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We describe a method for quantifying the contribution of climate change to local monthly, seasonal, and annual mean temperatures for locations where long observational temperature records are available. The method is based on estimating the change in the monthly mean temperature distribution due to climate change using CMIP6 (Coupled Model Intercomparison Project Phase 6) model data. As a case study, we apply the method to the record‐warm September 2023 in Helsinki, and then briefly examine all record‐warm months of the 21st century. Our results suggest that climate change made the record‐warm September in Helsinki 9.4 times more likely and 1.4°C warmer. Thus, the new monthly mean record in September 2023 would probably not have been set without the observed global warming. The presented and provided tool allows operational meteorologists and climatologists to monitor and report the impact of climate change on local temperatures in near real time. [ABSTRACT FROM AUTHOR]

Science can offer solutions to a wide range of societal problems. Key to capitalizing on such solutions is the public's trust and willingness to grant influence to scientists in shaping policy. However, previous research on determinants of trust is limited and does not factor in the diversity of scientific occupations. The present study (N = 2,780; U.S. participants) investigated how four well-established dimensions of social evaluations (competence, assertiveness, morality, warmth) shape trust in 45 types of scientists (from agronomists to zoologists). Trust in most scientists was relatively high but varied considerably across occupations. Perceptions of morality and competence emerged as the most important antecedents of trust, in turn predicting the willingness to grant scientists influence in managing societal problems. Importantly, the contribution of morality (but not competence) varied across occupations: Morality was most strongly associated with trust in scientists who work on contentious and polarized issues (e.g., climatologists). Therefore, the diversity of scientific occupations must be taken into account to more precisely map trust, which is important for understanding when scientific solutions find their way to policy. [ABSTRACT FROM AUTHOR]

Climate change is a complex phenomenon that affects all socio-environmental systems, manifesting itself uniquely in different regions. To comprehensively understand and project the extent of its impact, it is crucial to engage in a collaborative effort involving specialists from various disciplines. The international scientific community has made significant progress in developing diverse datasets for studying climate variability and change, along with the formulation of suitable methodologies for their analysis. However, there is a tendency within certain disciplines to rely solely on a single source of climate data, either for the sake of simplicity or due to its compatibility with desired resolution or availability requirements. In this context, climatologists express their apprehension regarding the uncritical utilization of climate databases. It is from this concern that the present article aims to provide a comprehensive description of the scope and limitations associated with the available databases. Furthermore, the article addresses the issue of uncertainty in climate projections and offers guidance on how to effectively employ climate data in conducting experiments pertaining to species distribution, while considering the inherent uncertainty associated with such data. Emphasis is placed on the significance of conducting multiple experiments utilizing independent climate projections, as well as utilizing statistical tools to draw conclusions based on a range of potential solutions. By adopting this approach, researchers can more effectively assess the impact of climate change and its implications for species distribution patterns. [ABSTRACT FROM AUTHOR]

Urban climatologist particularly those interested in Urban Heat Island (UHI), require some form of explanations to UHI variations at both spatial and temporal scales in cities. Temperature cooling and warming rate can be use as a form of explanations for spatial and temporal variations for UHI intensity characteristics of an area. This study therefore, assessed variations in temperature warming and cooling rates in Jalingo. The study used temperature data collected at six locations representing six different thermal climate zones in the study area. Temperature data were collected for the period of 90 days thirty days in each of rainy season, dry season, and hamattan period. Simple statistical analysis was performed to determine the warming and cooling rates. The results indicate that temperature warm and cool differently in the study area. The results also revealed that general warming in the area within the study period begins at 8:00 h local time (GMT +1) with warming rate ranging from 0.94℃ to 1.75℃ across locations with a mean of 1.30℃. Cooling starts at 15:00 h ranging from -0.88℃ to -1.84℃ with an average of -1.48℃. It is recommended that environmental planners particularly the urban planners and Architectures should take into considerations the warming and cooling rates in their building design and also embrace appropriate landscaping to improve thermal comfort. [ABSTRACT FROM AUTHOR]

Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies. [ABSTRACT FROM AUTHOR]

In this research, patterning of rainstorm (more than 10 mm) was conducted by instability indices in Ahvaz. At first, rainfall data from 2000 to 2015 was extracted and statistically examined. Instability indices for rainy days were calculated by the Skew-T diagram. Then, patterning was done by using hierarchical clustering, Ward method, and Euclidean distance. As the sample, one day was selected from each cluster and was synoptically analyzed. The results revealed 60 rainstorms for the respective period. More rainstorms occurred in January and December. Autumn and winter had the most frequent days of rainstorm, while it did not occur in the summer. The results of classification divided rainstorms into 4 patterns and more days were in the fourth class, while the least was in the second class. In the second and fourth classes, instability indices were severe and could predict possible rainstorms, but the first and third classes couldn't predict because synoptic systems caused the occurrence of the rainstorm. In the second and fourth classes, rainstorms were convectional. The synoptic analysis showed that every time rainstorm occurred in Ahvaz, a deep trough at 500 hPa was formed in the East Mediterranean and the area was in front of it. Also, at sea level pressure, a low-pressure system formed in Iraq and winds got humid by passing through the Persian Gulf and entered into the atmosphere of Ahvaz. Due to the unstable atmosphere, the air would rise to heights causing rainstorm. [ABSTRACT FROM AUTHOR]

For more than two decades, the Global Positioning System (GPS) under a method called GPS meteorology, has been providing valuable products and parameters for meteorologists and climatologists in addition to its main purpose, which is positioning. GPS meteorology can be used in both space-based and ground-based modes. The space-based approach, called GPS Radio Occultation (RO), is used to provide the profiles of refractivity, temperature, pressure, and water vapor pressure in a neutral atmosphere and electron density in the ionosphere. However, ground-based GPS meteorology is utilized to estimate the tropospheric delay of the GPS signals and Precipitable Water Vapor (PWV) value. To date, GPS RO profiles have been used in several researches to study ionosphere and troposphere layers in Iran. However, no studies have yet used these data to estimate and evaluate PWV. In this study, GPS RO profiles were used to calculate and evaluate PWV over the study area. For statistical comparison, ground-based PWV (GB PWV) estimates in 41 stations in the study region have been considered reliable values. After selecting the pair of PWV values obtained from the space-based and ground-based GPS meteorology in the region, statistical parameters were extracted. In general, the results showed that the GPSRO PWV values have 80% correlation with the corresponding values obtained from the ground-based method. The average and RMSE of the GB-GPSRO PWV differences in the region were estimated at 3 mm and 5.2 mm, respectively. Also, the effective parameters on the accuracy of GPSRO PWV values such as seasonal changes, the position of stations, the difference in height of the lowest point of the GPS RO profile from the ground (dh), and the horizontal distance between the profile and the ground station were examined. The correlation of GPSRO PWV and GB PWV for winter, spring, summer, and autumn seasons were estimated at 0.75, 0.72, 0.73, and 0.85, respectively. The reason for the greater correlation between these two methods in the cold seasons of the year can be attributed to the lower variation of PWV values in these seasons. After sensitivity analysis of the factors considered in relation to the quality of GPSRO PWV values, statistical comparison between GB and GPS RO methods was performed using new conditions. The results showed that with dh <500m condition, the MBE and RMSE of GPSRO PWV compare to ground-based method decreased by about 50% and 25%, respectively, and the correlation between these two methods improved by 5%. [ABSTRACT FROM AUTHOR]

The winter 1788/89 was one of the coldest winters Europe had witnessed in the past 300 years. Fortunately, for historical climatologists, this extreme event occurred at a time when many stations across Europe, both private and as part of coordinated networks, were making quantitative observations of the weather. This means that several dozen early instrumental series are available to carry out an in-depth study of this severe cold spell. While there have been attempts to present daily spatial information for this winter, there is more to be done to understand the weather variability and day-to-day processes that characterised this weather extreme. In this study, we seek to reconstruct daily spatial high-resolution temperature and sea level pressure fields of the winter 1788/89 in Europe from November through February. The reconstruction is performed with an analogue resampling method (ARM) that uses both historical instrumental data and a weather type classification. Analogue reconstructions are then post-processed through an ensemble Kalman fitting (EnKF) technique. Validation experiments show good skill for both reconstructed variables, which manage to capture the dynamics of the extreme in relation to the large-scale circulation. These results are promising for more such studies to be undertaken, focusing on different extreme events and other regions in Europe and perhaps even further back in time. The dataset presented in this study may be of sufficient quality to allow historians to better assess the environmental and social impacts of the harsh weather. [ABSTRACT FROM AUTHOR]

The generation of index-based series of meteorological phenomena, derived from narrative descriptions of weather and climate in historical documentary sources, is a common method to reconstruct past climatic variability and effectively extend the instrumental record. This study is the first to explicitly examine the degree of inter-rater variability in producing such series, a potential source of bias in index-based analyses. Two teams of raters were asked to produce a five-category annual rainfall index series for the same dataset, consisting of transcribed narrative descriptions of meteorological variability for 11 "rain years" in nineteenth-century Lesotho, originally collected by Nash and Grab (2010). One group of raters (n = 71) was comprised of students studying for postgraduate qualifications in climatology or a related discipline; the second group (n = 6) consisted of professional meteorologists and historical climatologists working in southern Africa. Inter-rater reliability was high for both groups at r = 0.99 for the student raters and r = 0.94 for the professional raters, although ratings provided by the student group disproportionately averaged to the central value (0: normal/seasonal rains) where variability was high. Back calculation of intraclass correlation using the Spearman–Brown prediction formula showed that a target reliability of 0.9 (considered "excellent" in other published studies) could be obtained with as few as eight student raters and four professional raters. This number reduced to two when examining a subset of the professional group (n = 4) who had previously published historical climatology papers on southern Africa. We therefore conclude that variability between researchers should be considered minimal where index-based climate reconstructions are generated by trained historical climatologists working in groups of two or more. [ABSTRACT FROM AUTHOR]

Climate change has contributed substantially to the weather and land characteristic phenomena. Accurate time series forecasting for climate and land parameters is highly essential in the modern era for climatologists. This paper provides a brief introduction to the algorithm and its implementation in Python. The pattern-sequence-based forecasting (PSF) algorithm aims to forecast future values of a univariate time series. The algorithm is divided into two major processes: the clustering of data and prediction. The clustering part includes the selection of an optimum value for the number of clusters and labeling the time series data. The prediction part consists of the selection of a window size and the prediction of future values with reference to past patterns. The package aims to ease the use and implementation of PSF for python users. It provides results similar to the PSF package available in R. Finally, the results of the proposed Python package are compared with results of the PSF and ARIMA methods in R. One of the issues with PSF is that the performance of forecasting result degrades if the time series has positive or negative trends. To overcome this problem difference pattern-sequence-based forecasting (DPSF) was proposed. The Python package also implements the DPSF method. In this method, the time series data are first differenced. Then, the PSF algorithm is applied to this differenced time series. Finally, the original and predicted values are restored by applying the reverse method of the differencing process. The proposed methodology is tested on several complex climate and land processes and its potential is evidenced. [ABSTRACT FROM AUTHOR]

Birch belongs to the most important allergenic taxa in Europe, therefore information on the start dates of the pollen season is very important for allergists and their patients as well as for climatologists. The study examined changes in the start of the birch pollen season as well as determined the trend of these changes. Pollen monitoring was performed in Lublin (eastern Poland) in the period 2001–2019 using the volumetric method. The Makra-test was used to detect periods with significantly higher or lower average of the onset than the average for the whole dataset. Two significant falls in the average of the pollen season start were found in 2007 and 2014. Besides, taking into account the 2-3-year rhythm of high and low concentrations of birch pollen in the atmospheric air, linear trends were fitted for the subsets of high and low abundance seasons. Significant changes in Betula pollen season start dates were only determined for the highly abundance seasons, while the results for seasons with a low concentration did not allow rejecting the hypothesis about the lack of a linear trend in the changes in the studied parameter. Moreover, a significant polynomial relationship was found between the beginning of a pollen season and the average values of monthly temperatures preceded a season. These analyses show that the start dates of the Betula pollen season are getting significantly earlier. The dynamics of changes differ between seasons with high and low concentrations of pollen. [ABSTRACT FROM AUTHOR]

Narrative evidence contained within historical documents and inscriptions provides an important record of climate variability for periods prior to the onset of systematic meteorological data collection. A common approach used by historical climatologists to convert such qualitative information into continuous quantitative proxy data is through the generation of ordinal-scale climate indices. There is, however, considerable variability in the types of phenomena reconstructed using an index approach and the practice of index development in different parts of the world. This review, written by members of the PAGES (Past Global Changes) CRIAS working group – a collective of climate historians and historical climatologists researching Climate Reconstructions and Impacts from the Archives of Societies – provides the first global synthesis of the use of the index approach in climate reconstruction. We begin by summarising the range of studies that have used indices for climate reconstruction across six continents (Europe, Asia, Africa, the Americas, and Australia) as well as the world's oceans. We then outline the different methods by which indices are developed in each of these regions, including a discussion of the processes adopted to verify and calibrate index series, and the measures used to express confidence and uncertainty. We conclude with a series of recommendations to guide the development of future index-based climate reconstructions to maximise their effectiveness for use by climate modellers and in multiproxy climate reconstructions. [ABSTRACT FROM AUTHOR]

Editor's Note: A version of this obituary first appeared online in the CMOS Bulletin. Morley Thomas, affectionately known as Canada's Mr. Climatology, died on March 31, 2018 in Watford, Ontario, [...]

State climatologists and other expert drought observers have speculated about the value of monitoring Twitter for #drought and related hashtags. This study statistically examines the relationships between the rate of tweeting using #drought and related hashtags, within states, accounting for drought status and news coverage of drought. We collected and geolocated tweets, 2017-18, and used regression analysis and a diversity statistic to explain expected and identify unexpected volumes of tweets. This provides a quantifiable means to detect state-weeks with a volume of tweets that exceeds the upper limit of the prediction interval. To filter out instances where a high volume of tweets is related to the activities of one person or very few people, a diversity statistic was used to eliminate anomalous state-weeks where the diversity statistic did not exceed the 75th percentile of the range for that state's diversity statistic. Anomalous state-weeks in a few cases preceded the onset of drought but more often coincided with or lagged increases in drought. Tweets are both a means of sharing original experience and a means of discussing news and other recent events, and anomalous weeks occurred throughout the course of a drought, not just at the beginning. A sum-to-zero contrast coefficient for each state revealed a difference in the propensity of different states to tweet about drought, apparently reflecting recent and long-term experience in those states, and suggesting locales that would be most predisposed to drought policy innovation. [ABSTRACT FROM AUTHOR]

Cooling and heating degree‐days (CDD/HDD) are important metrics used in energy studies as a proxy for determining demand and consumption patterns of residential/commercial buildings and work spaces. Driven by the requirements of energy impact modellers, policymakers and building design experts; a new historical high‐spatial resolution, global gridded dataset of degree‐days constructed using various base (threshold) temperatures (Tb) is presented in this study. Derived using sub‐daily temperature from a quality‐controlled reanalysis data product (Global Land Data Assimilation System—GLDAS), the dataset called 'DegDays_0p25_1970_2018' includes monthly and annual (i) CDD; (ii) HDD; and (iii) CDD computed using wet‐bulb temperature (CDDwb) at 0.25° × 0.25° gridded resolution, covering 49 years over the period 1970–2018. The Tb used for assembling DegDays_0p25_1970_2018 include 18, 18.3, 22, 23, 24, 25°C for CDD and CDDwb; and 10, 15, 15.5, 16, 17 and 18°C for HDD, respectively. The data of individual indices are made publicly available in the commonly used scientific Network Common Data Form 4 (NetCDF4) and Georeferenced Tagged Image File (GeoTIFF) formats. DegDays_0p25_1970_2018 fills gaps in existing energy indicators' datasets by being the only high‐resolution historical global gridded time series based on multiple threshold temperatures, thus offering applications in wide‐ranging climate zones and thermal comfort environments. The richness of DegDays_0p25_1970_2018 lies in its flexibility by allowing users to aggregate the degree‐days not only at varying spatial scales (such as administrative levels, national boundaries, economic organizations e.g. OECD; with or without population weights), but also at varying temporal scales (such as seasons), thereby offering climatologists with a potential to examine global teleconnection patterns more discretely. [ABSTRACT FROM AUTHOR]

The meteo-climatic arguments for the eastern biogeographic limit of beech in Romania are of particular interest to forestry, but also to geographers and climatologists. This limit marks the transition from the temperate humid climate of Western and Central Europe to the temperate continental climate of Eastern Europe. Our paper provides improved knowledge on climatic conditions that restrict the longitudinal distribution of beech at temperate latitudes in north-eastern Romania. Results show that rainfall scarcity and high temperature in the March-June interval, added to temperature drop below the freezing point in April-June are the main climatic conditions that limit beech expansion eastward of this biogeographic limit. [ABSTRACT FROM AUTHOR]

This article shows acoustic measurements from Svalbard archipelago in the Arctic, located in the Arctic Ocean. The aim of the research was to show the Svalbard soundscape as well as to record and analyse the spatial-temporal dynamics of the acoustic environment, the human impact on the soundscape and to collect baseline data for future comparative research. Svalbard is interesting for many science disciplines because it has an arctic climate and, at the same time, it is relatively easily accessible. Climatologists, geologists, glaciologists, biologists and even anthropologists could find interesting themes to investigate here. Additionally, the soundscape of Spitsbergen is worthy of detailed examination. This paper presents comparative analysis of the soundscape of various spots near Longyearbyen in Management Area 10. The soundscape analysis of selected valleys shows the strong influence of human activity on the soundscape as well as the variability and characteristic features of the natural Arctic soundscape. [ABSTRACT FROM AUTHOR]

A personal narrative is presented which explores the author's experience of being a climate scientist in the U.S. Congress.

Historians and historical climatologists have long pointed to an increased flood frequency in central Europe in the mid- and late 19th century. However, the causes have remained unclear. Here, we investigate the changes in flood frequency in Switzerland based on long time series of discharge and lake levels, precipitation, and weather types and based on climate model simulations, focusing on the warm season. Annual series of peak discharge or maximum lake level, in agreement with previous studies, display increased frequency of floods in the mid-19th century and decreased frequency after the Second World War. Annual series of warm-season mean precipitation and high percentiles of 3 d precipitation totals (partly) reflect these changes. A daily weather type classification since 1763 is used to construct flood probability indices for the catchments of the Rhine in Basel and the outflow of Lake Lugano, Ponte Tresa. The indices indicate an increased frequency of flood-prone weather types in the mid-19th century and a decreased frequency in the post-war period, consistent with a climate reconstruction that shows increased (decreased) cyclonic flow over western Europe in the former (latter) period. To assess the driving factors of the detected circulation changes, we analyze weather types and precipitation in a large ensemble of atmospheric model simulations driven with observed sea-surface temperatures. In the simulations, we do not find an increase in flood-prone weather types in the Rhine catchment in the 19th century but a decrease in the post-war period that could have been related to sea-surface temperature anomalies. [ABSTRACT FROM AUTHOR]

The article focuses on using proxy data to make claims about climate change. Topics discussed include proxy climatology activity is designed around a constructivist view of learning, paleoclimatologists gather proxy data from natural climate recorders such as tree rings, ice cores, fossil pollen, ocean sediments, and corals and corals are sessile ocean animals that build hard skeletons from calcium carbonate, a mineral extracted from seawater.

In modern conditions, there are cardinal climate changes on the Earth as at the planetary scale, as at the regional level. According to numerous hydrometeorological characteristics and indicators, climatologists specialists concluded that Ukraine also take place significant climatic changes in the last 10-25 years. In complicated natural-technical systems, which include irrigation and drainage systems (IDS) on drained lands, the selection of regime-technological and technical solutions on different levels of the decision including the time, should be based on the appropriate meteorological information for selecting climatologically optimal management strategies for such systems in the long- -term and annual periods. The decisive influence on the formation of water and the overall natural reclamation modes of reclaimed land and harvest crops in many cases depends exactly from climate or weather conditions. Thus, it is necessary to have available data about their implementation to the relevant object as for number of previous years retrospective observations and the forecast period of functioning of the object. Therefore, forecasting of weather and climate conditions become an indispensable condition for implementation of assessing the overall effectiveness of IDS operation. To solve this problem we performed large- -scale computer experiment for multi-year retrospective and current data observations in the area of Zhytomyr Polissya. Were planned and implemented the following variants of studies - «Base», «Transitional», «Recent», «CCCM», «UKMO». The forecast was done for five years of typical groups of vegetation periods regarding conditions of heat and moisture provision (very wet - 10%, wet - 30%, average - 50%, dry - 70%, very dry - 90%) on such basic meteorological characteristics: air temperature; precipitation; relative air humidity; deficit of air humidity; photosynthetically active radiation (PAR); coefficient of moisture provision (the ratio of precipitation to evapotranspiration). Obtained results of comparative assessment of climatic conditions in Zhytomyr Polissya zone, suggests that for most of the basic meteorological parameters, already there are changes that in the short term may exceed 10% of the critical ecological threshold, which will lead to relevant irreversible changes in the state of the environment in the region. [ABSTRACT FROM AUTHOR]

Plenty of climate data from various sources have become available in recent years. However, to obtain climate data adequately meeting the requirement of ecological studies remains a challenge in some cases due to the difficulty of data integration and the complexity of downscaling, especially for mountainous regions. Lapse rate is one of the most important factors that influence the change of climatic variables in the mountains, and it should be incorporated into climatic models. In this study, we applied a synthetic approach combining bilinear interpolation (to produce seamless surfaces) and dynamic local regression (to obtain local lapse rates) to develop a scale-free and topography-correspondent downscaling model in R environment for Taiwan, called clim.regression. This model can generate 73 climatic variable estimates specific to the user-defined points of interest, including primary climatic variables and additional biologically relevant derivatives for historical (1960-2009) and future periods (2016-2035, 2046-2065 and 2081-2100). Results of our evaluation indicated that clim.regression reduced prediction error by 54.6%-66.7% relative to the original gridded climate data for temperatures. In addition, we demonstrated the spatiotemporal patterns of lapse rate for different climate variables. [ABSTRACT FROM AUTHOR]

The Okubo–Weiss–Zeta (OWZ) tropical cyclone (TC) detection scheme, which has been used to detect TCs in climate, seasonal prediction, and weather forecast models, is assessed on its ability to produce a realistic TC track climatology in the ERA-Interim product over the 25-yr period 1989 to 2013. The analysis focuses on TCs that achieve gale-force (17 m s−1) sustained winds. Objective criteria were established to define TC tracks once they reach gale force for both observed and detected TCs. A lack of consistency between storm tracks preceding this level of intensity led these track segments to be removed from the analysis. A subtropical jet (STJ) diagnostic is used to terminate transitioning TCs and is found to be preferable to a fixed latitude cutoff point. TC tracks were analyzed across seven TC basins, using a probabilistic clustering technique that is based on regression mixture models. The technique grouped TC tracks together based on their geographical location and shape of trajectory in five separate “cluster regions” around the globe. A mean trajectory was then regressed for each cluster that showed good agreement between the detected and observed tracks. Other track measures such as interannual TC days and translational speeds were also replicated to a satisfactory level, with TC days showing limited sensitivity to different latitude cutoff points. Successful validation in reanalysis data allows this model- and grid-resolution-independent TC tracking scheme to be applied to climate models with confidence in its ability to identify TC tracks in coarse-resolution climate models. [ABSTRACT FROM AUTHOR]

The decadal oscillation of rainfall in Europe that has been observed since the end of the 20th century is a phenomenon well known to climatologists. Consequences are considerable because the succession of wet or dry years produces floods or, inversely, droughts. Moreover, much research has tried to answer the question about the possible link between the frequency and the intensity of extra-tropical cyclones, which are particularly devastating, and global warming. This work aims at providing an exhaustive description of the rainfall oscillation in the 5-10 year band during one century on a planetary scale. It is shown that the rainfall oscillation results from baroclinic instabilities over the oceans. For that, a joint analysis of the amplitude and the phase of sea surface temperature anomalies and rainfall anomalies is performed, which discloses the mechanisms leading to the alternation of high and low atmospheric pressure systems. For a prospective purpose, some milestones are suggested on a possible link with very long-period Rossby waves in the oceans. [ABSTRACT FROM AUTHOR]

This paper gives practical information related to the use of simplified EnergyPlus models and its impact on estimates of the cooling demand, especially when EnergyPlus models are coupled with an urban canopy model. By simplified models, it is referred to shoebox as well as multi-floor models. For the interest of climatologists, their influence on estimates of urban temperature and specific humidity is also studied. To explore divergences between the use of detailed and simplified EnergyPlus models, a typical office area in Singapore is selected as a case study. As a result, it is observed that the use of multi-floor models provides estimates of the cooling demand and urban microclimatic conditions which achieve the best agreement with these assessed from detailed models. On the other hand, less time is required to run a shoebox than a multi-floor model. Although these outcomes are inferred from an excellent case study, further research must be conducted on several types of urban areas to elaborate a general theory. [ABSTRACT FROM AUTHOR]

Information about the brain storming workshop on climate modeling that was held at the Indian Institute of Technology (ITT) in New Delhi, India on July 19 to 20, 2016 is presented. Topics mentioned include the current status and prospects of climate modeling in India, the weather services offered by the India Meteorological Department and the need to quantify the uncertainties on climate change projections. The attendance of 65 scientists on the event is also emphasized.

In this article we analyse the evolution in time of extreme temperatures significant for Romania with a focus on absolute extreme temperatures recorded on the overall present territory. After thoroughly investigating the credible sources referenced at the end of the paper, we present in chronological order the records for absolute minimum temperatures, and absolute maximum temperatures which were measured at the meteorological stations on the present territory of Romania, according to the availability of the data, i.e. the last two decades of the 19th century up until 2017. We classify and discuss the sources of climatological data in the form of minimum and maximum temperatures. The measurements of meteorological parameters on the current national territory were recorded since 1770 at Iași (cf. Dissescu 1931 and also http://www.meteoromania.ro/anm2/despre-noi/istoric/ - page in Romanian as of 30.03.2017). For a systematic approach with credible data, at least another century passed, until Ștefan Hepites (1851-1922) founded in 1884 in Bucharest the Central Meteorological Institute of Romania (I.M.C. in Romanian) (Dissescu, 1931 and cf. the ANM web page quoted earlier). The newly created Institute did not include the meteorological stations which were present at that time in Transylvania, but only the ones on the official Romanian territory of 1859-1918 made up of Moldavia and Wallachia. This paper argues in favour of the process of global warming (GW) and its effects upon the evolution of extreme temperature values in a certain time interval. The conclusions stemming from the investigation of the dataset in this paper should provide a helpful and necessary point of departure in subsequent research of climatologists in their quest of identifying the correct model of future climate. Our article should be regarded as part of a series of analyses of the variability of the climate in Romania, the recent influence of global warming on it and on certain climatological parameters in particular. [ABSTRACT FROM AUTHOR]

Ion Beam Analysis (IBA) techniques were used to assign nine years of PM 2.5 observations to seven source types, at Lucas Heights, a topographically complex urban fringe site of Sydney. The highest contributions to total PM 2.5 were from motor vehicles ( Autos , 26.3%), secondary sulfur ( 2ndryS , 23.7%), a mixture of industry and aged sea air ( IndSaged , 20.6%), and smoke ( Smoke , 13.7%). The Autos contribution was highest in winter, whereas 2ndryS was highest in summer, indicating that mitigation measures targeting SO 2 release in summer and vehicle exhaust in winter would be most effective in reducing the PM 2.5 concentrations at this site. Since concentrations of particulate matter can be significantly affected by local meteorology, generalised additive model (GAM) techniques were employed to investigate relationships between PM 2.5 source types and meteorological conditions. The GAM predictors used included: time (seasonal to inter-annual variations), mixing layer depth, temperature, relative humidity, wind speed, wind direction, and atmospheric pressure. Meteorological influences on PM 2.5 variability were found to be 58% for soil dust, 46% for Autos , 41% for total PM 2.5 , and 35% for 2ndryS . Effects were much smaller for other source types. Temperature was found to be an important variable for the determination of total PM 2.5 , 2ndryS , IndSaged , Soil and Smoke , indicating that future changes in temperature are likely to have an associated change in aerosol concentrations. However, the impact on different source types varied. Temperature had the highest impact on 2ndryS (sometimes more than a factor of 4 increase for temperatures above 25 °C compared to temperatures under 10 °C) and IndSaged , being predominantly secondary aerosols formed in the atmosphere from precursors, whereas wind speed and wind direction were more important for the determination of vehicle exhaust and fresh sea salt concentrations. The marginal effect of relative humidity on 2ndryS increased up to relative humidity of 70–80% and then plateaued, confirming previous findings that (NH4) 2 SO 4 is present in the solid phase below relative humidity of about 80%. [ABSTRACT FROM AUTHOR]

Urban climatologists have moved smoothly towards urban geometry meso-scales as obstruction between buildings, streets, and urban environment. Urban climatologists and designers have expressed that urban geometry parameters affect urban microclimate conditions. Improper functioning of the geometry factors, particularly air temperature and wind speed, can increase the harshness of climate change and Urban Heat Island (UHI) defects, which are more critical in coastal cities of tropical regions. In this regard, the current study aimed to identify the impact of each street geometry factor on urban microclimate through a critical literature review. The research determined a total of twenty seven (27) factors within three clusters; 1) geometry factors, 2) meteorological factors, and 3) streetscape factors. The content analysis calculated the Depth of Citation (DoC) which refers to the cumulative importance level of each factor. The content analysis resulted air temperature (Ta) (DoC = 18 out of 28) is the most important street geometry factor that should be extensively considered in urban microclimate studies in coastal cities. In contrast, the factors (such as air pollution and traffic load) have received a minimum Doc (1 out of 28). The research has also analyzed the importance level of clusters through an expert input study using Grounded Group Decision Making (GGDM) method. The results show that meteorological cluster (92 %), streetscape cluster (86 %), and geometry cluster (85 %) have to be respectively implemented in urban microclimate studies in coastal cities. The research states there are new approaches have not yet been touched by urban climatologist affecting urban microclimate; included; surface materials, sea-borne dust and sand, user's satisfaction, user's thermal adaptive behavior. These approaches can potentially exacerbate UHI effects in coastal cities, which need further research. [ABSTRACT FROM AUTHOR]

The nature of cave ventilation is of interest to cavers, speleologists, and paleoclimatologists working with stalagmites. Because cave ventilation systematics may change over the growth span of a stalagmite, understanding what factors affect them is critical for determining events that may have affected climate proxies within the stalagmite. Similarly, understanding how the hydrology of the drips feeding a stalagmite evolves through time is key to building robust records of paleoclimate, particularly because stalagmite records have become critical archives of climate change information of the last 500,000 years. Here we present data from an extensive, on-going monitoring effort at Yok Balum Cave, Belize, initiated in 2011, that characterizes high-resolution ventilation dynamics at this site. Clear seasonal ventilation regimes exist, driven by thermally induced inside-outside air density differences. The winter regime is dominated by air inflow into the cave, decreased drawdown from the epikarst into the cave, and a limited diurnal signal. Conversely, summer ventilation is dominated by air outflow from the cave, greater CO2 drawdown and drip water degassing, and a strong diurnal signal. Active monitoring during a large (M7.4) earthquake in November 2012 provides a unique opportunity to assess the response of the cave atmosphere and hydrology to substantial seismic activity. Cave atmosphere dynamics and hydrology are found to be highly resilient to seismic activity, with no observable disturbance occurring around the earthquake, despite there being considerable evidence of physical disruption in the cave. Monitoring included different kinds of drips, and the earthquake affected none of the monitored drip types. This suggests that stalagmite-derived paleoclimate records are not affected by seismic activity, except in extreme cases where the stalagmite or conjugate stalactite is damaged or reoriented. [ABSTRACT FROM AUTHOR]

Analog postprocessing methods have previously been applied using precipitation reforecasts and analyses to improve probabilistic forecast skill and reliability. A modification to a previously documented analog procedure is described here that produces highly skillful, statistically reliable precipitation forecast guidance at ° grid spacing. These experimental probabilistic forecast products are available via the web in near-real time. The main changes to the previously documented analog algorithm were as follows: (i) use of a shorter duration (2002-13), but smaller grid spacing, higher-quality time series of precipitation analyses for training and forecast verification (i.e., the Climatology-Calibrated Precipitation Analysis); (ii) increased training sample size using data from 19 supplemental locations, chosen for their similar precipitation analysis climatologies and terrain characteristics; (iii) selection of analog dates for a particular grid point based on the similarity of forecast characteristics at that grid point rather than similarity in a neighborhood around that grid point; (iv) using an analog rather than a rank-analog approach; (v) varying the number of analogs used to estimate probabilities from a smaller number (50) for shorter-lead forecasts to a larger number (200) for longer-lead events; and (vi) spatial Savitzky-Golay smoothing of the probability fields. Special procedures were also applied near coasts and country boundaries to deal with data unavailability outside of the United States while smoothing. The resulting forecasts are much more skillful and reliable than raw ensemble guidance across a range of event thresholds. The forecasts are not nearly as sharp, however. The use of the supplemental locations is shown to especially improve the skill of short-term forecasts during the winter. [ABSTRACT FROM AUTHOR]

The paper traces my career as a climatologist from the 1950s and that of most of my graduate students from the late 1960s. These decades were the formative ones in the evolution of climate science. Following a brief account of the history of climatology, a summary of my early training, my initial teaching and research in the UK is discussed. This is followed by new directions at the University of Colorado, Boulder from October 1968. The history of the World Data Center for Glaciology/National Snow and Ice Data Center in Boulder from 1977 is described and climate-cryosphere initiatives at the Cooperative Institute for Research in Environmental Sciences (CIRES). International activities and links are then reported, followed by a section on national and international committees. I then describe my activities during sabbaticals and research leaves. The paper concludes with discussion of my "retirement" activities and an epilogue. The paper is based on a lecture given at the Roger Barry Symposium: A Chronicle of Distinction: From the Arctic to the Andes, at the University of Colorado, 10 August 2004 and updated to 2014. [ABSTRACT FROM AUTHOR]

Current global warming is likely to result in a unipolar glaciated world with unpredictable repercussions on atmospheric and oceanic circulation patterns. These changes are expected to affect seasonal extremes and the year-to-year variability of seasonality. To better constrain the mode and tempo of the anticipated changes, climatologists require ultra-high-resolution proxy data of time intervals in the past, e.g., the Oligocene, during which boundary conditions were similar to those predicted for the near future. In the present paper, we assess whether such information can be obtained from shells of the long-lived bivalve mollusk Glycymeris planicostalis from the late Rupelian of the Mainz Basin, Germany. Our results indicate that the studied shells are pristinely preserved and provide an excellent archive for reconstructing changes of sea surface temperature on seasonal to interannual timescales. Shells of G. planicostalis grew uninterruptedly during winter and summer and therefore recorded the full seasonal temperature amplitude that prevailed in the Mainz Basin ~ 30 Ma. Absolute sea surface temperature data were reconstructed from δ18Oshell values assuming a δ18Owater signature that was extrapolated from coeval sirenian tooth enamel. Reconstructed values range between 12.3 and 22.0 °C and agree well with previous estimates based on planktonic foraminifera and shark teeth. However, temperatures during seasonal extremes vary greatly on interannual timescales. Mathematically re-sampled (i.e., corrected for uneven number of samples per annual increment) winter and summer temperatures averaged over 40 annual increments of three specimens equal 13.6 ± 0.8 and 17.3 ± 1.2 °C, respectively. Such high-resolution paleoclimate information can be highly relevant for numerical climate studies aiming to predict possible future climates in a unipolar glaciated or, ultimately, polar-ice-free world. [ABSTRACT FROM AUTHOR]

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies. [ABSTRACT FROM AUTHOR]

IN MEMORIAM ARIEH BITAN 1935-2019 ROLAND LIST 1929-2019 NORMAN PHILLIPS 1924-2019 Arieh Bitan passed away in Jerusalem on February 19, 2019 at the age of 84. He was a pioneer [...]