Browse
Abstract
Human-induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2, yet present-day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modeling the impact of LUC needs to accurately simulate CO2-driven changes in precipitation and snowfall and incorporate accurate, dynamic vegetation distribution.
Abstract
Human-induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2, yet present-day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modeling the impact of LUC needs to accurately simulate CO2-driven changes in precipitation and snowfall and incorporate accurate, dynamic vegetation distribution.
Abstract
Regional land surface and remote ocean variables have been considered as primary forcings altering the variability of summer rainfall over the Sahel. However, previous studies usually examined the two components separately. In this study, the authors apply statistical methods including correlation, multivariate linear regression, and Granger causality analyses to investigate the relative roles of spring–summer sea surface temperature (SST) and vegetation activity in explaining the Sahel summer rainfall variability from 1982 to 2006. The remotely sensed normalized difference vegetation index (NDVI) is used as an indicator of land surface forcing. This study shows that spring and summer SSTs over the subtropical North Atlantic have significant positive correlations with summer rainfall. The spring and summer NDVIs over the Sahel have significant negative and positive correlations, respectively, with summer rainfall. Based on the multivariate linear regression analysis, the adjusted R 2 for the integrated model with both the land and ocean variables is 0.70. It is around 2 times larger than the model with SST alone (adjusted R 2 = 0.36). To further investigate the causal relationships of summer rainfall with the SST and NDVI variables selected in the integrated multivariate model, the authors perform a Granger causality test. This study finds that summer NDVI over the Sahel does Granger cause summer rainfall over the Sahel, while the summer SST over the subtropical North Atlantic does not Granger cause the summer rainfall. The results indicate that the regional land surface forcing has a relatively strong contribution to Sahel summer rainfall, compared to the remote ocean forcing, during the recent decades.
Abstract
Regional land surface and remote ocean variables have been considered as primary forcings altering the variability of summer rainfall over the Sahel. However, previous studies usually examined the two components separately. In this study, the authors apply statistical methods including correlation, multivariate linear regression, and Granger causality analyses to investigate the relative roles of spring–summer sea surface temperature (SST) and vegetation activity in explaining the Sahel summer rainfall variability from 1982 to 2006. The remotely sensed normalized difference vegetation index (NDVI) is used as an indicator of land surface forcing. This study shows that spring and summer SSTs over the subtropical North Atlantic have significant positive correlations with summer rainfall. The spring and summer NDVIs over the Sahel have significant negative and positive correlations, respectively, with summer rainfall. Based on the multivariate linear regression analysis, the adjusted R 2 for the integrated model with both the land and ocean variables is 0.70. It is around 2 times larger than the model with SST alone (adjusted R 2 = 0.36). To further investigate the causal relationships of summer rainfall with the SST and NDVI variables selected in the integrated multivariate model, the authors perform a Granger causality test. This study finds that summer NDVI over the Sahel does Granger cause summer rainfall over the Sahel, while the summer SST over the subtropical North Atlantic does not Granger cause the summer rainfall. The results indicate that the regional land surface forcing has a relatively strong contribution to Sahel summer rainfall, compared to the remote ocean forcing, during the recent decades.
Abstract
Stand-clearing disturbances, which remove most of the tree cover but are followed by forest regrowth, affect extensive areas annually, yet each event is usually much smaller than a typical grid cell in Earth system climate models. This study argues that the approach taken to account for the resulting subgrid cell dynamic heterogeneity substantially affects the computation of land–atmosphere exchanges. The authors investigated in a simplified model the effects of three such approaches on the computation of albedo over boreal forests. It was found that the simplest approach—in which any new disturbance-created patch was immediately merged with the rest of the grid cell—underestimated the annual reflected solar radiation by ~3 W m−2 on average (a relative error of 15%) compared with the most accurate approach—in which albedo computations were performed for each individual subgrid patch. This study also investigated an intermediate approach, in which each patch was tracked individually, but albedo was estimated from a much smaller number of subgrid tiles grouping patches having a similar amount of tree cover. Results from this third approach converged quickly toward the most accurate results as the number of tiles increased and were robust to changes in the thresholds used to assign patches to specific tiles. When computing time prevents implementing the most accurate approach in Earth system climate models, the results advocate for using strategies similar to the intermediate approach in order to avoid biasing the net radiative forcing of stand-clearing disturbances toward a warming impact, at least over boreal forests.
Abstract
Stand-clearing disturbances, which remove most of the tree cover but are followed by forest regrowth, affect extensive areas annually, yet each event is usually much smaller than a typical grid cell in Earth system climate models. This study argues that the approach taken to account for the resulting subgrid cell dynamic heterogeneity substantially affects the computation of land–atmosphere exchanges. The authors investigated in a simplified model the effects of three such approaches on the computation of albedo over boreal forests. It was found that the simplest approach—in which any new disturbance-created patch was immediately merged with the rest of the grid cell—underestimated the annual reflected solar radiation by ~3 W m−2 on average (a relative error of 15%) compared with the most accurate approach—in which albedo computations were performed for each individual subgrid patch. This study also investigated an intermediate approach, in which each patch was tracked individually, but albedo was estimated from a much smaller number of subgrid tiles grouping patches having a similar amount of tree cover. Results from this third approach converged quickly toward the most accurate results as the number of tiles increased and were robust to changes in the thresholds used to assign patches to specific tiles. When computing time prevents implementing the most accurate approach in Earth system climate models, the results advocate for using strategies similar to the intermediate approach in order to avoid biasing the net radiative forcing of stand-clearing disturbances toward a warming impact, at least over boreal forests.
Abstract
Measurements of air temperature and precipitation at 35 stations in Hubei Province, China, during 1962–2011 are used to investigate the regional climate change. There is an increasing trend for observed air temperature (0.23°C decade−1), which is slightly higher than that from multiple model simulations/predictions [phase 5 of CMIP (CMIP5) datasets] (0.16°C decade−1). The observed precipitation increases at the rate of 11.4 mm decade−1, while the CMIP5 results indicate a much lower decreasing trend (0.8 mm decade−1) in this region. To examine the ecological responses to the climate changes in Hubei Province, annual gross primary productivity (GPP) and net primary productivity (NPP) products during 2000–10 and leaf area index (LAI) products during 1981–2011 are also analyzed. It is discovered that GPP, NPP, and LAI increase at the rate of 1.8 TgC yr−1 yr−1, 1.1 TgC yr−1 yr−1, and 0.14 m2 m−2 decade−1, respectively. A linear model is further used to conduct the correlation analyses between climatic parameters (i.e., air temperature and precipitation) and ecological indicators (i.e., GPP, NPP, and LAI). The results indicate that the air temperature has a significant positive correlation with LAI (R 2 = 0.311) and GPP (R 2 = 0.189); precipitation is positively correlated with NPP (R 2 = 0.209). Thus, it is concluded that the air temperature exerts a stronger effect on the ecosystem than precipitation in Hubei Province over the past decades.
Abstract
Measurements of air temperature and precipitation at 35 stations in Hubei Province, China, during 1962–2011 are used to investigate the regional climate change. There is an increasing trend for observed air temperature (0.23°C decade−1), which is slightly higher than that from multiple model simulations/predictions [phase 5 of CMIP (CMIP5) datasets] (0.16°C decade−1). The observed precipitation increases at the rate of 11.4 mm decade−1, while the CMIP5 results indicate a much lower decreasing trend (0.8 mm decade−1) in this region. To examine the ecological responses to the climate changes in Hubei Province, annual gross primary productivity (GPP) and net primary productivity (NPP) products during 2000–10 and leaf area index (LAI) products during 1981–2011 are also analyzed. It is discovered that GPP, NPP, and LAI increase at the rate of 1.8 TgC yr−1 yr−1, 1.1 TgC yr−1 yr−1, and 0.14 m2 m−2 decade−1, respectively. A linear model is further used to conduct the correlation analyses between climatic parameters (i.e., air temperature and precipitation) and ecological indicators (i.e., GPP, NPP, and LAI). The results indicate that the air temperature has a significant positive correlation with LAI (R 2 = 0.311) and GPP (R 2 = 0.189); precipitation is positively correlated with NPP (R 2 = 0.209). Thus, it is concluded that the air temperature exerts a stronger effect on the ecosystem than precipitation in Hubei Province over the past decades.
Abstract
Previous studies have shown strong negative correlation between multidecadal signatures in length of day (LOD)—an inverse measure of Earth’s rotational rate—and various climate indices. Mechanisms remain elusive. Climate processes are insufficient to explain observed rotational variability, leading many to hypothesize external (astronomical) forcing as a common source for observed low-frequency signatures. Here, an internal source, a core-to-climate, one-way chain of causality, is hypothesized. To test hypothesis feasibility, a recently published, model-estimated forced component is removed from an observed dataset of Northern Hemisphere (NH) surface temperatures to isolate the intrinsic component of climate variability, enhancing its comparison with LOD. To further explore the rotational connection to climate indices, the LOD anomaly record is compared with sea surface temperatures (SSTs)—global and regional. Because climate variability is most intensely expressed in the North Atlantic sector, LOD is compared to the dominant oceanic pattern there—the Atlantic multidecadal oscillation (AMO). Results reveal that the LOD-related signal is more global than regional, being greater in the global SST record than in the AMO or in global-mean (land + ocean) or land-only surface temperatures. Furthermore, the strong (4σ) correlation of LOD with the estimated NH intrinsic component is consistent with the view proffered here, one of an internally generated, core-to-climate process imprinted on both the climate and Earth’s rotational rate. While the exact mechanism is not elucidated by this study’s results, reported correlations of geomagnetic and volcanic activity with LOD offer prospects to explain observations in the context of a core-to-climate chain of causality.
Abstract
Previous studies have shown strong negative correlation between multidecadal signatures in length of day (LOD)—an inverse measure of Earth’s rotational rate—and various climate indices. Mechanisms remain elusive. Climate processes are insufficient to explain observed rotational variability, leading many to hypothesize external (astronomical) forcing as a common source for observed low-frequency signatures. Here, an internal source, a core-to-climate, one-way chain of causality, is hypothesized. To test hypothesis feasibility, a recently published, model-estimated forced component is removed from an observed dataset of Northern Hemisphere (NH) surface temperatures to isolate the intrinsic component of climate variability, enhancing its comparison with LOD. To further explore the rotational connection to climate indices, the LOD anomaly record is compared with sea surface temperatures (SSTs)—global and regional. Because climate variability is most intensely expressed in the North Atlantic sector, LOD is compared to the dominant oceanic pattern there—the Atlantic multidecadal oscillation (AMO). Results reveal that the LOD-related signal is more global than regional, being greater in the global SST record than in the AMO or in global-mean (land + ocean) or land-only surface temperatures. Furthermore, the strong (4σ) correlation of LOD with the estimated NH intrinsic component is consistent with the view proffered here, one of an internally generated, core-to-climate process imprinted on both the climate and Earth’s rotational rate. While the exact mechanism is not elucidated by this study’s results, reported correlations of geomagnetic and volcanic activity with LOD offer prospects to explain observations in the context of a core-to-climate chain of causality.
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.
