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.     

An ENSO stability analysis. Part I: results from a hybrid coupled model

In this study, we use the Bjerknes stability (BJ) index as a tool to investigate overall El Niño-Southern Oscillation (ENSO) stability in a hybrid-coupled model (HCM) with various atmosphere and ocean background states. This HCM shows that ENSO growth rates as measured by the BJ index and linear growth rates estimated directly with a time series of the Niño 3.4 indices from the coupled model simulations exhibit similar dependence on background states, coupling strength, and thermodynamic damping intensity. That is, the BJ index and linear growth rates increase with a decrease in the intensity of the background wind, an increase in coupling strength, or a decrease in the intensity of thermodynamic damping, although the BJ index tends to overestimate the growth rate. A detailed analysis of the components of the BJ index formula suggests the importance of model climatological background states and oceanic dynamic parameters in determining ENSO stability. We conclude that the BJ index may serve as a useful tool for qualitatively evaluating the overall ENSO stability in coupled models or in observations without a detailed eigen-analysis that is difficult to perform in models more complex than relatively simple models.     

Future changes in summer precipitation in regional climate simulations over the Korean Peninsula forced by multi-RCP scenarios of HadGEM2-AO

In this study, the regional climate of the Korean Peninsula (KP) was dynamically downscaled using a high-resolution regional climate model (RCM) forced by multi- representative concentration pathways (RCP) scenarios of HadGEM2-AO, and changes in summer precipitation were investigated. Through the evaluation of the present climate, the RCM reasonably reproduced long-term climatology of summer precipitation over the KP, and captured the sub-seasonal evolution of Changma rain-band. In future projections, all RCP experiments using different RCP radiative forcings (i.e., RCP2.6, RCP4.5, RCP6.0, and RCP8.5 runs) simulated an increased summer precipitation over the KP. However, there were some differences in changing rates of summer precipitation among the RCP experiments. Future increases in summer precipitation were affected by future changes in moisture convergence and surface evaporation. Changing ranges in moisture convergences among RCP experiments were significantly larger than those in surface evaporation. This indicates that the uncertainty of changes in summer precipitation is related to the projection of the monsoon circulation, which determines the moisture convergence field through horizontal advection. Changes in the sub-seasonal evolution of Changma rain-band were inconsistent among RCP experiments. However, all experiments showed that Changma rain-band was enhanced during late June to early July, but it was weakened after mid-July due to the expansion of the western North Pacific subtropical high. These results indicate that precipitation intensity related to Changma rain-band will be increased, but its duration will be reduced in the future.     

Combined effect of El Niño-Southern Oscillation and Pacific Decadal Oscillation on the East Asian winter monsoon

Using long-term observational data and numerical model experiments, the combined effect of the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on the variability of the East Asian winter monsoon is examined. In the observations, it is found that when the ENSO and PDO are in-phase combinations (i.e., El Niño/positive PDO phase and La Niña/negative PDO phase), a negative relationship between ENSO and East Asian winter monsoon is significantly intensified. In other words, when El Niño (La Niña) occurs with positive (negative) PDO phase, anomalous warm (cold) temperatures are dominant over the East Asian winter continent. On the other hand, there are no significant temperature anomalies when the ENSO and PDO are out-of-phase combinations (i.e., El Niño/negative PDO phase and La Niña/positive PDO phase). Further analyses indicate that the anticyclone over the western North Pacific including the East Asian marginal seas plays an essential role in modulating the intensity of the East Asian winter monsoon under the changes of ENSO–PDO phase relationship. Long-lasting high pressure and warm sea surface temperature anomalies during the late fall/winter and following spring over the western North Pacific, which appear as the El Niño occurs with positive PDO phase, can lead to a weakened East Asian winter monsoon by transporting warm and wet conditions into the East Asian continent through the southerly wind anomalies along the western flank of the anomalous high pressure, and vice versa as the La Niña occurs with negative PDO phase. In contrast, the anomalous high pressure over the western North Pacific does not show a prominent change under the out-of-phase combinations of ENSO and PDO. Numerical model experiments confirm the observational results, accompanying dominant warm temperature anomalies over East Asia via strong anticyclonic circulation anomalies near the Philippine Sea as the El Niño occurs with positive PDO phase, whereas such warming is weakened as the El Niño occurs with negative PDO phase. This result supports the argument that the changes in the East Asian winter monsoon intensity with ENSO are largely affected by the strength of the anticyclone over the western North Pacific, which significantly changes according to the ENSO–PDO phase relationship.     

Comparison of extended medium-range forecast skill between KMA ensemble,ocean coupled ensemble,and GloSea5

This article describes a three way inter-comparison of forecast skill on an extended medium-range time scale using the Korea Meteorological Administration (KMA) operational ensemble numerical weather prediction (NWP) systems (i.e., atmosphere-only global ensemble prediction system (EPSG) and ocean-atmosphere coupledEPSG) and KMA operational seasonal prediction system, the Global Seasonal forecast system version 5 (GloSea5). The main motivation is to investigate whether the ensemble NWP system can provide advantage over the existing seasonal prediction system for the extended medium-range forecast (30 days) even with putting extra resources in extended integration or coupling with ocean with NWP system. Two types of evaluation statistics are examined: the basic verification statistics - the anomaly correlation and RMSE of 500-hPa geopotential height and 1.5-meter surface temperature for the global and East Asia area, and the other is the Real-time Multivariate Madden and Julian Oscillation (MJO) indices (RMM1 and RMM2) - which is used to examine the MJO prediction skill. The MJO is regarded as a main source of forecast skill in the tropics linked to the mid-latitude weather on monthly time scale. Under limited number of experiment cases, the coupled NWP extends the forecast skill of the NWP by a few more days, and thereafter such forecast skill is overtaken by that of the seasonal prediction system. At present stage, it seems there is little gain from the coupled NWP even though more resources are put into it. Considering this, the best combination of numerical product guidance for operational forecasters for an extended medium-range is extension of the forecast lead time of the current ensemble NWP (EPSG) up to 20 days and use of the seasonal prediction system (GloSea5) forecast thereafter, though there exists a matter of consistency between the two systems.     

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.     

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.     

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.     

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.