Biosphere-Atmosphere Transfer Scheme Research Articles

Performance of regional climate model RegCM4 with a hydrostatic or non‐hydrostatic dynamic core at simulating precipitation extremes in China

AbstractIn this study, we investigated the performance of RegCM4 with a hydrostatic or non‐hydrostatic dynamic core and different land surface models at simulating the mean and extreme precipitation during 1991–1999 in China and the Beijing–Tianjin–Hebei urban agglomeration (JJJ) in northern China. The resolutions were 12 km with the whole of China included and 3 km nested over the JJJ region. The observed daily precipitation data comprised the CN05.1 data set from China Meteorological Administration. First, RegCM4 with a hydrostatic dynamic core forced by the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR) that participated in CMIP6 was used to simulate the east Asia area at a resolution of 12 km. Next, the RegCM4 results with 12 km resolution forced RegCM4 with a non‐hydrostatic dynamic core (RegCM4‐NH) to run over the JJJ region with a 3 km convection‐permitting scale through one‐way nesting. The results showed that RegCM4 with a hydrostatic and non‐hydrostatic core could obtain more detailed seasonal and annual precipitation in China and the JJJ region relative to MPI‐ESM1.2‐HR although their performance varied over different regions. RegCM4 with the community land surface model 4.5 (CLM4.5) generally performed better at simulating the mean and extreme precipitation over the four subregions of China than that with the Biosphere–Atmosphere Transfer Scheme because of more detailed descriptions of land surface processes of CLM4.5. RegCM4‐NH with convection‐permitting resolution improved the simulations of heavy precipitation extremes over JJJ compared with RegCM4 with a hydrostatic core and resolution of 12 km. In addition, RegCM4‐NH with CLM4.5 performed better at simulating heavy precipitation extremes over JJJ compared with all other simulations, with higher correlation coefficients and larger relative root mean squared errors.

Sensitivity experiments of RegCM4 using different cumulus and land surface schemes over the upper reaches of the Yangtze river

For the optimal performance of climate simulation, it is critical to localize physical parameterization schemes of climate models, especially in regions with unique geographic characteristics. To study the performance of different physical parameterization schemes for climate simulation in the upper reaches of the Yangtze River Basin (UYRB), we conducted short-term simulations with a resolution of 50 km from 1990 to 1993 using RegCM4 driven by ERA-Interim. Simulations with 72 different scheme combinations were conducted and analyzed to identify the optimal cumulus convection schemes (CSs) and the land surface process schemes in the RegCM4 model. Using the multi-standard scoring method, we evaluated the model performance of precipitation and temperature over the UYRB with different physical parameterization schemes. The results show that precipitation is more sensitive to the CSs than the LSPs. Among the selected CSs, the Kain-Fritsch scheme can better reproduce precipitation characteristics of the UYRB, with a wet bias of only 0.2 mm/day for the multi-year average precipitation. Compared to the community land model (CLM 3.5 and CLM4.5), the Biosphere-Atmosphere Transfer Scheme (BATS) performs better in reproducing temperature characteristics of the UYRB, with an average cold bias of only 0.2°C for all BATS schemes. The soil moisture, evapotranspiration and precipitation are lower and sensible heat flux is higher in CLM simulations, which can account for CLMs simulating warmer temperatures than BATS. The results provide a baseline for the localization of the RegCM4’s parameterization schemes in the UYRB and other regions of China.

Evaluation and Optimization of Snow Albedo Scheme in Noah‐MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies

AbstractThe Biosphere‐Atmosphere Transfer Scheme (BATS) ground snow albedo algorithm is commonly used in land‐surface models (LSM), weather forecasting and research applications. This study addresses key uncertainties in BATS simulated ground snow albedo within the Noah‐MP LSM framework through evaluation and optimization of the Noah‐MP BATS ground snow albedo formulation using 2‐band (visible and near‐infrared (NIR)) in situ albedo observations at Rocky Mountain field stations. The Noah‐MP BATS ground snow albedo scheme is extremely sensitive to its input parameters. Namely, an ensemble generated by varying BATS input parameters within potentially plausible ranges provides an average daily range (maximum ensemble member minus minimum ensemble member) of ground snow albedo exceeding 0.45 in visible and NIR bands. Parameter optimization improves agreement between simulated and in situ observed ground snow albedo in visible, NIR and broadband spectrums. Importantly, optimized parameters result in reduced biases relative to observed fresh‐snow albedo and better agreement with observed albedo decay. Our analysis across different sites supports that the optimized BATS ground snow albedo parameters are appropriate to transfer in space and time, at least within the region studied (the central‐southern Rocky Mountains). The primary error source remaining after parameter optimization is that observed fresh‐snow albedo is highly variable, particularly in the NIR spectrum, whereas BATS fresh‐snow albedo is constant, an issue which requires further investigation. This study shows significant correlations between observed fresh‐snow albedo and surface meteorological conditions (e.g., downward shortwave radiation and temperature) which can support future model development that attempts to include a time‐varying formulation for fresh‐snow albedo.

Simulation of Northeast Monsoon in a coupled regional model framework

The rainfall during Northeast Monsoon (NEM) meets most of the water demand and influences the socioeconomic condition of the population in the southern part of India. The present study focuses to identify a better, coupled land-atmosphere combination using regional downscaling experiments with RegCM4 for representing the mean characteristics of the NEM rainfall. Three suites of model integrations are made using three different land-surface schemes such as Biosphere-Atmosphere Transfer Scheme (BATS), Subgrid-BATS (SUB), and Community Land Model version 4.5 (CLM). The CLM experiment shows a better spatial representation of the rainfall due to the better representation of the moisture flux and convection, whereas the BATS and SUB experiments show strong wet bias (1–6 mm/yr) over Tamilnadu and Kerala. The spatial correlation of the climatological rainfall with respect to observation is maximum (0.5–0.6) for the CLM. However, the model experiments fail to reproduce the interannual variability of rainfall. The better representation of climatological rainfall, evaporation and turbulent fluxes (sensible and latent heat flux) leads to an improved temperature climatology in the CLM experiment. The study illustrates that the CLM land-surface scheme performs better in representing the northeast monsoon as compared to others however there is a need to explore avenues for further improvements in the performance of the coupled model framework.

Simulating the impact of extended desertification on Indian hydro climate using ICTP-RegCM4.4.5.10 model

Presented here is the numerical study of impact of extended desertification of the Thar desert (a data scarce arid region), on the Indian Summer Monsoon (ISM) meteorology using a robust state-of-the-art ICTP - regional climate model (RCM) RegCMv4.4.5.10 coupled with Biosphere – Atmosphere Transfer Scheme (BATS) land surface scheme. Firstly, the evolution of ISM precipitation, mean temperature and soil moisture during June to September 2001–2010 is verified using Emanuel over land and Grell over ocean with Arakawa and Schubert (1974) closure, in combination with the two planetary boundary layer (PBL) parameterization schemes, Holtslag and University of Washington - UW Turbulence closure model for PBL. Then the feedback due to extended desertification between land surface and PBL, during ISM regime is studied. The RCM simulations with Emanuel over land and Grell over ocean with Arakawa and Schubert (1974) closure in combination with UW PBL scheme, is able to properly simulate the rainfall, mean temperature JJAS climatology with bias in rainfall ~ 2 mm/day and bias in mean temperature is ~ 0.5–1 °C over the monsoon core region. Numerical experiments (control and design experiment) with the above mentioned combination of PBL schemes is performed for investigating the impact of extended desertification on the changes in the ISM precipitation, surface fluxes, circulation pattern, moisture fluxes and net radiation etc. In the extended desert design experiment, the land-use pattern in the model over Thar Desert (i.e. northwestern part of Indian sub-continent between Pakistan and northwestern India) is changed from “crop/mixed farming and semi-desert” to “desert/semi-desert” type of vegetation, mimicking extended desertification in the RegCMv4.4.5.10 model. Results show that due to increase in desertification over Thar deserts there is increase in albedo resulting from a decrease in plant cover, along with formation of anomalous anti-cyclonic circulation causes a decrease in JJAS rainfall (p < 0.01) over north, north-west India by −1 to −2 mm/day (~25% reduction). Anomalous anti-cyclonic circulation over the Indian land mass in the extended desertification experiment causes less convective heating and is responsible for the decrease in precipitation (with respect to control experiment). The anomalous anti-cyclonic circulation developed covers northern part of Bay of Bengal resulting in decrease in moisture advection of the order of −12 to −18 kgm-1sec-1 (~10% reduction). This drives away all moisture from the nearby regions. The effect of extended desertification induced feedbacks on variability and dominant modes of variability of Indian monsoon precipitation and soil wetness is also studied and reported. Finally, it is concluded that the relative magnitudes of the changes in albedo and vegetation (or vegetation roughness length) are important determinants of the size of climate change due to prescribed extended desert landscape over Thar desert region of Indian subcontinent. The results of this numerical study provides a basis and reference study for LULCC and mitigation measure human beings need to undertake for climate change adaptation.

Assessment of Seasonal Winter Temperature Forecast Errors in the RegCM Model over Northern Vietnam

This study verified the seasonal six-month forecasts for winter temperatures for northern Vietnam in 1998–2018 using a regional climate model (RegCM4) with the boundary conditions of the climate forecast system Version 2 (CFSv2) from the National Centers for Environmental Prediction (NCEP). First, different physical schemes (land-surface process, cumulus, and radiation parameterizations) in RegCM4 were applied to generate 12 single forecasts. Second, the simple ensemble forecasts were generated through the combinations of those different physical formulations. Three subclimate regions (R1, R2, R3) of northern Vietnam were separately tested with surface observations and a reanalysis dataset (Japanese 55-year reanalysis (JRA55)). The highest sensitivity to the mean monthly temperature forecasts was shown by the land-surface parameterizations (the biosphere−atmosphere transfer scheme (BATS) and community land model version 4.5 (CLM)). The BATS forecast groups tended to provide forecasts with lower temperatures than the actual observations, while the CLM forecast groups tended to overestimate the temperatures. The forecast errors from single forecasts could be clearly reduced with ensemble mean forecasts, but ensemble spreads were less than those root-mean-square errors (RMSEs). This indicated that the ensemble forecast was underdispersed and that the direct forecast from RegCM4 needed more postprocessing.

Application of a Regional Climate Model to Assess Changes in the Climatology of the Eastern United States and Cuba Associated With Historic Land Cover Change

AbstractWe examine the annual, seasonal, monthly, and diurnal climate responses to the land use change (LUC) in eastern United States and Cuba during four epochs (1650, 1850, 1920, and 1992) with ensemble simulations conducted with the RegCM4 regional climate model that includes the Biosphere Atmosphere Transfer Scheme (BATS1e) surface physics package (Dickinson et al., 1993). We derived the land use (LU) data sets by harmonizing a previous reconstruction (Steyaert &amp; Knox, 2008) with updated observations and modeled potential vegetation. The eight‐member ensembles for each epoch were driven with randomly perturbed 1990–2002 atmospheric boundary conditions derived from the National Center for Environmental Prediction global reanalysis. LUC induces statistically significant climate responses across all epochs; the largest changes occur between 1850 and 1920 with the widespread conversion of forests in the United States and forests, grassland, and woody wetlands in Cuba to agriculture. The atmospheric feedback from the aggregated grid‐cell responses attributed to physical and biophysical parameters in BATS1e alters the circulation in the lower atmosphere, thereby propagating the LUC regionally. Depending on the season and location, the altered circulation reinforces, attenuates, or has little effect on surface responses. Relative to pre‐settlement (1650), the 1992 LU produces colder mean annual air temperature (−0.09 ± 0.16 °C) and increased precipitation (0.08 ± 0.09 mm day−1) over the United States, warmer (0.08 °C) and wetter (0.03 mm day−1) conditions over Florida, and warming (0.32 °C) and drying (−0.03 mm day−1) over Cuba, indicating that LUC has played a varying role in climate change over the region.

Sensitivity of convective and land surface parameterization in the simulation of contrasting monsoons over CORDEX-South Asia domain using RegCM-4.4.5.5

An effort for testing the capability and suitability of different cumulus and land surface parameterization schemes in simulating the Indian summer monsoon (ISM) and associated features during contrasting monsoon years using a regional climate model framework is presented. The latest Regional Climate Model system (hereafter RegCM, Vn4.4.5.5) developed and managed by the International Centre for Theoretical Physics (ICTP) has been used to downscale the ERA-Interim reanalysis dataset for three different ISM years, namely, normal (1990), deficit (1987), and excess (1988). Three different convection schemes, namely, Grell (GFC), Emanuel (MIT), and mixed type (i.e., Grell over land and Emanuel over ocean (MIX)), have been used for the simulation of ISM and its associated features. Moreover, three different land surface schemes, namely, the Biosphere–Atmosphere Transfer Scheme or BATS (control), subgrid disaggregation of BATS (SUB-BATS), and Community Land Model 4.5 (CLM4.5), have also been tested for their performance. With these combinations, 27 different suites of experiments were simulated at a horizontal resolution of 50 km over the COordinated Regional Climate Downscaling Experiment (CORDEX)-South Asia domain. The validation of experiments was performed against the India Meteorological Department (IMD) and Climatic Research Unit (CRU) daily dataset for precipitation and near surface air temperature, respectively. In light of different performance metrics, it is found that the near surface air temperature and precipitation in the seasonal-scale simulations are well represented in space for most of the experiments with inherent biases. Among all the experiments, the SUB-BATS scheme in association with GFC cumulus scheme is found to perform consistently among all the years in simulating the ISM precipitation. In most of the cases for the simulation of precipitation, the SUB-BATS seems to outperform the control and CLM4.5 experiments. The domination of dry bias in CLM4.5 experiments is attributed to the improper representation of mean sea level pressure, weaker ISM circulation, and higher atmospheric stability, thus inhibiting the convective activity. Compared to other convection schemes, the MIT scheme is more suitable in representing the features of ISM simulation while using CLM4.5 as a land surface scheme. However, the GFC scheme was found suitable for the simulation of different precipitation years while using SUB-BATS as a land surface model. Such simulations portray reduced biases and improved spatial patterns compared to other schemes. Additionally, CLM4.5 experiments display more utility for the simulation of near surface air temperature. A more comprehensive process-based approach is envisaged to investigate the performance of CLM4.5 in the simulation of ISM for climate-scale simulations.

Obtaining best parameterization scheme of RegCM 4.4 for aerosols and chemistry simulations over the CORDEX South Asia

The regional climate model RegCM 4.4 at 50 km resolution is used to conduct a sensitivity study over South Asia Coordinated Regional climate Downscaling Experiment domain during the period 1998–2002, in order to investigate the best cumulus convective precipitation scheme, planetary boundary layer (PBL) and land-surface scheme. The inferences obtained from 11 sensitivity experiments include the better performance of community land model version 4.5 (CLM 4.5) over biosphere–atmosphere transfer scheme, Tiedtke as cumulus convective precipitation scheme and University of Washington (UW) as PBL scheme. The simulation with these parameterization schemes well captures the monsoon precipitation pattern over India ~ 7 mm/day and North Eastern Region of India (NER) ~ 12 mm/day, which are comparable to observations with a significant correlation of R2 > 0.93. The observed temperatures are also well simulated by the model. Therefore, RegCM 4.4 with these parameterization schemes is further used to simulate the aerosol fields (aerosol optical depth, AOD and black carbon, BC) and aerosol direct radiative forcing (DRF) for the period 2011–2014 over the same domain with special emphasis on NER. The model captures the seasonality in AOD and BC over the Indian Subcontinent and NER. BC hotspots in the Indo-Gangetic Plain and China are well captured by the model. The observed to simulated BC ratio over Dibrugarh (located in NER) is found to be improved. The model underestimation is significant in the dry season when burning over the region is predominant, which has not been considered by the emission inventories properly. Simulated DRF is found to exhibit seasonality qualitatively as well as a North–South latitudinal gradient.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Coupling of Community Land Model with RegCM4 for Indian Summer Monsoon Simulation

Three land surface schemes available in the regional climate model RegCM4 have been examined to understand the coupling between land and atmosphere for simulation of the Indian summer monsoon rainfall. The RegCM4 is coupled with biosphere–atmosphere transfer scheme (BATS) and the National Center for Atmospheric Research (NCAR) Community Land Model versions 3.5, and 4.5 (CLM3.5 and CLM4.5, respectively) and model performance is evaluated for recent drought (2009) and normal (2011) monsoon years. The CLM4.5 has a more distinct category of surface and it is capable of representing better the land surface characteristics. National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NNRP2) datasets are considered as driving force to conduct the experiments for the Indian monsoon region (30°E–120°E; 30°S–50°N). The NNRP2 and India Meteorological Department (IMD) gridded precipitation data are used for verification analysis. The results indicate that RegCM4 simulations with CLM4.5 (RegCM4–CLM4.5) and CLM3.5 (RegCM4–CLM3.5) surface temperature (at 2 ms) have very low warm biases (~1 °C), while with BATS (RegCM4–BATS) has a cold bias of about 1–3 °C in peninsular India and some parts of central India. Warm bias in the RegCM4–BATS is observed over the Indo-Gangetic plain and northwest India and the bias is more for the deficit year as compared to the normal year. However, the warm (cold) bias is less in RegCM4–CLM4.5 than other schemes for both the deficit and normal years. The model-simulated maximum (minimum) surface temperature and sensible heat flux at the surface are positively (negatively) biased in all the schemes; however, the bias is higher in RegCM4–BATS and lower in RegCM4–CLM4.5 over India. All the land surface schemes overestimated the precipitation in peninsular India and underestimated in central parts of India for both the years; however, the biases are less in RegCM4–CLM4.5 and more in RegCM4–CLM3.5 and RegCM4–BATS. During both the years, BATS scheme in RegCM4 failed to represent low precipitation over the leeward than windward side of the Western Ghats, while CLM schemes (both versions) in the RegCM4 are able to depict this feature. In the topographic regions, such as the Western Ghats, northeast India and state of Jammu and Kashmir, RegCM4–BATS overestimates the rainfall amount with higher bias. Statistical analysis using anomaly correlation coefficient, root mean square error, equitable threat score, and critical success index confirms that RegCM4–CLM performs better than RegCM4–BATS in the simulation of the Indian summer monsoon.

Performance evaluation of land surface models and cumulus convection schemes in the simulation of Indian summer monsoon using a regional climate model

In this study, an attempt has been made to investigate the sensitivity of land surface models (LSM) and cumulus convection schemes (CCS) using a regional climate model, RegCM Version-4.1 in simulating the Indian Summer Monsoon (ISM). Numerical experiments were conducted in seasonal scale (May–September) for three consecutive years: 2007, 2008, 2009 with two LSMs (Biosphere Atmosphere Transfer Scheme (BATS), Community Land Model (CLM 3.5) and five CCSs (MIT, KUO, GRELL, GRELL over land and MIT over ocean (GL_MO), GRELL over ocean and MIT over land (GO_ML)). Important synoptic features are validated using various reanalysis datasets and satellite derived products from TRMM and CRU data. Seasonally averaged surface temperature is reasonably well simulated by the model using both the LSMs along with CCSs namely, MIT, GO_ML and GL_MO schemes. Model simulations reveal slight warm bias using these schemes whereas significant cold bias is seen with KUO and GRELL schemes during all three years. It is noticed that the simulated Somali Jet (SJ) is weak in all simulations except MIT scheme in the simulations with (both BATS and CLM) in which the strength of SJ reasonably well captured. Although the model is able to simulate the Tropical Easterly Jet (TEJ) and Sub-Tropical Westerly Jet (STWJ) with all the CCSs in terms of their location and strength, the performance of MIT scheme seems to be better than the rest of the CCSs. Seasonal rainfall is not well simulated by the model. Significant underestimation of Indian Summer Monsoon Rainfall (ISMR) is observed over Central and North West India. Spatial distribution of seasonal ISMR is comparatively better simulated by the model with MIT followed by GO_ML scheme in combination with CLM although it overestimates rainfall over heavy precipitation zones. On overall statistical analysis, it is noticed that RegCM4 shows better skill in simulating ISM with MIT scheme using CLM.

Sensitivity of simulated South America climate to the land surface schemes in RegCM4

This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with the Biosphere–Atmosphere Transfer Scheme (RegBATS) and the Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979–2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, with regard to the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is wetter in general) over most of SA. RegCLM also produces smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer thickness and cause it to reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

Potential impact of reforestation programmes and uncertainties in land cover effects over the loess plateau: a regional climate modeling study

Using the Regional Climate Model version 4.3 (RegCM4.3), this paper investigates the potential effects of reforestation on the regional climate over the Loess Plateau in China with a focus on land-atmosphere interactions. Two land surface schemes are used here: the default Biosphere Atmosphere Transfer Scheme (BATS) and the Community Land Model version 3.5 (CLM3.5). Five simulations using a series of hypothetical reforestation scenarios from 1990 to 2009 have been performed. Results show that in the default BATS simulations, the surface air temperature increases significantly during both summer (June–July-August) and winter (December–January-February) seasons. These patterns are particularly evident over the south-eastern plateau where extensive areas of irrigated crop are converted to forest. In experiments with CLM3.5 and BATS with non-irrigation, in which irrigated crops are specified as regular crops, reforestation generally produces a more pronounced cooling effect in summer, and a slight cooling winter in CLM3.5 but a slight warming in BATS with non-irrigation. The land surface energy balance equation involving latent heat flux (LHF), absorbed solar radiation and downward atmospheric longwave radiation is used to explain the reforestation-induced seasonal responses. In the default BATS simulations, increased temperature induced by reforestation is predominantly driven by the reduced year round LHF. In contrast, the reforestation-induced summer cooling in CLM3.5 and BATS with non-irrigation is caused by the enhanced LHF. This study suggests that the default parameterization of irrigated crop in BATS overestimates soil water content and leading to excessive evapotranspiration (ET) in the Loess Plateau. Hence, non-irrigated cropland would be a more plausible land cover representation for the Loess Plateau, as demonstrated from the reforestation simulations using CLM3.5 and BATS with non-irrigation. An improved description of land characteristics in climate models is highly needed for a more reliable prediction of climate responses to land surface change.

Sensitivity analysis of different parameterization schemes using RegCM4.3 for the Carpathian region

In order to quantify the impact of the use of different parameterization schemes on regional climate model outputs, hindcast experiments have been completed applying the Regional Climate Model version 4.3 (RegCM4.3) for the Carpathian region and its surroundings at 10-km horizontal resolution with three different cumulus convection schemes. Besides, the sensitivity of outputs for subgrid-scale processes is also studied by activating the subgrid Biosphere-Atmosphere Transfer Scheme (BATS) model within other RegCM experiments. Among the analyzed factors, RegCM is most sensitive to the applied convection scheme. The impact of closure assumption related to the used convective parameterization is secondary, while the use of subgridding has less influence on the outputs. RegCM4.3 results show improved performance over our previous model simulations but still have larger amplitude for annual precipitation cycle than the measurement-based reference data. Our validation results for temperature and precipitation suggest that for the selected region, the overall best performance is achieved when using the mixed Grell-Emanuel scheme together with Fritsch and Chappell closure.

Performance evaluation of RegCM4 in simulating extreme rainfall and temperature indices over the CORDEX‐Southeast Asia region

ABSTRACTIn this study, simulations over Southeast Asia (15°S–40°N, 80°–145°E) at 36 km resolution were conducted for the period 1989–2007 using the Regional Climate Model version 4.3 (RegCM4.3) under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (or SEACLID/CORDEX‐SEA) project. Forced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA‐Interim), 18 experiments were carried out using different combinations of cumulus parameterization and ocean flux schemes. Twelve extreme indices for both rainfall and temperature were estimated from the model output. A statistical omega index was used to measure the degree of similarity among the 18 experiments in phase and shape. The results showed relatively high similarities among the experiments over mainland Asia compared to those over the Maritime Continent for both seasonal and inter‐annual variability. The extreme rainfall indices had a lower omega compared to that of temperature. Observed daily rainfall and temperature data at 52 meteorological stations over the SEA region were used to validate the simulated extreme indices. The results showed that extreme temperature indices were generally underestimated across the region. Systematic biases for each simulated rainfall index were also identified. A score ranking system was established to compare the relative performance of the 18 experiments over the 52 selected stations objectively. It was shown that the experiments with the Massachusetts Institute of Technology (MIT)‐Emanuel scheme performed relatively better than the other convective schemes. The combination of the MIT‐Emanuel convective scheme with the Biosphere–Atmosphere Transfer scheme (BATS1e) ocean flux scheme produced the best performance.

Improving precipitation simulation from updated surface characteristics in South America

Land use and land cover maps and their physical-chemical and biological properties are important variables in the numerical modeling of Earth systems. In this context, the main objective of this study is to analyze the improvements resulting from the land use and land cover map update in numerical simulations performed using the Regional Climate Model system version 4 (RegCM4), as well as the seasonal variations of physical parameters used by the Biosphere Atmosphere Transfer Scheme (BATS). In general, the update of the South America 2007 land use and land cover map, used by the BATS, improved the simulation of precipitation by 10 %, increasing the mean temporal correlation coefficient, compared to observed data, from 0.84 to 0.92 (significant at p < 0.05, Student’s t test). Correspondingly, the simulations performed with adjustments in maximum fractional vegetation cover, in visible and shortwave infrared reflectance, and in the leaf area index, showed a good agreement for maximum and minimum temperature, with values closer to observed data. The changes in physical parameters and land use updating in BATS/RegCM4 reduced overestimation of simulated precipitation from 19 to 7 % (significant at p < 0.05, Student’s t test). Regarding evapotranspiration and precipitation, the most significant differences due to land use updating were located (1) in the Amazon deforestation arc; (2) around the Brazil-Bolivia border (in the Brazilian Pantanal wetlands); (3) in the Northeast region of Brazil; (4) in northwestern Paraguay; and (5) in the River Plate Basin, in Argentina. Moreover, the main precipitation differences between sensitivity and control experiments occurred during the rainy months in central-north South America (October to March). These were associated with a displacement in the South Atlantic convergence zone (SACZ) positioning, presenting a spatial pattern of alternated areas with higher and lower precipitation rates. These important differences occur due to the replacement of tropical rainforest for pasture and agriculture and the replacement of agricultural areas for pasture, scrubland, and deciduous forest.

Simulated Impact of Intensification of Irrigation on Indian Monsoon Rainfall and Surface Fluxes

Using Bio-sphere Atmosphere Transfer scheme (BATS) coupled regional climate model (RegCM4) the impact of intensification of irrigation on Indian monsoon atmospheric circulations and surface fluxes is being studied. Land use/land cover change is performed in the model to study the design or sensitivity experiments. This is implemented by changing the vegetation/landuse type in the model. Impact of increase in irrigation activity over Central India and Northwestern region of India is still an open question and hence it is attempted to answer them in this research work. In the first irrigation sensitivity experiment, vegetation/land-use types have been modified to “irrigated crop” type along districts of Central India, Indo-Gangetic plain and northern parts of India, in the RegCM4 model to test the hypothesis that whether-“increase in irrigation decreases monsoon (JJAS) precipitation over certain regions of India and increases pre-monsoon (MAM) precipitation”. Simulations suggest that increase in irrigation over Indian monsoon domain has altered the Indian summer (JJAS) monsoon by weakening it at regional scale over various regions due to probable weakening of the temperature contrast between land and sea. Increase in irrigation over the central India causes a decrease (increase) in sensible heat flux (latent heat flux, surface pressure) in summer monsoon season. To further test the hypothesis that the northwestern region of India is a hotspot for land atmosphere interactions and to test the impact of irrigation intensification over northwestern region of Indian subcontinent, on Indian summer monsoon another sensitivity experiment with irrigation intensification over northwestern regions of India is performed using RegCM4. This experiment suggests that irrigation impact or sensitivity on soil moisture; surface fluxes are limited to northwestern region of Indian subcontinent. Simulations performed at higher (50 km) resolution shows increase in precipitation during pre-monsoon season over northwestern regions of India, too. The Indian monsoon circulations are a part of global general atmospheric circulations periodic in nature and any form of vegetation impact study is a complex process. Thus, from the irrigation sensitivity experiments (using a regional climate model) it can be concluded that due to increase in irrigated land over India, pre-monsoon (MAM) precipitation increase particularly over Central and northwestern regions of India, with the development of anomalous cyclonic circulations.

Numerical Simulation of Land Surface Hydrological Process Over Huaihe River Basin

The BATS (Biosphere Atmosphere Transfer Scheme) model was used to simulate the thunderstorm and flood events in the mountains and plains of the Huaihe River Basin in 1998. And the inherent relationship among runoff, soil moisture content, soil texture and vegetation distribution were exposed via the simulation of water exchange between land and atmosphere. Results show that the effect of soil moisture content in root layer, soil texture, and soil color on the runoff in the mountains is similar to that in the plains, whereas with different sensitivities. However, the effect of soil moisture content in deep layer and vegetation canopy ratio on the runoff in the mountains is opposite to that in the plains. The meteorological and land surface conditions are different between the mountains and the plains, so their hydrological characteristics are different, showing the different atmospheric-hydrological relationship.