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This paper presents climatological features of the longitudinal structures WN4, WN3, and WN2 and their drivers observed in the lower thermospheric temperatures and in the ionospheric TEC. For this purpose, two long-term data sets are utilized: the satellite SABER/TIMED temperature measurements, and the global TEC maps generated with the NASA JPL for the interval of 2002–2022. As the main drivers of the longitudinal structures are mainly nonmigrating tides, this study first investigates the climatology of those nonmigrating tides, which are the main contributors of the considered longitudinal structures; these are nonmigrating diurnal DE3, DE2, and DW2, and semidiurnal SW4 and SE2 tides. The climatology of WN4, WN3, and WN2 structures in the lower thermosphere reveals that WN4 is the strongest one with a magnitude of ~20 K observed at 10° S in August, followed by WN2 with ~13.9 K at 10° S in February, and the weakest is WN3 with ~12.4 K observed over the equator in July. In the ionosphere, WN3 is the strongest structure with a magnitude of 5.9 TECU located at −30° modip latitude in October, followed by WN2 with 5.4 TECU at 30 modip in March, and the last is WN4 with 3.7 TECU at −30 modip in August. Both the climatology of the WSA and the features of its drivers are investigated as well. [ABSTRACT FROM AUTHOR]

Aerosols, both natural and anthropogenic, are an important but complex component of the Earth's climate system. Their net impact on climate is about equal in magnitude to that of greenhouse gases but can vary significantly by region and type. Understanding and quantifying these aerosol effects is critical for accurate climate modeling and for developing strategies to mitigate climate change. In this paper, we utilize AERONET (Aerosol Robotic NETwork) data from 10 stations situated in the dust belt region to characterize aerosol properties essential for climate change assessment. Aerosol optical depth (AOD) data at 500 nm and Ångström exponent (α) data at the pair of wavelengths of 440 and 870 nm (α440-870) in the study region are analyzed to discriminate among different types of aerosols. The annual and monthly variabilities in AODs are analyzed to see the aerosols trend in the study region. In addition, the AOD and α440-870 data are utilized in order to determine different aerosol types during the period of study. Furthermore, the correlation coefficient between AODs and various meteorological parameters (temperature, wind speed, wind direction, relative humidity, and visibility) is analyzed. The results of the study indicate that Tamanrasset (2.49%), KAUST (1.29%), Solar Village (1.67%), and Dalanzadgad (0.64%) indicate an increasing trend, while Cairo (−0.38%), Masdar (−2.31%), Dushanbe (−1.18%), and Lahore (−0.10%) indicate a decreasing trend in AODs during the study period. Similarly, the results of characterizing aerosol types show that the highest percentage of desert dust aerosols (68%), mixed aerosols (86%), and biomass burning aerosols (15%) are found over Tamanrasset, Lahore, and Dalanzadgad AERONET stations. The study revealed a strong correlation between AODs and visibility, a moderate correlation with temperature, and a low correlation with other meteorological parameters (wind speed, wind direction, and relative humidity) in the study region. The results of the study are very encouraging and enhance our confidence in using historical AERONET data to improve our understanding of atmospheric aerosols' characteristics. [ABSTRACT FROM AUTHOR]

Clouds play a crucial role in Earth's climate system by modulating radiation fluxes via reflection and scattering, and thus the slightest variation in their spatial coverage significantly alters the climate response. Until now, due to the sparse distribution of advanced observation stations, large uncertainties in cloud climatology remain for many regions. Therefore, this paper estimates total cloud cover (TCC) by using sunshine duration measured in different tropical climates in Ghana. We used regression tests for each climate zone, coupled with bias correction by cumulative distribution function (CDF) matching, to develop the estimated TCC dataset from nonlinear empirical equations. It was found that the estimated percentage TCC, 20.8–84.7 ± 3.5%, compared well with station-observed TCC, 21.9–84.4 ± 3.5%, with root mean square errors of 1.08–9.13 ± 1.8% and correlation coefficients of 0.87–0.99 ± 0.03. Overall, spatiotemporal characteristics were preserved, establishing that denser clouds tended to prevail mostly over the southern half of the forest-type climate during the June–September period. Moreover, the model and the observations show a non-normality, indicating a prevalence of above-average TCC over the study area. The results are useful for weather prediction and application in meteorology. [ABSTRACT FROM AUTHOR]

This paper investigates the annual and seasonal variations in the minimum and maximum air temperature (Tmin and Tmax) and precipitation over Kashmir valley, Northwestern Himalayas from 1980–2019 by using the innovative trend analysis (ITA), Mann-Kendall (MK), and Sen's slope estimator methods. The results indicated that the annual and seasonal Tmin and Tmax are increasing for all the six climatic stations, whereas four of them exhibit significant increasing trends at (α = 0.05). Moreover, this increase in Tmin and Tmax was found more pronounced at higher altitude stations, i.e., Pahalgam (2650 m asl) and Gulmarg (2740 m asl). The annual and seasonal precipitation patterns for all climatic stations showed downward trends. For instance, Gulmarg station exhibited a significant downward trend for the annual, spring, and winter seasons (α = 0.05). Whereas, Qazigund showed a significant downward trend for the annual and spring seasons (α = 0.05). The overall analysis revealed that the increased Tmin and Tmax trends during the winter season are one of the reasons behind the early onset of melting of snow and the corresponding spring season. Furthermore, the observed decreased precipitation trends could result in making the region vulnerable towards drier climatic extremes. Such changes in the region's hydro-meteorological processes shall have severe implications on the delicate ecological balance of the fragile environment of the Kashmir valley. [ABSTRACT FROM AUTHOR]

Turkey is located in the heart of complex transition geography between Eurasia and the Middle East. In the grand scheme, the so-called eastern Mediterranean Basin is located almost in the middle of the dusty belt, and is a hot spot of climate change. The downstream location of dust-carrying winds from close desert sources reveals Turkey as an open plane to particulate matter exposure throughout the year. In order to clarify this phenomenon, this paper aims to determine the desert dust climatology of Turkey via CALIPSO onboard Lidar. This prominent instrument enables us to understand clouds, aerosols and their types, and related climatic systems, with its valuable products. In this study, a 9-year CALIPSO-derived pure dust product dataset was formed to explain horizontal and vertical distributions, transport heights and case incidences. The results indicated that the pure dust extinction coefficient increased as the location shifted from west to east. Moreover, in the same direction of west to east, the dominant spring months changed to summer and autumn. Mountain range systems surrounding Anatolia were the main obstacles against lofted and buoyant dust particles travelling to northern latitudes. Even if high ridges accumulated mass load on the southern slopes, they also enabled elevated particles to reach the ground level of the inner cities. [ABSTRACT FROM AUTHOR]

This paper explores the impact of choice of ventilation setting ("window open", "new (external) air" and "recirculate") on in-vehicle carbon monoxide exposures for commuters travelling by car at different times of the day (morning, midday, and evening) and different seasons (warm and cool) in Auckland, New Zealand. Three near-identical vehicles travelled in close proximity to each other on the same three "loops" out and into the city three times a day, each with a different ventilation setting. Concentrations of carbon monoxide were recorded using portable monitors placed inside each of the vehicles. The season was not found to be a significant factor. However, mean concentrations varied across ventilation settings by the time of day, typically peaking during the morning commute. The mean concentrations were significantly different between ventilation settings, with the recirculate setting found to result in a higher in-vehicle concentration than either new air or windows open but also heavily dependent on the initial in-vehicle concentration. However, this setting was the most effective at avoiding concentration spikes, especially when idling at intersections; an isolated peak event reaching 170 ppm was observed with the "new air" setting when following immediately behind an old, poorly-tuned, and visibly-emitting vehicle. This study suggests that having the windows open is the best setting for maintaining low in-cabin air pollution levels but that recirculate should be used in anticipation of congested conditions. [ABSTRACT FROM AUTHOR]

Deep convection is a threat to many human activities, with a great impact on aviation safety. On 7 July 2017, a widespread torrential precipitation event (associated with a cut-off low at mid-levels) was registered in the vicinity of Madrid, causing serious flight disruptions. During this type of episode, accurate short-term forecasts are key to minimizing risks to aviation. The aim of this research is to improve early warning systems by obtaining the best WRF model setup. In this paper, the aforementioned event was simulated. Various model configurations were produced using four different physics parameterizations, 3-km and 1-km domain resolutions, and 0.25° and 1° initial condition resolutions. Simulations were validated using data from 17 rain gauge stations. Two validation indices are proposed, accounting for the temporal behaviour of the model. Results show significant differences between microphysics parameterizations. Validation of domain resolution shows that improvement from 3 to 1 km is negligible. Interestingly, the 0.25° resolution for initial conditions produced poor results compared with 1°. This may be linked to a timing error, because precipitation was simulated further east than observed. The use of ensembles generated by combining different WRF model configurations produced reliable precipitation estimates. [ABSTRACT FROM AUTHOR]

In this paper, the performances of 12 CMIP5 (Coupled Model Intercomparison Project phase 5) models for simulating the climatology and interannual variability of the East Asian trough (EAT) are assessed using the National Centers for Environmental Prediction (NCEP) reanalysis data and the outputs of the CMIP5 models. The multimodel ensemble (MME) successfully reproduces the spatial pattern and spatial variations in the climatology and interannual variability of the EAT but the intensity and interannual variability of EAT are weaker than in the observations. The biases in intensity (interannual variability) are larger over the southern (northern) part of the EAT than over the northern (southern) part. The intermodel spreads are small for the EAT intensity but are large for its location in terms of both latitude and longitude. The simulated EAT in the MME is about 3° E and 1.5° S of that observed. All 12 CMIP5 models reproduce the first empirical orthogonal function (EOF) mode of EAT activity; however, its intensity and location are only successfully captured in half of the models and its linear weakening trend is simulated in ten models. The second EOF mode of EAT activity and its linear strengthening trend are successfully reproduced in eight models. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

Greece and the surrounding areas experienced an early warm spell with characteristics of a typical summer Mediterranean heatwave in mid-May 2020. The maximum 2 m temperature at Kalamata (southern Greece) reached 40 °C on 16 May and at Aydin (Turkey), it was 42.6 °C on 17 May. There was a 10-standard deviation positive temperature anomaly (relative to the 1975–2005 climatology) at 850 hPa, with a southwesterly flow and warm advection over Greece and western Turkey from 11 to 20 May. At 500 hPa, a ridge was located over the Eastern Mediterranean, resulting in subsidence. The aims of this study were (a) to investigate the prevailing synoptic conditions during this event in order to document its occurrence and (b) to assess whether this out-of-season heatwave was predictable on subseasonal timescales. The subseasonal predictability is not a well-researched scientific topic in the Eastern Mediterranean Sea. The ensemble global forecasts from six international meteorological centres (European Centre for Medium-Range Weather Forecasts—ECMWF, United Kingdom Met Office—UKMO, China Meteorological Administration—CMA, Korea Meteorological Administration—KMA, National Centers for Environmental Prediction—NCEP and Hydrometeorological Centre of Russia—HMCR) and limited area forecasts using the Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF) forced by Climate Forecast System version 2 (CFSv.2; NCEP) forecasts were evaluated for lead times ranging from two to six weeks using statistical scores. WRF was integrated using two telescoping nests covering Europe, the Mediterranean basin and large part of the Atlantic Ocean, with a grid spacing of 25 km, and Greece–western Turkey at 5 km. The results showed that there were some accurate forecasts initiated two weeks before the event's onset. There was no systematic benefit from the increase of the WRF model's resolution from 25 km to 5 km for forecasting the 850 hPa temperature, but regarding the prediction of maximum air temperature near the surface, the high resolution (5 km) nest of WRF produced a marginally better performance than the coarser resolution domain (25 km). [ABSTRACT FROM AUTHOR]

The 2015 release of the precipitation climatology from the Global Precipitation Climatology Centre (GPCC) for 1951-2000, based on climatological normals of about 75,100 rain gauges, allows for quantification of mean land surface precipitation as part of the global water cycle. In GPCC's 2011-release, a bulk climatological correction was applied to compensate for gauge undercatch. In this paper we derive an improved correction approach based on the synoptic weather reports for the period 1982-2015. The compared results show that the climatological approach tends to overestimate the correction for Central and Eastern Europe, especially in the northern winter, and in other regions throughout the year. Applying the mean weather-dependent correction to the GPCC's uncorrected precipitation climatology for 1951-2000 gives a value of 854.7 mm of precipitation per year (excluding Antarctica) or 790 mm for the global land surface. The warming of nearly 1 K relative to pre-industrial temperatures is expected to be accompanied by a 2%-3% increase in global (land and ocean) precipitation. However, a comparison of climatology for 30-year reference periods from 1931-1960 up to 1981-2010 reveals no significant trend for land surface precipitation. This may be caused by the large variability of precipitation, the varying data coverage over time and other issues related to the sampling of rain-gauge networks. The GPCC continues to enlarge and further improve the quality of its database, and will generate precipitation analyses with homogeneous data coverage over time. Another way to reduce the sampling issues is the combination of rain gauge-based analyses with remote sensing (i.e., satellite or radar) datasets. [ABSTRACT FROM AUTHOR]

Highlights from the article: This special issue collects original and review articles on large-scale atmospheric circulation variability and its climate impacts. Anomalous atmospheric circulations influence temperature and precipitation fields, the two most important climate elements. Papers 7-12 explore sea surface temperature (SST) forcings, particularly those associated with the tropical El Niño-Southern Oscillation (ENSO), on atmospheric circulation and climate anomalies over various regions across the globe.

In this study, we propose an easy and robust algorithm to identify and track extratropical cyclone events using 850 hPa relative vorticity data, gaussian filter and connected-component labeling technique, which recognize the cyclone as areas under a threshold. Before selecting the events, the algorithm can include essential characteristics that are good metrics of intensity, like minimum mean sea level pressure and maximum 10-m winds. We implemented the algorithm in the Southern Hemisphere, using a 41-year high resolution dataset. Sensitivity tests were performed to determine the best parameters for detection and tracking, such as degree of smoothing, thresholds of relative vorticity at 850 hPa and the minimum area within the threshold. Two case studies were used to assess the positive and negative points of the methodology. The results showed that it is efficient in obtaining the position of extratropical cyclones in their most intense stage, but it does not always perform well during cyclolysis. We compare the methodology using 1-h temporal resolution to that using a 6-hours temporal resolution, and their reproducibility regarding the literature. The extratropical cyclone climatology in the Southern Hemisphere is provided and discussed. The algorithm developed here can be applied to datasets with good spacial and temporal resolution, providing a better inventory of extratropical cyclones. [ABSTRACT FROM AUTHOR]

In weather forecasting and climate monitoring, daily maximum and minimum air temperatures (TMAX and TMIN) are fundamental for operational and research purposes, from early warning of extreme events to climate change studies. This study provides an integrated evaluation of TMAX and TMIN from two European Centre for Medium-range Weather Forecasts (ECMWF) products: ERA5 reanalysis (1980–2019) and operational weather forecasts (2017–2021). Both products are evaluated using in situ observations from the Global Historical Climatology Network (GHCN). While the analyses span globally, emphasis is given to four key regions: Europe, East and West United States, and Australia. Results reveal a general underestimation of TMAX and overestimation of TMIN in both operational forecasts and ERA5, highlighting the limitation of the ECMWF model in estimating the amplitude of the diurnal cycle of air temperature. ERA5′s accuracy has improved over the past decade, due to enhanced constrain of land–atmosphere analysis streaming from more and higher-quality satellite data. Furthermore, ERA5 outperforms one-day-ahead weather forecasts, indicating that non-real-time dependent studies should rely on ERA5 instead of real-time operational forecasts. This study underscores the importance of ongoing research in model and data assimilation, considering the relevance of daily temperature extremes forecasting and reanalysis for operational meteorology and climate monitoring. [ABSTRACT FROM AUTHOR]

This paper explores how climate services are framed in the literature and possible implications for climate services' policies and projects. By critically exploring the frames around climate services, the wider objective is to encourage more reflexive and responsible research in the field, particularly given the huge challenge that climate change represents. By using a framing analysis based on an extensive literature review, five dominant frames were identified. Climate services are mainly framed (1) as a technological innovation, (2) as a market, (3) as an interface between users and producers, (4) as a risk management tool, and (5) from an ethical angle. The predominant frames influence how we think about climate services, shared assumptions, and the way in which policies and projects are designed. To prevent negative effects of climate services on the ground, such as inequalities, the main recommendations include establishing interdisciplinary and transdisciplinary dialogues between different communities of practice and players, increasing empirical and social science research to improve our understanding of this new field, and finally, re-thinking climate services in terms of adaptation rather than as the mere production of new information products. [ABSTRACT FROM AUTHOR]

The impact of adverse weather conditions (AWCs) on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI) related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical ("event scenario") approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs. [ABSTRACT FROM AUTHOR]

The North China Famine of 1876–1879, known in Chinese as the Dingwu qihuang (丁戊奇荒), is a famous case of drought-induced famine in Chinese history. The purpose of this paper is to provide empirical and historical evidence for understanding the impacts of extreme climate events and major disasters and the mechanisms of adaptation. From the aspects of famine-related migration and the allocation of relief money and grain, the regional interactions in social responses to extreme climate events were analyzed. This paper collected 186 records from historical documents. Regarding the regions as the nodes and the relationships between regions as the links, the spatial patterns of famine-related migration and the allocation of money and grain from 1877 to 1878 were rebuilt. The results show that, firstly, famine-related migration appeared to be spontaneous and short-distanced, with the flow mainly spreading to the surrounding areas and towns. Secondly, as a state administrative action, the relief money and grain from the non-disaster areas were distributed to the disaster areas. However, the distribution of relief grain affected the equilibrium of the food market in non-disaster areas, which led to fluctuations in food prices. [ABSTRACT FROM AUTHOR]

The Third Pole region, especially the Himalayas, is a lightning hotspot. Predicting lightning activity in this region is difficult due to the complex monsoon and westerly circulations, as well as the complex orography. Km-scale simulations can explicitly, without parameterization, tackle deep convective phenomena. A year-long (October 2019–September 2020) ICON-CLM simulation was performed with a km-scale horizontal grid spacing of 3.3 km to assess the region's lightning activity and evaluate the model ICON-CLM. The simulated lightning potential index (LPI) was compared against the lightning proxy CAPE × PREC (CP) derived from ICON-CLM and reanalysis ERA5. In addition, the LPI was evaluated against the TRMM lightning climatology and observed flashes from the International Space Station Lightning Imaging Sensor (ISS-LIS). The LPI reproduced the major spatial, seasonal, and diurnal features of lightning activity as represented in the TRMM climatology. In contrast, the CP from both ICON-CLM and ERA5 performed less well regarding the location of events and the diurnal features. Taking the mean values of the LPI and CP of all the grids within 90 km × 90 km around the ISS-LIS detected lightning event, we found that over 80% of lightning events were recorded using the ICON-CLM simulation. Analysis of individual cases showed that the LPI predicted localization of lightning events better, but flash counts were slightly lower than the CP. Therefore, the combined use of ICON-CLM's simulated LPI and CP can be a valuable predictor for lightning events over the Third Pole region. [ABSTRACT FROM AUTHOR]

Based on the hourly ERA5 reanalysis dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF) from 1 January 1979 to 31 December 2019, the climatology of the planetary boundary layer height (PBLH) in Jiangsu, China, is studied. The PBLH based on ERA5 is verified by using radiosonde data, and the results show that the PBLH based on ERA5 fits very well with the PBLH diagnosed by the radiosonde data. Overall, the daytime average PBLH is between 700 and 1200 m, which is higher in the north and lower in the south. It is between 100 and 400 m at night, and it is lower in the north and higher in the south. The PBLH exhibits complex spatiotemporal variation. In the daytime, the PBLH in inland areas is highest in spring, followed by fall and summer, and lowest in winter. At night, the seasonal variation in the PBLH is less obvious. The seasonal variation in the PBLH in coastal areas is higher in fall and winter and lower in spring and summer. The PBLH shows an obvious diurnal cycle, usually reaching its peak at 14:00 (LST) or 15:00 (LST). The diurnal cycle of the PBLH is significantly positively correlated with the near-surface temperature and wind speed and significantly negatively correlated with the relative humidity and lower tropospheric stability. Over these 41 years, the daytime PBLH has increased significantly in most areas. The increase in the PBLH can be attributed to the increase in near-surface temperature and the decrease in near-surface relative humidity and lower tropospheric stability. [ABSTRACT FROM AUTHOR]

In Sub-Saharan Africa, the recurring erratic and uneven rainfall distribution has resulted in low crop yields, income losses, and low food stock. In response to these climate change challenges, farmers have recourse to several coping strategies to survive. This present paper explores farmers' perception of climate variability and the coping strategies in use in the Central River Region of The Gambia. The main purpose of this paper is to analyze perceived climate variability and farm level adaptation options in the region. Data were collected from 283 farmhouses through transect walks, quantitative surveys including the use focus group discussions. Data were analyzed using descriptive and inferential statistics. Results revealed that farmers generally perceive an increase in the frequency of extreme weather events and a decrease in the duration of the growing season. With regards to vulnerability and severity, nearly 95% of the respondents considered the dryness as the main threat to their farming activities and perceived its consequences as the most severe. The results equally showed that the perception of changes is linked to the adoption of some adaptation measures among which the preferred were the use of chemical fertilizers (66%), though it is stated to be the most expensive. The Spearman correlation test showed that the use of water conservation techniques is highly correlated with the quality of soil surface structure (p ≤ 0.01) and soil storage capacity (p ≤ 0.01). Findings of this study are of paramount importance in planning and implementing adaptation policies in The Gambia and beyond. To improve farmers' resilience, drought tolerant crops should be promoted along with climate change and variability awareness campaigns. [ABSTRACT FROM AUTHOR]

When assessing the magnitude of climate signals in a regional scale, a host of optional approaches is feasible. This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as employing empirical statistical downscaling methods (ESD). In this context the question is addressed: Is an empirical statistical downscaling method capable of yielding results that are comparable to those by dynamical RCMs? Based on the presented ESD method, the comparison of RCM and ESD results show a high amount of agreement. In addition the empirical statistical downscaling can be applied directly to a GCM or a GCM-RCM cascade. The paper aims at comparing the consequences of employing various CGM-RCM-ESD combinations on the derived future changes of temperature and precipitation. This adds to the insight on the scale dependency of downscaling strategies. Results for one GCM with several scenario runs driving several RCMs with and without subsequent empirical statistical downscaling are presented. It is shown that there are only small differences between using the GCM results directly or as a GCM-RCM-ESD cascade. [ABSTRACT FROM AUTHOR]

Severe convective windstorms and tornadoes regularly hit the territory of Russia causing substantial damage and fatalities. An analysis of the climatology and formation environments of these events is essential for risk assessments, forecast improvements and identifying of links with the observed climate change. In this paper, we present an analysis of severe convective windstorms, i.e., squalls and tornadoes reported between 1984 and 2020 in the Perm region (northeast of European Russia), where a local maximum in the frequency of such events was previously found. The analysed database consists of 165 events and includes 100 squalls (convective windstorms), 59 tornadoes, and six cases with both tornadoes and squalls. We used various information to compile the database including weather station reports, damage surveys, media reports, previously presented databases, and satellite images for windthrow. We found that the satellite images of damaged forests are the main data source on tornadoes, but their role is substantially lower for windstorm events due to the larger spatial and temporal scale of such events. Synoptic-scale environments and associated values of convective indices were determined for each event with a known date and time. Similarities and differences for the formation conditions of tornadoes and windstorms were revealed. Both squalls and tornadoes occur mostly on rapidly moving cold fronts or on waving quasi-stationary fronts, associated with low-pressure systems. Analyses of 72-h air parcel backward trajectories shows that the Caspian and Aral Seas are important sources of near-surface moisture for the formation of both squalls and tornadoes. Most of these events are formed within high CAPE and high shear environments, but tornadic storms are generally characterised by a higher wind shear and helicity. We also differentiated convective storms that caused forest damage and those did not. We found the composite parameter WMAXSHEAR is the best discriminator between these two groups. In general, storm events causing windthrow mainly occur under conditions more favourable for deep well-organised convection. Thus, forest damage can be considered as an indicator of the storm severity in the Perm region and in adjacent regions with forest-covered area exceeding 50%. [ABSTRACT FROM AUTHOR]

In the Yellow and Bohai Seas, the detailed characteristics of visibility are analyzed based on automatic hourly observation data of marine visibility between 2019 and 2021. The results show that the annual average visibility in the Yellow and Bohai Seas is 13.346 km. The average visibility at high latitudes is higher than that at low latitudes in the Yellow and Bohai Seas. The low visibility area is mainly distributed in the southwest of the Yellow Sea. There are obvious seasonal differences in visibility in the Yellow and Bohai Seas. Visibility is high from September to November, with maximum values in October. Visibility is lowest in July when the maximum visibility is low and the minimum visibility is high. The visibility in spring is overall relatively low, and the areas of low visibility appear in the southwest of the Yellow Sea. The visibility in autumn is overall relatively high, and the areas of high visibility occur in the northern part of the Bohai and Yellow Seas. The visibility has significant intraday variation. The visibility around sunset is significantly higher than that around sunrise. The hourly visibility is low between 4:00 and 9:00, with the lowest visibility most likely around 7:00. The hourly visibility is high between 16:00 and 21:00, with the highest visibility most likely around 18:00. Low visibility occurs frequently between November and April, most of all in March. Low visibility most often occurs between 4:00 and 7:00. Low visibility may occur at any time between November and April, and also in mornings between May and August. It occurs less often at other times. [ABSTRACT FROM AUTHOR]

The PannEx is a GEWEX-initiated, community driven research network in the Pannonian Basin. One of the main scientific issues to address in PannEx is the investigation of precipitation extremes. Meteorological Services in the PannEx area collected the hourly precipitation data and commonly used a computer program, which was developed in the INTENSE project, to produce a set of global hydro-climatic indices. Calculations are carried out on data aggregated 1-, 3- and 6-h intervals. Selected indices are analyzed in this paper to assess the general climatology of the short-term precipitation in the Pannonian basin. The following indices are illustrated on maps and graphs: the annual mean and maxima of 1-h, 3-h and 6-h sums, the count of 3-hr periods greater than 20 mm thresholds, the maximum length of wet hours, the timing of wettest hour and the 1-h precipitation intensity. The seasonal trends of the 1-h precipitation intensity were tested from 1998 to 2019. Analysis of sub-daily precipitation has been limited by the availability of data on a global or a regional scale. The international effort made in this work through collaboration in the PannEx initiative contributes to enlarging the data availability for regional and global analysis of sub-daily precipitation extremes. [ABSTRACT FROM AUTHOR]

Mediterranean regions are prone to heavy rainfall, flash floods, and erosion issues. Drop size distribution (DSD) is a key element for studying these phenomena through the hydrological variables which can be derived from it (rainfall rates and totals, kinetic energy fluxes). This paper proposes a five-year (2012-2016) DSD climatology, summarized by scaling parameters for concentration, size, and shape. The DSD network is composed of two longitudinal transects of three OTT Parsivel optical disdrometers each, across the Mediterranean Cevennes-Vivarais region. The influence of several factors are analysed: location (distance from the sea, orographic environment), season, daily synoptic weather situation (derived from geopotential heights, at 700 and 1000 hPa), rainfall type (analysed from 5 min radar data), as well as some combinations of these factors. It was found and/or confirmed that the orographic environment, season, weather patterns associated with the exposure to low level atmospheric flows, and rainfall types influenced the microphysical processes, leading to rainfall, measured at the ground. Consequently, the DSD characteristics, as well as the relationships between the rainfall rate and reflectivity factor, are influenced by these factors. [ABSTRACT FROM AUTHOR]

This study evaluated the historical precipitation simulations of 49 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing annual and seasonal precipitation climatology, linear trends, and their spatial correlation with global SST across Africa and the Arabian Peninsula during the period of 1980–2014, using Global Precipitation Climatology Centre (GPCP) data as a reference. Taylor's diagram was used to quantify the strengths and weaknesses of the models in simulating precipitation. The CMIP6 multi-mean ensemble (MME) and the majority of the GCMs replicated the dominant features of the spatial and temporal variations reasonably well. The CMIP6 MME outperformed the majority of the individual models. The spatial variation of the CMIP6 MME closely matched the observation. The results showed that at annual and seasonal scales, the GPCP and CMIP6 MME reproduced a coherent spatial pattern in terms of the magnitude of precipitation. The humid region received >300 mm and the arid region received <50 mm across Africa and the Arabian Peninsula. The models from the same modeling centers replicated the precipitation levels across different seasons and regions. The CMIP6 MME and the majority of the individual models overestimate (underestimate) in humid (arid and semi-arid)-climate zones. The annual and pre-monsoon seasons (i.e., DJFMA) were better replicated in the CMIP6 GCMs than in the monsoon-precipitation model (MJJASON). The CMIP6 MME (GPCP) showed stronger wetting (drying) trends in the northern hemisphere. In contrast, a strong drying trend in the CMIP6 MME and a weak wetting trend in the GPCP were shown in the Southern Hemisphere. The CMIP6 MME captures the spatial pattern of linear trends better than individual models across different climate zones and regions. The relationship between precipitation and sea-surface temperature (SST) exhibited a high spatial correlation (−0.80 and 0.80) with large variability across different regions and climate zones. The GPCP (CMIP6 MME) exhibited a heterogenous (homogeneous) spatial pattern, with higher correlation coefficients recorded in the CMIP6 MME than in the GPCP in all cases. Individual models from the same modeling centers showed spatial homogeneity in correlation values. The differences exhibited by the individual GCMs highlight the significance of each model's unique dynamics and physics; however, model selection should be considered for specific applications. [ABSTRACT FROM AUTHOR]

Based on severe weather reports, surface precipitation observations, surface routine observations, and the European Center for Medium-Range Weather Forecasts ERA5 reanalysis dataset during the warm seasons (May–September) of 2011–2018 over North China, this paper analyzes the statistical characteristics and environmental conditions of three types of severe convective events. Results are compared between events with different altitudes (i.e., mountains and plains), severities (i.e., ordinary and significant), and months. Hail and thunderstorm high winds (THWs) are more common over the mountains whereas short-duration heavy rainfall (SDHR) is more frequent over the plains. The occurrence frequency of severe convective events exhibits distinct monthly and diurnal variations. Analyses of the environmental parameters provide reference for the potential forecasting of severe convective events over this region. Specifically, the 850–500 hPa temperature lapse rate (LR85), pseudo-equivalent potential temperature at 500 hPa (thetase500), and precipitable water (PW) are skillful in distinguishing hail and THW environments from SDHR environments, and thetase500 is useful in discriminating between hail and THW environments. The convective environments over the plains are characterized by significantly higher (lower) PW (LR85) compared with mountains. The skill of these parameters in forecasting the severity of the convective hazards is limited. Probability distributions in the two parameters space indicate that the occurrence of significant hail requires both higher most unstable convective available potential energy (MUCAPE) and stronger 0–6 km bulk wind shear (SHR6) compared with ordinary hail. Compared with ordinary THWs, the significant THWs over the mountains depend more on the SHR6 whereas those over the plains rely more on the MUCAPE. The significant SDHR events over the plains tend to occur under a variety of instability conditions. The thermodynamic parameters (i.e., MUCAPE, thetase500, and downdraft convective available potential energy), and PW are significantly higher in July–August, whereas the LR85 and vertical wind shear are apparently higher in May, June and September. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the Regional Climate Model version 4.6.1 (RegCM4) at a high-resolution simulation at 10 km applied over the Tibetan Plateau. This simulation covers the period from 1980 to 2010 and is nested in a RegCM4 simulation at 30-km resolution, which is driven by the main European Centre for Medium-Range Weather and Forecasting reanalysis (ERA-Interim reanalysis) dataset. A new daily observational dataset is employed as reference data to evaluate the temperature and precipitation simulations for the inner model domain and the five largest river basins that originated in the Tibetan Plateau (TP) (i.e., the source region of Yangtze River, Yellow River, Mekong River, Salween River, and Brahmaputra River). In comparison with the low-resolution model run (R30), the cold biases for the area-averaged temperature were reduced from −2.5 to −0.1° C and the wet biases in summer mean precipitation were reduced from 58% to 25% in the high-resolution model run (R10). The substantial warming trends and slight wetting trends were basically reproduced by both RegCM4 simulations. Annual mean precipitation trends from both simulations show a better agreement with the observations than the ERA-Interim, which underestimates the annual mean precipitation trends in most regions, whereas both the RegCM4 and ERA-Interim consistently underestimate the annual mean temperature trends when compared with the observations. In addition, the overall improvement in the modeling trends for annual mean temperature and precipitation in R10 is limited when compared with R30. The extreme precipitation was also captured reasonably in both RegCM4 simulations, and the better performance is detected in the R10 simulation. The findings above show that RegCM4 with a high-resolution of 10 km is capable of reproducing the major regional climate features over the TP, but a great deal of uncertainties still exist, especially in the subregion of the Brahmaputra River basin. Thus, the 10-km resolution simulation in RegCM4 may still not be fine enough to resolve the topoclimates over the complex Himalayan terrain in the Brahmaputra River basin. [ABSTRACT FROM AUTHOR]

Using multisource sea ice fusion data, the spatiotemporal characteristics of sea ice cover were analyzed for the marginal seas of East Asia for the period 2005–2021. The results show that there were obvious differences in the beginning and end dates of the sea ice in the different sea areas. The northern Sea of Japan had the longest ice period, and Laizhou Bay and Bohai Bay in the Bohai Sea had the shortest ice period. The time when the largest sea ice extent appeared was relatively stable and mostly concentrated in late January to mid-February. There were obvious spatial differences in the duration of the sea ice cover in the marginal seas of East Asia. The duration of the sea ice cover gradually decreased from high latitude to low latitude and from nearshore to open seas. The annual average duration of the sea ice cover was more than 100 days in most of the Sea of Japan and approximately 20 days in most of Laizhou Bay and Bohai Bay. The melting speed was significantly faster than the freezing speed in the Bohai Sea and Yellow Sea, resulting in asymmetric changes in the daily sea ice extent in the two seas. The increasing trends in the maximum sea ice extent and total sea ice extent were 0.912 × 105 km2/10 yr and 0.722 × 107 km2/10 yr, respectively, from 2005 to 2013, both of which passed the significance test at the 0.05 level. [ABSTRACT FROM AUTHOR]

Climate patterns are natural processes that drive climate variability in the short, medium, and long term. Characterizing the patterns behind climate variability is essential to understand the functioning of the regional atmospheric system. Since investigations typically reveal only the link and extent of the influence of climate patterns in specific regions, the magnitude of that influence in meteorological records usually remains unclear. The central Peruvian Andes are affected by most of the common climate patterns of tropical areas, such as Intertropical Convergence Zone (ITCZ), Sea Surface Temperature (SST), solar irradiance, Madden Julian Oscillation (MJO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO). They are also affected by regional processes that are exclusive from South America, such as the South American Low-Level Jet (SALLJ), South American Monsoon System (SAMS), Bolivian High (BH), and Humboldt Current. The aim of this research is to study the climate variability of precipitation, maximum and minimum temperature records over Cordillera Blanca (Peru), and its relationship with the intensity and periodicity of the common climate patterns that affect this region. To achieve this aim, a spectral analysis based on Lomb's Periodogram was performed over meteorological records (1986–2019) and over different climate pattern indexes. Results show a coincidence in periodicity between MJO and SALLJ, with monthly cycles for precipitation and temperature (27-day, 56-day, and 90-day cycles). Moreover, the most intense periodicities, such as annual (365 days) and biannual (182 and 122 days) cycles in meteorological variables, possibly would be led by ITCZ and ENSO together, as well as a combination of the Humboldt Current and SALLJ. Additionally, interannual periodicities (3-year, 4.5-year, 5.6–7-year and 11-year cycles) would have coincidence with the ENSO–solar combination, while the longest cycles (16 years) could match PDO variability. [ABSTRACT FROM AUTHOR]

Unraveling the relationship between humidity, wind, and rainfall is vitally important to understand the dynamics of water vapor transport. In recent years, the use of causal networks to identify causal flows has gained much ground in the field of climatology to provide new insights about physical processes and hypothesize previously unknown ones. In this paper, the concept of a virtual control volume is proposed, which resembles the Eulerian description of a vector field, but is based on causal flows instead. A virtual control surface is used to identify the influence of surrounding climatic processes on the control volume (i.e., the study region). Such an influence is characterized by using a causal inference method that gives information about its direction and strength. The proposed approach was evaluated by inferring and spatially delineating areas of influence of humidity and wind on the rainfall of Ecuador. It was possible to confirm known patterns of influence, such as the influence of the Pacific Ocean on the coast and the influence of the Atlantic Ocean on the Amazon. Moreover, the approach was able to identify plausible new hypotheses, such as the influence of humidity on rainfall in the northern part of the boundary between the Andes and the Amazon, as well as the origin (the Amazon or the tropical Atlantic) and the altitude at which surrounding humidity and wind influence rainfall within the control volume. These hypotheses highlight the ability of the approach to exploit a large amount of scalar data and identify pathways of influence between climatic variables. [ABSTRACT FROM AUTHOR]

The atmospheric Kelvin wave has been widely studied due to its importance in atmospheric dynamics. Since a long-term climatological study is absent in the literature, we have employed the two-dimensional fast Fourier transform (2D-FFT) method for the 40-year long-term reanalysis of the dataset, ERA-Interim, to investigate the properties of Kelvin waves with wavenumbers 1 (E1) and 2 (E2) at 6–24 days wave periods over the equatorial region of ±10° latitude between a 15 and 45 km altitude during the period 1979–2019. The spatio-temporal variations of the E1 and E2 wave amplitudes were compared to the information of stratospheric quasi-biennial oscillation (QBO), and the wave amplitudes were found to have an inter-QBO cycle variation that was related to sea surface temperature and convections, as well as an intra-QBO cycle variation that was caused by interactions between the waves and stratospheric mean flows. Also, the E1 waves with 6–10 day periods and the E2 waves with 6 days period were observed to penetrate the westerly regime of QBO, which has a thickness less than the vertical wavelengths of those waves, and the waves could further propagate upward to higher altitudes. In a case study of the period 2006–2013, the wave amplitudes showed a good correlation with the Niño 3.4 index, outgoing longwave radiation (OLR), and precipitation during 2006–2013, though this was not the case for the full time series. The present paper is the first report on the 40-year climatology of Kelvin waves, and the morphology of Kelvin waves will help us diagnose the anomalies of wave activity and QBO in the future. [ABSTRACT FROM AUTHOR]

Through an empirical investigation of the historical relationship between the destination climate and tourist arrivals in the Caribbean, this study presents the first revealed preference evaluation of a climate index informed by tourists' stated climatic preferences for coastal-beach tourism (i.e., a sun-sand-surf or 3S travel market). The goal of this multi-organization collaboration was to examine the potential application of a newly designed climate index—the Holiday Climate Index (HCI):Beach—for three Caribbean destinations (Antigua and Barbuda, Barbados, Saint Lucia). This paper provides an overview of the evolution of climate indices, including the development of the (HCI):Beach. To test the validity of climate indices for a beach travel market, daily climate ratings based on outputs from the Tourism Climate Index and the HCI were correlated with monthly arrivals data from Canada (a key source market) at an island destination scale. The results underscore the strength of the new index, with each destination scoring consistently higher using the HCI:Beach, including a stronger relationship (R2) between index scores and tourist arrivals. These findings demonstrate the value of combining stated and revealed preference methodologies to predict tourism demand and highlight opportunities for future research. [ABSTRACT FROM AUTHOR]

Systematically observing components of the climate system as well as their processes and interactions are crucial to understand the weather, climate, climate change, etc. In order to launch long-term, continuous, stereoscopic, and integrated meteorological observations for key regions of the climate system in southwestern China where it is sensitive to interactions among multiple layers and exchanges of mass and energy, the Dali National Climate Observatory (DNCO) was established in May 2006. To date, the DNCO has gradually performed an integrated meteorological observation network in a complex terrain region over the southeastern Tibetan Plateau including the conventional observations of weather and climate, and the special observations of radiation, lightning, soil moisture, wind profile, water vapor, water quality, water level, water temperature profile, turbulent fluxes of momentum, sensible heat, latent heat, carbon dioxide, and methane, etc. Furthermore, the DNCO mainly focuses on the field observation experiments and scientific research activities for mountain meteorology. This paper presents an overview of the DNCO including its location, climatology, scientific objectives, research tasks, and existing observation projects. The progresses in observation and associated research including data quality controls and assessments, recent observation results, and regional numerical model tests are summarized. Future works are also discussed. [ABSTRACT FROM AUTHOR]

Stakeholder participation at the intersection of climate and health is essential to assess and plan for the human health impacts of current and projected climate-sensitive hazards. Using the Maricopa County Department of Public Health (MCDPH) Coalition on Climate Change and Public Health workgroup and the Climate Assessment for the Southwest (CLIMAS) program as examples, this paper describes the important role of scientist–public health stakeholder collaboratives in addressing the public health impacts of climate-sensitive hazards. Using the MCDPH and CLIMAS stakeholder groups, stakeholder connections were mapped to show relationships between the organization types and connections between scientists and public health stakeholders. Stakeholders, defined as meeting attendees, were primarily individuals from academic institutions (n = 175), government agencies (n = 114), non-profits (n = 90), and health departments (n = 85). Engaging public health stakeholders in transdisciplinary regional climate initiatives and addressing gaps in their networks helped these programs to develop more collaborative projects over time. [ABSTRACT FROM AUTHOR]

In this paper, the mechanism and model-representation of a late-spring severe blizzard event on eastern Romania are studied. The mechanism relies on the coupled contribution of the tropospheric ageostrophic circulations associated to jet streaks. These circulations: (1) interact under local and regional forcing (sea surface temperature, topography and latent heat) and (2) feedback on enhancing an upper-level jet's secondary streak, leading to a persistent, severe event. The enhanced secondary jet streak appears only for developing systems that lead to extreme impact, as shown by 40 years of knowledge of late-spring severe blizzards over the area. It is shown that actual regional high-resolution models are able to represent the occurrence and the mechanism of late-spring severe blizzard events, thus increasing the confidence on their ability to represent current and future climate extreme variability. Understanding the preconditioning of dynamic and thermodynamic processes indicated by this analysis could be useful in supporting the operational forecast analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region. [ABSTRACT FROM AUTHOR]

Physical activity is an increasingly frequent part of our leisure time. Within this context, hiking is a popular form of tourism which has a positive impact on the quality of life. In spite of the importance of climate conditions for this recreational activity, relatively little research has been done on hiking from the perspective of climate and tourism. With this in mind in this paper we make the first detailed extensive assessment of climate preferences for the practice of hiking tourism in Spain. To this end a review of the theoretical/methodological body of literature on tourism climatology was conducted together with a survey aimed at evaluating the stated climate preferences of hiking tourists. The results are offered within the framework of international research on climate preferences for a range of tourism activities. The comparative analysis of these results with regard to those obtained in previous research highlights various similarities but also certain factors specific to hiking in Spain. Overall, the climate preferences of hiking tourists are similar to those of other segments of the tourism market in terms of the aesthetic and physical aspects of the climate, although they also have certain specific preferences as regards thermal aspects, especially regarding the optimal daily thermal conditions for hiking. The results obtained are useful for assessing the suitability of the climate for the practice of hiking tourism in Spain and for promoting proper management and planning of this leisure activity in tourist destinations, including the development of climate calendars detailing the most suitable times of the year for hiking at these destinations. These issues will be addressed in future research studies. [ABSTRACT FROM AUTHOR]

Data from historical observatories and future simulations were analyzed using the representative concentration pathway (RCP) 8.5 scenario, which covered the period from 1951 to 2100. In order to characterize the drought, three widely used drought indicators were used: the standardized precipitation index (SPI), the reconnaissance drought index (RDI), and the standardized precipitation and evapotranspiration index (SPEI). The ensemble of the seven (7) GCMs that used RCA-4 was able to capture several useful characteristics of Nigeria's historical climatology. Future climates were forecasted to be wetter than previous periods during the study period based on the output of drought characteristics as determined by SPI. SPEI and RDI predicted drier weather, in contrast. SPEI and RDI's predictions must have been based on the effect of rising temperatures brought on by global warming as depicted by RCP 8.5, which would then have an impact on the rate of evapotranspiration. According to drought studies using the RCP 8.5 scenario, rising temperatures will probably cause more severe/extreme droughts to occur more frequently. SPEI drought frequency changes in Nigeria often range from 0.75 (2031–2060) to 1.80 (2071–2100) month/year, whereas RDI changes typically range from 0.30 (2031–2060) to 0.60 (2071–2100) month/year. The frequency of drought incidence has recently increased and is now harder to forecast. Since the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) and the Sustainable Development Goals (SDGs) have few more years left to be completed, drastic efforts must be made to create climate-resilient systems that can tackle the effects that climate change may have on the water resources and agricultural sectors. [ABSTRACT FROM AUTHOR]

Due to the scarcity of studies linking the variability of rainfall and population growth in the capital cities of Northeastern Brazil (NEB), the purpose of this study is to evaluate the variability and multiscale interaction (annual and seasonal), and in addition, to detect their trends and the impact of urban growth. For this, monthly rainfall data between 1960 and 2020 were used. In addition, the detection of rainfall trends on annual and seasonal scales was performed using the Mann–Kendall (MK) test and compared with the phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The relationship between population growth data and rainfall data for different decades was established. Results indicate that the variability of multiscale urban rainfall is directly associated with the ENSO and PDO phases, followed by the performance of rain-producing meteorological systems in the NEB. In addition, the anthropic influence is shown in the relational pattern between population growth and the variability of decennial rainfall in the capitals of the NEB. However, no capital showed a significant trend of increasing annual rainfall (as in the case of Aracaju, Maceió, and Salvador). The observed population increase in the last decades in the capitals of the NEB and the notable decreasing trend of rainfall could compromise the region's water security. Moreover, if there is no strategic planning about water bodies, these changes in the rainfall pattern could be compromising. [ABSTRACT FROM AUTHOR]

Data collected over a period of 18 months (December 2019–May 2021) at the Bucharest–Măgurele Cloudnet station were analysed for the first time to determine the macrophysical and microphysical cloud properties over this site. A total number of 1,327,680 vertical profiles containing the target classification based on the Cloudnet algorithm were analysed, of which 1,077,858 profiles contained hydrometeors. The highest number of profiles with hydrometeors (>60%) was recorded in December 2020, with hydrometeors being observed mainly below 5 km. Above 5 km, the frequency of occurrence of hydrometeors was less than <20%. Based on the initial Cloudnet target classification, a cloud classification scheme was implemented. Clouds were more frequently observed during winter compared with other seasons (45% of all profiles). Ice clouds were the most frequent type of cloud (468,463 profiles) during the study period, followed by mixed phases (220,280 profiles) and mixed phased precipitable clouds (164,868 profiles). The geometrical thickness varied from a median value of 244 m for liquid clouds during summer to 3362 m for mix phased precipitable clouds during spring. [ABSTRACT FROM AUTHOR]

An updated climatology for the occurrence of blockings in the Southern Hemisphere (SH) using daily reanalysis data from 1948–2021 is presented. Geopotential height (z) at 500 hPa was the working variable. The blocking index (BI) was defined for every 2.5° of longitude whenever z (35 °   S) − z (50 °   S) < 0 . The results were organized in longitudinal bands of a width of 10° in order to compare them with previous findings. The primary region for the occurrence of blockings was located around the date line, with a secondary region in southern South America (SSA) and its vicinities, with a third-rank region situated in southern Africa and its surroundings. The results were also stratified by the intensity and duration (persistence) of the events, and the annual and seasonal differences were discussed. Additionally, three different areas were defined to study the distribution of the blockings therein, with the Pacific region (110° E–80° W) having the maximum intensities and longest durations. Linear trends were estimated for the annual and the seasonal time series of the BI and for the number of episodes. On an annual basis, more frequent and the strongest events are expected at 180° E and their surroundings in the future. An alternative BI, using radiosonde data, was built for SSA at 58.50° W. The time evolution of this index was in general agreement with the one estimated from the reanalysis data at some longitudes. [ABSTRACT FROM AUTHOR]

In the context of urbanization, research on urban microclimate and thermal comfort has become one of the themes of eco-city design. Sky view factor (SVF), one of the parameters of urban spatial form, combines multiple morphological information, such as plane opening, aspect ratio, and building density and has an important impact on the urban microclimate. However, there is still no clear research conclusion on the correlation between SVF and microclimate. In this paper, nine Local Climate Zone (LCZ) models are used and typical summer meteorological conditions of Nanjing are applied as an attempt to partially fill this gap. The calculated microclimate and thermal comfort indices include air temperature (AT), surface temperature (ST), relative humidity (RH), wind speed (WS), mean radiant temperature (MRT), and predicted mean vote (PMV). Results show that the local effect of urban morphology on thermal comfort can be retrieved from the use of comprehensive parameters such as SVF (which takes into account the building height, layout, and density) whose distribution in the investigated models showed to be correlated with MRT, so did PMV under low wind speed conditions. [ABSTRACT FROM AUTHOR]

Examining the effects of climate change on spring maize, and its suitability under dynamic cultivation patterns, will aid strategic decision-making for future agricultural adaptation. This paper investigates the climate suitability of spring maize, based on daily data from 50 meteorological stations, and statistics on maize yield and area at the county level in Jilin Province, China, between 1986 and 2015. Based on a significant correlation between the cultivation patterns indicator ≥10 °C accumulated temperature (AAT10) and the average yield (R2 = 0.503), the yield data are used to determine suitable thresholds for meteorological factors under the dynamic cultivation pattern, and a fuzzy fitness approach is used to evaluate the climate suitability. The results showed a good agreement between suitability estimates and scaled observed yields (average d = 0.705). Moreover, good consistency between cultivation patterns, climate suitability and yield show that the late-maturing varieties of maize have gradually moved northward and eastward, and the areas of high suitability and high yield have gradually expanded eastward. In addition, drought and chilling hazard factors limit the suitability of climate resources, especially in the eastern and western regions. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard with critical societal and economic consequences to millions of people around the world. In this paper, we present the climatology of severe drought events that occurred during the 20th century in the region of Sao Paulo, Brazil. To account for the effects of rainfall deficit and changes in temperature at a climatic timescale, we chose the Standardized Precipitation Evapotranspiration Index (SPEI) to identify severe droughts over the city of Sao Paulo, and the eastern and central-western regions of the state. Events were identified using weather station data and European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis data, in order to assess the representation of drought periods in both datasets. Results show that the reanalysis seems suitable to represent the number of events and their mean duration, severity and intensity, but the timing and characteristics of individual events are not well reproduced. The correlation between observation and reanalysis SPEI time series is low to moderate in all cases. A linear trend analysis between 1901 and 2010 shows a tendency of increasing (decreasing) severe drought events in the central and western (eastern) Sao Paulo state, according to observational data. This is in agreement with previous findings, and the reanalysis presents this same signal. The weakened trend values in the reanalysis may be associated with issues in representing precipitation in this dataset. [ABSTRACT FROM AUTHOR]

Highlights from the article: Moreover, a number of studies in recent years have drawn attention to the increasing intensity of heavy rainfall events, heat waves, and severe droughts in monsoon regions. It is imperative that scientists who study monsoon circulations improve the prediction of their start date or onset, the monsoon intensity, and how these variables respond to climate change. The 16 papers in this volume cover several regional monsoons including East Asia, South Asia and the South China Sea, Australian monsoon, and African Monsoon.

The effect of weather on sport events is largely discussed in the sports medicine and exercise physiology context. It is important, both for event organizers and for medical staff, to know whether the competition is happening at a time and place with extreme weather or in general not appropriate weather and climatic conditions. In order to find out, whether a place or time is appropriate, two factors should be included when establishing the effect of atmospheric conditions on visitors and athletes. These are the main climatic conditions, based on long term data, and the quantification of extreme events, like heat waves. The present analysis aims at determining what kind of data are required for an appropriate quantification of weather and climate thermal stress. For the analysis, indices like Physiologically Equivalent Temperature (PET) and mPET (modified PET) are applied. The advantage of these indices is the consideration of both, thermo-physiological and meteorological factors to provide results and information that can be used for decision making. In this paper, we analyzed the Tokyo area with regards to the upcoming Tokyo 2020 Summer Olympic Games. The results show that this kind of event may not be appropriate for visitors, if it is placed during months with extreme conditions. For Tokyo, this is the period from May to September, when conditions cause strong heat stress to the visitors for the vast majority of hours of the day. A more appropriate time would be the months from November to February or the early morning and the late afternoon hours, when thermally comfortable conditions are much more frequent. The methods that are applied here can quantify the thermal conditions and show limitations and possibilities for specific events and locations. Should the organizers still want to have these competitions organized during these months with extreme conditions, they should promote and propose all possible countermeasures for the spectators, workforce, and athletes. [ABSTRACT FROM AUTHOR]

The climatology of different classifications (based on the intensity at the landfall time) of tropical cyclones (TCs) making landfall in Guangdong Province of China during 1951–2020 (70 years) is investigated using the best track data from the China Meteorological Administration and ERA5 reanalysis data. There were 234 TCs making landfall in Guangdong Province, with more severe tropical storms (STSs, 30.8%) and typhoons (TYs, 27.3%), and less tropical depressions (TDs, 19.7%) and tropical storms (TSs, 22.2%) during the past 70 years. The frequency of the landfall TCs had a significant interannual oscillation of 2–5 years. Landfall TCs generated over the western North Pacific (WNP) were usually more and stronger than those generated over the South China Sea (SCS). The TCs generated over the WNP had longer lifetime duration and shorter on-land duration than those generated over the SCS. TCs making landfall in western Guangdong were the most, followed by central Guangdong and eastern Guangdong. The composite analysis using TC-relative coordinates indicated that the precipitation of different classifications of TCs making landfall in Guangdong Province was asymmetric, which was stronger in the south of the TC center. The position of the maximum precipitation showed a cyclonic rotation around the TC center with increasing TC intensity. Generally, the vertical velocity, moisture flux, warm core, and vertical wind shear enhanced with the increasing landfall TC intensity. The vertical velocity and moisture flux of different classifications of TCs also showed an asymmetric structure related to the distribution of TC precipitation. TSs, STSs, and TYs had a double warm-core configuration. The precipitation of the TDs and TSs usually occurred over the down-shear of average vertical wind shear, those of the STSs and TYs over the left-of-shear. [ABSTRACT FROM AUTHOR]