Numerical experiments with the NASA finite-volume general circulation model show that heating of the atmosphere by dust and black carbon can lead to widespread enhanced warming over the Tibetan Plateau (TP) and accelerated snow melt in the western TP and Himalayas. During the boreal spring, a thick aerosol layer, composed mainly of dust transported from adjacent deserts and black carbon from local emissions, builds up over the Indo-Gangetic Plain, against the foothills of the Himalaya and the TP. The aerosol layer, which extends from the surface to high elevation (∼5 km), heats the mid-troposphere by absorbing solar radiation. The heating produces an atmospheric dynamical feedback-the so-called elevated-heat-pump (EHP) effect, which increases moisture, cloudiness, and deep convection over northern India, as well as enhancing the rate of snow melt in the Himalayas and TP. The accelerated melting of snow is mostly confined to the western TP, first slowly in early April and then rapidly from early to mid-May. The snow cover remains reduced from mid-May through early June. The accelerated snow melt is accompanied by similar phases of enhanced warming of the atmosphere-land system of the TP, with the atmospheric warming leading the surface warming by several days. Surface energy balance analysis shows that the short-wave and long-wave surface radiative fluxes strongly offset each other, and are largely regulated by the changes in cloudiness and moisture over the TP. The slow melting phase in April is initiated by an effective transfer of sensible heat from a warmer atmosphere to land. The rapid melting phase in May is due to an evaporation-snow-land feedback coupled to an increase in atmospheric moisture over the TP induced by the EHP effect.

). Further analyses from sub-sampling of ENSO years, with normal (<1-σ), and abnormal (>1-σ) NAI over northern India respectively show that the EHP may lead to an amplification of the Indian summer monsoon response to ENSO forcing, particularly with respect to the increased rainfall over the Himalayan foothills, and the warming of the upper troposphere over the Tibetan Plateau. Our results suggest that absorbing aerosol, particular desert dusts can strongly modulate ENSO influence, and possibly play important roles as a feedback agent in climate change in Asian monsoon regions.

The effect of sulfate aerosol radiative forcing on spring rainfall in East Asia are studied based on numerical simulations with the NASA finite‐volume General Circulation Model (fvGCM) forced with monthly varying three‐dimensional aerosol distribution from the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). Result shows that radiative forcing of sulfate aerosol leads to cooling of the land surface and reduction in rainfall over central East Asia. The maximum reduction in precipitation is shifted northward relative to the maximum aerosol loading region as a result of dynamical feedback. The anomalous thermal gradient by aerosol cooling near the land surface, reduces the baroclinicity of the atmosphere, leading to a deceleration of the upper level westerly flow. The westerly deceleration induces, through ageostrophic wind adjustment, anomalous meridional secondary circulation at the entrance region of the East Asian jetstream, with strong sinking motion and suppressed precipitation near 30°N, coupled to weak rising motion and moderately enhanced precipitation over southern China and the South China Sea. These results suggest that the radiative forcing of aerosol through induced dynamical feedback with the atmospheric water cycle, may be a causal factor in the observed spring precipitation trend over East Asia.

This paper examines the usefulness of the non-stationary generalized extreme value (GEV) distribution in modelling extreme rainfall. We modelled the annual maxima of daily (AMP1) and 2-day (AMP2) rainfall data observed during the summer rainy season, dating up to 2007 in 28 stations in South Korea. We fitted the GEV distribution to the data for each location. The location parameter of the GEV distribution was formulated as a function of time to explore the temporal trends in maximum precipitation over the course of climatic change and to predict future behaviours. We found evidence of non-stationarity in the form of increasing trends for six stations from AMP1 and for five stations from AMP2. This trend is consistent with the results from a regional climate model derived by the A1B emission forcing of IPCC AR4. The stationary Gumbel distribution provided a good fit to the AMP1 data for 18 stations and to the AMP2 data for 15 stations. We quantified the changes in extreme rainfall for each station; the return levels and their 95% confidence intervals for various return periods are provided.

In this study, the global Lorenz atmospheric energy cycle is evaluated using the Modern Era Retrospective analysis for Research and Applications (MERRA) and the National Center for Environmental Prediction and the Department of Energy (NCEP R2) reanalysis datasets over a 30-year period (1979-2008) for the annual, JJA, and DJF means. The energy cycle calculated from the two reanalysis datasets is largely consistent, but the energy cycle determined using the MERRA dataset is more active than that determined from the NCEP R2 dataset. For instance, with regard to the annual mean, the general discrepancy between the energy components in the global integral is about 5 %, whereas the discrepancy between the conversion components is about 16 %, with the exception of C(P M , K M ), which has a different sign in the global integrals. The latitude-altitude cross-section indicates that the difference in the energy cycle of the two reanalysis datasets is larger in the southern hemisphere than in the northern hemisphere. The conversion rates of mean available potential energy to mean kinetic energy [C(P M , K M )] and eddy available potential energy to eddy kinetic energy [C(P E , K E )] are also calculated using two formulations (socalled 'vÁgrad z' and 'xÁa') for the two reanalysis datasets. The differences in the conversion rate between the two reanalysis datasets for the global integral are not appreciable for the two formulations.

The direct effects of aerosols on global and regional climate during boreal spring are investigated based on simulations using the NASA Global Modeling and Assimilation Office (GMAO) finite-volume general circulation model (fvGCM) with Microphyics of clouds in Relaxed Arakawa Schubert Scheme (McRAS). The aerosol loading are prescribed from three-dimensional monthly distribution of tropospheric aerosols viz., sulfate, black carbon, organic carbon, soil dust, and sea salt from output of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol extinction coefficient, single scattering albedo, and asymmetric factor are computed as wavelength-dependent radiative forcing in the radiative transfer scheme of the fvGCM, and as a function of the aerosol loading and ambient relative humidity.We find that anomalous atmospheric heat sources induced by absorbing aerosols (dust and black carbon) excites a planetary scale teleconnection pattern in sea level pressure, temperature and geopotential height spanning North Africa through Eurasia to the North Pacific. Surface cooling due to direct effects of aerosols is found in the vicinity and downstream of the aerosol source regions, Le., South Asia, East Asia, and northern and western Africa. Additionally, atmospheric heating is found in regions with largdoading of dust (over Northern Africa, and Middle East), and black carbon (over South-East Asia). Paradoxically, the most pronounced feature in aerosol-induced surface temperature is an east-west dipole anomaly with strong cooling over the Caspian Sea. and warming over central and northeastern Asia, where aerosol concentration are low. Analyses of circulation anomalies show that the dipole anomaly is a part of an atmospheric teleconnection driven by atmospheric heating anomalies induced by absorbing aerosols in the source regions, but the influence was conveyed 2 globally through barotropic energy dispersion and sustained by feedback processes associated with the regional circulations. Atmospheric heating by dust aerosol over northern Africa and the Middle East is the primary driver of the atmospheric teleconnection, with significant contribution by black carbon over South and East Asia.The surface temperature signature associated with the aerosol-induced teleconnection bears striking resemblance to the spatial pattern of observed long-term trend -in surface temperature over Eurasia.Additionally, the boreal spring teleconnection pattern is similar to that reported by Fukutomi et a1 (2004) associated with boreal summer precipitation seesaw between eastern and western Siberia. The results of this study raise the possibility that global aerosol forcing during boreal spring may play an important role in spawning atmospheric teleconnection which affects regional and global climates.3

Seasonal precipitation at the decadal time scale is predicted using the downscaling super ensemble (DSE) method, which is developed by combining the superensemble procedure with a statistical downscaling method in this study. The multimodel data utilized are the long-term integration of six atmosphere-ocean general circulation models (AOGCMs) and the downscaling method is based on the singular value decomposition with the empirical orthogonal function (EOF) truncation to correct the systematic bias in the dynamic models.Interestingly, even though prediction skill in the training period is increased with increasing number of AOGCMs used, the skill is often decreased in the independent period. It is found that prediction skill in the independent period continues to rise when we use an optimal combination of predictors. The optimum combination used in constructing the superensemble model is the super-3 ensemble, which is a combination of three AOGCMs (CCCma, CSIRO, and NCAR) among the six AOGCMs used in this study. In general, the first four EOFs of sea-level pressure (SLP) in the super-3 ensemble are very similar to those of the observed SLP. The dynamic link between Korean winter precipitation and East Asian monsoon circulation in the super-3 ensemble is similar to that of the observed indicating that the super-3 ensemble realistically simulates the circulations in the East Asian monsoon region. The cross-validation for the prediction of the super-3 ensemble shows that the correlation skill score is about 0.49, which is significant at the 5% level. The results provide hope for regional climate prediction in decadal time-scales using superensemble methods together with statistical downscaling.

Attempts to assess the changes between the observed (or historical) and future projected daily rainfall extremes for 59 stations throughout Korea have been made with descriptive statistics and extreme value analysis. For the comparison, three different periods and four different data sets are considered: observation and historical data from 1976 to 2005 (period 0), simulation from 2021 to 2050 (period 1) and from 2066 to 2095 (period 2). The historical and projected rainfalls are obtained from RCP 4.5 and RCP 8.5 scenarios, which are based on a regional climate model HadGEM3‐RA. For the comparison of extreme values, the 20‐ and 50‐year return levels and the return period estimates are obtained by using the best one between two extreme value distributions, the method of L‐moments and the regional frequency analysis. From the descriptive statistics, we find that the numbers of heavy rainfall events will increase in the future. The total precipitation is projected to remain unchanged or slightly increased, compared to the observation. From the extreme value analysis, we realize that a 1‐in‐20 year and a 1‐in‐50 year annual maximum daily precipitation will likely become a 1‐in‐10 year and a 1‐in‐16 year event, respectively, when compared to the observation (a 1‐in‐5 year and a 1‐in‐7 year event, compared to the historical data), by the end of the 21st century. But this finding is based on only one simulation model, which confines the confidence of the result and suggests an ensemble approach based on multiple models to get more reliable result.