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- Author or Editor: Martin C. Todd x
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Abstract
Long-term records of winter ice duration, formation, and breakup dates (1869–1996) and maximum thickness (1950–95) on Lake Baikal are analyzed to determine the nature of temporal trends and the relationship with the large-scale atmospheric circulation. There are highly significant trends of decreasing ice duration (and thickness) over the period, associated with later ice formation and earlier breakup dates. These trends are broadly in line with those of winter air temperatures in the region. Variability in Lake Baikal ice formation date, duration, and thickness is significantly related to winter temperatures over a wide area from the Caspian Sea to the Pacific and from northern India to the Kara Sea off the northern coast of Siberia. Thus, Lake Baikal ice cover is a robust indicator of continental-scale winter climate. Correlation and composite analysis of surface and upper-atmospheric fields reveal that interannual variability in ice cover is associated with a tripolar pattern of upper-level geopotential height anomalies. In years of high (low) ice duration and thickness, significant positive (negative) 700-hPa geopotential height anomalies occur over northern Siberia and the Arctic, complemented by negative (positive) anomalies over central-eastern Asia and southern Europe. This structure induces an anomalous meridional flow regime in eastern Siberia with cold (warm) temperature advection from the northeast (southwest) in years of high (low) ice duration and thickness. Analysis of the lower-tropospheric heat budget during years of extreme early and late ice onset indicates that horizontal temperature advection is largely responsible for the observed temperature anomalies. These circulation anomalies are associated with certain recognized patterns of Northern Hemisphere climate variability, notably the Scandinavian and Arctic Oscillation patterns. Significant correlations also occur between Lake Baikal ice cover and the Pacific–North American pattern in the previous winter. The component of variability in Lake Baikal ice cover unrelated to these modes of Northern Hemisphere climate variability is associated with the position and intensity of the Siberian high.
Abstract
Long-term records of winter ice duration, formation, and breakup dates (1869–1996) and maximum thickness (1950–95) on Lake Baikal are analyzed to determine the nature of temporal trends and the relationship with the large-scale atmospheric circulation. There are highly significant trends of decreasing ice duration (and thickness) over the period, associated with later ice formation and earlier breakup dates. These trends are broadly in line with those of winter air temperatures in the region. Variability in Lake Baikal ice formation date, duration, and thickness is significantly related to winter temperatures over a wide area from the Caspian Sea to the Pacific and from northern India to the Kara Sea off the northern coast of Siberia. Thus, Lake Baikal ice cover is a robust indicator of continental-scale winter climate. Correlation and composite analysis of surface and upper-atmospheric fields reveal that interannual variability in ice cover is associated with a tripolar pattern of upper-level geopotential height anomalies. In years of high (low) ice duration and thickness, significant positive (negative) 700-hPa geopotential height anomalies occur over northern Siberia and the Arctic, complemented by negative (positive) anomalies over central-eastern Asia and southern Europe. This structure induces an anomalous meridional flow regime in eastern Siberia with cold (warm) temperature advection from the northeast (southwest) in years of high (low) ice duration and thickness. Analysis of the lower-tropospheric heat budget during years of extreme early and late ice onset indicates that horizontal temperature advection is largely responsible for the observed temperature anomalies. These circulation anomalies are associated with certain recognized patterns of Northern Hemisphere climate variability, notably the Scandinavian and Arctic Oscillation patterns. Significant correlations also occur between Lake Baikal ice cover and the Pacific–North American pattern in the previous winter. The component of variability in Lake Baikal ice cover unrelated to these modes of Northern Hemisphere climate variability is associated with the position and intensity of the Siberian high.
Abstract
The low-level jet (LLJ) over the Bodélé depression in northern Chad is a newly identified feature. Strong LLJ events are responsible for the emission of large quantities of mineral dust from the depression, the world’s largest single dust source, and its subsequent transport to West Africa, the tropical Atlantic, and beyond. Accurate simulation of this key dust-generating atmospheric feature is, therefore, an important requirement for dust models. The objectives of the present study are (i) to evaluate the ability of regional climate models (RCMs) and global analyses/reanalyses to represent this feature, and (ii) to determine the driving mechanisms of the LLJ and its strong diurnal cycle. Observational data obtained during the Bodélé Dust Experiment (BoDEx 2005) are utilized for comparison. When suitably configured, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) RCM can represent very accurately many of the key features of the jet including the structure, diurnal cycle, and day-to-day variability. Surface winds are also well reproduced, including the peak winds, which activate dust emission. Model fidelity is, however, strongly dependent on the boundary layer parameterization scheme, surface roughness, and vertical resolution in the lowest layers. A model horizontal resolution of a few tens of kilometers is sufficient to resolve most of the key features of the LLJ, while in global analyses/reanalyses many features of the LLJ are not adequately represented. Idealized RCM simulations indicate that under strong synoptic forcing the surrounding orography of the Tibesti and Ennedi Mountains acts to focus the LLJ onto the Bodélé and to accelerate the jet by ∼40%. From the RCM experiments it is diagnosed that the pronounced diurnal cycle of the Bodélé LLJ is largely a result of varying eddy viscosity, with elevated heating/cooling over the Tibesti Mountains to the north as a second-order contribution.
Abstract
The low-level jet (LLJ) over the Bodélé depression in northern Chad is a newly identified feature. Strong LLJ events are responsible for the emission of large quantities of mineral dust from the depression, the world’s largest single dust source, and its subsequent transport to West Africa, the tropical Atlantic, and beyond. Accurate simulation of this key dust-generating atmospheric feature is, therefore, an important requirement for dust models. The objectives of the present study are (i) to evaluate the ability of regional climate models (RCMs) and global analyses/reanalyses to represent this feature, and (ii) to determine the driving mechanisms of the LLJ and its strong diurnal cycle. Observational data obtained during the Bodélé Dust Experiment (BoDEx 2005) are utilized for comparison. When suitably configured, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) RCM can represent very accurately many of the key features of the jet including the structure, diurnal cycle, and day-to-day variability. Surface winds are also well reproduced, including the peak winds, which activate dust emission. Model fidelity is, however, strongly dependent on the boundary layer parameterization scheme, surface roughness, and vertical resolution in the lowest layers. A model horizontal resolution of a few tens of kilometers is sufficient to resolve most of the key features of the LLJ, while in global analyses/reanalyses many features of the LLJ are not adequately represented. Idealized RCM simulations indicate that under strong synoptic forcing the surrounding orography of the Tibesti and Ennedi Mountains acts to focus the LLJ onto the Bodélé and to accelerate the jet by ∼40%. From the RCM experiments it is diagnosed that the pronounced diurnal cycle of the Bodélé LLJ is largely a result of varying eddy viscosity, with elevated heating/cooling over the Tibesti Mountains to the north as a second-order contribution.
Abstract
Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple “wet get wetter” pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north–south SST gradient over the Indian Ocean, consistent with a “warmest get wetter” mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed.
Abstract
Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple “wet get wetter” pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north–south SST gradient over the Indian Ocean, consistent with a “warmest get wetter” mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed.
Abstract
Southern Africa is characterized by a high degree of rainfall variability, affecting agriculture and hydrology, among other sectors. This paper aims to investigate such variability and to identify stable relationships with its potential drivers in the climate system; such relationships may be used as the basis for the statistical downscaling of climate model outputs, for example. The analysis uses generalized linear models (GLMs). The GLMs are fitted to twentieth-century observational data for the period 1957–2006 to characterize the dependence of monthly precipitation occurrences and amounts upon the climate indicators of interest. In contrast with many of the analyses that have previously been used to investigate controls on precipitation in the region, GLMs allow for the investigation of the relationships between different components of the climate system (geographical and climatic drivers) simultaneously. Six climate factors were found to drive part of the rainfall variability in the region, and their modeled effect upon rainfall occurrences and amounts resulted in general agreement with previous studies. Among the retained indices, relative humidity and El Niño accounted for the highest degree of explained variability. The location and intensity of the jet stream were also found to have a statistically significant and physically meaningful effect upon rainfall variability.
Abstract
Southern Africa is characterized by a high degree of rainfall variability, affecting agriculture and hydrology, among other sectors. This paper aims to investigate such variability and to identify stable relationships with its potential drivers in the climate system; such relationships may be used as the basis for the statistical downscaling of climate model outputs, for example. The analysis uses generalized linear models (GLMs). The GLMs are fitted to twentieth-century observational data for the period 1957–2006 to characterize the dependence of monthly precipitation occurrences and amounts upon the climate indicators of interest. In contrast with many of the analyses that have previously been used to investigate controls on precipitation in the region, GLMs allow for the investigation of the relationships between different components of the climate system (geographical and climatic drivers) simultaneously. Six climate factors were found to drive part of the rainfall variability in the region, and their modeled effect upon rainfall occurrences and amounts resulted in general agreement with previous studies. Among the retained indices, relative humidity and El Niño accounted for the highest degree of explained variability. The location and intensity of the jet stream were also found to have a statistically significant and physically meaningful effect upon rainfall variability.
