Indian Monsoon Research Articles

Assessment of CMIP6 GCMs’ Simulation of Southwest Monsoon Rainfall over Indian Monsoon Core Region

Assessment of CMIP6 GCMs’ Simulation of Southwest Monsoon Rainfall over Indian Monsoon Core Region

In-situ observations of cloud microphysics over Arabian Sea during dust transport events

The unique in situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice processes. Cloud base droplet number concentration is about 142 ± 79 cm−3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2% supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion ( ε; the ratio of DSD spectral width ( σ ) to mean radius ( rm )) and liquid water adiabatic fraction (AF) indicates that the entrainment effect has increased relative dispersion significantly (2–3 times larger) in these clouds. Effective radius ( reff ) is found to be proportional to mean volume radius ( rv ) with a proportionality constant ( β ) that varies between 1.0–1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2–50 μ m and the large drizzle drops (or ice hydrometeors) with size range 100–6400 μ m are parameterized using the gamma function distributions useful for large-scale cloud models.

Anomalous Characteristics of Water Vapor Budget on the Tibetan Plateau under the Influence of Tropical Cyclones over the Bay of Bengal during Early Summer

Abstract Early summer is a peak time for tropical cyclone (TC) activities over the Bay of Bengal (BoB) and a period of South Asian monsoon onset, and the TCs during this time have a significant impact on the water vapor transport associated with monsoons. This study investigates the anomalous characteristics of the dynamic–thermal atmospheric circulation structure and water vapor budget over the Tibetan Plateau (TP) under the influence of BoB TCs generated in May from 1979 to 2020 with JTWC best track data and ERA5 data. Results reveal that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. A part of the water vapor is transported directly to the TP by deep southerly jet, while the other part is lifted by TCs and then climbs upward to the TP by two uplift processes occurring on the southern slope of the TP and over the TP respectively, which makes the whole troposphere over the southeastern TP warmer and wetter. It is found that anomalous southeasterly airflow in the northeast of TC circulation turns to anomalous southwesterly airflow forming an abnormal anticyclonic circulation over the southern TP in the middle and upper troposphere due to the diabatic heating effect. In this process, the TP acts as an anomalous water vapor sink with remarkable water vapor inflow through its southern boundary, with the main water vapor outflow through the eastern boundary, but a weak easterly water vapor backflow to the eastern TP in the lower troposphere. Significance Statement This study attempts to investigate the anomalous features of the water vapor budget over the Tibetan Plateau (TP) under the influence of the Bay of Bengal (BoB) tropical cyclones (TCs) during early summer. Results show that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. The TP acts as an anomalous water vapor sink with more and higher water vapor inflows through the southern boundary of the TP. A positive temperature and humidity anomaly can be found over the southeastern TP extending upward into the middle and upper troposphere. The results are helpful to understand how the BoB TCs affect the weather process over the TP.

Eocene Tectonic Uplifts Caused the Early Oligocene Intrusion of the Indian Monsoon Into the Tuotuohe Basin and the Increased Evaporation, Central‐Northern Tibet: Insights From the Oxygen Isotope Record

AbstractIt is not clear how the Asian monsoon evolved after leaving the spatial range of the Intertropical Convergence Zone in the Late Eocene and before the modern‐like Asian monsoon formed at ∼26 Ma. In this study, the results of a well‐dated, robust, and continuous paleoenvironmental carbonate oxygen isotope record from the Tuotuohe section in the Tuotuohe Basin on the central–northern Tibetan Plateau indicate that the carbonate oxygen isotope showed positive bias at 30.5 Ma. Evidence concerning the temperature, precipitation, paleolatitude, paleoelevation, salt mines and global temperature changes at this time suggest that the positive oxygen isotope shift was mainly due to a combination of the intrusion of the Indian monsoon into the basin and increased evaporation, both of which were ultimately induced by the tectonic uplift of the Tuotuohe Basin before 30.5 Ma and the retreat of the Paratethys Sea after the Eocene.

Mitigating against the between‐ensemble‐member precipitation bias in a lagged sub‐seasonal ensemble

AbstractThe Met Office GloSea5‐GC2 sub‐seasonal‐to‐seasonal 40‐member lagged ensemble consists of members who are up to 10 days different in age such that the between‐ensemble‐member bias is not internally consistent. Reforecasts tend to be used to convert these ensemble forecasts into anomalies from a normal state. These anomalies are however not that useful for applications where individual ensemble members are needed to drive downstream applications in the hazard and impact space. Here we explore whether there is a way of correcting for the within‐ensemble bias without using reforecasts. An investigation into the individual daily precipitation distributions from the JJAS 2019 Indian monsoon season, stratified by forecast horizon, highlights how the distribution changes, and shows that the model distribution is markedly different to the observed. Initial results suggest that it could be better to use recent model forecast distribution(s) as the reference for adjusting the model rainfall accumulations as a function of lead day horizon, that is, not attempting to correct the members to a vastly different (observed) distribution shape, but a more subtle shift towards the model's best guess of reality, rather than reality itself, to remove the between‐ensemble‐member bias. A combination of Exponential and Generalized Pareto distributions are used for parametric quantile mapping to remove this internal ensemble bias using computationally efficient pre‐computed lookup tables. Within‐ and out‐of‐sample results for the 2019 and 2020 monsoon seasons show that the method is effective in tightening precipitation gradients, with improvements in spread, accuracy and skill, especially for low accumulations.

Distribution patterns and origins of organophosphate esters in soils from different climate systems on the Tibetan Plateau

Organophosphate esters (OPEs) are extensively applied in various materials as flame retardants and plasticizers, and have high biological toxicity. OPEs are detected worldwide, even in distant polar regions and the Tibetan Plateau (TP). However, few studies have been performed to evaluate the distribution patterns and origins of OPEs in different climate systems on the TP. This study investigated the distribution characteristics, possible sources, and ecological risks of OPEs in soils from the different climate systems on the TP and its surroundings. The total concentrations of OPEs in soil varied from 468 to 17,451 pg g−1 dry weight, with greater concentrations in southeast Tibet (monsoon zone), followed by Qinghai (transition zone) and, finally, southern Xingjiang (westerly zone). OPE composition profiles also differed among the three areas with tri-n-butyl phosphate dominant in the westerly zone and tris(2-butoxyethyl) phosphate dominant in the Indian monsoon zone. Correlations between different compounds and altitude, soil organic carbon, or longitude varied in different climate zones, indicating that OPE distribution originates from both long-range atmospheric transport and local emissions. Ecological risk assessment showed that tris(2-chloroethyl) phosphate and tri-phenyl phosphate exhibited medium risks in soil at several sites in southeast Tibet. Considering the sensitivity and vulnerability of TP ecosystems to anthropogenic pollutants, the ecological risks potentially caused by OPEs in this region should be further assessed.

Influence of long-term observed trends on the performance of seasonal hydroclimate forecasts

Skillful forecasts of hydroclimate variables are essential for operational water management, agricultural planning, and food supply. Several studies have attempted to improve the skill of raw forecasts either by post-processing or by incorporating sea surface conditions into raw forecasts. However, to the best of our knowledge, limited to no study has investigated temporal trend, which is present in observed records but is absent from retrospective forecasts (also known as, hindcasts). The current study understands that a temporal trend can be yielded in raw meteorological forecasts by i) updating surface boundary forcings and ii) applying statistical models for either post-processing meteorological forecasts or issuing streamflow forecasting using weather forecasts as predictors. To analytically derive the relationship between temporal trend and forecast performance, this study applies three statistical approaches for post-processing season-ahead hindcasts of the Indian monsoon obtained from three general circulation models (GCM). The findings show that raw hindcasts of the Indian monsoons typically ignore the temporal trend present in the observed records. Furthermore, analytical derivations confirm that the absence of a trend in GCM hindcasts significantly influences post-processing performance. Moreover, a semi-parametric approach could not overcome the limitations of a parametric linear model in yielding a temporal trend in the hindcasts. Potential reasons for the absence of a trend in the hindcast is also discussed.

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.

Structure of the eastern Arabian Sea upper water column in the middle Miocene: Implications for the development of the South Asian monsoon

Global atmospheric circulation experienced drastic changes during the Middle Miocene climate transition (MMCT∼14.7–13.0 Ma) possibly related to the glaciation on West-Antarctica. Palaeoceanographic reconstructions have found that upwelling in the western Arabian Sea due to summer South Asian monsoon (SAM) winds likely occurred since ∼14.7 Ma, with fully modern-like monsoonal wind patterns after the end of the MMCT at around ∼13 Ma. Whether the changes in monsoonal circulation since ∼14.7 Ma are also associated with upper ocean hydrographic changes in the eastern Arabian Sea (EAS) is currently not known for the middle Miocene. To this end, the difference in Mg/Ca-based temperatures (ΔT°C) of surface-dwelling with lower mixed layer/thermocline-dwelling and sub-thermocline-dwelling planktic foraminifera was reconstructed to estimate the upper ocean thermal gradient at Site NGHP-01-01 A in the EAS and thus changes in the upper surface water column structure, i.e., mixed layer depth (MLD) and the depth of thermocline (DOT). The Mg/Ca-temperature estimates from the upper mixed layer down to the sub-thermocline show a prominent cooling trend between ∼14.2 Ma and 13.2 Ma. The upper water column reconstructions reveal weaker mixing, a shallower thermocline, and therefore a well stratified upper water column in the EAS after ∼14.2 Ma. We suggest that the weaker mixing and shallower thermocline in the EAS after ∼14.2 Ma are most likely due to an intensification of the summer SAM. A strong salinity stratification and/or the formation of a barrier layer (BL) because of increased SAM rainfall and advection of low salinity water may also have contributed to a weaker mixing and shallower thermocline in the EAS during the investigated time period. The change in the upper ocean hydrography in the EAS after ∼14.2 Ma fits well into the emerging picture of monsoonal-driven upper ocean hydrographic changes in the equatorial and northern Indian Ocean due to an intensification of the summer SAM since ∼14.7 Ma.

Orbital forcing of aridity/humidity fluctuations in the Hexi Corridor and Alxa Plateau, NW China, during the last 1.8 million years

The processes controlling aridity/humidity variations in mid-latitude Asia dust source regions on orbital timescales are unclear. Both insolation and polar ice sheets can affect the climate at mid-latitudes, but determining their individual contributions is challenging. Here we present a compilation of paleoclimate data (the content of smectite and aeolian sand, and the proportion of the hydraulic component) from sites in the Hexi Corridor and Alxa Plateau, located at the junction of the regions influenced by the mid-latitude East Asian Monsoon (EAM) and the Westerlies. Our objectives were to determine the links between aridity/humidity variations in this region and Earth orbital forcing and changes in high-latitude ice sheets. We found that the aridity/humidity variations in the Hexi Corridor and Alxa Plateau were paced mainly by the long eccentricity cycle (∼400 ka), facilitating roughly coherent beat in changes of the mass accumulation rate (MAR) and the excursions of thick/coarse loess layers L1, L5, L9, L15 and L24 on the Chinese Loess Plateau. Additionally, spectral analysis of the paleoclimate data revealed that the expression of the Mid-Pleistocene transition (MPT) was spatially variable. A transition between the dominant periodicities in the western Hexi Corridor and Alxa Plateau occurred at ∼0.9 Ma, but in the eastern Alxa Plateau this transition occurred at ∼0.7 Ma. Our data compilation also demonstrates an interval of wet climate in the Hexi Corridor and Alxa Plateau after ∼0.34 Ma, which is consistent with paleoclimate records from loess deposits in Westerlies-dominated Central Asia. We attribute this to insolation forcing via complex internal feedbacks in the Southern Ocean, involving the enhancement of the Atlantic deep-water circulation, and the interplay between Indian Monsoon and the Westerlies. Overall, our findings highlight the importance of the Earth orbital control of aridity/humidity cycles on the boundary of the EAM and the Westerlies in mid-latitude Asia.

Unraveling the Indian monsoon’s role in fueling the unprecedented 2022 Marine Heatwave in the Western North Pacific

An unprecedented marine heatwave (MHW) event occurred in the middle-high latitudes of the western North Pacific during the summer of 2022. We demonstrate that excessive precipitation thousands of kilometers away fuels this extreme MHW event in July 2022. In the upper atmosphere, a persistent atmospheric blocking system, forming over the MHW region, reduces cloud cover and increases shortwave radiation at the ocean surface, leading to high sea surface temperatures. Atmospheric perturbations induced by latent heat release from the extreme precipitation in the Indian summer monsoon region enhance this atmospheric blocking through the propagation of quasi-stationary Rossby waves. Our hypothesis is verified by using a numerical model that is forced with the observed atmospheric anomalous diabatic heating. This study sheds light on how a subtropical extreme event can fuel another extreme event at middle-high latitudes through an atmospheric teleconnection.

Orographic effects on droughts in a monsoon climate with the world's highest rainfall

AbstractDrought, a recurring natural phenomenon in South Asia's monsoon climate, presents challenges in delineating its spatiotemporal patterns within complex topographies. This study investigated the impact of the orographic barrier in the rice‐dominated agricultural region of northeastern India and Bangladesh on drought characteristics during 1951–2020, employing the relative Standardized Precipitation Index (rSPI) and relative Standardized Precipitation‐Evapotranspiration Index (rSPEI) across 3‐, 6‐ and 12‐month scales. The results indicate that even in the rainiest region of the world, droughts extend beyond the limits of the dry season inherent in the monsoon regime. These mostly regional droughts exhibit weak correlations with the core of the Indian subcontinent and other parts of Bangladesh. The region's orographic barrier has a greater influence on drought intensity than on frequency. The rSPI index, which depends solely on rainfall, may overestimate drought intensity and frequency in regions with high seasonal/annual rainfall and substantial intermonthly variability. In contrast, the rSPEI index, which depends on both rainfall and potential evapotranspiration (PET), better reflects the spatial variation of drought in complex terrain, identifying the leeward hinterland of the orographic barrier as the most drought‐prone area. The two indices give similar results for drought characteristics away from the barrier. Furthermore, the orographic barrier exerts a negligible influence on the trends in rSPI and rSPEI. Principal component analysis (PCA) highlights the influences of the rainfall coefficient of variation and elevation on rSPI, while the PET coefficient of variation strongly influences rSPEI. Strategies to minimize the adverse effects of drought in complex topography and year‐round cropping should be local and season‐specific. These include using shorter‐growing, drought‐resistant rice varieties and adjusting planting schedules in rain shadow areas during the summer monsoon. These efforts should be complemented by integrating indigenous irrigation methods with modern practices such as roof water harvesting and tube wells in winter.

Comparative Analysis of Characteristics and Physical Mechanisms for Typical Summer Extreme Precipitation in Pakistan

Abstract The 2022 floods in Pakistan resulted in severe losses and garnered global attention. This study aims to enhance the understanding of extreme precipitation (EP) events in Pakistan by examining the characteristics and mechanisms behind the persistent EP during summer, utilizing daily precipitation data from the Climate Prediction Center (CPC). Results showed that the monsoon precipitation in 2010, 2020 and 2022 are the highest three years on record. Notably, these peak events in 2010 (concentrating in the north) and 2022 (concentrating in the south) spanned from July through August. Conversely, the extreme precipitation in August 2020 was concentrated in northern Pakistan. For the circulation patterns, the intensification of the South Asian High and the western Pacific subtropical high with a strong Indian monsoon is a unifying feature, but the Iranian high and monsoon low-pressure system on the south of Pakistan was different. Additionally, the EP in July 2010 and August 2022 were also influenced by the teleconnection associated with European Blocking. La Niña events and the negative-phase Indian Ocean Dipole (IOD) also played a role in affecting summer EP, with the strongest La Niña occurring in 2010 and a notable triple-dip La Niña coinciding with a significant negative IOD phase in 2022. La Niña contributed to the formation of an anomalously strong anticyclone over the northwest Pacific and easterly winds along the southern Himalayas, impacting moisture transport to Pakistan. Conversely, the negative IOD phase amplified EP in Pakistan by enhancing the northward movement of convective systems and westerly winds over the Indian Ocean. Furthermore, reduced snow cover on the Tibetan Plateau in the springs of 2010 and 2022 likely induced a stronger thermal dynamical effect, acting as a heat source in summer and increasing precipitation in Pakistan.

Characteristics of the Urban Heat Island in Dhaka, Bangladesh, and Its Interaction with Heat Waves

This study examines the characteristics of the urban heat island (UHI) in Dhaka, the densely populated capital city of Bangladesh under the influence of the South Asian monsoon, and its interaction with heat waves. For this, meteorological data at Dhaka (urban) and Madaripur (rural) stations and reanalysis data for the period of 1995–2019 are used for analysis. Here, the UHI intensity is defined as the urban-rural difference in 2-m temperature, and a heat wave is defined as the phenomenon which persists for two or more consecutive days with the daily maximum 2-m temperature exceeding its 90th percentile. The UHI intensity in Dhaka is in an increasing trend over the past 25 years (0.21 °C per decade). The average UHI intensity in Dhaka is 0.48 °C. The UHI is strongest in winter (0.95 °C) and weakest in the monsoon season (0.23 °C). In all seasons, the UHI is strongest at 2100 LST. The average daily maximum UHI intensity in Dhaka is 2.15 °C. Through the multiple linear regression analysis, the relative importance of previous-day daily maximum UHI intensity (PER), wind speed, relative humidity (RH), and cloud fraction which affect the daily maximum UHI intensity is examined. In the pre-monsoon season, RH is the most important variable followed by PER. In the monsoon season, RH is the predominantly important variable. In the post-monsoon season and winter, PER is the most important variable followed by RH. The occurrence frequency of heat waves in Dhaka shows a statistically significant increasing trend in the monsoon season (5.8 days per decade). It is found that heat waves in Bangladesh are associated with mid-to-upper tropospheric anticyclonic-flow and high-pressure anomalies in the pre-monsoon season and low-to-mid tropospheric anticyclonic-flow and high-pressure anomalies in the monsoon season. Under heat waves, the UHI intensity is synergistically intensified in both daytime and nighttime (nighttime only) in the pre-monsoon (monsoon) season. The decreases in relative humidity and cloud fraction are favorable for the synergistic UHI-heat wave interaction.

The Toba Eruption 74,000 Years ago Strengthened the Indian Winter Monsoon‐Evidence From Coccolithophores

AbstractThe global impact of the Youngest Toba Tuff (YTT) supereruption is still heavily debated, ranging from having little effects on climate to significantly affecting modern human evolution. Climate models and proxy records show that the eruption may have caused cooling of the Asian landmass, thus impacting regional climate such as the Indian monsoon system. However, the immediate effect of the eruption on the Indian monsoon has not been indisputably demonstrated in any proxy record. Here, we present a paleo‐primary productivity (PP) record in core SO130‐289KL from the northeastern Arabian Sea based on the coccolithophore species Florisphaera profunda transfer function. Florisphaera profunda decreased from ∼30% before the YTT eruption to ∼8% right after the YTT eruption, which translates to an increase in PP by ∼65% from a long‐term average of ∼200 gC/m2/yr for about 8–19 years after the eruption. The duration was estimated using a new error‐weighted mean age of the YTT eruption (73.9 ± 0.1 ka, 2σ uncertainties) based on recent age estimates from ice cores, radiometric dating, and speleothem records. The elevated PP is most likely linked to the deepening of the surface ocean mixed layer driven by strengthened northeasterly Indian winter monsoon winds. This hypothesis is supported by stable oxygen isotope records from speleothem and ice cores, which show indications of a strengthening of the Indian winter monsoon during times of increased PP. Our results support previous modeling studies and provide unequivocal evidence from a marine record for an Indian monsoon response to the supereruption.

Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes

Predicting the temporal and spatial patterns of South Asian monsoon rainfall within a season is of critical importance due to its impact on agriculture, water availability, and flooding. The monsoon intraseasonal oscillation (MISO) is a robust northward-propagating mode that determines the active and break phases of the monsoon and much of the regional distribution of rainfall. However, dynamical atmospheric forecast models predict this mode poorly. Data-driven methods for MISO prediction have shown more skill, but only predict the portion of the rainfall corresponding to MISO rather than the full rainfall signal. Here, we combine state-of-the-art ensemble precipitation forecasts from a high-resolution atmospheric model with data-driven forecasts of MISO. The ensemble members of the detailed atmospheric model are projected onto a lower-dimensional subspace corresponding to the MISO dynamics and are then weighted according to their distance from the data-driven MISO forecast in this subspace. We thereby achieve improvements in rainfall forecasts over India, as well as the broader monsoon region, at 10- to 30-d lead times, an interval that is generally considered to be a predictability gap. The temporal correlation of rainfall forecasts is improved by up to 0.28 in this time range. Our results demonstrate the potential of leveraging the predictability of intraseasonal oscillations to improve extended-range forecasts; more generally, they point toward a future of combining dynamical and data-driven forecasts for Earth system prediction.

The Contrast Precipitation Patterns in Yangtze River Valley Between the Two La Niña Decaying Summers in 2021 and 2022

AbstractAlthough the summers of 2021 and 2022 are both in the two successive La Niña decaying stages and under the same climate background of negative Pacific Decadal Oscillation (PDO) phase and global warming trend, they exhibit significantly different and even opposite precipitation patterns in the Yangtze River Valley (YRV) as well as in the Indian monsoon region (IMR). In contrast to the abundant precipitation and lower temperature in the YRV in summer 2021, in summer 2022 the YRV experiences severe drought and extremely high temperatures, which is also accompanied by Mega‐floods in the IMR. This study identifies the joint influence of sea surface temperature anomalies (SSTAs) in Niño4 and Barents Sea (BS) regions as the underlying cause for the contrast YRV precipitation anomalies in the summers of 2021 and 2022. Specifically, the cold SSTAs in both Niño4 and BS regions in summer 2021 favor stronger and southward shifted western North Pacific subtropical high (WNPSH), leading to more precipitation in the YRV, which is however generally reversed but more intense in summer 2022 because of the synergistic effect of cold Niño4 and warm BS SSTAs. Moreover, the induced extreme precipitation in the IMR in summer 2022, which is absent in summer 2021 due to the offsetting effect of cold SSTAs in both Niño4 and BS regions, in turn further strengthens the anomalous atmospheric circulations via its released large diabatic heating and serves as a relay pathway for the dramatic drought and heat wave in the YRV.

How the enhanced East Asian summer monsoon regulates total gross primary production in eastern China

Recognizing the relationship between gross primary production (GPP) and precipitation in eastern China, the East Asian Summer Monsoon (EASM) plays a crucial role in shaping GPP. Despite confirmation of the strong link between EASM and GPP, there remains a notable research gap in understanding the specific impact of the EASM on GPP in different regions of eastern China. Here we used simulations from Trends in Net Land–Atmosphere Carbon Exchanges (TRENDY) models from 1951 to 2010 and divided eastern China into five subregions for the study. We also used the New East Asian Summer Monsoon Index (NEWI) as a quantitative metric to distinguish between periods of strong and weak EASM. Building on this, this study aims to investigate the response of GPP in different subregions of eastern China. Regionally, under strengthened EASM years (1954, 1957, 1965, 1969, 1977, 1980, 1983, 1987, 1993 and 1998), East China experienced the most pronounced increase in GPP at 12 ± 21 (mean ± 1 sigma) gC m−2 mon−1 compared to the weak EASM years (1958, 1961, 1972, 1973,1978, 1981, 1985, 1994, 1997 and 2004). In contrast, Southwest China showed a decline in GPP at −4 ± 10 gC m−2 mon−1. Moreover, GPP also increased in Northeast and North China when EASM strengthened, while South China showed a decline in GPP. This indicated that GPP changed with monsoon intensity. According to the mechanism analysis, during strong EASM, there was intense moisture convergence through alterations in the atmospheric circulation field over East China and abundant precipitation, which further contributed to the increase in GPP. Downward solar radiation in Southwest China decreased with EASM enhancement, which suppressed GPP and hindered vegetation growth. Overall, the results highlight the importance of accurately predicting the impact of different EASM intensities of regional carbon fluxes.

All‐sky assimilation of FY‐4A AGRI water vapor channels: An observing system experiment study for south Asian monsoon prediction

AbstractIn this study, a month‐long parallel experiment is conducted to assess the assimilation effects of all‐sky radiance (ASR) versus clear‐sky radiance (CSR) in the single and multiple water vapor (WV) channels provided by the Advanced Geostationary Radiation Imager (AGRI) onboard the Fengyun‐4A (FY‐4A) satellite. The Weather Research and Forecasting model data assimilation system (WRFDA) is utilized for assimilating the FY‐4A AGRI WV observations. Compared with the CSR, the assimilated data of the ASR increases by ~1.7 times in WV channel 9 and around 2.4 times in the multiple WV channels (channels 9 and 10). Both the CSR and ASR assimilation results demonstrate that the simulated brightness temperature (TB) from the WRF analyses is closer to the TB observations from Sondeur Atmospherique du Profil d'Humidite Intertropicale par Radiometrie (SAPHIR) channels 1–2 and Microwave Humidity Sounder (MHS) channel 3, as compared with the control experiment where only conventional data are assimilated. Furthermore, a larger improvement is noted in assimilation of multiple WV channel against assimilation of a single WV channel for both CSR and ASR runs. Overall, the analyses and forecasts generated from the ASR run exhibit superior performance compared with the CSR run when verified against SAPHIR and MHS measurements, as well as the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) analyses. The verification of the rainfall predicted by the WRF against the Global Satellite Mapping of Precipitation (GSMaP) products over India indicates that the assimilation of the ASR in multiple WV channels has the largest impact on rainfall prediction. Moreover, the ASR run demonstrates an accurate prediction of heavy rainfall events that are missed in the control experiment and underestimated in the CSR run.

Hydroclimate variability over the past 4730 years based on multi-proxy stalagmite records from southwest China

Southwest China has experienced a series of record-breaking droughts over the last two decades, threatening regional ecosystems and exerting socioeconomic effects. Recent studies have focused on the drivers of specific drought events that seasonally vary in occurrence and duration, and a better understanding of regional paleo-records may be key to understanding their underlying mechanisms. Here, we present records of dry and wet alterations from 4730 yr B.P. based on multi-proxy stalagmite records. In particular, we report δ13C records at a five-year-resolution, and trace element (Mg, Sr, and Ba) to Ca ratios at a 25-year-resolution for stalagmite HD12 from Dark Cave, southwest China. Statistically significant correlations between δ13C and Mg/Ca suggest that they are controlled by a common factor, possibly related to local hydrological variations associated with the monsoon circulation. Long-term trends in the Sr/Ca and Ba/Ca ratios may be related to temperature- and/or precipitation-controlled growth rates. The first principal component (multi-proxy PC1) of δ13C and Mg/Ca can be used as the hydrological index in southwest China, indicating high-frequency oscillations on the millennial to multidecadal scales, with four prominent dry periods at 4255 ± 21 to 3430 ± 11, 2605 ± 12 to 2105 ± 9, 1755 ± 11 to 1255 ± 13, and 705 ± 8 to 405 ± 7 yr B.P. This is in general agreement with the monsoon index reconstructed from the detrended and z-scored cave δ18O PC1 in southwest China, indicating the sensitivity of regional hydrological response to monsoon intensity. The dry conditions of southwest China on the millennial-centennial scale may be related to solar forcing and the North Atlantic Oscillation owing to their influence on the strength and position of the westerlies and the Intertropical Convergence Zone. Additionally, the El Niño Southern Oscillation could also affect water vapor transport to southwest China by influencing the strength and position of the Walker circulation and Western Pacific Subtropical High. Moreover, the dry periods of southwest China over the past 4730 years are closely related to the warming of the sea surface temperature of the tropical warm pool on multidecadal scales. Such warming may be detrimental to the transport of water vapor from the North Western Pacific and Indian Ocean to southwest China, resulting in a dry regional environment.