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- Author or Editor: Toby N. Carlson x
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A simple one-layer, quasi-geostrophic model of vertical motion and surface pressure tendency is derived and used to illustrate relationships between various parameters such as stability, latitude, wind speed, and the sea-level pressure tendency for sinusoidal disturbances in a baroclinic current. It is shown in the model that the wavelength at which the maximum surface pressure tendency occurs varies with the Rossby radius of deformation, as well as with the zonal wind speed and amplitude of the disturbance. In the case of a simulated polar cyclone, which exists at high latitudes under conditions of low static stability and shallow atmospheric depth, the wavelength of maximum growth rate is relatively short.
The primary virtue of this model is that it can be used as a pedagogical tool for explaining quantitatively, but without lengthy calculations, the behavior of surface pressure systems.
A simple one-layer, quasi-geostrophic model of vertical motion and surface pressure tendency is derived and used to illustrate relationships between various parameters such as stability, latitude, wind speed, and the sea-level pressure tendency for sinusoidal disturbances in a baroclinic current. It is shown in the model that the wavelength at which the maximum surface pressure tendency occurs varies with the Rossby radius of deformation, as well as with the zonal wind speed and amplitude of the disturbance. In the case of a simulated polar cyclone, which exists at high latitudes under conditions of low static stability and shallow atmospheric depth, the wavelength of maximum growth rate is relatively short.
The primary virtue of this model is that it can be used as a pedagogical tool for explaining quantitatively, but without lengthy calculations, the behavior of surface pressure systems.
The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information.
A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.
The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information.
A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.
Abstract
There is great interest in wind-borne mineral dust because of the role that dust plays in climate by modulating solar radiation and cloud properties. Today, much research focuses on North Africa because it is Earth’s largest and most persistently active dust source. Moreover, this region is expected to be greatly impacted by climate change, which would affect dust emission rates. Interest in dust was stimulated over 50 years ago when it was discovered that African dust was frequently transported across the Atlantic in great quantities. Here we report on the initial discovery of African dust in the Caribbean Basin. We show that there were three independent “first” discoveries of African dust in the 1950s through the 1960s. In each case, the discoverers were not seeking dust but, rather, they had other research objectives. The meteorological context of African dust transport was first elucidated in 1969 with the characterization of the Saharan air layer (SAL) and its role in effecting the efficient transport of African dust over great distances to the Western Hemisphere. The link between dust transport and African climate was established in the 1970s and 1980s when dust transport to the Caribbean increased greatly following the onset of severe drought in the Sahel. Here we chronicle these events and show how they contributed to our current state of knowledge.
Abstract
There is great interest in wind-borne mineral dust because of the role that dust plays in climate by modulating solar radiation and cloud properties. Today, much research focuses on North Africa because it is Earth’s largest and most persistently active dust source. Moreover, this region is expected to be greatly impacted by climate change, which would affect dust emission rates. Interest in dust was stimulated over 50 years ago when it was discovered that African dust was frequently transported across the Atlantic in great quantities. Here we report on the initial discovery of African dust in the Caribbean Basin. We show that there were three independent “first” discoveries of African dust in the 1950s through the 1960s. In each case, the discoverers were not seeking dust but, rather, they had other research objectives. The meteorological context of African dust transport was first elucidated in 1969 with the characterization of the Saharan air layer (SAL) and its role in effecting the efficient transport of African dust over great distances to the Western Hemisphere. The link between dust transport and African climate was established in the 1970s and 1980s when dust transport to the Caribbean increased greatly following the onset of severe drought in the Sahel. Here we chronicle these events and show how they contributed to our current state of knowledge.
Abstract
Simsphere, a soil–vegetation–atmosphere–transfer (SVAT) model developed at The Pennsylvania State University, can be downloaded from the web for use by students and researchers. In existence for several decades, Simsphere has figured in both the classroom and in research at several universities. As such, Simsphere has been supported by a knowledgeable group of academic users and has been applied in a variety of applications, such as in remote sensing of surface soil water content and in the assessment of water and ozone stresses on plants. This paper describes the model and how it can be downloaded and run.
Abstract
Simsphere, a soil–vegetation–atmosphere–transfer (SVAT) model developed at The Pennsylvania State University, can be downloaded from the web for use by students and researchers. In existence for several decades, Simsphere has figured in both the classroom and in research at several universities. As such, Simsphere has been supported by a knowledgeable group of academic users and has been applied in a variety of applications, such as in remote sensing of surface soil water content and in the assessment of water and ozone stresses on plants. This paper describes the model and how it can be downloaded and run.
A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale numerical weather-prediction models by modifying model output with geophysical and land-cover data. Mesoscale forecasts generated by the MOE technique are displayed as color-class maps overlaid on perspective plots of terrain. The MOE technique has been demonstrated in the generation of mesoscale maximum-temperature and minimum-temperature forecasts for case-study days of clear-sky conditions over the Commonwealth of Pennsylvania. The generated forecasts were evaluated using data from selected climatological stations.
A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale numerical weather-prediction models by modifying model output with geophysical and land-cover data. Mesoscale forecasts generated by the MOE technique are displayed as color-class maps overlaid on perspective plots of terrain. The MOE technique has been demonstrated in the generation of mesoscale maximum-temperature and minimum-temperature forecasts for case-study days of clear-sky conditions over the Commonwealth of Pennsylvania. The generated forecasts were evaluated using data from selected climatological stations.
