scholarly journals Asymmetric Expansion of Summer Season on May and September in Korea

2020 ◽  
Author(s):  
Chang-Hoi Ho ◽  
Chang-Kyun Park ◽  
Jeongmin Yun ◽  
Eun-Ju Lee ◽  
Jinwon Kim ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Warming Trend ◽  
Summer Season ◽  
Positive Trend ◽  
Grid Data ◽  
Surface Warming

Abstract Global warming and its associated changes in the timing of seasonal progression may produce substantial ripple effects on the regional climate and ecosystem. This study analyzes the surface air temperature recorded during the period 1919–2017 at seven stations in the Republic of Korea to investigate the long-term changes at the beginning and ending of the summer season and their relationship with the warming trends of spring and autumn. The temperatures at the starting (June 1) and ending (August 31) dates of the past period (1919–1948) advanced by 13 days and delayed by 4 days, respectively, for the recent period (1988–2017). This asymmetric change was caused by continuous warming in May for the entire period of analysis and an abrupt warming in September in the recent decades. Different amplitudes of the expansion of the western North Pacific subtropical high in May and September are responsible for the asymmetric expansion of the summer season. The projections of surface warming for spring and autumn in Korea used the downscaled grid data of a regional climate model, which were obtained by the Representative Concentration Pathway 8.5 scenario of a general circulation model, and indicated a continuous positive trend until 2100. Larger interannual variability of blooming timing of early autumn flowers than that of late spring flowers may represent the response of the ecosystem to the seasonally asymmetric surface warming. Results suggest that the shift of seasons and associated warming trend have a disturbing effect on an ecosystem, and this trend will intensify in the future.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Applying an isotope-enabled regional climate model over the Greenland ice sheet: effect of spatial resolution on model bias

2021 ◽  
Vol 17 (4) ◽  
pp. 1685-1699
Author(s):  
Marcus Breil ◽  
Emanuel Christner ◽  
Alexandre Cauquoin ◽  
Martin Werner ◽  
Melanie Karremann ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Ice Cores ◽  
Arctic Region ◽  
The Arctic ◽  
Simulation Results ◽  
The Arctic Region

Abstract. In order to investigate the impact of spatial resolution on the discrepancy between simulated δ18O and observed δ18O in Greenland ice cores, regional climate simulations are performed with the isotope-enabled regional climate model (RCM) COSMO_iso. For this purpose, isotope-enabled general circulation model (GCM) simulations with the ECHAM5-wiso general circulation model (GCM) under present-day conditions and the MPI-ESM-wiso GCM under mid-Holocene conditions are dynamically downscaled with COSMO_iso for the Arctic region. The capability of COSMO_iso to reproduce observed isotopic ratios in Greenland ice cores for these two periods is investigated by comparing the simulation results to measured δ18O ratios from snow pit samples, Global Network of Isotopes in Precipitation (GNIP) stations and ice cores. To our knowledge, this is the first time that a mid-Holocene isotope-enabled RCM simulation is performed for the Arctic region. Under present-day conditions, a dynamical downscaling of ECHAM5-wiso (1.1∘×1.1∘) with COSMO_iso to a spatial resolution of 50 km improves the agreement with the measured δ18O ratios for 14 of 19 observational data sets. A further increase in the spatial resolution to 7 km does not yield substantial improvements except for the coastal areas with its complex terrain. For the mid-Holocene, a fully coupled MPI-ESM-wiso time slice simulation is downscaled with COSMO_iso to a spatial resolution of 50 km. In the mid-Holocene, MPI-ESM-wiso already agrees well with observations in Greenland and a downscaling with COSMO_iso does not further improve the model–data agreement. Despite this lack of improvement in model biases, the study shows that in both periods, observed δ18O values at measurement sites constitute isotope ratios which are mainly within the subgrid-scale variability of the global ECHAM5-wiso and MPI-ESM-wiso simulation results. The correct δ18O ratios are consequently not resolved in the GCM simulation results and need to be extracted by a refinement with an RCM. In this context, the RCM simulations provide a spatial δ18O distribution by which the effects of local uncertainties can be taken into account in the comparison between point measurements and model outputs. Thus, an isotope-enabled GCM–RCM model chain with realistically implemented fractionating processes constitutes a useful supplement to reconstruct regional paleo-climate conditions during the mid-Holocene in Greenland. Such model chains might also be applied to reveal the full potential of GCMs in other regions and climate periods, in which large deviations relative to observed isotope ratios are simulated.

scholarly journals Sensitivity of Pliocene climate simulations in MRI-CGCM2.3 to respective boundary conditions

2016 ◽  
Vol 12 (8) ◽  
pp. 1619-1634 ◽  
Author(s):  
Youichi Kamae ◽  
Kohei Yoshida ◽  
Hiroaki Ueda
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Model Comparison ◽  
Climate Model ◽  
Phase 1 ◽  
Regional Climate ◽  
Circulation Model ◽  
Poleward Heat Transport ◽  
Climate Simulations ◽  
Intercomparison Project

Abstract. Accumulations of global proxy data are essential steps for improving reliability of climate model simulations for the Pliocene warming climate. In the Pliocene Model Intercomparison Project phase 2 (PlioMIP2), a part project of the Paleoclimate Modelling Intercomparison Project phase 4, boundary forcing data have been updated from the PlioMIP phase 1 due to recent advances in understanding of oceanic, terrestrial and cryospheric aspects of the Pliocene palaeoenvironment. In this study, sensitivities of Pliocene climate simulations to the newly archived boundary conditions are evaluated by a set of simulations using an atmosphere–ocean coupled general circulation model, MRI-CGCM2.3. The simulated Pliocene climate is warmer than pre-industrial conditions for 2.4 °C in global mean, corresponding to 0.6 °C warmer than the PlioMIP1 simulation by the identical climate model. Revised orography, lakes, and shrunk ice sheets compared with the PlioMIP1 lead to local and remote influences including snow and sea ice albedo feedback, and poleward heat transport due to the atmosphere and ocean that result in additional warming over middle and high latitudes. The amplified higher-latitude warming is supported qualitatively by the proxy evidences, but is still underestimated quantitatively. Physical processes responsible for the global and regional climate changes should be further addressed in future studies under systematic intermodel and data–model comparison frameworks.

Atlantic Atmosphere–Ocean Interaction: A Stochastic Climate Model–Based Diagnosis

2005 ◽  
Vol 18 (7) ◽  
pp. 1086-1095 ◽  
Author(s):  
Timothy J. Mosedale ◽  
David B. Stephenson ◽  
Matthew Collins
Keyword(s):  
Simple Model ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Daily Data ◽  
Stochastic Climate Model ◽  
Fully Coupled ◽  
Northeastern Atlantic

Abstract A simple linear stochastic climate model of extratropical wintertime ocean–atmosphere coupling is used to diagnose the daily interactions between the ocean and the atmosphere in a fully coupled general circulation model. Monte Carlo simulations with the simple model show that the influence of the ocean on the atmosphere can be difficult to estimate, being biased low even with multiple decades of daily data. Despite this, fitting the simple model to the surface air temperature and sea surface temperature data from the complex general circulation model reveals an ocean-to-atmosphere influence in the northeastern Atlantic. Furthermore, the simple model is used to demonstrate that the ocean in this region greatly enhances the autocorrelation in overlying lower-tropospheric temperatures at lags from a few days to many months.

scholarly journals Estimation of discharge from Langtang River basin, Rasuwa, Nepal, using a glacio-hydrological model

2014 ◽  
Vol 55 (66) ◽  
pp. 223-230 ◽  
Author(s):  
Niraj S. Pradhananga ◽  
Rijan B. Kayastha ◽  
Bikas C. Bhattarai ◽  
Tirtha R. Adhikari ◽  
Suresh C. Pradhan ◽  
...  
Keyword(s):  
River Basin ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Glacier Area ◽  
Monsoon Period ◽  
Ice Melt ◽  
The Future ◽  
Total Discharge

AbstractThis paper provides the results of semi-distributed positive degree-day (PDD) modelling for a glacierized river basin in Nepal. The main objective is to estimate the present and future discharge from the glacierized Langtang River basin using a PDD model (PDDM). The PDDM is calibrated for the period 1993–98 and is validated for the period 1999–2006 with Nash–Sutcliffe values of 0.85 and 0.80, respectively. Furthermore, the projected precipitation and temperature data from 2010 to 2050 are obtained from the Bjerknes Centre for Climate Research, Norway, for the representative concentration pathway 4.5 (RCP4.5) scenario. The Weather Research and Forecasting regional climate model is used to downscale the data from the Norwegian Earth System Model general circulation model. Projected discharge shows no significant trend, but in the future during the pre-monsoon period, discharge will be high and the peak discharge will be in July whereas it is in August at present. The contribution of snow and ice melt from glaciers and snowmelt from rocks and vegetation will decrease in the future: in 2040–50 it will be just 50% of the total discharge. The PDDM is sensitive to monthly average temperature, as a 2°C temperature increase will increase the discharge by 31.9%. Changes in glacier area are less sensitive, as glacier area decreases of 25% and 50% result in a change in the total discharge of –5.7% and –11.4%, respectively.

scholarly journals Addressing the Issue of Systematic Errors in a Regional Climate Model

2007 ◽  
Vol 20 (5) ◽  
pp. 801-818 ◽  
Author(s):  
Vasubandhu Misra
Keyword(s):  
Regional Climate Model ◽  
Bias Correction ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Systematic Errors ◽  
Driver Model ◽  
South American ◽  
Driving Model

Abstract A methodology is proposed in which a few prognostic variables of a regional climate model (RCM) are strongly constrained at certain wavelengths to what is prescribed from the bias-corrected atmospheric general circulation model (AGCM; driver model) integrations. The goal of this strategy is to reduce the systematic errors in a RCM that mainly arise from two sources: the lateral boundary conditions and the RCM errors. Bias correction (which essentially corrects the climatology) of the forcing from the driving model addresses the former source while constraining the solution of the RCM beyond certain relatively large wavelengths in the regional domain [also termed as scale-selective bias correction (SSBC)] addresses the latter source of systematic errors in RCM. This methodology is applied to experiments over the South American monsoon region. It is found that the combination of bias correction and SSBC on the nested variables of divergence, vorticity, and the log of surface pressure of an RCM yields a major improvement in the simulation of the regional climate variability over South America from interannual to intraseasonal time scales. The basis for such a strategy is derived from a systematic empirical approach that involved over 100 regional seasonal climate integrations.

scholarly journals PALEO-PGEM v1.0: a statistical emulator of Pliocene–Pleistocene climate

2019 ◽  
Vol 12 (12) ◽  
pp. 5137-5155 ◽  
Author(s):  
Philip B. Holden ◽  
Neil R. Edwards ◽  
Thiago F. Rangel ◽  
Elisa B. Pereira ◽  
Giang T. Tran ◽  
...  
Keyword(s):  
High Resolution ◽  
General Circulation ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Time Frame ◽  
Quasi Equilibrium ◽  
Bioclimatic Variables ◽  
Spatio Temporal ◽  
Value Decomposition

Abstract. We describe the development of the “Paleoclimate PLASIM-GENIE (Planet Simulator–Grid-Enabled Integrated Earth system model) emulator” PALEO-PGEM and its application to derive a downscaled high-resolution spatio-temporal description of the climate of the last 5×106 years. The 5×106-year time frame is interesting for a range of paleo-environmental questions, not least because it encompasses the evolution of humans. However, the choice of time frame was primarily pragmatic; tectonic changes can be neglected to first order, so that it is reasonable to consider climate forcing restricted to the Earth's orbital configuration, ice-sheet state, and the concentration of atmosphere CO2. The approach uses the Gaussian process emulation of the singular value decomposition of ensembles of the intermediate-complexity atmosphere–ocean GCM (general circulation model) PLASIM-GENIE. Spatial fields of bioclimatic variables of surface air temperature (warmest and coolest seasons) and precipitation (wettest and driest seasons) are emulated at 1000-year intervals, driven by time series of scalar boundary-condition forcing (CO2, orbit, and ice volume) and assuming the climate is in quasi-equilibrium. Paleoclimate anomalies at climate model resolution are interpolated onto the observed modern climatology to produce a high-resolution spatio-temporal paleoclimate reconstruction of the Pliocene–Pleistocene.

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