scholarly journals Spatial–temporal changes in runoff and terrestrial ecosystem water retention under 1.5 and 2 °C warming scenarios across China

2018 ◽  
Vol 9 (2) ◽  
pp. 717-738 ◽  
Author(s):  
Ran Zhai ◽  
Fulu Tao ◽  
Zhihui Xu
Keyword(s):  
Interannual Variability ◽  
Water Retention ◽  
Terrestrial Ecosystem ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Warming Scenario ◽  
Basin Scale ◽  
High Runoff ◽  
Median Change

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ∘C above pre-industrial levels, pursuing efforts to limit this to 1.5 ∘C; it is therefore important to understand the impacts of climate change under 1.5 and 2.0 ∘C warming scenarios for climate adaptation and mitigation. Here, climate scenarios from four global circulation models (GCMs) for the baseline (2006–2015), 1.5, and 2.0 ∘C warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on runoff and terrestrial ecosystem water retention (TEWR) across China at a spatial resolution of 0.5∘. This study applied ensemble projections from multiple GCMs to provide more comprehensive and robust results. The trends in annual mean temperature, precipitation, runoff, and TEWR were analyzed at the grid and basin scale. Results showed that median change in runoff ranged from 3.61 to 13.86 %, 4.20 to 17.89 %, and median change in TEWR ranged from −0.45 to 6.71 and −3.48 to 4.40 % in the 10 main basins in China under 1.5 and 2.0 ∘C warming scenarios, respectively, across all four GCMs. The interannual variability of runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from the 1.5 to the 2.0 ∘C warming scenario. In contrast, TEWR would remain relatively stable, the median change in standard deviation (SD) of TEWR ranged from −10 to 10 % in about 90 % grids under 1.5 and 2.0 ∘C warming scenarios, across all four GCMs. Both low and high runoff would increase under the two warming scenarios in most areas across China, with high runoff increasing more. The risks of low and high runoff events would be higher under the 2.0 than under the 1.5 ∘C warming scenario in terms of both extent and intensity. Runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our results were supported by previous studies. However, there existed large uncertainties in climate scenarios from different GCMs, which led to large uncertainties in impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. Our findings on the spatiotemporal patterns of climate impacts and their shifts from the 1.5 to the 2.0 ∘C warming scenario are useful for water resource management under different warming scenarios.

scholarly journals Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

2017 ◽  
Author(s):  
Ran Zhai ◽  
Fulu Tao ◽  
Zhihui Xu
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
River Runoff ◽  
Water Retention ◽  
Terrestrial Ecosystem ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Warming Scenario ◽  
Basin Scale ◽  
The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

Building a Resilient Tomorrow

2019 ◽  
Author(s):  
Alice C. Hill ◽  
Leonardo Martinez-Diaz
Keyword(s):  
Global Climate Change ◽  
Global Climate ◽  
Climate Impacts ◽  
Decision Makers ◽  
Climate Scenarios ◽  
Related Disease ◽  
Climate Resilience ◽  
Personal Experiences ◽  
Financial Disincentives ◽  
Biological Solutions

Even under the most optimistic scenarios, significant global climate change is now inevitable. Although we cannot tell with certainty how much average global temperatures will rise, we do know that the warming we have experienced to date has already caused significant losses, and that the failure to prepare for the consequences of further warming may prove to be staggering. This book does not dwell on overhyped descriptions of apocalyptic climate scenarios, nor does it travel down well-trodden paths surrounding the politics of reducing carbon emissions. Instead, it starts with two central facts: there will be future climate impacts, and we can make changes now to buffer their effects. While squarely confronting the scale of the risks we face, this pragmatic guide focuses on solutions—some gradual and some more revolutionary—currently being deployed around the globe. Each chapter presents a thematic lesson for decision-makers and engaged citizens to consider, outlining replicable successes and identifying provocative recommendations to strengthen climate resilience. Between discussions of ideas as wide-ranging as managed retreat from coastal hot zones to biological solutions for resurgent climate-related disease threats, the authors draw on their personal experiences to tell behind-the-scenes stories of what it really takes to advance progress on these issues. The narrative is dotted with stories of on-the-ground citizenry, from small-town mayors and bankers to generals and engineers, who are chipping away at financial disincentives and bureaucratic hurdles to prepare for life on a warmer planet.

scholarly journals A hydrological modelling-based approach for vulnerable area identification under changing climate scenarios

2020 ◽  
Author(s):  
Sonam S. Dash ◽  
Dipaka R. Sena ◽  
Uday Mandal ◽  
Anil Kumar ◽  
Gopal Kumar ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Fold Increase ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Vulnerable Area ◽  
Temperature And Precipitation ◽  
Monthly Streamflow ◽  
Rcp 8.5 ◽  
Streamflow Data ◽  
Critical Zones

Abstract The hydrologic behaviour of the Brahmani River basin (BRB) (39,633.90 km2), India was assessed for the base period (1970–1999) and future climate scenarios (2050) using the Soil and Water Assessment Tool (SWAT). Monthly streamflow data of 2000–2009 and 2010–2012 was used for calibration and validation, respectively, and performed satisfactorily with Nash-Sutcliffe Efficiency (ENS) of 0.52–0.55. The projected future climatic outcomes of the HadGEM2-ES model indicated that minimum temperature, maximum temperature, and precipitation may increase by 1.11–3.72 °C, 0.27–2.89 °C, and 16–263 mm, respectively, by 2050. The mean annual streamflow over the basin may increase by 20.86, 11.29, 4.45, and 37.94% under RCP 2.6, 4.5, 6.0, and 8.5, respectively, whereas the sediment yield is likely to increase by 23.34, 10.53, 2.45, and 27.62% under RCP 2.6, 4.5, 6.0, and 8.5, respectively, signifying RCP 8.5 to be the most adverse scenario for the BRB. Moreover, a ten-fold increase in environmental flow (defined as Q90) by the mid-century period is expected under the RCP 8.5 scenario. The vulnerable area assessment revealed that the increase in moderate and high erosion-prone regions will be more prevalent in the mid-century. The methodology developed herein could be successfully implemented for identification and prioritization of critical zones in worldwide river basins.

scholarly journals Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 165
Author(s):  
Prem B. Parajuli ◽  
Avay Risal
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Minimum Temperature ◽  
Future Climate ◽  
Maximum Temperature ◽  
Nutrient Load ◽  
Climate Scenarios ◽  
Monthly Average ◽  
Average Maximum ◽  
Monthly Streamflow

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.

scholarly journals Comparing dynamical, stochastic and combined downscaling approaches – lessons from a case study in the Mediterranean region

2012 ◽  
Vol 9 (8) ◽  
pp. 9847-9884
Author(s):  
N. Guyennon ◽  
E. Romano ◽  
I. Portoghese ◽  
F. Salerno ◽  
S. Calmanti ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Max Planck ◽  
Basin Scale ◽  
Quantile Transform

Abstract. Various downscaling techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Such techniques may be grouped into two downscaling approaches: the deterministic dynamical downscaling (DD) and the stochastic statistical downscaling (SD). Although SD has been traditionally seen as an alternative to DD, recent works on statistical downscaling have aimed to combine the benefits of these two approaches. The overall objective of this study is to examine the relative benefits of each downscaling approach and their combination in making the GCM scenarios suitable for basin scale hydrological applications. The case study presented here focuses on the Apulia region (South East of Italy, surface area about 20 000 km2), characterized by a typical Mediterranean climate; the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined for the period 1953–2000. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile transform. The SD resulted efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but it was not able to correct the miss-modeled non-stationary components of the GCM dynamics. The DD provided a partial correction by enhancing the trend spatial heterogeneity and time evolution predicted by the GCM, although the comparison with observations resulted still underperforming. The best results were obtained through the combination of both DD and SD approaches.

scholarly journals Assessment of Heat Stress and Cloudiness Probabilities in Post-Flowering of Wheat and Canola in The Southern Cone of South America

2021 ◽  
Author(s):  
Gonzalo Martín Rivelli ◽  
María Elena Fernández Long ◽  
Leonor Gabriela Abeledo ◽  
Daniel Calderini ◽  
Daniel Julio Miralles ◽  
...  
Keyword(s):  
Heat Stress ◽  
Solar Radiation ◽  
South America ◽  
Southern Cone ◽  
Maximum Temperature ◽  
Curvilinear Relationship ◽  
Climate Scenarios ◽  
Incident Solar Radiation ◽  
Probability Of Occurrence ◽  
Combined Stresses

Abstract Episodes of heat stress constrain crop production and will be aggravated in the near future according to short and medium-term climate scenarios. Global increase in cloudiness has also been observed, decreasing the incident solar radiation. This work was aimed to quantify the probability of occurrence of heat stress and cloudiness, alone or combined, during the typical post-flowering period of wheat and canola in the Southern Cone of South America. Extended climate series (last 3-5 decades with daily register) of 33 conventional weather stations from Argentina, Brazil, Chile and Uruguay (23ºS to 40ºS) were analysed considering the period from September to December. Two different daily events of heat stress were determined: i) maximum daily temperature above 30ºC (T>30ºC), and ii) 5ºC above the historical average maximum temperature of that day (T+5ºC). A cloudiness event was defined in our work as incident solar radiation 50% lower than the historical average radiation of that day (R50%). The T>30ºC event increased its probability of occurrence throughout the post-flowering phase, from September to December. By contrast, the risk of T+5ºC event decreased slightly, just like for R50%, and the higher the latitude, the lower the probability of R50%. The T>30ºC plus R50% combined stresses reached greater cumulated probabilities during post-flowering, compared to T+5ºC plus R50%, being 42% vs. 15% in northernmost locations, 26% vs. 19% in central (between 31ºS to 35ºS), and 28% vs. 1% in southernmost locations, respectively. A curvilinear relationship emerged between the monthly probability of combined stresses and the number of days with stress per month. In summary, T>30ºC was the most frequent thermal stress during post-flowering in wheat and canola. Both combined stresses had a noticeable risk of occurrence, but T>30ºC plus R50% was the highest. Evidence of the recent past and current occurrence of heat stress individually, and its combination with cloudiness events during post-flowering of temperate crops, serves as a baseline for future climate scenarios in main cropped areas in the Southern Cone of South America.

Impacts of interannual climate and biophysical variability on global agriculture markets

2020 ◽  
Author(s):  
Xin Zhao ◽  
Katherine Calvin ◽  
Marshall Wise ◽  
Pralit Patel ◽  
Abigail Snyder ◽  
...  
Keyword(s):  
Land Use ◽  
Interannual Variability ◽  
Weather Conditions ◽  
Climate Impacts ◽  
Interannual Variations ◽  
Standard Assumption ◽  
Adaptive Expectations ◽  
Equilibrium Modeling ◽  
Production And Consumption ◽  
Global Agriculture

Abstract Most studies assessing climate impacts on agriculture have focused on average changes in market-mediated responses (e.g., changes in land use, production, and consumption). However, the response of global agricultural markets to interannual variability in climate and biophysical shocks is poorly understood and not well represented in global economic models. Here we show a strong transmission of interannual variations in climate-induced biophysical yield shocks to agriculture markets, which is further magnified by endogenous market fluctuations generated due to producers’ imperfect expectations of market and weather conditions. We demonstrate that the volatility of crop prices and consumption could be significantly underestimated (i.e., on average by 55% and 41%, respectively) by assuming perfect foresight, a standard assumption in the economic equilibrium modeling, compared with the relatively more realistic adaptive expectations. We also find heterogeneity in interannual variability across crops and regions, which is considerably mediated by international trade.

scholarly journals Climate Impacts of Land-Cover and Land-Use Changes in Tropical Islands under Conditions of Global Climate Change

2013 ◽  
Vol 26 (5) ◽  
pp. 1535-1550 ◽  
Author(s):  
Daniel E. Comarazamy ◽  
Jorge E. González ◽  
Jeffrey C. Luvall ◽  
Douglas L. Rickman ◽  
Robert D. Bornstein
Keyword(s):  
Boundary Layer ◽  
Land Use ◽  
Global Warming ◽  
Land Cover ◽  
Atmospheric Modeling ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Tropical Islands ◽  
Near Surface ◽  
Convergence Zones

Abstract Land-cover and land-use (LCLU) changes have significant climate impacts in tropical coastal regions with the added complexity of occurring within the context of a warming climate. The individual and combined effects of these two factors in tropical islands are investigated by use of an integrated mesoscale atmospheric modeling approach, taking the northeastern region of Puerto Rico as the test case. To achieve this goal, an ensemble of climate simulations is performed, combining two LCLU and global warming scenarios. Reconstructed agricultural maps and sea surface temperatures form the past (1955–59) scenario, while the present (2000–04) scenario is supported with high-resolution remote sensing LCLU data. Here, the authors show that LCLU changes produced the largest near-surface (2-m AGL) air temperature differences over heavily urbanized regions and that these changes do not penetrate the boundary layer. The influence of the global warming signal induces a positive inland gradient of maximum temperature, possibly because of increased trade winds in the present climatology. These increased winds also generate convergence zones and convection that transport heat and moisture into the boundary layer. In terms of minimum temperatures, the global warming signal induces temperature increases along the coastal plains and inland lowlands.

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