This study presents an approach for modelling and mapping fluvial flooding, considering both land use/land cover (LULC) change and climate change, and applies it to the Brahmani River Basin in ...eastern India. Climate change projections were obtained from the Coupled Model Intercomparison Project Phase 6 (CMIP6), and their impacts on the hydrology of the catchment were investigated using HEC-HMS and HEC-RAS software. Results reveal that changes in LULC types, specifically an increase in proportions of agricultural and built-up areas and a decrease in forest cover, as undergone between years 1985 and 2018, have increased peak discharge following a storm, thereby causing an increase in spatial extent of floods of different return periods. Moreover, downscaled climate change scenarios from two General Circulation Models were used to determine potential changes in river discharge according to two GHG emission scenarios from the latest IPCC: SSP245 and SSP585. The projections indicate that peak discharge and the spatial extent of flooded areas will increase for floods with return periods ranging from two to 100 years. This study demonstrates the important influence that changes in LULC have had on the susceptibility of the BRB to flooding, with climate change projected to further enhance the risk of flooding as the century progresses.
Abstract
Observations of soil moisture (SM) during excess and deficit monsoon seasons between 2000 to 2021 present a unique opportunity to understand the soil water dynamics (SWD) over core monsoon ...zone (CMZ) of India. This study aims to analyse SWD by investigating the SM variability, SM memory (SMM), and the coupling between surface and subsurface SM levels. Particularly intriguing are instances of concurrent monsoonal extremes, which give rise to complex SWD patterns. Usually, it is noted that a depleted convective activity and persistence of higher temperatures during the pre-monsoon season leads to lower SM, while monsoon rains and post-monsoon showers support the prevalence of higher SM conditions. The long persistent dry spells during deficit monsoon years enhances the Bowen ratio (BR) due to the high sensible heat fluxes. On the other hand, the availability of large latent heat flux during excess monsoon and post-monsoon seasons tend to decrease the BR. This enhancement or reduction in BR is due to evapotranspiration (ET), which influences the SWD by modulating the surface—subsurface SM coupling. The surface and subsurface SM coupling analysis for CMZ exhibits significant distinction in the evolution of wet and dry extremes. SM variations and persistence time scale is used as an indicator of SMM, and analysed for both surface and subsurface SM observation levels. Evidently, subsurface SM exhibits remarkably prolonged memory timescales, approximately twice that of surface SM. Furthermore, we dissect SWD linked to wet and dry extremes by analysing annual soil water balance at a local site in Pune, India. Our findings reveal that ET and deep drainage on annual scale are modulated largely by number of break events during the monsoon season. In essence, our study underscores the significance of surface–subsurface SM observations in unravelling the intricate tapestry of SWD.
Abstract
Soil moisture (SM) plays a crucial role in altering climate extremes through complex land-atmosphere feedback processes. In the present study, we investigated the impact of SM perturbations ...on temperature extremes (ExT) over India for the historical period (1951–2010) and future climate projection (2051–2100) under 4 K warming scenario. We note that more than 70% area of the Indian landmass has experienced significant changes in characteristics of ExT due to SM perturbations. In particular, we see larger impact of SM perturbations on ExT over the north-central India (NCI), which is a hotspot of strong SM-temperature coupling. Over NCI, a 20% departure in SM significantly revamps frequency, duration and intensity of ExT by 2–5 events/year, 1-2 days/event and 0.5–2.1 °C, respectively, through modulating surface energy partitioning, evapotranspiration and SM memory. Importantly, the impact of SM perturbations on frequency and duration of ExT events becomes less prominent with intensification of global warming.
This study assesses the aerosol optical depth (AOD) from historical simulations (2003–2014) and future climate scenarios (2015–2100) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) over ...the Middle East and North Africa (MENA) region. Multi-model mean (MME) AOD statistics are generated as the average of those from the five best-performing CMIP6 models, which reproduce observational climate statistics. These models were selected based on the validation of various climate metrics, including strong pattern correlations with observations (>0.8). The resulting MME reproduces the observed AOD seasonal cycle well. The observed positive trends (summer and annual) over the Arabian Peninsula (AP) and negative trends (winter) over North Africa are well captured by MME, as regional meteorological drivers associated with observed AOD trends, with few discrepancies. Crucially, the MME fails to capture the AOD trends over North West Africa (NWA). For MENA and NWA regions, two high-emission scenarios, SSP370 and SSP585, project a continuous rise in the annual mean AOD until the end of the century. In contrast, the low-emission scenarios, SSP126 and SSP245, project a decreasing AOD trend. Interestingly, the projected future AOD area-averaged over the AP region varies significantly across all four scenarios in time. Notably, a substantial decrease of about 8–10% in the AOD is projected by the SSP126, SSP245, and SSP585 scenarios at the end of the century (2080–2100) relative to the current period. This projected decrease in annual-mean AOD, including the frequency of extreme AOD years under SSP585, is potentially associated with a concurrent increase in annual-mean rainfall over the AP.
We present analyses of nitrogen and oxygen isotopic ratios and site‐preference (SP) values of atmospheric nitrous oxide samples obtained from Taiwan in west Pacific. Air samples were collected during ...September 2013 to January 2016 from Taipei and during November 2011 to December 2014 from Keelung, located in the northeastern coast of Taiwan. The average values of δ15N, δ18O, and SP are 6.4 ± 0.3 ‰, 44.0 ± 0.4 ‰, and 17.1 ± 1.0 ‰, respectively, at Taipei and 6.4 ± 0.2 ‰, 44.6 ± 0.4 ‰, and 17.9 ± 1.3 ‰, for δ15N, δ18O, and SP respectively, at Keelung, comparable to the average values (6.6 ± 0.2, 44.2 ± 0.2, and 18.1 ± 0.5 ‰, scaled to year 2014) from Hateruma, an open ocean station in western Pacific. Strong temporal variations in the delta values, however, are seen. During a subtropical jet‐strengthening period in October to mid‐December 2014, the δ15N, δ18O and SP values increased at the rate of 0.006 ± 0.002 ‰/day, 0.010 ± 0.002 ‰/day and 0.008 ± 0.002 ‰/day, respectively at Taipei and 0.013 ± 0.005 ‰/day, 0.011 ± 0.005 ‰/day and 0.011 ± 0.027 ‰/day at Keelung. This suggests intrusion of air to the lower troposphere from the stratosphere where δ15N, δ18O and SP values are higher. This is consistent with earlier observations of oxygen isotope anomaly in atmospheric CO2 and elevated 35S in sulfate aerosols, indicating frequent stratospheric intrusions in this region. The observed δ15N and δ18O values, along with the oxygen isotope anomaly in CO2 and multiple sulfur isotopes in sulfate, can be used to constrain local emissions from the surface, improving our knowledge of anthropogenic contribution to the global budget of N2O.
Key Points
Temporal variations in isotopic ratios of atmospheric N2O from Taiwan
Isotopic ratio increase is concurrent with strengthening of the subtropical jet
Positive trends suggest intrusion of air from the stratosphere
This study examines the combined influence of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on Upper Troposphere Lower Stratosphere (UTLS) ozone variability. The investigation ...employs data from the Microwave Limb Sounder (MLS) aboard the Aura Satellite and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis, spanning the period 2005–2020 across tropical latitudes (20º N–20º S). Three specific events were chosen for analysis: a strong La Niña event in 2010, the co-occurrence of El Niño and moderate IOD in 2015, and a robust IOD event in 2019. During years marked by the simultaneous occurrence of ENSO and IOD events, the UTLS (100 hPa altitude is considered for the present study. 82 hPa is the altitude just above the tropopause, therefore also shown in the results) ozone mixing ratio demonstrates a decline in absolute values. The Quasi-biennial Oscillation (QBO) was also investigated, revealing a synchronized variation with the ozone anomaly in the UTLS region. Furthermore, the calculated eddy heat flux, utilized as a proxy for the Brewer–Dobson Circulation (BDC), aligns with the UTLS ozone anomalies, indicating a positive (negative) anomaly during periods of intense tropical downwelling (upwelling). To quantitatively elucidate the contributions of ENSO, IOD, and QBO to the observed ozone anomaly, a multivariate linear regression analysis was executed utilizing the least square method. The findings underscore that a notable fraction—about one-fourth of the observed UTLS ozone anomaly within the study timeframe (2005–2020) can be attributed collectively to ENSO, IOD, and QBO. This preliminary exploration underscores the substantial role played by large-scale climate drivers emanating from the Pacific and Indian oceans in shaping UTLS ozone distribution. These insights emphasize the significance of considering these climatic influences when examining the intricate dynamics and variability of UTLS ozone patterns.
Using the long-term (2005–2019) observations from the Microwave Limb Sounder (MLS) onboard Aqua satellite, the present study delineates the variability of the lower stratospheric ozone (LSO) in the ...Asian Summer Monsoon Anticyclone (ASMA) region. The climatological features of LSO indicate a peak minimum in the southern flank of ASMA noticed by the geopotential measurements from MLS. Further, the temporal variability of LSO indicates significant interannual variability during the 15 years of MLS observations. Our analysis found that two prominent source regions control the LSO variability at interannual time scales in the ASMA region, associated with the Pacific and Indian Ocean sea surface temperatures. More importantly, the extreme (positive/negative) values in ozone anomalies coincide with the El Niño–Southern Oscillation(El Niño/La Niña) events. Further, the composite analysis reveals a significant change in the mean magnitude of LSO of about 10 ppb between El Niño and La Niña phases. The results indicate that reduced water vapor transport due to subsidence and suppressed convection during the El Niño phase leads to less mixing across the upper troposphere and lower stratosphere, therefore, causing higher concentrations of ozone and vice-versa during the La Niña phase. Hence, this study indicates a strong implication for the climatic perturbations over the ASMA region.
•Exploring missing links between Asian Summer Monsoon Anticyclone Ozone and global sea surface temperatures.•Impact of El Niño–Southern Oscillation on the interannual variability of Ozone.•Investigation of physical mechanisms for ozone variability in different ENSO phases.
This study evaluates performance of a series of freely available gridded precipitation datasets that have been developed from the satellite (CHIRPS and TRMM TMPA), rain-gauged interpolation ...(APHRODITE and IMD-gridded), and Coupled Model Intercomparison Project Phase 6 (CMIP6)-General Circulation Models (GCMs) with the gauged observations (n = 49) for assessing their ability in capturing annual and seasonal rainfall characteristics over Central Godavari River basin in India. A rank matrix was developed for the purpose of comparing the performance of gridded datasets with that of gauged observations. This matrix was generated on the basis of the goodness-of-fit (GOF) statistics. The results reveal that APHRODITE dataset (r = 0.91–0.94; NSE = 0.68 to 0.87) has performed the best across all three zones, followed by the IMD-gridded (r = 0.93–0.95; NSE = 0.57 to 0.77) and CHIRPS datasets (r = 0.89–0.92; NSE = 0.38 to 0.60). However, TRMM TMPA dataset show the poorest accuracy with the gauged observation for all three zones. Additionally, projections from the CMIP6-GCMs reveal that the western part of the basin will receive more rainfall as compared to the eastern and central parts of the basin in future (2050s). This is opposite from prevailing rainfall variability pattern in the basin. The Zone 1 and Zone 2 of the basin are found to be comparatively more susceptible to the climate change under Shared Socio-Economic Pathway (SSP)245 and SSP585 scenarios than Zone 3. These results will aid in the future development of actionable agricultural water management plans for the basin, especially for rainfed agriculture, by assisting in the selection of the most effective gridded precipitation and CMIP6-GCM datasets.
•Zonal comparison of 5 gridded and 13 CMIP6-GCMs precipitation data with gauged data over a semi-arid region.•APHRODITE dataset demonstrated the best performance followed by the IMD-gridded datasets.•Zone 1 and Zone 2 are more susceptible to the climate change than Zone3 under projected climate change.•Zonal analysis of gridded datasets will help to devise plans for sustainable agriculture in CGRB.
Abstract The advent of weather and climate models has equipped us to forecast or project monsoon rainfall patterns over various spatiotemporal scales; however, utilizing a single model is not usually ...sufficient to yield accurate projection due to the inherent uncertainties associated with the individual models. An ensemble of models or model runs is often used for better projections as a multimodel ensemble (MME). This study analyzes the accuracy of MME in simulating the Indian summer monsoon rainfall (ISMR) variability using Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. The results highlighted that although the MME primarily reproduces the observed pattern and annual cycle of rainfall, significant biases are noted over homogeneous meteorological regions of India, except northeast India. To overcome this issue, an analysis of variance (ANOVA) and post hoc statistical tests are employed to identify a group of models for which the modified MME gives a better estimate of rainfall and reduces the bias significantly. Our findings underscore the potential of ANOVA and post hoc tests as a practical approach to enhancing the accuracy of multimodel ensemble rainfall for the assessment of model projections.
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