Near Future Projection of Indian Summer Monsoon Circulation under 1.5 °C and 2.0 °C Warming

Abstract

The Indian summer monsoon’s (ISM) response to low (1.5 °C) and medium (2.0 °C) warming scenarios are examined during the period 2021–2050 using 11 member ensembles of the state-of-the-art Community Earth System Model, version 1 (CESM1-CAM5) datasets. We find that in the near-term period an increase in warming by 0.5 °C will strengthen the monsoon circulation and precipitation over the Indian landmass and east Asia. Under the 1.5 °C warming scenario, the ISM circulation will weaken, and precipitation will exhibit a decreasing trend, while the ISM precipitation and circulation will strengthen under the 2.0 °C warming scenario. The strengthening of ISM under the 2.0 °C warming scenario is due to the strengthening of the South China Sea (SCS) anticyclone and a high-pressure center near the Philippine Island. This high-pressure center over the SCS will facilitate a cross-basin strengthening of the easterly wind from the western Pacific Ocean/SCS to the equatorial Indian Ocean, which will, in turn, strengthen the transport of the Pacific-origin moisture to the Indian subcontinent and East Asia. This increase in moisture content over the Indian subcontinent will strengthen the monsoonal circulation and precipitation under the 2.0 °C warming scenario.

1. Introduction

As an integral part of the global climate system, the Indian summer monsoon (ISM) is generally characterized by the seasonal migration of the Intertropical Convergence Zone [1,2] and the establishment of cross-equatorial surface flow resulting in the north–south pressure gradient. About 80% of annual rainfall in India occurs during the summer monsoon season (June, July, August, and September—JJAS), which is crucial for agricultural and industrial activities [3]. The interannual and intraseasonal variability of the ISM often has a strong impact on agriculture and water resources. As a fully coupled ocean–land–atmospheric system, the ISM and its variability are often very challenging to understand and predict. Although the future climate trajectory lies on the combination of anthropogenic climate change and internal variability at the global scale, human-induced or anthropogenic climate change is likely to dominate over internally generated variability [4,5]. The climate response to the rising concentrations of greenhouse gases (GHGs) and tropospheric sulfate aerosols are associated with human activities involving a complex set of feedbacks within the climate system [6]. In the context of the summer monsoon circulation, modeling studies have projected an enhanced ISM precipitation with increasing CO₂ levels [7], which is accompanied by an intensified interannual variability [8] and large regional differences [9]. As the observed global mean atmospheric temperature (GMAT) has increased over the twentieth century, several attempts have already been made to project monsoon circulations under different scenarios of radiative forcing with the GCMs [10]. Ueda et al. [11] have investigated the impact of the ISM on the transient increase in future anthropogenic radiative forcing using multi-model global runs. They reported that the ISM rainfall is likely to increase significantly due to global warming and an increase in moisture transport. Also, they showed that the large-scale monsoon circulation is projected to weaken due to a reduction in meridional thermal contrast in the ISM region. Based on the multi-model ensemble mean technique, Kripalani et al. [12] showed a significant increase in the mean south Asian summer monsoon precipitation by 8% but a weakening of the monsoon circulation.

According to the Paris agreement, the global mean temperature rise should be below 2.0 °C, and efforts should be made to limit it to 1.5 °C. Recently at the Glasgow Climate Change Conference (COP26) of the United Nations Framework Convention on Climate Change (UNF-CCC), the participating agencies reaffirmed the long-term global goal to hold the increase in the global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change. Global temperature rises and its impact on the climate is an important topic to study. The specific warming levels (SWLs) approach is a better way to understand and quantify the magnitude of climate change. These SWLs are explained in terms of a 1.5 °C and 2 °C global temperature rises with respect to the pre-industrial level.

From the latest studies using global coupled models, there is a widespread consensus that the ISM rainfall will increase in the 21st-century warming climate [13,14,15,16,17,18,19]. Sharmila et al. [18] projected substantial changes in the daily-to-interannual variability of the ISM under the RCP8.5 scenario. They reported that on the seasonal scale, the all-India summer monsoon means rainfall is likely to increase moderately in the future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large-scale monsoon circulation. Based on the 32 models from the coupled model, intercomparison project phase 6 (CMIP6), Katzenberger et al. [20] showed a substantial increase in the JJAS mean rainfall under Socioeconomic Pathways (SSP-8.5) [20]. Furthermore, studies have shown that the global monsoon domain will be expanded except for the North American monsoon; also, rainfall intensity will increase in a warming climate [15,21,22]. A recent study by Mondal et al. [23] indicated that as the degree of global warming increases, the changes in the magnitude of extreme events will also intensify. By analyzing the latest CMIP6 models they further showed precipitation extremes over south Asia are likely to intensify with continued warming. Maharana et al. [24] studied future changes in the ISM circulation under SWLs using a set of 12 regional climate simulations under the Coordinated Regional Climate Downscaling Experiments-South Asia (CORDEX-SA). They reported that the increase in global temperature to 1.5 °C (2 °C) SWLs leads to an earlier onset of the ISM over India by 7 (11) days, and the resulting higher land-sea temperature contrast gradually increases the strength of the Findlater jet (by 0.5–0.9 m/s), which transports more moisture towards land and causes higher rainfall (increase by 2–10%) over India.

Although CMIP models are frequently used to assess uncertainty in future climate projections, the spread in the CMIP projections results from both model formulation differences and internal climate variability, the relative importance of which is unknown. Unlike the CMIP ensemble spread, the National Center for Atmospheric Research (NCAR) Community Earth System Model, version 1 (CESM1) [25], large ensemble projection mean spread is due to the internal climate variability alone. Thus, to explicitly address the projected changes in the summer monsoon precipitation and circulation under low warming of 1.5 °C and 2.0 °C, respectively, we use datasets from an ensemble of transient coupled climate simulations of the CESM1-CAM5 low warming dataset over the entire Asian summer monsoon (ASM) region. Our results demonstrate an increasing summer monsoon precipitation over the South and East Asia at the 2 °C warming scenario. It suggests an improved adaptation measure, particularly water resource planning, will be required to cope with the projected increase in monsoon rainfall over the South and East Asia. To identify and quantify the projected changes in rainfall and climate shifts for which stakeholders could find themselves unprepared, information is extracted from individual large ensemble members to explore the probabilities for low and medium warming scenarios. In this study, we use the ensemble mean of 11-member climate change simulations conducted with the CESM1-CAM5 model. The ensemble mean represents the contribution due to external forcing factors on the near-term projection trends of monsoon circulation and rainfall under the 1.5 °C and 2.0 °C warming scenarios. We mainly concentrate on two key climate parameters, i.e., low-level wind and precipitation during the summer (JJAS) monsoon months.

2. Data and Methodology

CESM1-CAM5 model projection dataset is used in this study [26]. CESM1-CAM5 is one of the better-performing models in the CMIP5 archive [27]. It consists of coupled atmosphere, ocean, land, and sea ice component models. It also includes a representation of the land carbon cycle, diagnostic biogeochemistry calculations for the ocean ecosystem, and a model of the atmospheric carbon dioxide cycle [28,29]. It is a coupled CMIP5 model with identical initial conditions for all the ensembles except for slight differences (10⁻¹⁴ K) in the initial air temperature field. It first documents a simple climate model emulator, which can predict the transient evolution of GMAT and using this emulator it produces concentration scenarios that result in stable 2 °C and 1.5 °C scenarios in the CESM1 for the 21st century. The simulations are using CESM1-CAM5 at a 1° horizontal resolution. The CESM1-CAM5 1.5 °C and 2.0 °C projects are specifically designed to achieve the goal of the 2015 Paris Agreement [26]. The scenarios employ an emulator to simulate both the GMAT and emission concentration evolution in the Earth systems, and the parameters in the emulator were calibrated using the CESM1 simulations [26]. In these simulations, before 2017, the carbon emissions follow the RCP8.5; then, the combined fossil fuel and land carbon emissions rapidly decline to net zero. Finally, the emission fluxes are reduced to negative to ensure that the GMAT achieves the 1.5 °C and 2.0 °C warming targets by 2100.

All simulations within one ensemble only differ by perturbation in their atmospheric initial state [26]. The simulations are available for 11 ensemble members at the 1.5 °C and 2 °C warming scenarios. This includes one ensemble member with extended output, including high frequency for regional downscaling. Every individual simulation can be considered as a superposition of intrinsic variability and external forcing factors [30]. In general, multimodel ensembles, such as the CMIP5 model simulations, are often used for climate projections. However, there exist uncertainties in this approach because of structural differences among the models, which can lead to different externally forced responses [31]. A large ensemble of a single model with slightly different initial conditions is, therefore, suitable for future projection. In this study, we employed the ensemble mean of 11 members of the same model with identical external forcings. This methodology can sufficiently mask the randomly generated internal variability and estimate the response due to external factors only. The CESM1-CAM5 1.5 °C and 2.0 °C low warming products can be downloaded from https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.lowwarming.html (accessed on 26 May 2022).

Here, JJAS ensemble means precipitation, wind at 850 hPa, specific humidity, and sea level pressure (SLP) data from the CESM1-CAM5 projection (2021–2050) at the 1.5 °C and 2.0 °C scenarios are analyzed over the ASM region (10° S–40° N, 30° E–180°). Here, linear trend is used, which is estimated by a linear fit equation,

$$Y_i=A+B{X}_i$$

(1)

where, X_i, Y_i, A and B are the independent, fitted dependent variable, intercept, and slope, respectively. A and B can be estimated using the linear least square fitting method.

We also analyze internal climate variability. In doing so, we estimate the transient forced response (Ft) by taking the ensemble mean at each time step:

$$F_t=\frac{{{\displaystyle \sum }}_{e=1}^n{f}_{et}}{n}$$

(2)

where f_et is a single ensemble member with ensemble number e at time step t. To robustly estimate the internal variability (InV) at time t, we then remove the ensemble mean (F_t) from each ensemble member (f_et) and calculate the variability (here as the standard deviation) across the ensemble:

$$InV=std\left(f_{et}-F_t\right)$$

(3)

This method allows us to estimate the transient InV. InV arises from atmospheric, oceanic, land, and cryospheric processes and their coupled interactions. InV in climate is known to have important effects on climate change projections, especially at regional spatial scales and subdecadal time scales [30,32]. The future climate projection in individual model realizations results from the superposition of InV and the response to external forcing (i.e., GHGs increases). To illustrate this point, we partition the total trends into contributions from the forced response (obtained by averaging all ensemble members) and the InV (obtained by subtracting the forced response from the total trend).

3. Results

Here we demonstrate how precipitation and the summer monsoonal circulation over the ASM will change at the 1.5 °C and 2.0 °C warming scenarios. Figure 1a,b shows the near-term (2021–2050) projection of summer monsoonal (JJAS) precipitation trend at the 1.5 °C and 2.0 °C scenarios, respectively. Under the 1.5 °C warming, precipitation exhibits an increasing trend over east Asia, equatorial west Pacific Ocean, and southwest Indian Ocean. On the other hand, the precipitation trend will decrease over the Indian subcontinent, Bay of Bengal, southeast Indian Ocean, and Indonesian archipelagoes. Unlike the 1.5 °C warming, under the 2 °C warming, precipitation will likely increase over the Indian landmass, along the path of the Somali Jet over the Indian Ocean and off the coast of Sumatra and equatorial eastern Indian Ocean. In addition, the increasing trend in precipitation becomes stronger over east Asia and southern China, whereas it becomes weaker over the equatorial western Pacific Ocean. Therefore, a difference in warming by 0.5 °C will facilitate a substantial increase in summer monsoonal precipitation over the ASM region. In the following section, we investigate the possible reason underlying the increasing trend in precipitation and changes in the ISM circulation pattern in the warming climate.

According to the Clausius–Clapeyron (C–C) relationship, an increase in global temperature will enhance precipitation [33]. Multiple pieces of literature also suggested an increase in global monsoon precipitation due to an increasing amount of water vapor in the atmosphere under global warming [11,33,34]. Wang et al. [35] analyzed the changes in the East Asian summer monsoon (EASM) circulation caused by El Niño and the Southern Oscillation (ENSO) that may occur more frequently due to global warming. They further found that a strong (weak) EASM tends to occur about two to three seasons after the Niño-3 SST anomalies exceed 1.5 °C, a delayed response by the ENSO. Interannual variability of the EASM circulation was observed in response to the increase in GMAT. Therefore, to investigate the pattern of monsoon circulation in response to the low warming, we analyze 850 hPa wind and moisture transport. Figure 2a,b illustrates the projection of low-level monsoon wind (850 hPa) at the 1.5 °C and 2.0 °C, respectively. Under the low warming scenario, i.e., 1.5 °C warming (Figure 2a), the ISM wind at 850 hPa exhibits a weakening trend. The wind vectors along the path of the Somali Jetstream are seen more equatorward, i.e., opposite to the climatology, which implies a near-term weakening of the ISM circulation under the 1.5 °C warming scenario. However, the easterly wind over the equatorial southern Indian Ocean along the eastern coast of the Indonesian islands and the Indonesian through flow (ITF) strait strengthens significantly at 1.5 °C warming. Therefore, at 1.5 °C warming, the eastern and western Indian Ocean will behave differently; on the other hand, under the 2.0 °C warming scenario, the monsoon circulation is likely to strengthen over the Indian Ocean. The equatorial easterly wind over the Indian Ocean, stretching from the Indonesian archipelagoes to the Arabian Sea strengthens the ISM circulation (Figure 2b). A strong anticyclone over the South China Sea (SCS) centered near the Philippines extends westward and merges with the equatorial easterly wind over the Indian Ocean. Therefore, a cross-basin propagation of the easterly wind vectors from the western Pacific Ocean/SCS to the equatorial Indian Ocean is evident from the projection. To illustrate the near-term (2021–2050) projection of moisture transport, we analyze the JJAS trend in vertically integrated moisture transport (VIMT, integrated over the surface to 200 hPa) in Figure 3. Under the 1.5 °C warming, we observe an increase in VIMT over the equatorial west Pacific Ocean and the east Indian Ocean, adjacent to the Indonesian coastline. Although under the 2.0 °C warming scenario, the VIMT is projected to strengthen over the equatorial Indian Ocean and the west Pacific Ocean, compared to the 1.5 °C warming scenario. An intriguing aspect of the VIMT trend under the 2.0 °C warming is that more Pacific-origin moisture fluxes appear to transport from the Celebes Sea, south of the Philippine islands to the Indian Ocean through Borneo and the Indonesian archipelagos. Over the Indian Ocean, the VIMT increases along the equatorial easterly wind and stretches from the Indonesian coastline in the east to the African coastline in the west, which substantially increases the Indian Ocean moisture content under the 2.0 °C warming. The strengthening of Pacific-origin moisture flux transport is due to the strengthening in anticyclone over the SCS, which causes the moisture to converge south of the Philippine Island and make its pathways to the Indian Ocean. The increase in moisture fluxes over SCS and the Indian Ocean under the 2.0 °C warming may influence the SCS and the ISM monsoon precipitation.

Since the ISM circulation depends largely on the north-south pressure gradient, we examine the behavior of SLP in response to the forced climate change. In Figure 4a, the ensemble means the projected trend in SLP decreases continuously over East Asia, the north Pacific Ocean, and central Asia, whereas the trend is increasing over the Indian subcontinent under the 1.5 °C warming (Figure 4a). From this figure, it is evident that the Arctic is warming substantially, and this warming is further extended toward East Asia. With an increase in 0.5 °C warmings (Figure 4b), i.e., at the 2.0 °C warming the JJAS mean SLP increases significantly over the SCS anticyclone, which is centered near the Philippines. In addition, under the 2.0 °C warming, the SLP decreases substantially over the extreme north Pacific Ocean, while the band of positive SLP trend strengthens over the Indian subcontinent and the Indian Ocean and extends towards Central Asia and the west Pacific Ocean.

Figure 5 depicts the standard deviation (STD) of InV in SLP under two scenarios. The more prominent InV is noticed from the projection of SLP over the far north Pacific Ocean. As the warming increases, we see a much higher STD of InV over the far north Pacific Ocean, as well as over the Eurasian region, which overlaps with the increasing trend of SLP over there. Therefore, it can be said that the importance of internal climate variability in SLP over the far north Pacific is likely to influence the monsoon projection pattern in the warmer climate. Such internal variation in climate projection is largely a consequence of the chaotic nature of the large-scale atmospheric circulation patterns, and these internal variation and uncertainty in projection are unlikely to be reduced as models improve or as GHGs trajectories become more accurate.

The high-pressure center over the SCS under the 2.0 °C warming strengthens the SCS anticyclone, which in turn strengthens the low level (850 hPa) monsoon wind from the western Pacific Ocean/SCS (near the Philippines) to the eastern Indian Ocean. A cross basin strengthening of easterly wind vectors from the western Pacific Ocean/SCS to the equatorial Indian Ocean strengthens the transport of Pacific origin moisture to the Indian subcontinent. In Figure 1, under the 2.0 °C warming scenario, we observe a decreasing trend in precipitation on and around the SCS anticyclone, while the precipitation is projected to increase along the easterly Jetstream. In near-term, the precipitation is projected to increase over Indonesia, the equatorial Indian Ocean, the Arabian Sea, the central Indian landmass, and east Asia. Therefore, the ISM rainfall and circulation will likely strengthen under the 2.0 °C warming scenario, compared to the 1.5 °C warming scenario. On the other hand, over East Asia, the projected precipitation increase can be linked to the extension of Arctic warming (band of low SLP as seen in Figure 4) and the presence of north Pacific internal variability. Moreover, D. Choudhury et al. [36] illustrated that the low-level jet usually diverts towards east Asia in response to an extension of low SLP bands over there, thus strengthening the EASM monsoon precipitation.

4. Conclusions

The ISM response to low (1.5 °C) and medium (2.0 °C) warming scenarios are examined using the CESM1-CAM5 state-of-the-art model. We analyze the period from 2021 to 2050 to determine the near-term projection of the ISM circulation and rainfall. It is demonstrated that an increase in warming by 0.5 °C will enhance the monsoon precipitation over the Indian landmass, East Asia, and along the path of the Somali Jet over the equatorial Indian Ocean. We then investigate the mechanism underlying the increase in the summer monsoon precipitation under the 2.0 °C warming scenario. We observe that at the 1.5 °C warming scenario the monsoon circulation over the western Indian Ocean will likely weaken and the monsoonal precipitation will exhibit a decreasing trend, while the ISM precipitation and circulation will strengthen under the 2.0 °C warming scenario. In addition, under the 2.0 °C warming scenario, the SCS anticyclone will be stronger, and a high-pressure center will develop near the Philippines. This high-pressure center will facilitate a cross-basin strengthening of the easterly wind vectors from the western Pacific Ocean/SCS to the equatorial Indian Ocean, which will strengthen the transport of Pacific origin moisture to the Indian subcontinent and East Asia. This will increase the monsoon precipitation over the Indian subcontinent and will strengthen the monsoon circulation under the 2.0 °C warming scenario. As the warming increases, we see much higher STD of InV in SLP over the far north Pacific Ocean, as well as over the Eurasian region, which overlaps with the increasing trend of SLP over there. Therefore, the importance of internal climate variability in SLP over the far north Pacific is seen to influence the ISM projection pattern in the warming climate.

Although model systematic biases in simulation still cause great concern for climate modelers, we recognize that climate projections are inherently uncertain because a model can never fully describe the system that it attempts to specify. To project near-term future climate in the presence of internal climate variability is a major challenge for climate prediction. The CESM1 addresses this challenge through its transparent experimental design and relevant accessible outputs. Initial illustrative CESM1-CAM5 results affirm that because of the internal climate variability, single realizations from climate models are often insufficient for model comparison to the observational record, model intercomparison, and future projections. We anticipate our analysis based on the CESM1 ensemble will inspire probabilistic thinking and inform planning for the summer monsoon community and related stakeholders. However, we also need to take into consideration the uncertainty in climate projections, which is attributed to three main factors: emissions scenario uncertainty, model response uncertainty, and natural variability. However, despite the improvement of climate models or accuracy of the projections of GHGs concentrations, uncertainty in future climate change due to natural variability is unlikely to be reduced given the inherently unpredictable nature of unforced climate fluctuations.