Simulation Of Summer Monsoon Research Articles

Indian summer monsoon simulations in successive generations of the NCAR Community Atmosphere Model

Indian summer monsoon simulations in successive generations of the NCAR Community Atmosphere Model

Sensitivities of the Asian Summer Monsoon Simulations to Physical Parameters for the Perturbed Parameter Ensemble of HadGEM3‐GC3.05

AbstractThe simulation skill of the perturbed parameter ensemble (PPE) of HadGEM3‐GC3.05 on the mean climate pattern of the Asian summer monsoon (ASM) is evaluated in this study. The sensitivities of the model bias to the perturbed parameters are investigated based on metrics. The results show that the PPE mean (PPE‐20M) could effectively capture the general ASM precipitation and wind patterns, with a correlation coefficient of 0.78. PPE‐20M mainly shows positive precipitation biases over the tropical western Pacific, southern slope of the Tibetan Plateau, Indochina Peninsula, and South China and negative precipitation biases over the Indian continent and Bay of Bengal. The magnitude of the precipitation biases is more sensitive than its pattern to the variation of the perturbed parameters. Four parameters (ent_fac_dp, qlmin, ps_cloud‐ph, and psm) are found to be crucial for simulating the ASM precipitation intensity, and their combined effects are related to the simulated precipitation biases.

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.

Dynamic Downscaling the South Asian Summer Monsoon From a Global Reanalysis Using a Regional Coupled Ocean‐Atmosphere Model

AbstractIn this study, we present the results of a regional model (regional spectral model‐regional ocean model [(RSM‐ROMS]) simulation of the South Asian Summer Monsoon (SASM). The RSM‐ROMS integration is carried out at 20 km grid spacing over a period of 25 years (1986–2010). The simulation is forced by global atmospheric and oceanic reanalysis. The RSM‐ROMS simulation shows a realistic alignment of the simulated rainfall along the orographic features of the domain. Furthermore, the RSM‐ROMS simulates the observed feature of convection over continental SASM region being more vigorous with dominance of mixed warm and cold phase hydrometeors in contrast to the dominance of the warm rain process in the neighboring tropical oceans. Similarly, the upper ocean features of contrasting mixed layer and thermocline depths between the northern and equatorial Indian Ocean are also simulated in the RSM‐ROMS. Intra‐Seasonal Oscillation (ISO) of the SASM at 10–20 and 20–70 days are also simulated in the RSM‐ROMS with many of its features verifying with observations. For example, the 20–70 days ISO are of higher amplitude and its meridional propagation is slower in Bay of Bengal compared to that over Arabian Sea. Additionally, RSM‐ROMS shows 12.3 Monsoon Low Pressure Systems (LPSs) per season that is comparable to 14.6 per season from observations. Furthermore, the observed intraseasonal contrasts of LPS between the wet and dry spells of ISO is also reproduced in the RSM‐ROMS.

Evaluation of the interannual variability in the East Asian summer monsoon in AMIP and historical experiments of CAS FGOALS-f3-L

The evaluation of East Asian summer monsoon (EASM) simulations could improve our understanding of Asian monsoon dynamics and climate simulations. In this study, by using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments of the Atmospheric Model Intercomparison Project (AMIP) and historical runs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean–Atmosphere–Land System (FGOALS-f3-L) model, the model simulation skill for the interannual variability in the EASM was determined. According to multivariate empirical orthogonal function (MV-EOF) analysis, the major mode of the EASM mainly emerged as a Pacific-Japan pattern in the western Pacific accompanied by a local anticyclonic anomaly with a total variance of 24.6%. The historical experiment could suitably reproduce this spatial pattern and attained a closer total variance than that attained by the AMIP experiment. The historical experiment could also better simulate the time frequency of the EASM variability than the AMIP experiment. However, the phase of principal component 1 (PC1) was not suitably reproduced in the historical experiment since no initialization procedure was applied at the beginning of the integration in the historical simulation process, whereas the sea surface temperature (SST) was preset in the AMIP experiment. Further analysis revealed that air–sea interactions in the Indian Ocean and tropical western Pacific were important for the model to provide satisfactory EASM simulations, while El Niño–Southern Oscillation (ENSO) simulation was possibly related to the climate variability in the EASM simulations, which should be further analyzed.摘要对东亚夏季季风(EASM)模拟的评估可以提高我们对亚洲季风动力和气候模拟的理解. 在这项研究中, 通过使用中国科学院(CAS)全球海洋-大气-陆地系统(FGOALS-f3-L)模式参加的第六次耦合模式相互比较计划(CMIP6)中的大气模式相互比较计划(AMIP)和历史(historical)试验, 明确了EASM的年际变率的模拟能力. 通过多变量经验正交函数(MV-EOF)分析发现, 观测的EASM的主导模态为西太平洋上的太平洋-日本模态, 并伴有局部反气旋异常. 主导模态的方差贡献率为24.6%. 历史(historical)试验可以基本再现这种空间模态, 其方差贡献率较AMIP试验更接近于观测. 与AMIP试验相比, 历史(historical)试验还能更好地模拟EASM变率的时间频率. 然而, 由于历史(historical)模拟没有在积分开始时应用初始化过程, 而AMIP试验受到海表面温度(SST)的约束, 因此主成分(PC1)的位相在历史(historical)试验中没有得到较好地再现. 进一步分析发现, 印度洋和西太平洋热带地区的海气相互作用对EASM的模拟非常重要, 而EASM气候变率的模拟可能与厄尔尼诺-南方涛动(ENSO)的模拟能力有关, 这值得进一步分析.

Comparison of East Asian Summer Monsoon Simulation between an Atmospheric Model and a Coupled Model: An Example from CAS-ESM

In this study, the Chinese Academy of Sciences’ Earth System Model Version 2 (CAS-ESM2) and its atmospheric component were evaluated for the ability to simulate the East Asian summer monsoon (EASM), in terms of climatology and composites in El Niño decaying years (EN) and La Niña years (LN). The results show that the model can realistically simulate the El Niño Southern Oscillation (ENSO) annual cycle, the interannual variation, the evolution process, and the prerequisites of ENSO, but the trend of developing and decaying is faster than that of the observations. With regard to the climatological mean state in the EASM, the coupled model run can largely improve the precipitation and 850 hPa wind simulated in the atmospheric model. Moreover, the coupled run can also reduce the mid-latitude bias in the atmospheric model simulation. Composite methods were then adopted to examine performance in different phases of the ENSO, from a mature winter to a decaying summer. The atmospheric model can well reproduce the Western North Pacific Anomalous Anticyclone (WNPAC)/Western North Pacific Anomalous Cyclone (WNPC) during EN/LN well, but the westerly/easterly anomalies and the associated precipitation anomalies over the equatorial Central Eastern Pacific are somewhat overestimated. Compared with the atmospheric model, these anomalies are all underestimated in the coupled model, which may be related to the ENSO-related SST bias appearing in the Eastern Indian Ocean. Due to the ENSO and ITCZ bias in the historical simulations, the simulated ENSO-related SST and the precipitation anomaly are too equator-trapped in comparison with the observations, and the cold tongue overly extends westward. This limits the ability of the model to simulate ENSO-related EASM variability. For the subseasonal simulations, though atmospheric model simulations can reproduce the westward extension of the Western Pacific subtropic high (WPSH) in EN decaying summers, the eastward retreat of the WPSH in LN is weak. The historical simulations show limited improvement, indicating that the subseasonal variation in the EASM is still a considerable challenge for current generation models.

Impact of Riverine Fresh Water on Indian Summer Monsoon: Coupling a Runoff Routing Model to a Global Seasonal Forecast Model

Rivers form an essential component of the earth system, with ~36,000 km3 of riverine freshwater being dumped into the global oceans every year. The role of rivers in controlling the sea-surface salinity and ensuing air-sea interactions in the Bay of Bengal (BoB) is well-known from observational studies; however, attempts to include rivers in coupled models used for seasonal prediction have been limited. This study reports the benefits of river routing in coupled models over prescribing observational river discharge and the impact on the Indian Summer Monsoon (ISM) simulation. Seasonal hindcasts are carried out using a state-of-the-art global coupled ocean-atmosphere-land-sea ice model, Climate Forecast System version 2, coupled to a runoff routing model. It is demonstrated that such a coupling leads to a better representation of the upper ocean stratification in northern BoB, causes mixed layer warming during July-August, and imparts a significant inter-annual variability to the mixed layer heat budget. The rainfall-runoff coupled feedback associated with ISM is captured better, and remote teleconnections with the equatorial Pacific are enhanced. Improved seasonal mean temperature and salinity profiles in the northern BoB lead to the formation of a thicker barrier layer, which is closely tied to the freshwater from rivers. These processes result in an overall enhancement of the ISM rainfall simulation skill, which stems from scale interactions between the sub-seasonal and seasonal variability of ISM. A significant community effort is required to reduce biases in land-surface processes to improve streamflow simulations, along with better parameterization of mixing of river water with the ocean.

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.

Crucial Role of Mesoscale Convective Systems in the Vertical Mass, Water, and Energy Transports of the South Asian Summer Monsoon

AbstractConvective vertical transport is critical in the monsoonal overturning, but the relative roles of different convective systems are not well understood. This study used a cloud classification and tracking technique to decompose a convection-permitting simulation of the South Asian summer monsoon (SASM) into subregimes of mesoscale convective systems (MCSs), non-MCS deep convection (non-MCS), congestus, and shallow convection/clear sky. Isentropic analysis is adopted to quantify the contributions of different convective systems to the total SASM vertical mass, water, and energy transports. The results underscore the crucial roles of MCSs in the SASM vertical transports. Compared to non-MCSs, the total mass and energy transports by MCSs are at least 1.5 times stronger throughout the troposphere, with a larger contributing fraction from convective updrafts compared to upward motion in stratiform regions. Occurrence frequency of non-MCSs is around 40 times higher than that of MCSs. However, per instantaneous convection features, the vertical transports and net moist static energy (MSE) exported by MCSs are about 70–100 and 58 times stronger than that of non-MCSs. While these differences are dominantly contributed by differences in the per-feature MCS and non-MCS area coverage, MCSs also show stronger transport intensities than non-MCSs over both ocean and land. Oceanic MCSs and non-MCSs show more obvious top-heavy structures than their inland counterparts, which are closely related to the widespread stratiform over ocean. Compared to the monsoon break phase, MCSs occur more frequently (~1.6 times) but their vertical transport intensity slightly weakens (by ~10%) during the active phases. These results are useful for understanding the SASM and advancing the energetic framework.

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.

Sensitivity of South Asian summer monsoon simulation to land surface schemes in Weather Research and Forecasting model

AbstractThe land surface scheme is crucial for the performance of regional climate models in dynamic downscaling application. In this study, we explore the sensitivity of the simulation with 10‐km resolution Weather Research and Forecasting (WRF) model to the land surface schemes in simulating South Asian summer monsoon. The WRF simulations for 19 summers from 2000 to 2018 are conducted with four different land surface schemes including Exp‐CLM4, Exp‐Noah‐MP, Exp‐PX, and Exp‐SSiB, with that the initial and boundary conditions for the WRF model simulations are provided from the NCEP‐FNL data. The ERAI reanalysis data, GHCN‐CAMS, and CRU gridded data are used to comprehensively evaluate the WRF simulations. Compared with verification data, the WRF model can reasonably capture the spatial patterns of summer mean large‐scale atmospheric circulation, 2‐m temperature and precipitation. The simulation results, however, are sensitive to the option of land surface scheme. The performance of Exp‐CLM4 and Exp‐SSiB is better than that of Exp‐Noah‐MP and Exp‐PX assessed by multivariable integrated evaluation (MVIE) method. To explore the dynamic and physical mechanisms behind the WRF model sensitivity to land surface schemes, the differences in the surface energy balance between the ensemble means Ens‐CLM4‐SSiB and Ens‐NoanMP‐PX are analysed in detail. The results illustrate that the intensity of the simulated sensible heat flux over South Asia is weaker in Ens‐CLM4‐SSiB than that in Ens‐NoahMP‐PX. The simulated wind fields are influenced due to the geostrophic adjustment process caused by large differences in geopotential height; thus, the simulations of 2‐m temperature and precipitation are all affected.

Impact of Stochastic Entrainment in the NCAR CAM Deep Convection Parameterization on the Simulation of South Asian Summer Monsoon

Model simulations are highly sensitive to the formulation of the atmospheric mixing process or entrainment in the deep convective parameterizations used in their atmospheric component. In this paper, we have implemented stochastic entrainment in the deep convection scheme of NCAR CAM5 and analyzed the improvements in model simulation, focusing on the South Asian Summer Monsoon (SASM), as compared to the deterministic entrainment formulation in the default version of the model. Simulations using stochastic entrainment (StochCAM5) outperformed default model simulations (DefCAM5), as inferred from multiple metrics associated with the SASM. StochCAM5 significantly alleviated some of the longstanding SASM biases seen in DefCAM5, such as precipitation pattern and magnitude over the Arabian Sea and western Equatorial Indian ocean, early monsoon withdrawal, and the overestimation in the frequency of light precipitation and the underestimation in the frequency of large-to-extreme precipitation. Related SASM dynamical and thermodynamical features, such as Somali Jet, low-level westerly winds, and meridional tropospheric temperature gradient (MTTG), are improved in StochCAM5. Further, the simulation of monsoon intra-seasonal oscillation (MISO), Madden Julian Oscillation (MJO), and equatorial Kelvin waves are improved in StochCAM5. Many essential climate variables, such as shortwave and longwave cloud forcing, cloud cover, relative and specific humidity, and precipitable water, show significant improvement in StochCAM5.

The impact of coupled air–sea interaction on extreme East Asian summer monsoon simulation in CMIP5 models

AbstractIn this study, the relationship between the ability to simulate air–sea interactions over the western North Pacific (WNP), and to reproduce the extreme East Asian summer monsoon (EASM), were investigated by comparing the performances of several global climate models (GCMs). High ranked in air–sea interaction simulation (HRA) and low ranked in air–sea interaction simulation (LRA) models were selected, according to their performance in simulating relations between sea surface temperature (SST) and precipitation over the WNP, from the ensemble of models that participated in the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3, CMIP5). Compared with CMIP3 models, CMIP5 models exhibited improved simulations of the distinctive air–sea interaction over the WNP, namely, the strong atmospheric forcing on the ocean. Among CMIP5 models, HRA models, which reproduced intrinsic negative correlations between precipitation and SST over the WNP, could simulate the extreme EASM better than LRA models. In particular, HRA models generated a more realistic spatial distribution of the extreme EASM compared with LRA models. The defects of the LRA models resulted from distorted synoptic fields, including underestimated geopotential height and overestimated low‐level wind over the WNP, inducing unrealistic moisture supply and convection due to the exaggerated SST forcing. In contrast, reasonable air–sea interactions represented in HRA models lead to realistic synoptic fields over the WNP, and proper simulation of the extreme EASM.

Diversity of intraseasonal oscillation over the western North Pacific

The western North Pacific (WNP) intraseasonal oscillation (ISO) is the strongest over the globe, its prediction is the cornerstone for subseasonal prediction of the Asian summer monsoon. Yet, our understanding of the diversity of the WNP ISO is limited, which challenges our modeling and prediction efforts. We study the diversity of observed WNP ISO by performing cluster analysis on propagation patterns of ISO events, targeting three clusters: westward, northeastward, and northwestward propagations. The westward cluster exists within the WNP, while the other two are related to the northeastward propagating rain band originated from the central equatorial Indian Ocean and to the northwestward propagating dipole across the western Pacific and Indian Ocean, respectively. Moist static energy (MSE) tendency contributing to these different propagations is mainly due to horizontal advection, while radiative heating mainly maintains the ISO’s development. Background sea surface temperature (SST) and MSE anomalies partly determine this ISO diversity, especially for those ISOs with large similarity. The westward cluster is related to warm SST anomalies in the western Indian Ocean, as a combination of seasonal cycle and internal interannual-to-interdecadal variability. The northeastward cluster is related to the cold Pacific Meridional Mode and La Nina-like pattern, while the northwestward cluster is related to the opposite warm background, both as the internal variability. Our finding of the background-affected ISO diversity over the WNP can be conducive to both model simulation and subseasonal prediction of the Asian summer monsoon.

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.

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.

Dynamically Downscaled Climate Simulations of the Indian Monsoon in the Instrumental Era: Physics Parameterization Impacts and Precipitation Extremes

AbstractThe complex orography of South Asia, including both the Himalayas and the Tibetan Plateau, renders the regional climate complex. How this climate, especially the monsoon circulations, will respond to the global warming process is important given the large population of the region. In a first step toward a contribution to the understanding of the expected impacts, a series of dynamically downscaled instrumental-era climate simulations for the Indian subcontinent are described and will serve as a basis for comparison against global warming simulations. Global simulations based upon the Community Earth System Model (CESM) are employed to drive a dynamical downscaling pipeline in which the Weather Research and Forecasting (WRF) Model is employed as regional climate model, in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for 15 years (1980–94), with the global model representing a complete integration from the onset of Northern Hemisphere industrialization. Compared to CESM, WRF significantly improves the representation of orographic precipitation. Precipitation extremes are also characterized using extreme value analysis. To investigate the sensitivity of the South Asian summer monsoon simulation to different parameterization schemes, a small physics ensemble is employed. The Noah multiphysics (Noah-MP) land surface scheme reduces the summer warm bias compared to the Noah land surface scheme. Compared with the Kain–Fritsch cumulus scheme, the Grell-3 scheme produces an increased moisture bias at the first western rain barrier, whereas the Tiedtke scheme produces less precipitation over the subcontinent than observed. Otherwise the improvement of fit to the observations derived from applying the downscaling methodology is highly significant.

Moisture flux adjustments in RegCM4 for improved simulation of Indian summer monsoon precipitation

The complexity of the Indian summer monsoon precipitation makes it’s prediction a challenging task as it is not only influenced by the large-scale flows but also by the micro-scale features. In a dynamical model, precipitation is resulted from the formation of clouds. The cloud formation and its processes occur at a micro scale. Current state-of-the-art dynamical models lack proper representation of the cloud processes, particularly at high resolutions for which the cloud processes are parameterized, thereby poorly resolving the precipitation. This study aims at examining the impact of the cloud parameters on the simulation of Indian summer monsoon precipitation in Regional Climate Model version 4 (RegCM4). The autoconversion coefficient which determines the conversion of cloud water into precipitation in the Explicit Moisture Convergence scheme is adjusted in the RegCM4. The impact of autoconversion is experimented with ten different values and it is found that it has a significant effect on the simulation of precipitation during summer monsoon season. The experiments are conducted by changing autoconversion from 1.5 × 10−4 to 7.5 × 10−4/s along with the default value of 2.5 × 10−4/s. On changing the autoconversion values from 60 to 300% of the default value, the precipitation pattern improves over most parts of India. The model simulates the rainfall better when the autoconversion coefficient is changed to 7.5 × 10−4/s. With the best outcome with the adjusted autoconversion and control configuration, the model is simulated for seventeen monsoon seasons and the analyses of RegCM4 simulated vertically integrated moisture transport, convective available potential energy and atmospheric moisture budget suggest that the model efficacy is enhanced in higher autoconversion value than the control one. Statistical evaluations using bias, correlation coefficients, comprehensive rating matrices and skill score confirm the suitability of higher autoconversion rate for summer monsoon simulations. The model with adjusted autoconversion coefficient (at 7.5 × 10−4/s) has improved the representation of seasonal precipitation distribution and its year-to-year variation including other derived features. The rainfall pattern is improved over North West India and North East India especially, the monsoon core regions. The mean seasonal rainfall is in phase 94% of the time with the modeler-adjusted moisture as compared to 82% in the control in the long term simulation.

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.