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Aerosol–cloud interactions play a crucial role in shaping Earth's climate and hydrological cycle. Observing these interactions with high precision and accuracy is of the utmost importance for improving climate models and predicting Earth's climate. Over the past few decades, lidar techniques have emerged as powerful tools for investigating aerosol–cloud interactions due to their ability to provide detailed vertical profiles of aerosol particles and clouds with high spatial and temporal resolutions. This review paper provides an overview of recent advancements in the study of ACI using lidar techniques. The paper begins with a description of the different cloud microphysical processes that are affected by the presence of aerosol, and with an outline of lidar remote sensing application in characterizing aerosol particles and clouds. The subsequent sections delve into the key findings and insights gained from lidar-based studies of aerosol–cloud interactions. This includes investigations into the role of aerosol particles in cloud formation, evolution, and microphysical properties. Finally, the review concludes with an outlook on future research. By reporting the latest findings and methodologies, this review aims to provide valuable insights for researchers engaged in climate science and atmospheric research. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) can cause severe wind and rain hazards. Unusual TC tracks and their extreme precipitation forecasts have become two difficult problems faced by conventional models of primitive equations. The case study in this paper finds that the numerical computation of the climatological component in conventional models restricts the prediction of unusual TC tracks. The climatological component should be a forcing quantity, not a predictor in the numerical integration of all models. Anomaly-based variable models can overcome the bottleneck of forecast time length or the one-week forecasting barrier, which is limited to less than one week for conventional models. The challenge in extreme precipitation forecasting is how to physically get the vertical velocity. The anomalous moisture stress modulus (AMSM), as an indicator of heavy rainfall presented in this paper, considers the two conditions associated with vertical velocity and anomalous specific humidity in the lower troposphere. Vertical velocity is produced by the orthogonal collision of horizontal anomalous airflows. [ABSTRACT FROM AUTHOR]

The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model's precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms. [ABSTRACT FROM AUTHOR]

This bibliometric analysis dealswith research on the collapse of the Maya civilization--a research topic with a long-lasting history, which has been boosted significantly by recent paleoclimatic research. The study is based on a publication set of 433 papers published between 1923 and 2016. The publications covered by theWeb of Science (WoS) show a significant increase since 1990, reaching about 30 papers per year at present. The results show that the current discourse on the collapse of the Maya civilization is focused on the role of climate as a major factor for the demise of this ancient civilization. The bibliometric analyses also reveal that (1) paleoclimatic records become numerous and are increasingly better dated; (2) the explanatory power of the records has been significantly increased by analyzing samples from regions closer to the relevant Maya sites; and (3) interdisciplinary cooperation of the humanities (archeology, anthropology, history) with natural sciences disciplines (geoscience, ecology, paleoclimatology, meteorology) seems to be highly promising. The collapse of the Maya civilization is a good example of how natural sciences entered research in the humanities and social sciences (anthropology, archeology, history) and boosted research (and solutions) around long-discussed, but unsolved questions. [ABSTRACT FROM AUTHOR]

The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and now finds applications across a wide range of disciplines. This multidisciplinary expansion has impressively demonstrated the potential of digital twin research. While the simulation aspect of a digital twin is often emphasized, the role of artificial intelligence (AI) and machine learning (ML) is severely understudied. For this reason, in this paper, we highlight the pivotal role of AI and ML for digital twin research. By recognizing that a digital twin is a component of a broader Digital Twin System (DTS), we can fully grasp the diverse applications of AI and ML. In this paper, we explore six AI techniques—(1) optimization (model creation), (2) optimization (model updating), (3) generative modeling, (4) data analytics, (5) predictive analytics and (6) decision making—and their potential to advance applications in health, climate science, and sustainability. [ABSTRACT FROM AUTHOR]

The optimal control problems of degenerate parabolic equations have many applications in economics, physics, climatology, and so on. Motivated by the applications, we consider the optimal control problems of a class of nonlinear degenerate parabolic equations in this paper. The main result is that we deduce the first order necessary condition for the optimal control problem of nonlinear degenerate parabolic equations by variation method. Moreover, we investigate the uniqueness of the solutions to the optimal control problems. For the linear equations, we obtain the global uniqueness, while for the nonlinear equations, we obtain only the local uniqueness. Finally, we give a numerical example to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

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]

Soil moisture operational product system (SMOPS) is developed by National Oceanic and Atmospheric Administration (NOAA) to provide the real-time blended soil moisture (SM) for numeric weather prediction and national water model applications. However, all individual satellite SM data ingested into the current operational SMOPS are scaled to global land data assimilation system (GLDAS) 0–10 cm SM climatology before the combination. As a result, the useful information from the original microwave SM retrievals could be lost, and the GLDAS model errors could be brought into the final SMOPS blended product. In this paper, we propose to scale the individual SM retrievals to the soil moisture active passive (SMAP) data through building regression models. The rescaled individual SM data and the SMAP observations then have similar climatology and dynamics, which allows producing the SMOPScdr (distinguishing with the current operational SMOPSopr) data using an equal-weight averaging approach. With respect to the in situ SM measurements, the developed SMOPScdr is more successful tracking the surface SM status than the individual satellite SM products with significantly decreased errors. The proposed method also preserves the climatology of the reference SMAP data for the period when SMAP is not available, allowing us to produce a long-term SMOPScdr data product. [ABSTRACT FROM AUTHOR]

The paper deals with long-term means of 557.7 nm atomic oxygen airglow intensity (OI) and air temperature within the mesopause over the southern regions of East Siberia. Data on temperature and emission parameters were obtained with a SABER radiometer, KEO Scientific "Arinae" Fabry–Pérot interferometer, SATI spectrometer and NRLMSIS model over the Tory Geophysical Observatory (52° N, 103° E). Annual variations of 557.7 nm emission intensity and temperature obtained in observations differ from model approximations. Potential reasons for the discrepancies revealed are discussed. [ABSTRACT FROM AUTHOR]

This essay addresses the long-term effectiveness of urban climate change adaptation approaches, based, inter alia, on work in the C40 city network. We argue that in most cities, the dominant framing of climate risk management almost exclusively focuses on short-term incrementalities and preventive solutions directly tackling hazards, vulnerability, and exposure. This approach has serious flaws, leading to missed opportunities for longer-term sustainable urban development. Until very recently, climate science usually provided only a marginal input to long-term urban planning and design. We argue that any analysis of urban climate risk management and the associated climate services should be broadened beyond solely climate focusing on impacts. In this context, the development of positive urban visions is a key gap for both research and practice. A change is required from negatively addressing risks to positively pursuing a positive vision of attractive, resilient, and sustainable cities. The emphasis on short-term incremental solutions should shift towards long-term transformation. This embodies a paradigm shift from "function follows system" to "system follows function". For many cities, this also means a change in procedural practice from siloed top-down to integrated, participatory urban transformation. Our main argument in this paper is that simple, longer-term sustainable urban transformation would not only reduce climate risks but also enhance overall environmental quality, economic opportunities, and social wellbeing. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel on Climate Change (IPCC), which is the United Nations body for assessing the science related to climate change, has recently recognized the natural carbonation process as a way of carbon offsetting with mortar and concrete. Accordingly, this activity could be recognized as a carbon removal process for which certification should be granted. The aim of the certification of carbon removal is to promote the development of adequate and efficient new carbon removal processes. Therefore, the main objective of this study is to provide reliable results on carbon dioxide uptake by cement-based materials in Spain. Yearly, greenhouse gas emissions are reported to the United Nations Framework Convention on Climate Change (UNFCCC) by each country, and the natural carbonation should be added up to the carbon accounting. Therefore, natural carbonation should be included in the IPCC Guidelines for National Greenhouse Gas Inventories, and such accounting information should be made available promptly to the national regulatory authorities. This paper provides the results of carbon dioxide uptake by Spanish cement-based materials from 1990 to 2020 by using an easy method of estimating the net carbon dioxide emissions (simplified method) considering the carbon dioxide released by the calcination during clinker production (process emissions). The outcome of this study reveals that there was 93,556,000 tons of carbon dioxide uptake by the mortar and concrete manufactured in Spain from 1990 to 2020. [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]

In this paper, a statistical analysis of the diurnal, seasonal and solar cycle variation in the TEC longitudinal difference in midlatitudes of East Asia is presented using CODE GIMs data in 2015–2019. Moreover, the empirical neutral wind model HWM-14 and geomagnetic field model IGRF-2020 were employed to analyze the influence of geomagnetic configuration-neutral wind mechanism on the TEC longitudinal difference, and the F2 layer peak electron density (NmF2) data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) were also used to study the role of local electron density in the TEC longitudinal difference. For the high solar activity year, the results show that east-west TEC longitudinal difference index Re/w is negative in the noon and positive at evening-night. Moreover, the longitudinal difference of daytime TEC is most evident in summer, less in autumn and least in spring and winter, while the nighttime difference is most obvious in equinox, followed by summer and winter during nighttime. The model simulation shows that the TEC longitude difference around noon is mainly caused by the zonal wind-declination mechanism, and a 4-h time delay seems to be an optimal result for the vertical drift velocity to cause the longitudinal TEC difference during pre-noon hours. At night, the uplifting electron flux, which is a product of local electron density and vertical drift velocity, shows a good correlation with Re/w, indicating that the local electron density is also an important factor affecting the TEC longitudinal difference during the nighttime. Moreover, there was about a 3-h time delay between the TEC longitudinal variations and the uplifting electron flux at night. For the low solar activity years, the western TEC is greater than eastern TEC during most of the year except in the summer nighttime. The TEC diurnal variation in the east and west suggested that the nighttime Re/w should be related to other physical process, such as the midlatitude summer nighttime anomaly (MSNA) in the east and the ionospheric nighttime enhancement (INE). The current study provides evidence for the longitudinal difference of NmF2 in East Asian midlatitudes and geomagnetic configuration-neutral wind mechanism proposed in previous studies and finds some new features which need further studying to improve our current understanding of ionospheric longitudinal difference in the low solar activity years. The results provide new insight into TEC longitudinal variations at midlatitudes, and they can contribute to understanding the ionosphere-thermosphere coupling system. [ABSTRACT FROM AUTHOR]

Europe and the Mediterranean are considered climate change hot spots. This is the reason why this paper focuses on the analysis of the trends of essential climate variables in a Mediterranean country, Greece. The analyzed period is 1991–2020, and the dataset used is ERA5-Land (produced by the European Center for Medium-Range Weather Forecasts), which has global coverage and an improved resolution of ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put in evidence during the analyzed period. More specifically, the country averaged a 30-year trend of temperature of +1.5 °C, locally exceeding +2 °C, and this increasing trend is positively correlated with the distance of the areas from the coasts. Accordingly, the number of frost days has decreased throughout the country. In terms of rainfall, a major part of Greece has experienced increasing annual rainfall amounts, while 86% of the Greek area has experienced a positive trend of days with heavy rainfall (>20 mm). Finally, a multiple signal of the trend of consecutive dry days was found (statistically non-significant in the major part of Greece). [ABSTRACT FROM AUTHOR]

This paper addresses the modification of the F-test for count data following the Poisson distribution. The F-test when the count data are expressed in intervals is considered in this paper. The proposed F-test is evaluated using real data from climatology. The comparative study showed the efficiency of the F-test for count data under neutrosophic statistics over the F-test for count data under classical statistics. [ABSTRACT FROM AUTHOR]

The low-lying coastal areas of the countries around the North Sea are exposed to flooding and the influence of sea level rise. The countries in the North Sea Region need to continue to adapt if the associated risk is to be well-managed into the future. In addition to reducing flood risk, adaptation measures can bring development opportunities for those same places. These opportunities, however, are unlikely to be achieved through a 'defence only' paradigm, and instead a new approach is needed that simultaneously reduces risk and promotes liveable places, ecosystem health and social well-being. The building blocks of this new approach are promoted here and are based on an adaptation process that is collaborative and takes a whole-system, long-term perspective. The approach developed through the Interreg funded project, C5a, brings together governments, practitioners and researchers from across the North Sea to share policies, practices and the emerging science of climate change adaptation and enabling sustainable development. The new approach reflects a Cloud to Coast management paradigm and emerged through a combination of knowledge exchange and peer-to-peer learning across seven case studies. Central to the case studies was a maturity analysis of existing capabilities across the North Sea countries and their ability to adopt the new approach. This paper presents the results of this analysis, including the common challenges that emerged and the methods and examples of good practice to overcome them. Building upon these findings, the paper concludes by presenting four priority policy directions to support the uptake of the Cloud to Coast approach. [ABSTRACT FROM AUTHOR]

Typically, storing a two-dimensional wave spectrum could occupy more than one thousand storage units, making saving and reading boundary spectra computationally burdensome in nested wave simulations. This paper proposes a new approach for preservation of a wave spectrum that can reduce the required number of storage units to dozens. Using a corresponding reconstruction approach, the spectrum can then be rebuilt with intact spectral characteristics. Experimental application confirmed that the reconstructed spectra could be adopted as boundary conditions in nested wave modeling. The newly proposed approach for preservation and reconstruction of spectra allows long-term spectral information covering the entire simulated domain to be saved with more acceptable storage consumption, and such information can then be adopted as nesting conditions for nested-child simulations without the limitations of predefined boundaries. The above-mentioned properties of the new method could help support engineering projects concerning wave environments, research focused on wave climatology, and studies associated with wave energy assessment. [ABSTRACT FROM AUTHOR]

The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth's surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe. [ABSTRACT FROM AUTHOR]

X-band weather radar can provide high spatial and temporal resolution data, which is essential to precipitation observation and prediction of mesoscale and microscale weather. However, X-band weather radar is susceptible to precipitation attenuation. This paper presents an X-band attenuation correction method based on the light gradient machine (LightGBM) algorithm (the XACL method), then compares it with the ZH correction method and the ZH-KDP comprehensive correction method. The XACL method was validated using observations from two radars in July 2021, the X-band dual-polarization weather radar at the Shouxian National Climatology Observatory of China (SNCOC), and the S-band dual-polarization weather radar at Hefei. During the rainfall cases on July 2021, the results of the attenuation correction were used for precipitation estimation and verified with the rainfall data from 1204 automatic ground-based meteorological network stations in Anhui Province, China. We found that the XACL method produced a significant correction effect and reduced the anomalous correction phenomenon of the comparison methods. The results show that the average error in precipitation estimation by the XACL method was reduced by 39.88% over 1204 meteorological stations, which is better than the effect of the other two correction methods. Thus, the XACL method proved good local adaptability and provided a new X-band attenuation correction scheme. [ABSTRACT FROM AUTHOR]

In the past two decades, major breakthroughs that improve our understanding of the pathophysiology and therapy of kidney stones (KS) have been lacking. The disease continues to be challenging for patients, physicians, and healthcare systems alike. In this context, epidemiological studies are striving to elucidate the worldwide changes in the patterns and the burden of the disease and identify modifiable risk factors that contribute to the development of kidney stones. Our expanding knowledge of the epidemiology of kidney stones is of paramount importance and largely upgrades the modern management of the disease. In this paper, we review the variables affecting prevalence and incidence, including age, gender, race, ethnicity, occupation, climate, geography, systemic diseases, diabetes, vascular disease, chronic kidney disease, and dietary risk factors relevant to kidney stones. [ABSTRACT FROM AUTHOR]

This paper presents a literature review on urban design indicators addressing the impact of urban geometry and vegetation on the outdoor thermal environment at the pedestrian level, as urban geometry and vegetation have been regarded as the most influential urban design factors that affect outdoor microclimate. The thermal balance concept is first introduced to elaborate how each component of energy fluxes is affected by the urban built environment, which helps to explore the underlying thermophysical mechanisms of how urban design modifies the outdoor thermal environment. The literature on numerous urban design descriptors addressing urban geometric characteristics is categorized into five groups in this paper according to the design features that the parameters entail, including land use intensity, building form, canyon geometry, space enclosure and descriptive characteristics. The literature on urban vegetation descriptors is reviewed together, followed by the combined effect of urban geometry and vegetation. This paper identifies a series of important urban design parameters and shows that the impact of design parameters on thermal environment varies with time, season, local climate and urban contexts. Contradictory impacts often occur between daytime and nighttime, or different seasons, which requests trade-offs to be achieved when proposing design strategies. [ABSTRACT FROM AUTHOR]

Given the need to prevent food fraud within the international food supply chain and the current lack of research on food integrity, in this paper, the relation between the organizational food integrity climate and employees' food integrity behavior is examined to understand the role of the individual or psychological dimension in food integrity. The construct of food integrity behavior was introduced and defined, and the conceptual model of the food integrity climate in relation to food integrity behavior was elaborated along with study variables and hypotheses. In the proposed model, the potential moderating role of employees' psychological well-being (i.e., burnout and job stress) was analyzed, and two mediating variables were also proposed (i.e., knowledge and motivation) which both could explain how the prevailing food integrity climate might influence employees' food integrity behavior. Data was collected through convenience sampling in four Belgian food companies with a total of 118 participating employees through a self-assessment questionnaire. Based on the statistical analysis, it was concluded that a well-developed organizational food integrity climate promotes positive employees' food integrity behavior. Specifically, results of this semi-quantitative study demonstrated that the companies' food integrity climate is positively related to the employees' food integrity behavior both directly and indirectly, and that food integrity knowledge is a partial mediator in the relation between food integrity climate and food integrity behavior, while food integrity motivation is a full mediator. Study limitations and implications are also discussed. [ABSTRACT FROM AUTHOR]

The GRACE Follow-On satellite mission measures distance variations between its two satellites in order to derive monthly gravity field maps, indicating mass variability on Earth on a scale of a few 100 km originating from hydrology, seismology, climatology and other sources. This mission hosts two ranging instruments, a conventional microwave system based on K(a)-band ranging (KBR) and a novel laser ranging instrument (LRI), both relying on interferometric phase readout. In this paper, we show how the phase measurements can be converted into range data using a time-dependent carrier frequency (or wavelength) that takes into account potential intraday variability in the microwave or laser frequency. Moreover, we analyze the KBR-LRI residuals and discuss which error and noise contributors limit the residuals at high and low Fourier frequencies. It turns out that the agreement between KBR and LRI biased range observations can be slightly improved by considering intraday carrier frequency variations in the processing. Although the effect is probably small enough to have little relevance for gravity field determination at the current precision level, this analysis is of relevance for detailed instrument characterization and potentially for future more precise missions. [ABSTRACT FROM AUTHOR]

Cyanobacteria blooms have been reported to be increasing worldwide. In addition to potentially causing major economic and ecological damage, these blooms can threaten human health. Furthermore, these blooms can be exacerbated by a warming climate. One approach to monitoring and modeling cyanobacterial biomass is to use processed satellite imagery to obtain long-term data sets. In this paper, an existing algorithm for estimating cyanobacterial biomass previously developed for MERIS is validated for Green Bay using cyanobacteria biovolume estimates obtained from field samples. Once the algorithm was validated, the existing MERIS imagery was used to determine the bloom phenology of the cyanobacterial biomass in Green Bay. Modeled datasets of heat flux (as a proxy for stratification), wind speed, water temperature, and gelbstoff absorption along with in situ river discharge data were used to separate bloom seasons in Green Bay from bloom seasons in nearby cyanobacteria bloom hotspots including western Lake Erie and Saginaw Bay. Of the ten-year MERIS dataset used here, the highest five years were considered "high bloom" years, and the lowest five years from biomass were considered "low bloom" years and these definitions were used to separate Green Bay. Green Bay had a strong relationship with gelbstoff absorption making it unique among the water bodies, while western Lake Erie responded strongly with river discharge as previously reported. Saginaw Bay, which has low interannual bloom variability, did not exhibit a largely influential single parameter. [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]

Certain wind turbine maintenance tasks require specialist equipment, such as a large crane for heavy lift operations. Equipment hire often has a lead time of several weeks but equipment use is restricted by future weather conditions through wind speed safety limits, necessitating an assessment of future weather conditions. This paper sets out a methodology for producing subseasonal-to-seasonal (up to 6 weeks ahead) forecasts that are site- and task-specific. Forecasts are shown to improve on climatology at all sites, with fair skill out to six weeks for both variability and weather window forecasts. For the case of crane hire, a cost-loss model identifies the range of electricity prices where the hiring decision is sensitive to the forecasts. While there is little difference in the hiring decision made by the proposed forecasts and the climatology benchmark at most electricity prices, the repair cost per turbine is reduced at lower electricity prices. [ABSTRACT FROM AUTHOR]

Optically thin layers of tiny ice particles near the summer mesopause, known as noctilucent clouds, are of significant interest within the aeronomy and climate science communities. Ground-based optical cameras mounted at various locations in the arctic regions collect the dataset during favorable summer times. In this paper, first, we compare the performances of various deep learning-based image classifiers against a baseline machine learning model trained with support vector machine (SVM) algorithm to identify an effective and lightweight model for the classification of noctilucent clouds. The SVM classifier is trained with histogram of oriented gradient (HOG) features, and deep learning models such as SqueezeNet, ShuffleNet, MobileNet, and Resnet are fine-tuned based on the dataset. The dataset includes images observed from different locations in northern Europe with varied weather conditions. Second, we investigate the most informative pixels for the classification decision on test images. The pixel-level attributions calculated using the guide back-propagation algorithm are visualized as saliency maps. Our results indicate that the SqueezeNet model achieves an F1 score of 0.95. In addition, SqueezeNet is the lightest model used in our experiments, and the saliency maps obtained for a set of test images correspond better with relevant regions associated with noctilucent clouds. [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]

As clean, renewable energy, photovoltaic (PV) energy can reduce the ozone-layer loss and climate deterioration caused by the use of traditional types of energy to generate electricity. At present, most PV energy products involve the influence of cloud cover on solar radiation. However, the resolution and precision of most cloud cover data are not fine enough to reflect the actual cloud distribution in local areas. This leads to incorrect distribution results of PV energy in areas with high-spatial-variability clouds. Using high-resolution and high-precision cloud cover data obtained by satellite remote sensing to estimate the distribution of PV energy can solve this problem. In this study, the Global Land High-Resolution Cloud Climatology (GLHCC), a 10-day cloud frequency product with a resolution of 1 km and located in China, was used to construct a cloud-based solar radiation estimation model. Using the inverse relationship between cloud cover and solar radiation, the GLHCC was converted into sunshine percentage data. Using meteorological station data in China, a Least Squares Fit (LSF) and error check were carried out on the A-P, Lqbal, Bahel and Sen Models to determine the optimal solar radiation estimation model (Sen Model). Based on the sunshine percentage data, the Sen Model and terrain shielding factors, the distribution of PV energy in China was estimated. Finally, comparing to the Global Horizontal Irradiance (GHI) of the World Bank and the yearly average global irradiance of the Photovoltaic Geographic Information System (PVGIS), PV energy data in this paper more accurately reflected the distribution of PV energy in China, especially in areas with high-spatial-variability clouds. [ABSTRACT FROM AUTHOR]

Climate science as a data-intensive subject has overwhelmingly affected by the era of big data and relevant technological revolutions. The big successes of big data analytics in diverse areas over the past decade have also prompted the expectation of big data and its efficacy on the big problem--climate change. As an emerging topic, climate change has been at the forefront of the big climate data analytics implementations and exhaustive research have been carried out covering a variety of topics. This paper aims to present an outlook of big data in climate change studies over the recent years by investigating and summarising the current status of big data applications in climate change related studies. It is also expected to serve as a one-stop reference directory for researchers and stakeholders with an overview of this trending subject at a glance, which can be useful in guiding future research and improvements in the exploitation of big climate data. [ABSTRACT FROM AUTHOR]

In this paper, we provide a novel Bayesian solution to forecasting extreme quantile thresholds that are dynamic in nature. This is an important problem in many fields of study including climatology, structural engineering, and finance. We utilize results from extreme value theory to provide the backdrop for developing a state-space model for the unknown parameters of the observed time-series. To solve for the requisite probability densities, we derive a Rao-Blackwellized particle filter and, most importantly, a computationally efficient, recursive solution. Using the filter, the predictive distribution of future observations, conditioned on the past data, is forecast at each time-step and used to compute extreme quantile levels. We illustrate the improvement in forecasting ability, versus traditional methods, using simulations and also apply our technique to financial market data. [ABSTRACT FROM AUTHOR]

The urban climatology consists not only of the urban canopy temperature but also of wind regime and boundary layer evolution among other secondary variables. The energetic input and response of urbanized areas is rather different to rural or forest areas. In this paper, we outline the physical characteristics of the urban canopy that make its energy balance depart from that of vegetated areas and change local climatology. Among the several canopy characteristics, we focus on the aspect ratio h / d and its effects. The literature and methods of retrieving meteorological quantities in urban areas are reviewed and a number of physical analyzes from conceptual or numerical models are presented. In particular, the existence of a maximum value for the urban heat island intensity is discussed comprehensively. Changes in the local flow and boundary layer evolution due to urbanization are also discussed. The presence of vegetation and water bodies in urban areas are reviewed. The main conclusions are as follows: for increasing h / d , the urban heat island intensity is likely to attain a peak around h / d ≈ 4 and decrease for h / d > 4 ; the temperature at the pedestrian level follows similar behavior; the urban boundary layer grows slowly, which in combination with low wind, can worsen pollution dispersion. [ABSTRACT FROM AUTHOR]

Water, energy, food, land and climate form a tightly-connected nexus in which actions on one sector impact other sectors, creating feedbacks and unanticipated consequences. This is especially because at present, much scientific research and many policies are constrained to single discipline/sector silos that are often not interacting (e.g., water-related research/policy). However, experimenting with the interaction and determining how a change in one sector could impact another may require unreasonable time frames, be very difficult in practice and may be potentially dangerous, triggering any one of a number of unanticipated side-effects. Current modelling often neglects knowledge from practice. Therefore, a safe environment is required to test the potential cross-sectoral implications of policy decisions in one sector on other sectors. Serious games offer such an environment by creating realistic 'simulations', where long-term impacts of policies may be tested and rated. This paper describes how the ongoing (2016-2020) Horizon2020 project SIM4NEXUS will develop serious games investigating potential plausible cross-nexus implications and synergies due to policy interventions for 12 multi-scale case studies ranging from regional to global. What sets these games apart is that stakeholders and partners are involved in all aspects of the modelling definition and process, from case study conceptualisation, quantitative model development including the implementation and validation of each serious game. Learning from playing a serious game is justified by adopting a proof-of-concept for a specific regional case study in Sardinia (Italy). The value of multi-stakeholder involvement is demonstrated, and critical lessons learned for serious game development in general are presented. [ABSTRACT FROM AUTHOR]

Preserving hydrological variability is important when developing environmental flow regimes, and a number of tools have been developed to support this process. A commonly applied method is the index of hydrological alteration (IHA), which describes a set of indices that can be used to assess changes in flow regimes. In cold climate regions, river ice can have large effects on flow regimes through frazil and anchor ice formation, ice cover formation, and ice break-up, and the impact of this is usually not included in the commonly used indexes. However, to understand the effect of ice formation and the break-up on the flow regime, the ice effects on the hydrology should be considered when assessing winter alteration indexes. This paper looks at the effects of river ice on winter flow conditions using data from Norwegian rivers, and discusses these effects in relation to hydrological variability. This paper also shows how indexes can be used to classify ice-induced variability, how this should be used to avoid ice-induced effects in the current analysis, and how this can be combined with the current indices to improve the winter flow regime classification. The findings from this paper show that frazil- and anchor-induced raises of the water level have a large impact on the perceived flow in winter, producing higher flow and deeper water than what the open water conditions discharge could do. Corresponding to this, winter lows connected to ice-induced high flows at other locations are also common. Finally, issues related to the assessment of the temporal and spatial effects of ice formation are discussed. [ABSTRACT FROM AUTHOR]

Simple Summary: European Union (EU) legislation states that the routine tail docking of pigs should not be carried out and that manipulable materials should be made available to all pigs to prevent tail biting and allow them to behave naturally. However, between 90 and 95% of pigs within the EU still have their tails docked to avoid the risk of tail biting. Farmers say they require information tailored to their particular production systems before they abandon this practice. In this study, four types of enrichment materials used in Spanish pig fattening production systems are compared. Most of these systems have fully slatted floors and high external temperatures for considerable periods of the year. The effects of chains (the control group), wood, paper or straw in a rack on the behaviour, health/physiology, performance and meat and carcass quality are evaluated. Straw in a rack was found to be the best material to meet the behavioural needs of pigs, whereas paper met the criteria of being manipulable, but only for a short period. To avoid the risk of blockages in the slurry system, there are some practical issues to consider and improvements to be made to the design of the rack for providing straw used in this study. Some positive effects regarding the use of enrichment material on the stimulation of pig exploration and a reduction in redirected behaviour was reported. This study aims to evaluate the effects of four enrichment materials on the behaviour, physiology/health, performance and carcass and meat quality in pigs kept in Spanish production conditions. Ninety-six male pigs (six pigs/pen) ranging from 70 to 170 days old were used. Chains were used for the control group (CH), and wooden logs (W), straw in a rack (S) or paper (P) were also used. The pigs were subjected to two pre-slaughter treatments: 0 or 12 h of fasting. Their behaviour was observed for 12 weeks using scan and focal sampling. Samples of the Neutrophil: Lymphocyte (N:L) ratio and lactate were obtained from the pigs at 66 and 170 days old. Saliva samples for Chromogranin-A (CgA) were obtained at 67, 128, 164 and 170 days old. The weight, skin lesions and feed intake of the pigs were recorded. S triggered more exploratory behaviour than W and CH (P < 0.001). Skin lesions and redirected behaviour were lower for pigs with S (P < 0.01 and P < 0.05, respectively). The pigs offered S presented lower CgA after no fasting than pigs with P or CH (P = 0.055). Lactate was higher in pigs with W and CH treatments, regardless of fasting (P < 0.05). The N:L ratio increased over time (P < 0.05). No other significant effects were found. Overall, straw in a rack was the enrichment material that enhanced pig inherent behaviour. [ABSTRACT FROM AUTHOR]

The so-called urban heat islands (UHI) is a thermal phenomenon characterized by higher air temperatures in the urban area than in rural surroundings. Vernacular passive strategies such as courtyards are proved to be useful to generate specific microclimates, especially in the warmer regions of the Earth. Courtyards increase the porosity of the cities, understanding porosity as building voids. Accordingly, their study will be fundamental in reducing the UHI effect by generating urban cooling microislands. This paper aims to analyze two passive strategies capable of modifying the thermal effect of radiation inside the courtyard of two school buildings: albedo and vegetation. In this regard, two case studies were assessed, both of them located in the city of Seville. Results show that the temperature in these spaces can vary up to 7 °C depending on the albedo, which confirms the importance of detecting an optimal albedo factor. In addition, data showed a significant increase in the thermal delta (TD), courtyard versus outdoor temperature, after the installation of a vegetal facade. Accordingly, both strategies will be fundamental in locations affected by climate change, especially considering that they are not only effective cooling strategies but also relatively easy to implement in the building's refurbishment process. [ABSTRACT FROM AUTHOR]

Monitoring soil moisture dynamics from local to global scales is essential for a wide range of applications. The field of remote sensing of soil moisture has expanded greatly and the first dedicated soil moisture satellite missions (SMOS, SMAP) were launched, and new missions, such as SENTINEL-1 provide long-term perspectives for land surface monitoring. This special issue aims to summarize the recent advances in soil moisture estimation from remote sensing, including recent advances in retrieval algorithms, validation, and applications of satellite-based soil moisture products. Contributions in this special issue exploit the estimation of soil moisture from both microwave remote sensing data and thermal infrared information. The validation of satellite soil moisture products can be very challenging, due to the different spatial scales of in situ measurements and satellite data. Some papers present validation studies to quantify soil moisture uncertainties. On the other hand, soil moisture downscaling schemes and new methods for soil moisture retrieval from GPS are also addressed by some contributions. Soil moisture data are used in fields like agriculture, hydrology, and climate sciences. Several studies explore the use of soil moisture data for hydrological application such as runoff prediction. [ABSTRACT FROM AUTHOR]

Polar stratospheric clouds (PSCs) play a crucial role in ozone depletion in the polar stratosphere. In this study, the space-based PSCs record from CALISPO and an offline three-dimensional chemical transport model (SLIMCAT) are used to analyze the PSCs in the Arctic and the Antarctic for the period 2006−2021. Observations indicate that the seasonal evolution of the Antarctic PSC area is similar from year to year. In contrast, the Arctic PSCs show large differences in seasonal variations of coverage and duration in different years. The SLIMCAT simulations effectively capture the seasonal and interannual variations of PSCs. However, the simulated PSC areas are larger than CALIPSO observations, which can be attributed to the relatively high instrumental detection threshold of CALIPSO. SLIMCAT can capture the zonal asymmetry of PSCs in both the Antarctic and Arctic, and it can reproduce a more accurate spatial distribution of PSCs when the PSC coverage area is larger. In addition, accurate simulation of HNO3 is important for PSC simulation. Because the simulation of denitrification processes is poor in SLIMCAT, which uses the thermodynamic equilibrium PSC scheme, the PSCs modeled by SLIMCAT are located at higher altitudes compared to the observation in the Antarctic, where the denitrification processes are strong. In contrast, for ice PSCs of which HNO3 is not required in calculations and the Arctic where denitrification is weak, the simulated PSC at different altitudes closely matches the observations. [ABSTRACT FROM AUTHOR]

Climate conditions affect buildings' performance and durability. The purpose of this paper is to examine the influence of climate conditions on roof deficiencies. 763 cases of such deficiencies were analyzed in this regard. Once the construction deficiencies were quantified, they were characterized from a climatological point of view and their 'climate location segments' were studied to obtain 'ranges of concentration of anomalies' according to the obtained percentage. A direct relation is shown to exist between the location of the building (latitude, situation, type of climate, precipitation, thermal demands, and average wind speed) and a greater or smaller concentration of deficiencies found in both flat and pitched buildings. It was also found that an annual average wind speed greater than 3 m/s increases the appearance of deficiencies in roofs. A higher prevalence of deficiencies was also found in those geographical zones with a thermal demand of 1800–2800 heating degree days or 450–700 cooling degree days. It was found that a higher percentage of construction deficiencies are concentrated in buildings located in the northern coastal climate segments of Spain. With these results, technicians will be able to take more appropriate precautions during both the building process and the use and maintenance phase. [ABSTRACT FROM AUTHOR]

This paper describes how Earth Observation (EO) data--in particular from satellites--can support climate science, monitoring, and services by delivering global, repetitive, consistent, and timely information on the state of the environment and its evolution. Some examples are presented of EO demonstration pilot projects performed in partnership with scientists, industry, and development practitioners to support climate science, adaptation, mitigation, and disaster risk management. In particular, the paper highlights the challenge of gathering observations and generating long-term climate data records, which provide the foundation of risk management. The paper calls for a science-based integrated approach to climate risk management supported by data and knowledge, providing decision-makers with a unique analytical lens to develop a safety net to risk and maximize opportunities related to climate change and variability. [ABSTRACT FROM AUTHOR]

This paper is dealing with mechanisms that can accelerate the global diffusion of climate-friendly technologies. The accelerated diffusion of low-carbon technology innovation can possibly be achieved by interactive processes such as: (1) mutually reinforcing cycles of policy-induced domestic market growth, innovation, and policy feedback; (2) lead markets and political lesson-drawing, the reinforced international adoption of innovations from pioneer countries; and (3) interaction between the vertical and horizontal dynamics in multi-level systems of governance. The three mechanisms are not exclusive. They can overlap and reinforce each other. After a theoretical introduction they will be described. The empirical focus is on the European system of multi-level climate governance. The paper draws some final conclusions for policy makers. [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]

Urban sustainability has been connected to form and compactness of the urban tissue. At the same time the relationship between urban form and energy efficiency is strongly affected by climate. This paper investigates the effect of climate conditions on the relation between urban morphology and energy efficiency of urban blocks, focusing on the Greek city context. A set of building block typologies is analyzed with regard to their form factors such as S/V ratio, coverage ratio and building ratio for the climatic conditions of two cities, each one belonging to a different climatic zone. Heating and cooling loads are calculated at an urban block scale for the climate of the city of Thessaloniki (zone C) and of the city of Heraklion (zone A) in order to draw conclusions about the relation between geometry factors and energy efficiency. The results of the research indicate that there is a strong relationship between urban morphology factors and energy efficiency and that the total load demand of urban blocks can be described as a function of form parameters. Results of the research, concerning the energy demand calculation, are valuable since they indicate the energy profile of each typology according to climate and can be used for defining different urban strategies towards sustainability in a context-based climate dependent analysis. [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]

Three-dimensional water vapor can be reconstructed from Global Navigation Satellite System (GNSS) observations, which can study 3-D profile variations of atmospheric water vapor and climate. However, there is a large uncertainty of water vapor tomography from single GPS system observations due to limited satellites. The rapid development of multi-GNSS, including China's Beidou Navigation Satellite System (BDS) and Russia's GLONASS, has greatly improved the geometric distribution of satellite ray-path signals, which may improve the performance of water vapor tomography by combining multi-GNSS. In this paper, 3-D water vapor tomography results are the first time obtained using multi-GNSS data from Continuously Operating Reference Stations (CORS) network inWuhan, China, whose performances are validated by radiosonde and the latest ECMWF ERA5 reanalysis products. The results show that the integrated multi-GNSS can pronouncedly increase the number of effective signals, and 3-D water vapor results are better than those from the GPS-only system, improving by 5% with GPS + GLONASS or GPS + GLONASS + BDS, while BDS has results that are not improved too much. Therefore, multi-GNSS will enhance the reliability and accuracy of 3-D water vapor tomography, which has more potential applications in the future. [ABSTRACT FROM AUTHOR]

Satellite-based rainfall products have extensive applications in global change studies, but they are known to contain deviations that require comprehensive verification at different scales. In this paper, we evaluated the accuracies of two high-resolution satellite-based rainfall products: the Tropical Rainfall Measurement Mission (TRMM) rainfall product 3B42V7 and the Climate Prediction Center morphing (CMORPH) technique from January 2010 to December 2011 in Shanghai, by using categorical metrics (Probability of Detection, False Alarm Ratio, and Critical Success Index) and statistical indicators (Mean Absolute Error, Root Mean Square Error, Relative Bias, and Correlation Coefficient). Our findings show that, firstly, CMORPH data has a higher accuracy than 3B42V7 at the daily scale, but it underestimates the occurrence frequency of daily rainfall for some intensity ranges. Most errors of the two products are distributed between −10 and 10 mm/day. Second, at the monthly scale, the total accuracy of 3B42V7 is higher than CMORPH in terms of the value of the Correlation Coefficient (CC) and Relative Bias (RB). Finally, CMORPH brings about daily rainfall detection results from categorical metrics computation better than 3B42V7. Generally, the two satellite-based rainfall products show a high correlation with rain gauge data in Shanghai, particularly in spring and winter. Unfortunately, in summer, both of them do not perform well in detecting the short-duration heavy rainfall events. Overall, the relatively poor data accuracy has limited their further applications in Shanghai and similar urban areas. [ABSTRACT FROM AUTHOR]