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The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E -OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia. • For Serbia negative trends in SPEI index, for different months and timescales, are dominant. • Occurrence of extreme drought categories has doubled over the last decades. • Transitions from neutral and wet categories to dry categories are more frequent. • These changes are driven by long-term warming and large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

The Mediterranean region is a unique area characterized by a large spectrum of atmospheric phenomena, some of which have a high impact on many aspects of human activities, safety and wellbeing. The area is long considered as a hot spot of such atmospheric phenomena deserving multidisciplinary scientific attention. The scientific research that has been carried out on these high impact atmospheric processes that occur in the Mediterranean area is indeed widespread and the available international literature is very extensive. The paper touches initially the temperature and precipitation regimes, followed by a discussion of floods and droughts. The exciting cyclogenetic patterns of explosive cyclones and medicanes are presented in separate sections. The lightning activity and the presence of dust and other pollutants are also presented herein. The atmospheric chemistry of the region which is increasingly becoming of utmost importance for the area under study is distinctly discussed. Attempts to modify the weather (the precipitation, in particular) are outlined too. The effects of climatic change on various atmospheric processes are considered throughout this paper, in addition to a dedicated section on temperature and precipitation. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Understanding climate extremes and indices is crucial for addressing climate change impacts, including the increased variability in local weather patterns and extreme events. Previous studies on the Arabian Peninsula (AP) have been limited by sparse station data and restricted spatial coverage. To overcome this limitation, this paper aims to assess the spatial distribution and temporal trends of temperature and precipitation indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) using ERA5 reanalysis data from 1951 to 2020 for the AP. Additionally, this study investigated the changes relative to the reference period (1951–1980). The modified Mann-Kendall test and Sen's Slope estimator are utilized to detect significant trends and estimate their magnitude. Results revealed that ERA5 was consistent with previous studies that utilized in-situ station data, which offers a more detailed picture of the affected areas. The findings indicated a significant warming trend in temperature indices, with an increase of over 1 °C per decade observed across several areas, including the northern AP, and certain regions experiencing a discrepant change of 3 °C increase compared to the reference period. Changes in rainfall indices indicate a shift in rainfall patterns from the AP's fertile southwest regions towards more intense patterns in specific eastern regions, including Oman, Kuwait, Saudi Arabia, and Yemen. However, the precipitation temporal trends are weak in magnitude and variable spatially, with dominant decreases in both intensity (-10 mm per decade) and frequency indices (-5 days per decade). Some locations are subject to the combined effects of most heatwave indicators simultaneously, while flood indicators and yet others by drought indicators influence others. All these locations have been accurately identified in this study. The findings provide valuable information regarding the region's climate change vulnerability and adaptation needs. [Display omitted] • Prior studies relied on limited station data, short period, and MK trend test. • Extremes are assessed using ERA5, ETCCDI, Modified-MK, and Sen's Slope. • Affected areas are identified, and valuable insights for policymakers are set. • Significant warming trend: >1 °C/decade and > 2 °C change from reference period. • Spatiotemporal trends of precipitation are weak in magnitude and variable spatially. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

Climate classifications based on temperature and precipitation measurements are increasingly being used for environmental and climate change studies. Using three classification methods (Köppen, Extended Köppen, and Holdridge) and one observational dataset for present climate (CRU, Climate Research Unit), we show that GCMs have bridged the gap that led to the emergence of RCMs thirty years ago, as GCMs can now provide global climate classifications whose accuracy and precision are comparable to those of regional outputs of the RCMs. Projections of high-resolution GCMs for future climates under the assumptions of three Representative Concentration Pathways (RCP26, RCP45 and RCP85) can therefore be used as a primary source for climate change and global warming studies at high resolution. This paper provides comprehensive, model-derived climate classifications for the entire planet, using RCMs and two GCMs for present and future climate-change scenarios, and discusses how well the models actually represent the climates of the world when compared with reference, ground validation data. It turns out that both GCMs and RCMs appear still limited to provide practical estimates of the world climates even for present climate conditions. The modeling of precipitation remains the Achilles' heel of models and thus of multidimensional indices, which are very sensitive to this variable. The conclusion is that model outputs at regional scale need to be taken with extreme caution without venturing into informing policies presenting potentially large societal impacts. Nonetheless, the role of models as privileged tools to advance our scientific knowledge of the Earth's system remains undisputed. • A systematic analysis of climate classifications with RCMs and two high resolution GCMs is presented. • Three classification methods are used to illustrate the differences between models and observations. • Current high-resolution GCMs can provide climate classifications with the same accuracy as those from RCMs. • Uncertainties in modeling precipitation persist for large parts of the world. [ABSTRACT FROM AUTHOR]

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation with a proper representation of standard observations and key physical processes for a wide range of applications. In this regard, RAMS is assessed against in-situ surface observations during a selected period within July 2011 over Eastern Spain. In addition, the simulation results are also compared with different surface remote sensing data derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI) as well as the uncoupled Land Surface Models (LSM) Global Land Data Assimilation System (GLDAS). Both datasets complement the available in-situ observations and are used in the current study as the reference or ground truth when no observations are available on a selected location. Several sensitivity tests have been performed involving the initial soil moisture content, by adjusting this parameter in the vertical soil profile ranging from the most superficial soil layers to those located deeper underground. A refined adjustment of this parameter in the initialization of the model has shown to better represent the observed surface energy fluxes. The results obtained also show an improvement in the model forecasts found in previous studies in relation to standard observations, such as the air temperature and the moisture fields. Therefore, the application of a drier or wetter soil in distinct soil layers within the whole vertical soil profile has been found to be crucial in order to produce a better agreement between the simulation and the observations, thus reiterating the determining role of the initial soil moisture field in mesoscale modelling, but in this case considering the variation of this parameter vertically. [ABSTRACT FROM AUTHOR]

Recent studies found a long-term drought and resulting declines in vegetation greenness and canopy water content over the Congo Basin, the second largest rainforest in the world after the Amazon. Since most precipitation in tropical latitudes stems from convection, this paper analyzed 35 years of high-resolution (8 km spatial resolution and 3 h temporal resolution) satellite data to document the long-term trends in the number, size and intensity of thunderstorms activity over the Congo Basin during April, May, and June (AMJ) for the period 1982–2016. Changes in the magnitude and area of cold cloud top brightness temperatures ( T b ) at different thresholds were used as a proxy to quantify the number and size of individual thunderstorms at different intensities. We found that the areal extent and intensity of thunderstorms increased over the past 35 years, particularly over Northern Congo Basin, and these changes are consistent with other satellite datasets. Combined with a reanalysis dataset, our work suggests that thunderstorms over the Congo Basin are becoming taller and wider, and likely resulting in a moister (drier) upper (lower) troposphere. [ABSTRACT FROM AUTHOR]

With population growth and climate change increasing the exposure of communities and assets to extreme hydrological events, such as floods and droughts, it is crucial to make accurate and timely early warning, climate adaptation and water management information available that can help minimize the loss of the limited quantities of water in arid regions. Trend estimation using wavelets has continued to attract ubiquitous applications in various fields including atmospheric and water studies. While Fourier analysis employs big waves, wavelet analysis uses small waves. Since wavelets localise features in a signal data to different scales, we can therefore preserve vital signal features while removing noise in the signal. Hence the basic notion of wavelet denoising or wavelet thresholding is that the wavelet transform results in a sparse representation for many real-world signals, meaning that the wavelet transform concentrates signal features in a few large-magnitude wavelet coefficients. Since small wavelet coefficients are typically noise, we can “shrink” or remove them without affecting the signal quality. This paper employs wavelet analyses of some selected meteorological factors of the Namibian atmosphere to investigate the noise in the data collected from a number of Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) stations, for the years 2012 to 2015. The results show some significant levels of noise around the thresholds of various optimal time series peaks of the data. Hence the denoised data serve to represent fairly refined representations of data for the given period. Moreover, the results of comparing the optimal game model solutions for the original and denoised data specifically identified some weather stations that are “humidity noise stable” and “temperature noise stable”. Thus, these suggest that despite the noise in the respective meteorological data for these stations, the effects of the noise in the data appear to be manageable or optimally controllable, within the given period. [ABSTRACT FROM AUTHOR]

Concern about climate change has amplified the need for accurate information about variations in statistical characteristics of extreme rainfall events in both smaller temporal and spatial scale. For this reason, in this paper the hourly precipitation measurements obtained at the Department of Meteorology and Climatology of the Aristotle University of Thessaloniki meteorological station, during the period 1947–2003, are used. A new threshold determining method is proposed, in order to define the extreme rainfall event in Thessaloniki, based upon the polynomial trends of the cumulative distribution functions, retrieved from hourly precipitation measurements. Through this approach, three statistical goodness-of-fit tests were carried out, in order to come up with the best fitting probability distributions, for annual and seasonal extreme precipitation conditions. Based upon this fitting distribution procedure, return periods for different precipitation extreme values were calculated. Results indicate that the value of 6.5 mm/h is the hourly threshold of extreme precipitation in Thessaloniki over the studied period. Furthermore, the Generalized Pareto, and the Johnson SB, the log-Gamma and the Lognormal are the best fitted probability models for the description of annual and seasonal extreme rainfall events, respectively. Last but not least, the contribution of hourly data in the accuracy of the results is discussed. [ABSTRACT FROM AUTHOR]

Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5 °C to 2.0 °C. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]

Understanding future climate change is crucial for securing and managing water supplies necessary for agricultural activities in China, particularly in rainfed agriculture regions. This paper evaluates the projected climate change for nine major agricultural zones in China, using ensembles of regional climate models (RCMs) simulated under the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II) framework. The simulations were conducted for two climate scenarios (RCP2.6 and RCP8.5) at a 25 km grid spacing, with three RCMs (RegCM4, REMO, and WRF) driven by multiple CMIP5 global climate models (GCMs). The study compares the RCM simulations to the driving CMIP5 and the recent CMIP6 ensembles, focusing on surface temperature, precipitation, and surface relative humidity for the present day (1981–2010), mid-future (2036–2065), and far future (2070–2099) periods. The model evaluations indicate that the GCM and RCM simulations are consistent with observations, with RCMs showing better performance than the driving GCMs. The results show that both GCMs and RCMs project increased temperature and precipitation in most agricultural zones of China in the future, with the CMIP6 ensembles projecting the largest temperature increase and the CORDEX-EA-II ensemble showing the finest spatial details. Relative humidity is projected to decrease over major rice-producing areas of South China in the CORDEX-EA-II, CMIP5, and CMIP6 ensembles. This study provides valuable information to support climate change adaptation and mitigation efforts in China, particularly in the agricultural sectors. • CORDEX-EA-II simulations demonstrate better model performance over China. • Temperature and precipitation are projected to increase in the future. • Relative humidity is projected to decrease over South China. [ABSTRACT FROM AUTHOR]

On 5 September 2015 a violent hailstorm hit the Gulf and the city of Naples in Italy. The storm originated over the Tyrrhenian Sea dropping 7–10 cm diameter hailstones along its path. During its mature phase, at 08:47 UTC, the hailstorm was captured by one overpass of the Global Precipitation Measurement mission Core Observatory (GPM-CO) embarking the GPM Microwave Imager (GMI) and the Ka/Ku-band Dual-frequency Precipitation Radar (DPR). In this paper, observations by both GMI and DPR are thoroughly analyzed in conjunction with other spaceborne and ground-based measurements, to show how the GPM-CO integrates established observational tools in monitoring, understanding, and characterizing severe weather. Rapid-scan MSG SEVIRI images show an extremely rapid development, with 10.8 μm cloud-top temperatures dropping by 65 K in 40 min down to 198 K. The LIghtning NETwork registered over 37,000 strokes in 5 h, with intracloud positive stroke fraction increasing during the regeneration phases, when ground-based polarimetric radar and DPR support the presence of large graupel/hail particles. DPR Ku 40 dBZ and 20 dBZ echo top heights at 14 km and 16 km, respectively, indicate strong updraft and deep overshooting. GMI extremely low brightness temperatures (TBs) in correspondence of the convective core (158, 97, 67, and 87 K at 18.7, 36.5, 89 and 166 GHz) are compatible with the presence of massive ice particles. In two years of GPM global observations the storm ranks as fourth and first in terms of minimum 36.5 and 18.7 GHz (V-pol) TBs, respectively. This study illustrates GPM-CO sensing capabilities for characterizing the structure of such severe hailstorm, while providing observational evidence of its intensity and rarity, both globally and over the Mediterranean area. [ABSTRACT FROM AUTHOR]

This paper provides an account of observed variations in Black carbon (BC) aerosol concentrations and their induced radiative forcing for the first time over Granada a measurement site in Southeastern Iberian Peninsula. Column-integrated BC concentrations were retrieved for the period 2005–2012. Monthly averages of BC concentrations (± one standard deviation) ranged from higher values in January and December with 4.0 ± 2.5 and 4 ± 3 mg/m 2 , respectively, to lower values in July and August with 1.6 ± 1.2 and 2.0 ± 0.5 mg/m 2 , respectively. This reduction is not only observed in the average values, but also in the median, third and first quartiles. The average BC concentration in winter (3.8 ± 0.6 mg/m 2 ) was substantially higher than in summer (1.9 ± 0.3 mg/m 2 ), being the eight-year average of 2.9 ± 0.9 mg/m 2 . The reduction in the use of fossil fuels during the economic crisis contributed significantly to reduced atmospheric loadings of BC. According to our analysis this situation persisted until 2010. BC concentration values were analyzed in terms of air mass influence using cluster analysis. BC concentrations for cluster 1 (local and regional areas) showed high correlations with air masses frequency in winter and autumn. In these seasons BC sources were related to the intense road traffic and increased BC emissions from domestic heating. High BC concentrations were found in autumn just when air mass frequencies for cluster 3 (Mediterranean region) were more elevated, suggesting that air masses coming from that area transport biomass burning particles towards Granada. BC aerosol optical properties were retrieved from BC fraction using aerosol AERONET size volume distribution and Mie theory. A radiative transfer model (SBDART) was used to estimate the aerosol radiative forcing separately for composite aerosol (total aerosols) and exclusively for BC aerosols. The mean radiative forcing for composite aerosol was + 23 ± 6 W/m 2 (heating rate of + 0.21 ± 0.06 K/day) and + 15 ± 6 W/m 2 for BC aerosol (heating rate of + 0.15 ± 0.06 K/day). These values of radiative forcing and heating rate for BC aerosol represent about 70% of their values for composite aerosol, which highlights the crucial role that BC aerosols play in modifying the radiation budget and climate. [ABSTRACT FROM AUTHOR]

A great dust storm occurred in Tehran on 2 June 2014 and caused severe damage to properties and involved loss of human life. From the visual evidence available, it can be regarded as a case of haboob. As a lower latitude phenomenon, its occurrence in Tehran was unprecedented in the last 50 years. This paper aims to present a detailed analysis of the weather conditions, the pathways by which dust particles were ingested by the haboob, as well as the impact of the urban boundary layer on the intensity and propagation of the dust storm. Using numerical simulation carried out by the WRF-Chem model and various observational techniques, the coupling of a low-level small-scale deformation field with a lower-tropospheric cold pool produced by precipitating mid-tropospheric clouds is identified as the main process involved in shaping this rare dust storm. [ABSTRACT FROM AUTHOR]

The Madden-Julian Oscillation (MJO) is the dominant mode of sub-seasonal climate variability in the global tropics. As such it represents an opportunity for intra-seasonal rainfall prediction and, perhaps, for explaining dynamics that underlie longer term variability and trends. This opportunity is of substantial interest for tropical Africa, where rainfall variability has significant impacts on agriculture, energy, and natural ecosystems. The objective of this review paper is to inventory and assess the state of knowledge of MJO influence on African rainfall. A number of studies have identified statistical links between MJO and sub-seasonal rainfall variability in West, East, and Southern Africa. The proposed mechanisms to explain this influence differ by region and by season, and they often involve multiscale interactions between local precipitation processes and MJO-associated atmospheric dynamics. Dynamically-based forecast systems have some skill in predicting MJO evolution to time horizons of 3–4 weeks, and some can capture teleconnections to Africa. On longer time scales, there is evidence that MJO activity both modulates and is modulated by the El Niño Southern Oscillation and the Indian Ocean Dipole. The implications of these interactions for MJO connections to Africa require further research, as does the potential for trends in MJO behavior and impacts on Africa under global climate change. [ABSTRACT FROM AUTHOR]

In this paper, the HYSPLIT model, driven with reanalysis meteorological data from 1978 to 2013, was used to understand the potential transport characteristics of dust and salt dust emanating from the playa of Ebinur Lake in arid northwest China. Daily air parcel trajectories were computed forward for 8 days from an origin centered over Ebinur Lake at 100 m above ground level. Air parcel trajectory density plots were mapped for seven levels: 0–100 m agl., 100–500 m agl., 500–1000 m agl., 1000–1500 m agl., 1500–2000 m agl., 2000–3000 m agl., and 3000–5000 m agl. These show that potential dust transport pathways have clear seasonal differentiation. The potential transport distance of dust and salt dust is greatest in spring and summer. In autumn and winter, the potential transport of the high-density air trajectory is below 1000 m traveling a shorter distance. Potential dust transport pathways showed notifying directivity in different seasons and heights. Southeast in spring and summer, and north to northeast in autumn and winter are the two main potential transport channels of dust and salt dust. Accordingly, dust and salt dust from the playa of Ebinur Lake may influence the atmospheric processes and biogeochemical cycles of a vast region. The main area of influence of dust and salt dust is close to the source area, and will significantly accelerate the melting of snow and ice in the Tianshan Mountains. This highlights the urgent need to combine remote sensing, isotope and other methods to further research the transport characteristics of dust and salt dust from the playa of the Ebinur Lake. [ABSTRACT FROM AUTHOR]

Thunderstorms, which usually occur when there are cumulonimbus (Cb) clouds in the sky, can be a natural hazard if they are severe. Most previous studies have focused on the physical and dynamic structure of thunderstorms, with little focus on exploring the trends of thunderstorm occurrence. In this paper, the time series of days with thunderstorms were studied at 30 synoptic stations in Iran during the past five decades (1961 to 2010). The non-parametric Mann–Kendall statistical method was the main approach employed since it is very useful in hydro-meteorological studies. The results of this study showed that the trend of days with thunderstorms in Iran was positive in most parts of the country for all months of the year. The largest area with positive and significant trends occurred in April and May, especially in the northwestern and northern parts of Iran. Based on the annual time series, more than 90% of the country's area had positive (significant or non-significant) trends. In addition, no significant negative trends were observed in days with thunderstorms for any months of the year in the study region. This research supports the hypothesis that climate change can have significant effects on extreme atmospheric phenomena. Additional research is necessary to explore the climatic and physical causes of the trends presented in this study. [ABSTRACT FROM AUTHOR]

Recent climate change is characterized (among other things) by changes in the frequency of some meteorological phenomena. This paper deals with the long-term changes in various precipitation types, and the connection between their variability and cloud type frequencies, at 11 meteorological stations from Eastern Romania over 1961–2008. These stations were selected with respect to data record completeness for all considered variables (weather phenomena and cloud type). The meteorological variables involved in the present study are: monthly number of days with rain, snowfall, snow showers, rain and snow (sleet), sleet showers and monthly frequency of the Cumulonimbus, Nimbostratus and Stratus clouds. Our results show that all stations present statistically significant decreasing trends in the number of days with rain in the warm period of the year. Changes in the frequency of days for each precipitation type show statistically significant decreasing trends for non-convective (stratiform) precipitation – rain, drizzle, sleet and snowfall –, while the frequencies of rain shower and snow shower (convective precipitation) are increasing. Cloud types show decreasing trends for Nimbostratus and Stratus, and increasing trends for Cumulonimbus. [ABSTRACT FROM AUTHOR]

The assessment of future precipitation variations prevailing in an area is essential for the research regarding climate and climate change. The current paper focuses on 3 selected areas in Greece that present different climatic characteristics due to their location and aims to assess and compare the future variation of annual and seasonal precipitation. Future precipitation data from the ENSEMBLES anthropogenic climate-change (ACC) global simulations and the Climate version of the Local Model (CLM) were obtained and analyzed. The climate simulations were performed for the future periods 2021–2050 and 2071–2100 under the A1B and B1 scenarios. Mann–Kendall test was applied to investigate possible trends. Spatial distribution of precipitation was performed using a combination of dynamic and statistical downscaling techniques and Kriging method within ArcGIS 10.2.1. The results indicated that for both scenarios, reference periods and study areas, precipitation is expected to be critically decreased. Additionally, Mann–Kendall test application showed a strong downward trend for every study area. Furthermore, the decrease in precipitation for the Ardas River basin characterized by the continental climate will be tempered, while in the Sperchios River basin it will be smoother due to the influence of some minor climatic variations in the basins' springs in the highlands where milder conditions occur. Precipitation decrease in the Geropotamos River basin which is characterized by Mediterranean climate will be more vigorous. B1 scenario appeared more optimistic for the Ardas and Sperchios River basins, while in the Geropotamos River basin, both applied scenarios brought similar results, in terms of future precipitation response. [ABSTRACT FROM AUTHOR]

The chemical composition and size distribution characteristics of atmospheric aerosols have important effects on the environment, human health and climate change. In this paper, we study the size distribution of carbonaceous aerosols at the remote and pristine site, Nam Co Monitoring and Research Station for Multisphere Interactions, in the inland Tibetan Plateau (TP) based on collected size-segregated aerosols during 2012. The samples were quantified using the thermal/optical (TOR) method. The overall average concentrations of OC and EC in TSP, PM 9.0 , PM 2.1 , and PM 1.0 were 4.61 μg m − 3 and 0.19 μg m − 3 , 4.52 μg m − 3 and 0.18 μg m − 3 , 2.72 μg m − 3 and 0.11 μg m − 3 , and 2.11 μg m − 3 and 0.09 μg m − 3 , respectively. Generally, the highest concentration of OC and EC in different aerosol size occurred during winter. The low level of EC indicated that direct anthropogenic disturbances in the interior of the TP still remain insignificant. The size distributions of OC and EC concentrations presented bimodal variations. In winter, pre-monsoon, monsoon, and post-monsoon seasons, the peaks for OC were in droplet mode (0.43–0.65 μm) and coarse mode (4.7–5.8 μm); while in the monsoon period, the coarse mode shifted to a smaller size bin (3.3–4.7 μm). The coarse mode may be due to dust particles while the droplet mode may be due to the growth process of particles. For EC, the peaks variations in coarse mode were as same as OC, while the other peaks were complicated: the peaks during winter, pre-monsoon, and monsoon seasons exhibited in droplet mode (1.1–2.1 μm, 0.65–1.1 μm, and 0.43–0.65 μm, respectively), and in post-monsoon period, the peak located in condensation mode. The highest peak concentrations for OC and EC occurred in winter and the pre-monsoon period, while the lowest peak values in the monsoon and post-monsoon periods, respectively. The size distribution variations may be caused by deposition, gas/particles exchange, hygroscopic growth, external mixing, and secondary organic carbon formation. OC/EC ratios in aerosols over the TP mostly exhibit high values, which emphasizes the importance of OC over this region. [ABSTRACT FROM AUTHOR]

An accurate cloud top retrieval from geostationary (GEO) and low earth orbit (LEO) platforms is still a pending problem. This particularly holds for low level clouds. Furthermore, cloud top height is a crucial parameter to calculate cloud immersion of underlying terrain from GEO/LEO data and thus, for the discrimination between low level stratus and ground fog, where the latter is a main obstruction for air, land and sea traffic. All problems are particularly evident for ocean areas such as the Yellow Sea where no ground observations are available. In this paper, a novel method is presented to retrieve low stratus/fog top heights with special reference to the Yellow Sea and its surroundings, based on GEO data of MTSAT-1 and MTSAT-2 (JAMI sensor) and LEO data (MODIS sensor on Terra and Aqua) using the infrared (IR) water vapor and split-window bands. Two cases with very good data coverage are discussed where the retrieved low stratus/fog heights are compared to CALIPSO cloud top heights, and simulated data using the mesoscale model WRF. The comparison of JAMI retrievals with the spatial data sources used shows an encouraging accuracy (root-mean-square error, RMSE, around 300 m) in comparison to other retrieval schemes base on IR data hitherto published. A validation of the retrievals for the position of two radiosonde stations using available sounding data of seven foggy days revealed an even better performance with an average deviation of 184 m (standard deviation of 132 m). However, the validation revealed that the application of the underlying equations to retrieve inversion strength and thickness under foggy conditions would need some adjustments because the equations taken from the work of Liu and Key (2003) were originally developed for clear sky situations. Thus, the adaptation of the original scheme during future work should especially address cloudy conditions under moderate inversion strengths which could lead to an improvement of the retrieval accuracy. [ABSTRACT FROM AUTHOR]

The present paper shows an in-depth analysis of the evolution of floods and precipitation in Catalonia for the period 1981–2010. In order to have homogeneous information, and having in mind that not gauge data was available for all the events, neither for all the rivers and stream flows, daily press from a specific newspaper has been systematically analysed for this period. Furthermore a comparison with a longer period starting in 1900 has been done. 219 flood events (mainly flash flood events) have been identified for the period of 30 years (375 starting in 1900), 79 of them were ordinary, 117 of them were extraordinary and 23 of them were catastrophic, being autumn and summer the seasons with the maxima values. 19% of the events caused a total of 110 casualties. 60% of them died when they tried to cross the street or the stream. Factors like the evolution of precipitation, population density and other socio-economical aspects have been considered. The trend analysis shows an increase of 1 flood/decade that probably has been mainly due to inter-annual and intra-annual changes in population density and in land-use and land-cover. [ABSTRACT FROM AUTHOR]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Mesoscale Convective Systems (MCSs) over the southern Arabian Peninsula are more common during the spring months of March and April. In this paper, the processes behind such severe convective events and their local-scale impacts are investigated using reanalysis data, satellite-derived and observational products. The analysis of 95 MCS events from 2000 to 2020 revealed that they are triggered by low-level wind convergence and moisture advection from the Arabian Sea, Arabian Gulf and/or Red Sea. An equatorward displacement and strengthening of the subtropical jet also precondition the environment, as does the presence of a mid-level trough. The latter is generally part of a large-scale pattern of anomalies that are equivalent barotropic in nature, and therefore likely a response to tropical or subtropical forcing. At more local-scale, a drying of the mid-troposphere between 850 and 250 hPa typically by 50%, a reduction of the upper-level winds by about 5 m s−1, and an increase in the upper-tropospheric temperature on average by 2–3 K, are typically observed during MCS events. Over the 21-year period, a statistically significant increase in the MCSs' duration over southeast Arabian Peninsula has been found, suggesting that such extreme events may be even more impactful in a warming world. • MCSs over the southern Arabian Peninsula occur more frequently in March and April months. • Preconditioning and triggering processes for MCSs over this region are investigated. • Over the 20-year period, MCSs have been lasting longer over the UAE. [ABSTRACT FROM AUTHOR]

This paper aims to analyse the distribution and temporal evolution of convective precipitation in the Mediterranean region of Spain. To accomplish this goal, we used 148 sets of 5-min rainfall rate data from the 1989–2015 period. The selected regions were the Júcar Hydrographic Confederation (CHJ) and the Internal Basins of Catalonia (CIC), which cover most of the autonomous communities of Catalonia and the Valencian Community (east Spain). The average 5-min intensity threshold of 35 mm/h and the β parameter, defined as the ratio between convective precipitation versus total precipitation in any period, were used to characterise convective precipitation. Convective episodes were categorised as "very convective", "moderately convective", and "slightly convective" based on the β value. After quality control, the series of 129 stations were clustered into homogeneous precipitation zones that also include β as one of the variables of characterisation. The results show that convective precipitation can contribute to total annual precipitation by up to 16% on average, but it is generated by a very small percentage of convective events (between 3% and 6% across all the stations) in comparison with the total number of rainfall episodes. In this sense, moderately convective events are the most common, with a predominantly unimodal monthly distribution of β, with summer the most convective season. Trends show a significant increase in precipitation, convective precipitation, and convective episodes in the CHJ. On the other hand, a positive trend of convective events is predominant in the CIC region, despite an overall precipitation decrease in the analysed period. These results are relevant given that extreme daily rainfall does not show a positive or significant trend, and they are in line with the impact of climate change on increased atmospheric instability and water vapour in the atmosphere. They highlight the need to work with sub-daily precipitation series in the case of the Mediterranean, which is mainly affected by flash floods. • The contribution of convective precipitation in the East of Spain exceeds 10% annually and can reach 100% in late summer. • Convective precipitation is caused by less than 5% of annual rain episodes that are associated to heavy rains. • Orography (height, orientation, and distance to the sea) plays the major role in triggering convective precipitation. • There is a predominant increase of convective precipitation resulting from a strengthening of thermodynamic conditions. • SST has increased 0,3ºC more than air temperature in the Mediterranean region that results in increasing potential instability. [ABSTRACT FROM AUTHOR]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]

The selection of global climate models (GCMs) for a region remained a difficult step in climate change studies. A state-of-the-art Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm is proposed in this paper for GCM selection. The ranking of GCMs obtained using SVM-RFE was compared to that obtained using entropy-based similarity assessment index known as Symmetrical Uncertainty (SU). The study was conducted in the sub-Himalayan region of Pakistan where a reliable projection of climate is highly significant for water resources management in the entire western part of South Asia. The RF-based regression model was employed to generate a multi-model ensemble (MME) mean of the top-ranked GCMs. The MME mean projection was utilized to estimate the spatiotemporal changes in annual precipitation in comparison with precipitation of 1961‐–2000 for various representative concentration pathway (RCP) scenarios. The SVM-RF selected five GCMs (MIROC5, EC-EARTH, CNRM-CM5, BCC-CSM1.1(m) and BCC-CSM1.1) as most suitable for climate change projections in the study area. Obtained results were found to collaborate well with the results of multiple conventional statistical metrics. The MME mean projections revealed precipitation alteration between −1% and 18% during 2020‐–2059, and 0 and 24% during 2060–2099 for different RCPs. Precipitation was projected to increase up to 20% in the north whereas a decrease up-to −16% in the south. • SVM-RFE algorithm is used for selection of GCMs for Upper Indus Basin (IUB). • Performance of SVM-RF was compared with symmetrical uncertainty (SU) and conventional statistics based methods. • SVM-RFE was found to select the same GCMs as selected by SU and conventional statistics. • Precipitation projections in IUB revealed high heterogeneity in future changes in precipitation. [ABSTRACT FROM AUTHOR]

Climate change effects can have significant impacts worldwide. Extreme events can modify water availability and agricultural production, making climate change planning an essential task. The National Institute for Space Research (INPE in Portuguese) in Brazil has made a large dataset of regional climate model outputs (simulations and projections) available, which opens up many possibilities of carrying out high-resolution climate change studies. However, there is still no performance evaluation of the model-derived rainfall output against high-resolution ground-based observation data considering the Brazilian biomes. This paper attempts to fill this gap and evaluates the simulated precipitation throughout Brazil. We used gridded observed precipitation data and historical climate simulations from the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) and from the Hadley Center Global Environment Model, version 2 (HadGEM2-ES), which were downscaled by the Eta RCM (Regional Climate Model). For the overlapping period (1980–2005), there is good agreement (PBIAS up to 10%) of downscaled annual simulations for the Amazon and Cerrado biomes and large biases (reaching 40%) in the Pampa biome, compared to the observations. Our results showed that HadGEM2-ES is capable of representing long-term mean monthly precipitation for large areas well, such as the Amazon and Cerrado. Furthermore, the Eta RCM has considerably improved the driving GCM MIROC5 simulations. In conclusion, we recommend using the HadGEM2-ES simulations for the Amazon, Eta/HadGEM2-ES for the Atlantic Forest, Cerrado, and Pampa, and Eta/MIROC5 for the Caatinga and Pantanal. Our study provides an overview of two downscaled simulation datasets in Brazil that may help verify the models' suitability for further climate change assessments. • We evaluated the so far most detailed precipitation projections for Brazil. • We compared the Eta RCM and driving GCMs against high-resolution observed dataset. • HadGEM2-ES GCM can represent the precipitation for large areas, such as the Amazon. • Eta RCM considerably improved the MIROC5 GCM precipitation simulations in all biomes. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades. • Significant decreases will occur in the intensity and amount of heavy precipitation for upcoming decades. • Change rates of precipitation indices combinations illustrate obvious spatial heterogeneity. • The frequency of simultaneous floods and droughts in a year and that of extreme heavy precipitation events will augment. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to demonstrate the magnitude in which validation results of space-based total ozone column, TOC, measurements are affected by the location of the polar vortex. Potential Vorticity is used as an indicator to determine the polar vortex's boundary and surface area, provided by ERA-Interim reanalysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). The total ozone measurements that were examined fall within the hemispherical winter-spring period, focusing on middle and high latitudes on both hemispheres. The space-based total ozone data produced by the GODFIT (GOME-type Direct FITting) v4 algorithm as applied to the OMI/Aura, GOME-2/Metop-A and Metop-B observations, part of the European Space Agency's Ozone Climate Change Initiative project, are compared to TOC measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) repository. The satellite-to-ground collocations were classified depending on whether both satellite and ground-based measurements are inside or outside the polar vortex (matched) or one measurement is inside whereas the other one is outside the polar vortex (mismatched). It is shown that the matched cases present an improved agreement between satellite and ground TOC measurements compared to the mismatched cases. Considering all examined stations for GOME2-A, GOME2-B, and OMI, the mean bias for the mismatched cases was found to be 2.22 ± 0.4%, 1.84 ± 0.57%, and 1.93 ± 0.39% respectively, while for the matched cases was found to be 1.46 ± 0.17%, 1.69 ± 0.22%, 1.7 ± 0.19% respectively. For the three satellite sensors, the mismatched cases do not exceed 3.3% of the total available collocations per station during the winter-spring period between years 2007 and 2017, where applicable. Hence, on a global scale, the exclusion of mismatched collocated measurements does not cause significant changes and the resulting impact on the validation of the satellite TOCs is small. However, when considering single stations consistently affected by the polar vortex, we conclude that mismatched cases should be excluded from the comparisons. • Satellite ozone validation efforts may depend on the location of the polar vortex. • Different columns may be observed by the satellite and the ground-based observations. • For ten years of collocations very few mismatched cases are found on a global scale. • For individual stations the mismatched cases could be excluded. [ABSTRACT FROM AUTHOR]

Trend detection in hydro-climatological time series is a prime task under the context of climate changes. Rainfall is a key component of the water cycle and its variability can profoundly influence agriculture, ecosystems and water resource management. In this paper, an innovative trend analysis (ITA) method with a significant test is used for rainfall trend detection at 14 stations in the Yangtze River Delta (YRD) during 1961–2016. The trends are separately evaluated for low (<10th percentile), medium (10th–90th percentile) and high (>90th percentile) rainfall at the annual and seasonal scales. The slope and significance of the rainfall trends derived from the ITA method are compared with those from the classical trend analysis methods Theil-Sen approach and Mann-Kendall test, respectively. The ITA shows significant increasing trends at the 99% confidence level in annual rainfall at all stations. While the same significant increasing trends are identified for summer and winter, decreasing trends dominate in spring and autumn. Contrasting trends are found for extreme rainfall with strong increasing trends in high rainfall in summer and winter and decreasing trends in low rainfall in spring and autumn. The results of the ITA confirmed by the classical trend analysis methods call for more attention to the risk management of flood in extreme seasons and drought in transitional seasons across the YRD region. • Trends analysis of rainfall across the Yangtze River Delta is performed by the innovative trend analysis (ITA) method. • Separate trends in low, medium and high rainfall are quantitatively calculated based on the ITA method. • Some advantages of the ITA method to classical trend methods (Mann-Kendall test and Theil-Sen approach) are presented. • High rainfall in summer showed significant increase while low rainfall in spring and autumn exhibited decrease. [ABSTRACT FROM AUTHOR]