scholarly journals Uncertainty in climate change projections of discharge for the Mekong River Basin

2011 ◽  
Vol 15 (5) ◽  
pp. 1459-1471 ◽  
Author(s):  
D. G. Kingston ◽  
J. R. Thompson ◽  
G. Kite

Abstract. The Mekong River Basin is a key regional resource in Southeast Asia for sectors that include agriculture, fisheries and electricity production. Here we explore the potential impacts of climate change on freshwater resources within the river basin. We quantify uncertainty in these projections associated with GCM structure and climate sensitivity, as well as from hydrological model parameter specification. This is achieved by running pattern-scaled GCM scenarios through a semi-distributed hydrological model (SLURP) of the basin. Pattern-scaling allows investigation of specific thresholds of global climate change including the postulated 2 °C threshold of "dangerous" climate change. Impacts of a 2 °C rise in global mean temperature are investigated using seven different GCMs, providing an implicit analysis of uncertainty associated with GCM structure. Analysis of progressive changes in global mean temperature from 0.5 to 6 °C above the 1961–1990 baseline (using the HadCM3 GCM) reveals a relatively small but non-linear response of annual river discharge to increasing global mean temperature, ranging from a 5.4 % decrease to 4.5 % increase. Changes in mean monthly river discharge are greater (from −16 % to +55 %, with greatest decreases in July and August, greatest increases in May and June) and result from complex and contrasting intra-basin changes in precipitation, evaporation and snow storage/melt. Whilst overall results are highly GCM dependent (in both direction and magnitude), this uncertainty is primarily driven by differences in GCM projections of future precipitation. In contrast, there is strong consistency between GCMs in terms of both increased potential evapotranspiration and a shift to an earlier and less substantial snowmelt season. Indeed, in the upper Mekong (Lancang sub-basin), the temperature-related signal in discharge is strong enough to overwhelm the precipitation-related uncertainty in the direction of change in discharge, with scenarios from all GCMs leading to increased river flow from April–June and decreased flow from July–August.

2010 ◽  
Vol 7 (4) ◽  
pp. 5991-6024 ◽  
Author(s):  
D. G. Kingston ◽  
J. R. Thompson ◽  
G. Kite

Abstract. The Mekong River Basin comprises a key regional resource in Southeast Asia for sectors that include agriculture, fisheries and electricity production. Here we explore the potential impacts of climate change on freshwater resources within the river basin. We quantify uncertainty in these projections associated with GCM structure and climate sensitivity, as well as from hydrological model parameter specification. This is achieved by running pattern-scaled GCM output through a semi-distributed hydrological model (SLURP) of the basin. These pattern-scaled GCM outputs allow investigation of specific thresholds of global climate change including the postulated 2 ºC threshold of "dangerous" climate change as simulated using outputs from seven different GCMs. Detailed analysis of results based on HadCM3 climate scenarios reveals a relatively small but non-linear response of annual river discharge to increasing global mean temperature, ranging from a 5.4% decrease to 4.5% increase. Intra-annual (monthly) changes in river discharge are greater (from −16% to +55%, with greatest decreases in July and August, greatest increases in May and June) and result from complex and contrasting intra-basin changes in precipitation, evaporation and snow storage/melt. Whilst overall results are highly GCM dependent (in both direction and magnitude), this uncertainty is primarily driven by differences in GCM projections of future precipitation. In contrast, there is strong consistency between GCMs in terms of both increased potential evapotranspiration and a shift to an earlier and less substantial snowmelt season. Indeed, in the upper Mekong (Lancang sub-basin), the temperature-related signal in discharge is strong enough to overwhelm the precipitation-related uncertainty in the direction of change in discharge, with scenarios from all GCMs leading to increased river flow from April–June, and decreased flow from July–August.


2019 ◽  
Vol 34 (S1) ◽  
pp. 367-380
Author(s):  
Dao Nguyen Khoi ◽  
Van Thinh Nguyen ◽  
Truong Thao Sam ◽  
Nguyen Ky Phung ◽  
Nguyen Thi Bay

2021 ◽  
Vol 36 ◽  
pp. 100873
Author(s):  
Yishan Li ◽  
Hui Lu ◽  
Kun Yang ◽  
Wei Wang ◽  
Qiuhong Tang ◽  
...  

2020 ◽  
Vol 12 (9) ◽  
pp. 3737
Author(s):  
Osamu Nishiura ◽  
Makoto Tamura ◽  
Shinichiro Fujimori ◽  
Kiyoshi Takahashi ◽  
Junya Takakura ◽  
...  

Coastal areas provide important services and functions for social and economic activities. Damage due to sea level rise (SLR) is one of the serious problems anticipated and caused by climate change. In this study, we assess the global economic impact of inundation due to SLR by using a computable general equilibrium (CGE) model that incorporates detailed coastal damage information. The scenario analysis considers multiple general circulation models, socioeconomic assumptions, and stringency of climate change mitigation measures. We found that the global household consumption loss proportion will be 0.045%, with a range of 0.027−0.066%, in 2100. Socioeconomic assumptions cause a difference in the loss proportion of up to 0.035% without greenhouse gas (GHG) emissions mitigation, the so-called baseline scenarios. The range of the loss proportion among GHG emission scenarios is smaller than the differences among the socioeconomic assumptions. We also observed large regional variations and, in particular, the consumption losses in low-income countries are, relatively speaking, larger than those in high-income countries. These results indicate that, even if we succeed in stabilizing the global mean temperature increase below 2 °C, economic losses caused by SLR will inevitably happen to some extent, which may imply that keeping the global mean temperature increase below 1.5 °C would be worthwhile to consider.


2019 ◽  
Author(s):  
Inne Vanderkelen ◽  
Jakob Zschleischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.


2010 ◽  
Vol 106 (2) ◽  
pp. 141-177 ◽  
Author(s):  
Rachel Warren ◽  
Jeff Price ◽  
Andreas Fischlin ◽  
Santiago de la Nava Santos ◽  
Guy Midgley

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.


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