Effects of anthropogenic aerosol and greenhouse gas emissions on Northern Hemisphere monsoon precipitation: mechanisms and uncertainty

Northern Hemisphere Land monsoon precipitation (NHLM) exhibits multidecadal variability, decreasing over the second half of the 20st century and increasing after the 1980s. We use a novel combination of CMIP6 simulations and several large ensembles to assess the relative roles of drivers of monsoon precipitation trends, analyzing the effects of anthropogenic aerosol (AA), greenhouse gas (GHG) emissions and natural forcing. We decomposed summer global monsoon precipitation anomalies into dynamic and thermodynamic terms to assess the drivers of precipitation trends. We show that the drying trends are likely to be mainly due to increased AA emissions, which cause shifts of the atmospheric circulation and a decrease in moisture advection. Increases in GHG emissions cause monsoon precipitation to increase due to strengthened moisture advection. The uncertainty in summer monsoon precipitation trends is explored using three initial condition large ensembles. AA emissions have strong controls on monsoon precipitation trends, exceeding the effects of internal climate variability. However, uncertainties in the effects of external forcings on monsoon precipitation are high for specific periods and monsoon domains, and due to differences in how models simulate shifts in atmospheric circulation. The effect of AA emissions is uncertain over the northern African monsoon domain, due to differences among climate models in simulating the effects of AA emissions on net shortwave radiation over the North Atlantic Ocean.

Rain drop size distribution characteristics of cyclonic and north east monsoon thunderstorm precipitating clouds observed over Kadapa (14.47°N, 78.82°E), Tropical semi-arid region of India

Hkkjr ds vkU/kz izns’k jkT; ds v/kZ'kq"d HkwHkkx] dM+ik ¼14-47 fMxzh m-] 78-82 fMxzh iw- ½ esa yxk, x, d.k ds vkdkj vkSj osx ¼ikjohosy½ okys fMLMªksehVj l ‘ty’ pØokr ls mRiUu o"kZ.k es?kksa ¼07 uoEcj 2010½ rFkk mRrj iwoZ ¼,u- bZ-½ ekulwu xtZ okys rwQku ds o"kZ.k es?kksa ¼16 uoEcj 2010½ ds cw¡n ds vkdkj ds forj.kksa ¼vkj- ,l- Mh-½ dks ekik x;k gSA izs{k.kkRed ifj.kkeksa ls gesa ;g irk pyk gS fd pØokr dh otg ls mRiUu o"kZ.k es?kksa esa laoguh o"kZ.k izcy jgkA tcfd mRrj iwoZ ekulwu ds ekeys esa xtZ okys rwQku o"kZ.k laoguh es?k ds Hkkx Lrjh es?kksa dh rwyuk esa vf/kd gSaA pØokr ls mRiUu o"kZ.k] mRrj iwoZ ekulwu o"kZ.k dh rqyuk esa Lrjh {ks= ¼laoguh {ks=½ esa NksVh cw¡nksa ¼NksVh vkSj e/;e vkdkj dh cw¡nksa½ ls laca/k gSA Lrjh vkSj laoguh es?k {ks=ksa esa mRrj iwoZ ekulwu o"kZ.k dh rwyuk esa vkSlr nzO;eku Hkkfjr O;kl] pØokr ls mRiUu o"kZ.k dk Dm de gSA o"kkZ dh cw¡nksa ds vkdkj dk izs{k.k pØokrh; vkSj mRrj iwoZ ekulwu xtZ ds lkFk rwQkuksa ds o"kZ.k es?kksa esa vyx rjg dh fHkUurk ns[kh xbZ gSA Raindrop size distributions (RSD) of “JAL” Cyclone induced precipitating clouds (7 Nov. 2010) and North- East (NE) monsoon thunderstorm precipitating clouds (16 November 2010) were measured with a Particle Size and Velocity (PARSIVEL) disdrometer deployed at Kadapa (14.47°N; 78.82°E), a semiarid continental site in Andhra Pradesh state, India. From the observational results we find that stratiform precipitation is predominant than convective precipitation in cyclone induced precipitation clouds. Where as in the case of NE monsoon thunderstorm precipitation convective cloud fraction is more than stratiform clouds. The cyclone induced precipitation is associated with higher concentration of small drops (small and middrops) in stratiform region (convective region) than NE monsoon precipitation. The average mass weighted diameter, Dm of cyclone induced precipitation is less than the NE monsoon precipitation both in stratiform and convective cloud regions. The observed RSD are found distinctly vary from cyclonic and NE monsoon thunderstorm precipitating clouds.

The effect of ENSO / Anti ENSO on northeast monsoon rainfall

Northeast monsoon precipitation data of 5 meteorological sub-divisions in India, spanning the period 1901-97, were analysed to identify the effect of ENSO/Anti ENSO events on the rainfall over southern peninsular India. ENSO/Anti ENSO years were selected on the basis of seasonal Southern Oscillation Index (SOI). The analysis revealed that ENSO years were generally associated with enhanced northeast monsoon precipitation while there was reduced precipitation during Anti ENSO years, the reduction in Anti ENSO years being significant for Tamil Nadu (at 0.1% level), for Kerala (at 1% level) and for South Peninsular India (at 1% level). Of 22 ENSO years, 18 years were found to be either flood or wet years, while 11 years out of 15 Anti ENSO years were found to be either drought or dry years. During ENSO years, the Sea Surface Temperature (SST) anomalies both over the Arabian Sea and the Bay of Bengal were positive during the months October to December, while the reverse was the case during Anti ENSO years. A concurrent significant positive correlation was noted between SST over east central Arabian Sea and the north central Bay regions and northeast monsoon rainfall. The cyclonic systems were observed to form relatively at lower latitudes during ENSO years as compared to those during Anti ENSO years. These systems were also found to move in a more westerly direction, hit Tamil Nadu and south Andhra coast, thus giving more rain over peninsula during ENSO years. The ridge line at 200 hPa level during ENSO years was located 3° south as compared to its location during Anti ENSO years.

Seasonal and Inter-Annual Variations of Stable Isotopic Characteristics of Rainfall and Cave Water in Shennong Cave, Southeast China, and Its Paleoclimatic Implication

Speleothem calcite stable oxygen isotope (δ18OC) is one of the most widely used proxies in paleoclimate research, and understanding its seasonal-annual variability is very significant for palaeoclimate reconstruction. Five-year precipitation and karst cave water from 2016 to 2021 were monitored in Shennong cave, Jiangxi Province, Southeast China. The local meteoric water line (LMWL) is δD = 8.20 × δ18O + 13.34, which is similar to the global meteoric water line. The stable hydrogen and oxygen isotope (δD and δ18O) characteristics of precipitation and cave water were studied. δ18O and δD of precipitation and cave water show obvious seasonal variations. Lower precipitation δ18O and δD generally occur during summer and autumn compared with higher δ18O and δD values during winter and spring. Meanwhile, low precipitation δ18O values do not only appear in June–July when precipitation is the highest of the year but also appear in August–September when precipitation is limited. The back-trajectory analysis of monsoon precipitation moisture sources shows that the moisture uptake regions vary little on inter-annual scales; the water vapor of rainfall in June–July comes from the South China Sea and the Bay of Bengal, while the moisture source in August–September is mainly from the West Pacific and local area. The El Niño-Southern Oscillation is an important factor affecting the value of δ18O by modulating the percentage of summer monsoon precipitation in the annual precipitation and moisture source. The relationship between amount-weighted monthly mean precipitation δ18O and Niño-3.4 index shows that the East Asian summer monsoon (EASM) intensifies during La Niña phases, resulting in more precipitation in monsoon season (May to September, MJJAS) and lower δ18O values, and vice versa during El Niño phases.

Modulation of summer monsoon sub-seasonal surface air temperature over India by soil moisture-temperature coupling

The influence of soil moisture on the sub-seasonal warmer surface air temperature anomalies during drier soil conditions associated with break spells in the Indian summer monsoon precipitation is explored using observations. The multi-model analysis of land surface states and fluxes available from the Second Global Soil Wetness Project (GSWP-2) are found useful in understanding the mechanism for this soil moisture-temperature coupling on sub-seasonal timescales. The analysis uses a soil moisture-temperature coupling diagnostic computed based on linear correlations of daily fields. It is shown that the summer surface air temperature variations are linked to intraseasonal variations of the Indian monsoon precipitation, which control the land-climate coupling by modulating the soil moisture variations. Strong coupling mainly occurs during dry soil states within the summer monsoon season over the transition zones between wet and dry climates of central to north-west India. In contrast, the coupling is weak for constantly wet and energy-limited evaporative regimes over eastern India during the entire summer monsoon season. This observational based analysis provided a better understanding of the linkages between the sub-seasonal dry soil states and warm conditions during the Indian summer monsoon season. A proper representation of these aspects of land-atmosphere interactions in weather and climate models used for sub-seasonal and seasonal monsoon forecasting could be critical for several applications, in particular agriculture. The soil moisture-temperature coupling diagnostic used in this study will be a useful metric for evaluating the performance of weather and climate models.

Observed and Predicted Precipitation Changes in Pakistan Using Ground Observations, Satellite Data and Model Projections with Special Focus on Winter and Pre-Monsoon Precipitation

This study utilizes ground, satellite and model data to investigate the observed and future precipitation changes in Pakistan. Pakistan Meteorological Department’s (PMD) monthly precipitation data set along with Tropical Rainfall Measuring Mission (TRMM) monthly dataset TRMM_3B43 (0.25˚x0.25˚ resolution) have been used to evaluate rainfall trends over the climatic zones of Pakistan through Man-Kendall test and Sen’s slope estimator for the time period 1978-2018. Community Climate System Model (CCSM4) projections have been employed to explore the projected changes in precipitation till 2099. Furthermore, TRMM and CCSM4 projections have been correlated and validated using Root Mean Square Error (RMSE) and Mean Bias Error (MBE). There is a good correlation between TRMM and PMD ground observation at all stations of the country for all seasons, with correlation coefficient values ranging from 0.89 (November) to 0.97 (July and August). The study shows a decreasing trend in winter precipitation in all zones of the country with a significant decrease over western mountains i.e. zone C of the country. During 2008-2018, a sharp decrease in winter precipitation is observed as compared to the baseline value of 1978-2007 in all climatic zones. There seems to be a shift in precipitation from winter towards pre-monsoon season as pre-monsoon precipitation in last 11 years increased in all zones except Zone C. Coherently, there is a decrease in area affected by winter precipitation and an increase in area for pre-monsoon precipitation. Future precipitation estimates from CCSM4 model for RCP 4.5 and RCP 8.5 over-estimate precipitation in most parts of the country for the first 9 observed years (2010-2018) and predict a rise in precipitation by 2099 which is more pronounced in the northern and western Pakistan while a decrease is predicted for the plains of the country, which might have negative consequences for agriculture.