Lateral Boundary Forcing Research Articles

Changes in Four Decades of Near‐CONUS Tropical Cyclones in an Ensemble of 12 km Thermodynamic Global Warming Simulations

AbstractWe evaluate tropical cyclones (TCs) in a set of thermodynamic global warming (TGW) simulations over the continental United States (CONUS). A 12 km simulation forced by ERA5 provides a 40‐year historical (1980–2019) control. Four complimentary future scenarios are generated using thermodynamic deltas applied to lateral boundary, interior, and surface forcing. We curate a data set of 4,498 6‐hourly TC snapshots in the control and find a corresponding “twin” in each counterfactual, permitting a paired comparison. Warming results in an increase in mean dynamical TC intensity and moisture‐related quantities, with the latter being more pronounced. TC inner cores contract slightly but outer storm size remains unchanged. The frequency with which TCs become more intense is only moderately consistent, with snapshots having increased hazards ranging from 50% to 80% depending on warming level. The fractions of TCs undergoing rapid intensification and weakening both increase across all warming simulations, suggesting elevated short‐term intensity variability.

Contributions of atmospheric forcing and ocean preconditioning in the 2016 Antarctic sea ice extent drop

The 2016 Antarctic sea ice extent (SIE) drop was a rapid decrease that led to persistent low sea ice conditions. The event was triggered by atmospheric anomalies, but the potential preconditioning role of the ocean is unsettled. Here, we use sensitivity experiments with a fully-coupled regional climate model to elucidate the impact of the ocean conditions on the drop and on the persistence of the negative SIE anomalies during 2017. In particular, we re-initialize the model in January 2016 using different ocean and sea ice conditions, keeping lateral boundary forcings in the atmosphere and ocean unchanged. We find that the state of the Southern Ocean in early 2016 does not determine whether the drop occurs or not, but indeed has an impact on its amplitude and regional characteristics. Our results also indicate that the ocean initialization affects the sea ice recovery after the drop in the short term (one year), especially in the Weddell sector. The ocean’s influence appears not to be linked to the ocean surface and sea-ice initialization, but rather to the sub-surface conditions (between 50 m and 150 m) and heat exchange fluctuations at the regional scale, while the atmospheric forcing triggering the drop is driven by the large-scale circulation.

Influences of Lateral Boundary Forcings on the 2020 Extreme Meiyu in the Yangtze‐Huaihe River Valley

AbstractMeiyu occurs in Yangtze‐Huaihe River valley (YHRV) every summer. Its intensity, distribution, and intraseasonal variation are greatly influenced by atmospheric forcings from different directions, such as the monsoon southwesterlies from the south, the western Pacific subtropical high (WPSH) in the east, the atmospheric longwave activities in the north, the southwest vortex from the west, and so on. In this study, to explore the contributions of the atmospheric forcings from different directions to 2020 extreme Meiyu, Regional Climate Model version 4.6 (RegCM4.6) is employed. A series of sensitivity experiments are conducted with realistic or climatological averaged lateral boundary conditions. The results show that the monsoon westerlies from the south transport moisture and heat to YHRV, converge with the cold air brought by the frequent atmospheric longwave activities in the north, and result in this extreme Meiyu. The frequent cold air from the north can lift warm air, provide unstable conditions, and make the distribution of precipitation similar to the teleconnection pattern in East Asia. The stable WPSH in the east anchors the 2020 Meiyu rainband to the YHTV for a long time. In addition, the contributions of the atmospheric forcings from different directions to evolution of 2020 Meiyu change with time. Before 10 June, the WPSH in the east mainly contributes to the Meiyu evolution. From 11 June to 3 July, the combined effects of atmospheric forcings from the south and north are dominant. From 3 July to 10 July, the cold air from the north plays a major role.

Appropriately representing convective heating is critical for predicting catastrophic heavy rainfall in 2021 in Henan Province of China

An unprecedented heavy rainfall event occurred in Henan Province of central China during 19–20 July 2021 with the maximum hourly rainfall rate of 201.9 mm, which broke the historical record in mainland China. To investigate the impacts of predicted atmospheric circulation on the regional convection-permitting prediction of this event, two sets of nested experiments with different convective parameterizations (GF and MSKF) in the outer domain and at convection-permitting resolution in the inner domain are performed with the Weather Research and Forecasting (WRF) model. The analysis found the prediction of ‘21.7’ rainstorm at convection-permitting resolution in the inner domain is largely affected by convective scheme in the outer domain. The atmospheric circulation forcing from the outer domain with different convective schemes is significantly different, which ultimately affects the regional synoptic pattern and precipitation in the refined region through lateral boundary forcing. The difference in regional prediction at convection-permitting resolution can be mitigated by adjusting convective latent heat parameterization in the outer domain. This work highlights that appropriately parameterizing convective latent heat is the key to provide reasonable large-scale forcing for regionally predicting this catastrophic heavy rainfall event at convection-permitting resolution, which may also be applicable to other events and other regions.

A high resolution coupled ocean-atmosphere simulation of the regional climate over Central America

This study analyzes a relatively high resolution (15 km grid spacing), regional coupled ocean–atmosphere simulation configured over Central America. The simulation is conducted with the Regional Spectral Model-Regional Ocean Model System (RSM-ROMS) forced with global atmospheric and oceanic reanalysis for a period of 25 years (1986–2010). The spatial resolution of the RSM-ROMS simulation is unprecedented for the region. The highlights of the RCM simulation include the verifiable seasonal cycle of mesoscale features like the Low-Level Jets (LLJs), the Mid-Summer Drought (MSD), and the seasonal Tropical Cyclone (TC) activity both in the Pacific and in the Atlantic Oceans. However, some of the biases of the RSM-ROMS simulation of the frequency and amplitude of the MSD, the track density of the TCs in the two ocean basins, and the seasonal bias of the LLJs are noted. The seasonal cycle of the robust surface ocean currents in the eastern Pacific and the Costa Rica Dome is also well captured in the RSM-ROMS simulation. The RSM-ROMS simulation also resolves the seasonal cycle of the cyclonic Panama-Colombia Gyre and the anti-cyclonic Gulf of Papagayo-Tehuantepec Gyre. In many instances we find the RSM-ROMS improves upon the global reanalysis forcing the simulation, indicating the potential value of dynamic downscaling. Furthermore, the co-evolving components of the atmosphere and ocean in the RCM is an added benefit to the atmosphere only and ocean only global reanalysis forcing the simulation. However, the RCM displays significant biases that manifest in precipitation, precipitable water, SST, and winds which in the cases of prognostic variables of RSM-ROMS are perpetrated by the biases in the lateral boundary forcing (e.g., precipitable water) and in other instances forced by biases within the RSM-ROMS (e.g., precipitation, SST).

Challenges and outlook for convection-permitting climate modelling.

Climate projections at very high resolution (kilometre-scale grid spacing) are becoming affordable. These 'convection-permitting' models (CPMs), commonly used for weather forecasting, better represent land-surface characteristics and small-scale processes in the atmosphere such as convection. They provide a step change in our understanding of future changes at local scales and for extreme weather events. For short-duration precipitation extremes, this includes capturing local storm feedbacks, which may modify future increases. Despite the major advance CPMs offer, there are still key challenges and outstanding science issues. Heavy rainfall tends to be too intense; there are challenges in representing land-surface processes; sub-kilometre scale processes still need to be parametrized, with existing parametrization schemes often requiring development for use in CPMs; CPMs rely on the quality of lateral boundary forcing and typically do not include ocean-coupling; large CPM ensembles that comprehensively sample future uncertainties are costly. Significant progress is expected over the next few years: scale-aware schemes may improve the representation of unresolved convective updrafts; work is underway to improve the modelling of complex land-surface fluxes; CPM ensemble experiments are underway and methods to synthesize this information with larger coarser-resolution model ensembles will lead to local-scale predictions with more comprehensive uncertainty context for user application. Large-domain (continental or tropics-wide) CPM climate simulations, potentially with additional earth-system processes such as ocean and wave coupling and terrestrial hydrology, are an exciting prospect, allowing not just improved representation of local processes but also of remote teleconnections. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Hydrological Extremes in the Canadian Prairies in the Last Decade due to the ENSO Teleconnection—A Comparative Case Study Using WRF

In the Prairie provinces of Alberta, Saskatchewan, and Manitoba, agricultural production depends on winter and spring precipitation. There is large interannual variability related to the teleconnection between the regional hydroclimate and El Niño and La Niña in the Tropical Pacific. A modeling experiment was conducted to simulate climatic and hydrological parameters in the Canadian Prairie region during strong El Niño and La Niña events of the last decade in 2015–2016 and 2010–2011, respectively. The National Center for Atmospheric Research (NCAR) Weather Research and Forecasting (WRF) model was employed to perform two sets of sensitivity experiments with a nested domain at 10 km resolution using the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA) interim data as the lateral boundary forcing. Analysis of the hourly model output provides a detailed simulation of the drier winter, with less soil moisture in the following spring, during the 2015–2016 El Niño and a wet winter during the La Niña of 2010–2011. The high-resolution WRF simulation of these recent weather events agrees well with observations from weather stations and water gauges. Therefore, we were able to take advantage of the WRF model to simulate recent weather with high spatial and temporal resolution and thus study the changes in hydrometeorological parameters across the Prairie during the two extreme hydrological events of the last decade.

Confronting Arctic Troposphere, Clouds, and Surface Energy Budget Representations in Regional Climate Models With Observations

AbstractA coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

How good is regional climate model version 4 in simulating the monsoon onset over Kerala?

This study assesses the performance of regional climate model version 4 (RegCM4) in simulating the monsoon onset over Kerala (MOK). It also examines any possible relationship between the onset dates with the summer monsoon rainfall over India as whole as well as each grid points of the India land points and also the moisture inflow into Indian subcontinent. A 30‐year long simulation starting from 1979 till 2008 was carried out with the lateral boundary forcings provided by European Centre for Medium Range Weather Forecasts Reanalysis (ERA‐interim) at 25 km horizontal resolution. The simulated climatological MOK date is found to be 28th May, while as per the India Meteorological Department, climatological normal onset date is 1st June. The model has performed well in simulating the inter‐annual variation of MOK during the study period. The correlation coefficient between model simulated and observed MOK is 0.83 significant at 95% confidence level. In both model and observations, the MOK is weakly correlated with All India Summer Monsoon Rainfall. Again, the model skill was examined through equitable threat score (ETS). The ETS score is high for normal (0.48) and delayed (0.42) onset years, while the score is very low in early onset years. The spatial patterns of rainfall over central India are very similar in early and normal onset years. The model has performed well in reproducing the moisture inflow in to the Indian subcontinent from all the directions in most of the years, but there is no one‐to‐one relation between different categories of MOK years with total rainfall and net moisture inflow. Based on this study, it is found that RegCM4 reproduces different aspects of MOK reasonably well.

Convective-Permitting Hindcast Simulations during the North American Monsoon GPS Transect Experiment 2013: Establishing Baseline Model Performance without Data Assimilation

AbstractDuring the North American monsoon global positioning system (GPS) Transect Experiment 2013, daily convective-permitting WRF simulations are performed in northwestern Mexico and the southern Arizona border region using the operational Global Forecast System (GFS) and North American Mesoscale Forecast System (NAM) models as lateral boundary forcing and initial conditions. Compared to GPS precipitable water vapor (PWV), the WRF simulations display a consistent moist bias in the initial specification of PWV leading to convection beginning 3–6 h early. Given appreciable observed rainfall, days are classified as strongly and weakly forced based only on the presence of an inverted trough (IV); gulf surges did not noticeably impact the development of mesoscale convective systems (MCSs) and related convection in northwestern Mexico. Strongly forced days display higher modeled precipitation forecast skill than weakly forced days in the slopes of the northern Sierra Madre Occidental (SMO) away from the crest, especially toward the west where MCSs account for the greatest proportion of all monsoon-related precipitation. A case study spanning 8–10 July 2013 illustrates two consecutive days when nearly identical MCSs evolved over northern Sonora. Although a salient MCS is simulated on the strongly forced day (9–10 July 2013) when an IV is approaching the core monsoon region, a simulated MCS is basically nonexistent on the weakly forced day (8–9 July 2013) when the IV is farther away. The greater sensitivity to the initial specification of PWV in the weakly forced day suggests that assimilation of GPS-derived PWV for these types of days may be of greatest value in improving model precipitation forecasts.

Assessment of two versions of regional climate model in simulating the Indian Summer Monsoon over South Asia CORDEX domain

This study assess the performance of two versions of Regional Climate Model (RegCM) in simulating the Indian summer monsoon over South Asia for the period 1998 to 2003 with an aim of conducting future climate change simulations. Two sets of experiments were carried out with two different versions of RegCM (viz. RegCM4.2 and RegCM4.3) with the lateral boundary forcings provided from European Center for Medium Range Weather Forecast Reanalysis (ERA-interim) at 50 km horizontal resolution. The major updates in RegCM4.3 in comparison to the older version RegCM4.2 are the inclusion of measured solar irradiance in place of hardcoded solar constant and additional layers in the stratosphere. The analysis shows that the Indian summer monsoon rainfall, moisture flux and surface net downward shortwave flux are better represented in RegCM4.3 than that in the RegCM4.2 simulations. Excessive moisture flux in the RegCM4.2 simulation over the northern Arabian Sea and Peninsular India resulted in an overestimation of rainfall over the Western Ghats, Peninsular region as a result of which the all India rainfall has been overestimated. RegCM4.3 has performed well over India as a whole as well as its four rainfall homogenous zones in reproducing the mean monsoon rainfall and inter-annual variation of rainfall. Further, the monsoon onset, low-level Somali Jet and the upper level tropical easterly jet are better represented in the RegCM4.3 than RegCM4.2. Thus, RegCM4.3 has performed better in simulating the mean summer monsoon circulation over the South Asia. Hence, RegCM4.3 may be used to study the future climate change over the South Asia.

Decomposition of thermal and dynamic changes in the South China Sea induced by boundary forcing and surface fluxes during 1970-2000

Based on a fully-coupled, high-resolution regional climate model, this study analyzed three-dimensional temperature and momentum changes in the South China Sea (SCS) from 1970 to 2000, during which period the climate shifts from a decadal La Nina-like condition (before 1976/77) to a decadal El Nino-like condition afterward. With a set of partially-coupled experiments, sea surface temperature (SST) and kinetic energy (KE) changes during this period are first decomposed into two components: those induced by lateral boundary forcing and those induced by atmospheric surface fluxes. The results showed that the total SST and KE changes show an increasing trend from 1970 to 2000. The two decomposed components together determined 96% and 89% of the SST and KE changes respectively, implying their dominant roles on the SCS's surface variability. Spatially, a sandwich pattern of air-sea forcing relationship is revealed in the SCS basin. The increased KE, represented by a cyclonic flow anomaly in the northern SCS, was induced by enhanced cold water intrusion from Pacific into the SCS via the Luzon Strait (boundary forcing). This cold-water inflow, however, resulted in SST cooling along the northern shelf of the SCS. The maximal SST warming occurred in the central SCS and was attributed to the wind-evaporation-SST (WES) positive feedback (surface forcing), in which a southwestward wind anomaly is initialized by SST gradients between the northern and southern SCS. This wind anomaly decelerates the southwestly summer monsoons and in turn increases the SST gradients. Over the shallow Sunda shelf, which is far from the Luzon Strait, the SST/KE variability appeared to be determined primarily by local air–sea interactions. Furthermore, analyses on subsurface components indicated that the subsurface temperature changes are primarily induced by internal ocean mixing, which becomes significantly important below the thermocline. The enhanced subsurface flow is driven by the Luzon Strait inflow as well, and exits the SCS via the Mindoro-Sibutu passage. This article is protected by copyright. All rights reserved.

Impact of GCM boundary forcing on regional climate modeling of West African summer monsoon precipitation and circulation features

In this study, the latest version of the International Centre for Theoretical Physics Regional Climate Model (RegCM4) driven by three CMIP5 Global Climate Models (GCMs) is used at 25 km grid spacing over West Africa to investigate the impact of lateral boundary forcings on the simulation of monsoon precipitation and its relationship with regional circulation features. We find that the RegCM4 experiments along with their multimodel ensemble generally reproduce the location of the main precipitation characteristics over the region and improve upon the corresponding driving GCMs. However, the provision of different forcing boundary conditions leads to substantially different precipitation magnitudes and spatial patterns. For instance, while RegCM4 nested within GFDL-ESM-2M and HadGEM2-ES exhibits some underestimations of precipitation and an excessively narrow Intertropical Convergence Zone, the MPI-ESM-MR driven run produces precipitation spatial distribution and magnitudes more similar to observations. Such a superior performance originates from a much better simulation of the interactions between baroclinicity, temperature gradient and African Easterly Jet along with an improved connection between the Isentropic Potential Vorticity, its gradient and the African Easterly Waves dynamics. We conclude that a good performing GCM in terms of monsoon dynamical features (in this case MPI-ESM-MR) is needed to drive RCMs in order to achieve a better representation of the West Africa summer monsoon precipitation.

Erratum to: Impact of domain size on the simulation of Indian summer monsoon in RegCM4 using mixed convection scheme and driven by HadGEM2

In this study, a smaller domain over India alone and a larger South Asia (SA) domain have been used in the Regional Climate Model version 4.2 (RegCM4.2) to examine the effect of the domain size on the Indian summer monsoon simulations. These simulations were carried out over a period of 36 years at 50 km horizontal resolution with the lateral boundary forcings of the UK Met Office Hadley Centre Global Circulation Model Version 2.0. Results show that the Indian summer monsoon rainfall is significantly reduced when the domain size for the model integration is reduced from SA to the Indian domain. In case of SA domain simulation, the Equitable Threat Scores have higher values in case of very light, light and moderate rainfall events than those in case of the Indian domain simulation. It is also found that the domain size of model integration has dominant impact on the simulated convective precipitation. The cross-equatorial flow and the Somali Jet are better represented in the SA simulation than those in the Indian domain simulation. The vertically integrated moisture flux over the Arabian Sea in the SA domain simulation is close to that in the NCEP/NCAR reanalysis while it is underestimated in the Indian domain simulation. It is important to note that when RegCM4.2 is integrated over the smaller Indian domain, the effects of the Himalayas and the moisture advection from the Indian seas are not properly represented in the model simulation and hence the monsoon circulation and associated rainfall are underestimated over India.

Impact of data assimilation on high‐resolution rainfall forecasts: A spatial, seasonal, and category analysis

AbstractIn a limited area model (LAM), the impact of data assimilation is likely to depend on the background state through lateral boundary forcing; this may introduce certain seasonality in the impact of data assimilation on rainfall forecasting. It is also likely that the impact of data assimilation on forecasts will have certain spatial variability. Finally, owing to the convective nature of rainfall and the roles of parameterization scheme, the impact of data assimilation may depend on the category (intensity) of rainfall. Here these aspects for rainfall forecasts at high resolution were examined. Using a LAM (An advanced version of Weather Research and Forecasting Model), we have carried out twin simulations with and without data assimilation; the simulations without data assimilation are used as the benchmark for assessing the impact of data assimilation. Analysis of simulations for 40 sample days distributed over the years 2012–2014 over Karnataka (southern state in India) is carried out to estimate impact of data assimilation. Various statistical measures show that data assimilation improved the rainfall prediction in most cases; however, there is also strong seasonality and location dependence in impact of data assimilation. Our results also show that improvement due to data assimilation is higher/lower for lower/higher rainfall categories. Analysis shows that the cases where the initial states with data assimilation depart strongly from the first guess generally result in less or even negative impact. It is pointed out that the results have important implications in design of observation system and assessment of impact of forecasts.

A Numerical Study of Mesoscale Model Initialization with Data Assimilation

Data for model analysis derived from the finite volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4) and the Land Data Assimilation System (LDAS) have been utilized in a mesoscale model. These data are tested to provide initial conditions and lateral boundary forcings to the Purdue Mesoscale Model (PMM) for a case study of the Midwestern flood that took place from 21-23 May 1998. The simulated results with fvGCM and LDAS soil moisture and temperature data are compared with that of ECMWF reanalysis. The initial conditions of the land surface provided by fvGCM/LDAS show significant differences in both soil moisture and ground temperature when compared to ECMWF control run, which results in a much different atmospheric state in the Planetary Boundary Layer (PBL). The simulation result shows that significant changes to the forecasted weather system occur due to the surface initial conditions, especially for the precipitation and temperature over the land. In comparing precipitation, moisture budgets, and surface energy, not only do the intensity and the location of precipitation over the Midwestern U.S. coincide better when running fvGCM/LDAS, but also the temperature forecast agrees better when compared to ECMWF reanalysis data. However, the precipitation over the Rocky Mountains is too large due to the cumulus parameterization scheme used in the PMM. The RMS errors and biases of fvGCM/LDAS are smaller than the control run and show statistical significance supporting the conclusion that the use of LDAS improves the precipitation and temperature forecast in the case of the Midwestern flood. The same method can be applied to Korea and simulations will be carried out as more LDAS data becomes available.

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

Abstract This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (R-2) data are downscaled to 36 km × 36 km by nudging only at the lateral boundaries, using gridpoint (i.e., analysis) nudging and using spectral nudging. Seven annual simulations are conducted and evaluated for 1988 by comparing 2-m temperature, precipitation, 500-hPa geopotential height, and 850-hPa meridional wind to the 32-km North American Regional Reanalysis (NARR). Using interior nudging reduces the mean biases for those fields throughout the CONUS compared to the simulation without interior nudging. The predictions of 2-m temperature and fields aloft behave similarly when either analysis or spectral nudging is used. For precipitation, however, analysis nudging generates monthly precipitation totals, and intensity and frequency of precipitation that are closer to observed fields than spectral nudging. The spectrum of 250-hPa zonal winds simulated by the WRF model is also compared to that of the R-2 and NARR. The spatial variability in the WRF model is reduced by using either form of interior nudging, and analysis nudging suppresses that variability more strongly than spectral nudging. Reducing the nudging strengths on the inner domain increases the variability but generates larger biases. The results support the use of interior nudging on both domains of a two-way nest to reduce error when the inner nest is not otherwise dominated by the lateral boundary forcing. Nevertheless, additional research is required to optimize the balance between accuracy and variability in choosing a nudging strategy.

HadGEM2-AO를 강제자료로 사용한 SNURCM과 WRF의 동아시아 지역기후 모의

본 연구에서는 신뢰성 있는 국가표준 지역기후변화 시나리오 생산을 위해 현재기후에 대한 SNURCM과 WRF의 재현성을 검증하였다. 국립기상연구소에서 생산된 HadGEM2-AO 전구자료를 지역기후모형의 경계조건으로 사용하여 CORDEX 규준 하에 28년(1978-2005)간의 장기적분을 수행하였다. 두 모형은 연평균 지표 온도 분포를 관측과의 공간상관계수가 0.98 이상으로 매우 높은 일치성을 나타내었지만, 모형 영역의 북쪽 경계를 중심으로 한랭 편차를 공통적으로 보였다. 강수의 경우 또한 육지 지역을 대상으로 한 관측과의 공간 상관 계수는 SNURCM이 0.85, WRF가 0.79로 나타나 우수한 모의 결과를 보였다. 두 모형에서 모의된 강수 분포는 적도와 중위도 지역 간에 상반되는 특성을 보였다. SNURCM은 WRF에 비교하여 중위도 동아시아 몬순 강수대의 분포를 적도 지역의 강수대보다 상대적으로 잘 모의하였으나, WRF는 그 반대의 결과를 나타내었다. 여름철(JJA) 보다 봄철(MAM)에 과다 모의되었지만 모의된 강수 분포의 일치성은 봄철에 높게 나타났다. 세부영역 별 분석에서 두 모형은 7월 강수 최대 시점과 양을 비교적 정확히 모의하였고, 특히 내륙 지역 강수량의 모의 정확도가 해양에 영향 받는 지역보다 높았다. 모의결과는 한반도 상의 높은 일평균 지표온도일수와 강한 강수일수를 표현하는데 한계를 보였다. In this study, the reproducibility of the simulated current climate by using two regional climate models, such as Seoul National University Regional Climate Model (SNURCM) and Weather Resuearch and Forecasting (WRF), is evaluated in advance to produce the standard regional climate scenario of future climate. Within the evaluation framework of a COordinated Regional climate Downscaling EXperiment (CORDEX), 28-year-long (1978-2005) regional climate simulation was conducted by using the Hadley Centre Global Environmental Model (HadGEM2-AO) global simulation data of the National Institute of Meteorological Research (NIMR) as a lateral boundary forcing. The simulated annual surface temperatures were in good agreement with the observation; the spatial correlation coefficients between each model and observation were over 0.98. The cold bias, however, were shown over the northern boundary in the both simulated results. In evaluation of the simulated precipitation, the skill was reasonable and good. The spatial correlation coefficients for the precipitation over the land area were 0.85 and 0.79 in SNURCM and WRF, respectively. It is noted that two regional climate models (RCMs) have different characteristics for the distribution of precipitation over equatorial and midlatitude areas. SNURCM shows better distribution of the simulated precipitation associated with the East Asia summer monsoon in the mid-latitude areas, but WRF shows better in the equatorial areas in comparison to each other. The simulated precipitation is overestimated in summer season (JJA) rather than in spring season (MAM), whereas the spatial distribution of the precipitation in spring season corresponds to the observation better than in summer season. Also the RCMs were capable of reproducing the annual variability of the maximum amount and its timing in July, in which the skills over the inland area were in better agreement with the observation than over the maritime area. The simulated regional climates, however, have the limitation to represent the number of days for extremely hot temperature and heavy rainfall over South Korea.

Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing

Reduction of uncertainty in large-scale lateral-boundary forcing in regional climate modeling is a critical issue for improving the performance of regional climate downscaling. Numerical simulations of 1998 East Asian summer monsoon were conducted using the Weather Research and Forecast model forced by four different reanalysis datasets, their equal-weight ensemble, and Bayesian model averaging (BMA) ensemble means. Large discrepancies were found among experiments forced by the four individual reanalysis datasets mainly due to the uncertainties in the moisture field of large-scale forcing over ocean. We used satellite water–vapor-path data as observed truth-and-training data to determine the posterior probability (weight) for each forcing dataset using the BMA method. The experiment forced by the equal-weight ensemble reduced the circulation biases significantly but reduced the precipitation biases only moderately. However, the experiment forced by the BMA ensemble outperformed not only the experiments forced by individual reanalysis datasets but also the equal-weight ensemble experiment in simulating the seasonal mean circulation and precipitation. These results suggest that the BMA ensemble method is an effective method for reducing the uncertainties in lateral-boundary forcing and improving model performance in regional climate downscaling.

Reduction of systematic biases in regional climate downscaling through ensemble forcing

Simulations of the East Asian summer monsoon for the period of 1979–2001 were carried out using the Weather Research and Forecast (WRF) model forced by three reanalysis datasets (NCEP-R2, ERA-40, and JRA-25). The experiments forced by different reanalysis data exhibited remarkable differences, primarily caused by uncertainties in the lateral boundary (LB) moisture fluxes over the Bay of Bengal and the Philippine Sea. The climatological mean water vapor convergence into the model domain computed from ERA-40 was about 24% higher than that from the NCEP-R2 reanalysis. We demonstrate that using the ensemble mean of NCEP-R2, ERA-40, and JRA-25 as LB forcing considerably reduced the biases in the model simulation. The use of ensemble forcing improved the performance in simulated mean circulation and precipitation, inter-annual variation in seasonal precipitation, and daily precipitation. The model simulated precipitation was superior to that in the reanalysis in both climatology and year-to-year variations, indicating the added value of dynamic downscaling. The results suggest that models having better performance under one set of LB forcing might worsen when another set of reanalysis data is used as LB forcing. Use of ensemble mean LB forcing for assessing regional climate model performance is recommended.