Building Asian climate change scenario by multi-regional climate models ensemble. Part II: mean precipitation

2016 ◽  
Vol 36 (13) ◽  
pp. 4253-4264 ◽  
Author(s):  
Qian Li ◽  
Shuyu Wang ◽  
Dong-Kyou Lee ◽  
Jianping Tang ◽  
Xiaorui Niu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Scenario ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Change Scenario

Building Asian climate change scenario by multi-regional climate models ensemble. Part I: surface air temperature

2016 ◽  
Vol 36 (13) ◽  
pp. 4241-4252 ◽  
Author(s):  
Jianping Tang ◽  
Qian Li ◽  
Shuyu Wang ◽  
Dong-Kyou Lee ◽  
Pinhong Hui ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Change Scenario ◽  
Climate Models ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Regional Climate Models ◽  
Change Scenario

scholarly journals An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Dongwoo Jang
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Circulation Model ◽  
Regional Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Precipitation Data ◽  
Simulated Precipitation

Climate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional climate models (RCMs) suitable for each country. In Korea, there are studies for improving the accuracy of climate change scenario precipitation forecasts compared with observed precipitation. In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. The ANN ensemble of RCMs simulates the actual observed precipitation more accurately than the individual RCM. In particular, it is more effective inland than in coastal areas, where precipitation patterns are complex. Pearson correlation coefficient of ANN is high as 0.04 compared with MRA. It is expected that more detailed analysis will be possible if it is applied not only to four cities but also to other regions in Korea. If observed precipitation data are collected in sufficient quantity, the applicability of the ANN model will widen.

Kriging Approach to Quantile Delta Mapping (QDM) for Spatial Downscaling of Climate Change Scenario

2020 ◽  
Author(s):  
Yong-Tak Kim ◽  
Carlos H R Lima ◽  
Hyun-Han Kwon
Keyword(s):  
Climate Change ◽  
Spatial Variability ◽  
Bias Correction ◽  
Climate Change Scenario ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Change Scenario ◽  
Proposed Model ◽  
Spatial Downscaling

<p>Rainfall simulation by climate model is generally provided at coarse grids and bias correction is routinely needed for the hydrological applications. This study aims to explore an alternative approach to downscale daily rainfall simulated by the regional climate model (RCM) at any desired grid resolution along with bias correction using a Kriging model, which better represents spatial dependencies of distribution parameters across the watershed. The Kringing model also aims to reproduce the spatial variability observed in the ground rainfall gauge. The proposed model is validated through the entire weather stations in South Korea and climate change scenarios simulated by the five different RCMs informed by two GCMs. The results confirmed that the proposed spatial downscaling model could reproduce the observed rainfall statistics and spatial variability of rainfall. The proposed model further applied to the climate change scenario. A discussion of the potential uses of the mode is offered.</p><p>KEYWORDS: Climate Change Scenario, Global Climate Models, Regional Climate Models, Statistical Downscaling, Spatial-Temporal Bias</p><p> </p><p>Acknowledgement</p><p>This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI(KMI2018-01215)</p>

Reproduction and projection of sea level around Korean Peninsula using regional climate ocean model with dynamical downscaling method

2020 ◽  
Author(s):  
Kwang-Young Jeong ◽  
Eunil Lee ◽  
Do-Seong Byun ◽  
Gwang-Ho Seo ◽  
Hwa-Young Lee ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
Korean Peninsula ◽  
Climate Change Scenario ◽  
Climate Models ◽  
Regional Climate ◽  
Ocean Model ◽  
Global Ocean ◽  
Change Scenario

<p>Recently, the rate of sea level rise in accelerating with time, and many studies have reported that sea level will increase rapidly in the near future. Also, various global ocean climate models are used to predict sea level rise due to global warming. However, most global ocean climate models have low resolutions, so it is hard to explain detailed the ocean phenomena such as sea level and currents around Korean Peninsula. This study aims to past 30-year reproduce and future 100-year predict for rising trend of sea level using Regional Climate Ocean Model (RCOM) with ROMS according to IPCC climate change scenario (RCP 4.5).</p><p>The RCOM with high resolution of 1/20° horizontally and 40 layers vertically has been established for reproduction and long term forecast of sea-level rise in the Northwest Pacific, including marginal seas around Korea. Dynamic downscaling processes using result of the global climate models were applied to the open boundary conditions of our RCOM. To prepare the optimal boundary data for RCOM, the CMIP5 climate model was evaluated to select 4 climate models: IPSL-CM5A-LR, and -MR, NorESM1-M, MPI-ESM-LR.</p><p>Based on the RCOM results of 4 experiments, the rate of sea level rise for IPCC climate change scenario (RCP4.5) around Korean peninsula were 2.52, 2.21, 3.11, 3.36 mm/yr for the last 30 years (1976~2005), and 5.17, 4.99, 5.62, 5.42 mm/yr for the next 100 years (2006~2100), respectively. Ensemble mean value of next 100 years for 4 model results was 5.30 mm/yr. The sea level rise of 4 models for RCP 4.5 were 48, 48, 58, 48 cm for next 100 years, respectively, and ensemble mean value of 4 models was 50 cm during 2006~2100.</p><p>Future studies will focus on predicting the next 100 years of sea level change based on IPCC climate change scenario (RCP2.6, 8.5).</p><p> </p>

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

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.

Optimized planning and operation of interconnected multi-purpose reservoir systems using integrated modeling for climate change adaptation

2021 ◽  
Author(s):  
Patrick Nistahl ◽  
Tim Müller ◽  
Gerhard Riedel ◽  
Hannes Müller-Thomy ◽  
Günter Meon
Keyword(s):  
Climate Change ◽  
Reservoir Operation ◽  
Climate Models ◽  
Hydrological Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Flood Protection ◽  
Performance Criteria ◽  
Low Flow ◽  
Operation Model

&lt;p&gt;Climate change impact studies performed for Northern Germany indicate a growing demand for water storage capacity to account for flood protection, low flow augmentation, drinking and agricultural water supply. At the same time, larger storage volumes for hydropower plants can be used to cope with the demands of changing energy supply from fossil to renewable energies. To tackle these challenges for the next decades, a novel reservoir system planning instrument is developed, which consists of combined numerical models and evaluation components. It allows to model simultaneously the current interconnected infrastructure of reservoirs as well as additional planning variants (structural and operational) as preparation for climate change. This planning instrument consists of a hydrological model and a detailed reservoir operation model.&lt;/p&gt;&lt;p&gt;As hydrological model, the conceptual, semi-distributed version of PANTA RHEI is applied. &amp;#160;Bias-corrected regional climate models (based on the RCP 8.5 scenario) are used as meteorological input. The hydrological model is coupled with a detailed reservoir operation model that replicates the complex rules of various interconnected reservoirs based on an hourly time step including pumped storage plants, which may have a subsurface reservoir as a lower basin. Downstream of the reservoirs, the hydrological model is used for routing the reservoir outflows and simulating natural side inflows. In areas of particular interest for flood protection, the hydrological routing is substituted with 2D hydraulic models to calculate the flood risk in terms of expected annual flood damage based on resulting inundation areas.&lt;/p&gt;&lt;p&gt;For the performance analysis, the simulation runs for all integrated modeling variants are evaluated for a reference period (1971-2000) and for future periods (2041-2070). Performance criteria involve flood protection, drinking water supply, low flow augmentation and energy production. These performance criteria will be used as stake holder information as well as a base for further optimization and ranking of the planning variants.&lt;/p&gt;&lt;p&gt;The combination of the hydrological model and the reservoir operation model shows a good performance of the existing complex hydraulic infrastructure using observed meteorological forcing as input. The usage of regional climate models as input shows a wide dispersion of several performance criteria, confirming the expected need for an innovative optimization scheme and the communication of the underlying uncertainties.&lt;/p&gt;

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

The role of conceptual hydrologic model calibration in climate change impact on water resources assessment

2015 ◽  
Vol 7 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Andrijana Todorovic ◽  
Jasna Plavsic
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
High Sensitivity ◽  
Regional Climate Models ◽  
Baseline Period ◽  
Hydrologic Model ◽  
Calibration Period ◽  
Rainfall Runoff Model ◽  
Parameter Values

Assessment of climate change (CC) impact on hydrologic regime requires a calibrated rainfall-runoff model, defined by its structure and parameters. The parameter values depend, inter alia, on the calibration period. This paper investigates influence of the calibration period on parameter values, model efficiency and streamflow projections under CC. To this end, a conceptual HBV-light model of the Kolubara River catchment in Serbia is calibrated against flows observed within 5 consecutive wettest, driest, warmest and coldest years and in the complete record period. The optimised parameters reveal high sensitivity towards calibration period. Hydrologic projections under climate change are developed by employing (1) five hydrologic models with outputs of one GCM–RCM chain (Global and Regional Climate Models) and (2) one hydrologic model with five GCM–RCM outputs. Sign and magnitude of change in projected variables, compared to the corresponding values simulated over the baseline period, vary with the hydrologic model used. This variability is comparable in magnitude to variability stemming from climate models. Models calibrated over periods with similar precipitation as the projected ones may result in less uncertain projections, while warmer climate is not expected to contribute to the uncertainty in flow projections. Simulations over prolonged dry periods are expected to be uncertain.

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