Selection and downscaling of general circulation model datasets and extreme climate indices analysis - Manual

2020 ◽  
Author(s):  
Saurav Pradhananga ◽  
Arthur Lutz ◽  
Archana Shrestha ◽  
Indira Kadel ◽  
Bikash Nepal ◽  
...  

A supplement to the Climate Change Scenarios for Nepal report published by the Ministry of Forests and Environment for the National Adaptation Plan (NAP) Process, this manual provides detailed information about the processes through which the assessment highlighted in the report can be carried out. They include – selection of the general circulation/climate models (GCMs), downscaling of the GCM dataset, assessment of changes in precipitation and temperature, and assessment of change in climate extremes. The manual downscales climate datasets for the Koshi River basin, the Kabul River basin, and the Kailash Sacred Landscape to analyse future scenarios in these basins and the landscape.

Author(s):  
M. S. Saranya ◽  
V. Nair Vinish

Abstract It is well recognised that the performance of climate model simulations and bias correction methods is region specific, and, therefore, careful validation should always be performed. This study evaluates the performance of five general circulation model–regional climate model (GCM–RCM) combinations selected from CORDEX–SA datasets over a humid tropical river basin in Kerala, India, for climate variables such as precipitation, maximum and minimum temperatures. This involves ranking of the selected climate models based on an EDAS (Evaluation Based on Distance from Average Solution) method and the selection of an appropriate bias correction method for the selected three climate variables. A range of indices are used to evaluate the performance of the bias-corrected climate models to simulate observed climate data. Finally, the hydrological impact of the bias-corrected ranked models is assessed by simulating streamflow over the river basin using individual models and different combinations of models based on rank. According to the findings, hydrological simulation using an average of all GCM–RCM pairs provides the best model output in simulating streamflow, with an NSE value of 0.72. The results confirm the importance of a multimodel ensemble for improving the reliability and minimising the uncertainty of climate predictions for impact studies.


2017 ◽  
Vol 9 (3) ◽  
pp. 421-433 ◽  
Author(s):  
Hamed Rouhani ◽  
Marayam Sadat Jafarzadeh

Abstract A general circulation model (GCM) and hydrological model SWAT (Soil and Water Assessment Tool) under forcing from A1B, B1, and A2 emission scenarios by 2030 were used to assess the implications of climate change on water balance of the Gorganrood River Basin (GRB). The results of MPEH5C models and multi-scenarios indicated that monthly precipitation generally decreases while temperature increases in various parts of the basin with the magnitude of the changes in terms of different stations and scenarios. Accordingly, seasonal ET will decrease throughout the GRB over the 2020s in all seasons except in summer, where a slight increase is projected for A1B and A2 scenarios. At annual scale, average quick flow and average low flow under the B1, A1B, and A2 scenarios are projected to decrease by 7.3 to 12.0% from the historical levels. Over the ensembles of climate change scenarios, the simulations project average autumn total flow declines of ∼10% and an overall range of 6.9 to 13.2%. In summer, the components of flow at the studied basin are expected to increase under A2 and A1B scenarios but will slightly decrease under B1 scenario. The study result addresses a likelihood of inevitable future climate change.


2020 ◽  

<p>Two hydrological climate modelling techniques, general circulation model (GCM) and hypothetical climate change scenarios, were used to analyse the hydrological response to the anticipated climate change scenarios in the Subarnarekha river basin in Eastern India. Both models verified individually for the same river basin and a comparative performance of the models was evaluated to relate the two models for the near (2014-2040) period climate. The hydrological response under the anticipated climate change in the Subarnarekha river basin is well assessed by GCM under the RCP 8.5 scenarios compared to the RCPs 4.5. Results indicate GCM best suited over the hypothetical climate change scenarios as GCM has demonstrated their potential in accurately reproducing the past observed climatic changes. The strong performance of the hypothetical climate change scenarios model, particularly for warming climate scenarios, suggests that it may have distinct advantages for the analysis of water balance components in the river basin. The monthly streamflows of Subarnarekha river basin was simulated using a total of 14 years (2000-2013) daily observed streamflow data in the ArcSWAT model integrated with model calibration and uncertainty analysis by means of SUFI-2 algorithm. The results indicate during the calibration the coefficient of determination (R2) and Nash-Sutcliff Efficiency (NSE) were reported as 0.98 and 0.97, respectively, while during the validation the R2 and NSE were obtained as 0.94 and 0.94, respectively, confirms the hydrological model performance was very good both in calibration and validation. The obtained climate change water impact index (ICCWI) values reveal the Subarnarekha river basin is more responsive to climate change. The reduction in precipitation along with the significant warming under the projected future climate is likely to reduce availability of water substantially in the study region. This work would be useful for the effective management of water resources for sustainable agriculture and in mitigating natural hazards such as droughts and floods in the study region.</p>


2014 ◽  
Vol 5 (4) ◽  
pp. 676-695 ◽  
Author(s):  
Mou Leong Tan ◽  
Darren L. Ficklin ◽  
Ab Latif Ibrahim ◽  
Zulkifli Yusop

The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) on streamflow in the Johor River Basin, Malaysia was assessed. Eighteen GCMs were evaluated, and the six that adequately simulated historical climate were selected for an ensemble of GCMs under three Representative Concentration Pathways (RCPs; 2.6 (low emissions), 4.5 (moderate emissions) and 8.5 (high emissions)) for three future time periods (2020s, 2050s and 2080s) as inputs into the Soil and Water Assessment Tool (SWAT) hydrological model. We also quantified the uncertainties associated with GCM structure, greenhouse gas concentration pathways (RCP 2.6, 4.5 and 8.5), and prescribed increases of global temperature (1–6 °C) through streamflow changes. The SWAT model simulated historical monthly streamflow well, with a Nash–Sutcliffe efficiency coefficient of 0.66 for calibration and 0.62 for validation. Under RCPs 2.6, 4.5, and 8.5, the results indicate that annual precipitation changes of 1.01 to 8.88% and annual temperature of 0.60–3.21 °C will lead to a projected annual streamflow ranging from 0.91 to 12.95% compared to the historical period. The study indicates multiple climate change scenarios are important for a robust hydrological impact assessment.


2020 ◽  
Author(s):  
Ernesto Pasten-Zapata ◽  
Paul Royer-Gaspard ◽  
Rafael Pimentel ◽  
Torben O. Sonnenborg ◽  
Anthony Lemoine ◽  
...  

&lt;p&gt;Commonly, the analysis of climate change impacts on hydrology involves a series of steps that begin with a General Circulation Model followed by the application of a downscaling or bias correction method and then coupling the climate outputs to a hydrological model. Nevertheless, frequently the hydrological models employed in these analyses are not tested to assess their skill to simulate the hydrology of a catchment under changing climate regimes. We evaluate such skill by applying a Differential Split Sampling Test (DSST) using the available observations. The models are calibrated during the three most extreme dry (or wet) years and evaluated on the three most wet (or dry) years. The DSST is applied on three catchments located across Europe: Denmark, France and Spain. This spatial distribution allows us to evaluate the method on diverse climatic and hydrological regimes. Furthermore, the DSST is applied to three different models in each of the catchments and case-specific metrics are evaluated to determine the practical usefulness of the models. Based on the DSST results, we assign a weight to the hydrological models and drive them with six Euro-CORDEX Regional Climate Models to assess climate change scenarios for the case-specific metrics. This methodology allows us to increase the confidence of our projections considering the hydrological model uncertainty for transient climatic conditions.&lt;/p&gt;


2007 ◽  
Vol 20 (4) ◽  
pp. 765-771 ◽  
Author(s):  
Markus Jochum ◽  
Clara Deser ◽  
Adam Phillips

Abstract Atmospheric general circulation model experiments are conducted to quantify the contribution of internal oceanic variability in the form of tropical instability waves (TIWs) to interannual wind and rainfall variability in the tropical Pacific. It is found that in the tropical Pacific, along the equator, and near 25°N and 25°S, TIWs force a significant increase in wind and rainfall variability from interseasonal to interannual time scales. Because of the stochastic nature of TIWs, this means that climate models that do not take them into account will underestimate the strength and number of extreme events and may overestimate forecast capability.


2019 ◽  
Vol 111 ◽  
pp. 06056
Author(s):  
Kuo-Tsang Huang ◽  
Yu-Teng Weng ◽  
Ruey-Lung Hwang

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.


2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.


Author(s):  
Dao Nguyen Khoi ◽  
Truong Thao Sam ◽  
Pham Thi Loi ◽  
Bui Viet Hung ◽  
Van Thinh Nguyen

Abstract In this paper, the responses of hydro-meteorological drought to changing climate in the Be River Basin located in Southern Vietnam are investigated. Climate change scenarios for the study area were statistically downscaled using the Long Ashton Research Station Weather Generator tool, which incorporates climate projections from Coupled Model Intercomparison Project 5 (CMIP5) based on an ensemble of five general circulation models (Can-ESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). The Soil and Water Assessment Tool model was employed to simulate streamflow for the baseline time period and three consecutive future 20 year periods of 2030s (2021–2040), 2050s (2041–2060), and 2070s (2061–2080). Based on the simulation results, the Standardized Precipitation Index and Standardized Discharge Index were estimated to evaluate the features of hydro-meteorological droughts. The hydrological drought has 1-month lag time from the meteorological drought and the hydro-meteorological droughts have negative correlations with the El Niño Southern Oscillation and Pacific Decadal Oscillation. Under the climate changing impacts, the trends of drought severity will decrease in the future; while the trends of drought frequency will increase in the near future period (2030s), but decrease in the following future periods (2050 and 2070s). The findings of this study can provide useful information to the policy and decisionmakers for a better future planning and management of water resources in the study region.


2012 ◽  
Vol 12 (6) ◽  
pp. 13827-13880
Author(s):  
R. D. Field ◽  
C. Risi ◽  
G. A. Schmidt ◽  
J. Worden ◽  
A. Voulgarakis ◽  
...  

Abstract. Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the modeled meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, "categorical" approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and modeled meteorology at short time scales. To test this approach, nudged simulations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the δD fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30‰ over the ocean and decreases of up to 40‰ over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had δD biases of −8‰ over ocean and −34‰ over land compared to TES δD, which were less than the biases using raw modeled δD fields.


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