Explore the vast range of titles available.

Birch ( Betula ) trees and forests are found across much of the temperate and boreal zones of the Northern Hemisphere. Yet, despite being an ecologically significant genus, it is not well studied compared to other genera like Pinus , Picea , Larix , Juniperus , Quercus , or Fagus . In the Himalayas, Himalayan birch ( Betula utilis ) is a widespread broadleaf timberline species that survives in mountain rain shadows via access to water from snowmelt. Because precipitation in the Nepalese Himalayas decreases with increasing elevation, we hypothesized that the growth of birch at the upper timberlines between 3900 and 4150 m above sea level is primarily limited by moisture availability rather than by low temperature. To examine this assumption, a total of 292 increment cores from 211 birch trees at nine timberline sites were taken for dendroecological analysis. The synchronous occurrence of narrow rings and the high interseries correlations within and among sites evidenced a reliable cross-dating and a common climatic signal in the tree-ring width variations. From March to May, all nine tree-ring-width site chronologies showed a strong positive response to total precipitation and a less-strong negative response to temperature. During the instrumental meteorological record (from 1960 to the present), years with a high percentage of locally missing rings coincided with dry and warm pre-monsoon seasons. Moreover, periods of below-average growth are in phase with well-known drought events all over monsoon Asia, showing additional evidence that Himalayan birch growth at the upper timberlines is persistently limited by moisture availability. Our study describes the rare case of a drought-induced alpine timberline that is comprised of a broadleaf tree species.

India has observed increasingly persistent heat extremes in recent decades. North‐Central India, a highly populated region prone to heatwaves, has experienced record maximum temperatures (>${ >} $ 48°C) during the pre‐monsoon season. While studies have shown positive trends in heatwaves due to rising air temperature, we identify a shift in pre‐monsoon mean daily maximum temperature over North‐Central India, resulting in an increase in temperature by 0.7°C post‐1998. The jump in temperature is associated with a northward migration of the subtropical westerly jet since 1998. We find that the meridional shift in the subtropical westerly jet explains more than 25% of the variability in heatwave characteristics over North‐Central India, implying that the increase in heatwaves post‐1998 is associated with a northward shift of the jet. These findings highlight that the exacerbation of heatwaves in North‐Central India is driven by atmospheric dynamical changes triggered by a regime shift, further compounded by global warming. Plain Language Summary In recent years, India has been experiencing more frequent and intense heatwaves, especially over the North‐Central region. We found that since 1998, the temperature over North‐Central India has increased by about 0.7°C during the pre‐monsoon season. This increase appears to be due to the northward displacement of the band of strong upper tropospheric winds, known as the subtropical westerly jet. The shifting in the jet stream is making the heatwaves occur more frequently and last longer, exacerbating heatwave risks in this densely populated region. Overall, our findings emphasize the importance of understanding how winds have changed in the atmosphere due to natural variability or climate change and their contribution to the intensification of heatwaves in the region. Such understanding has potential applications in forecast of heatwaves in India. Key Points The pre‐monsoon season witnessed a regime shift in 1998, resulting in a rise in temperature over North‐Central India The subtropical westerly jet index positively correlates with the heatwave characteristics, explaining more than 25% of heatwave variability The increase in heatwaves post‐1998 can be partially attributed to the northward shifting of the subtropical westerly jet

Abstract Despite a significant increasing trend in historical food grain production (FGP) in India, deficient Indian summer monsoon rainfall (ISMR) often causes a reduction in FGP. The present study was carried out to understand temporal and spatial variations in deficient rainfall (drought) and their impact on national and regional FGP of India. Long-term (1901–2020) percentage departure in rainfall and drought areas over the country showed nonsignificant and significant trends, respectively. Subdivisional rainfall showed significant decreasing and increasing trends in 4 and 5 subdivisions, respectively. Drought years of high frequency (once in 3–4 years) and 4 to 5 consecutive drought years (once in 120 years) occurred in northwest and western subdivisions of India. Departure in de-trended production of All India Kharif food grains from its normal (DDP) showed significant quadratic relationship with departure in ISMR from its normal (DRF). Besides the quadratic equation, another multiple regression model taking de-trended crop area, DRF, and drought area as predictor variables was developed for predicting DDP. Both these models, with high R2 (0.8–0.88) between observed and predicted data and low RMSE (2.6–2.7%), can be employed for advanced estimation of DDP of the country and for taking country-level policy decisions by the Indian Government. For the first time, models were formulated to estimate state-wise departure in FGP (DP). In these models, novel indices viz., (i) rainfall departure and irrigation index (RDII) and (ii) physical and socio-economic index (PSEI), were used as predictor variables. These models, with R2 (0.71–0.75) and RMSE of 11.8–14.2(< SD of observed data), hold promise for advance estimation of production loss in states, useful for regional-level planning by the Government of India, and testing them in other countries.

The quality and completeness of rainfall data is a critical aspect in time series analysis and for the prediction of future water-related disasters. An accurate estimation of missing data is essential for better rainfall prediction results. This study suggests a novel approach for estimating missing rainfall data using Multilayer Perceptron (MLP) neural networks based on three configurations that are represented by the monsoon season (MS), non-monsoon season (NMS), and non-seasonal variation. For this purpose, first, the rainfall dataset was transformed by the wavelet transform method and then, a mathematical model was created to analyze and predict the transformed data in Seoul, South Korea. Missing rainfall data in three time periods from Seoul station were reconstructed using the transformed rainfall data of the other five stations (e.g., Guroguchung, Daegokgyo, Songjeongden, Dongmakgoljuchajang, and Wallgaegyo). The results showed that using the Coiflet wavelet transform with MLP model (named Coi_MLP) estimated missing data more accurately, which is obtained from the results of statistical criteria including root mean square error, mean absolute error, and correlation coefficient of 1.18, 0.49, and 0.99 for transformed MS data and 0.76, 0.18, and 0.99 for transformed NMS data, respectively. The Coi_MLP model can effectively perform rainfall data reconstruction and predict missing rainfall data accurately, especially when the length of the statistical period is limited to the MS and NMS with different volumes of rainfall.

The South China Sea (SCS) is the largest and southernmost sea in China. Water vapor from the SCS is the primary source of precipitation over coastal areas during the summer monsoon season and may cause the uneven distribution of rainfall in southern China. Deep insight into the spatial variability of raindrop size distribution (DSD) is essential for understanding precipitation microphysics, since DSD contains abundant information about rainfall microphysics processes. However, compared to the studies of DSDs over mainland China, very little is known about DSDs over Chinese ocean areas, especially over the South China Sea (SCS). This study investigated the statistical characteristics of the DSD in summer monsoon seasons using the second-generation Particle Size and Velocity (Parsivel2) installed on the scientific research vessel that measured the size and velocity of raindrops over the SCS. In this study, the characteristics of precipitation over the SCS for daytime and nighttime rains were analyzed for different precipitation systems and upon different rain rates. It was found that: (1) rain events were more frequent during the late evening to early morning; (2) more than 78.2% of the raindrops’ diameters were less than 2 mm, and the average value of mass-weighted mean diameter Dm (1.46 mm) of the SCS is similar to that over land in the southern China; (3) the stratiform precipitation features a relatively high concentration of medium to large-sized rain drops compared to other regions; (4) the DSD in the SCS agreed with a three-parameter gamma distribution for the small raindrop diameter. Furthermore, a possible factor for significant DSD variability in the ocean compared with the coast and large islands is also discussed.

Creating precise quantitative precipitation forecasts is essential for reducing losses and damages. This study aimed to identify the best microphysics and cumulus schemes for forecasting monsoon rainfall over the Kelani River basin, Sri Lanka, using the WRF-ARW model. Four extreme rainfall events from the 2020 and 2021 monsoon seasons were simulated with various microphysics and cumulus parameterizations to find the optimal combinations. These combinations were then tested for their ability to forecast two monsoon events with a 24-h lead time. Simulated and forecasted rainfalls were compared with observations from 15 gauging stations. Results indicate that WSM3 and WSM6 microphysics schemes with the Betts–Miller–Janjic (BMJ) cumulus scheme are optimal for simulating rainfall, with WSM3_BMJ being the most suitable for forecasting. The findings of this study provide valuable initial data for research in regions with similar environmental conditions, offering insights into the suitability of various physics schemes for simulating and forecasting monsoon rainfall, particularly under extreme conditions. Furthermore, given the prevalence of monsoons in many tropical and subtropical climates, these results will be instrumental in enhancing the use of numerical weather prediction models for forecasting monsoon rainfall on a global scale.

The present study investigates the spatiotemporal characteristics of rainfall events during the summer monsoon season over Odisha (one of the vulnerable zone for heavy rainfall) with the main aim for heavy-to-extreme rainfall events. India Meteorological Department (IMD) station observations and gridded rainfall analysis datasets for a period of 34 years (1980–2013) are used and four frequency indices (heavy-to-extreme, light-to-moderate, dry days, and wet spells) and four intensity indices (daily maximum rainfall, 5-day maximum rainfall, seasonal rainfall total, and daily intensity index) from both the datasets are evaluated. Furthermore, the above-stated indices are analysed over the four meteorological zones of Odisha, as classified by IMD.The analysis reveals that both the heavy-to-extreme rainfall days and dry days are increasing, while the light-to-moderate rainfall days and wet days are decreasing. It is also found that the rate of increase in rainfall amount and number of wet-day are higher in the southern than northern Odisha. This implies that the climate is becoming drier as one move from south to north and the gradient is also increasing with time. The climatological analysis suggests not only the heavy-to-extreme rainfall days and intensity are more in urban (Khordha) and highly elevated (Eastern Ghat; height ~ 1.6 km) areas but also the trend is increasing over those regions. The Murphy skill score of daily rainfall between two datasets is 0.94; however, the number of the extreme rainfall events is more in station data (297) than the gridded data (150) during the study period.

C-band radars were installed at Baramati and Shegaon as a part of operational cloud seeding program of Maharashtra State in the monsoon season (June–September) 2004. These provided first time a unique opportunity to study (1) characteristics of precipitating monsoon clouds (2) convection and (3) number of seedable clouds over Indian meteorological subdivisions of Madhya Maharashtra (rain-shadow) and Vidarbha (drought-hit). The monsoon season is divided into active and break periods. The cloud characteristics studied are: diurnal variation, cloud top heights and durations. Diurnal variation of cloud frequency shows maximum in the afternoon hours (10–11 UTC) and minimum in the early morning hours (3–4 UTC) in both the periods. Cloud tops show trimodal distributions with modes at 2–3, 8–9 and above 9 km. Mean cloud duration is 55 min. Congestus has been found prominent cloud type (65%) with mean top height of 6.76 km. Frequency of cumulonimbus clouds is found higher in the break periods. Cloud scale is taken as a metric for characterization of convection. Maximum frequency of cloud scale is found at C scale (mesoscale: area 100–1000 km2). Mesoscale Convective System has been found dominating convection type. The convection over the area has been shown to be hybrid type, consisting of basic oceanic type modulated by land convection. Convective clouds having maximum reflectivities between 25 and 35 dBZ, suitable for hygroscopic and glaciogenic seeding, are found in a large number. Understanding of characteristics of clouds and convection is useful for the diagnostic and precipitation enhancement studies over the rain-shadow/drought-hit regions.

In the management of water resources, quality of water is just as important as its quantity. In order to know the quality and/or suitability of groundwater for domestic and irrigation in upper Gunjanaeru River basin, 51 water samples in post-monsoon and 46 in pre-monsoon seasons were collected and analyzed for various parameters. Geological units are alluvium, shale and quartzite. Based on the analytical results, chemical indices like percent sodium, sodium adsorption ratio, residual sodium carbonate, permeability index (PI) and chloroalkaline indices were calculated. The pre-monsoon waters have low sodium hazard as compared to post-monsoon season. Residual sodium carbonate values revealed that one sample is not suitable in both the seasons for irrigation purposes due the occurrence of alkaline white patches and low permeability of the soil. PI values of both seasons revealed that the ground waters are generally suitable for irrigation. The positive values of Chloroalkaline indices in post-monsoon (80%) and in pre-monsoon (59%) water samples indicate absence of base-exchange reaction (chloroalkaline disequilibrium), and remaining samples of negative values of the ratios indicate base-exchange reaction (chloroalkaline equilibrium). Chadha rectangular diagram for geochemical classification and hydrochemical processes of groundwater for both seasons indicates that most of waters are Ca-Mg-HCO^sub 3^ type. Assessment of water samples from various methods indicated that majority of the water samples in both seasons are suitable for different purposes except at Yanadipalle (sample no. 8) that requires precautionary measures. The overall quality of groundwater in post-monsoon season in all chemical constituents is on the higher side due to dissolution of surface pollutants during the infiltration and percolation of rainwater and at few places due to agricultural and domestic activities.[PUBLICATION ABSTRACT]

The dynamic and thermal effects of the Tibetan Plateau (TP) on the precipitation in the Asian arid and monsoon regions were investigated using three numerical experiments—one using real topography, one with the whole TP removed, and one with sensible heat turned off over the TP. The results show that there are strong seasonal and regional differences in the dynamic and thermal effects of the TP on the precipitation in the Asian arid regions. The dynamic effect dominated the decrease in winter precipitation by blocking the westerly, while the thermal effect dominated the decrease in summer precipitation due to the TP-induced compensation downdraft in Central Asia and arid East Asia. The thermal effect dominated and accounted for 60% of the decrease in summer precipitation in West Asia. The results also show that both the dynamic and thermal effects of TP exhibit a more salient influence on the East Asian monsoon region than the South Asian monsoon region. The thermal effect dominated and accounted for 40% of the increase in summer precipitation due to intensification of the summer monsoon, while the dynamic effect dominated and accounted for 80% of the decrease in winter precipitation due to the northeast wind anomaly in the northern East Asian monsoon region. The anomalous wind can reach to the coast of South China and form frontal precipitation in the southern East Asian monsoon region in winter. The thermal effect dominated and accounted for 80% of the increase in precipitation in the pre-monsoon period due to intensification of the Asian summer monsoon.