Large Climate Variability Research Articles

An Empirical Seasonal Rainfall Forecasting Model for the Northeast Region of Brazil

The Northeast region of Brazil (NEB) is characterized by large climate variability that causes extreme and long unseasonal wet and dry periods. Despite significant model developments to improve seasonal forecasting for the NEB, the achievement of a satisfactory accuracy often remains a challenge, and forecasting methods aimed at reducing uncertainties regarding future climate are needed. In this work, we implement and assess the performance of an empirical model (EmpM) based on a decomposition of historical data into dominant modes of precipitation and seasonal forecast applied to the NEB domain. We analyzed the model’s performance for the February-March-April quarter and compared its results with forecasts based on data from the North American Multi-model Ensemble (NMME) project for the same period. We found that the first three leading precipitation modes obtained by empirical orthogonal functions (EOF) explained most of the rainfall variability for the season of interest. Thereby, this study focuses on them for the forecast evaluations. A teleconnection analysis shows that most of the variability in precipitation comes from sea surface temperature (SST) anomalies in various areas of the Pacific and the tropical Atlantic. The modes exhibit different spatial patterns across the NEB, with the first being concentrated in the northern half of the region and presenting remarkable associations with the El Niño-Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), both linked to the latitudinal migration of the intertropical convergence zone (ITCZ). As for the second mode, the correlations with oceanic regions and its loading pattern point to the influence of the incursion of frontal systems in the southern NEB. The time series of the third mode implies the influence of a lower frequency mode of variability, probably related to the Interdecadal Pacific Oscillation (IPO). The teleconnection patterns found in the analysis allowed for a reliable forecast of the time series of each mode, which, combined, result in the final rainfall prediction outputted by the model. Overall, the EmpM outperformed the post-processed NMME for most of the NEB, except for some areas along the northern region, where the NMME showed superiority.

Spatial‐temporal evaluation of different reference evapotranspiration methods based on the climate forecast system reanalysis data

AbstractEvapotranspiration is a major component of the interaction between land‐surface processes and the atmosphere. Climate Forecast System Reanalysis (CFSR) data offer a promising database for overcoming the limitations in availability and reliability of climatological data and, hence, for understanding the evapotranspiration process. Using these data on grid‐by‐grid daily, seasonal and yearly scales, the present study attempts to advance the spatio‐temporal evaluation of two radiation‐based and three temperature‐based methods for estimating potential evapotranspiration (PET) against estimates of grass reference evapotranspiration (ETo) by FAO Penman–Monteith method (FAO‐PM). The analysis was performed for the period 1979–2013, considering the second largest (79 000 km2) river system in Ethiopia, that is, Omo‐Gibe basin, which accommodates national parks and vast hydropower, cultivation and afforestation developments and discharges its flow to Lake Turkana in Kenya. Despite the large regional variations in climate and elevation, the results in overall emphasize the outperformance of the simple temperature method, viz. Hargreaves–Samani method, in capturing both the annual and seasonal FAO‐PM estimates. Calibration of the Hargreaves–Samani equation is, however, a requisite for spectacular improvement of its performance. Accordingly, new coefficients of the equation are proposed. The annual trends in the basin's ETo increased with rising temperature and decreasing relative humidity, wind speed, and solar radiation, but with decreasing (increasing) rainfall in the upper region (the middle and lower regions). It is deduced that trends in simple methods do not necessarily reflect the true trends in ETo. Annual ETo decreases with increasing elevation and annual rainfall. The present findings are discussed in the context of a worldwide literature, thereby improving the understanding of the best performing PET methods in similar data‐scarce national or transboundary rivers basin in Ethiopia, the region or worldwide. The wider implications regarding water loss from reservoirs and the rain‐fed food and sugar production in the basin under study are also highlighted.

A Comparative Analysis of the Temperature-Mortality Risks Using Different Weather Datasets Across Heterogeneous Regions.

New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature‐mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population‐weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high‐resolution GCDs (HadUK‐grid UKPOC‐9 and MeteoSwiss‐grid‐product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi‐Poisson time series regression with distributed lag nonlinear models to obtain the GCD‐ and region‐specific temperature‐mortality associations and calculated the corresponding cold‐ and heat‐related excess mortality. Although the five exposure datasets yielded different average area‐level temperature estimates, these deviations did not result in substantial variations in the temperature‐mortality association or impacts. Moreover, local population‐weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data.

Observed Statistical Connections Overestimate the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate

AbstractDisentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called Atmospheric Model Intercomparison Project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents–Kara sea ice and Eurasian surface temperature, and between winter Chukchi–Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November–December Barents–Kara sea ice, a weakened winter stratospheric polar vortex, and a shift toward the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-yr-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent or are substantially weaker in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.

Rethinking Climate, Climate Change, and Their Relationship with Water

We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate was established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acts upon it. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever-changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate, and not the opposite.

The Association of Cold Ambient Temperature With Fracture Risk and Mortality: National Data From Norway-A Norwegian Epidemiologic Osteoporosis Studies (NOREPOS) Study.

ABSTRACTNorway is an elongated country with large variations in climate and duration of winter season. It is also a high‐risk country for osteoporotic fractures, in particular hip fractures, which cause high mortality. Although most hip fractures occur indoors, there is a higher incidence of both forearm and hip fractures during wintertime, compared with summertime. In a nationwide longitudinal cohort study, we investigated whether cold ambient (outdoor) temperatures could be an underlying cause of this high incidence and mortality. Hospitalized/outpatient forearm fractures (International Classification of Diseases and Related Health Problems, 10th Revision [ICD‐10] code S52) and hospitalized hip fractures (ICD‐10 codes S72.0–S72.2) from 2008 to 2018 were retrieved from the Norwegian Patient Registry. Average monthly ambient temperatures (degrees Celsius, °C) from the years 2008 to 2018 were provided by the Norwegian Meteorological Institute and linked to the residential area of each inhabitant. Poisson models were fitted to estimate the association (incidence rate ratios [IRRs], 95% confidence intervals [CIs]) between temperature and monthly incidence of total number of forearm and hip fractures. Flexible parametric survival models (hazard ratios [HR], 95% CI) were used to estimate the association between temperature and post–hip fracture mortality, taking the population mortality into account. Monthly temperature ranged from −20.2°C to 22.0°C, with a median of −2.0°C in winter and 14.4°C in summer. At low temperatures (<0°C) compared to ≥0°C, there was a 53% higher risk of forearm fracture (95% CI, 51%–55%) and 21% higher risk of hip fracture (95% CI, 19%–22%), adjusting for age, gender, calendar year, urbanization, residential region, elevation, and coastal proximity. When taking the population mortality into account, the post–hip fracture mortality in both men (HR 1.08; 95% CI, 1.02–1.13) and women (HR 1.09; 95% CI, 1.04–1.14) was still higher at cold temperatures. There was a higher risk of forearm and hip fractures, and an excess post–hip fracture mortality at cold ambient temperatures. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins

Abstract. The total water storage change (TWSC) over land is a major component of the global water cycle, with a large influence on the climate variability, sea level budget and water resource availability for human life. Its first estimates at a large scale were made available with GRACE (Gravity Recovery and Climate Experiment) observations for the 2002–2016 period, followed since 2018 by the launch of the GRACE-FO (Follow-On) mission. In this paper, using an approach based on the water mass conservation rule, we propose to merge satellite-based observations of precipitation and evapotranspiration with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources and for which long-term records of in situ discharge measurements are available. Our Satellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP (Interactions between Soil, Biosphere and Atmosphere CNRM – Centre National de Recherches Météorologiques – Total Runoff Integrating Pathways) model simulations (1980–2015) and (3) the multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived datasets along with in situ data to perform a hydrologically coherent reconstruction of a missing water component estimate. It provides a new critical source of information for the long-term monitoring of TWSC and to better understand its critical role in the global and terrestrial water cycle.

Seasonal variation of fig tree (Ficus carica L.) physiological characteristics reveals its adaptation performance

In the context of climate change, understanding fig trees physiology is very important, since the areas of fig production registered a large climate variability that severely affects fruit quality. The present study was conducted to evaluate the seasonal changes of physiological leaf behaviour of two Tunisian fig cultivars, Zidi and Bither Abiadh during two years. Plants were subjected to full irrigation to maintain the soil moisture around pot capacity through the experimental period. Leaf gas exchange characteristics (net photosynthetic rate (PN), stomatal conductance (gs), and transpiration rate (E)), chlorophyll content index, leaf temperature and the maximum photochemical efficiency of PSII (Fv/Fm) were measured. Results showed that the photosynthetic characteristics changed during the growing season. Changes of photosynthetic CO2 assimilation, stomatal conductance, and chlorophyll content were not significantly affected by cultivar, and their variation was attributed to year. Seasonal changes of PN and gs were similar suggesting that both processes are dependent. Indeed the best photosynthetic performance of fig occurred about 80-87 days after bud break (spring) of the second season of growth, being supported by a high stomatal aperture. The lowest values of PN, E and gs were recorded 156 days after bud break (summer) for 2017. The decrease of gas exchange rates and high temperatures were registered during the same dates. A little increase of the photosynthetic characteristics and chlorophyll content was noticed in the autumn period, about 180 days after bud break, until a definitive decrease at the end of the growing season with the occurrence of low winter temperature. These results revealed particular adaptive behaviour and could be used as preliminary criteria to predict the future impact of environmental abiotic stresses on ecophysiological fig tree behaviour.

Climate change risks and adaptation: new indicators for Mediterranean viticulture

The Mediterranean region, expanding across Southern Europe and North Africa, has developed agricultural systems over thousands of years and today is a major agricultural trade actor in the global market. At the same time, environmental and social equity differences in the region are pronounced, and this inequality is reflected in the production of traditional Mediterranean crops, such as grapevine (Vitis vinifera L.), a permanent wood crop, well adapted to the lack of water and recurrent drought in the region, and that has a role in the mitigation role of agriculture in arid environments. Increasing the ability to adapt to adverse impacts of climate change is an important task for Mediterranean agriculture. The indicators selected are widely used by practitioners in this grapevine production sector, linking science to the tools used by stakeholders and therefore encouraging action and innovation among all stakeholders. The novelty of the study is: the definition of adaptation needs based on a combination of indicators of production quantity and quality with a consistent set of climate scenarios; the evaluation of probabilistic changes with special emphasis on drought in a region that has very large climate variability; the definition of adaptation needs based on a consistent set of scenarios in an over 2 million km2; and the evaluation of potential adaptation choices that may contribute to real-time policy analysis and development as national and international policies and agreements in the grapevine production sector. The climate changes scenarios are derived from global datasets. Adaptation efforts are estimated proportionally to the change of the climatic indices and are categorized into low, medium, or high, as a function of the excepted changes in climatic indices. The study emphasizes that non-informed adaptation limits future choices in areas severely impacted.

Meteorological observations for Eversleigh Station, near Armidale, New South Wales, Australia: 1877–1922

AbstractHistorical weather observations on the daily scale are vital for the improvement of reanalysis products and the analysis of long‐term variability of extreme events. While daily datasets extend for several centuries in parts of the Northern Hemisphere, the majority of historical data for the Southern Hemisphere are monthly averages or totals. In this paper, we describe a newly recovered dataset of ten daily meteorological variables for 1877 to 1922 from Eversleigh, a property in the New England region of New South Wales in Australia. Here, we present the full process of data rescue, from digitization to quality control and an assessment of homogeneity. We show that the majority of variables were recorded to a high standard and that the data are of general use for climate analysis. Forty years of daily temperature, cloud cover, wind, and pressure observations are now available for the New England Plateau, offering data that are more complete than any other records for the region in the Australian Bureau of Meteorology dataset. The Eversleigh dataset now provides an opportunity to gain more insight into the 19th century weather and climate of eastern Australia during a time of large interannual climate variability before the dominant impact of an anthropogenic warming signal.

Simulated surface and shallow groundwater resources in the Abaya-Chamo Lake basin, Ethiopia using a spatially-distributed water balance model

Study regionThe volcano-tectonic lakes basin of Abaya-Chamo is part of the Main Ethiopian Rift system and exhibits large variations in geomorphology, physiography and climate between the rift floor and the plateau. Study focusDespite the importance of streamflow for water resources management and planning in the basin, many of the rivers there are ungauged. To make quantitative estimates of streamflow for spatially resolved water availability in such a highly heterogeneous environment, therefore, requires numerical modeling. This study is the first to quantify the surface and shallow groundwater resources in Abaya-Chamo, and to validate the physically fully distributed hydrologic model WetSpass under highly data-limited conditions, in a complex two-lake environment. New hydrological insightsSimulated total river flow and estimated baseflow were verified at 15 gauging stations, with a good agreement. The WetSpass model is shown to be suitable for such a complex setting with a correlation coefficient of 0.95 and 0.97 for total flow and baseflow respectively at a statistically significant level (p-value < 0.05). The simulated annual water budget reveals that 74.6% of the 22.1 billion lit/yr in total precipitation in the basin is lost through evapotranspiration, 15.7% through surface runoff, and only 9.7% recharges the groundwater system. The simulations also revealed the surface runoff and groundwater recharge are the most sensitive to soil textural class, while evapotranspiration depends more strongly on land use.

Water scarcity in Brazil: part 1—regionalization of the AWARE model characterization factors

This paper presents the regionalized water scarcity characterization factors (CFs) of the available water remaining (AWARE) model, which was found by a previous study, on the water scarcity in Brazil, to be the most indicative characterization model for the water-scarce regions in Brazil. We used the national database and hydrographic delimitations defined by the National Water Agency (Agencia Nacional de Aguas — ANA) to generate the regionalized AWARE BR CFs. The CFs were regionalized by hydrographic delimitations used by ANA: (i) State Hydrographic Units (SHU) and (ii) Hydrographic Regions (HR). These AWARE BR CFs were compared with the factors originally proposed by WULCA (2018) and with the Scarcity Index used by ANA to identify the scarcest regions in the country. Finally, the AWARE and AWARE BR factors were applied to a case study of Brazilian melons, evaluating the regionalization effects on the results of water scarcity analysis. The AWARE BR CFs demonstrate most consistency with the regions recognized by ANA to have water scarcity problems, such as the semiarid region. Approximately 12% of the SHUs exhibited maximum water scarcity (CF = 100) during the entire year, while 11% presented minimum scarcity factors (CF = 0.1). The comparison of hydrologic data from ANA with those from WaterGAP indicated that water availability was overestimated in WaterGAP, while demand was underestimated in different basins. The comparison of AWARE BR CFs with ANA Scarcity Index values indicated more similarity (smaller residual error) than the comparison of AWARE BR CFs with AWARE. The case study regarding the impact of water scarcity on melons showed a significant difference between characterization factors and, consequently, in the values of impact. AWARE BR factors generated with national characterization data are adapted to the different regions of Brazil, exhibiting higher sensitivity to the semiarid region. This regionalization provided a more accurate representation of the scarcity in smaller basins located in larger basins, characterized by large climate variation.

A note on air temperature and precipitation variability and extremes over Asmara: 1914–2015

AbstractMeteorological series (daily precipitation, minimum and maximum air temperature) for Asmara (Eritrea) for the last 100 years (1914–2015) are analysed. The data were quality‐controlled and homogenized using publicly available data from surrounding countries as well as newly recovered data from 12 stations in Eritrea. Overall, the Asmara data showed a consistent pattern and there were no outliers outside of four standard deviations from the corresponding reference. Climate indices were calculated using the program RClimDex. Overall, 8 indices for description of the air temperature data and 10 for precipitation data were calculated. The analyses of averages and indices reveal large climatic variations in the central highlands of Eritrea. The results indicate significant changes in air temperature since 1943, with daily minimum and maximum air temperature increasing at a similar rate of 0.22 and 0.19°C/decade, respectively. The diurnal air temperature range shows a non‐significant decreasing trend over the study period. No significant variation was found in the annual total and the seasonal precipitation over the last century. Significant trends were detected for some daily precipitation indices, although the lack of reference series prevents an evaluation of their reliability.

Conventional versus agro-ecological intensification: assessing the effect of conservation agriculture in maize cropping systems with the DSSAT model in Côte d’Ivoire (West Africa)

Integrated soil fertility management options are being promoted as ways of adapting agricultural systems to sustain yields on highly degraded and poor soils encountered throughout West Africa. The efficiency of these practices may be affected by high variability and uncertainty associated with seasonal rainfall, especially for areas such as Cote d’Ivoire, where intra-seasonal rainfall has been observed to change from 1 year to another. The DSSAT crop simulation model was used in this study as a tool to evaluate the impacts of soil improvement options including inorganic fertilizer and conservation agriculture generating higher carbon sequestration and crop yield in maize agro-ecosystems. The model was calibrated using agronomic data for three cropping seasons from 2009 to 2010 in Goulikao (Center-West Cote d’Ivoire) and Aheremou 2 (Central Cote d’Ivoire), respectively and validated against independent datasets of yield of 2003–2004 seasons in the buffer zone of the Lamto Natural Reserve, Central Cote d’Ivoire. The model predicted average maize yields of 1454 kg ha−1 across the sites versus an observed average value of 1736 kg ha−1, R2 of 0.72, and RMSE of 597 kg ha−1 after the default values for stable soil organic matter fraction used in the model were substituted by the estimated one. For the validation, the predicted higher maize yield was consistently related to fallow biomass inputs and different rates of fertilizer, thus generating a RMSE of total aboveground biomass and grain yield of 606 kg ha−1 and 350 kg ha−1, respectively. The impact of fallow residues and cropping sequence on subsequent maize yield was simulated and compared with conventional fertilizer and control data using 12 years historic climate time series. We conclude that soil fertility improvements through conservation agriculture can sustain grain yield at the same level as conventional inputs of urea against larger climate variability. However, this system may be substituted by conventional agriculture when climate forecast reveals a dry cropping season year.

Antarctic temperature and CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;: near-synchrony yet variable phasing during the last deglaciation

Abstract. The last deglaciation, which occurred from 18 000 to 11 000 years ago, is the most recent large natural climatic variation of global extent. With accurately dated paleoclimate records, we can investigate the timings of related variables in the climate system during this major transition. Here, we use an accurate relative chronology to compare temperature proxy data and global atmospheric CO2 as recorded in Antarctic ice cores. In addition to five regional records, we compare a δ18O stack, representing Antarctic climate variations with the high-resolution robustly dated WAIS Divide CO2 record (West Antarctic Ice Sheet). We assess the CO2 and Antarctic temperature phase relationship using a stochastic method to accurately identify the probable timings of changes in their trends. Four coherent changes are identified for the two series, and synchrony between CO2 and temperature is within the 95 % uncertainty range for all of the changes except the end of glacial termination 1 (T1). During the onset of the last deglaciation at 18 ka and the deglaciation end at 11.5 ka, Antarctic temperature most likely led CO2 by several centuries (by 570 years, within a range of 127 to 751 years, 68 % probability, at the T1 onset; and by 532 years, within a range of 337 to 629 years, 68 % probability, at the deglaciation end). At 14.4 ka, the onset of the Antarctic Cold Reversal (ACR) period, our results do not show a clear lead or lag (Antarctic temperature leads by 50 years, within a range of −137 to 376 years, 68 % probability). The same is true at the end of the ACR (CO2 leads by 65 years, within a range of 211 to 117 years, 68 % probability). However, the timings of changes in trends for the individual proxy records show variations from the stack, indicating regional differences in the pattern of temperature change, particularly in the WAIS Divide record at the onset of the deglaciation; the Dome Fuji record at the deglaciation end; and the EDML record after 16 ka (EPICA Dronning Maud Land, where EPICA is the European Project for Ice Coring in Antarctica). In addition, two changes – one at 16 ka in the CO2 record and one after the ACR onset in three of the isotopic temperature records – do not have high-probability counterparts in the other record. The likely-variable phasing we identify testify to the complex nature of the mechanisms driving the carbon cycle and Antarctic temperature during the deglaciation.

Ecosystem water use efficiency in a young plantation in Northern China and its relationship to drought

Climate models predict large climatic variability and more frequent, prolonged droughts in northern China. Still, few studies have examined the seasonal and interannual variation in water use efficiency (WUE) in northern China’s young plantations predisposed to drought. Here, variation in WUE was examined in a young plantation in Beijing over a 6-year period (2012–2017) at several timescales. The study was conducted by examining eddy-covariance measurements of gross ecosystem production (GEP) and evapotranspiration (ET). Results showed that the multi-year mean WUE for this young plantation was 1.71 ± 0.22 g C per kg H2O. Drought reduced WUE in summer, but increased it in autumn, with no apparent effect in spring. Long-term droughts usually had a greater effect on the annual GEP, ET and WUE than short-term droughts. Intense drought was observed to have a long-term legacy effect on ecosystem GEP, ET and WUE of about 3 years. Monthly WUE had a strong positive linear relationship with normalized difference vegetation index (NDVI) and soil volumetric water content (VWC) during the growing season. Seasonal variation in WUE was mainly regulated by the biophysical factors controlling GEP. In contrast, interannual variation in WUE was controlled to a greater extent by vegetation cover (i.e., NDVI), which in turn responded to variation in VWC. These results clearly show the importance of timing and duration of drought in controlling ecosystem WUE. Collectively, WUE was more strongly affected by factors affecting carbon uptake than water consumption. Our findings suggest that future drought, when coupled with increased climate variability, irrigation-support planning and selection of appropriate tree species should be central to afforestation programs in northern China.

Changes in the Relationship between Particulate Matter and Surface Temperature in Seoul from 2002–2017

This study focuses on the changes over time in the relationship between surface temperature and particulate matter (PM) concentration over Seoul using long-term observational data. Correlation coefficients between the daily mean PM10 concentration and surface temperature were calculated to investigate the relationship between the two. The PM10 and temperature displayed a strong positive correlation, suggesting the increase in PM was driven by large-scale synoptic patterns accompanying such high temperatures. It was found that the correlation coefficient in 2002–2009 was significantly higher than that of 2010–2017, indicating that the relationship between PM10 concentration and temperature has weakened over time in recent decades. Correlation coefficients between daily averaged temperature and the PM10 of each year were calculated to account for the decreased correlation in the most recent decade. We found that the correlation coefficients between surface temperature and PM of each year exhibited a clear negative correlation with the longitudinal position of the Siberian High, suggesting that the position of the Siberian High might affect the strength of the relationship between PM concentration and temperature over Seoul. We also found that the eastward shift of the Siberian High reduces the standard deviation of pressure over Seoul, indicating reduction of synoptic perturbation. These results imply that the eastward shift of the Siberian High in recent decades might weaken the relationship between the PM and surface temperature over Seoul. This study suggests that the relationship between PM and meteorological variables is changing over time through changes in large climate variability.

Social, environmental and microbiologic aspects of endemic mycoses in Brazil.

Many factors that lead to host immunosuppression are clearly known to predispose the host to fungal diseases, significantly influencing the occurrence of mycoses. However, little or nothing has been discussed regarding social or economic factors that can influence the occurrence of diseases caused by fungi. In this minireview, we discuss several factors that may affect the occurrence of mycoses in Brazil, a continentally extended country that is marked by large climatic variations and severe socioeconomic distortions that may limit access to health services for the population.

Mechanisms influencing non-stationarity in rainfall-runoff relationships in southeast Australia

Arid and semi-arid regions experience large hydroclimatic variability and decadal-scale droughts. During droughts, the reduced water availability alters the biophysical properties of the catchments which leads to non-stationarity in rainfall-runoff (r-r) relationships. Uncertainty exists regarding the mechanisms causing r-r non-stationarity, especially at seasonal scales. This study analyses endogenous and exogenous catchment mechanisms which could possibly influence r-r relationships in two case study catchments in southeast Australia (SEA). The case study catchments are chosen such that they are representative of arid to semi-arid catchments that experience large climatic variability and decadal-scale droughts. The results demonstrate that endogenous catchment mechanisms (i.e. groundwater table, baseflow and vegetation) have stronger influences on non-stationarity in r-r relationships than exogenous catchment mechanisms like temperature and potential evapotranspiration. These findings highlight the importance of understanding changes in r-r relationships in order to develop more realistic and reliable hydrological models that are needed to quantify and adapt to the impacts of changing catchment or hydroclimatic conditions. While this study is focussed on SEA the findings are relevant to all catchments that experience large climatic variability and decadal-scale droughts.

Is climate change impacting Rideau Canal Skateway, the world’s longest skating rink?

This study aims to establish a comprehensive understanding of the effects of climate change on the Rideau Canal Skateway of Canada, the longest natural skating rink in the world. Through this study, we can establish that the Skateway season length can be explained by local temperature. Other variables considered in the study are snowfall as well as large-scale climate variations, namely Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and El Nino Southern Oscillation (ENSO) using their annual average indices values. The regression analyses conducted demonstrate that the variation in the season length of the Skateway can be explained by local temperature, and the variation in the local temperature can be explained by the AO and NAO. The ENSO does not explain the local temperature in the Skateway area. Therefore, it can be established that this study enhances our understanding of the complex climate phenomena in relation to the Skateway season length. We recommend that large climatic variables should be taken into account when predicting and planning for the Skateway season in a given year.