Regional Climate Model RegCM4 Research Articles

Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing–Tianjin–Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing–Tianjin–Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Modeling the effects of the plastic-mulched cropland over the arid and semi-arid areas of China on the East Asian regional climate

Arid and semi-arid areas of Northwest China are extremely sensitive to climate change. Plastic mulch is a technology used worldwide to inhibit soil evaporation and increase crop yield. The properties of plastic film are significantly different from the soil. Plastic mulch not only alters the physical attributes of the underlying surface, but also blocks the energy and mass exchanges between the land surface and the atmosphere. This latter situation has not been depicted in current regional climate models. This study couples a detailed plastic mulch layer submodel considering the effects of the plastic mulch on the radiation and heat transfer into the regional climate model RegCM4.5 to explore the effects of plastic mulch on East Asian regional climate over Northwest China. Results suggest that the plastic film covering cropland can enhance the near surface sensible heat transfer, accelerate the rise of near surface air temperature, and reduce the water vapor supply of convective process. Meanwhile, the rainfall is reduced in Northwest China and most areas south of the Yangtze River, while the precipitation is improved from Sichuan and Chongqing to North and Northeast China when the cropland underlying surface is covered by the plastic film. Moreover, the cyclone of the lower troposphere in Northwest China is strengthened and the air pressure is weakened, which promotes the subtropical high to the northwest, thus East Asian summer monsoon is influenced because of the plastic film mulching.

Comparison of RegCM4.7.1 Simulation with the Station Observation Data of Georgia, 1985–2008

The global climate change, driven by natural processes and increasing human activities, is especially significant for Georgia. The region is experiencing increases in temperature, desertification, redistribution of precipitation, and a rise in the frequency and severity of extreme weather events. Georgia’s complex topography and its proximity to the Black and Caspian seas make it essential to employ high-resolution regional climate models to evaluate future climate change risks. In this study, we examine the results of a high-resolution simulation of mean and extreme precipitation and temperature using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4.7.1 for the period 1985–2008, providing an initial evaluation of the model’s performance for the territory of Georgia. The model domain (1524 km; 2388 km) encompasses the entirety of Georgia’s territory and surrounding regions. The simulation, conducted at a 12 km horizontal grid spacing using ERA5 data as boundary conditions, indicates that the least discrepancy between observed and modeled average annual temperatures and precipitation, falling within a −1 to 1 °C and −200 to 200 mm range, respectively, was observed at most stations of eastern Georgia. The largest disparities between the model and observed average annual precipitation totals were noted along the Black Sea coast, in the Kolkheti Lowland, and in some high mountain stations in western Georgia. The most significant differences in average annual temperatures between the model and observations were observed in Ambrolauri, Mt. Sabueti, and Dedoplistskaro. For Georgia territory, such a long run with such a high resolution using ERA5 as boundary conditions was conducted for the first time. Overall, the modeling results are quite satisfactory, providing a solid basis for the successful utilization of the regional climate model RegCM4.7.1 with the selected parameterization for modeling monthly mean and extreme temperatures and precipitation in Georgia.

Historical meteorological droughts over the CORDEX‐CAM (Central America, Caribbean and Mexico) domain: Evaluating the simulation of dry hot spots with RegCM4

AbstractHistorical meteorological droughts are analysed over the Coordinated Regional Downscaling Experiment‐Central America, Caribbean and Mexico (CORDEX‐CAM) domain during 1981–2010, with particular emphasis on the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. We analyse droughts based on the standardized precipitation index (SPI‐12) and the standardized precipitation‐evapotranspiration index (SPEI‐12) using observations from CRU, CHIRPS, GPCP and ERA5‐Land reanalysis (ERA5), and assess the skill of the regional climate model RegCM4 (version 7) at 25 km resolution driven by ERA‐Interim (Reg‐ERA) and by three global climate models (Reg‐GCMs: Reg‐Had, Reg‐MPI and Reg‐GFDL). Observational data sets show large spatial variations in drought frequency, and both Reg‐ERA and Reg‐GCMs have difficulties simulating it. RegCM4 shows positive precipitation and water balance biases over mountain regions and negative ones over Central America, possibly due to the complex terrain and poor observational data coverage. Despite differences among observations, the trend in droughts, duration and severity show consistent dry hot spots (regions with long‐duration severe droughts) over the western United States, the United States‐Mexico border region, the NAM, the Yucatan Peninsula and northern Central America, with stronger values of SPEI‐12 than SPI‐12, particularly over the subtropical regions. Reg‐ERA and ERA5 show similar spatial patterns and similar positive and negative spatial biases relative to observations. Reg‐ERA and Reg‐Had adequately simulate the spatial patterns of the trend, duration and severity of droughts, with smaller biases in SPI‐12 than SPEI‐12; in contrast, Reg‐MPI and Reg‐GFDL overestimate the trend biases over northwest CAM. Observations, reanalysis, and RegCM4 capture an inverse drought response between the NAM and the MSD regions linked to climate teleconnections; however, a stronger drought signal is observed in the NAM, which appears to be linked to decadal variations from negative to positive phases of the Atlantic Multidecadal Oscillation combined with La Niña conditions (negative El Niño 1+2 phase).

Impact of urbanization on fine particulate matter concentrations over central Europe

Abstract. Rural-to-urban transformation (RUT) is the process of turning a rural or natural land surface into an urban one, which brings about important modifications in the surface, causing well-known effects like the urban heat island (UHI), reduced wind speeds, and increased boundary layer heights. Moreover, with concentrated human activities, RUT introduces new emission sources which greatly perturb local and regional air pollution. Particulate matter (PM) is one of the key pollutants responsible for the deterioration of urban air quality and is still a major issue in European cities, with frequent exceedances of limit values. Here we introduce a regional chemistry–climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, (i) urban emissions and (ii) urban canopy meteorological forcing (UCMF; i.e. the impact of modified meteorological conditions on air quality), we also analyse two less studied contributors to RUT's impact on air quality: (iii) the impact of modified dry-deposition velocities (DVs) due to urbanized land use and (iv) the impact of modified biogenic emissions due to urbanization-induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations, whereby each contributor is added one by one to the reference state, while focus is given on PM2.5 (particulate matter with diameter less then 2.5 µm). Its primary and secondary components, namely primary elemental carbon (PEC), sulfates (PSO4), nitrates (PNO3), ammonium (PNH4), and secondary organic aerosol (SOA), are analysed too. The validation using surface measurements showed a systematic negative bias for the total PM2.5, which is probably caused by underestimated organic aerosol and partly by the negative bias in sulfates and elemental carbon. For ammonium and nitrates, the underestimation is limited to the warm season, while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured. We evaluated the RUT impact on PM2.5 over a sample of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µg m−3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µg m−3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µg m−3 (in both seasons), which was mainly controlled by enhanced vertical eddy diffusion, while increases were modelled over rural areas. The transformation of rural land use into an urban one caused an increase in dry-deposition velocities by around 30 %–50 %, which alone resulted in a decrease in PM2.5 by 0.1–0.25 µg m−3 in both seasons. Finally, the impact of biogenic emission modifications due to modified land use and meteorological conditions caused a decrease in summer PM2.5 of about 0.1 µg m−3, while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µg m−3 for PEC, 0.05 and 0.02 µg m−3 for PSO4, 0.1 and 0.08 µg m−3 for PNO3, 0.04 and 0.03 µg m−3 for PNH4, and 0 and 0.05 µg m−3 for SOA. The main contributor of each of these components was the impact of emissions, which was usually larger than the total impact due to the fact that UCMF was counteracted with a decrease. For each aerosol component, the impact of modified DV was a clear decrease in concentration, and finally, the modifications of biogenic emissions impacted SOA predominantly, causing a summer decrease, while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased). In summary, we showed that when analysing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one also has to consider the effect of modified land use and its impact on dry deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that they act on PM2.5 predominantly through SOA modifications, which only turned out to be important during summer.

Effects of Potential Large-Scale Irrigation on Regional Precipitation in Northwest China

Understanding the impact of irrigation on the spatiotemporal characteristics of precipitation is important for the ecological stability of the arid region of Northwest China (NWC). In this study, the global climate model MPI-ESM-MR is utilized to provide the initial and lateral boundary conditions for the regional climate model RegCM4, enabling the simulation of the long-term climate of the arid NWC region under two Representative Concentration Pathways (RCPs). The study focuses on analyzing the differences in the spatiotemporal distribution, intensity, and frequency of precipitation before and after irrigation. Furthermore, the study explores the primary factors influencing changes in the spatiotemporal distribution characteristics of precipitation in the irrigation district and its downwind region. The results indicate that RegCM4 performs well in simulating the climatology and diurnal cycle of precipitation in the NWC, particularly excelling during the summer. Large-scale irrigation significantly impacts the structure of summer precipitation, leading to a notable increase in convective precipitation near the irrigation district and surrounding mountain ranges. Anomalous cyclonic circulation and enhanced vertical velocity enhancement provide dynamic conditions for increased precipitation in the irrigation district and surrounding mountainous regions. Furthermore, the evaporation of water vapor resulting from large-scale irrigation serves as an additional source of moisture, contributing to increased precipitation in the irrigation district and its downwind region. Due to the difference in climatic conditions between the western and eastern regions around the irrigated areas, the summer extreme precipitation in the west predominantly increases. At the same time, in the east, it predominantly decreases due to irrigation. The findings of this study contribute to a deeper understanding of the physical mechanisms through which agricultural irrigation influences precipitation in the arid region of the NWC, thereby providing scientific evidence for the sustainable utilization of water resources in the region.

Comparison between statistical and dynamical downscaling of rainfall over the Gwadar‐Ormara basin, Pakistan

AbstractThis paper evaluated and compared the performance of a statistical downscaling method and a dynamical downscaling method to simulate the spatial–temporal rainfall distribution. Outputs from RegCM4 Regional Climate Model (RCM) and the CanESM2 Atmosphere–Ocean General Circulation Model (AOGCM) were selected for the data scarce Gwadar‐Ormara basin, Pakistan. The evaluation was based on the climatological average and standard deviation for historic (1971–2000) and future (2041–2070) time periods under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. The performance evaluation showed that statistical downscaling is preferred to simulate and project rainfall patterns in the study area. Additionally, the Statistical DownScaling Model (SDSM) showed low R2 values in calibration and validation of the simulations with respect to observed data for the historic period. Overall, SDSM generated satisfactory results in simulating the monthly rainfall cycle of the entire basin. In this study, RegCM4 showed large rainfall errors and missed one rainfall season in the historic period. This study also explored whether the grid‐based rainfall time series of the Asian Precipitation—Highly Resolved Observational Daily Integration Towards Evaluation (APHRODITE) dataset could be used to enlarge and complement the sample of in situ observed rainfall time series. A spatial correlogram was used for observed and APHRODITE rainfall data to assess the consistency between the two data sources, which resulted in rejecting APHRODITE data. For the future time period (2041–2070) under RCPs 4.5 and 8.5 scenarios, rainfall projections did not show significant difference for both downscaling approaches. This may relate to the driving model (CanESM2 AOGCM) and not necessarily suggests poor performance of downscaling; either statistical or dynamical. Hence, the study recommends evaluating a multi‐model ensemble including other GCMs and RCMs for the same area of study.

Frequency and Intensity of Cyclonic Systems in CORDEX RCMs Model Environment under the Future Emission Scenarios

Tropical Cyclonic Disturbances (TCDs) are one of the most extreme meteorological calamities bringing destruction to life and livelihood in the coastal societies across the globe. With the rising concerns of climate change today, addressing the TCDs in future scenarios under the representative concentration pathways (RCPs) in climate models becomes a necessity. The current study investigates the frequency and intensity of these cyclonic systems in future climate over the Bay of Bengal (BoB) which is one of most vulnerable regions on earth for deadliest TCDs. To assess the TCDs frequency and intensity, we have considered TCDs in regional climate model REMO2009 and RegCM4 in future climatic conditions. The future climatic conditions include the intermediate emissions (IE) represented as RCP4.5 (R4.5) and high emission (HE) pathways i.e., RCP8.5 (R8.5). For this, we have considered the upcoming decades 2031-2060 (as near future climate) at model horizontal resolution 0.44°x0.44° (spatial resolution ~ 50 km) under both RCPs in both models i.e., REMO2009 under R4.5, RegCM4 under R4.5, REMO2009 under R8.5 and RegCM4 under R8.5. The projected TCD frequencies in the models under both the RCPs show high occurrence frequencies. Further, we observe a bimodal characteristic in the occurrence with October as primary TCD active month and May as secondary in almost all conditions. However, highly intense TCDs are more dominant in the month of May. The projected TCDs in future emissions scenarios likely show slightly increased TCDs besides surge in the intensity. The current results possibly suggest more potential destructive impacts due to TCDs on the coastal societies lying beside the BoB in upcoming decades. Thus, the present study is likely to help in framing TCDs associated mitigation and adaptation policies by the apex decision making authorities.

Predicting Changes in Population Exposure to Precipitation Extremes over Beijing–Tianjin–Hebei Urban Agglomeration with Regional Climate Model RegCM4 on a Convection-Permitting Scale

In this study, we have investigated changes in precipitation extremes and the population’s exposure to these extremes during 2091–2099 in China’s Beijing–Tianjin–Hebei (JJJ) region relative to the historical period of 1991–1999. First, the regional climate model RegCM4, with a hydrostatic dynamic core, was run for east Asia, including China, at a 12 km resolution for 1990–1999 and 2090–2099. This model is forced by global climate model (GCM) MPI-ESM1.2-HR under the middle shared socioeconomic pathways (SSP245). The first year was used as a model spinup. Then, the 12 km results were used to force RegCM4 with a non-hydrostatic dynamic core (RegcM4-NH) at a 3 km convection-permitting scale over the JJJ region during the historical and future periods. Future precipitation extremes were predicted to increase over the whole of China and its four subregions, while decreases were predicted over the JJJ region. This may partly be caused by lower increases in specific humidity over the JJJ region. The percentage contributions of the three components of total population exposure, i.e., changes in exposure due to changes in the population, precipitation extremes and the joint impact of the population and extremes, were then analyzed. Changes in the population and wet extremes were closely related to changes in the total exposure over the JJJ region. The population is the dominant factor that most impacts the total exposure to dry extremes. Finally, changes in future population exposure to precipitation extremes per degree of warming were quantified for the JJJ region.

Assessment and improvement of RegCM 4.6 coupled with CLM4.5 in simulation of land surface temperature in mainland China

Land surface temperature(LST) is an important indicator to study climate change and test the performance of regional climate model simulation. RegCM4.6 is the representative version of regional climate model RegCM, which is coupled with advanced third-generation land surface model NCAR CLM4.5. Currently, RegCM4.6 has become an important tool to study regional climate change in China. However, its ability to simulate land surface temperature in mainland China and the reasons for its deviation have not been systematically studied, and targeted improvement work is lacking. The present study is the first to employ LST data collected from 809 Chinese meteorological stations from the last 30 years to comprehensively assess the ability of CLM4.5 to simulate LST. Sensitivity tests of soil thermal conductivity (STC) were carried out to improve the model. Although the coupled regional climate model could accurately simulate the temporal and spatial variation of LST, a cold bias of 2~8 °C existed for all of mainland China, which was larger in seasons with more precipitation and greater soil moisture than other seasons. Deviation increased from southeast to northwest. which was caused by the incoming long-wave radiation, sensible heat, and latent heat simulated. There was a significant linear relationship between the observed and simulated LSTs, with correlation coefficients for all the stations ranged from 0.75 to 0.9 (P < 0.001). The observed LST increased at a rate of 0.58 °C/decade, but the simulated LST increased at a lower rate. Assessment of three different STC schemes showed that the Lu-Ren scheme was the most suitable for LST simulation in mainland China. Developing a new STC scheme that considers the role of water vapor can effectively improve the model when used in mainland China.

Assessment of performance of the regional climate model (RegCM4.6) to simulate winter rainfall in the north of Morocco: The case of Tangier-Tétouan-Al-Hociema Region

We examine the performance of the regional climate model RegCM v4.6 to simulate spatial variability of precipitation in the northwestern region of Morocco during the winter of 2009–2010. Simulations cover 24 months from 2009 to 2010 with 30 km as a horizontal grid. We use NCEP reanalysis as forcing data and for better comparison of results, observed precipitations derived from CRU, CHIRPS, and CMORPH data. Results indicate that, on the whole, the RegCM4 model represents appropriate regional aspects of rainfall over the study area but underestimates precipitations over mountainous and Mediterranean regions of the study area (Case of Tangier-Tétouan-Al-Hociema Region) which is probably due to poor representation of orography in the Model and some aspects of local Mediterranean climate. Projected precipitations are also examined in this work in comparison with the reference period of 1970–2005, with simulations performed by RegCM 4.6 regional model for the period 2023–2099 under scenarios RCP4.5 and RCP8.5, forced by HadGEM2-ES General Circulation Model. Results show a decrease in precipitations mean for (2023–2099) for both RCP4.5 and RCP8.5 scenarios over the study area in comparison with the historical period (1970–2005), with a significant decrease under RCP8.5 scenarios. This work proves that the RegCM v4.6 model can be used for regional climate prediction, particularly for the spatial distribution of precipitation, but for sectorial applications and impact studies, the Model outputs should be bias corrected.

Analysis of climate extremes indices in tropical South America through the RegCM4.7

AbstractIn recent decades, the frequency and intensity of extreme weather events induced by global warming have increased significantly, exerting serious impacts on the development of society and ecosystems. Based on low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios from the Intergovernmental Panel on Climate Change, we use the general circulation model HadGEM2‐ES that is part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to drive the regional climate model RegCM4.7. This study evaluated the ability of both models to simulate (1986–2005) and projection (2080–2099) spatio‐temporal features of extreme indices over tropical South America (TSA). Indices based on precipitation and daily maximum and minimum temperature follow the definitions of the Expert Team on Climate Change Detection and Indices (ETCCDI). In general, the RegCM4.7 reproduces accordingly the spatial distribution of the ETCCDI indices derived from precipitation and temperature on the TSA, in addition to added value to HadGEM2‐ES, especially over regions of complex topography. HadGEM2‐ES performs poorly along the west coast, due to the topography and altitude of the Andes. On the other hand, it demonstrates better performance in the Amazon Basin compared to RegCM4.7. The projection results showed that climate extreme indices based on precipitation and temperature indicate that drought events may advance to the end of the century, showing a spatial pattern that precipitation will be gradually reduced in the Amazon Basin and Northeast region of Brazil. Despite some discrepancies between the models, studies like this one help us to understand how climate change can affect regional planning and development.

Analysis of the Outdoor Microclimate and the Effects on Greek Cultural Heritage Using the Heritage Microclimate Risk (HMR) and Predicted Risk of Damage (PRD) Indices: Present and Future Simulations

This study aims to assess the impacts of climate change on the cultural heritage of two Greek areas for both the present time and the future. As the climate is constantly evolving, cultural heritage is continuously exposed to the risk of damage and deterioration. Therefore, museum directors and boards as well as the national ministries must be informed so that measures and practices are adapted to the new climatic conditions. Greece is a country with immense cultural wealth, both tangible and intangible, which stretches back four and a half thousand years. As a homeland of important historical and cultural resources, Greece is vulnerable to climate change. Two up-to-date indices were applied to two Greek areas with high cultural value: Thessaloniki and Delphi. In order to evaluate the suitability of the microclimate and to assess the damage risk, the Heritage Microclimate Risk (HMR) index and the Predicted Risk of Damage (PRD) index were used for two variables: temperature and relative humidity. The study was carried out for three different time periods, the period 1980–2000 (hereafter, the reference period) and the future periods 2039–2059 and 2079–2099. For the reference period, data from three different sources were incorporated in the study (observed, reanalysis, and model data). The simulated data were derived from the Regional Climate Model RegCM4 with a fine spatial resolution of 10 × 10 km. In addition, the emission scenario RCP4.5 was used for the model’s future simulations. The present and future ideal outdoor climate conditions for the monuments were also estimated and are presented in this work. Overall, the future estimations revealed that the ideal outdoor temperature conditions will be higher compared to the reference period, meaning that the monuments will have to adapt to new warmer climate conditions. In addition to the new temperature conditions to which the monuments will have to adapt, the study showed that the monuments will be exposed to “moderate-maximum” risk more often in the future.

Dynamic downscaling of climate simulations and projected changes in tropical South America using RegCM4.7

AbstractHigh‐resolution (dx = 25 km) simulations of the regional climate model RegCM4.7 coupled with the Community Land Model version 4.5 (CLM4.5) under low (RCP2.6) and high (RCP8.5) emissions scenarios, which interact with the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (AR5‐IPCC), were carried out over tropical South America (TSA). These simulations were produced through boundary conditions from simulations driven by the general circulation model HadGEM2‐ES. With the goal of verifying the added value (AV) of RegCM4.7, reproducing in an adequate and coherent way the regional aspects of the historical period (1986–2005), as well as evaluating the regional aspects simulated by the model in the scope of the change projections for the far‐future (2080–2099). For this study, the climate in the TSA was characterized based on the variables of precipitation and near‐surface air temperature. For the evaluation of the spatial–temporal representation, frequency and distribution of the regional and global simulation, the high‐resolution observational dataset of the Climate Research Unit version ts4.02 (CRU) was used. Although some differences and biases still persist, RegCM4.7 presents AV in the spatial representation of precipitation and temperature over the northeast region of Brazil and part of the Andes, especially in winter. However, it does not adequately represent precipitation over the Amazon Basin, especially in summer. Results for future projections indicate that the more refined simulation of RegCM4.7 improves the projected change patterns of the coarser resolution simulation of HadGEM2‐ES and even modifies the precipitation signal in some cases. Both models project increase temperature with greater magnitude for RCP8.5. RegCM4.7 presents a much more refined and realistic spatial distribution. HadGEM2‐ES simulates the major aspects of climate enough to consider forcing RegCM4.7 to generate simulations with better performance and more realistic projections.

Future fire risk under climate change and deforestation scenarios in tropical Borneo

Fire in the tropical peatland forests of Borneo is an environmental issue interactioning with climate change and deforestation, and the consequences have local and global implications. While research has shown that fire severity and frequency are expected to increase with climate change, there is conflicting model and observational data as to the effect of deforestation on precipitation, which is a key metric for fire risk. To better understand the changes in fire risk from deforestation and climate change we ran simulations of the climate scenario RCP8.5 with and without total deforestation using regional climate model RegCM4. The output was then used for calculations of the fire weather index. We find that annual temperature change from deforestation at elevations above 500 m is 53% of the change over the 21st century in RCP8.5. Fire risk is significantly affected by both climate change and deforestation, despite some increases in precipitation from deforestation. While the multi model dry season (June–August) mean increases in fire risk are larger from elevated atmospheric carbon dioxide, the increases in maximum fire risk are larger from deforestation. The altitude is a good predictor of fire risk change, with larger increases at more densely populated lower elevations where the peatlands are concentrated and smaller increases at higher elevations. Therefore, while deforestation generally causes a smaller increase in climate-related fire risk than climate change, its local control and heterogeneous effects compared to global carbon emissions makes it critical for climate mitigation policy. These high-resolution simulations provide a guide to the most vulnerable areas of Borneo from climatic increases in fire risk.

Estimates of the accuracy and rate of convergence of short-term meteorological forecasts using the regional climate model RegCM4

We use the regional climate model RegCM 4.9 for the territory of Southern Russia to estimate the accuracy of meteorological forecasts. The errors of meteorological and climatic forecasts is due to complex non-equilibrium physicochemical processes in the components of the Earth's geosystem, which are characterized by gasdynamic and thermal instabilities at various spatial scales. A method for assessing the convergence of forecasts based on time series analysis is discussed for various localities. The reliability of forecasts for temperatures up to 1 degree can lie within 5-10 days for the south of the European part of Russia, depending on the predominance of cyclonic or anticyclonic atmospheric movements. The interval of acceptable precipitation forecast, as a rule, does not exceed 2-4 days for an area of about 104km2 and greatly decreases with decreasing area of the region under consideration. The annual volume of precipitation correlates in the cities of Rostov-on-Don and Volgograd at the level of 70 percent with each other. The correlation between the Rostov-on-Don City or the Volgograd City on the one hand, and the cities Astrakhan, Stavropol, Elista on the other hand, turns out to be significantly less, ranging from 30 to 40 percent.

Effects of Soil Thermal Conductivity on Rainy Season Precipitation in Northern China

Abstract Parameterization schemes such as soil thermal conductivity (STC) have an important impact on precipitation simulation. The precipitation in the rainy season (April–September) is the main factor affecting aridification in northern China. However, it is unclear how STC affects precipitation simulation during the rainy season. In this study, comparative experiments were conducted using the regional climate model RegCM4.6 coupled with the third-generation land surface model NCAR CLM4.5 to assess the effect of the Johansen and Lu–Ren STC schemes on precipitation. The results show that the STC had a significant effect on the simulation of rainy season precipitation and its variation in northern China. The precipitation variation characteristics simulated by the Lu–Ren scheme were closer than that of the Johansen scheme to the observation. The difference in land surface temperatures (LSTs) simulated by the two STC schemes could be a major cause of the sensitivity in the simulated precipitation. When the local LST increases by 1 K, precipitation decreases by 5–30 mm in most areas of northern China. The numerical experiments revealed that the rise of LST increases the longwave radiation, reduces the surface net radiation, and causes the redistribution of sensible and latent heat flux, forming local water vapor and thermal conditions that are not conducive to precipitation. Moreover, the difference of LST significantly changes the 500-hPa large-scale circulation field, the 700-hPa vapor transportation, and its divergence. The combined action of local heat, water vapor, and large-scale circulation factors reduces the precipitation in the rainy season. On the other side, the variation of the East Asia summer monsoon (EASM) affects the soil water content. In addition, a new STC scheme was added to NCAR CLM4.5, promoting the development of this land surface model.

Modeling the impacts of the energy closure degree over the arid and semiarid areas of China on the East Asian regional climate

Arid and semiarid areas are extremely sensitive to climate change. The atmospheric boundary layer in these areas acts as a major factor of matter exchange and energy transport for the land–atmosphere interactions. In this study, two turbulent transfer parameterization schemes respectively with surface energy closure and unclosure based on the Lanzhou university Semi-Arid Climate Observatory and Laboratory (SACOL) station are coupled into a regional climate model RegCM4.5 (referred to as Exp-BALANCE and Exp-IMBALANCE) to explore the effects of the surface energy closure degree on the East Asian summer monsoon simulations. The results show that the surface soil temperature simulated by Exp-BALANCE is lower than that simulated by Exp-IMBALANCE because energy transferred from the underlying surface increases so that the energy retained in the underlying surface decreases in Exp-BALANCE, which weakens sensible heat transport and decreases the surface air temperature in the case of Exp-BALANCE. This is because the net radiation absorbed by the underlying surface for Exp-BALANCE is in agreement with Exp-IMBALANCE, while the soil temperature simulated by Exp-BALANCE is lower than that of Exp-IMBALANCE. Compared with Exp-IMBALANCE, Exp-BALANCE can contribute to increasing the atmospheric energy, and more upward air flow begins to diverge as the anticyclonic circulation strengthens in the middle and upper tropospheres over the arid and semiarid regions. Consequently, the subtropical high moving to the northward is hindered, the rain belt stays in the South China for a long time, and the precipitation in Northeast China is reduced, but in the south of the Yangtze River, it is enhanced in the case of Exp-BALANCE.

Reforestation in Southern China Enhances the Convective Afternoon Rainfall During the Post-flood Season

Dynamic and continuous land use and cover change (LUCC) is one of the external forcing factors affecting regional climate in China. Based on the annual dynamic global land cover dataset derived from the Global Land Surface Satellite (GLASS-GLC), this paper modelled and investigated the effects of annual transient LUCC on precipitation over China using the regional climate model RegCM4.8.2. Analysis of the GLASS-GLC data revealed that considerable conversions of cropland to forest, grassland to cropland and bare ground to grassland had occurred during the last 3 decades (1984–2013) in southern, northeastern and northwestern China respectively. By comparing the differences between the two sets of experiments under the fixed LUCC and dynamic LUCC scenarios, the results showed that reforestation in southern China during the past 3 decades significantly enhanced local convective afternoon rainfall (CAR; ∼2 mm/day) during the post-flood season (POF; July-August-September). This reforestation effect on CAR also increased with the intensity of LUCC. However, the realistic LUCC effects were weak and negligible for other periods, regions and large-scale precipitation. Furthermore, we have identified two possible reasons that favored the occurrence of POFCAR, namely that the moisture and instability conditions required to trigger convections were both enhanced by reforestation. This was evidenced by increases (decreases) in convective available potential energy (lifting condensation level), increases in atmospheric water vapor content and declining tendencies of equivalent potential temperature with height. Overall, this study highlights the importance of reforestation impacts on the diurnal variations of the precipitation.

Effects of Land Cover Changes on Compound Extremes over West Africa Using the Regional Climate Model RegCM4

This study aims to characterize the impacts of the Sahel–Sahara interface reforestation on compound extremes in the Sahel region during the West African monsoon season (June–July–August–September, JJAS). For this purpose, we performed a simulation with the standard version of the RegCM4 model, and another simulation with the altered version of the same model, taking into account the incorporated forest. Results show that reforestation may strongly influence the frequency of individual extreme events (dry and warm days) by decreasing them over and off the reforested zone. The reduction in these extreme dry and warm days may be due partly to the strengthening of the atmospheric moisture content over most parts of the West African domain and the weakening of the sensible heat flux south of 16° N. The analysis also shows an increase in extreme wet days over and off the reforested zone, which could be associated partly with the strengthening of evapotranspiration over most parts of the West African domain, including the reforested area. The analysis of compound extremes shows a strong occurrence of the compound dry/warm mode over the northern Sahel for both runs, probably due to the weak precipitation recorded in this zone. Both experiments also simulated a strong compound wet/warm mode occurrence over the Sahel due to a high rainfall occurrence over this region. When comparing both runs, the impact of the reforestation was to decrease (increase) the compound extreme dry/warm (wet/warm) mode over the reforested zone. The dry/warm mode decrease is consistent with that of individual extreme dry and warm days, while the compound wet/warm mode increase may be driven by that of the extreme wet days. Finally, when considering the seasonal cycle, the dry/warm mode exhibits a more substantial decrease in the beginning (June–July, JJ) than during the peak of the West African summer monsoon season (August–September, AS). Moreover, reforestation similarly affects the compound wet/warm mode in JJ and AS by increasing it in the reforested region and decreasing it over the Southern Sahel (south of 15° N). This work suggests that reforestation may be a good solution for West African policymakers to mitigate climate change over the region and to develop better strategies for water resource management.