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- Author or Editor: R. B. Fritz x
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Abstract
In a cooperative field study of the planetary boundary layer, three optical wind sensors were placed around a 300 m meteorological tower in a 450 m equilateral triangle 3–4 m above the terrain. It was found that the convergence measured by the three-sensor system correlates well with in situ measurements of vertical wind by anemometers located on the tower at heights up to 300 m during the occurrence of thermal plumes. By analyzing the correlation between the optically measured convergence and the vertical wind measurements made on the tower, the inversion layer, if below the top of the tower, can usually be located in the early morning when thermal plumes are active. The space-averaged horizontal wind vectors measured by the optical system have good, though not perfect, agreement with the tower measurements at the lowest layer (10 m above the ground), and with the measurements of a nearby network of surface anemometers. A comparison of the optically measured convergence with the direction of the surface horizontal wind indicates some effect of irregular terrain.
Abstract
In a cooperative field study of the planetary boundary layer, three optical wind sensors were placed around a 300 m meteorological tower in a 450 m equilateral triangle 3–4 m above the terrain. It was found that the convergence measured by the three-sensor system correlates well with in situ measurements of vertical wind by anemometers located on the tower at heights up to 300 m during the occurrence of thermal plumes. By analyzing the correlation between the optically measured convergence and the vertical wind measurements made on the tower, the inversion layer, if below the top of the tower, can usually be located in the early morning when thermal plumes are active. The space-averaged horizontal wind vectors measured by the optical system have good, though not perfect, agreement with the tower measurements at the lowest layer (10 m above the ground), and with the measurements of a nearby network of surface anemometers. A comparison of the optically measured convergence with the direction of the surface horizontal wind indicates some effect of irregular terrain.
Abstract
Validation of the decadal to centennial timescale variability of coupled climate models is limited by the scarcity of long observational records. Proxy indicators of climate, such as tree rings, ice cores, etc., can be utilized for this purpose. This study presents a quantitative comparison of the variability of the third version of the Hadley Centre ocean–atmosphere coupled model with a network of temperature-sensitive tree-ring densities covering the northern high latitudes. The tree-ring density records are up to 600 years long, and temperature reconstructions based on two different methods of removing the bias due to changing tree age are used. The first is a standard method that may remove low-frequency variability on timescales of the order of the tree life span (i.e., multidecadal to century timescales). The second (age-band decomposition) maintains low-frequency variability by only comparing similar age tree rings at each site, thus avoiding the need to remove the age effect (but at the cost of greater uncertainty in the earlier years when fewer tree cores are available). The variability of the model control simulation, which represents only the internal variability of the climate system, agrees reasonably well with the tree-ring reconstructions using the standard method at the regional level, although the model may underestimate the variance of mean Northern Hemisphere land temperature by as much as a factor of 1.8 on all timescales if one takes account of the uncertainty in the tree-ring reconstructions. Agreement with the age-band decomposition tree-ring reconstructions is less good with the model underestimating the hemispheric variance by as much as a factor of 2.1 on all timescales and by as much as a factor of 3.0 on decadal to centennial timescales. Underestimation of the natural variability of climate by the model would be serious as it may lead to false detections of climate change or erroneously low uncertainty estimates in future climate predictions. However, it is shown that some of this underestimation may be due to the lack of natural climate forcing in the model control simulation due, for example, to solar variability and volcanic eruptions. The study suggests that further quantification of the uncertainties in the proxy data, and inclusion of natural climate forcings in the model simulations, are important steps in making comparisons of climate models with the proxy record over the last 1000 years.
Abstract
Validation of the decadal to centennial timescale variability of coupled climate models is limited by the scarcity of long observational records. Proxy indicators of climate, such as tree rings, ice cores, etc., can be utilized for this purpose. This study presents a quantitative comparison of the variability of the third version of the Hadley Centre ocean–atmosphere coupled model with a network of temperature-sensitive tree-ring densities covering the northern high latitudes. The tree-ring density records are up to 600 years long, and temperature reconstructions based on two different methods of removing the bias due to changing tree age are used. The first is a standard method that may remove low-frequency variability on timescales of the order of the tree life span (i.e., multidecadal to century timescales). The second (age-band decomposition) maintains low-frequency variability by only comparing similar age tree rings at each site, thus avoiding the need to remove the age effect (but at the cost of greater uncertainty in the earlier years when fewer tree cores are available). The variability of the model control simulation, which represents only the internal variability of the climate system, agrees reasonably well with the tree-ring reconstructions using the standard method at the regional level, although the model may underestimate the variance of mean Northern Hemisphere land temperature by as much as a factor of 1.8 on all timescales if one takes account of the uncertainty in the tree-ring reconstructions. Agreement with the age-band decomposition tree-ring reconstructions is less good with the model underestimating the hemispheric variance by as much as a factor of 2.1 on all timescales and by as much as a factor of 3.0 on decadal to centennial timescales. Underestimation of the natural variability of climate by the model would be serious as it may lead to false detections of climate change or erroneously low uncertainty estimates in future climate predictions. However, it is shown that some of this underestimation may be due to the lack of natural climate forcing in the model control simulation due, for example, to solar variability and volcanic eruptions. The study suggests that further quantification of the uncertainties in the proxy data, and inclusion of natural climate forcings in the model simulations, are important steps in making comparisons of climate models with the proxy record over the last 1000 years.
Abstract
Rain rate during light precipitation in winter was measured with high temporal resolution optical systems at a site in Illinois. In addition to quasi-periodic variations, a clearly sinusoidal oscillation in rain rate was found imbedded in the general precipitation. The phase shift in the occurrence of the oscillation at two sensors, with the simultaneous recording of sinusoidal fluctuations of the attenuation of a millimeter wave signal, allows simulation of this particular rain pattern by a simple model. The basic mechanism that can produce a rain event with such a sinusoidal pattern is not clearly understood.
Abstract
Rain rate during light precipitation in winter was measured with high temporal resolution optical systems at a site in Illinois. In addition to quasi-periodic variations, a clearly sinusoidal oscillation in rain rate was found imbedded in the general precipitation. The phase shift in the occurrence of the oscillation at two sensors, with the simultaneous recording of sinusoidal fluctuations of the attenuation of a millimeter wave signal, allows simulation of this particular rain pattern by a simple model. The basic mechanism that can produce a rain event with such a sinusoidal pattern is not clearly understood.
