Impact of vegetation feedback on the temperature and its diurnal range over the Northern Hemisphere during summer in a 2 × CO2 climate

This study examines the potential impact of vegetation feedback on the changes in the diurnal temperature range (DTR) due to the doubling of atmospheric CO₂ concentrations during summer over the Northern Hemisphere using a global climate model equipped with a dynamic vegetation model. Results show that CO₂ doubling induces significant increases in the daily mean temperature and decreases in DTR regardless of the presence of the vegetation feedback effect. In the presence of vegetation feedback, increase in vegetation productivity related to warm and humid climate lead to (1) an increase in vegetation greenness in the mid-latitude and (2) a greening and the expansion of grasslands and boreal forests into the tundra region in the high latitudes. The greening via vegetation feedback induces contrasting effects on the temperature fields between the mid- and high-latitude regions. In the mid-latitudes, the greening further limits the increase in T _max more than T _min, resulting in further decreases in DTR because the greening amplifies evapotranspiration and thus cools daytime temperature. The greening in high-latitudes, however, it reinforces the warming by increasing T _max more than T _min to result in a further increase in DTR from the values obtained without vegetation feedback. This effect on T _max and DTR in the high latitude is mainly attributed to the reduction in surface albedo and the subsequent increase in the absorbed insolation. Present study indicates that vegetation feedback can alter the response of the temperature field to increases in CO₂ mainly by affecting the T _max and that its effect varies with the regional climate characteristics as a function of latitudes.     

Climate change in the 21st century simulated by HadGEM2-AO under representative concentration pathways

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.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 mass (21.5 μg m^− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM_2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

Spring Arctic Oscillation-East Asian summer monsoon connection through circulation changes over the western North Pacific

In the present study the links between spring Arctic Oscillation (AO) and East Asian summer monsoon (EASM) was investigated with focus on the importance of the North Pacific atmospheric circulation and sea surface temperature (SST). To reduce the statistical uncertainty, we analyzed high-pass filtered data with the inter-annual time scales, and excluded the El Ni?o/Southern Oscillation signals in the climate fields using a linear fitting method. The significant relationship between spring AO and EASM are supported by the changes of multi-monsoon components, including monsoon indices, precipitation, and three-dimensional atmospheric circulations. Following a stronger positive spring AO, an anomalous cyclonic circulation at 850?hPa appears in southeastern Asia and the western North Pacific in summer, with the easterly anomalies spanning from the Pacific to Asian continent along 25°N?C30°N and the westerly anomalies south of 15°N. At the same time, the summer western North Pacific subtropical high becomes weaker. Consistently, the positive precipitation anomalies are developed over a broad region south of 30°N stretching from southern China to the western Pacific and the negative precipitation anomalies appear in the lower valley of the Yangtze River and southern Japan. The anomalous cyclone in the western North Pacific persisting from spring to summer plays a key role in modulating EASM and monsoon precipitation by a positive air-sea feedback mechanism. During spring the AO-associated atmospheric circulation change produces warmer SSTs between 150°E?C180° near the equator. The anomalous sensible and latent heating, in turn, intensifies the cyclone through a Gill-type response of the atmosphere. Through this positive feedback, the tropical atmosphere and SST patterns sustain their strength from spring to summer, that consequently modifies the monsoon trough and the western North Pacific subtropical high and eventually the EASM precipitation. Moreover, the SST response to AO-circulation is supported by the numerical simulations of an ocean model, and the anomalous atmospheric circulation over the western North Pacific is also reproduced by the dedicated numerical simulations using the coupled atmosphere?Cocean model. The observation evidence and numerical simulations suggest the spring AO can impact the EASM via triggering tropical air-sea feedback over the western North Pacific.     

The effect of aerosol representation on cloud microphysical properties in Northeast Asia

This study performed a three-dimensional regional-scale simulation of aerosol and cloud fields using a meso-scale non-hydrostatic model with a bin-based cloud microphysics. The representation of aerosols in the model has been improved to account for more realistic multi-modal size distribution and multiple chemical compositions. Two case studies for shallow stratocumulus over Northeast Asia in March 2005 were conducted with different aerosol conditions to evaluate model performance. Improved condensation nuclei (CN) and cloud condensation nuclei (CCN) are attributable to the newly constructed aerosol size distribution. The simulated results of cloud microphysical properties (cloud droplet effective radius, liquid water path, and optical thickness) with improved CN/CCN number are close to the retrievals from satellite-based observation. The effects of aerosol on the microphysical properties of shallow stratocumulus are investigated by model simulation, in terms of columnar aerosol number concentration. Enhanced aerosol number concentration results in increased liquid water path in humid case, but invariant liquid water path in dry case primarily due to precipitation occurrence. The changes of cloud microphysical properties are more predominant for small aerosol burden than for large aerosol burden with the retarded changes in cloud mass and size due to inactive condensation and collision-coalescence processes. Quantitative evaluation of sensitivity factor between aerosol and cloud microphysical properties indicates a strong aerosol-cloud interaction in Northeast Asian region.     

Winter precipitation variability over Korean Peninsula associated with ENSO

In this study, winter precipitation variability associated with the El Niño-Southern Oscillation (ENSO) over the Korean Peninsula was investigated using a 5-pentad running mean data because significant correlation pattern cannot be revealed using seasonal-mean data. It was found a considerably significant positive correlation between Niño3 sea-surface temperature and precipitation during early winter (from Mid-November to early-December), when the correlation coefficient is close to 0.8 in early-December; the correlation is distinctively weakened during late winter. It is demonstrated that such sudden intraseasonal change in relation to ENSO is associated with the presence of anticyclonic flow over the Kuroshio extension region (Kuroshio anticyclone). In early winter, there is strong southerly wind over the Korean Peninsula, which is induced by the Philippine Sea anticyclone and Kuroshio anticyclone. However, in January, although the Philippine Sea anticyclone develops further, the Kuroshio anticyclone suddenly disappears; as a result, the impact of ENSO is considerably weakened over the Korean Peninsula. These results indicate that the Kuroshio anticyclone during El Niño peak phase plays a critical role by strongly affecting Northeast Asia climate, including the Korean Peninsula. In addition, it is also found that there are distinctive interdecadal changes of the relationship between ENSO and precipitation over the Korean Peninsula. In particular, the strong correlation in early winter is clearer in the recent 30 years than that in the previous period of 1950–1979.     

Analysis of solar radiation on the surface estimated from GWNU solar radiation model with temporal resolution of satellite cloud fraction

Preliminary analysis with a solar radiation model is generally performed for photovoltaic power generation projects. Therefore, model accuracy is extremely important. The temporal and spatial resolutions used in previous studies of the Korean Peninsula were 1 km × 1 km and 1-h, respectively. However, calculating surface solar radiation at 1-h intervals does not ensure the accuracy of the geographical effects, and this parameter changes owing to atmospheric elements (clouds, aerosol, ozone, etc.). Thus, a change in temporal resolution is required. In this study, one-year (2013) analysis was conducted using Chollian geostationary meteorological satellite data from observations recorded at 15-min intervals. Observation data from the intensive solar site at Gangneung-Wonju National University (GWNU) showed that the coefficient of determination (R²), which was estimated for each month and season, increased, whereas the standard error (SE) decreased when estimated in 15-min intervals over those obtained in 1-h intervals in 2013. When compared with observational data from 22 solar sites of the Korean Meteorological Administration (KMA), R² was 0.9 or higher on average, and over- or under-simulated sites did not exceed 3 sites. The model and 22 solar sites showed similar values of annual accumulated solar irradiation, and their annual mean was similar at 4,998 MJ m^?2 (3.87 kWh m^?2). These results show a difference of approximately ± 70 MJ m^?2 (± 0.05 kWh m^?2) from the distribution of the Korean Peninsula estimated in 1-h intervals and a higher correlation at higher temporal resolution.     

Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere

An ensemble data assimilation system using the 4-dimensional Local Ensemble Transform Kalman Filter is implemented to a global non-hydrostatic Numerical Weather Prediction model on the cubed-sphere. The ensemble data assimilation system is coupled to the Korea Institute of Atmospheric Prediction Systems Package for Observation Processing, for real observation data from diverse resources, including satellites. For computational efficiency in a parallel computing environment, we employ some advanced software engineering techniques in the handling of a large number of files. The ensemble data assimilation system is tested in a semi-operational mode, and its performance is verified using the Integrated Forecast System analysis from the European Centre for Medium-Range Weather Forecasts. It is found that the system can be stabilized effectively by additive inflation to account for sampling errors, especially when radiance satellite data are additionally used.     

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.     

High-resolution climate simulation of the last glacial maximum

The climate of the last glacial maximum (LGM) is simulated with a high-resolution atmospheric general circulation model, the NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. The purpose of the study is to assess whether there are significant benefits from the higher resolution simulation compared to the lower resolution simulation associated with the role of topography. The LGM simulations were forced with modified CLIMAP sea ice distribution and sea surface temperatures (SST) reduced by 1°C, ice sheet topography, reduced CO₂, and 21,000 BP orbital parameters. The high-resolution model captures modern climate reasonably well, in particular the distribution of heavy precipitation in the tropical Pacific. For the ice age case, surface temperature simulated by the high-resolution model agrees better with those of proxy estimates than does the low-resolution model. Despite the fact that tropical SSTs were only 2.1°C less than the control run, there are many lowland tropical land areas 4–6°C colder than present. Comparison of T170 model results with the best constrained proxy temperature estimates (noble gas concentrations in groundwater) now yield no significant differences between model and observations. There are also significant upland temperature changes in the best resolved tropical mountain belt (the Andes). We provisionally attribute this result in part as resulting from decreased lateral mixing between ocean and land in a model with more model grid cells. A longstanding model-data discrepancy therefore appears to be resolved without invoking any unusual model physics. The response of the Asian summer monsoon can also be more clearly linked to local geography in the high-resolution model than in the low-resolution model; this distinction should enable more confident validation of climate proxy data with the high-resolution model. Elsewhere, an inferred salinity increase in the subtropical North Atlantic may have significant implications for ocean circulation changes during the LGM. A large part of the Amazon and Congo Basins are simulated to be substantially drier in the ice age—consistent with many (but not all) paleo data. These results suggest that there are considerable benefits derived from high-resolution model regarding regional climate responses, and that observationalists can now compare their results with models that resolve geography at a resolution comparable to that which the proxy data represent.