Simulation of paleoclimate over East Asia at 6 ka BP and 21 ka BP by a regional climate model

Using a regional climate model with detailed land surface processes (RegCM2), East Asian monsoon climates at 6 ka BP and 21 ka BP are simulated by prescribing vegetation and employing paleovegetation respectively in order to examine land surface effects on East Asian climate system and the potential mechanisms for climate change. The RegCM2 with a 120 × 120 km² resolution has simulated the enlargement of the seasonal cycle of insolation, the temperature rising the whole year, and the reduction of perpetual snow in high latitudes at 6 ka BP. The simulation shows the East Asian summer monsoon strengthening, precipitation and P–E increasing, and the monsoon rain belt shifting westwards and northwards. Effect of paleovegetation included in the modeling reduced surface albedo and caused an increase in the winter temperature, which led to weakening of the winter continental cold anticyclone over China. The results make the seasonal characteristics of simulated temperature changes in better agreement with the geological records, and are an improvement over previous simulations of Paleoclimate Modeling Intercomparison Project (PMIP). The RegCM2 simulated the 21 ka BP climate with lowered temperature throughout the year, and with precipitation reduced in most areas of East Asia (but increased in both the Tibetan Plateau and Central Asia). Low temperature over East Asia led to the strengthening of the East Asian winter monsoon and the shrinking of the summer monsoon. The effect of paleovegetation included in the experiment has enlarged the glacial climate influence in East Asia, which is closer to geological data than the PMIP simulations directly driven by insolation, glaciation and low CO₂ concentration.     

Can ensembles of regional climate model simulations improve results from sensitivity studies?

Intrinsic variability (IV) in regional climate models (RCMs) is often assumed to be small because at climatological timescales, the model solutions tend to be dominated by the model??s lateral boundary conditions. Recent studies have indicated that this IV may actually be large in certain instances for some variables. Direct interpretation of anomalies from RCM sensitivity studies relies on the assumption that differences between model simulations are entirely due to a physical forcing. However, if IV is as large or larger than the physical signal, then this assumption is violated. Using a 20 member ensemble of RCM simulations, we verify that IV of precipitation within a RCM can be large enough to violate the sensitivity study assumption, and we show that generating ensembles of simulations can help reduce the level of IV. We also present two indicators that can rule out the influence of IV when it is ambiguous whether anomalies within a sensitivity study are due to the sensitivity perturbation or whether they are due to IV.     

Investigation of regional climate models’ internal variability with a ten-member ensemble of 10-year simulations over a large domain

Previous investigations on regional climate models’ (RCM) internal variability (IV) were limited owing to small ensembles, short simulations and small domains. The present work extends previous studies with a ten-member ensemble of 10-year simulations performed with the Canadian Regional Climate Model over a large domain covering North America. The results show that the IV has no long-term tendency but rather fluctuates in time following the synoptic situation within the domain. The IV of mean-sea-level pressure (MSLP) and screen temperature (ST) show a small annual cycle with larger values in spring, which differs from previous studies. For precipitation (PCP), the IV shows a clear annual cycle with larger values in summer, as previously reported. The 10-year climatology of the IV for MSLP and ST shows a well-defined spatial distribution with larger values in the northeast of the domain, near the outflow boundary. A comparison of the IV of MSLP and ST in summer with the transient-eddy variance reveals that the IV is close to its maximum in a small region near the outflow boundary. Same analysis for PCP in summer shows that the IV reaches its maximum in most parts of the domain, except for a small region on the western side near the inflow boundary. Finally, a comparison of the 10-year climate of each simulation of the ensemble showed that the IV may have a significant impact on the climatology of some variables.     

Influence of PDO on South Asian summer monsoon and monsoon–ENSO relation

This study has investigated the possible relation between the Indian summer monsoon and the Pacific Decadal Oscillation (PDO) observed in the sea surface temperature (SST) of the North Pacific Ocean. Using long records of observations and coupled model (NCAR CCSM4) simulation, this study has found that the warm (cold) phase of the PDO is associated with deficit (excess) rainfall over India. The PDO extends its influence to the tropical Pacific and modifies the relation between the monsoon rainfall and El Niño-Southern Oscillation (ENSO). During the warm PDO period, the impact of El Niño (La Niña) on the monsoon rainfall is enhanced (reduced). A hypothesis put forward for the mechanism by which PDO affects the monsoon starts with the seasonal footprinting of SST from the North Pacific to the subtropical Pacific. This condition affects the trade winds, and either strengthens or weakens the Walker circulation over the Pacific and Indian Oceans depending on the phase of the PDO. The associated Hadley circulation in the monsoon region determines the impact of PDO on the monsoon rainfall. We suggest that knowing the phase of PDO may lead to better long-term prediction of the seasonal monsoon rainfall and the impact of ENSO on monsoon.     

Simulation of the Indian monsoon using the RegCM3–ROMS regional coupled model

A regional coupled atmosphere–ocean model was developed to study the role of air–sea interactions in the simulation of the Indian summer monsoon. The coupled model includes the regional climate model (RegCM3) as atmospheric component and the regional ocean modeling system (ROMS) as oceanic component. The two-way coupled model system exchanges sea surface temperature (SST) from the ocean to the atmospheric model and surface wind stress and energy fluxes from the atmosphere to the ocean model. The coupled model is run for four years 1997, 1998, 2002 and 2003 and the results are compared with observations and atmosphere-only model runs employing Reynolds SSTs as lower boundary condition. It is found that the coupled model captures the main features of the Indian monsoon and simulates a substantially more realistic spatial and temporal distribution of monsoon rainfall compared to the uncoupled atmosphere-only model. The intraseasonal oscillations are also better simulated in the coupled model compared to the atmosphere-only model. These improvements are due to a better representation of the feedbacks between the SST and convection and highlight the importance of air–sea coupling in the simulation of the Indian monsoon.     

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.     

Projected climate change scenario over California by a regional ocean–atmosphere coupled model system

This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.     

Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 2: future climate projection (2021–2050)

An analysis of simulated future surface climate change over the southern half of Korean Peninsula using a RegCM3-based high-resolution one-way double-nested system is presented. Changes in mean climate as well as the frequency and intensity of extreme climate events are discussed for the 30-year-period of 2021–2050 with respect to the reference period of 1971–2000 based on the IPCC SRES B2 emission scenario. Warming in the range of 1–4°C is found throughout the analysis region and in all seasons. The warming is maximum in the higher latitudes of the South Korean Peninsula and in the cold season. A large reduction in snow depth is projected in response to the increase of winter minimum temperature induced by the greenhouse warming. The change in precipitation shows a distinct seasonal variation and a substantial regional variability. In particular, we find a large increase of wintertime precipitation over Korea, especially in the upslope side of major mountain systems. Summer precipitation increases over the northern part of South Korea and decreases over the southern regions, indicating regional diversity. The precipitation change also shows marked intraseasonal variations throughout the monsoon season. The temperature change shows a positive trend throughout 2021–2050 while the precipitation change is characterized by pronounced interdecadal variations. The PDF of the daily temperature is shifted towards higher values and is somewhat narrower in the scenario run than the reference one. The number of frost days decreases markedly and the number of hot days increases. The regional distribution of heavy precipitation (over 80 mm/day) changes considerably, indicating changes in flood vulnerable regions. The climate change signal shows pronounced fine scale signal over Korea, indicating the need of high-resolution climate simulations     

Application of a “Big-Tree” model to regional climate modeling: a sensitivity study

Summary ¶In order to better understand land-atmosphere interactions and increase the predictability of climate models, it is important to investigate the role of forest representation in climate modeling. Corresponding to the big-leaf model commonly employed in land surface schemes to represent the effects of a forest, a so called big-tree model, which uses multi-layer vegetation to represent the vertical canopy heterogeneity, was introduced and incorporated into the National Center for Atmospheric Research (NCAR) regional climate model RegCM2, to make the vegetation model more physically based. Using this augmented RegCM2 and station data for China during 1991 Meiyu season, we performed 10 experiments to investigate the effects of the application of the big-tree model on the summer monsoon climate.With the big-tree model incorporated into the regional climate model, some climate characteristics, e.g. the 3-month-mean surface temperature, circulation, and precipitation, are significantly and systematically changed over the model domain, and the change of the characteristics differs depending on the area. Due to the better representation of the shading effect in the big-tree model, the temperature of the lower layer atmosphere above the plant canopy is increased, which further influences the 850hPa temperature. In addition, there are significant decreases in the mean latent heat fluxes (within 20–30W/m²) in the three areas of the model domain.The application of the big-tree model influences not only the simulated climate of the forested area, but also that of the whole model domain, and its impact is greater on the lower atmosphere than on the upper atmosphere. The simulated rainfall and surface temperature deviate from the originally simulated result and are (or seem to be) closer to the observations, which implies that an appropriate representation of the big-tree model may improve the simulation of the summer monsoon climate.We also find that the simulated climate is sensitive to some big-tree parameter values and schemes, such as the shape, height, zero-plane displacement height and mixing-length scheme. The simulated local/grid differences may be very large although the simulated areal-average differences may be much lower. The area-average differences in the monthly-mean surface temperature and heat fluxes can amount to 0.5°C and 4W/m², respectively, which correspond to maximum local/grid differences of 3.0°C and 40W/m² respectively. It seems that the simulated climate is most sensitive to the parameter of the zero-plane displacement among the parameters studied.     

Pre-onset land surface processes and ��internal�� interannual variabilities of the Indian summer monsoon

It is proposed that, land?Catmosphere interaction around the time of monsoon onset could modulate the first episode of climatological intraseasonal oscillation (CISO) and may generate significant ??internal?? interannual variation in the Indian summer monsoon rainfall. The regional climate model RegCM3 is used over Indian monsoon domain for 27?years of control simulation. In order to prove the hypothesis, another two sets of experiment are performed using two different boundary conditions (El Ni?o year and non-ENSO year). In each of these experiments, a single year of boundary conditions are used repeatedly year after year to generate ??internal?? interannual monsoon variability. Simulation of monsoon climate in the control model run is found to be in reasonably good agreement with observation. However, large rainfall bias is seen over Arabian Sea and Bay of Bengal. The interannual monsoon rainfall variability are of the same order in two experiments, which suggest that the external influences may not be important on the generation of ??internal?? monsoon rainfall variability. It is shown that, a dry (wet) pre-onset land-surface condition increases (decreases) rainfall in June which in turn leads to an anomalous increase (decrease) in seasonal (JJAS) rainfall. The phase and amplitude of CISO are modulated during May?CJune and beyond that the modulation of CISO is quite negligible. Though the pre-onset rainfall is unpredictable, significant modulation of the post-onset monsoon rainfall by it can be exploited to improve predictive skill within the monsoon season.     

Performance of GCMs for seasonal prediction over India��a case study for 2009 monsoon

The 2009 drought in India was one of the major droughts that the country faced in the last 100?years. This study describes the anomalous features of 2009 summer monsoon and examines real-time seasonal predictions made using six general circulation models (GCMs). El Ni?o conditions evolved in the Pacific Ocean, and sea surface temperatures (SSTs) over the Indian Ocean were warmer than normal during monsoon 2009. The observed circulation patterns indicate a weaker monsoon in that year over India with weaker than normal convection over the Bay of Bengal and Indian landmass. Skill of the GCMs during hindcast period shows that neither these models simulate the observed interannual variability nor their multi-model ensemble (MME) significantly improves the skill of monsoon rainfall predictions. Except for one model used in this study, the real-time predictions with longer lead (2- and 1-month lead) made for the 2009 monsoon season did not provide any indication of a highly anomalous monsoon. However, with less lead time (zero lead), most of the models as well as the MME had provided predictions of below normal rainfall for that monsoon season. This study indicates that the models could not predict the 2009 drought over India due to the use of less warm SST anomalies over the Pacific in the longer lead runs. Hence, it is proposed that the uncertainties in SST predictions (the lower boundary condition) have to be represented in the model predictions of summer monsoon rainfall over India.     

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.     

Impact of soil moisture�Catmosphere coupling on European climate extremes and trends in a regional climate model

Processes acting at the interface between the land surface and the atmosphere have a strong impact on the European summer climate, particularly during extreme years. These processes are to a large extent associated with soil moisture (SM). This study investigates the role of soil moisture?Catmosphere coupling for the European summer climate over the period 1959?C2006 using simulations with a regional climate model. The focus of this study is set on temperature and precipitation extremes and trends. The analysis is based on simulations performed with the regional climate model CLM, driven with ECMWF reanalysis and operational analysis data. The set of experiments consists of a control simulation (CTL) with interactive SM, and sensitivity experiments with prescribed SM: a dry and a wet run to determine the impact of extreme values of SM, as well as experiments with lowpass-filtered SM from CTL to quantify the impact of the temporal variability of SM on different time scales. Soil moisture?Cclimate interactions are found to have significant effects on temperature extremes in the experiments, and impacts on precipitation extremes are also identified. Case studies of selected major summer heat waves reveal that the intraseasonal and interannual variability of SM account for 5?C30% and 10?C40% of the simulated heat wave anomaly, respectively. For extreme precipitation events on the other hand, only the wet-day frequency is impacted in the experiments with prescribed soil moisture. Simulated trends for the past decades, which appear consistent with projected changes for the 21st century, are identified to be at least partly linked to SM-atmosphere feedbacks.     

An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation

We present an atmosphere–ocean regional climate model for the Mediterranean basin, called the PROTHEUS system, composed by the regional climate model RegCM3 as the atmospheric component and by a regional configuration of the MITgcm model as the oceanic component. The model is applied to an area encompassing the Mediterranean Sea and compared to a stand-alone version of its atmospheric component. An assessment of the model performances is done by using available observational datasets. Despite a persistent bias, the PROTHEUS system is able to capture the inter-annual variability of seasonal sea surface temperature (SST) and also the fine scale spatio-temporal evolution of observed SST anomalies, with spatial correlation as high as 0.7 during summer. The close inspection of a 10-day strong wind event during the summer of 2000 proves the capability of the PROTHEUS system to correctly describe the daily evolution of SST under strong air–sea interaction conditions. As a consequence of the model’s skill in reproducing observed SST and wind fields, we expect a reliable estimation of air–sea fluxes. The model skill in reproducing climatological land surface fields is in line with that of state of the art regional climate models.     

Impact of diurnal atmosphere–ocean coupling on tropical climate simulations using a coupled GCM

The impacts of diurnal atmosphere–ocean (air–sea) coupling on tropical climate simulations are investigated using the SNU coupled GCM. To investigate the effect of the atmospheric and oceanic diurnal cycles on a climate simulation, a 1-day air–sea coupling interval experiment is compared to a 2-h coupling experiment. As previous studies have suggested, cold temperature biases over equatorial western Pacific regions are significantly reduced when diurnal air–sea coupling strategy is implemented. This warming is initiated by diurnal rectification and amplified further by the air–sea coupled feedbacks. In addition to its effect on the mean climatology, the diurnal coupling has also a distinctive impact on the amplitude of the El Nino-Southern Oscillation (ENSO). It is demonstrated that a weakening of the ENSO magnitude is caused by reduced (increased) surface net heat fluxes into the ocean during El Nino (La Nina) events. Primarily, decreased (increased) incoming shortwave radiation during El Nino (La Nina) due to cloud shading is responsible for the net heat fluxes associated with ENSO.     

Multi-year variability or unidirectional trends? Mapping long-term precipitation and temperature changes in continental Southeast Asia using PRECIS regional climate model

The subject of change detection in climate time series has recently received greater interest as the perception of a human-induced change in the climate is now widely accepted. However, changes in regional precipitation and temperature remain uncertain. This study characterizes projected fine-scale changes in precipitation and temperature in continental Southeast Asia over the period 1960?C2049. Twenty four annual variables were derived from grid-based daily precipitation and temperature produced by the PRECIS regional climate model under A2 and B2 scenarios. These time series, capturing precipitation intensities (classified as low, medium and high), seasonality and extremes in precipitation and temperature, were subjected to the modified Mann-Kendall trend detection test accounting for long-term persistence. The results indicate that temperature increases over the whole region with steeper trends in higher latitudes. Increases in annual precipitation, mainly restricted to Myanmar and the Gulf of Thailand, result from increases in high precipitation during the wet season. Decreases are observed mainly over the sea and caused by a reduction of low precipitation. Changes in the occurrence of the monsoon affect the low-latitude sea areas only. By showing that significant precipitation change are minor over land areas, these results challenge most of the previous studies that suggested significant precipitation changes over Southeast Asia, often mixing up multi-decadal variability and long-term unidirectional trends. Significant changes in precipitation and temperature may induce higher agricultural yields as steepest temperature and precipitation increases will predominantly affect the coldest and driest land areas of the region.     

The sensitivity of the Indian summer monsoon to a global warming of 2��C with respect to pre-industrial times

In this study the potential future changes in different aspects of the Indian summer monsoon associated with a global warming of 2°C with respect to pre-industrial times are assessed, focussing on the role of the different mechanisms leading to these changes. In addition, these changes as well as the underlying mechanisms are compared to the corresponding changes associated with a markedly stronger global warming exceeding 4.5°C, associated with the widely used SRES A1B scenario. The study is based on two sets of four ensemble simulations with the ECHAM5/MPI-OM coupled climate model, each starting from different initial conditions. In one set of simulations (2020?C2200), greenhouse gas concentrations and sulphate aerosol load have been prescribed in such a way that the simulated global warming dioes not exceed 2°C with respect to pre-industrial times. In the other set of simulations (1860?C2200), greenhouse gas concentrations and sulphate aerosol load have been prescribed according to observations until 2000 and according to the SRES A1B scenario after 2000. The study reveals marked changes in the Indian summer monsoon associated with a global warming of 2°C with respect to pre-industrial conditions, namely an intensification of the summer monsoon precipitation despite a weakening of the large-scale monsoon circulation. The increase in the monsoon rainfall is related to a variety of different mechanisms, with the intensification of the atmospheric moisture transport into the Indian region as the most important one. The weakening of the large-scale monsoon circulation is mainly caused by changes in the Walker circulation with large-scale divergence (convergence) in the lower (uppper) troposphere over the Indian Ocean in response to enhanced convective activity over the Indian Ocean and the central and eastern Pacific and reduced convective activity over the western tropical Pacific. These changes in the Walker circulation induce westerly (easterly) wind anomalies at lower (upper) level in the Indian region. The comparison with the changes in the Indian summer monsoon associated with a global warming of 4.5°C reveals that both the intensification of the monsoon precipitation and the weakening of the large-scale monsoon circulation (particularly in the lower troposphere) are relatively strong (with respect to the magnitude of the projected global warming by the end of the twentieth century for the two scenarios) in the scenario with a global warming of 2°C. The relatively strong intensification of the monsoon rainfall is related to rather strong increases in evaporation over the Arabian Sea and the Bay of Bengal, while a rather weak amplification of the meridional temperature gradient between the Indian Ocean and the land areas to the north contributes to the relatively strong reduction of the large-scale monsoon flow.     

Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation?

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south–east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south–east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level.