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/lp/springer_journal/projection-of-seasonal-summer-precipitation-over-indian-sub-continent-a409t725sa
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by The Author(s)
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- Earth Sciences; Atmospheric Sciences; Meteorology; Math. Appl. in Environmental Science; Terrestrial Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
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- 0177-7971
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- 1436-5065
- DOI
- 10.1007/s00703-018-0612-7
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Abstract
Seasonal changes in precipitation characteristics over India were projected using a high-resolution (40-km) atmospheric general circulation model (AGCM) during the near- (2010–2039), mid- (2040–2069), and far- (2070–2099) futures. For the model evaluation, we simulated an Atmospheric Model Intercomparison Project-type present-day climate using AGCM with observed sea-surface temperature and sea-ice concentration. Based on this simulation, we have simulated the cur- rent climate from 1979 to 2009 and subsequently the future climate projection until 2100 using a CMCC-CM model from Coupled Model Intercomparison Project phase 5 models based on RCP4.5 and RCP8.5 scenarios. Using various observed precipitation data, the validation of the simulated precipitation indicates that the AGCM well-captured the high and low rain belts and also onset and withdrawal of monsoon in the present-day climate simulation. Future projections were performed for the above-mentioned time slices (near-, mid-, and far futures). The model projected an increase in summer precipitation from 7 to 18% under RCP4.5 and from 14 to 18% under RCP8.5 from the mid- to far futures. Projected summer precipitation from different time slices depicts an increase over northwest (NWI) and west-south peninsular India (SPI) and a reduction over northeast and north-central India. The model projected an eastward shift of monsoon trough around 2° longitude and expansion and intensification of Mascarene High and Tibetan High seems to be associated with projected precipitation. The model projected extreme precipitation events show an increase (20–50%) in rainy days over NWI and SPI. While a significant increase of about 20–50% is noticed in heavy rain events over SPI during the far future. 1 Introduction and economy of the south Asian countries. The living envi- ronment and society are highly sensitive to the duration of Climate change can be considered as a fluctuation in atmos - extreme events. The agriculture sectors, food, and energy pheric components over a longer time scale and long-term security of India are closely associated with the severity fluctuations in atmospheric components have a major of weather events. Therefore, a proper understanding and impact on human activities. In the recent past, heavy rain advance prediction of the climate change characteristics are events caused by climate change have resulted in devastat- important to respond the adoption policies. ing floods and landslides, causing severe loss of human life The Intergovernmental Panel on Climate Change (IPCC 2007) in the Fourth Assessment report (IPCC AR4) men- tioned an increase in surface air temperature (by 0.2 °C/ Responsible Editor: S. Hong. decade) globally and more frequent occurrences of extreme events like heat waves, heavy rain events, etc. Although * Jai-Ho Oh jhoh@pknu.ac.kr the possible changes in extreme events induced by global warming were described in IPCC report but the horizontal Department of Environmental and Atmospheric Sciences, resolution of the climate models needs more attention. In Pukyong National University, 45, Yongso-ro, Nam-gu, IPCC AR5 (2013), a large number of climate models are Busan 48513, South Korea 2 run of the order of more than 100 km in horizontal resolu- Department of Geophysics, Institute of Science, Banaras tions, due to the centennial to millennial timescales and non- Hindu University, Varanasi 221005, India 3 availability of good computing resources. Although there CRAY Korea Inc, #317, 27, Seochojungang-ro, Seocho-Gu, is a remarkable advancement in climate models during the Seoul 06601, South Korea Vol.:(0123456789) 1 3 898 S. Woo et al. recent few decades, the horizontal resolution of most of the significant increase in total ISMR. While other research- global models is still relatively coarse (above 100 km). This ers (Zhao and Bailey-Kellogg 1998; Ashfaq et al. 2009) avoids them from reproducing the actual sub-grid scale forc- have projected a decrease or minor change in ISMR dur- ings that have a large impact on the climate at the regional ing the same period, Ashrit et al. (2003) have shown that scales. Especially, Indian summer monsoon rainfall (ISMR) future changes in land–ocean contrast could be stronger which accounts approximately 75–80% of the total yearly and projected an increased ISMR are likely to be related to rainfall has shown a large interannual variability in the Asian a northward shift of the Somali jet. Similar results of weak monsoon system. The ISMR is highly affected by complex monsoon westerlies over South Asia can be seen in Ueda interactions of various monsoon processes, irregular topog- et al. (2006) using the subset of CMIP3 models, although raphy, diverse land surfaces, and surrounding oceans (Rajen- projected an increased ISMR in the future. dran et al. 2013). Therefore, it is hard to get an accurate It is well-known facts that the global warming trans- forecast of seasonal precipitation over India for agriculture, ported more moisture in the lower troposphere and these power generation, industry, etc. Rajendran et al. (2013) men- transported moistures are directly related to the condition tioned that the Global Circulation Models (GCMs) generally of extreme precipitation events (Trenberth et al. 2005). failed to capture the detailed features of local climate due to Some of the studies projected a significant change in resolution problem. Therefore, they studied the ISMR and ISMR especially in or after mid-century climate (Ram- extremes weather cases at 20-km high-resolution using an anathan et al. 2005; Ramesh and Goswami 2007; Dash MRI-AGCM for the historical period (1979–2003) and end et al. 2007). While other researchers have shown that the of century (2075–2099) climates. Although it is possible intraseasonal distribution of ISMR will be more extremes to study the future climate projection for a partial period, (Goswami et al. 2006; Dash et al. 2009) in the future. using an ultra-high-resolution model that can represent a Recently, Srivastava et al. (2015, 2016) found an increase better fine-scale structures such as Western Ghats over India in hot days (at the rate of 5.4 days/decade) and a decline in (Rajendran and Kitoh 2008). Due to limitations of the com- cold days (2.4 days/decade) over India. Based on observed puting facility, regional climate models (RCMs) could be gridded data of IMD, they have also shown an increase used for the study of regional details at a high resolution in the frequency of heavy rain events of above 100 and (Giorgi and Mearns 1999; Hong and Kanamitsu 2014; Lee 200 mm/day. The above-mentioned studies clearly indicate and Hong 2014). In general, the performances of RCMs are a large diversity in the model’s results. Hence, more care- highly related to the performance of the GCMs (Saini et al. ful studies using the high-resolution models are needed for 2015), because RCMs use lateral boundary forcings from getting better projection over Indian sub-continent. the GCMs. The present study is, therefore, aimed to investigate the Several studies have examined the changes in ISMR changes in seasonal monsoon characteristics over India and extreme events using different types of the greenhouse from the present-day climate to the future climate (until emission scenarios. Using the Met Office Hadley Center 2100) continuously using a high-resolution Atmospheric coupled model (HadCM3), Turner et al. (2007) projected Global Climate Model (AGCM) on the icosahedral–hex- an increase in ISMR in doubled CO experiment. Meehl agonal grids. After model validation for seasonal mean et al. (2007) found an increase in JJA (June–August) pre- precipitation, circulations, annual cycle with the various cipitation with the larger inter-models spread in projec- observed data sets, we assess the projected changes in tions over India during 2080–2099 in the Coupled Model temperature, precipitation, circulations, extreme indices, Intercomparison Project phase 3 (CMIP3). For extreme etc. Descriptions of the high-resolution AGCM (GME) [it events, Turner and Slingo (2009) investigated the change has been named GME, because it replaced the operational in extreme indices (on 95th and 99th percentile of pre- global model (GM) and the regional model for the central cipitation) using CMIP3 multi-models and found a similar Europe (EM)] and designs of the experiments are intro- change as in mean wind field, but with a larger magnitude. duced in Sect. 2. Section 3 describes the model evaluation. Kripalani et al. (2007a, b) extensively studied the IPCC Projected temperature, precipitation, large-scale circula- AR4 contributing models simulated data sets, found an tions, extreme indices, etc. are discussed in Sect. 4. Our enhancement in summer rain over South and East Asia conclusions are summarized in Sect. 5. regions at the end of the twenty-first century. Sabade et al. (2011) assessed the CMIP3 models and noted that ten models out of total 25, reasonably well-simulated the annual cycles of ISMR over South Asia. They have found a significant decrease in south westerlies wind fields over South Asia in A1B, A2, and B1 scenarios simulations by ten best performing CMIP3 models, but reported a 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 899 simulation like future climate change characteristics over 2 Description of GME model, observed data, Asia region. and simulation details 2.2 Experiment design 2.1 GME model With GME, simulations are performed for (a) present-day The GME (AGCM) used here is an operational global climate for evaluating model performance and (b) continu- Numerical Weather Prediction (NWP) model of German ously for selecting desired three-time slices in the future Weather services (Majewski et al. 2002). The GME worked for climate change projection. For the model evaluation, on uniform icosahedral–hexagonal grids (brief descrip- we have performed the present-day climate simulation at tions about grid shape generation are given in Appendix 1). 40-km horizontal resolution for 30-year periods from 1979 This method provides two advantages: first, it avoids the to 2008 (considered as a present-day/current/reference cli- pole problem in latitude–longitude grids which is a major mate). In the present study, we simulated an Atmospheric drawback of spectral technique. Second, it provides the data Model Intercomparison Project (AMIP)-type present-day structure which is well-suited and enhanced the efficiency of climate using a GME (40-km) with sea-surface tempera- distributed memory parallel computers. The mass flux con- ture (SST) and sea-ice concentration (SIC) data observed vection scheme was used for the cumulus parameterization by the National Center for Atmospheric Research (NCAR) (Tiedtke 1989). For long-term simulation, the mass correc- following a procedure described by Hurrell et al. (2008). In tion was applied in GME model (Chaudhari 2006). In this addition, for the future climate projection, GME was first study, GME has been run at high resolution (n = 192, L40) integrated for the present-day climate from 1979 to 2009 and such as 40-km corresponding to T 511 of ECMWF, where sequentially future climate simulation from 2010 to 2100 n is the number of equal intervals into which each side of with the future SST and SIC boundary conditions. These the original icosahedral triangles is divided. In n 192 (40- boundary data are the projected SST and SIC of the Cen- km mesh size), the number of grid points are 368,642 and tro Euro-Mediterraneo sui Cambiamenti Climatici Climate transform grid uses 900 × 451 grid cells. GME has 40 levels Model (CMCC-CM) of the Coupled Model Intercompari- in vertical with a model top at 10 hPa. Detailed descriptions son Project phase 5 (CMIP5) participating models based on of the GME experiment are summarized in Table 1. the Representative Concentration Pathway (RCP) scenarios Chaudhari (2006) described the model performance in by IPCC Fifth Assessment Report (AR5). The CMCC- NWP mode by simulating the severe weather events like CM (Scoccimarro et al. 2011) model has a relatively high typhoons and associated heavy precipitation events over East resolution (0.75° × 0.75°) in CMIP5 models. Both monthly Asia. In long-term seasonal prediction, model performance observed and projected SST and SIC data are converted into was tested by examining the impact of sea-surface tem- daily data using temporal linear interpolation technique. In perature and associated atmospheric conditions over South addition, we forced the changes in CO concentration and and East Asia monsoons. Recently, using GME, Woo et al. other greenhouse gasses yearly from RCP database (refer- (2018) have projected the teleconnection between South ence: http://www.iiasa.ac .at/ web-apps/tnt/RcpDb) for future and East Asian summer monsoon systems during twenty- climate simulation. first century and recommended for the study of long-term 2.3 Observed data Table 1 Detail descriptions of the GME model configuration The model performance was evaluated in the present-day climate simulation. Here, monthly precipitation from CPC Model configuration Merged Analysis of Precipitation (CMAP) data at 2.5° lat/ Horizontal resolution 40 km (ni192) long grid for 30 years (1979–2008) by Xie and Arkin (1997) Grid points 900 × 451 and the Global Precipitation Climatology Project (GPCP) Vertical levels 40 (top at 10 hPa) data on 2.5° lat/long grid for 30 years (1979–2008) by Adler Time step 133.33 s et al. (2003) and Huffman et al. (2009) have been utilized. Convection scheme Tiedtke (1989) To analyze the detailed characteristics of precipitation over Cloud microphysics Doms and Schättler (1999) Indian landmass, the gridded data of India Meteorologi- Radiative transfer of solar and thermal Ritter and Geleyn (1992) cal Department (IMD) were also studied. Its spatial reso- radiation lution is 0.5° lat/long grid and it covers only over Indian Vertical turbulent fluxes Müller (1981) land points (Rajeevan et al. 2006). For other variables, we Sub-grid-scale orographic effects Lott and Miller 1997 have considered the National Center for Environmental Pre- Soil model Heise and Schrodin (2002) diction/Department of Energy (NCEP/DOE) Reanalysis II 1 3 900 S. Woo et al. data (Kanamitsu et al. 2002, hereafter NCEP2) from 1979 2008 (30 years). GME-simulated seasonal precipitation in to 2008 with the spatial resolutions of 2.5°. summer (JJAS) and winter (DJF) is compared to the above- mentioned observed data sets for the period 1979–2008 (Fig. 1). The simulation for the present-day climate has been 3 Evaluation of present‑day climate started from 1979, because observed GPCP precipitation is simulations available from that year only. Here, the present study focuses on surface temperature (at 2 m) and precipitation character- 3.1 Seasonal precipitation istics. Statistical correlation shows that the model represents the spatial features perfectly well with a very high magnitude The GME model is used first time for projecting mean sea- of pattern correlation (> 0.9) between model and observed sonal monsoon characteristics in summer (JJAS) and winter (NCEP2) surface air temperature. (DJF) over India at 40-km horizontal resolutions in three The observed climatological summer monsoon (JJAS) different time slices in the future during the twenty-first precipitation features have found the belts of high pre- century. Therefore, a proper validation is required to make cipitation over western Ghats, northeast India and north- certain whether GME is able to simulate the present-day ern Bay of Bengal (BoB), while a low precipitation over monsoon condition before analyzing the future projection. northwest India and east coast of India (Fig. 1a). The mean Seasonal precipitation simulated in the present-day climate JJAS precipitation simulated by GME (Fig. 1b) is able to is validated against the observed precipitation data sets of reproduce these belts of high and low precipitation reason- GPCP (precipitation data available over entire South Asian ably well. For winter (DJF) season, GME well-captured domain) and IMD (only over land points on 0.5° × 0.5° the precipitation over Jammu and Kashmir regions, north- grids). We have evaluated the long-term climate simulation east and southern tips of India mainly over Tamilnadu at a 40-km horizontal resolution over India from 1979 to and Kerala regions. However, model underestimated the Fig. 1 Climatological seasonal mean precipitation (mm/day) during d GPCP observation, b and e GME and c and f seasonal biases in 1979–2008 (30 years) in a–c JJAS (June–September) and d–f DJF GME. The dotted patterns present the level of significance at 95% (December–February) over South Asian monsoon region in a and 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 901 precipitation over north and northeast regions (Fig. 1d, by black dots. Large biases are noticed over oceanic sec- e) in DJF. Figure 1c, f illustrates the precipitation biases tors, while low biases can be seen over landmasses. in GME and GPCP during JJAS and DJF seasons. Com- Seasonal precipitation and biases in GME simulation pared to the GPCP, the model depicted high positive biases against the IMD data set during JJAS and DJF seasons over (Fig. 1c) of 5–7 mm/day over large parts of the oceanic the Indian landmasses are also analyzed and are shown in regions and extreme northeast India in JJAS. GME-sim- Fig. 2a–f. Compared to the IMD, GME has shown the ulated precipitation has a positive bias of 1–5 mm/day positive and negative biases over large parts of India and over NCI (central northeast India) and negative biases over they are similar to those in Fig. 1. However, major dif- west Ghat (5–7 mm/day). While large portions of penin- ferences can be seen over the peninsular India, where sular India have shown negative biases of less than 3 mm/ GME-simulated precipitation has negative biases of up day. Similar biases of high and low precipitation zones are to 1–3 mm/day over large parts of peninsular India. Over also mentioned in Preethi et al. (2017a, b) using CMIP5 northeast and north-central India, GME has positive biases model. During DJF (Fig. 1f), positive biases can be seen of up 1–5 mm/day in JJAS. While in DJF (Fig. 2d, e), above the equator and negative biases below the equator GME simulation has shown a very low bias over Jammu over the Indian Ocean. While over Indian landmass, GME and Kashmir, north India, and northeast India. Here also, well-captured (large white portions) the precipitation pat- similar nature of biases is noticed, as shown in Fig. 1c, f. terns. To examine whether the biases are significant, we It is interesting to note that GME has shown less biases have applied the statistical significant tests on the biases with IMD compared to GPCP over Indian land masses (Fig. 1c, f). The biases at 95% significant level are shown especially in JJAS. It is also appears that GME behaves Fig. 2 Climatological seasonal mean precipitation (mm/day) during tion, b and e GME and c and f seasonal biases in GME. The dotted 1979–2008 (30 years) in a–c JJAS (June–September) and d–f DJF patterns present the level of significance at 95% (December–February) over Indian landmass in a and d IMD observa- 1 3 902 S. Woo et al. differently over different parts of the Indian land mass. 3.2 Wind analysis This suggests that the model-simulated biases in seasonal precipitation could be attributed to errors in simulating The present section compares the performance of GME the exact locations of precipitation maxima, as reported in in simulating the mean JJAS wind fields with NCEP2 several other global models also (Annamalai et al. 2007). (observed) at lower (850 hPa) and upper (200 hPa) levels. Figure 3a–c presents the variations in JJAS mean pre- The main features of the winds during JJAS are westerlies cipitation in the first (1979–1988) and last (1999–2008) at lower and easterlies at upper levels. Another important decades for IMD, GPCP, and GME. Analysis indicates that feature of the wind at the lower level is low-level jet over the the GME (Fig. 3c) well-captured the observed character- Arabia Sea and a huge anticyclone (called Tibetan anticy- istics of IMD (Fig. 3a) with an increasing precipitation clone) at the upper level. Figures 4a, c and 5a, c display the bands in the foothills of Himalaya and over east coast of observed (NCEP2) and model (GME)-simulated JJAS wind India. Over northeast India, IMD and GPCP have shown fields, and Figs. 4b, d and 5b, d show the difference wind a decreased precipitation of 2–5 mm/day compared to the e fi lds between the initial and last decades during 1979–2008 GME (1–2 mm/day). While over the west coast, GPCP has at 850 and 200 hPa, respectively. Results indicate that the shown the largest decrease in precipitation of 5 mm/day GME well-reproduced the mean position of the low-level compared to the GME and IMD. It is interesting to note jet at 850 hPa and upper level Tibetan anticyclone and east- that over Indian landmass, high precipitation spreads over erly jet (EJ) over the latitude of southern parts of India at large parts of India in IMD and GME (large green and blue 200 hPa. The wind at 850 hPa is underestimated over the patches) compared to the GPCP. The maximum increase Arabian Sea, but GME realistically reproduced the cross- in JJAS precipitation can be seen in IMD and GME in equatorial flow from southern to northern hemisphere and the range of 1–5 mm/day and only 1–2 mm/day in GPCP southeasterly trade winds in the lower troposphere (Fig. 4c). (Fig. 3). While a maximum decrease in precipitation was The GME satisfactorily simulated the weaker monsoon 5 mm/day (northeast) in IMD and GPCP (west coast), but westerlies over the Arabian Sea during last decade of the less than 2 mm/day (northeast and west coast) can be noted present-day climate (Fig. 4b, d). However, GME simulates in GME. Results of the above analysis indicate that the stronger easterlies over the head BoB, which brings mois- GME closely captured the important features of observed tures from BoB and provides high precipitation over the cen- patterns of seasonal rain in the present-day climate simula- tral northeast and northeast India (as shown in Figs. 1 and tion compared to GPCP. The purpose of the initial and last 2). Similar results are also noted from the analysis of wind decade’s analyses is to assess whether GME reproduces circulation at 200 hPa (Fig. 5a–d). Where GME underesti- the characteristics of seasonal precipitation within the pre- mated the EJ and Tibetan anticyclone in the final decades of sent-day climate period. This analysis definitely enhances the present-day climate simulation, which is noticed in the the belief and confirms the use of GME for the study of observations (Fig. 5b, d) also. The present analysis of wind future climate characteristics. Overestimated precipitation circulations at lower and upper levels appear to be well- in GME can be investigated by examining the wind fields. represented in GME. Fig. 3 Changes in mean JJAS precipitation over India between the initial and final decades in the period of 1979–2008 in a IMD observation, b GPCP observation and c GME simulation. The dotted patterns present the level of significance at 95% 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 903 Fig. 4 Mean wind (m/s) fields at 850 hPa in JJAS and their changes between initial and final decades in the period of 1979–2008. The top (a, b) panel represent the NCEP/NCAR Reanalysis II and bottom (c, d) panel represent GME simula- tion, respectively Gadgil 1980). It is to be noted that the northward pro- 3.3 T ime latitude variations in monthly gression of the oceanic convective zone approaches close precipitation to 30°N over the Indian longitude. Compared to other observed data sets, a northward progression of high pre- The performance of GME in reproducing the annual cycle cipitation band can be seen in IMD and GME also. A high of monthly rain over this large domain is investigated to magnitude of northward propagated precipitation of 7 mm/ understand how the model performs in different months. day (yellow contour) can be seen in IMD (above 30°N), Figure 6 shows the annual cycle in zonal-averaged pre- GME (close to 30°N), GPCP (close to 28°N), and CMAP cipitation over the Indian monsoon region (67°–99°E). (close to 26°N). GME well-captured the northward pro- Here, we have used three observational (GPCP, CMAP, gression and retreat of monsoon from May to September and IMD) data sets for validation of GME performance. during summer monsoon season over India (67°–99°E). Propagation of precipitation over India depicts the dis- Although, GME underestimated the seasonal precipita- tinct northward propagation characteristics of rainband tion amount below 20°N (West central region), but well- (Fig. 6a–d) that a gradual northward propagation of rain- captured the peaks near 20°N (Western Ghats) and below band from south to north is discernible from April to July. 30°N (northeast India) when compared to the IMD. While The dominant precipitation activity starts from June to other two observational data due to relatively coarse reso- September and a retreat after August is noticeable over lution could not be captured these peak positions clearly. India. Other noteworthy features are the presence of the From this validation, it appears that a high-resolution Convergence Zone over the equator (not shown here) or model can be used for the study of monthly and seasonal zonally aligned zones of precipitation (Sikka and Gadgil precipitation over India. 1980) in the southern hemisphere (10°S–Equator). In general, an enhanced (suppressed) precipitation over the oceanic equatorial zone is related to the suppressed (increased) convection over Indian landmass (Sikka and 1 3 904 S. Woo et al. Fig. 5 Same as in Fig. 4 but for the wind at 200 hPa Fig. 6 Climatological (1979–2008) zonal-averaged monthly mean precipitation (mm/day) over Indian (67–99°E) for a GPCP, b CMAP, c IMD, and d GME (present day). The black contour line depicts precipitation of 2 mm/day in CMAP observation These comparative studies of climatological precipitation, 4 Projection of climate and extreme events circulations, and seasonal migration of precipitation patterns over Indian sub-continent suggest that the GME has abun- 4.1 Projected annual temperature and precipitation dant reasons for its true use to investigate the changes in the twenty-first century climate over south Asia. Figure 7a, b depicts the GME-projected annual tempera- ture and precipitation relative to the present-day climate 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 905 Fig. 7 Interannual (dashed lines) and multidecadal (11-year moving average, solid lines) variations of a 2 m temperature anomalies (°C) and b precipita- tion anomalies (mm/day) rela- tive to the present-day climate (1979–2008) during twenty-first century (2010–2100). The blue and red contours represent the RCP4.5 and RCP8.5 scenarios, respectively (1979–2008) for RCP4.5 and RCP8.5 scenarios over India Figure 7b presents the annual precipitation (mm/day) over from 2010 to 2100. Figure 7a shows that the GME (RCP8.5) Indian landmass from 2010 to 2100 relative to the present- simulated annual temperature increasing rapidly after 2070 day climate (1979–2008) based on two RCP scenarios. Cat- compared to GME (RCP4.5). The year 2096 (6.17 °C) is egorizing the GME-projected flood (based on precipitation projected as the warmest year under RCP8.5, while 2081 ≥ 1σ) and drought (precipitation ≤ − 1σ) cases under both (3.67 °C) under RCP4.5 during the twenty-first century. the scenarios, the present analysis listed 23 floods and 11 Categorizing the number of warm cases (years) having an droughts under RCP4.5, while 11 floods and 22 droughts in increase of annual temperature above 2 and 3 °C, analy- RCP8.5. Here, regression analysis does not show any trend sis identifies 35 cases of above 2 °C and 5 cases of above in precipitation means precipitation. For listing the com- 3 °C under RCP4.5, with RCP8.5, analysis found 52 cases mon years of projected droughts and floods within the both of above 2 °C, 37 cases of above 3 °C, 23 cases of above scenarios, the analysis found only three cases in floods and 4 °C, 13 cases of above 5 °C, and only one case of above two in droughts. It is interesting to note that 7 floods year out 6 °C (2096) during the study period. While considering the of 23 under RCP4.5 scenario are listed in droughts category common cases of warm years within the both scenarios, under RCP8.5. Here, higher scenario shows higher drought results noted a list of 33 cases of above 2 °C and only five and a lesser flood cases. (2068, 2073, 2080, 2081, and 2084 cases) of above 3 °C. It is worth to note that the maximum common warm cases are 4.2 Projected seasonal summer monsoon after 2070. It implies that there is a strong evidence of warm- precipitation ing of above 2 °C after 2070 compared to the present-day climate. Considered time slices projections show a warm- In this section, projected changes in summer monsoon pre- ing of 0.7 °C in the end of 2040 s (near-), 1.8 °C in 2070 s cipitation over India and its surrounding oceanic sectors are (mid-) and 2.4 °C during the end of the twenty-first century studied in detail. As discussed earlier, we have analyzed for (far future) over Indian landmass relative to the present-day the near-, mid-, and far-future time slices and each time slice climate under RCP4.5. While a warming of 0.8, 2.4, and consists of 30-year period, as mentioned in Figs. 8 and 9, and 4.6 °C is projected with RCP8.5 during the same periods, the the period 1979–2008 represents a present-day climate. The regression analysis shows an increasing trend in surface air possible changes in the future for the twenty-first century temperature under both the scenarios, but the rate of increase are computed by subtracting the present-day climate from is higher in a higher scenario. the futures. Figures 8a–g and 9a–g present the GME-simu- lated mean precipitation in JJAS for the present-day and for 1 3 906 S. Woo et al. Fig. 8 GME-simulated mean precipitation (mm/day) in JJAS for a the RCP4.5 scenario and their future changes in percentage during e present day (1979–2008) and projected climates in b near- (2010– near-, f mid-, and g far-future climates (right most column). The con- 2039), c mid- (2040–2069), and d far- (2070–2099) futures under tours present the level of significance at 95% three-time slices in the future based on RCP4.5 and RCP8.5 during the same period under RCP4.5. While for RCP8.5, scenarios, respectively. The right columns of Figs. 8 and 9 Fig. 9e–g shows an increase of about 5–50% over the SPI illustrate the changes during the near-, mid-, and far-future and WPI from the near- to far-future periods and a decrease periods. Since India is vast country and JJAS precipitation of about 15% over NWI in the near future. This analysis shows large spatial variations within the same monsoon does not support the finding of Dash et al. (2015) using a year. Therefore, it is advisable to emphasize over its differ - RegCM4 model and Josepth et al. (2016), and both the stud- ent homogeneous regions also to get better regional informa- ies have reported a reduction in seasonal precipitation over tion. Over Indian landmass, Fig. 8e–g depicts an increase in the southern parts of India in mid-century. After all, most precipitation over northwest India (NWI), south peninsular of the study has suggested a revival of summer monsoon India (SPI), and west peninsular India (WPI) in the range of precipitation activity similar to the GME projection in the 4–19% from the near- to far futures and a decrease of about far future. Over the Arabian Sea, high successive precipita- 5% in precipitation is noted over the northeast India (NEI) tion is noted from the near- to far-future periods under both 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 907 Fig. 9 Same as in Fig. 8, but for the RCP8.5 scenario the scenarios, but the rate of increase over the Arabian Sea future precipitation changes. Most of the research papers is larger in higher forcing (RCP8.5) compared to the stable mentioned an increase in seasonal summer precipitation over (RCP4.5) scenario. Analysis of percentage change in pro- India in spite of weak south westerlies and tropical circula- jected JJAS precipitation relative to the present-day climate tions. They have stated that the warming climate enhanced over Indian landmass shows an increase of about 7.4% in the moisture fluxes towards the continent and it leads to near-, 7.6% in mid-, and about 18% during the far future high precipitation (IPCC 2007; Stevenson et al. 2006; Ueda under RCP4.5. While a little change in near-, but an increase et al. 2006). The other monsoon systems play a key role in of about 14–18% is projected during the mid-to-far future increasing/decreasing the seasonal precipitation, are mon- under RCP8.5. soon trough, Mascarene High, and Tibetan High, and are also investigated in the present study. 4.3 Projected seasonal circulations The projected change in wind fields at 850 hPa for the above-mentioned scenarios during the near-, mid-, Some of the past studies found a wind–precipitation para- and far-future climates is illustrated in Figs. 10a–g and dox over the Asian monsoon sectors while estimating the 11a–g, respectively. The wind patterns show anomalous 1 3 908 S. Woo et al. Fig. 10 GME-simulated mean wind (m/s) field at 850 hPa in JJAS for RCP4.5 scenario and their corresponding changes (in m/s) in e near-, a present-day (1979–2008) climate and projected in b near- (2010– f mid-, and g far-future periods 2039), c mid- (2040–2069), and d far- (2070–2099) futures under the northeasterly/easterly flows and are dominant over large AR4 models under different global warming experiments parts of India indicating a weakening of westerlies in both and this weakening could be associated with hydrological the emission scenarios. A similar weakening in wind com- cycle (Vecchi and Soden 2007; Held and Soden; 2006). In ponent (precipitation–wind paradox) can be seen in Ueda mid-period under both scenarios, the changes in circulations et al. (2006) under different scenarios simulations. Com- are significant mostly in Northern Hemisphere. While for pared to RCP4.5, the RCP8.5 scenarios have shown stronger the far future, there is an indication of weak circulation in northeasterly/easterly flows over the study domain from the Southern Hemisphere. This weak circulation during different mid- to far-future periods. However, there is an indication time slices suggests that the cross-equatorial flow declines of southerly/southwesterly winds over the Arabian Sea and itself in strength due to global warming. A similar weak- a part of Pakistan close to 20°N, and west of 60°E indicated ening in monsoon circulations is also suggested in Tanaka some shifting in the monsoonal flow. A similar weakening et al. (2005) during the far-future climate. The model pro- of circulation systems is also mentioned in most of the IPCC jected anomalous northeasterly flow over BoB carrying a 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 909 Fig. 11 Same as in Fig. 10, but for the RCP8.5 scenario moisture fluxes over the Indian sub-continent and it can be 4.4 Projected components of monsoon circulation attributed with the projected high precipitation over India system (as found in Sect. 4.2). It is also to be noted that over head Bay of Bengal, there is an indication of anomalous anti- In the present section, we will investigate the changes in cyclonic circulation from the mid- to far-future periods in various components of summer monsoon systems, namely, both the scenarios, which prevents the evaluation and growth Monsoon Trough (MT), the Mascarene High (MH), and of westward moving low-pressure systems during monsoon upper tropospheric Tibetan High (TH) in the near-, mid-, season, supports Singh et al. (2014), who has mentioned a and far-future periods relative to the present-day climate significant decline in the frequency of cyclonic disturbances condition using GME model. The MT is an elongated zone during recent periods. of a low-pressure system which extends from northwest India to head BoB during the northward progress of summer monsoon. The MT oscillates in north and south directions from the climatological normal. When it is shifted close to the foothills of Himalayas, a break monsoon conditions is 1 3 910 S. Woo et al. noticed over large parts of India. The position of MT is gen- edge exhibited a westward shift by more than 2° longitudes erally represented by the mean sea-level pressure. relative to the present-day climate mainly during the mid- Figure 12a, b depicts the GME-projected climatological to-far-future periods. This large westward shifting can be position of the south Asian MT under two different emis- considered as a weakening of the MT, and projected low sion scenarios (RCP4.5 and RCP8.5) in the present-day precipitation in JJAS over the northeast and north-central (reference), near-, mid-, and far-future periods. An eastward India (as mentioned in Sect. 4.2) during the mid- and far- extension of the eastern edge of the MT into BoB is gener- future periods. ally considered as a favorable condition for good monsoon Another prominent component plays an important role activities over South Asia. The used model, in general, has for ISMR is Mascarene High (MH). The location of MH projected the patterns (intensity) similar to the present-day can be traced on mean sea-level charts and it is normal climate under both the scenarios. The western edge of the position mentioned over the West Indian Ocean close to trough is located around 67.5°E and eastern edge is around the Madagascar. It is interesting to note that the strength of 87.5°E in the present-day climate. It is interesting to note MH directly associated with monsoon westerlies and mois- that the GME-projected elongated zone of low-pressure area ture flux over the Indian landmass. Similar to MT, the MH is be noticed in west close to the northwest India and Paki- swings north–south and east–west directions from its normal stan. There is no any significant shift in west portion of MT position during JJAS season. Figure 13a, b illustrates the while comparing with the present-day climate, but an eastern projection of MH using the above-mentioned scenarios in the present-day (black contour), near- (green), mid- (blue), and far- (red) future periods. Figure 13a, b shows an inten- sification of MH mainly towards the eastern edge compared to the west edge relative to the present-day climate. A more eastward extension can be seen in RCP8.5 as compared to Fig. 12 GME-simulated mean position of South Asian summer Fig. 13 GME-simulated mean position of Mascarene High (MH) monsoon trough in JJAS, represented by closed contours in mean in JJAS, represented as closed contours in mean sea-level pressure sea-level pressure (hPa), during present day (1979–2008, black con- (hPa), during present day (1979–2008, black contours) and pro- tours) and projected future climates in the near- (2010–2039, green jected future climates in the near- (2010–2039, green contours), mid- contours), mid- (2040–2069, blue contours), and far- (2070–2099, red (2040–2069, blue contours) and far- (2070–2099, red contours) future contours) future using a RCP4.5 and b RCP8.5 scenarios with the a RCP4.5 and b RCP8.5 scenarios 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 911 the RCP4.5 during the study period. A large eastward exten- sion as compared to the westward under both the scenarios can be linked with weak monsoon westerly over the Arabia Sea and a slightly stronger easterly/northeasterly over BoB as noticed in wind analysis (Sect. 4.3) during the near-, mid-, and far-future periods. Third important component considered in the present study is Tibetan High (TH). The TH plays very important role in enhancing the heat low over India in JJAS and finally ISMR (Wei et al. 2014). It is a high-pressure area at 200 hPa (strong anticyclone) over the Tibet regions. The TH is ori- ented from east to west directions and generally centered on 88°E. The westerlies are dominant to north of TH and easterlies to south. The spatial distribution of seasonal pre- cipitation is closely connected with the strength and position of TH during the monsoon period. An intensification and expansion of TH in the present study is depicted by upper tropospheric (200 hPa) geopoten- tial height (Fig. 14). Strengthening of westerlies in the north- ern flank and weakening of easterlies in the southern flank of TH are associated with the expansion of TH. Figure 14a, b shows an expansion and intensification appears more in west limb rather than its east limb in the near-, mid-, and far- future periods compared to the present-day climate. South- eastward (northwestward) shift of TH is associated with less (high) precipitation over India particularly over NEI and Fig. 14 GME-simulated mean position of South Asian High in JJAS, represented as closed contours in geopotential height (m) at 200 hPa, north-central India and this is consistent with the results of during present day (1979–2008, black contours) and projected future Preethi et al. (2017a, b) which is using observation data sets climates in the near- (2010–2039, green contours), mid- (2040–2069, (Preethi et al. 2017a) and based on CMIP5 coupled model blue contours) and far- (2070–2099, red contours) future with the a projections (Preethi et al. 2017b). Southeastward extension RCP4.5 and b RCP8.5 scenarios of TH (Fig. 14a, b) can be associated with low precipita- tion mainly over northeast India (as mentioned in Sect. 4.2). The orientation and strength of TH are very closely associ- warming requires more detail study on extreme precipitation events. An attempt for the projection of extreme precipita- ated with the increased sea-surface temperature (SST) over the Indian and west Pacific Oceans (Zhou et al. 2009). Fig- tion events over India under global warming scenarios is thus more fruitful to elaborate any national climate change ure 14a, b shows that the western edge of TH is expanding more southeastward rather than northwestward compared to mitigation policies. Here also, a GME model is used to project the changes the present-day climate under both the scenarios during the twenty-first century can be attributed with high precipitation in the behavior of future summer (JJAS) extreme precipita- tion intensity in JJAS under the above-mentioned emission over large parts of India. scenarios. We have examined the several extreme precipita- tion indices, as discussed in Klein et al. (2009) and Zhang 4.5 Projected seasonal summer monsoon extreme precipitation events et al. (2011). The WDAY is defined as the number of rainy days having daily precipitation ≥ 1 mm/day and R20D pre- Under the background of global warming, extreme events sents the number of heavy rainy days of ≥ 20 mm/day. We have also studied the longest spells of consecutive dry days also changed in frequency and intensity, even more sig- nificantly than the mean climate. Meehl et al. (2007) pro- (CDD) (daily precipitation < 1 mm/day). Figure 15a–r illus- trates the future changes in extreme precipitation indices like jected an increase in heavy rain events over wide portions of the continent and also seasonal summer precipitation is WDAY, R20D, and CDD in three-time slices as mentioned above relative to the present-day climate (1979–2008) over likely to be increased. They also mentioned that the fea- tures of extreme events will be more devastating in nature India. Analysis of Fig. 15a, b depicts that over northwest India, WDAY increases by 5–20% under RCP4.5 and around on regional scales. For Indian sub-continent, a country with a vast territory that is also sensitive to the impact of global 5–10% over south peninsular India in RCP4.5 and RCP8.5 1 3 912 S. Woo et al. Fig. 15 Assessment of changes (%) in seasonal (JJAS) extreme pre- precipitation < 1 mm/day) for the near- (2010–2039), mid- (2040– cipitation indices in a–f WDAY (number of days having precipita- 2069) and far- (2070–2099) futures relative to the present day (1979– tion ≥ 1 mm/day), g–l R20D (number of days having precipitation 2008) over Indian landmass with the RCP4.5 and RCP8.5 scenarios, ≥ 20 mm/day) and m–r CDD (longest spells of consecutive dry days; respectively. The contours present the level of significance at 95% in the near future. While during the same period, RCP8.5 In the case of CDD (Fig. 15m–r), it shows a reverse pat- projected a decrease of about 5–10% in WDAY over large tern especially over northwest and north-central India under portions of central India (Fig. 15b). During the mid-to-far- both scenarios. RCP4.5 projects an enhancement of 5–10% future periods, both the scenarios projected a significant in CDD over northwest India and a reduction over large (95% level) increase of about 20–30% in WDAY (Fig. 15c–f) parts of the central northeast India, while RCP8.5 projects over the west-southern peninsula. Moreover, RCP4.5 pro- a reverse pattern; an increase in the central northeast and jected a significant increase of about 5–10% over large parts a decrease over northwest India in the near-future climate. of central India during the far future, while a decrease of While for the mid future, the patterns are nearly similar as in about 5–50% is projected over large parts of India under the near future with RCP4.5, but major differences are noted RCP8.5 during same period (far future) (Fig. 15f). Both in RCP8.5 which covers a larger area of CDD compared to the scenarios have projected a decrease in WDAY over the RCP4.5 over Indian landmass. Again, during the far-future northeast India during the twenty-first century (Fig. 15e, f). period (Fig. 15q, r), both the scenarios projected an inten- For the heavy rain events, analysis of Fig. 15g, i, k shows sification in CDD, a reverse pattern as in the near future. an increase of 5–50% in R20D over northern parts of India RCP4.5 have shown a decrease in CDD over north-central in the near future, small portion of northwest India and India and an increase over northwest India, while RCP8.5 over a wide area of peninsular India in mid- and a gradual projects an increase in CDD over north-central India and intensification and spread over larger portions during the a decrease over northwest India. Here also, over northeast far future with RCP4.5. While for RCP8.5, Fig. 15h, j, l India, there is an increase in CDD over larger portions in the shows a reduction in R20D over large portions of north India near future which is gradually intensifying up to more than and an increase of 10–50% over peninsular India in the near 30% and spreads over larger areas in the far future with both future. The R20D intensifies and widens from the mid- to far the scenarios. A comparison of CDD spells under both the future over the northwest and south peninsular India. Here scenarios depicts that the CDD is largely increasing with also, GME projects a reduction in R20D over larger parts of RCP8.5 as compared to the RCP4.5 over large parts of the northeast India and an enhancement over the peninsula and Indian landmass. A large number of drought cases projected northwest India with both the scenarios. under RCP8.5 (see Sect. 4.1) may be attributed to the high 1 3 Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution… 913 CDD events over large parts of India as compared to the modulate the southwesterly flow over the south Asia and RCP4.5. precipitation variations are well-matched with the changes Overall, analysis of seasonal extreme rain events sup- in large-scale circulation systems. The analysis of projected ports the outcome of Kumar et al. (2006) and Krishnamurthy heavy rain events (R20D) with both the scenarios has shown et al. (2009) who have mentioned a significant increase in an increase of about 10–50% over northwest India and west- heavy rain events over large parts of northwest and south- south peninsular India, while the analysis of CDD (long- west regions and a decrease in central northeast India. The est spell of dry days) shows a reverse pattern within both outcome of the present research is in tune with the other the scenarios from the near- to far-future climates. Over model’s projection (i.e., an increase in heavy rain events and India, the projected high precipitation is in line with the a reduction in weak events) in warming climates over India most of the global model projections (IPCC 2007) and a (Meehl et al. 2000; Semenov and Bengtsson 2002). broad direction of projected extreme events of the present study is also consistent with the other model results, as men- tioned in Kumar et al. (2006) and May (2004). Although a 5 Summary and conclusions high-resolution GME may not able to capture accurately the regional climate details in the present-day climate simula- The present paper uses a high-resolution atmospheric Gen- tion, but these results may provide important information to eral Circulation Model (GME) for the study of future cli- estimate regionally detail temperature increase and changes mate change over India during the twenty-first century. For in precipitation pattern over South Asia especially over the this long-term climate simulation, we have performed the Indian regions. These results might be utilized to set up present-day climate simulation at a 40-km horizontal reso- both national and regional adaptation strategies for global lution for 30 years (1979–2008) using AMIP observation. warming. For future climate projection, GME is integrated from 1979 Acknowledgements The authors want to acknowledge the Korea Mete- to 2009 for the present-day climate and subsequently the orological Administration research and Development Program under future climate simulation from 2010 to 2100 with RCP4.5 Grant KMIPA 2015-6130. We also want to acknowledge the Global and RCP8.5 scenarios. Before the analysis of future climate Science experimental Data hub Center (GSDC) Project, Korea Institute of Science and Technology Information (KISTI) for using computing projection over India, GME reliability was evaluated by resources. simulating the seasonal monsoon precipitation and annual cycle and it is validated against three observation precipita- Open Access This article is distributed under the terms of the Crea- tion (CMAP, GPCP, and IMD) data sets and seasonal circu- tive Commons Attribution 4.0 International License (http://creat iveco lations against the NCEP2. Validation shows that the GME mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- captures the seasonal precipitation pattern satisfactorily tion, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the over India with a reliable pattern correlation of above 0.9. Creative Commons license, and indicate if changes were made. The occurrence of high precipitation over the west coast of India, the head of BoB, and its extension towards the south of the equator are also well-reproduced. The analysis of the present-day climate shows that the GME captured the major Appendix 1 precipitation characteristics like high precipitation belts over northeast and west coast of India and low precipitation over Grid generation in GME model northwest and east coast of India. GME also well-captured the annual cycle, onset, and withdrawal of seasonal precipi- To generate the geodesic grids, a regular icosahedron tation validated against the various observed data sets. (Fig. 16) is constructed inside the sphere, such that 2 of its The future projections of precipitation with both the sce- 12 vertices coincide with the North and South Poles. Five of narios have shown a systematic increase over wider por- the other 10 vertices are spaced at equal longitudinal inter- tions of India from the near- to far future. This consists of vals of 72° (= 360°/5) along a latitude circle at 26.565°N, strengthening of summer precipitation over northwest India, the other 5 a long a latitude circle at 26.565°S. Connecting south peninsular India (5–50%), and weakening of mon- nearest neighbors among these 12 points with great circle soon over the northeast India and Gujarat (20–30%) regions arcs divides the spherical surface into 20 equal spherical compared to the present-day climate condition. Projected triangles (Fig. 16a). Beginning from this grid, a new finer large-scale circulation features associated with the seasonal grid of triangles is generated by connecting mid-points of precipitation depict a westward shift especially in MT over the spherical triangle sides by an additional set of great cir- south Asia by 2°–3° longitude and the associated large-scale cle arcs (Fig. 16b). This process may be repeated until a response of MH and an expansion of upper tropospheric TH grid of the desired resolution is obtained (Fig. 16c, d). This are also evident. These changes in large-scale circulations 1 3 914 S. Woo et al. 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Journal
Meteorology and Atmospheric Physics – Springer Journals
Published: May 31, 2018