Regional Climate Model Experiments Research Articles

Did recent sea surface temperature warming reinforce the extreme East Asian summer monsoon precipitation in 2020?

We analyzed the possible effects of recent sea surface temperature (SST) warming on the extraordinary East Asian summer monsoon (EASM) precipitation in 2020 summer. The dynamic and thermodynamic impacts of SST are examined by conducting regional climate model experiments with observed SST and cold SST where the 22-year SST trend is removed. In the presence of warm SST, precipitation increases in low latitudes but decreases in the EASM region. This dipolar precipitation change pattern opposes the precipitation anomalies in 2020 summer, indicating that the extraordinary 2020 EASM precipitation is not likely driven by recent SST warming. The warm SST suppresses the western North Pacific subtropical high expansion and weakens the southwesterly from the South China Sea toward the EASM region. In terms of large-scale atmospheric circulations, SST-induced wind changes strengthen the local Walker circulation in the South China Sea and the Philippines and the local Hadley circulation across the EASM region. These support the reduced EASM rainfall in the control experiment compared to the cold SST experiment and imply that the precipitation reduction by dynamical effects could exceed the precipitation increase by thermodynamic effects in the EASM region under warm SST.

Projected changes in heatwaves and its impact on human discomfort over India due to global warming under the CORDEX-CORE framework

Due to climate change, rapid warming and its further intensification over different parts of the globe have been recently reported. This has a direct impact on human health, agriculture, water availability, power generation, various ecosystems, and socioeconomic conditions of the exposed population. The current study thus investigates the frequency and duration of heatwaves, human discomfort, and exposure of the human population to these extremes using the high-resolution regional climate model experiments under two Representative Concentration Pathways (RCP2.6, RCP8.5) over India. We find that more than 90% of India will be exposed to uncomfortable warm nights by the end of the 21st century with the highest rise over western India, Madhya Pradesh (MP), Uttar Pradesh (UP), Punjab, and the Haryana region. States like Odisha, Chhattisgarh, eastern parts of MP and UP, and some parts of J&K will be the worst hit by the intense and frequent heatwaves and human discomfort followed by the densely populated Indo-Gangetic plains under RCP8.5. Strict enforcement of the stringent policies on stabilization of population growth, improvement of local adaptive capacities, and economic status of the vulnerable population along with enforcing effective measures to curb greenhouse gas emissions are important to reduce human exposure to future heat stress. We demonstrate that a proper mitigation-based development (RCP2.6) instead of a business-as-usual scenario (RCP8.5) may help to reduce 50–200 heatwave days, 3–10 heatwave spells, and 10–35% warm nights over the Indian region. Consequently, this can avoid the exposure of 135–143 million population to severe discomfort due to extreme heat conditions by the end of the 21st century.

Analyzing the influences of the selection of the RCP scenario and the reference period on the evaluation results of EURO‐CORDEX simulations for Hungary

AbstractTemperature and precipitation simulations are evaluated for Hungary based on 11 regional climate model experiments with 0.1° horizontal resolution from the EURO‐CORDEX programme. The aim of the study is to assess the different simulations and the multi‐model (MM) mean as well for 1991–2005 and 2006–2020 separately, on a monthly basis. For the period 2006–2020, three different representative concentration pathway (RCP) scenarios, namely, RCP2.6, RCP4.5 and RCP8.5 are taken into consideration, so the uncertainty arising from the radiative forcing pathways can also be analysed. Specifically, we addressed three questions: (i) Which is the best model simulation for 1991–2005 and for 2006–2020? (ii) Which scenario is closer to the observations, regarding the period 2006–2020? (iii) Which has a greater effect: the selection of the model or the scenario? According to our results, the spatial and the annual distribution of temperature is simulated appropriately by the MM mean, however, in the case of precipitation the maximum values occur in spring, instead of summer. In 2006–2020, in the first half of the year, simulated temperature is closer to the observations, when the RCP8.5 scenario is taken into account. However, in the case of precipitation, the MM mean of RCP4.5 driven simulations generally performed the best. In the investigated period, the selection of the model simulation has a greater effect compared to the selection of the scenario.

The potential of an increased deciduous forest fraction to mitigate the effects of heat extremes in Europe

Abstract. Deciduous forests are characterized by a higher albedo, a reduced stomatal resistance, and a deeper root system in comparison to coniferous forests. As a consequence, less solar radiation is absorbed and evapotranspiration is potentially increased, making an increase in the deciduous forest fraction a potentially promising measure to mitigate the burdens of heat extremes for humans and nature. We analyze this potential by means of an idealized 30-year-long regional climate model (RCM) experiment, in which all coniferous forests in Europe are replaced by deciduous forests and compared to a simulation using the actual forest composition. Results show that an increase in the deciduous forest fraction reduces the heat intensity during heat periods in most regions of Europe. During heat periods, there is a slight reduction in the mean daily maximum 2 m temperatures simulated of about 0.2 K locally and 0.1 K non-locally. Regions with a high cooling potential are southwestern France and northern Turkey, where heat period intensities are reduced by up to 1 K. Warming effects are simulated in Scandinavia and eastern Europe. Although the cooling effect on heat period intensities is statistically significant over large parts of Europe, the magnitude of the temperature reduction is small. Consequently, an increase in the deciduous forest fraction only has a limited potential to reduce heat period intensities in Europe and can therefore only be considered as a supporting mitigation measure to complement more effective mitigation strategies.

Comprehensive future projections for the line-shaped convective system associated with Baiu front in Japan under RCP scenarios using regional climate model and pseudo global warming experiments

Herein, climate change projections of localized extreme rainfall associated with the Baiu front (Baiu extreme rainfall) are investigated from June to August in Japan under two representative concentration pathway scenarios (RCP2.6 and RCP8.5) by analyzing the numerical simulations of a 5-km-mesh high-resolution regional climate model (NHRCM05), which gives us the probabilistic future projections by using ensemble simulations, and by conducting Pseudo Global Warming (PGW) experiments for two typical events (Kameoka heavy rainfall in 2012 and Hiroshima heavy rainfall in 2014) with the cloud-resolving model, which enables us to elucidate the mechanisms of future change. The NHRCM05 analysis revealed that the frequency of Baiu extreme rainfall would increase by 1.2-times under RCP2.6 and by ≥ 1.5-times under RCP8.5 compared with the present climate. Moreover, the maximum total rainfall would increase due to global warming. To elucidate the mechanisms of rainfall intensification, the PGW experimental results were analyzed. 2012-Kameoka PGW analysis revealed that the rainfall increasing rate was almost twofold compared to the theoretical Clausius-Clapeyron scaling, which was attributed to a nonlinear effect of intensification of the back-building dynamical structure by the convergence in the lower level and the strengthening of the updraft, resulting in localization of water vapor into the cumulonimbus that cause much more buoyancy. Meanwhile, 2014-Hiroshima event experiments indicated that the rainfall decreased with global warming due to water vapor consumption in upstream areas. However, the PGW of 2014-Hiroshima possibly happened to show a decreasing trend as further NHRCM05 analysis of events similar to 2014-Hiroshima showed an increasing trend in rainfall. This study highlights the importance of predicting future changes by combining results obtained from various methods, including climate model analysis or PGW, with a profound understanding of the implications and feature of each result as well as the fact that disaster prevention and adaptation measures are urgently needed.

The substantial role of May soil temperature over Central Asia for summer surface air temperature variation and prediction over Northeastern China

The slowly varying soil temperature can exert local and nonlocal influences on regional climate system, and may thus provide a critical source of subseasonal-to-seasonal climate prediction. In this study, we identify that soil temperature in May over the key region of Central Asia (42 °N–50 °N, 62 °E–80°E, KRCA) from Noah, Mosaic, CLM and ERA-interim datasets is closely linked to variations of the surface air temperature, daily maximum temperature and hot days over Northeastern China in summer (June–July–August), with correlation coefficients of regional average detrended time series ranging from 0.42 to 0.54, and all significant at the 99% confidence level for the period of 1979–2018. The possible physical mechanism behind the substantial downstream impacts of soil temperature over Central Asia are explored via diagnostical analysis combined with regional climate model experiments. Warmer soil temperature in May over the KRCA can keep to the summer and cause positive anomalies of geopotential height in summer over Northeastern China through the Rossby wave propagation, and associated stronger subsidence warming, less cloud cover, more solar radiation reaching the surface, higher planetary boundary layer, and stronger thermal advection at 850 hPa, which provide favorable conditions for warmer surface air temperature particularly in the daytime as well as more hot days. This study further reveals that soil temperature over Central Asia in May makes important contribution to prediction of summer surface air temperature, daily maximum temperature and hot days over Northeastern China in terms of regional average time series and spatial patterns. Our findings highlight the previously-unknown substantial role of antecedent soil temperature condition over Central Asia for summer surface air temperature variation and prediction over Northeastern China.

Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

Abstract. Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario–GCM–RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central–eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 ∘C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

West African monsoon precipitation impacted by the South Eastern Atlantic biomass burning aerosol outflow

The West African Monsoon (WAM) is a complex system depending on global climate influences and multiple regional environmental factors. Central and Southern African biomass-burning (SABB) aerosols have been shown to perturb WAM during episodic northward inter-hemispheric transport events, but a possible dynamical connection between the core of the SABB aerosol outflow and the WAM system remains unexplored. Through regional climate modeling experiments, we show that SABB aerosols can indeed impact WAM dynamics via two competitive regional scale and inter-hemispheric dynamical feedbacks originating from (i) enhanced diabatic heating occurring in the Southeastern Atlantic low-cloud deck region, and (ii) aerosol and cloud-induced sea surface temperature cooling. These mechanisms, related to aerosol direct, semi-direct, and indirect effects, are shown to have different seasonal timings, resulting in a reduction of June to September WAM precipitation, while possibly enhancing late-season rainfall in WAM coastal areas.

Contrasting Responses of Local Climate to the Perturbation of Atmospheric Boundary Layer Winds Linked to Land‐Atmosphere Interactions

AbstractThe atmospheric boundary layer (ABL) is an interface through which the land surface influences the atmosphere and is crucial to land‐atmosphere (L‐A) interactions. Winds are an important element of the ABL, but their role in L‐A interactions is still partly unclear. Here, we use regional climate model experiments to investigate the impact of ABL winds on intraseasonal climate variabilities in East Asia. Two ensemble experiments were performed: one is a control ensemble, and the other is a perturbed ensemble, in which the ABL winds are shuffled from corresponding ensemble members of the control ensemble to produce a random perturbation of ABL winds. We found that the climates of the ensemble members become less similar in humid southern China, but generally more similar in semiarid northern China/Mongolia (NCM), especially for the mean values of several variables. The weather in southern China strongly responds to ABL winds and becomes less similar after perturbation. In NCM, however, the strong L‐A positive feedbacks, which involve wind field change in response to land surface changes and tend to cause large weather and climate anomalies, are weakened by the ABL wind perturbations. Thus, the inter‐member divergences of related variables, including surface temperature, sensible heat flux, soil moisture, and to some extent precipitation, are smaller and their time series are more similar. Clearly, the different L‐A interactions in these two regions are the main reason for the contrasting responses of local climate to the ABL wind perturbations.

Climate Change Projections of Aridity Conditions in the Iberian Peninsula

The assessment of aridity conditions is a key factor for water management and the implementation of mitigation and adaptation policies in agroforestry systems. Towards this aim, three aridity indices were computed for the Iberian Peninsula (IP): the De Martonne Index (DMI), the Pinna Combinative Index (PCI), and the Erinç Aridity Index (EAI). These three indices were first computed for the baseline period 1961–1990, using gridded observational data (E-OBS), and subsequently, for the periods 2011–2040 (short range) and 2041–2070 (medium range), using an ensemble of six regional climate model (RCM) experiments generated by the EURO-CORDEX project. Two representative concentration pathways (RCPs) were analyzed, an intermediate anthropogenic radiative forcing scenario (RCP4.5) and a fossil-intensive emission scenario (RCP8.5). Overall, the three indices disclose a strengthening of aridity and dry conditions in central and southern Iberia until 2070, mainly under RCP8.5. Strong (weak) statistically significant correlations were found between these indices and the total mean precipitation (mean temperature) along with projected significant decreasing (increasing) trends for precipitation (temperature). The prevalence of years with arid conditions (above 70% for 2041–2070 under both RCPs) are projected to have major impacts in some regions, such as southern Portugal, Extremadura, Castilla-La Mancha, Comunidad de Madrid, Andalucía, Región de Murcia, Comunidad Valenciana, and certain regions within the Aragón province. The projected increase in both the intensity and persistence of aridity conditions in a broader southern half of Iberia will exacerbate the exposure and vulnerability of this region to climate change, while the risk of multi-level desertification should be thoroughly integrated into regional and national water management and planning.

Urban-climate interactions during summer over eastern North America

The urban heat island is a representative urban climate characteristic, which can affect heat-stress conditions and extreme precipitation that are closely connected with human life. Better understanding of urban-climate interactions, therefore, is crucial to ultimately support better planning and adaptation in various application fields. This study assesses urban-climate interactions during summer for eastern North America using regional climate model simulations at 0.22° resolution. Two regional climate model experiments, with and without realistic representation of urban regions, are performed for the 1981–2010 period. Comparison of the two experiments shows higher mean temperatures and reduced mean precipitation in the simulation with realistic urban representation, which can be attributed primarily to reduced albedo and soil moisture for the urban regions in this simulation. Furthermore, the mean temperature and precipitation in the simulation with improved urban representation is also closer to that observed. Analysis of short-duration precipitation extremes for climatologically different sub-regions, however, suggests that, for higher temperatures, the magnitudes of precipitation extremes are generally higher in the simulation with realistic urban representation, particularly for coastal urban regions, and are collocated with higher values of convective available potential energy and cloud fraction. Enhanced sea and lake breezes associated with lower sea level pressure found around these regions, contribute additional water vapor and further enhance dynamic convective development, leading to higher precipitation intensities. Analysis of temperature extremes clearly demonstrates that urban regions experience aggravated heat-stress conditions due to relatively higher temperatures despite reduced relative humidity. Double the number of extreme heat spells lasting six or more days are noted for the coastal urban regions in the study domain. This study, in addition to demonstrating the differences in urban-climate interactions for climatologically different regions, also demonstrates the need for better representation of urban regions in climate models to generate realistic climate information.

Time of emergence of climate signals over Vietnam detected from the CORDEX‐SEA experiments

AbstractThis study uses six regional climate model (RCM) experiments from the Coordinated Regional Climate Downscaling Experiment—Southeast Asia (CORDEX‐SEA) and their driving global climate models (GCM) to investigate the model performance and the time of emergence (ToE) of temperature and precipitation over Vietnam and its seven sub‐climatic regions. A simple delta (multiplicative) bias correction (BC) method has been applied to the model temperature (precipitation). Results show clear added values of the BC downscaled products compared to their driving GCMs, particularly for temperature. The projected trends of RCM temperature during 2006–2100 under two representative concentration pathway (RCP) RCP4.5 and RCP8.5 scenarios are similar to those of their driving GCMs. Consequently, the RCM‐based ToE and GCM‐based ToE are generally consistent for temperature, occurring in the beginning of the 21st century. The earliest and latest ToE occur in summer and winter, respectively. The seasonal differentiation for temperature‐ToEs is stronger in the northern areas compared to the southern areas of Vietnam. The ToE difference between two RCPs increases from the south to the north. As for precipitation, ToE occurs quite late, in the latter half of the 21st century at the earliest. Results from ToE estimations also indicate an opposite precipitation trend between the GCMs and RCMs. The largest difference is in summer over the southern region of Vietnam. The opposite trend between the GCM and RCM precipitation under a similar increasing temperature implies the uncertainty in assessing the impact of warming on hydrological cycles in Vietnam.

The North Atlantic High-Resolution Regional Climate Model Experiment for Oceanic and Atmospheric Applications

We present a high-resolution historical analysis of the atmosphere over the North Atlantic for the period from January 1979 to December 2018. The dataset was obtained using the nonhydrostatic atmospheric model WRF-ARW version 3.8.1 and contains two experiments that differ in spatial resolution: 14 km (HiRes) and 77 km (LoRes). Except for the spatial resolution, the configuration remained identical in both experiments: 50 vertical sigma-levels (starting from ~12 m up to 50 hPa); ERA-Interim reanalysis was used as forcing and spectral nudging. The dataset for HiRes and LoRes experiments was named NAAD (North Atlantic Atmospheric Downscaling). Preliminary results of both HiRes and LoRes reveal good agreement with observations and the ERA-Interim, ERA5, and ASRv2 reanalyses. The NAAD dataset is available online at http://www.naad.ocean.ru and provides a variety of surface and upper-troposphere atmospheric variables with a time step of 3 h.

Evaluation for Characteristics of Tropical Cyclone Induced Heavy Rainfall over the Sub-basins in The Central Hokkaido, Northern Japan by 5-km Large Ensemble Experiments

Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin.

Contribution of Snow Cover Decline to Projected Warming Over North America

AbstractGiven the critical role that snow plays in modulating current climate, it is vital to examine the contribution of the projected snow decline to the future warming. This is investigated over North America using regional climate modeling experiments with prescribed current and future snow conditions. Results indicate that the decline in snow contributes to future warming by up to 2°C and 4°C, respectively, to annual and spring temperature increases. Results also show that decline in snow depth and cover lead to the attenuation (amplification) of cold (warm) extremes. The rate of intensification of warm extremes is higher over the snow‐abundant regions of northern Canada—where current snow cover fraction is close to one. The largest attenuation in cold extremes, on the other hand, is over snow marginal regions of the Great Plains and Prairies. These results demonstrate the spatiotemporal differences in projected changes exclusively associated with snow cover and depth decline.

Assessment of Indian summer monsoon variability in a regional climate model coupled to a slab ocean model

A suite of Regional Climate Model (RegCM) experiments are performed over south Asia to examine the skill of RegCM to simulate the seasonal and sub-seasonal mean features of Indian summer monsoon (ISM). Because of coupled nature of ISM, three model experiments with RegCM are conducted to examine the skill of coupled and uncoupled configurations of RegCM by forcing it with observed SST (Exp1), coupling it to a simple slab ocean model (SOM) with constant mixed layer depth (MLD; Exp2) and with climatology of MLD (Exp3). The coupled experiments show an overall improvement in several aspects of ISM variability at seasonal and intraseasonal time-scales, despite bias in simulated SSTs. Between coupled experiments; Exp3 reduces biases in SST distribution over the region to the north of Arabian Peninsula, eastern Arabian Sea (AS), and broadly over north Indian Ocean (NIO). Noteworthy is the improved precipitation over central India (CI), head Bay of Bengal (BoB), as well as the representation of easterly wind shear in coupled experiments. At intraseasonal time scales, Exp3 produces spectral peaks above red noise at 25–50-day and 15–20-day periods closely representing the northward propagating intraseasonal mode and quasi-biweekly oscillating mode as in observed precipitation. The improved representation of spatial distribution of intraseasonal activity over NIO as well as the SST and precipitation relationships over head BoB and eastern AS is attributed to better representation of air-sea interaction in Exp3. In brief, the coupling improves the model skill for the true representation of mean ISM variability during boreal summer, and the thorough evaluation of model for longer periods is required to employ it as a downscaling tool for regional climate change studies.

Impacts of Green Vegetation Fraction Derivation Methods on Regional Climate Simulations

The representation of vegetation in land surface models (LSM) is crucial for modeling atmospheric processes in regional climate models (RCMs). Vegetation is characterized by the green fractional vegetation cover (FVC) and/or the leaf area index (LAI) that are obtained from nearest difference vegetation index (NDVI) data. Most regional climate models use a constant FVC for each month and grid cell. In this work, three FVC datasets have been constructed using three methods: ZENG, WETZEL and GUTMAN. These datasets have been implemented in a RCM to explore, through sensitivity experiments over the Iberian Peninsula (IP), the effects of the differences among the FVC data-sets on the near surface temperature (T2m). Firstly, we noted that the selection of the NDVI database is of crucial importance, because there are important bias in mean and variability among them. The comparison between the three methods extracted from the same NDVI database, the global inventory modeling and mapping studies (GIMMS), reveals important differences reaching up to 12% in spatial average and and 35% locally. Such differences depend on the FVC magnitude and type of biome. The methods that use the frequency distribution of NDVI (ZENG and GUTMAN) are more similar, and the differences mainly depends on the land type. The comparison of the RCM experiments exhibits a not negligible effect of the FVC uncertainty on the monthly T2m values. Differences of 30% in FVC can produce bias of 1 ∘ C in monthly T2m, although they depend on the time of the year. Therefore, the selection of a certain FVC dataset will introduce bias in T2m and will affect the annual cycle. On the other hand, fixing a FVC database, the use of synchronized FVC instead of climatological values produces differences up to 1 ∘ C, that will modify the T2m interannual variability.

Modification of Near‐Surface Temperature Over East Asia Associated With Local‐Scale Paddy Irrigation

AbstractThis study used two regional climate model experiments to assess the impact of paddy irrigation in the Sichuan Basin, China, on the near‐surface temperature across East Asia: a control experiment (CTL run), which was used to calculate soil moisture using an unmodified land surface scheme and a sensitivity experiment (SEN run) that incorporated an increase in soil moisture over the basin at the beginning of the rice‐growing season. Although the near‐surface temperature in the Sichuan Basin was higher in the CTL run than in the observations, it improved in the SEN run because of a change in the Bowen ratio associated with the increase in soil moisture. In the SEN run, the modification of local‐scale land surface wetness in the basin causes the decrease in the near‐surface temperature over northeastern China and its increase over southern China relative to that in the CTL run because of a change in the cloud convection associated with precipitation, which, in turn, modifies the solar and net radiation at the surface and the partitioning into the sensible and latent heat fluxes. The greenhouse effect associated with an increase in precipitable water in the SEN run also influences near‐surface warming over southeastern China and the ocean north of southwestern Japan, where the impacts of radiation processes and surface heat fluxes on the near‐surface temperature are small. Consequently, these results suggest that local‐scale modifications to land surface wetness in the Sichuan Basin result in changes in the spatial distribution of near‐surface temperatures over a part of East Asia.

Dynamical downscaling the impact of spring Western US land surface temperature on the 2015 flood extremes at the Southern Great Plains: effect of domain choice, dynamic cores and land surface parameterization

Recent studies have shown that spring land surface temperature (LST) and subsurface temperature (SUBT) over the high elevation areas in the western US (WUS) have significant impacts on the downstream summer droughts/floods in North America. In this paper, both the National Centers for Environmental Prediction—Global Forecast System (NCEP-GFS) general circulation model (GCM) and the weather research and forecasting (WRF) regional climate model (RCM) are employed, where RCM scenarios utilized initial and lateral boundary conditions derived from the corresponding NCEP-GFS scenarios. Here we use a late spring flood in the US Southern Great Plains (SGP) case to examine whether simulation of the LST/SUBT downstream effects is sensitive to the domain size choice, change in dynamical cores within the same model, as well as to the representation of surface processes parameterizations. Although all RCM experiments with different settings simulate reasonably geographical patterns of observed LST and precipitation anomalies, we found that the choice of the domain size is crucial for proper downscaling the LST/SUBT downstream effects to accurately produce the observed precipitation/LST anomalies over the SGP/WUS, respectively, along with the associated large-scale features. The southern boundary location has been identified to be crucial in producing the SGP Low Level Jet strength, which in turn brings more moisture from the Gulf of Mexico to the SGP and thereby resulting in a better simulation of the precipitation anomaly in that area. The sensitivity of the simulation of the LST/SUBT downstream effect to dynamical cores is assessed by inter-comparing the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF dynamic cores. We find NMM was better at generating the large-scale eastward wave train, a crucial process associated with the LST/SUBT downstream effect. Meanwhile, this study also shows that the LST/SUBT downstream effects were not significantly dependent on the surface process parameterizations, although the Simplified Simple Biosphere model version 3 (SSiB3) highlighted a better performance over SSiB2.

Role of soil moisture-atmosphere feedback during high temperature events in 2002 over Northeast Eurasia

In summer 2002, abnormally high-temperature events and associated low soil moisture conditions were observed in Northeast Eurasia. In this study, two regional climate model experiments, one with and the other without soil moisture–atmosphere interaction, were conducted to investigate the role of soil moisture in surface air temperature and precipitation in Northeast Eurasia utilizing the Weather Research and Forecasting (WRF) model. In the experiment without interaction, satellite-based soil moisture was prescribed. Under the persistent mid-tropospheric ridge pattern with prolonged clear skies, both experiments captured the magnitude of the extreme surface air temperature events. A comparison of the model experiments demonstrated that the mid-tropospheric ridge pattern was intensified by dry soil moisture conditions that further increase the surface air temperature. The temporal variability of surface air temperature for the experiments with and without soil moisture–atmosphere interaction reveals the strong coupling of soil moisture to surface air temperature in June–August, raising the possibility that extreme hot temperature events in Northeast Eurasia were strengthened by the soil moisture anomaly. These results also indicate that the impact of soil moisture–atmosphere coupling on surface air temperature varies spatially and temporally, having higher importance for the predictability of extreme high-temperature events in Northeast Eurasia during mid-summer. This also suggests that the performance of the land surface model in simulating appropriate land–atmosphere coupling intensity is a key to evaluating the impact of climate change on extreme heat events in this region.