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Abstract
We investigated how weather conditions and environmental factors affect the spatiotemporal variability in Culex pipiens population using the data collected from a surveillance program in Ontario, Canada, from 2005 to 2008. This study assessed the relative influences of temperature and precipitation on the temporal patterns of mosquito abundance using harmonic analysis and examined the associations with major landscape predictors, including land-use type, population density, and elevation, on the spatial patterns of mosquito abundance. The intensity of trapping efforts on the mosquito abundance at each trap site was examined by comparing the spatial distribution of mosquito abundance in relation to the spatial intensity of trapping efforts. The authors used a mixed effects modeling approach to account for potential dependent structure in mosquito surveillance data due to repeated observations at single trap sites and/or similar mosquito abundance at nearby trap sites each week. The model fit was improved by taking into account the nested structure of mosquito surveillance data and incorporating the temporal correlation in random effects.
Abstract
We investigated how weather conditions and environmental factors affect the spatiotemporal variability in Culex pipiens population using the data collected from a surveillance program in Ontario, Canada, from 2005 to 2008. This study assessed the relative influences of temperature and precipitation on the temporal patterns of mosquito abundance using harmonic analysis and examined the associations with major landscape predictors, including land-use type, population density, and elevation, on the spatial patterns of mosquito abundance. The intensity of trapping efforts on the mosquito abundance at each trap site was examined by comparing the spatial distribution of mosquito abundance in relation to the spatial intensity of trapping efforts. The authors used a mixed effects modeling approach to account for potential dependent structure in mosquito surveillance data due to repeated observations at single trap sites and/or similar mosquito abundance at nearby trap sites each week. The model fit was improved by taking into account the nested structure of mosquito surveillance data and incorporating the temporal correlation in random effects.
Abstract
This paper aims to define atmospheric pathways related with the occurrence of daily winter low temperature episodes (LTE) in England, for the 26-yr period 1974–99, and to reveal possible associations with increased mortality rates. For this purpose, backward airmass trajectories, corresponding to LTE in five regions of England, were deployed. A statistically significant increase in mortality levels, at the 0.05 level, was found for LTE, compared to non-LTE days across all five regions. Seven categories of atmospheric trajectory patterns associated with LTE were identified: east, local, west, North Atlantic, Arctic, southwest, and Scandinavian. Consideration of the link between airmass trajectory patterns and mortality levels by region revealed a possible west-to-east split in the nature of air masses connected with elevated mortality. Specifically, for the West Midlands and northwest regions, relatively warm winter weather conditions from the west, most likely associated with the eastward progression of low pressure systems, are allied with the highest daily average mortality counts, whereas, for the northeast, Humberside/York, and southeast regions, cold continental air advection from northern or eastern Europe, which lasts for several days and is linked with either a blocking pattern over the western margins of Europe or an intense high pressure anomaly over eastern or northern Europe, appears important in mortality terms. This finding confirms that winter weather health associations are complex, such that climate setting and airmass climatology need to be taken into account when considering climate and health relationships.
Abstract
This paper aims to define atmospheric pathways related with the occurrence of daily winter low temperature episodes (LTE) in England, for the 26-yr period 1974–99, and to reveal possible associations with increased mortality rates. For this purpose, backward airmass trajectories, corresponding to LTE in five regions of England, were deployed. A statistically significant increase in mortality levels, at the 0.05 level, was found for LTE, compared to non-LTE days across all five regions. Seven categories of atmospheric trajectory patterns associated with LTE were identified: east, local, west, North Atlantic, Arctic, southwest, and Scandinavian. Consideration of the link between airmass trajectory patterns and mortality levels by region revealed a possible west-to-east split in the nature of air masses connected with elevated mortality. Specifically, for the West Midlands and northwest regions, relatively warm winter weather conditions from the west, most likely associated with the eastward progression of low pressure systems, are allied with the highest daily average mortality counts, whereas, for the northeast, Humberside/York, and southeast regions, cold continental air advection from northern or eastern Europe, which lasts for several days and is linked with either a blocking pattern over the western margins of Europe or an intense high pressure anomaly over eastern or northern Europe, appears important in mortality terms. This finding confirms that winter weather health associations are complex, such that climate setting and airmass climatology need to be taken into account when considering climate and health relationships.
Abstract
The Lajas Formation in the Neuquén Basin, Argentina, consists of a succession of mainly deltaic deposits. In the Middle Jurassic (170 million years ago), the basin was in western Gondwana roughly at the same paleolatitude as its present location (32°–40°S). Decimeter-scale, interbedded, coarser-grained and finer-grained beds in channelized and nonchannelized deltaic deposits have been interpreted as a product of variability in river discharge. The coarser-grained sandstone beds have erosional bases and contain mudstone clasts; internal cross bedding is commonly directed paleoseawards. These beds are interpreted as deposition during river-flood conditions. In contrast, the finer-grained beds are composed of interlaminated sandstone and mudstone, deposited during interflood periods. Bidirectional ripples and millimeter-scale sand–mud laminae suggest the influence of tides. This sedimentological evidence raises the question of whether these cycles represent annual variability in fluvial input. To answer this question, a simulation using the Fast Ocean Atmosphere Model for the Middle Jurassic was run to equilibrium. The model shows that the paleoclimate of the Neuquén Basin was characterized by a strong seasonal cycle, with a wet winter and a dry summer. Model runs suggest that February mean temperatures were 28°C with 4-mm precipitation (±4 mm standard deviation) per month, whereas August mean temperatures were 8°C with 34-mm precipitation (±17 mm standard deviation) per month. The strong seasonal cycles in the simulation, representing 24% of the variance in the precipitation time series, suggest that the sedimentological cycles represent annual variations. The simulation also suggests a Middle Jurassic climate where increased seasonality of precipitation occurred farther poleward than previously thought.
Abstract
The Lajas Formation in the Neuquén Basin, Argentina, consists of a succession of mainly deltaic deposits. In the Middle Jurassic (170 million years ago), the basin was in western Gondwana roughly at the same paleolatitude as its present location (32°–40°S). Decimeter-scale, interbedded, coarser-grained and finer-grained beds in channelized and nonchannelized deltaic deposits have been interpreted as a product of variability in river discharge. The coarser-grained sandstone beds have erosional bases and contain mudstone clasts; internal cross bedding is commonly directed paleoseawards. These beds are interpreted as deposition during river-flood conditions. In contrast, the finer-grained beds are composed of interlaminated sandstone and mudstone, deposited during interflood periods. Bidirectional ripples and millimeter-scale sand–mud laminae suggest the influence of tides. This sedimentological evidence raises the question of whether these cycles represent annual variability in fluvial input. To answer this question, a simulation using the Fast Ocean Atmosphere Model for the Middle Jurassic was run to equilibrium. The model shows that the paleoclimate of the Neuquén Basin was characterized by a strong seasonal cycle, with a wet winter and a dry summer. Model runs suggest that February mean temperatures were 28°C with 4-mm precipitation (±4 mm standard deviation) per month, whereas August mean temperatures were 8°C with 34-mm precipitation (±17 mm standard deviation) per month. The strong seasonal cycles in the simulation, representing 24% of the variance in the precipitation time series, suggest that the sedimentological cycles represent annual variations. The simulation also suggests a Middle Jurassic climate where increased seasonality of precipitation occurred farther poleward than previously thought.
Abstract
In the first half of this research, this study examines the trend in tropical cyclone (TC) activity over the economically important northwest Western Australia (NWA) TC basin (equator–40°S, 80°–140°E) based on statistical analyses of the International Best Track Archive for Climate Stewardship (IBTrACS) and large-scale environmental variables, which are known to be closely linked to the formation and longevity of TCs, from NCEP–NCAR reanalyses. In the second half, changes in TC activity from climate model projections for 2000–60 are compared for (i) no scenario change (CNTRL) and (ii) the moderate IPCC Special Report on Emission Scenarios (SRES) A1B scenario (EGHG). The aims are to (i) determine differences in mean annual TC frequency and intensity trends, (ii) test for differences between genesis and decay positions of CNTRL and EGHG projections using a nonparametric permutation test, and (iii) use kernel density estimation (KDE) for a cluster analysis of CNTRL and EGHG genesis and decay positions and generate their probability distribution functions.
The main findings are there is little difference in the mean TC number over the period, but there is a difference in mean intensity; CNTRL and EGHG projections differ in mean genesis and decay positions in both latitude and longitude; and the KDE reveals just one cluster in both CNTRL and EGHG mean genesis and decay positions. The EGHG KDE is possibly disjoint, with a wider longitudinal spread. The results can be explained in terms of physical, meteorological, and sea surface temperature (SST) conditions, which provide natural limits to the spread of the genesis and decay points.
Abstract
In the first half of this research, this study examines the trend in tropical cyclone (TC) activity over the economically important northwest Western Australia (NWA) TC basin (equator–40°S, 80°–140°E) based on statistical analyses of the International Best Track Archive for Climate Stewardship (IBTrACS) and large-scale environmental variables, which are known to be closely linked to the formation and longevity of TCs, from NCEP–NCAR reanalyses. In the second half, changes in TC activity from climate model projections for 2000–60 are compared for (i) no scenario change (CNTRL) and (ii) the moderate IPCC Special Report on Emission Scenarios (SRES) A1B scenario (EGHG). The aims are to (i) determine differences in mean annual TC frequency and intensity trends, (ii) test for differences between genesis and decay positions of CNTRL and EGHG projections using a nonparametric permutation test, and (iii) use kernel density estimation (KDE) for a cluster analysis of CNTRL and EGHG genesis and decay positions and generate their probability distribution functions.
The main findings are there is little difference in the mean TC number over the period, but there is a difference in mean intensity; CNTRL and EGHG projections differ in mean genesis and decay positions in both latitude and longitude; and the KDE reveals just one cluster in both CNTRL and EGHG mean genesis and decay positions. The EGHG KDE is possibly disjoint, with a wider longitudinal spread. The results can be explained in terms of physical, meteorological, and sea surface temperature (SST) conditions, which provide natural limits to the spread of the genesis and decay points.
Abstract
The mechanisms driving trends and variability of the normalized difference vegetation index (NDVI) for tundra in Alaska along the Beaufort, east Chukchi, and east Bering Seas for 1982–2013 are evaluated in the context of remote sensing, reanalysis, and meteorological station data as well as regional modeling. Over the entire season the tundra vegetation continues to green; however, biweekly NDVI has declined during the early part of the growing season in all of the Alaskan tundra domains. These springtime declines coincide with increased snow depth in spring documented in northern Alaska. The tundra region generally has warmed over the summer but intraseasonal analysis shows a decline in midsummer land surface temperatures. The midsummer cooling is consistent with recent large-scale circulation changes characterized by lower sea level pressures, which favor increased cloud cover. In northern Alaska, the sea-breeze circulation is strengthened with an increase in atmospheric moisture/cloudiness inland when the land surface is warmed in a regional model, suggesting the potential for increased vegetation to feedback onto the atmospheric circulation that could reduce midsummer temperatures. This study shows that both large- and local-scale climate drivers likely play a role in the observed seasonality of NDVI trends.
Abstract
The mechanisms driving trends and variability of the normalized difference vegetation index (NDVI) for tundra in Alaska along the Beaufort, east Chukchi, and east Bering Seas for 1982–2013 are evaluated in the context of remote sensing, reanalysis, and meteorological station data as well as regional modeling. Over the entire season the tundra vegetation continues to green; however, biweekly NDVI has declined during the early part of the growing season in all of the Alaskan tundra domains. These springtime declines coincide with increased snow depth in spring documented in northern Alaska. The tundra region generally has warmed over the summer but intraseasonal analysis shows a decline in midsummer land surface temperatures. The midsummer cooling is consistent with recent large-scale circulation changes characterized by lower sea level pressures, which favor increased cloud cover. In northern Alaska, the sea-breeze circulation is strengthened with an increase in atmospheric moisture/cloudiness inland when the land surface is warmed in a regional model, suggesting the potential for increased vegetation to feedback onto the atmospheric circulation that could reduce midsummer temperatures. This study shows that both large- and local-scale climate drivers likely play a role in the observed seasonality of NDVI trends.
Abstract
The very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of the India Odisha state since the supercyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10 000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18 000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance that benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three-tier disaster management agencies at central, state, and district levels.
Abstract
The very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of the India Odisha state since the supercyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10 000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18 000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance that benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three-tier disaster management agencies at central, state, and district levels.
Abstract
While estimates of the impact of climate change on health are necessary for health care planners and climate change policy makers, models to produce quantitative estimates remain scarce. This study describes a freely available dynamic simulation model parameterized for three West Nile virus vectors, which provides an effective tool for studying vectorborne disease risk due to climate change. The Dynamic Mosquito Simulation Model is parameterized with species-specific temperature-dependent development and mortality rates. Using downscaled daily weather data, this study estimates mosquito population dynamics under current and projected future climate scenarios for multiple locations across the country. Trends in mosquito abundance were variable by location; however, an extension of the vector activity periods, and by extension disease risk, was almost uniformly observed. Importantly, midsummer decreases in abundance may be offset by shorter extrinsic incubation periods, resulting in a greater proportion of infective mosquitoes. Quantitative descriptions of the effect of temperature on the virus and mosquito are critical to developing models of future disease risk.
Abstract
While estimates of the impact of climate change on health are necessary for health care planners and climate change policy makers, models to produce quantitative estimates remain scarce. This study describes a freely available dynamic simulation model parameterized for three West Nile virus vectors, which provides an effective tool for studying vectorborne disease risk due to climate change. The Dynamic Mosquito Simulation Model is parameterized with species-specific temperature-dependent development and mortality rates. Using downscaled daily weather data, this study estimates mosquito population dynamics under current and projected future climate scenarios for multiple locations across the country. Trends in mosquito abundance were variable by location; however, an extension of the vector activity periods, and by extension disease risk, was almost uniformly observed. Importantly, midsummer decreases in abundance may be offset by shorter extrinsic incubation periods, resulting in a greater proportion of infective mosquitoes. Quantitative descriptions of the effect of temperature on the virus and mosquito are critical to developing models of future disease risk.
Abstract
Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.
Abstract
Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.
Abstract
The rapid expansion of irrigation since the 1950s has significantly depleted the Ogallala Aquifer. This study examines the warm-season climate impacts of irrigation over the Ogallala using high-resolution (6.33 km) simulations of a version of the Weather Research and Forecasting (WRF) Model that has been coupled to the Community Land Model with dynamic crop growth (WRF-CLM4crop). To examine how dynamic crops influence the simulated impact of irrigation, the authors compare simulations with dynamic crops to simulations with a fixed annual cycle of crop leaf area index (static crops). For each crop scheme, simulations were completed with and without irrigation for 9 years that represent the range of observed precipitation. Reduced temperature and precipitation biases occur with dynamic versus static crops. Fundamental differences in the precipitation response to irrigation occur with dynamic crops, as enhanced surface roughness weakens low-level winds, enabling more water from irrigation to remain over the region. Greater simulated rainfall increases (12.42 mm) occur with dynamic crops compared to static crops (9.08 mm), with the greatest differences during drought years (+20.1 vs +5.9 mm). Water use for irrigation significantly impacts precipitation with dynamic crops (R 2 = 0.29), but no relationship exists with static crops. Dynamic crop growth has the largest effect on the simulated impact of irrigation on precipitation during drought years, with little impact during nondrought years, highlighting the need to simulate the dynamic response of crops to environmental variability within Earth system models to improve prediction of the agroecosystem response to variations in climate.
Abstract
The rapid expansion of irrigation since the 1950s has significantly depleted the Ogallala Aquifer. This study examines the warm-season climate impacts of irrigation over the Ogallala using high-resolution (6.33 km) simulations of a version of the Weather Research and Forecasting (WRF) Model that has been coupled to the Community Land Model with dynamic crop growth (WRF-CLM4crop). To examine how dynamic crops influence the simulated impact of irrigation, the authors compare simulations with dynamic crops to simulations with a fixed annual cycle of crop leaf area index (static crops). For each crop scheme, simulations were completed with and without irrigation for 9 years that represent the range of observed precipitation. Reduced temperature and precipitation biases occur with dynamic versus static crops. Fundamental differences in the precipitation response to irrigation occur with dynamic crops, as enhanced surface roughness weakens low-level winds, enabling more water from irrigation to remain over the region. Greater simulated rainfall increases (12.42 mm) occur with dynamic crops compared to static crops (9.08 mm), with the greatest differences during drought years (+20.1 vs +5.9 mm). Water use for irrigation significantly impacts precipitation with dynamic crops (R 2 = 0.29), but no relationship exists with static crops. Dynamic crop growth has the largest effect on the simulated impact of irrigation on precipitation during drought years, with little impact during nondrought years, highlighting the need to simulate the dynamic response of crops to environmental variability within Earth system models to improve prediction of the agroecosystem response to variations in climate.
Abstract
The role of land–atmosphere coupling in modulating the impact of land-use change (LUC) on regional climate extremes remains uncertain. Using the Weather and Research Forecasting Model, this study combines the Global Land–Atmosphere Coupling Experiment with regional LUC to assess the combined impact of land–atmosphere coupling and LUC on simulated temperature extremes. The experiment is applied to an ensemble of planetary boundary layer (PBL) and cumulus parameterizations to determine the sensitivity of the results to model physics. Results show a consistent weakening in the soil moisture–maximum temperature coupling strength with LUC irrespective of the model physics. In contrast, temperature extremes show an asymmetric response to LUC dependent on the choice of PBL scheme, which is linked to differences in the parameterization of vertical transport. This influences convective precipitation, contributing a positive feedback on soil moisture and consequently on the partitioning of the surface turbulent fluxes. The results suggest that the impact of LUC on temperature extremes depends on the land–atmosphere coupling that in turn depends on the choice of PBL. Indeed, the sign of the temperature change in hot extremes resulting from LUC can be changed simply by altering the choice of PBL. The authors also note concerns over the metrics used to measure coupling strength that reflect changes in variance but may not respond to LUC-type perturbations.
Abstract
The role of land–atmosphere coupling in modulating the impact of land-use change (LUC) on regional climate extremes remains uncertain. Using the Weather and Research Forecasting Model, this study combines the Global Land–Atmosphere Coupling Experiment with regional LUC to assess the combined impact of land–atmosphere coupling and LUC on simulated temperature extremes. The experiment is applied to an ensemble of planetary boundary layer (PBL) and cumulus parameterizations to determine the sensitivity of the results to model physics. Results show a consistent weakening in the soil moisture–maximum temperature coupling strength with LUC irrespective of the model physics. In contrast, temperature extremes show an asymmetric response to LUC dependent on the choice of PBL scheme, which is linked to differences in the parameterization of vertical transport. This influences convective precipitation, contributing a positive feedback on soil moisture and consequently on the partitioning of the surface turbulent fluxes. The results suggest that the impact of LUC on temperature extremes depends on the land–atmosphere coupling that in turn depends on the choice of PBL. Indeed, the sign of the temperature change in hot extremes resulting from LUC can be changed simply by altering the choice of PBL. The authors also note concerns over the metrics used to measure coupling strength that reflect changes in variance but may not respond to LUC-type perturbations.
