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ABSTRACT Indian summer monsoon (ISM) is the prominent global monsoon system, which occur annually from June to September and impacts the lives of over a quarter of the world's population. Studies show that global warming is one of the key reasons for the extreme events such as droughts and floods, and that also alter regional dynamics of ISM. Consequently, a comprehensive investigation of flood and drought events in India is imperative, because of their important role in the economy of the country. Here, we employ simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) models to evaluate the intensity and frequency of droughts and floods across historical (1950–2014) and future (2015–2100) periods. We explore the best‐performing model for the ISM rainfall (ISMR) to unravel the characteristics of floods and droughts by analysing rainfall data from 53 models. Although majority of the models successfully replicate the annual cycle of ISMR, there exists a significant difference in rainfall amounts. Following an initial screening to identify the most efficient models, eight are selected for an in‐depth assessment. The chosen models slightly overestimate drought conditions, although they demonstrate a commendable concurrence in simulating the flood occurrences in India. Regarding the future projections, we analyse the Shared Socioeconomic Pathways (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5) for near (2015–2035)‐, mid (2047–2067)‐ and far (2079–2099)‐future periods, in addition to the total projection period (2015–2100). Our analysis reveals an increasing trend of droughts in the near‐future, compared to an increase in floods during the far‐future. It is also highlighted that the intensity of droughts is projected to amplify in the far‐future, while the intensity of floods is likely to diminish. Therefore, this study serves as a valuable resource for decision‐making processes, particularly in the flood, drought and agricultural disaster preparedness. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) is a prominent air pollutant in cities, with far-reaching implications for both local air quality and global atmospheric chemistry. The long-term change in atmospheric CO levels at a specific location is influenced by a complex interplay of local emissions, atmospheric transport, and photochemical processes, making it a subject of considerable interest. This study presents an 8-year analysis (2014–2021) of in situ CO observations using a cutting-edge laser-based analyzer at an urban site in Ahmedabad, western India. The long-term observations reveal a subtle trend in CO levels, masked by contrasting year-to-year variations, particular after 2018, across distinct diurnal time windows. Mid-afternoon (12:00–16:00 h) CO levels, reflecting background and regional conditions, remained relatively stable over the study period. In contrast, evening (18:00–21:00 h) CO levels, influenced by local emissions, exhibited substantial inter-annual variability without discernible trends from 2014 to 2018. However, post-2018, evening CO levels showed a consistent decline, predating COVID-19 lockdown measures. This decline coincided with the nationwide adoption of Bharat stage IV emission standards and other measures aimed at reducing vehicular emissions. The COVID-19 lockdown in 2020 further resulted in a noteworthy 29% reduction in evening CO levels compared to the pre-lockdown (2014–2019) period, highlighting the potential for substantial CO reduction through stringent vehicular emission controls. The observed long-term changes in CO levels do not align with the decreasing emission estimated by various inventories from 2014 to 2018, suggesting a need for improved emission statistics in Indian urban regions. This study underscores the importance of ongoing continuous CO measurements in urban areas to inform policy efforts aimed at controlling atmospheric pollutants. [ABSTRACT FROM AUTHOR]

The Middle East has major sources of anthropogenic carbon dioxide (CO2) emissions, but a dearth of ground-based measurements precludes an investigation of its regional and temporal variability. This is achieved in this work with satellite-derived estimates from the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 missions from September 2014 to February 2023. The annual maximum and minimum column (XCO2) concentrations are generally reached in spring and autumn, respectively, with a typical seasonal cycle amplitude of 3–8 ± 0.5 ppmv in the Arabian Peninsula rising to 8–10 ± 1 ppmv in the mid-latitudes. A comparison of the seasonal-mean XCO2 values with the CO2 emissions estimated using the divergence method stresses the role played by the sources and transport of CO2 in the spatial distribution of XCO2, with anthropogenic emissions prevailing in arid and semi-arid regions that lack persistent vegetation. In the 8-year period 2015–2022, the XCO2 concentration in the United Arab Emirates (UAE) increased at a rate of about 2.50 ± 0.04 ppmv/year, with the trend empirical orthogonal function technique revealing a hotspot over northeastern UAE and southern Iran in the summer where anthropogenic emissions peak and accumulate aided by low-level wind convergence. A comparison of the satellite-derived CO2 concentration with that used to drive climate change models for different emission scenarios in the 8-year period revealed that the concentrations used in the latter is overestimated, with maximum differences exceeding 10 ppmv by 2022. This excess in the amount of CO2 can lead to an over-prediction of the projected increase in temperature in the region, an aspect that needs to be investigated further. This work stresses the need for a ground-based observational network of greenhouse gas concentrations in the Middle East to better understand its spatial and temporal variability and for the evaluation of remote sensing observations as well as climate models.

ABSTRACT The occurrence of fog and low stratus (FLS) clouds is a common phenomenon over the Swiss plateau during the winter half years. Classical fog observations using horizontal visibility are of limited use for climatological analyses of persistent FLS situations. We present a simple method for determining long climatological series of days with FLS lasting at least a half or a full daylight day. The method relies solely on high quality relative sunshine duration measurements at two stations, a Plateau station below or within the FLS layer (e.g. Zürich/Fluntern) and a nearby peak station above the FLS layer (e.g. Säntis). The analysis for the period 1901-2012 shows that full day FLS are a typical phenomenon of the months November to January, whereas the half day FLS also often occur in October and February. There is substantial interannual and decadal variability. The total number of Zürich full FLS days varies between 4 and 31 d (mean: 17 d) and between 10 and 49 d (mean: 28 d) for at least a half FLS days in the September to March period. The foggiest decade in the 1901-2012 record was 1984-1993; the least foggy decade was 1999-2008 with roughly 40-45% less FLS occurrence than only 15 years before. In the most recent years a return towards the climatological mean can be observed. The long term data series does not show any significant long-term trends for the occurrence of full nor for half day FLS events. The reconstructed FLS occurrence is well correlated with the number of days with cold air pooling. They show very similar decadal variability and long term trends. © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]