Search

GCM ensembles indicate that the October 2021 South Korean heatwave was extremely unlikely to occur without human influences, which corresponds to 2060s’ new normal without ambitious greenhouse gas mitigation.

Severe spatiotemporal heterogeneity of emissions sources and limited measurement networks have been hampering the monitoring and understanding of CO2 fluxes in large cities, a great concern in climate research as big cities are among the major sources of anthropogenic CO2 in the climate system. To understand the CO2 fluxes in Seoul, Korea, CO2 fluxes at eight surface energy balance sites, six urban (vegetation-area fraction 60%), for 2017–2018 are analyzed and attributed to the local land-use and business types. The analyses show that the CO2 flux variations at the suburban sites are mainly driven by vegetation and that the CO2 flux differences between the urban and suburban sites originate from the differences in the vegetation-area fraction and anthropogenic CO2 emissions. For the CO2 fluxes at the urban sites; (1) vehicle traffic (traffic) and heating-fuel consumption (heating) contribute > 80% to the total, (2) vegetation effects are minimal, (3) the seasonal cycle is driven mainly by heating, (4) the contribution of heating is positively related to the building-area fraction, (5) the annual total is positively (negatively) correlated with the commercial-area (residential-area) fraction, and (6) the traffic at the commercial sites depend further on the main business types to induce distinct CO2 flux weekly cycles. This study shows that understanding and estimation of CO2 fluxes in large urban areas require careful site selections and analyses based on detailed consideration of the land-use and business types refined beyond the single representative land-use type widely-used in contemporary studies.

Hadley circulation (HC) is a planetary-scale overturning circulation in the tropics that transports momentum, heat, and moisture poleward. In this study, we evaluate the strength and extent of the HC in the historical and future climate simulations of the Korean Meteorological Administration (KMA) Advanced Community Earth system model (K-ACE), which was recently developed by the National Institute of Meteorological Sciences of Korea. Compared with a reanalysis product, the overall structure of the HC is reasonably reproduced by the K-ACE. At the same time, it is also found that the Northern Hemisphere HC in the K-ACE is shifted southward by a few degrees, while the strength of the Southern Hemisphere (SH) HC is under-represented by approximately 20%. These biases in the strength and extent of the HC can be explained by biases in the eddy momentum flux and precipitation in the tropics. In the future climate simulations under the Shared Socioeconomic Pathway 5-Representative Concentration Pathway 8.5 scenario, the HCs in the K-ACE show a weakening and widening trend in both hemispheres, which is consistent with the projections of many Coupled Model Intercomparison Project Phase 6 models. A notable feature of the K-ACE is the widening of the SH HC, which takes place at a rate that is about double the multi-model mean. Climate models that share the component models with the K-ACE, such as UKESM, HadGEM3-GC31-LL, and ACCESS-CM2/ESM1, also show enhanced poleward expansion of the HC in the SH. This strong expansion is shown to be dominated by the expansion of the regional HC over the Pacific.

Earth system models (ESMs) comprise various Earth system components and simulate the interactions between these components. ESMs can be used to understand climate feedbacks between physical, chemical, and biological processes and predict future climate. We developed a new ESM, UKESM-TOPAZ, by coupling the UK ESM (UKESM1) and the Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) biogeochemical module. We then compared the preliminary simulated biogeochemical variables, which were conducted over a period of 70 years, using observational and existing UKESM1 model data. Similar to UKESM1, the newly developed UKESM-TOPAZ closely simulated the relationship between the El Niño-Southern Oscillation and chlorophyll concentration anomalies during the boreal winter. However, there were differences in the chlorophyll distributions in the eastern equatorial Pacific between the two models, which were due to dissolved iron, as this value was higher in UKESM-TOPAZ than in UKESM1. In a mean field analysis, the distributions of the major marine biogeochemical variables in UKESM-TOPAZ (i.e., nitrate, silicate, dissolved oxygen, dissolved inorganic carbon, and alkalinity) were not significantly different from those of UKESM1, likely because the models share the same initial conditions. Our results indicate that TOPAZ has a simulation performance that does not lag behind UKESM1’s basic biogeochemical model (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification; MEDUSA). The UKESM-TOPAZ model can simulate the variability of the observed Niño 3.4 and 4 indices more closely than UKESM1. Thus, the UKESM-TOPAZ model can be used to deepen our understanding of the Earth system and to estimate ESM uncertainty.

The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

This study evaluated tropical cyclone (TC) activity simulated by two regional climate models (RCMs) incorporated in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework with two different horizontal resolutions. Evaluation experiments with two RCMs (RegCM4 and MM5) forced by reanalysis data were conducted over the CORDEX-East Asia domain for phases I and II. The main difference between phases I and II is horizontal resolution (50 and 25 km). The 20-yr (1989–2008) mean performances of the experiments were investigated in terms of TC genesis, track, intensity, and TC-induced precipitation. In general, the simulated TC activities over the western North Pacific (WNP) varied depending on the model type and horizontal resolution. For both models, higher horizontal resolution improved the simulation of TC tracks near the coastal regions of East Asia, whereas the coarser horizontal resolution led to underestimated TC genesis compared with the best track data because of greater convective precipitation and enhanced atmospheric stabilization. In addition, the increased horizontal resolution prominently improved the simulation of TCs landfalling in East Asia and associated precipitation around coastal regions. This finding implies that high-resolution RCMs can improve the simulation of TC activities over the WNP (i.e., added value by increasing model resolution); thus, they have an advantage in climate change assessment studies.

In this study, the regional climate of East Asia was dynamically downscaled using Hadley Centre Global Environmental Model version 3-Regional Atmosphere (HadGEM3-RA) forced by the historical simulation data (1979–2005) of HadGEM2-AO produced by the National Institute of Meteorological Sciences (NIMS). To understand the impact of corrected SST on regional climate simulation, we integrated the experiments using uncorrected (UC_SST) and Bias- and Variance-corrected (BCVC_SST) HadGEM2-AO SST and used the simulated data driven by the ERA-Interim reanalysis data and HadGEM2-AO data. Examination of the spatial distribution, statistics, and interannual variation on wintertime precipitation over East Asia indicates that BCVC_SST reduced the overestimation of the climatological mean precipitation. In order to understand the impact of corrected SST on variability, we investigated the relationship between winter snowfall in South Korea and SST over East Asia. The negative correlation coefficient between the winter precipitation and the SST of the seas surrounding Korea appears in the result of observation data. The experiment result using BCVC_SST simulated the negative correlation between the winter snowfall and the SST around Korea more realistically than that of the simulations using UC_SST and HadGEM2-AO data. These results indicate that corrected SST helps to improve the variability of snowfall and SST simulated by HadGEM3-RA. However, time lag about the years when had peak point of SST appeared in the results compared between BCVC_SST experiment and observation data. The peak years shown in the result of the BCVC_SST experiment were similar to that of HadGEM2-AO data. At these results, even though the corrected SST improves climatological mean and variability of simulated data, it has the limitation not to overcome the error such as time lag showed in GCM SST. Additionally, the analysis of the snowfall in South Korea describes that SST is passively used for the source of snowfall and atmospheric variables mainly lead the intensity and the amount of snowfall.

Potential intensity (PI) is a metric for climate model evaluation of TC-related thermodynamic conditions. However, PI is utilized usually for assessing basin-wide TC-related thermodynamic conditions, and not for evaluating TC passage to a certain region. Here we evaluate model-simulated PI over the passage of TCs affecting South Korea (KOR PI) as well as the PI over the entire western North Pacific basin (WNP PI) using 25 CMIP5 and 27 CMIP6 models. In terms of pattern correlations and bias-removed root mean square errors, CMIP6 model performances for KOR PI are found to be noticeably improved over CMIP5 models in contrast to negligible improvement for WNP PI, although it is not in terms of normalized standard deviations. This implies that thermodynamic condition on the route of TCs affecting South Korea is likely better captured by CMIP6 models than CMIP5 models.

Earth System Models (ESMs) simulating the interrelationship between atmospheric chemistry, ocean biogeochemistry, terrestrial ecology, and climate processes are used to understand current climate and predict future climate change. However, ocean biogeochemical results show wide variability between ESMs. We have implemented the Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) ocean biogeochemistry model into the National Institute of Meteorological Sciences ESM. The offline version (Nucleus for European Modelling of the Ocean – Tracers of Ocean Phytoplankton with Allometric Zooplankton v2 (NEMO-TOPAZ) of the coupled global ocean biogeochemistry model has been evaluated compared to both observational data and another biogeochemistry model (NEMO-Pelagic Interactions Scheme for Carbon and Ecosystem Studies volume 2 [PISCES]) with the same ocean physics model. Biogeochemical tracers simulated by these models showed horizontal and vertical spatial distributions similar to observations. However, limitations caused by the shared ocean physical model were found in both models. While NEMO-TOPAZ tended to overestimate surface chlorophyll and nutrients, variation of simulated equatorial surface chlorophyll has a significant relationship with the El Nino-Southern Oscillation (ENSO) consistent with the observational result. NEMO-TOPAZ achieved superior simulation of dissolved inorganic carbon and alkalinity along with vertical distributions of biogeochemical variables in the Pacific and Atlantic Oceans. For nutrients, NEMO-PISCES showed better results overall. This model will improve scientific understanding of ocean biogeochemical processes and can be used in combination with other models for other components of the Earth’s system to develop a new ESM.

Scientific community has been elaborating to better understand the observed climate and its variations, and to improve the capability for predicting future climate. Many modeling groups participating in the Coupled Model Inter-comparison Project (CMIP) have been working towards multi-model ensemble approach that have become a standard technique for projecting future climate and for assessing associated uncertainties to deal with intrinsic shortcomings of climate models. Within this context, the National Institute of Meteorological Sciences/Korea Meteorological Administration (NIMS/KMA) has developed the KMA Advanced Community Earth-system model (K-ACE) under KMA-Met Office collaboration for climate research. This paper provides general descriptions of the first generation K-ACE model including the coupling strategy, as well as preliminary evaluations of the model performance in mean climate fields. The first generation K-ACE model appears to capture the mean climatology and the inter-annual variability of the observed climate. Horizontal distributions and the variability of the surface and pressure-level variables agree well with observations with correlation coefficients of 0.88–0.99 and 0.69–0.99, respectively. Measured in terms of performance index between the observed and simulated fields, the K-ACE performance is comparable with those of 29 CMIP5 models. This study also identifies key weaknesses of the K-ACE in the present-day climate. Improving these deficiencies will be a topic of future studies. The NIMS/KMA will employ the K-ACE model to contribute to the CMIP6 experiment.

The CarbonTracker (CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model’s performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within −0.3 and 1.3 ppm, except for inland stations (7.7 ppm).

It is evident that evaluating the measurement of greenhouse gases (GHGs) obtained from multi-platform instruments against accurate and precise instrument such as aircraft in-situ is very essential when using remote sensing GHGs results for source/sink estimations with inverse modeling. The results of the inverse models are very sensitive even to small biases in the data (Rayner and O’Brien 2001). In this work, we have evaluated ground-based high resolution Fourier Transform Spectrometer (g-b FTS) and the Greenhouse gases Observing SATellite (GOSAT) column-averaged dry air mole fraction of methane (XCH4) through aircraft in-situ observations over Anmyeondo station (36.538o N, 126.331o E, 30 m above sea level). The impact of the spatial coincidence criteria was assessed by comparing GOSAT data against g-b FTS. We noticed there was no any systematic difference based on the given coincidence criteria. GOSAT exhibited a bias ranging from 0.10 to 3.37 ppb, with the standard deviation from 4.92 to 12.54 ppb, against g-b FTS with the spatial coincidence criteria of ±1, ±3, ±5 degrees of latitude and longitude and ± 1 h time window. Data observed during ascent and descent of the aircraft is considered as vertical profiles within an altitude range of 0.2 to a maximum of 9.0 km so that some assumptions were applied for the construction of the profiles below 0.2 and above 9.0 km. In addition, the suitability of aircraft data for evaluation of remote sensing instruments was confirmed based on the assessment of uncertainties. The spatial coincidence criteria is ±1o latitude and ± 2o longitude and for temporal difference is ±1 h of the satellite observation overpass time were applied, whereas g-b FTS data are the mean values measured within ±30 min of the aircraft observation time. Furthermore, the sensitivity differences of the instruments were taken into account. With respect to aircraft, the g-b FTS data were biased by −0.19 ± 0.69%, while GOSAT data were biased by −0.42 ± 0.84%. These results confirm that both g-b FTS and GOSAT are consistent aircraft observations and assure the reliability of the datasets for inverse estimate of CH4.

In recent decades, extremely cold winters have occurred repeatedly throughout the Northern Hemisphere, including the Korean Peninsula (hereafter, Korea). Typically, cold winter temperatures in Korea can be linked to the strengthening of the Siberian High (SH). Although previous studies have investigated the typical relationship between the SH and winter temperatures in Korea, this study uniquely focused on a change in the relationship, which reflects the influence of the Arctic Oscillation (AO) and El Niño–Southern Oscillation (ENSO). A significant change in the 15-year moving correlation between the SH and the surface air temperature average in Korea (K-tas) was observed in January. The correlation changed from −0.80 during 1971–1990 to −0.16 during 1991–2010. The mean sea-level pressure pattern regressed with the temperature, and a singular value decomposition analysis that incorporated the temperature and pressure supports that the negative high correlation during 1971–1990 was largely affected by AO. This connection with AO is substantiated by empirical orthogonal function (EOF) analysis with an upper-level geopotential height at 300 hPa. In the second mode of the EOF, the temperature and pressure patterns were primarily affected by ENSO during 1991–2010. Consequently, the interdecadal change in correlation between K-tas and the SH in January can be attributed to the dominant effect of AO from 1971–1990 and of ENSO from 1991–2010. Our results suggest that the relative importance of these factors in terms of the January climate in Korea has changed on a multidecadal scale.

Understanding the response of the Earth system to CO2 removal (CDR) is crucial because the possibility of irreversibility exists. Therefore, the Carbon Dioxide Removal Model Inter-comparison Project (CDRMIP) for the protocol experiment in the Coupled Model Inter-comparison Project Phase 6 (CMIP6) has been developed. Our analysis focuses on the regional response in the hydrological cycle, especially in East Asia (EA). The peak temperature changes in EA (5.9 K) and the Korean peninsula (KO) (6.1 K) are larger than the global mean surface air temperature (GSAT) response. The precipitation changes are approximately 9.4% (EA) and 23.2% (KO) at the phase change time (130&ndash, 150 years), however, the largest increase is approximately 16.6% (EA) and 36.5% (KO) in the ramp-down period (150&ndash, 160 years). In addition, the differences are below 5 mm/day and 1 day for the precipitation intensity indices (Rx1day and Rx5day) and frequency indices (R95 and R99), respectively. Furthermore, the monsoon rainband of the ramp-down period moves northward as the earlier onset with high confidence compared to the ramp-up period, however, it does not move north to the KO region. The results suggest that reducing CO2 moves the rainband southward. However, a detailed interpretation in terms of the mechanism needs to be carried out in further research.

The effects of the emissions of anthropogenic greenhouse gases (GHGs), aerosols, and natural forcing on the summer-mean surface air temperature (TAS) in the East Asia (EA) land surface in the 20th century are analyzed using six-member coupled model inter-comparison project 5 (CMIP5) general circulation model (GCM) ensembles from five single-forcing simulations. The simulation with the observed GHG concentrations and aerosol emissions reproduces well the land-mean EA TAS trend characterized by warming periods in the early (1911&ndash, 1940, P1) and late (1971&ndash, 2000, P3) 20th century separated by a cooling period (1941&ndash, 1970, P2). The warming in P1 is mainly due to the natural variability related to GHG increases and the long-term recovery from volcanic activities in late-19th/early-20th century. The cooling in P2 occurs as the combined cooling by anthropogenic aerosols and increased volcanic eruptions in the 1960s exceeds the warming by the GHG increases and the nonlinear interaction term. In P3, the combined warming by GHGs and the interaction term exceeds the cooling by anthropogenic aerosols to result in the warming. The SW forcing is not driving the TAS increase in P1/P3 as the shortwave (SW) forcing is heavily affected by the increased cloudiness and the longwave (LW) forcing dominates the SW forcing. The LW forcing to TAS cannot be separated from the LW response to TAS, preventing further analyses. The interaction among these forcing affects TAS via largely modifying the atmospheric water cycle, especially in P2 and P3. Key forcing terms on TAS such as the temperature advection related to large-scale circulation changes cannot be analyzed due to the lack of model data.

Scientists occasionally predict projected changes in extreme climate using multi-model ensemble methods that combine predictions from individual simulation models. To predict future changes in precipitation extremes in the Korean peninsula, we examined the observed data and 21 models of the Coupled Model Inter-Comparison Project Phase 6 (CMIP6) over East Asia. We applied generalized extreme value distribution (GEVD) to a series of annual maximum daily precipitation (AMP1) data. Multivariate bias-corrected simulation data under three shared socioeconomic pathway (SSP) scenarios&mdash, namely, SSP2-4.5, SSP3-7.0, and SSP5-8.5&mdash, were used. We employed a model weighting method that accounts for both performance and independence (PI-weighting). In calculating the PI-weights, two shape parameters should be determined, but usually, a perfect model test method requires a considerable amount of computing time. To address this problem, we suggest simple ways for selecting two shape parameters based on the chi-square statistic and entropy. Variance decomposition was applied to quantify the uncertainty of projecting the future AMP1. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1973&ndash, 2010), were estimated for three overlapping periods in the future, namely, period 1 (2021&ndash, 2050), period 2 (2046&ndash, 2075), and period 3 (2071&ndash, 2100). From these analyses, we estimated that the relative increases in the observations for the spatial median 20-year return level will be approximately 18.4% in the SSP2-4.5, 25.9% in the SSP3-7.0, and 41.7% in the SSP5-8.5 scenarios, respectively, by the end of the 21st century. We predict that severe rainfall will be more prominent in the southern and central parts of the Korean peninsula.

Climate sensitivity and feedback processes are important for understanding Earth&rsquo, s system response to increased CO2 concentration in the atmosphere. Many modelling groups that contribute to Coupled Model Intercomparison Project phase 6 (CMIP6) have reported a larger equilibrium climate sensitivity (ECS) with their models compared to CMIP5 models. This consistent result is also found in the Korea Meteorological Administration Advanced Community Earth System model (K-ACE). Idealized climate simulation is conducted as an entry card for CMIP6 to understand Earth&rsquo, s system response in new coupled models and compared to CMIP5 models. The ECS in the K-ACE is 4.83 K, which is higher than the range (2.1&ndash, 4.7 K) of CMIP5 models in sensitivity to CO2 change and higher bound (1.8&ndash, 5.6 K) of CMIP6 models. The radiative feedback consists of clear-sky and cloud radiative feedback. Clear-sky feedback of K-ACE is similar to CMIP5 models whereas cloud feedback of K-ACE is more positive. The result is attributable for strong positive shortwave cloud radiative effect (CRE) feedback associated with reduced low-level cloud cover at mid latitude in both hemispheres. Despite the cancellations in strong negative long wave CRE feedback with the changes in high-level clouds in the tropics, shortwave CRE has a dominant effect in net CRE. Detailed understanding of cloud feedback and cloud properties needs further study.

This study analyzes the relationship between various atmospheric fields and the observed PM10 concentrations in the Seoul metropolitan area, South Korea, during the winters of the 2001&ndash, 2014 period to find suitable atmospheric indices for predicting high PM10 episodes in the region. The analysis shows that PM10 concentration in the metropolitan area is mainly affected by the intensity of horizontal ventilation and the 500 hPa high-pressure system over the Korean peninsula. The modified Korea particulate matter index (MKPI) is proposed based on a 10 m wind speed for surface ventilation and 500 hPa zonal wind for the intensity of a 500 hPa high-pressure system over the Korean peninsula. It is found that a positive MKPI value is closely correlated with the occurrence of high PM10 concentration episodes, and hence, can be used as a predictor for high PM10 episodes in the area. A future projection of the MKPI using two three-member general circulation model (GCM) ensembles with four shared socioeconomic pathway (SSP) scenarios in Coupled Model Intercomparison Project Phase 6 (CMIP6) shows that positive MKPI events and high PM10 episodes are expected to increase by 5.4%&minus, 16.4% depending on the SSP scenarios in the 2081&minus, 2100 period from the present-day period of 1995&minus, 2014.

The influence of aerosol emissions on North Pacific sea surface temperature (SST) variability during the twentieth century is investigated using a comparison between historical simulations with and without anthropogenic aerosol changes. The historical simulations using the Hadley Global Environment Model version 2 show that there is a common externally forced component in relation to the twentieth century North Pacific SST variability. This matches a number of important temporal and spatial characteristics of the observed multidecadal SST variability from the 1920s to 1990s, which is not found in experiments without aerosol changes. This paper explores both direct and indirect aerosol influences, and finds that in this model the aerosol-cloud interactions dominate the total aerosol forcing of the surface energy budget. These aerosol-cloud processes were not commonly included in most models in the previous (Coupled Model Intercomparison Project phase 3) generation, which may explain why the potential role of aerosols in Pacific variability has not been previously discussed. However, unlike recently reported aerosol drivers of Atlantic SST variability, the aerosol surface radiative forcing pattern does not map directly onto the historical spatial surface radiative and SST changes but is instead modulated by circulation changes to the Aleutian Low. These circulation changes share common features with previously reported studies of natural drivers of Pacific variability, suggesting that both forced and internally generated SST variability may be modulated via the same circulation response.

We present climate responses of Representative Concentration Pathways (RCPs) using the coupled climate model HadGEM2-AO for the Coupled Model Intercomparison Project phase 5 (CMIP5). The RCPs are selected as standard scenarios for the IPCC Fifth Assessment Report and these scenarios include time paths for emissions and concentrations of greenhouse gas and aerosols and land-use/land cover. The global average warming and precipitation increases for the last 20 years of the 21st century relative to the period 1986-2005 are +1.1°C/+2.1% for RCP2.6, +2.4°C/+4.0% for RCP4.5, +2.5°C/+3.3% for RCP6.0 and +4.1°C/+4.6% for RCP8.5, respectively. The climate response on RCP 2.6 scenario meets the UN Copenhagen Accord to limit global warming within two degrees at the end of 21st century, the mitigation effect is about 3°C between RCP2.6 and RCP8.5. The projected precipitation changes over the 21st century are expected to increase in tropical regions and at high latitudes, and decrease in subtropical regions associated with projected poleward expansions of the Hadley cell. Total soil moisture change is projected to decrease in northern hemisphere high latitudes and increase in central Africa and Asia whereas near-surface soil moisture tends to decrease in most areas according to the warming and evaporation increase. The trend and magnitude of future climate extremes are also projected to increase in proportion to radiative forcing of RCPs. For RCP 8.5, at the end of the summer season the Arctic is projected to be free of sea ice.

This paper investigates the effects of river discharge on simulated climatology from 1979 to 1988 using the Hadley Centre Global Environmental Model version 2. Two experiments are performed with and without the inclusion of Total Runoff Integrating Pathways. The results show that the inclusion of flow routing can lead to the decrease of salinity over the coastal region due to freshwater. This reduction results in a shallower mixed layer depth, which in turn leads to the weakening of trade winds and a decrease in vertical mixing in the ocean. The enhanced sensible and latent heat fluxes over warmed SST improve the simulated precipitation and thermodynamic circulation. As a result, the experiment with flow routing is capable of improving the large-scale climate feature with an increase in precipitation over the eastern tropical equatorial Pacific region.

In this paper, the intraseasonal oscillation (ISO) and its possible link to dynamical seasonal predictability within a general circulation model framework is investigated. Two experiments with different convection scheme algorithms, namely, the simplified Arakawa–Schubert (SAS) and the relaxed Arakawa–Schubert (RAS) convection algorithms, were designed to compare seasonal simulations from 1979 to 2002 on a seasonal model intercomparison project (SMIP)-type simulation test bed. Furthermore, the wave characteristics (wave intensity, period, and propagation) of the simulated ISO signal provided by the model with two different convection schemes for extended boreal summers from 1997 to 2004 were compared to the observational ISO signal. Precipitation in the boreal summer was fairly well simulated by the model irrespective of the convection scheme used, but the RAS run outperformed the SAS run with respect to tabulated skill scores. Decomposition of the interannual variability of boreal summer precipitation based on observations and model results demonstrates that the seasonal predictability of precipitation is dominated by the intraseasonal component over the warm pool area and the SST-forced signal over the equatorial Pacific Ocean, implying that the seasonal mean anomalies are more predictable under active ISO conditions as well as strong ENSO conditions. Comparison of the ISO simulations with the observations revealed that the main features, such as the intensity of precipitation variance in the intraseasonal time scale and the evolution of propagating ISOs, were reproduced fairly well by the model; however, the wave characteristics associated with the ISO signals were better captured by the experiment with the RAS scheme than the SAS scheme. This study further suggests that accurate simulation of the ISO can improve the seasonal predictability of dynamical seasonal prediction systems.

The purpose of this study is to investigate the effects of precipitation physics in a general circulation model (GCM) on a simulated climate. Experiments are performed under the single column model (SCM) framework to examine basic features and under the general circulation model framework to investigate the impact on seasonal simulation. The SCM simulation shows that convection processes in the model have a considerable influence on the change in vertical thermodynamic structure, resulting in a change in precipitation, whereas in the GCM framework stratiform precipitation physics play a distinct role in changing the atmospheric structure. The GCM experiments also show that the overall reduction of precipitation in simulations with prognostic stratiform precipitation physics is highly related to changes in cloudiness and corresponding changes in radiative flux, which in turn leads to the reduction of convective activities.

This study describes a revised approach for the subgrid-scale convective properties of a moist convection scheme in a global model and evaluates its effects on a simulated model climate. The subgrid-scale convective processes tested in this study comprise three components: 1) the random selection of cloud top, 2) the inclusion of convective momentum transport, and 3) a revised large-scale destabilization effect considering synoptic-scale forcing in the cumulus convection scheme of the National Centers for Environmental Prediction medium-range forecast model. Each component in the scheme has been evaluated within a single-column model (SCM) framework forced by the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment data. The impact of the changes in the scheme on seasonal predictions has been examined for the boreal summers of 1996, 1997, and 1999. In the SCM simulations, an experiment that includes all the modifications reproduces the typical convective heating and drying feature. The simulated surface rainfall is in good agreement with the observed precipitation. Random selection of the cloud top effectively moistens and cools the upper troposphere, and it induces drying and warming below the cloud-top level due to the cloud–radiation feedback. However, the two other components in the revised scheme do not play a significant role in the SCM simulations. On the other hand, the role of each modification component in the scheme is significant in the ensemble seasonal simulations. The random selection process of the cloud top preferentially plays an important role in the adjustment of the thermodynamic profile in a manner similar to that in the SCM framework. The inclusion of convective momentum transport in the scheme weakens the meridional circulation. The revised large-scale destabilization process plays an important role in the modulation of the meridional circulation when this process is combined with other processes; on the other hand, this process does not induce significant changes in large-scale fields by itself. Consequently, the experiment that involves all the modifications shows a significant improvement in the seasonal precipitation, thereby highlighting the importance of nonlinear interaction between the physical processes in the model and the simulated climate.

The impact of boundary layer (BL) processes on simulated tropical precipitation was studied using the National Centers for Environmental Prediction (NCEP) Medium-Range Forecast (MRF) Model. A new BL scheme, which is a nonlocal mixing concept of Noh et al. after Troen and Mahrt, was successfully incorporated into the MRF Model. In this study, simulations with 10-member ensembles were conducted for boreal summers of normal, El Nino, and La Nina years, respectively. In particular, the authors focused on the impact on tropical rainfall of the new BL scheme when two different convection schemes are utilized respectively in the model. The new BL scheme improves simulated tropical precipitation overall and in particular reduces the simulated rainfall in the central and eastern equatorial Pacific Ocean. This reduction over the eastern Pacific is a direct effect of the new BL scheme resulting in less mixing of heat and moisture and is irrespective of the convection scheme. The effect of BL processes over ...

[1] Metrics are widely used as a tool for model evaluation to assess both the performance of and changes between different generations of models. However, often the choice of metrics is limited to simple root-mean-square statistics, and it can be difficult to interpret the quality of the models in representing important physical processes. In this study, metrics have been gathered from the available literature and have been refined and augmented to include the climatology, the evolution of the rainy season, and the interannual variability of the East Asian monsoon. We investigate how these process-based metrics may be used to evaluate the simulation of the characteristics of the East Asian monsoon in climate models. The metrics confirm previous findings that climate models tend to exhibit skill in simulating the climatology and variability of temperature and winds, with lower skill in simulating precipitation distribution, seasonal cycle, and interannual variability. However, this work illustrates that a wide variety of metrics is required to make a comprehensive evaluation of East Asian climate in global circulation models. These must include consideration of both the local conditions and the large-scale circulation and measures of the seasonal cycle and interannual variability. It is also apparent that careful choice of analyzed regions must be made to avoid cancellation of biases. Such comprehensive evaluation of regional climate can be useful in estimation of current climate model performance and model development.

To understand impacts of the Tibetan Plateau (TP) upon the Asian summer monsoon (ASM), including both the Indian summer monsoons (ISM) and East Asian summer monsoons (EASM), a series of numerical experiments using the National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) are conducted with various TP heights ranging from the flat surface (1.2 km) to 140% of the actual height. It was found that an increase in the TP height leads to an increase in the simulated ISM precipitation over northern India and conversely a decrease in the height leads to a decrease in precipitation. This sensitivity is associated with both the thermal and dynamical effects of the TP; however, although the ISM precipitation over India is affected by the changes in atmospheric circulation, it is not directly affected by the thermal effect. The thermal effect of surface heating plays a role in developing positive vorticity with a consequent increase in monsoon precipitation over northern India. The width of the plateau also seems to be associated with the intensity of the sensitivity for the ISM region. For the EASM region, the orographic effect caused by changes in the lower-atmospheric circulation and its link with upper-atmospheric circulation are crucial to the monsoon circulation and precipitation. With increased TP height, the monsoon precipitation moves inland in a northwestward direction, which qualitatively follows the previous findings based on general circulation models (GCMs), but with a detailed dynamical mechanism in linkage between the lower- and upper-atmospheric circulation in the regional climate modelling (RCM) framework in this study. Copyright © 2009 Royal Meteorological Society