Monthly Climate Research Articles

Weather types and their frequencies over Central Asia –an ERA-Interim based analysis of monthly climate variability and change for the boreal cold season

Climate research in Central Asia is usually based on the analysis of meteorological observations. However, data scarcity in mountain regions causes uncertainties and, thus, the magnitude of climate change and variability in Central Asia is still under debate. Furthermore, the investigation of observations does only allow an assessment of the near surface climate. Since the meteorological conditions in the upper troposphere are generally unknown, the atmospheric mechanisms leading to observed climate changes remain unexamined. Here, the authors present a study of climate change and variability in Central Asia based on the ERA-Interim reanalysis, which provides gridded data-sets of various meteorological parameters for 60 atmospheric levels. In order to investigate the climatic conditions during the boreal cold season, the authors apply an objective weather type classification to 500hPa geopotential height fields. The results show that warm and wet conditions in Central Asia are associated with an anticyclonic anomaly over South Asia or a southward shift of the westerly jet stream. Dry conditions are accompanied by a cyclonic anomaly over South Asia. The authors show that the WT composition strongly affects the monthly and seasonal temperature and precipitation characteristics and that prevailing climatic trends are partially triggered by changing WT frequencies. About 50% of the seasonal temperature trend and 60% of the trend in March can be explained by WT frequency changes. While the observed seasonal precipitation trends cannot be explained by WT frequency changes, a positive trend in November seems to be accompanied by a decreasing frequency of high pressure over Central Asia.

Identification of highly pathogenic avian influenza suitable areas for wild birds using species distribution models in South Korea.

Event Abstract Back to Event Identification of highly pathogenic avian influenza suitable areas for wild birds using species distribution models in South Korea. Lee Kyuyoung1*, Dae-sung Yu2*, Beatriz Martínez-López1, Jaber A. Belkhiria1, Sung-il Kang2, Hachung Yoon2, Seong-Keun Hong2, ILSEOB LEE2, Han-Mo Son2 and Kwangnyeong Lee2 1 Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, United States 2 Animal and Plant Quarantine Agency (South Korea), Republic of Korea Highly pathogenic avian influenza (HPAI) virus is influenza A type virus with high mortality and morbidity in the broad range of host species domestic and wild birds to humans. HPAI infection has been a high-priority concern in global poultry industry because of consistent generation and circulation of novel HPAI strains, and consequent tremendous financial losses. Wild birds are considered one of the most important sources of novel HPAI introductions in poultry farms due to the experimental evidence of their asymptomatic infection with viral shedding, genetic closeness of HPAI virus identified in domestic poultry and wild birds, and spatial and temporal coincidence of identification of HPAI in wild birds and domestic poultry. The poultry industry in South Korea has annually suffered from the introduction of novel HPAI strains since early 2000s. HPAI infection in annually migrated wild birds has been carefully monitored to rapidly establish preventive measures of HPAI introduction into poultry farms in South Korea. However, current understanding of highly risk areas or suitable areas for HPAI in wild birds and contribution of other geographical and environmental factors contributing to HPAI vírus suitability is limited. Application of species distribution models based on digitalized geographical and environmental information facilitates our understanding about suitability of wild species’ habitat and its association with environmental and geographical factors. Furthermore, species distribution modelling can be applied to identify high-risk areas of potential disease transmission at the interface between wild species and domestic animals. Our study aimed to evaluate the areas with higher suitability/risk for HPAI identification in wild birds in South Korea and to describe what is the influence or association with the different environmental and geographical factors. Our results will help to not only have a better understanding of the ecology of HPAI in wild birds but also to establish more effective, risk-based, surveillance to prevent novel HPAI introductions into domestic poultry farms in South Korea We obtained land cover, monthly climate (precipitation, temperature and wind speed) and ecological preservation area (Level 1-3) data of South Korea in digitalized form as environmental and geographical data. The observation records of 7 species of wild birds (Baikal teal, white-front goose, common teal, mandarin duck, mallard, bean goose, spot-billed duck) in 206 habitats in South Korea from 1999 to 2017 were used to estimate the suitability map for the wild bird distribution in South Korea. The geographical records of wild bird HPAI surveillance from 2014 to 2018 was combined with 7 wild birds species distribution and environmental and geographical data to estimate the suitability map of HPAI identification in wild birds. Each suitability maps was estimated by maximum entropy approach (Maxent model) via the “dismo” package in R studio. 3. Results and Discussion Our study presents the suitability map of HPAI identification in wild birds and how geographical, environmental factors and 7 wild birds species distributions are contributing to the prediction. These results will not only provide a high-resolution map for the target allocation of surveillance and rapid detection of HPAI in wild birds but also will allow the improvement of the cost-effectiveness of risk-based surveillance of HPAI introduction into domestic poultry farms in South Korea. Acknowledgements This study was supported by the 2019-20 cooperative research grant from the veterinary epidemiology Division in the Animal and Plant Quarantine Agency (APQA) in South Korea and the fellowship of the graduate student support program (GSSP) at UC Davis

Influence of Climate Variation on Growth of Tropical Tree Species in Western Kenya

Aims: Growth-climate relationships were examined in 7 tropical tree species growing in the Yala river basin of western Kenya: Acacia mearnsii, Cupressus lusitanica, Eucalyptus camaldulensis, Eucalyptus grandis, Eucalytus saligna, Mangifera indica, and Markhamia lutea.
 Methodology: Standardized basal area increments were correlated with monthly and seasonal (3 month periods) climate variables (precipitation, mean temperature, Climate Moisture Index) obtained from nearby meteorological stations.
 Results: A majority of the tree species (M. indica, C. lusitanica, E. camaldulensis, and E. saligna) showed positive correlations with monthly and seasonal precipitation and moisture index during periods of the long and short rainy seasons. This study also revealed significant correlations between monthly and seasonal temperature data and radial growth of M. indica, M. lutea and E. grandis. Growth of M. lutea was negatively affected by cool growing season conditions while M. indica and E. grandis experienced high temperature stress. 
 Conclusion: Associations between radial growth of tropical tree species and temperature are generally rare in warm tropical regions, and for some of the species examined in this study that are non-native (i.e., M. indica and E. grandis), strongly suggests that they may be growing outside the optimal temperature conditions of their native geographical range.

Multi-site multivariate downscaling of global climate model outputs: an integrated framework combining quantile mapping, stochastic weather generator and Empirical Copula approaches

A distributed modeling of hydrological impact under climate change relies on climate scenarios for multiple climate variables at multiple locations across the catchment. The site-specific or variable-specific downscaling methods only produce climate change scenarios for a specific site or specific variable, which is inadequate to drive distributed hydrological models to investigate the spatio-temporal variability of climate change impacts at the catchment scale. This study proposes an integrated framework combining quantile mapping (QM), stochastic weather generator (WG) and Empirical Copula (EC) approaches for multi-site multivariate downscaling of global climate model outputs from monthly, grid-scale to daily, station-specific scale. In this hybrid scheme, the QM method is used to spatially downscale the monthly large-scale climate model outputs; then a stochastic WG is used to temporally downscale the monthly data to daily data by adjusting the WG parameters according to the predicted changes from large-scale climate models; at last, the observed inter-site and inter-variable dependencies, the temporal persistence, as well as the inter-annual variability are restored using the EC approach. An application of the proposed methodology is presented for statistical downscaling of the monthly precipitation, maximum and minimum temperatures from historical simulations of two Earth System Models (ESMs) to eleven weather stations over Daqing river basin in north China. The proposed methodologies are calibrated during the period 1957–1986 and evaluated in the period 1987–2016. The results show that the proposed downscaling approach is able to reconstruct the marginally distributional statistics, inter-site and inter-variable dependencies, and temporal persistence in the downscaled data for the validation period. A Limitation is also noted, such as a possible misrepresentation of the dependence structure and inter-annual variability under a non-stationary climate condition. The proposed methodologies are useful for downscaling ensembles of large-scale climate model simulations and projections for distributed hydrological impact studies.

Winter Tourism in Croatia: Is It Possible?

Tourism in Croatia primarily relies on the “sun and sea” product as the main asset of its offering. The current lack of adequate infrastructure, an underdeveloped winter tourism offering and the lack of stakeholders’ interest in developing winter tourism products are only some of the problems facing winter tourism development in Croatia. Winter tourism development does not include only snow-related activities but all outdoor activities, where weather and climate play a significant role. This paper analyzes the relationship between average monthly climate indicators in summer and winter periods and the number of overnight stays in Croatia from 1977 to 2014. In the regression analysis, we used a multivariate model with first difference specification and ordinary least square (OLS) estimation, in which past period of the dependent variable was also included. Seasonality was controlled by using quarterly dummy variable. The analyses for coastal and continental Croatia were made separately. Using regression and correlation analyses, we prove that Croatian tourism in the coastal part is strongly related to climate parameters while that influence in the continental part is less significant. The main hypothesis of the paper is that, with the increase in temperature, the tourism season will be prolonged in both the coastal and continental part of the Republic of Croatia. However, other interventions in tourism (such as raising the quality, expanding the offering etc.) can also increase tourism results since climate parameters do not have the same effect on the continental and coastal part of the Republic of Croatia. The impending climate change will cause climate indicators to change, thus unlocking the potential for winter tourism development in areas not related to the sea, but also requiring the development of various forms of special-interest tourism. Winter tourism in Croatia represents a big potential not only because climate change will potentially make winters in Croatia milder but also because, with the right policies, there is a huge potential to develop the undeveloped region of continental Croatia with products that would diversify the Croatian tourism offerings.

Testing annual tree-ring chemistry by X-ray fluorescence for dendroclimatic studies in high-elevation forests from the Spanish Pyrenees

Climate reconstructions based on tree-ring features rely on the assumption that growth drivers are mainly meteorological variables. Consequently, annually resolved and absolutely dated temperature reconstructions in high-elevation conifer forests are mainly based on tree-ring width (TRW) and maximum wood density (MXD). However, long-term and annually resolved chronologies of chemical elements are scarce despite they could complement TRW- and MXD-based reconstructions. Here, we used a novel non-destructive method by applying Micro X-ray fluorescence (μXRF) to wood samples of old mountain pine (Pinus uncinata) trees from two Pyrenean high-elevation forests. We tested if Calcium (Ca) relative concentration, as estimated through μXRF, is a valuable proxy of long-term climatic and environmental changes in two sites with basic and acid soils, respectively. We compared the climate sensitivity of TRW, MXD and Ca by using calculating correlations with monthly climate data (mean temperature and total precipitation). Then, we built linear regressions to predict temperatures for the period 1900–2009. Prior-autumn and spring temperatures were positively related to TRW, MXD and Ca. However, Ca series revealed a high sensitivity to temperatures during the prior winter and spring but also to summer precipitation. We confirm the potential of long-term wood-chemistry studies based on the μXRF non-destructive technique to reconstruct environmental changes.

Influence of the ecological conditions on the productive potential of grey alder

The aim of the study is to analyse the productive potential of grey alder (Alnus incana (L.) Moench) along an altitudinal gradient to verify coincidence ofproductive and ecological optimum and to identify climatic factors that control the growth. Along the altitudinal gradient of the river basin, dendrometric data has been analysed on the eight permanent research plots at the altitude of 525–705m. Correlations between standard chronology and average monthly climate characteristics were calculated for the period 1969–2015. Significant differences in the average basal area increments have been recognized among the investigated altitudinal zones. The highest basal area increment (1661±975mm<sup>2</sup>y<sup>-1</sup>) was detected in the zone of altitude 605m. and the average annual volume increment of the model grey alder stand was 4.59m<sup>3</sup>. The radial growth of grey alder has been positively affected only by the temperature of the current April and negatively by precipitation of the previous growing season. Based on the pointer year analysis can be claimed that condition of the root system is the most influential factor in relation to the radial growth and is dependent on water stress in the previous year. Investigated relationships may significantly influence decision making process in the forest management focused on grey alder re- or afforestation.

Influence of the ecological conditions on the productive potential of grey alder

The aim of the study is to analyse the productive potential of grey alder (Alnus incana (L.) Moench) along an altitudinal gradient to verify coincidence ofproductive and ecological optimum and to identify climatic factors that control the growth. Along the altitudinal gradient of the river basin, dendrometric data has been analysed on the eight permanent research plots at the altitude of 525–705m. Correlations between standard chronology and average monthly climate characteristics were calculated for the period 1969–2015. Significant differences in the average basal area increments have been recognized among the investigated altitudinal zones. The highest basal area increment (1661±975mm<sup>2</sup>y<sup>-1</sup>) was detected in the zone of altitude 605m. and the average annual volume increment of the model grey alder stand was 4.59m<sup>3</sup>. The radial growth of grey alder has been positively affected only by the temperature of the current April and negatively by precipitation of the previous growing season. Based on the pointer year analysis can be claimed that condition of the root system is the most influential factor in relation to the radial growth and is dependent on water stress in the previous year. Investigated relationships may significantly influence decision making process in the forest management focused on grey alder re- or afforestation.

Accounting for missing data in monthly temperature series: Testing rule‐of‐thumb omission of months with missing values

The “3/5 rule” is a commonly used rule‐of‐thumb for dealing with missing data when calculating monthly climate normals. The rule states that any month that is missing more than three consecutive daily values, or more than five daily values in total, should not be included in calculated monthly climate normals. We quantify the impact of missing data in a given year–month for between 1 and 25 missing values. As such, we describe the error the “3/5 rule” (and a related rule that we have dubbed the “4/10 rule”) permits. We tested the statistical robustness of these rules using observed temperature data from a temperate station and a tropical station. We show that, for observed data, the “3/5 rule” permits an average of between 0.06 and 0.07 standard deviations of error in the calculated monthly mean (ɛ) when three consecutive or five random values are missing. For its part, the “4/10 rule” permits a maximum ɛ of between 0.07 and 0.09 when four consecutive values are missing, or up to 0.10 when 10 random values are missing. The proportional impact of missing values was similar across variables. We performed a correlation analysis and show that each additional missing value from a year–month of data increases ɛ by between 0.008 and 0.018 for up to 19 missing values. There is a significant relationship between the lag‐1 autocorrelation of a year–month, and ɛ. ɛ can be reduced by simple linear interpolation when values are missing at random and the year–month exhibits lag‐1 autocorrelation. Overall, we find that the application of any “rule‐of‐thumb” should be based on the particular characteristics of the source data and the goals of the research project.

Sea level oscillations in Japan and China since the start of the 20th century and consequences for coastal management - Part 2: China pearl river delta region

This study examines low-frequency (>10 years) sea level variations in the Pearl River Delta (PRD) Region. The low-frequency sea level variability is relevant to regional sea level forecasting and flood risk management. Linear and parabolic fittings are applied to the monthly average mean sea levels (MSL) measured by tide gauges. A spectral analysis is performed of the time series of the MSL and the time series of the monthly climate indices of Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO)/NINO. Based on the analysis of a composite record of different tide gauges, the PRD Region sea levels, despite being complicated by the river discharge, have reduced similarity with either ENSO, NINO or PDO indices. The PRD Region sea levels have low frequency similarities with the sea level pattern in the Western North Pacific (e.g. Hosojima, Japan) and Western South Pacific (e.g. Sydney, Australia), while at higher frequencies the similarities reduce. One strong low frequency fluctuation of periodicity quasi-20 years is very clear and another of a longer periodicity of quasi-60 years is clear. There is then a relevant fluctuation of about 12 years of periodicity, of reduced amplitude compared to the quasi-20 years fluctuation. In the medium frequency range (<10 years), there are several components detected, but the intensity of the fluctuations is largely reduced compared to the fluctuation of 12 years periodicity. Regionally, the sea levels in the PRD region and Japan show no significant acceleration from 1900 to present, but only oscillations. This result is consistent with the other coastal area of the world where long-term tide gauges are located. Policy making, and management, should therefore focus on adaptive measures linked to the monitoring by tide gauges and Global Navigation Satellite System (GNSS) of relative sea level rise and land subsidence. Extreme sea level rise warnings based on predictions by never validated models, or speculations, that are defocusing coastal management from every other relevant situation, should be discharged.

Tree-Ring Carbon Isotope Records from the Western Oregon Cascade Mountains Primarily Record Summer Maximum Temperatures

Abstract Here we examine climatic influences on inter-annual variation in latewood tree growth (i.e. ring-width indices, RWILW) and stable-carbon isotope discrimination (Δ13CLW) from 1950 to 2013 at two SNOTEL snowpack monitoring sites in the Oregon Cascade Mountains. Douglas-fir and mountain hemlock trees were sampled at the lower and upper elevation sites where annual peak snow water equivalent (SWE) averaged 467 and 1128 mm, respectively. RWILW chronologies were poorly correlated among sites/species (r = 0.23, P = 0.063) and neither exhibited strong correlations with monthly or seasonal climate variables. By contrast, Δ13CLW chronologies were significantly correlated (r = 0.69, P < 0.001) and exhibited stronger climate responses. Multiple regression analyses identified summertime maximum temperature (Tmax) and/or vapor pressure deficit (VPD) as the primary drivers of Δ13CLW. Secondary influences included summertime precipitation, specific humidity, cloud cover, and SWE from the previous fall and winter...

Evaluating the Impact of Beach Nourishment on Surfing: Surf City, Long Beach Island, New Jersey, U.S.A.

Dally, W.R. and Osiecki, D.A., 2018. Evaluating the impact of beach nourishment on surfing: Surf City, Long Beach Island, New Jersey, U.S.A.Utilizing the Cornell University Long and Intermediate WAVE (COULWAVE) Boussinesq wave model, the effect of the construction of a conventional beach nourishment project in Surf City, New Jersey, on the quality of the local surf break is examined in detail. A 20-year-long nearshore synthetic wave record is first developed for use in creating a monthly wave climate “almanac” so that typical seasonal effects on surf-break quality can be objectively portrayed. The wave model is then run with preconstruction bathymetric conditions, and with three postconstruction surveys performed in subsequent months. Construction of the nourishment project was found to affect the quality of the surf break adversely by (1) compression of the surf zone, (2) an increase in the occurrence of “closeouts,” (3) a shift in breaker type toward collapsing breakers, particularly during high tide, and (4) an increase in wave reflection—findings that are in agreement with anecdotal testimony offered by local surfers. On the basis of modeling results conducted using the sequential postconstruction surveys and the wave almanac, it appears to have required nominally 21–22 months for the surf-break quality to return to preproject conditions. A paradigm shift in the design and construction of beach nourishment projects in the United States is required if such effects are to be avoided, and several options are offered and discussed.

Global soil consumption of atmospheric carbon monoxide: an analysis using a process-based biogeochemistry model

Abstract. Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric methane (CH4) dynamics. We develop a process-based biogeochemistry model to quantify the CO exchange between soils and the atmosphere with a 5 min internal time step at the global scale. The model is parameterized using the CO flux data from the field and laboratory experiments for 11 representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems using monthly climate forcing data. Global soil gross consumption, gross production, and net flux of the atmospheric CO are estimated to be from −197 to −180, 34 to 36, and −163 to −145 Tg CO yr−1 (1 Tg = 1012 g), respectively, when the model is driven with satellite-based atmospheric CO concentration data during 2000–2013. Tropical evergreen forest, savanna and deciduous forest areas are the largest sinks at 123 Tg CO yr−1. The soil CO gross consumption is sensitive to air temperature and atmospheric CO concentration, while the gross production is sensitive to soil organic carbon (SOC) stock and air temperature. By assuming that the spatially distributed atmospheric CO concentrations (∼ 128 ppbv) are not changing over time, the global mean CO net deposition velocity is estimated to be 0.16–0.19 mm s−1 during the 20th century. Under the future climate scenarios, the CO deposition velocity will increase at a rate of 0.0002–0.0013 mm s−1 yr−1 during 2014–2100, reaching 0.20–0.30 mm s−1 by the end of the 21st century, primarily due to the increasing temperature. Areas near the Equator, the eastern US, Europe and eastern Asia will be the largest sinks due to optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.

Limited evidence for CO2 -related growth enhancement in northern Rocky Mountain lodgepole pine populations across climate gradients.

Forests sequester large amounts of carbon annually and are integral in buffering against effects of global change. Increasing atmospheric CO2 may enhance photosynthesis and/or decrease stomatal conductance (gs ) thereby enhancing intrinsic water-use efficiency (iWUE), having potential indirect and direct benefits to tree growth. While increasing iWUE has been observed in most trees globally, enhanced growth is not ubiquitous, possibly due to concurrent climatic constraints on growth. To investigate our incomplete understanding of interactions between climate and CO2 and their impacts on tree physiology and growth, we used an environmental gradient approach. We combined dendrochronology with carbon isotope analysis (δ13 C) to assess the covariation of basal area increment (BAI) and iWUE over time in lodgepole pine. Trees were sampled at 18 sites spanning two climatically distinct elevation transects on the lee and windward sides of the Continental Divide, encompassing the majority of lodgepole pine's northern Rocky Mountain elevational range. We analyzed BAI and iWUE from 1950 to 2015, and explored correlations with monthly climate variables. As expected, iWUE increased at all sites. However, concurrent growth trends depended on site climatic water deficit (CWD). Significant growth increases occurred only at the driest sites, where increases in iWUE were strongest, while growth decreases were greatest at sites where CWD has been historically lowest. Late summer drought of the previous year negatively affected growth across sites. These results suggest that increasing iWUE, if strong enough, may indirectly benefit growth at drier sites by effectively extending the growing season via reductions in gs . Strong growth decreases at high elevation windward sites may reflect increasing water stress as a result of decreasing snowpack, which was not offset by greater iWUE. Our results imply that increasing iWUE driven by decreasing gs may benefit tree growth in limited scenarios, having implications for future carbon uptake potential of semiarid ecosystems.

Atmospheric and Surface Climate Associated With 1986–2013 Wildfires in North America

AbstractWe analyze climate simulations conducted with the RegCM3 regional climate model on 50‐ and 15‐km model grids to diagnose the dependence of wildfire incidence and area burned variations on monthly climate long‐term means and anomalies over North America for the period 1986–2013. We created a new wildfire database by merging the Fire Program Analysis Fire‐Occurrence Database, the National Interagency Fire Center Fire History Data, and the Canadian National Fire Database. The database includes 2,083,865 daily fire starts that burned a total of 1.25 × 108 ha in North America. We derive long‐term climatologies, standardized gamma indices, and composite climate anomalies of atmospheric circulation (500‐hPa height and wind) and various surface fields (e.g., solar radiation, soil moisture, vapor pressure deficit, and latent and sensible heat fluxes) to illustrate the climatology of burned area. The immediate and lagged monthly atmospheric circulation and surface climate anomalies differentiate high‐ and low‐fire years and the role of El Niño–Southern Oscillation in wildfire occurrence. Our approach demonstrates the association of the seasonal cycles of wildfire and climate and the strong role of climatic variability in modulating the seasonal cycle as a control of wildfire on monthly time scales.

Do Downscaled General Circulation Models Reliably Simulate Historical Climatic Conditions?

AbstractThe accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

Estimating shallow soil available water supply for Douglas-fir forests of the coastal Pacific Northwest: climate change impacts

Douglas-fir forests of the coastal Pacific Northwest experience yearly summer droughts; however, the variation in shallow soil available water supply throughout the region is not well understood nor is the effect of future climate change. Soil moisture sensors were installed in 60 Douglas-fir plantation forests over 6 years. Stands were grouped by physiographic regions to describe differences in climate and available water supply. Monthly available water supply (MAWS) (0–50 cm) was calculated as the average daily available moisture content. MAWS was modeled using monthly climate variables, and the equation was then used to predict the change in MAWS due to mild, moderate, and severe climate change predictions. Regional monthly air temperature and precipitation were strongly predictive of MAWS. Mild to severe climate change are predicted to decrease yearly available water supply by 8% to 19%, while summer available water supply will decrease from 25% to 72%. The greatest decreases due to climate change will be found in the coastal regions of Washington and Oregon due to greater negative effects of temperature on available water supply. Climate change, especially the most severe predictions, was shown to have a sizeable effect on shallow soil available water supply in coastal Douglas-fir forests.

Factors associated with human West Nile virus infection in Ontario: a generalized linear mixed modelling approach

BackgroundWest Nile Virus (WNV) is a mosquito-borne pathogen that has become established in North America. Risk for human infection varies geographically in accordance with climate and population factors. Though often asymptomatic, human WNV infection can cause febrile illness or, rarely, neurologic disease. WNV has become a public health concern in Canada since its introduction in 2001.MethodsTo identify predictors of human WNV incidence at the public health unit (PHU) level in Ontario, Canada, we combined data on environmental and population characteristics of PHUs with historical mosquito and human surveillance records from 2002 to 2013. We examined the associations between annual WNV incidence and monthly climate indices (e.g. minimum and maximum temperature, average precipitation), land cover (e.g. deciduous forest, water), population structure (e.g. age and sex composition) and the annual percentage of WNV-positive mosquito pools from 2002 to 2013. We then developed a generalized linear mixed model with a Poisson distribution adjusting for spatial autocorrelation and repeat measures. Further to this, to examine potential ‘early season’ predictors of WNV incidence in a given year, we developed a model based on winter and spring monthly climate indices.ResultsSeveral climate indices, including mean minimum temperature (o C) in February (RR = 1.58, CI: [1.42, 1.75]), and the annual percentage of WNV-positive mosquito pools (RR = 1.07, CI: [1.04, 1.11]) were significantly associated with human WNV incidence at the PHU level. Higher winter minimum temperatures were also strongly associated with annual WNV incidence in the ‘early season’ model (e.g. February minimum temperature (RR = 1.91, CI: [1.73, 2.12]).ConclusionsOur study demonstrates that early season temperature and precipitation indices, in addition to the percentage of WNV-positive mosquito pools in a given area, may assist in predicting the likelihood of a more severe human WNV season in southern regions of Ontario, where WNV epidemics occur sporadically.

Does sex matter? Gender-specificity and its influence on site-chronologies in the common dioecious shrub Juniperus communis

In recent years an increasing number of studies have shown shrubs to be reliable proxies of environmental conditions in regions where Trees − due to harsh climate conditions − are absent. Although many shrubs are monoecious, some are dioecious, which poses certain questions related to gender-specific growth as observed for trees in previous studies. Here, we address the questions whether dioecious shrubs, similar to trees, show growth differences between male and female plants, and − if so − whether this difference needs to be considered in terms of sample selection. We chose Juniperus communis. L., the most widely distributed woody plant, and a common and well-studied dioecious shrub species in the northern hemisphere, especially in the Boreal, Subarctic tundra and Alpine regions. Our samples were collected from four sites − three from the Ural Mountains and one site from Kirkenes in Norway. To see if there were differences in radial growth between sexes we performed four different analyses. First, we used multivariate explorative statistics to see if there were gender biased sub-populations and generally found no differences. Secondly, to compare growth over the lifetime of shrubs we computed cumulative annual increments of basal area which revealed no gender-specific growth patterns. Thirdly, to test if differences in radial growth between male and female shrubs affect the resulting site-chronology, we compared individual shrub chronologies with the site-chronology and found a significant differentiation between normalized correlations of gender-specific chronologies to the site-chronology. This significant difference was restricted to an overall comparison, but not evident at individual site-level. Lastly, we compared correlations of gender-specific chronologies and a mean site-chronology with monthly climate records to find only very few meaningful differences in their responses. In summary, we could not detect any clear gender-specific growth pattern in Juniperus communis but observed a trend towards more non-climatic signals in female junipers which may affect the resulting site-chronology.

Changes in Annual, Seasonal and Monthly Climate and Its Impacts on Runoff in the Hutuo River Basin, China

Much attention has focused on the effects of precipitation (P) and temperature (T) changes on runoff (R); however, the impacts of other climatic factors need to be studied further. Moreover, the monthly and seasonal scale also need to be investigated. In this paper, we investigated the characteristics of changes in annual, seasonal, and monthly hydroclimatic variables, including R, P, T, sunshine duration (SD), relative humidity (RH), and wind speed (WS), between 1956 and 2015 in the Hutuo River basin (HTRB) using the nonparametric Mann-Kendall test, the cumulative anomaly test and the Precipitation-Runoff double cumulative curve method. Additionally, we assessed the contributions of climatic factors to changes in R in the HTRB between 1956 and 2015 using the climate elasticity method. The results indicated that significant downward trends were found for both annual and seasonal R, SD, RH, and WS. In contrast, there was a nonsignificant decrease in annual P; specifically, P significantly increased in spring and winter, but P insignificantly decreased in summer and autumn. Annual and seasonal T increased significantly. The annual R showed an abrupt change in 1979; thus, the entire study period from 1956 to 2015 was divided into two periods: the baseline period (i.e., 1956–1978) and the change period (i.e., 1979–2015). The elasticities in the climatic factors were calculated using the climate elasticity method, and the elasticity values of P, T, SD, RH, and WS were 1.84, −1.07, −2.79, 1.73, and −0.45, respectively. Increasing T was the main cause of the decline in R, and decreasing SD had a large negative contribution to the decline in R in the HTRB. This study will help researchers understand the interactions between climate change and hydrological processes at the basin scale and promote water resource management and watershed planning.