Simulation Of Indian Summer Monsoon Research Articles

Evaluation of atmospheric moisture transport to the Tibetan Plateau from 33 CMIP6 models

Atmospheric moisture transport is pivotal in regulating water resources over the Tibetan Plateau (TP). With the growing concerns about climate change, understanding the evolution of atmospheric moisture transport over the TP has become increasingly critical. however, the spatiotemporal distinctions of this transport remain poorly understood in the CMIP6 models. Here, we conducted a comprehensive evaluation of simulated historical atmospheric moisture transport from 33 CMIP6 models, utilizing a novel methodology that assesses the accuracy of model simulations in replicating regional atmospheric moisture transport over the TP. Our results indicate that the CMIP6 models generally succeed in reproducing the broad spatial patterns of atmospheric moisture transport. Nonetheless, substantial errors occur during the monsoon period, primarily attributable to inaccuracies in the location, movement, and intensity of the simulated Indian summer monsoon. The coarser resolution and poor representation of physical processes are potential reasons for errors in atmospheric moisture transport simulation over the TP. The Failure to simulate the terrain blocking on atmospheric moisture transport exacerbates these deficiencies, leading to significant discrepancies. Of the 33 CMIP6 models we investigated, over one-third displayed serious deficiencies in this regard. While coarser resolution and orographic gravity waves are plausible factors, they do not fully account for all the results obtained in this study. Insufficiently detailed or inaccurate topographic data used in the models may also contribute to this deficiency. This study highlights the necessity of using rigorously evaluated models to develop effective regional adaptation strategies over the Tibetan Plateau.

The role of land surface schemes in non‐hydrostatic RegCM on the simulation of Indian summer monsoon

AbstractThis study evaluates the performance of a non‐hydrostatic Regional Climate Model (RegCM) with two land surface parameterizations, namely Biosphere‐Atmosphere Transfer (BAT) scheme and Community Land Model (CLM) scheme on the simulation of summer monsoon over India. The initial and boundary conditions are taken from ERA‐Interim (ERA‐I) reanalysis available at a 0.75° spatial grid. The RegCM is designed with 25 km horizontal resolution and 23 vertical levels, and it integrated for the period 1st January 1982 to 30th September 2016. We used the NOAA Optimum Interpolation Weekly sea surface temperatures, the topography and land‐use data from the United States Geological Survey, and Global Land Cover Characterization. Our results reveal that the summer monsoon precipitation anomaly is reasonably well simulated with BAT and CLM schemes compared to those of India Meteorological Department (IMD) observations. The spatial distributions of temperature anomaly over India with BAT compared to CRU shows cold bias over most of the Indian sub‐continent, whereas the CLM shows large warm bias over central India and monsoon trough region. The low‐level and upper‐level winds are in good agreement with ERA‐I. Further, the analysis of extreme monsoon events (i.e., excess and deficit seasons) reveals that CLM depicts less bias in simulating the excess and deficit precipitation regions as compared to those of BAT. Conversely, BAT simulates temperature well over India in both excess and deficit monsoon seasons. The Taylor's diagram analysis, Added Value Index based on Mean Square Error, and Modified Brier Skill Score are also applied for the extreme rainfall seasons. Our quantitative analysis demonstrates that the CLM have resolved better rainfall features with more skills with respect to that of BAT. The results suggest that CLM have added value in Indian Summer Monsoon (ISM) regional climate simulation than the BAT, particularly on simulation of the rainfall characteristics during extreme rainfall seasons.

Impact of air–sea coupling on the simulation of Indian summer monsoon using a high-resolution Regional Earth System Model over CORDEX-SA

A new high-resolution Regional Earth System Model, namely ROM, has been implemented over CORDEX-SA towards examining the impact of air–sea coupling on the Indian summer monsoon characteristics. ROM's simulated mean ISM rainfall and associated dynamical and thermodynamical processes, including the representation of northward and eastward propagating convention bands, are closer to observation than its standalone atmospheric model component (REMO), highlighting the advantage of air–sea coupling. However, the value addition of air–sea coupling varies spatially with more significant improvements over regions with large biases. Bay of Bengal and the eastern equatorial Indian Ocean are the most prominent region where the highest added value is observed with a significant reduction up to 50–500% precipitation bias. Most of the changes in precipitation over the ocean are associated with convective precipitation (CP) due to the suppression of convective activity caused by the negative feedback due to the inclusion of air–sea coupling. However, CP and large-scale precipitation (LP) improvements show east–west asymmetry over the Indian land region. The substantial LP bias reduction is noticed over the wet bias region of western central India due to its suppression, while enhanced CP over eastern central India contributed to the reduction of dry bias. An insignificant change is noticed over Tibetan Plateau, northern India, and Indo Gangetic plains. The weakening of moisture-laden low-level Somalia Jets causes the diminishing of moisture supply from the Arabian Sea (AS) towards Indian land regions resulting in suppressed precipitation, reducing wet bias, especially over western central India. The anomalous high kinetic energy over AS, wind shear, and tropospheric temperature gradient in REMO compared to observation is substantially reduced in the ROM, facilitating the favourable condition for suppressing moisture feeding and hence the wet bias over west-central India in ROM. The warmer midlatitude in ROM than REMO over eastern central India strengthens the convection, enhancing precipitation results in reducing the dry bias. Despite substantially improved ROM’performance, it still exhibits some systematic biases (wet/dry) partially associated with the persistent warm/cold SST bias and land–atmosphere interaction.

EC‐Earth Simulations Reveal Enhanced Inter‐Hemispheric Thermal Contrast During the Last Interglacial Further Intensified the Indian Monsoon

AbstractPaleoclimate proxy data indicate a stronger Indian summer monsoon (ISM) during the Last Interglacial (LIG) than in the present day. This is largely attributed to orbital forcing induced high seasonal and latitudinal insolation anomalies in the Northern Hemisphere during LIG. According to the general circulation model EC‐Earth3, the simulated ISM rainfall is increased by approximately 28% during the LIG compared to the pre‐industrial period as a result of the orbital forcing and the amplified land‐sea contrast due to both local and remote ocean feedbacks. Although the LIG is often portrayed as a potential analogue of future warmer climates, our study suggests that the enhanced inter‐hemispheric thermal gradient during the LIG strengthened the ISM, in opposition to the observed weakening of ISM under present‐day warming.

Role of Soil Moisture Initialization in RegCM4.6 for Indian Summer Monsoon Simulation

Role of Soil Moisture Initialization in RegCM4.6 for Indian Summer Monsoon Simulation

Impact of Soil Moisture Initialization in the Simulation of Indian Summer Monsoon Using RegCM4

Soil moisture is one of the key components of land surface processes and a potential source of atmospheric predictability that has received little attention in regional scale studies. In this study, an attempt was made to investigate the impact of soil moisture on Indian summer monsoon simulation using a regional model. We conducted seasonal simulations using a regional climate model (RegCM4) for two different years, viz., 2002 (deficit) and 2011 (normal). The model was forced to initialize with the high-resolution satellite-derived soil moisture data obtained from the Climate Change Initiative (CCI) of the European Space Agency (ESA) by replacing the default static soil moisture. Simulated results were validated against high-resolution surface temperature and rainfall analysis datasets from the India Meteorology Department (IMD). Careful examination revealed significant advancement in the RegCM4 simulation when initialized with soil moisture data from ESA-CCI despite having regional biases. In general, the model exhibited slightly higher soil moisture than observation, RegCM4 with ESA setup showed lower soil moisture than the default one. Model ability was relatively better in capturing surface temperature distribution when initialized with high-resolution soil moisture data. Rainfall biases over India and homogeneous regions were significantly improved with the use of ESA-CCI soil moisture data. Several statistical measures such as temporal correlation, standard deviation, equitable threat score (ETS), etc. were also employed for the assessment. ETS values were found to be better in 2011 and higher in the simulation with the ESA setup. However, RegCM4 was still unable to enhance its ability in simulating temporal variation of rainfall adequately. Although initializing with the soil moisture data from the satellite performed relatively better in a normal monsoon year (2011) but had limitations in simulating different epochs of monsoon in an extreme year (2002). Thus, the study concluded that the simulation of the Indian summer monsoon was improved by using RegCM4 initialized with high-resolution satellite soil moisture data although having limitations in predicting temporal variability. The study suggests that soil moisture initialization has a critical impact on the accurate prediction of atmospheric circulation processes and convective rainfall activity.

Impact of INSAT-3D radiance data assimilation using WRF 3DVAR on simulation of Indian summer monsoon and high-resolution rainfall forecast over hilly terrain

Impact of INSAT-3D radiance data assimilation using WRF 3DVAR on simulation of Indian summer monsoon and high-resolution rainfall forecast over hilly terrain

Large Sensitivity of Simulated Indian Summer Monsoon Rainfall (ISMR) to Global Warming: Implications of ISMR Projections

AbstractReliable projections of Indian Summer Monsoon Rainfall (ISMR) to the next century by climate models is critical for policy toward sustainable development goals but depends on sensitivity of the models simulating ISMR as global mean temperature changes. Here, using observed ISMR and historical global temperature (1850–2005), we find that the mean ISMR scales as (3.95 ± 1.13%)/K, lower than the Clausius‐Clapeyron (CC) scaling (∼7%/K). However, the sensitivity of the intensity of daily rainfall extremes is (29.5 ± 3.4)%/K, four times as large as the CC scaling. We also find that the sensitivities of simulated mean ISMR by 36 CMIP5 and CMIP6 models each at 13.36%/K and 11.82%/K, respectively, are 2–3 times larger than the observed sensitivity and independent of the chosen period. Larger than simulated CC scaling of ISMR is consistent with simulated strengthening of Indian monsoon circulation in contrast to observations. Models' sensitivity appears to be due to their stronger than observed response to forcing over land resulting in stronger north‐south heating gradient and acceleration of monsoon circulation. Projected sensitivity of ISMR in models with increased greenhouse gas forcing weakens compared to the historical period approaching the CC scaling. Required to delineate the contributions of larger than observed intrinsic sensitivity of the models from projected sensitivity, our findings provide a way to correct the bias potentially improving the reliability of ensemble mean projections of ISMR.

Simulations of Indian summer monsoon using RegCM: a comparison with ERA and GFDL analysis

A comprehensive understanding of the variation of Indian summer monsoon (ISM) features is necessary for accurate prediction of seasonal and sub-seasonal scale meteorological parameters. In this study, the summer monsoon features over India are investigated using RegCM simulations over South Asia Coordinated Regional Downscaling Experiment (SA-CORDEX) domain with 45-km spatial resolution. The initial-boundary data are derived from the European Centre for Medium Range Weather Forecasts Re-Analysis (ERA) and Geophysical Fluid Dynamics Laboratory (GFDL) analysis for the period 1989 to 2005. For both model simulations, mixed convection scheme (Emmanuel over ocean and Grell over land), Holtslag planetary boundary layer (PBL) scheme and biosphere atmospheric transfer system (BATS) land surface scheme are used throughout the experiment. The simulation results are validated with Climatic Research Unit (CRU) observations of precipitation and temperature. The spatial distribution of precipitation and temperature is reasonably simulated with ERA and GFDL analysis as compared with CRU observation. However, the simulation of precipitation and temperature with ERA analysis iscloser to CRU observations as compared with GFDL analysis. The seasonal scale (JJAS) simulation of precipitation with ERA and GFDL illustrates wet bias (2 mm per day) as compared to CRU observation, whereas temperature simulated with ERA indicated warm bias (1 °C) and GFDL depicts cold bias (2 °C) against CRU observations. The wind magnitude and distribution of ERA simulations show considerably higher magnitude over the western Himalaya which is connected to low values of specific humidity over the same terrain as compared with GFDL.

Context of the added value in coupled atmosphere-land RegCM4–CLM4.5 in the simulation of Indian summer monsoon

The potential of the RegCM4–CLM4.5 model for value addition over the MIROC5 GCM for Indian Summer Monsson (ISM) simulation for the present climate (1975–2005) has been examined. The added value has been investigated in terms of the added value index (AV) and the Modified Brier Skill Score (MBSS). In general, a strong dry (wet) bias > 5 mm/day in the RegCM4 (MIROC5) dataset was prevalent over different parts of India. Additional precipitation statistics such as the area-averaged mean, standard deviation, correlation coefficient, and percentage bias over the homogeneous region of precipitation suggest that the RegCM4 occasionally improves over the MIROC5, depending upon the region and the metric under consideration. Further, a comparable tropospheric temperature gradient and the vertical wind shear have been found for both the dataset. However, this does not hold for the large-scale moisture transport as the RegCM4 shows an advantage in representing the magnitude and the location of the low-level jet. The dominant unrealistic moisture transport and associated stronger Bay of Bengal branch of circulation causes heavy precipitation (> 12 mm/day), thus leading to improved precipitation statistics for MIROC5. A quantifiable added value over the GCM in terms of the positive indices have been found in the RegCM4. The AV (MBSS) suggests positive values i.e. 0.6–0.8 (0.2–0.5) over major parts of India, signifying added information and/or the improvement upon the downscaling. The experiment certainly provides additional information in the precipitation simulation over the major part of India however the two indices do not necessarily agree over certain areas.

Performance of hydrostatic and non‐hydrostatic dynamical cores in RegCM4.6 for Indian summer monsoon simulation

AbstractThe efficacy of regional climate model RegCM4.6 using hydrostatic core resolutions at 36km (HY36) and 12km (HY12) and a non‐hydrostatic core resolution at 12km (NH12) is investigated by simulating the normal, excess and deficit monsoon seasons. The ERA‐Interim reanalysis data are used to drive the model and the India Meteorological Department (IMD) and modern‐era retrospective analysis for research and applications (MERRA) rainfall data are used for precipitation verification. The heavy rainfall regions are well simulated in the high‐ compared with the coarse‐resolution simulations, with the maximum in the NH12. The non‐hydrostatic dynamics amalgamate the vertical acceleration with the orographic uplifting that causes more precipitation over hilly regions than that of the hydrostatic core. On the other hand, the lesser precipitation over northwest India is better portrayed in the HY12 than in the other two. Over central India, the HY36 performs better followed by the NH12; and the contrasting precipitation features are also well depicted in the HY36 and NH12. This is probably because of the better representation of large‐scale monsoon features, such as a monsoon trough in the HY36 and local‐scale convective activities in the NH12. Daily rainfall analysis also shows that the high‐resolution model is capable of capturing the active and break phases during the El Niño and La Niña seasons. The non‐hydrostatic model possesses good correlation co‐efficients >0.5 over the hydrostatic model with co‐efficients of 0.35. The analysis of upper air circulations and the derived parameters, including statistical tests, confirm that the RegCM4.6 with non‐hydrostatics is useful for orographic regions, hydrostatic at a coarse resolution and non‐hydrostatic at a finer resolution and could be suitable for plain regions.

Investigating Indian summer monsoon in coupled regional land–atmosphere downscaling experiments using RegCM4

The ability of Regional Climate Model (RCM: RegCM4) forced with two different Global Climate Model (GCM: CCSM4 and MIROC5) and three land-surface parameterization (LSP) (i.e., BATS, CLM4.5 and Subgrid-BATS) in simulating the Indian summer monsoon (ISM) is tested for the present climate (1975–2005). Thus six simulation combinations are assessed for seasonal mean temperature, precipitation, and low-level wind for ISM season (June, July, August, September: JJAS) over the COordinated Regional climate Downscaling EXperiment-South Asia (CORDEX-SA) domain. The simulations are evaluated in terms of Taylor’s metric (for precipitation, temperature, zonal wind, meridional wind and total cloud fraction), mean annual cycle, index of agreement, normalized root mean squared deviation and probability distribution function. The experiments simulated moderate events more accurately than high-intensity precipitation events compared to the corresponding observations. The inherent biases in the model simulations are attributed to the weaker meridional wind along with restrained vertical motion during ISM, especially with CCSM4 forcing. A careful analysis of tropospheric temperature gradient (TTG) suggests a weaker north–south (N–S) gradient due to the warmer atmospheric column in these experiments. On the contrary, the MIROC5_CLM4.5 experiment captures the magnitude and the temporal evolution of TTG better during ISM. It also represents the mean features of ISM better than other experiments. Also, the CLM4.5 LSP shows promising performance in ISM simulation when forced with MIROC5. It also provides further avenues for testing of the same combination under different frameworks, including the intended future climate study. This study emphasizes the importance of using appropriate GCM and LSP forcings to the RCM for simulating a coupled complex systems such as ISM.

Monsoon Mission: A Targeted Activity to Improve Monsoon Prediction across Scales

AbstractIn spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (∼38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.

Assessment of coupled regional climate model (RegCM4.6–CLM4.5) for Indian summer monsoon

A model experiment with a regional climate model (RegCM4.6) coupled with an updated land–surface scheme (Community Land Model; CLM4.5) is integrated for 34 years to study the Indian summer monsoon (ISM). An eastward shift (towards Bay of Bengal; BoB) in simulated monsoon features due to the secular shift of the moist convective systems is observed. Further diagnostics show lower temperature over India as compared to BoB; while the Findlater jet is significantly weakened over the Arabian Sea. The low-pressure drags the southwesterly towards BoB through India. The Bowen ratio and evaporation reflect less soil moisture availability over the land. The analysis of simulated omega, moist static energy and Hadley circulation illustrates that an atmospheric condition dominates over land which further suppresses the convection and hence the rainfall. However, favorable atmospheric condition supporting convection and moisture availability leads to heavy precipitation over BoB and hence causes the eastward shift in simulated ISM rainfall. The convective fraction contributes the major share to the total precipitation. An evaluation of appropriate land surface spin-up period in order to investigate the optimum stabilization period for CLM4.5, indicates a possible weak coupling between land and atmosphere components in model simulation. This led to the improper energy and moisture exchanges between land and atmosphere in the simulation. The present work also suggests that, the simulated mean rainfall is not predominantly influenced by the length of different spin-up periods (up to 25 years) in case of weak coupling of land and atmosphere.

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.

The Impact of Modified Fractional Cloud Condensate to Precipitation Conversion Parameter in Revised Simplified Arakawa‐Schubert Convection Parameterization Scheme on the Simulation of Indian Summer Monsoon and Its Forecast Application on an Extreme Rainfall Event Over Mumbai

AbstractThe impact of modified fractional conversion parameter (from cloud condensate to precipitation) in the revised simplified Arakawa‐Schubert (RSAS) convection scheme in Climate Forecast System version 2 on the simulation of Indian summer monsoon (ISM) is examined. While the default fractional conversion parameter is constant in RSAS, the modified parameter has the form of an exponential function of temperature above the freezing level, whereas below the freezing, level it is kept constant. The model simulation indicates RSAS with modified conversion parameter (RSAS_mod) shows a better fidelity in capturing the mean monsoon features over the ISM region. The spatial distribution of precipitation shows notable improvement over the ISM region. Most of the global general circulation models has a tendency to grossly overestimate (underestimate) the convective (large‐scale) rainfall over the ISM region, which has somewhat improved in RSAS_mod simulation. It is suggested that reduced rate of conversion of cloud condensate to convective precipitation above the freezing level leads to suppression of convective precipitation, which further increases the detrained moisture from the upper‐level, resulting enhancement in large‐scale precipitation. Further, improvement has been noted in outgoing longwave radiation, wind circulation, total cloud fraction, and dynamical and thermodynamical processes in RSAS_mod simulation. The modified conversion parameter helps in improving the feedback between moisture and convective processes through better lower tropospheric moistening. In addition to mean summer monsoon, the RSAS_mod indicates its potential in predicting an extreme rainfall event over Mumbai in high‐resolution global forecast system at T1534 horizontal resolution. However, its fidelity needs to be further tested for more number of heavy rainfall events.

Impact of a Narrow Coastal Bay of Bengal Sea Surface Temperature Front on an Indian Summer Monsoon Simulation

A dry bias in climatological Central Indian rainfall plagues Indian summer monsoon (ISM) simulations in multiple generations of climate models. Here, using observations and regional climate modeling, we focus on a warm coastal Bay of Bengal sea surface temperature (SST) front and its impact on Central Indian rainfall. The SST front, featuring sharp gradients as large as 0.5 °C/100 km, is colocated with a mixed layer depth (MLD) front, in a region where salinity variations are known to control MLD. Regional climate simulations coupling a regional atmospheric model with an ocean mixed layer model are performed. A simulation with observed MLD climatology reproduces SST, rainfall, and atmospheric circulation associated with ISM reasonably well; it also eliminates the dry bias over Central India significantly. Perturbing MLD structure in the simulations, we isolate the SST front’s impact on the simulated ISM climate state. This experiment offers insights into ISM climatological biases in the coupled NCEP Climate Forecast System version-2. We suggest that the warm SST front is essential to Central Indian rainfall as it helps to sustain deep and intense convection in its vicinity, which may be a source for the vortex cores seeding the monsoon low-pressure systems.

The Indian summer monsoon in MetUM-GOML2.0: effects of air–sea coupling and resolution

Abstract. The fidelity of the simulated Indian summer monsoon is analysed in the UK Met Office Unified Model Global Ocean Mixed Layer configuration (MetUM-GOML2.0) in terms of its boreal summer mean state and propagation of the boreal summer intraseasonal oscillation (BSISO). The model produces substantial biases in mean June–September precipitation, especially over India, in common with other MetUM configurations. Using a correction technique to constrain the mean seasonal cycle of ocean temperature and salinity, the effects of regional air–sea coupling and atmospheric horizontal resolution are investigated. Introducing coupling in the Indian Ocean degrades the atmospheric basic state compared with prescribing the observed seasonal cycle of sea surface temperature (SST). This degradation of the mean state is attributable to small errors (±0.5 ∘C) in mean SST. Coupling slightly improves some aspects of the simulation of northward BSISO propagation over the Indian Ocean, Bay of Bengal, and India, but degrades others. Increasing resolution from 200 to 90 km grid spacing (approximate value at the Equator) improves the atmospheric mean state, but increasing resolution again to 40 km offers no substantial improvement. The improvement to intraseasonal propagation at finer resolution is similar to that due to coupling.

Performance of CMIP5 models in the simulation of Indian summer monsoon

In this paper, the fidelity of 28 models under Coupled Model Inter-comparison Project Phase-5 is examined for the Indian summer monsoon for the historical period from 1975 to 2005. It is found that all models simulate the spatial distribution of the seasonal mean surface air temperatures (Tas) quite well (pattern correlation > 0.75), whereas the simulation of precipitation is found to be relatively poor (correlation 0.1–0.7). Most models underestimate the Tas with more bias during winter and less bias during summer. In regard to precipitation, most models fail to capture the observed contribution ratio of convective and large-scale precipitation (LSP) and simulate more convective precipitation as compared to the LSP. Extremely large wet (dry) biases are noted in convective (large-scale) precipitation. The total precipitation is also noted to have a large dry bias in most models, which is mainly due to the large dry bias in the LSP. Contrary to the notion that better simulation of the contribution ratio would lead to better simulation of total precipitation or vice-versa, our results show that both of these notions are not valid for most models. In observations, the LSP dominates the annual cycle of the total precipitation, whereas in models, the convective component dominates. In few models, the annual cycle in the individual precipitation component is either weak or completely missing. None of the models are found to simulate the observed trend in precipitation and temperature. The model with the highest resolution, MIROC-4h, simulates many of the observed features better than the other models, thereby emphasizing the usefulness of finer resolutions in better simulation of Indian monsoon. A comprehensive list of models has been prepared on the basis of their capability in simulating various features of Indian summer monsoon. The multimodel mean of the better models identified in this study is expected to produce more reliable projections of the Indian monsoon.

Inter-comparison and evaluation of mixed-convection schemes in RegCM4 for Indian summer monsoon simulation

The present study evaluates the performances of mixed-convection schemes (MCSs) in which different cumulus schemes are activated over the land and ocean separately to simulating the Indian Summer Monsoon (ISM). The regional climate model RegCM4.4 is used and the initial and boundary conditions are derived from the National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NCEP-R2). The NCEP-R2 and the Indian Meteorological Department (IMD) precipitation analysis at 0.25° × 0.25° are used to evaluate the model simulated results. The four cumulus schemes Grell, MIT-Emanuel, Tiedtke, and Kain and Fritsch have been used to setting ten different combinations of MCSs.The MCSs having Tiedtke/Emanuel scheme over the land and the Grell scheme over the ocean (L:Ti_O:Gr; L:Em_O:Gr) are found qualitatively and quantitatively better to simulating the semi-permanent characteristics of the ISM. These MCSs are effectual in predicting seasonal mean precipitation intensity and distribution during the ISM and closer to IMD precipitation analysis than any other MCSs. It is found that the MCS having Grell scheme over the land and ocean, spatial gradient of precipitation is reasonably well when compared to IMD precipitation analysis. The representation of precipitation over the central India is poor in all the MCSs; this is probably due to increased cloud cover in RegCM4 which in turn, leads to reducing surface air temperature over land and thus reduce convective instability in the model simulations. The present study proposes a statistically based screening method to identify the useful MCSs that have reasonable skills. The best performing MCSs examined for normal and deficit monsoon years are used to simulate 15 consecutive monsoon seasons (1982–1996). Simulations of several monsoon years confirm that the two MCSs namely L:Ti_O:Gr and L:Em_O:Gr are suitable to simulate the ISM.