VR c photometry of dwarf cepheids (I)

In this paper, we present VRc photometric observations of four dwarf cepheids: YZ Boo (P = 0 _. ^d 104, V = 0 _. ^m 5), AD CMi (P = 0 _. ^d 123, V = 0 _. ^m 5), XX Cyg (P = 0 _. ^d 135, V = 0 _. ^m 5), EH Lib (P = 0 _. ^d 088, V = 0 _. ^m 7). The light curves were obtained at West Mountain Observatory, Provo, Utah on 14 nights from 1983 through 1986 and contain 589 data points in each of theV andR bands in the Cousin photometric system. A detailed study of these stars, based on the present light curves, will be published separately.     

Radiative effect of black carbon aerosol on seasonal variation in snow depth in the Northern-Hemisphere

In this research, we studied the effects of black carbon (BC) aerosol radiative forcing on seasonal variation in the Northern Hemisphere (NH) using numerical simulations with the NASA finite-volume General Circulation Model (fvGCM) forced with monthly varying three-dimensional aerosol distributions from the Goddard Ozone Chemistry Aerosol Radiation and Transport Model (GOCART). The results show that atmospheric warming due to black carbon aerosols subsequently warm the atmosphere and land surfaces, especially those over Eurasia. As a result, the snow depth in Eurasia was greatly reduced in late winter and spring, and the reduction in snow cover decreased the surface albedo. Our surface energy balance analysis shows that the surface warming due to aerosol absorption causes early snow melting and further increases surface-atmosphere warming through snow/ice albedo feedback. Therefore, BC aerosol forcing may be an important factor affecting the snow/ice albedo in the NH.     

Simulation of snowstorm over the Yellow Sea using a mesoscale coupled model

This study aims to examine the favorable conditions for an ocean effect snowstorm across the Yellow Sea over the southwestern coast of Korea on 21 December 2005, using a coupled model with a Coupled Ocean/Atmosphere Mesoscale Prediction System as the atmospheric component and the Regional Ocean Modeling System as the oceanic component. Simulation of heavy snowfall event, which was 44.3 cm of snow accumulated in 24-hour, was performed to investigate the mesoscale structure, dynamics and development mechanisms in the snowstorm. As a result from 48-hour integration, the results of simulation showed that barotropic instability and turbulent heat fluxes played important roles in the formation of snowstorm. The enhanced surface diabatic heating was dominant in the latent heat flux, and eventually induced convective instability. An additional factor was the favorable condition of synoptic environment, accessing the cold air transport by the approach of the upper-level cold vortex over the warm ocean. Besides these factors, conditional symmetric instability (CSI) is a mechanism which can result in a heavy snowfall with sufficient moisture and upward vertical motion. A slantwise convection from the release of CSI could support a complex snowfall event with heavier than expected amounts. The result comparison between a coupled model and an uncoupled model supports that airsea coupling has an impact of decreasing of about 10% in a snowfall amount on the snowstorm.     

How do weather characteristics change in a warming climate?

The possible change in the characteristics of weather in the future should be considered as important as the mean climate change because the increasing risk of extremes is related to the variability on daily time scales. The weather characteristics can be represented by the climatological mean interdiurnal (day-to-day) variability (MIDV). This paper first assessed the phase five of the Coupled Model Intercomparison Project coupled climate models’ capability to represent MIDV for the surface maximum and minimum temperature, surface wind speed and precipitation under the present climate condition. Based on the assessment, we selected three best models for projecting future change. We found that the future changes in MIDV are characterized by: (a) a marked reduction in surface maximum and minimum temperature over high latitudes during the cold season; (b) a stronger reduction in the surface minimum temperature than in the maximum temperature; (c) a reduction in surface wind speed over large parts of lands in Northern Hemisphere (NH) during NH spring; (d) a noticeable increase in precipitation in NH mid-high latitudes in NH spring and winter, and in particular over East Asia throughout most of the year.     

Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble

Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m^?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.     

Variation in summer surface air temperature over Northeast Asia and its associated circulation anomalies

This study investigates the interannual variation of summer surface air temperature over Northeast Asia(NEA) and its associated circulation anomalies.Two leading modes for the temperature variability over NEA are obtained by EOF analysis.The first EOF mode is characterized by a homogeneous temperature anomaly over NEA and therefore is called the NEA mode.This anomaly extends from southeast of Lake Baikal to Japan,with a central area in Northeast China.The second EOF mode is characterized by a seesaw pattern,showing a contrasting distribution between East Asia(specifically including the Changbai Mountains in Northeast China,Korea,and Japan) and north of this region.This mode is named the East Asia(EA) mode.Both modes contribute equivalently to the temperature variability in EA.The two leading modes are associated with different circulation anomalies.A warm NEA mode is associated with a positive geopotential height anomaly over NEA and thus a weakened upper-tropospheric westerly jet.On the other hand,a warm EA mode is related to a positive height anomaly over EA and a northward displaced jet.In addition,the NEA mode tends to be related to the Eurasian teleconnection pattern,while the EA mode is associated with the East Asia-Pacific/PacificJapan pattern.     

Seasonal scale variability of the East Asian winter monsoon and the development of a two-dimensional monsoon index

This study investigates the seasonal scale variability of the East Asian winter monsoon (EAWM), which is distinguished from the seasonal cycle with temporal variation throughout winter. Winters lasting 120 days (Nov. 17–Mar. 16) for a period of 64 years from the NCEP daily reanalysis data set are used to study the seasonal scale variability of the EAWM. Cyclostationary empirical orthogonal function (CSEOF) analysis is adopted to decompose the variability of the EAWM. The second CSEOF mode of 850-hPa temperature exhibits a seasonal scale variation, the physical mechanism of which is explained in terms of physically consistent variations of temperature, geopotential height, sea level pressure, wind, and surface heat fluxes. The seasonal-scale EAWM exhibits a weak subseasonal and a strong interannual variability and has gradually weakened during the 64 years. In a weak EAWM phase, the land-sea contrast of sea level pressure declines in East Asia. Consistent with this change, low-level winds decrease and warm thermal advection increases over the eastern part of mid-latitude East Asia. Latent and sensible heat fluxes are reduced significantly over the marginal seas in East Asia. However, during a strong EAWM phase, the physical conditions in East Asia reverse. A large fraction of the variability of the EAWM is explained by the seasonal cycle and the seasonal scale variation. A two-dimensional EAWM index was developed to explain these two distinct components of the EAWM variability. The new index appears to be suitable for measuring both the subseasonal and the interannual variability of the EAWM.     

Sensitivity analysis of the Ångstrom exponent for multimodal aerosol size distributions

This study characterizes the Ångstrom exponent for polydispersed aerosol size distributions. Under the assumption of a lognormal size distribution, the dependence of Ångstrom exponent on the size distribution and the refractive index with varying real and imaginary parts are determined. Further, the influence of coarse mode particles on the Ångstrom exponent is investigated quantitatively. The results show that the nuclei mode has less influence under the simulation conditions considered in this study. It is also shown that the refractive index is an important factor influencing the Ångstrom exponent. The effect of the coarse mode on the Ångstrom exponent computed with different aerosol number concentrations and as a function of a geometric standard deviation and a geometric mean diameter is tested. It is shown that the coarse mode is crucial for determining the Ångstrom exponent.     

Effects of Resolution,Cumulus Parameterization Scheme,and Probability Forecasting on Precipitation Forecasts in a High-Resolution Limited-Area Ensemble Prediction System

This study investigates the effects of horizontal resolution, cumulus parameterization scheme (CPS), and probability forecasting on precipitation forecasts over the Korean Peninsula from 00 UTC 15 August to 12 UTC 14 September 2013, using the limited-area ensemble prediction system (LEPS) of the Korea Meteorological Administration. To investigate the effect of resolution, the control members of the LEPS with 1.5- and 3-km resolution were compared. Two 3-km experiments with and without the CPS were conducted for the control member, because a 3-km resolution lies within the gray zone. For probability forecasting, 12 ensemble members with 3-km resolution were run using the LEPS. The forecast performance was evaluated for both the whole study period and precipitation cases categorized by synoptic forcing. The performance of precipitation forecasts using the 1.5-km resolution was better than that using the 3-km resolution for both the total period and individual cases. The result of the 3-km resolution experiment with the CPS did not differ significantly from that without it. The 3-km ensemble mean and probability matching (PM) performed better than the 3-km control member, regardless of the use of the CPS. The PM complemented the defect of the ensemble mean, which better predicts precipitation regions but underestimates precipitation amount by averaging ensembles, compared to the control member. Further, both the 3-km ensemble mean and PM outperformed the 1.5-km control member, which implies that the lower performance of the 3-km control member compared to the 1.5-km control member was complemented by probability forecasting.     

Effect of aerosol pollution on clouds and its dependence on precipitation intensity

In this study, simulations performed with a large-eddy resolving numerical model are used to examine the effect of aerosol on cumulus clouds, and how this effect varies with precipitation intensity. By systematically varying the surface moisture fluxes, the modeled precipitation rate is forced to change from weak to strong intensity. For each of these intensities, simulations of a high-aerosol case (a polluted case with a higher aerosol concentration) and a low-aerosol case (a clean case with a lower aerosol concentration) are performed. Whether or not precipitation and associated sub-cloud evaporation and convective available potential energy (CAPE) are large, liquid–water path (LWP) is larger in the high-aerosol case than in the low-aerosol case over the first two-thirds of the entire simulation period. In weak precipitation cases, reduction in aerosol content leads to changes in CAPE in the middle parts of cloud layers, which in turn induces larger LWP in the low-aerosol case over the last third of the simulation period. With strong precipitation, stronger stabilization of the sub-cloud layers in the low-aerosol case counters the CAPE changes in the middle parts of cloud layers, inducing smaller LWP in the low-aerosol case over the last third of the simulation period. The results highlight an interaction between aerosol effects on CAPE above cloud base and those in sub-cloud layers, and indicate the importance of a consideration of aerosol effects on CAPE above cloud base as well as those in sub-cloud layers. In the high-aerosol case, near the beginning of the simulation period, larger environmental CAPE does not necessarily lead to larger in-cloud CAPE and associated larger cloud intensity because aerosol-induced increase in cloud population enhances competition among clouds for the environmental CAPE. This demonstrates the importance of the consideration of cloud population for an improved parameterization of convective clouds in climate models.