCP 2.6, RCP 4.5 and RCP 8.5 climate change scenarios. Our interest is in the extent to which global terrestrial carbon pools and sinks, in particular those of the Amazonian region, are vulnerable to the adverse effects of climate change. CanESM2 results indicate that land remains an overall sink of atmospheric carbon for the 2006–2100 period. The net carbon uptake by land in response to changes in climate and atmospheric CO2 is close to 20, 80 and 140 Pg C for the RCP 2.6, 4.5 and 8.5 scenarios, respectively. The latitudinal structure of future atmosphere–land CO2 flux remains similar to that observed for the historical period with northern mid- to high-latitude regions gaining carbon from the atmosphere while the tropics remain either carbon neutral or a modest source of atmospheric carbon depending on scenario. These changes occur in conjunction with simulated precipitation and soil moisture increases over northern mid- and high-latitude land regions and precipitation and soil moisture decreases over the South American continent in all scenarios. Compared to other regions of the globe, which are either carbon sinks or near neutral, the Amazonian region is simulated to be a net source of carbon during the 21st century. Moreover, and unexpectedly, the rate of carbon loss to the atmosphere from the Amazonian region is largely independent of the differences between the three scenarios considered.

scholarly journals Terrestrial ecosystems response to future changes in climate and atmospheric CO<sub>2</sub> concentration

2014 ◽  
Vol 11 (3) ◽  
pp. 3581-3614 ◽  
Author(s):  
V. K. Arora ◽  
G. J. Boer
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
High Latitude ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Terrestrial Carbon ◽  
Simulated Precipitation ◽  
Atmospheric Carbon ◽  
Amazonian Region

Abstract. The response of the terrestrial carbon cycle to future changes in climate and atmospheric CO2 is assessed by analyzing simulations, for the 2006–2100 period, made with the second generation Canadian Earth system model (CanESM2) for the RCP 2.6, RCP 4.5 and RCP 8.5 climate change scenarios. Our interest is in the extent to which global terrestrial carbon pools and sinks, in particular those of the Amazonian region, are vulnerable to the adverse effects of climate change. CanESM2 results indicate that land remains an overall sink of atmospheric carbon for the 2006–2100 period. The net carbon uptake by land in response to changes in climate and atmospheric CO2 is close to 20, 80 and 140 Pg C for the RCP 2.6, 4.5 and 8.5 scenarios, respectively. The latitudinal structure of future atmosphere–land CO2 flux remains similar to that observed for the historical period with northern mid- to high-latitude regions gaining carbon from the atmosphere while the tropics remain either carbon neutral or a modest source of atmospheric carbon depending on scenario. These changes occur in conjunction with simulated precipitation and soil moisture increases over northern mid- and high-latitude land regions and precipitation and soil moisture decreases over the South American continent in all scenarios. Compared to other regions of the globe, which are either carbon sinks or near neutral, the Amazonian region is simulated to be a net source of carbon during the 21st century. Moreover, and unexpectedly, the rate of carbon loss to the atmosphere from the Amazonian region is largely independent of the differences between the three scenarios considered.

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

&lt;p&gt;Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.&amp;#160; Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late). &amp;#160;A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21&lt;sup&gt;st&lt;/sup&gt; century.&lt;/p&gt;

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Vol 11 (4) ◽  
pp. 995-1012
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Retrospective Analysis ◽  
Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Uncertainty Range ◽  
Future Warming ◽  
The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

scholarly journals Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

2012 ◽  
Vol 9 (5) ◽  
pp. 5695-5718 ◽  
Author(s):  
U. Mishra ◽  
W. J. Riley
Keyword(s):  
Climate Change ◽  
Spatial Variability ◽  
Soil Carbon ◽  
Active Layer ◽  
High Latitude ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Soil Wetness ◽  
Soc Stocks

Abstract. The direction and magnitude of soil organic carbon (SOC) changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially-resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5). Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were: land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth System Models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%), followed by discontinuous (28%), isolated (24.3%), and sporadic (23.6%) permafrost areas. Our high resolution mapping of soil carbon stock reveals the potential vulnerability of high-latitude soil carbon and can be used as a basis for future studies of anthropogenic and climatic perturbations.

scholarly journals Soil moisture regimes in Mexico in a global 1.5°C warming scenario

2019 ◽  
Vol 11 (4) ◽  
pp. 465-482 ◽  
Author(s):  
Jesus David Gomez Diaz ◽  
Alejandro I. Monterroso ◽  
Patricia Ruiz ◽  
Lizeth M. Lechuga ◽  
Ana Cecilia Conde Álvarez ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Regional Scale ◽  
Moisture Regime ◽  
Monthly Precipitation ◽  
Climate Change Scenarios ◽  
Content Type ◽  
Warming Scenario ◽  
Moisture Regimes ◽  
Gfdl Model

Purpose This study aims to present the climate change effect on soil moisture regimes in Mexico in a global 1.5°C warming scenario. Design/methodology/approach The soil moisture regimes were determined using the Newhall simulation model with the database of mean monthly precipitation and temperature at a scale of 1: 250,000 for the current scenario and with the climate change scenarios associated with a mean global temperature increase of 1.5°C, considering two Representative Concentration Pathways, 4.5 and 8.5 W/m2 and three general models of atmospheric circulation, namely, GFDL, HADGEM and MPI. The different vegetation types of the country were related to the soil moisture regimes for current conditions and for climate change. Findings According to the HADGEM and MPI models, almost the entire country is predicted to undergo a considerable increase in soil moisture deficit, and part of the areas of each moisture regime will shift to the next drier regime. The GFDL model also predicts this trend but at smaller proportions. Originality/value The changes in soil moisture at the regional scale that reveal the impacts of climate change and indicate where these changes will occur are important elements of the knowledge concerning the vulnerability of soils to climate change. New cartography is available in Mexico.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Model Test ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Transient Climate Response ◽  
Uncertainty Range ◽  
Perfect Model ◽  
Future Warming

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as mean and likely range. Here, we use a model weighting approach, which accounts for a model's historical performance based on several diagnostics as well as possible model inter-dependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we remove each CMIP6 model from the ensemble in turn, use it as pseudo-observation in the historical period, and evaluate the weighted CMIP6 ensemble against it in the future. This is complemented by a second perfect model test drawing on the previous-generation CMIP5 models as pseudo-observations. In addition, we show that our independence diagnostics correctly clusters models known to be similar based on a CMIP6 family tree, which enables applying a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (ERA5 and MERRA2), to constrain CMIP6 projections in weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios. Our results show a reduction in projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 °C, compared to 4.1 °C without weighting; the likely (66 %) uncertainty range is 3.1 °C to 4.6 °C, a decrease of 13 %. For SSP1-2.6, weighted end-of-century warming is 1 °C (0.7 °C to 1.4 °C). Applying the weighting to estimates of Transient Climate Response (TCR) yields 1.9 °C (1.6 °C to 2.1 °C – a reduction in the likely uncertainty range of 46 %), which is consistent with estimates from previous model generations and other lines of evidence.

scholarly journals Projeções Climáticas das Alterações da Quantidade de Água no Solo Disponível para o Cultivo de Soja (Climate Projections of Quality Changes in Water Available on the Ground for Cultivation of Soybeans)

2012 ◽  
Vol 5 (4) ◽  
pp. 807
Author(s):  
Luciana Da Silva Mieres ◽  
Claudinéia Brazil Saldanha ◽  
Arthur Da Fontoura Tschiedel ◽  
Rogério De Lima Saldanha ◽  
Maria Angélica Gonçalves Cardoso
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Agricultural Productivity ◽  
Rio Grande ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Quality Changes ◽  
Rio Grande Do Sul ◽  
International Panel ◽  
Impacts Of Climate Change

As alterações climáticas estão associadas a graves impactos na agricultura uma vez que o crescimento e o desenvolvimento das culturas dependem diretamente do clima e das interações solo-atmosfera. A umidade do solo é uma informação fundamental no planejamento agrícola, subsidiando a definição das datas de plantio, necessidades de irrigação e produtividades agrícolas. O presente estudo objetivou avaliar os impactos das mudanças climáticas na umidade do solo para uma região de cultura de soja do estado do Rio Grande do Sul através dos cenários estabelecidos pelo IPCC (International Panel on Climate Change). Os resultados indicaram uma tendência ao aumento da precipitação, favorecendo o aumento da taxa de umidade do solo na região do médio alto Uruguai. Em síntese, o fator de umidade do solo apresentou condições favoráveis ao desenvolvimento vegetal e pelos resultados apresentados, verifica-se que o modelo de previsão de umidade do solo, analisado em conjunto com os cenários do IPCC, são importantes ferramentas para os estudos dos impactos das mudanças climáticas na produtividade agrícola. Palavras chaves: mudanças climáticas, soja, umidade do solo.   Climate Projections of Quality Changes in Water Available on the Ground for Cultivation of Soybeans   ABSTRACT Climate change is associated with serious impacts on agriculture since the crop growth and development depend directly on the climate and soil-atmosphere interactions. Soil moisture is fundamental information in agricultural planning, helping to define the dates of planting, irrigation needs, and agricultural productivity. In this study was evaluated the impacts of climate change in moisture soil to a region of the soybean crop in the state of Rio Grande do Sul using the IPCC (International Panel on Climate Change) scenarios set. The results indicated a tendency to increased rainfall, favoring an increase in the rate of soil moisture in the region of the middle upper Uruguay. The factor of soil moisture showed favorable conditions for plant development and the results presented showed that prediction model of soil moisture analyzed in conjunction with the IPCC scenarios are important tools for studies of the impacts of climate change on agricultural productivity. Keywords: Climate change, soybean, soil moisture.

scholarly journals Global soil organic carbon removal by water erosion under climate change and land use change during 1850–2005 AD

2018 ◽  
Author(s):  
Victoria Naipal ◽  
Philippe Ciais ◽  
Yilong Wang ◽  
Ronny Lauerwald ◽  
Bertrand Guenet ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Climate Variability ◽  
Carbon Cycle ◽  
Atmospheric Co2 ◽  
Terrestrial Carbon

Abstract. The onset and expansion of agriculture has accelerated soil erosion by rainfall and runoff substantially, mobilizing vast quantities of soil organic carbon (SOC) globally. Studies show that at timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use change (LUC). However, a full understanding of the impact of erosion on land-atmosphere carbon exchange is still missing. The aim of our study is to better constrain the terrestrial carbon fluxes by developing methods compatible with Earth System Models (ESMs) in order to explicitly represent the links between soil erosion by rainfall and runoff and carbon dynamics. For this we use an emulator that represents the carbon cycle of a land surface model, in combination with the Revised Universal Soil Loss Equation model. We applied this modeling framework at the global scale to evaluate the effects of potential soil erosion (soil removal only) in the presence of other perturbations of the carbon cycle: elevated atmospheric CO2, climate variability, and LUC. We found that over the period 1850–2005 AD acceleration of soil erosion leads to a total potential SOC removal flux of 100 Pg C of which 80 % occurs on agricultural, pasture and natural grass lands. Including soil erosion in the SOC-dynamics scheme results in a doubling of the cumulative loss of SOC over 1850–2005 due to the combined effects of climate variability, increasing atmospheric CO2 and LUC. This additional erosional loss decreases the cumulative global carbon sink on land by 5 Pg for this specific period, with the largest effects found for the tropics, where deforestation and agricultural expansion increased soil erosion rates significantly. We also show that the potential effects of soil erosion on the global SOC stocks cannot be ignored when compared to the effects of climate change or land use change on the carbon cycle. We conclude that it is necessary to include soil erosion in assessments of LUC and evaluations of the terrestrial carbon cycle.

scholarly journals Diverging responses of high-latitude CO<sub>2</sub> and CH<sub>4</sub> emissions in idealized climate change scenarios

2020 ◽  
Author(s):  
Philipp de Vrese ◽  
Tobias Stacke ◽  
Thomas Kleinen ◽  
Victor Brovkin
Keyword(s):  
Climate Change ◽  
Organic Matter ◽  
Global Warming ◽  
21St Century ◽  
High Latitude ◽  
Climate Change Scenarios ◽  
Climate Scenarios ◽  
Soil Co2 ◽  
Linear Dependency ◽  
Soil Co2 Emissions

Abstract. The present study investigates the response of the high latitude's carbon cycle to in- and decreasing atmospheric greenhouse gas (GHG) concentrations in idealized climate change scenarios. For this, we use an adapted version of JSBACH – the land-surface component of the Max-Planck-Institute for Meteorology's Earth system model (MPI-ESM) – that accounts for the organic matter stored in the permafrost-affected soils of the high northern latitudes. To force the model, we use different climate scenarios that assume an increase in GHG concentrations, following the Shared Socioeconomic Pathway 5, until peaks in the years 2025, 2050, 2075 or 2100, respectively. The peaks are followed by a decrease in atmospheric GHGs that returns the concentrations to the levels at the beginning of the 21st century. We show that the soil CO2 emissions exhibit an almost linear dependency on the global mean surface temperatures that are simulated for the different climate scenarios. Here, each degree of warming increases the fluxes by, very roughly, 50 % of their initial value, while each degree of cooling decreases them correspondingly. However, the linear dependency does not mean that the processes governing the soil CO2 emissions are fully reversible on short timescales, but rather that two strongly hysteretic factors offset each other – namely the vegetation's net primary productivity and the availability of formerly frozen soil organic matter. In contrast, the soil methane emissions show almost no increase with rising temperatures and they are consistently lower after than prior to a peak in the GHG concentrations. Here, the fluxes can even become negative and we find that methane emissions will play only a minor role in the northern high latitudes' contribution to global warming, even when considering the gas's high global warming potential. Finally, we find that the high-latitude ecosystem acts as a source of atmospheric CO2 rather than a sink, with the net fluxes into the atmosphere increasing substantially with rising atmospheric GHG concentrations. This is very different to scenario simulations with the standard version of the MPI-ESM in which the region continues to take up atmospheric CO2 throughout the entire 21st century, confirming that the omission of permafrost-related processes and the organic matter stored in the frozen soils leads to a fundamental misrepresentation of the carbon dynamics in the Arctic.

Sign in / Sign up

Export Citation Format

Share Document