scholarly journals Comparing soil carbon loss through respiration and leaching under extreme precipitation events in arid and semi-arid grasslands

2017 ◽  
Author(s):  
Ting Liu ◽  
Liang Wang ◽  
Xiaojuan Feng ◽  
Jinbo Zhang ◽  
Tian Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Carbon ◽  
Extreme Precipitation ◽  
Dissolved Inorganic Carbon ◽  
Precipitation Event ◽  
Carbon Loss ◽  
Research Attention ◽  
Extreme Precipitation Events ◽  
Leaching Loss ◽  
Arid And Semiarid

Abstract. Respiration and leaching are two main processes responsible for soil carbon loss. While the former has received considerable research attention, studies examining leaching processes are limited especially in semiarid grasslands due to low precipitation. Climate change may increase the extreme precipitation event (EPE) frequency in arid and semiarid regions, potentially enhancing soil carbon loss through leaching and respiration. Here we incubated soil columns of three typical grassland soils from Inner Mongolia and Qinghai-Tibetan Plateau and examined the effect of simulated EPEs on soil carbon loss through respiration and leaching. EPEs induced transient increase of soil respiration, equivalent to 32 % and 72 % of the net ecosystem productivity (NEP) in the temperate grasslands (Xilinhot and Keqi) and 7 % in the alpine grasslands (Gangcha). By comparison, leaching loss of soil carbon accounted for 290 %, 120 % and 15 % of NEP at the corresponding sites, respectively, with dissolved inorganic carbon (DIC) as the main form of carbon loss in the alkaline soils. Moreover, DIC loss increased with re-occuring EPEs in the soil with the highest pH due to increased dissolution of soil carbonates and elevated contribution of dissolved CO2 from organic carbon degradation (indicated by DIC-δ13C). These results highlight that leaching loss of soil carbon (particularly DIC) is important in the regional carbon budget of arid and semiarid grasslands. With a projected increase of EPEs under climate change, soil carbon leaching processes and its influencing factors warrant better understanding and should be incorporated into soil carbon models when estimating carbon balance in grassland ecosystems.

scholarly journals Comparing soil carbon loss through respiration and leaching under extreme precipitation events in arid and semiarid grasslands

2018 ◽  
Vol 15 (5) ◽  
pp. 1627-1641 ◽  
Author(s):  
Ting Liu ◽  
Liang Wang ◽  
Xiaojuan Feng ◽  
Jinbo Zhang ◽  
Tian Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Carbon ◽  
Extreme Precipitation ◽  
Precipitation Event ◽  
Alkaline Soils ◽  
Carbon Loss ◽  
Research Attention ◽  
Extreme Precipitation Events ◽  
Leaching Loss ◽  
Arid And Semiarid

Abstract. Respiration and leaching are two main processes responsible for soil carbon loss. While the former has received considerable research attention, studies examining leaching processes are limited, especially in semiarid grasslands due to low precipitation. Climate change may increase the extreme precipitation event (EPE) frequency in arid and semiarid regions, potentially enhancing soil carbon loss through leaching and respiration. Here we incubated soil columns of three typical grassland soils from Inner Mongolia and the Qinghai–Tibetan Plateau and examined the effect of simulated EPEs on soil carbon loss through respiration and leaching. EPEs induced a transient increase in CO2 release through soil respiration, equivalent to 32 and 72 % of the net ecosystem productivity (NEP) in the temperate grasslands (Xilinhot and Keqi) and 7 % of NEP in the alpine grasslands (Gangcha). By comparison, leaching loss of soil carbon accounted for 290, 120, and 15 % of NEP at the corresponding sites, respectively, with dissolved inorganic carbon (DIC, biogenic DIC + lithogenic DIC) as the main form of carbon loss in the alkaline soils. Moreover, DIC loss increased with recurring EPEs in the soil with the highest pH due to an elevated contribution of dissolved CO2 from organic carbon degradation (indicated by DIC-δ13C). These results highlight the fact that leaching loss of soil carbon (particularly in the form of DIC) is important in the regional carbon budget of arid and semiarid grasslands and also imply that SOC mineralization in alkaline soils might be underestimated if only measured as CO2 emission from soils into the atmosphere. With a projected increase in EPEs under climate change, soil carbon leaching processes and the influencing factors warrant a better understanding and should be incorporated into soil carbon models when estimating carbon balance in grassland ecosystems.

Quantifying the added value of downscaling in extreme precipitation attribution

2020 ◽  
Author(s):  
Jonathan Eden ◽  
Bastien Dieppois
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
General Circulation ◽  
Regional Climate ◽  
Precipitation Event ◽  
Extreme Precipitation Events ◽  
Statistical Correction ◽  
Precipitation Events

<p>While there is a discernible global warming fingerprint in the increase observed daily temperature extremes, there is far greater uncertainty of the role played by anthropogenic climate change with regard to extreme precipitation. A logical progression of thought is that an increase in extreme precipitation results from the 7% increase in atmospheric moisture per 1°C global temperature increase predicted by the Clausius-Clapeyron (CC) relation.  While this is supported by observations on the global scale, rates of extreme precipitation at smaller spatial and temporal scales are influenced to a far greater extent by atmospheric circulation and vertical stability in addition to local moisture availability. Many of these processes and other features of extreme precipitation events are not sufficiently represented in general circulation model (GCM) simulations. Meanwhile, limited observational networks mean that many short-term convective events are not accurately represented in the observational data.  </p><p>Errors and biases are common to all global and regional climate models, and many users of climate information require some form of statistical correction to improve the usefulness of model output. As so-called bias correction has become commonplace in climate impact research, its development has been hastened by a sustained debate regarding model correction in general leading to techniques that merge statistical correction and downscaling, represent random variability using stochasticity and are explicitly applicable to extremes. To date, attribution of extreme precipitation has not fully utilised the tools available from recent advances in bias correction, stochastic postprocessing and statistical downscaling. In the same way that GCMs are the most important tool in making climate change projections, understanding the degree to which the nature of a particular weather event has changed due to global warming requires long-term simulations of global climate from the pre-industrial era to the present day.  The lack of a correction and/or downscaling step in almost all precipitation event attribution methodologies is therefore surprising. </p><p>Here, we present a multi-scale attribution analysis of a sample of extreme precipitation events across Europe using a blend of observation- and model-based data. Attribution information generated using the raw output of global and regional climate model ensembles will be compared to that generated using the same set of models following a statistical postprocessing and downscaling step. Our conclusions will make recommendations for the value and wider application of downscaling methodologies in attribution science.</p>

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Historical Period ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

The effect of climate change on urban drainage: an evaluation based on regional climate model simulations

2006 ◽  
Vol 54 (6-7) ◽  
pp. 9-15 ◽  
Author(s):  
M. Grum ◽  
A.T. Jørgensen ◽  
R.M. Johansen ◽  
J.J. Linde
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Extreme Precipitation Events ◽  
Rainfall Extremes ◽  
The Future ◽  
Precipitation Events

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 × 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at time-scales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

Comparative Analysis or Precipitation Variation Characteristics between Subtropical Monsoon Climate and Temperate Monsoon Climate-Take Changsha and Chengde for Example

2021 ◽  
Vol 7 (5) ◽  
pp. 1113-1122
Author(s):  
Bo Chen ◽  
Shi-jun Xu ◽  
Xin-ping Zhang ◽  
Yi Xie
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Precipitation Intensity ◽  
Annual Precipitation ◽  
Wet Season ◽  
Precipitation Frequency ◽  
Extreme Precipitation Events ◽  
Average Precipitation ◽  
Autumn And Winter ◽  
Average Annual Precipitation

Using the methods of literature review, regression analysis and moving average, this paper selects the daily precipitation of Changsha and Chengde from 1951 to 1986 as samples, and analyzes the average precipitation, precipitation frequency, precipitation intensity, extreme precipitation time and other indicators of Changsha and Chengde from the perspective of interannual and seasonal changes Trends. The researches show that: the average precipitation of Changsha in the 36 years is 1151.2mm, spring is the wet season, autumn and winter are the dry seasons, and the maximum average precipitation is in spring; the average annual precipitation, precipitation frequency in spring, summer and winter, annual precipitation frequency, annual precipitation intensity and extreme precipitation events show a decreasing trend. The average annual precipitation of Chengde city is 454.1 mm, wet season in summer and dry season in spring, autumn and winter; the average annual precipitation, precipitation in four seasons, annual precipitation frequency, precipitation frequency in spring, autumn and winter, annual precipitation intensity and extreme precipitation events show a decreasing trend, while the precipitation frequency in summer shows an increasing trend. The study of regional climate change based on the time series data of this stage is of great significance to comprehensively understand the law of regional climate change and predict the future trend of climate change.

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