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- Author or Editor: A. E. MacDonald x
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Abstract
Mesoscale bounded derivative initialization (BDI) is utilized to derive dynamical constraints, from which elliptic equations are formulated to derive smooth initial fields over complex terrain for mesoscale models. The initialization is implemented specifically for the quasi-nonhydrostatic (QNH) model. This study presents the first real data application of the mesoscale BDI and the QNH model to simulate a mesoscale storm that produced heavy precipitation along the Colorado Front Range. In this study, the focus is on (i) smooth numerical solution over complex terrain, (ii) baroclinic instability associated with condensational heating and high mountains, and (iii) the simulation of orographic precipitation. Numerical results show that initial fields derived from BDI were smooth and evolved smoothly in the QNH model for 48 h. It is noteworthy that the smooth solution existed up to the lateral boundaries. During the 48-h simulation, the midtropospheric storm moved freely in and out of the limited-area domain as if there were no lateral boundaries. The mesoscale storm for northeast Colorado was initiated by the persistent upslope easterlies and strong upward motions that triggered heavy precipitation. The simulated precipitation amounts and pattern were in good agreement with those observed. In general, both the large-scale dynamic system and the mesoscale precipitation event evolved smoothly and accurately, which indicates the value of BDI and QNH for mesoscale weather prediction.
Abstract
Mesoscale bounded derivative initialization (BDI) is utilized to derive dynamical constraints, from which elliptic equations are formulated to derive smooth initial fields over complex terrain for mesoscale models. The initialization is implemented specifically for the quasi-nonhydrostatic (QNH) model. This study presents the first real data application of the mesoscale BDI and the QNH model to simulate a mesoscale storm that produced heavy precipitation along the Colorado Front Range. In this study, the focus is on (i) smooth numerical solution over complex terrain, (ii) baroclinic instability associated with condensational heating and high mountains, and (iii) the simulation of orographic precipitation. Numerical results show that initial fields derived from BDI were smooth and evolved smoothly in the QNH model for 48 h. It is noteworthy that the smooth solution existed up to the lateral boundaries. During the 48-h simulation, the midtropospheric storm moved freely in and out of the limited-area domain as if there were no lateral boundaries. The mesoscale storm for northeast Colorado was initiated by the persistent upslope easterlies and strong upward motions that triggered heavy precipitation. The simulated precipitation amounts and pattern were in good agreement with those observed. In general, both the large-scale dynamic system and the mesoscale precipitation event evolved smoothly and accurately, which indicates the value of BDI and QNH for mesoscale weather prediction.
Abstract
In recent years, there has been extensive study of the mathematical basis of weather prediction leading to a new system of continuous equations that are well posed, and a set of conditions that make discrete atmospheric and other models stable and potentially more accurate. In particular, the theory deals with initial boundary value problems that admit multiple timescales. Using this theory, a quasi-nonhydrostatic model called QNH was developed at NOAA’s Forecast Systems Laboratory. The model is fully compressible and explicit in the vertical as well as the horizontal direction. It is characterized by a parameter, “α” (typically the square of the vertical to horizontal aspect ratio), which multiplies the hydrostatic terms in the vertical equation of motion. In this paper, the authors describe the theoretical basis for the use of these models in mesoscale weather prediction. It is shown that for the mesoscale, the parameter has the effect of decreasing both the frequency and amplitude of the gravity wave perturbation response to small-scale impulses in forcing and to unbalanced initial conditions. This allows a modeler to choose a length scale below which gravity wave generation is suppressed. A weakness of the approach is that the hydrostatic adjustment process is slowed down. The analysis indicates that the parameter does not have an effect on the Rossby waves, the larger horizontal-scale gravity waves, nor on forced solutions such as those created by heating. The bounded derivative initialization is discussed. Since the speeds of the vertical acoustic waves are decreased, quasi-nonhydrostatic models can calculate the vertical equations explicitly and still meet the Courant–Friedrichs–Levy criteria. It is concluded that the unique characteristics of quasi-nonhydrostatic models may make them valuable in mesoscale weather prediction, particularly of clouds and precipitation.
Abstract
In recent years, there has been extensive study of the mathematical basis of weather prediction leading to a new system of continuous equations that are well posed, and a set of conditions that make discrete atmospheric and other models stable and potentially more accurate. In particular, the theory deals with initial boundary value problems that admit multiple timescales. Using this theory, a quasi-nonhydrostatic model called QNH was developed at NOAA’s Forecast Systems Laboratory. The model is fully compressible and explicit in the vertical as well as the horizontal direction. It is characterized by a parameter, “α” (typically the square of the vertical to horizontal aspect ratio), which multiplies the hydrostatic terms in the vertical equation of motion. In this paper, the authors describe the theoretical basis for the use of these models in mesoscale weather prediction. It is shown that for the mesoscale, the parameter has the effect of decreasing both the frequency and amplitude of the gravity wave perturbation response to small-scale impulses in forcing and to unbalanced initial conditions. This allows a modeler to choose a length scale below which gravity wave generation is suppressed. A weakness of the approach is that the hydrostatic adjustment process is slowed down. The analysis indicates that the parameter does not have an effect on the Rossby waves, the larger horizontal-scale gravity waves, nor on forced solutions such as those created by heating. The bounded derivative initialization is discussed. Since the speeds of the vertical acoustic waves are decreased, quasi-nonhydrostatic models can calculate the vertical equations explicitly and still meet the Courant–Friedrichs–Levy criteria. It is concluded that the unique characteristics of quasi-nonhydrostatic models may make them valuable in mesoscale weather prediction, particularly of clouds and precipitation.
Abstract
A new mesoscale weather prediction model, called QNH, is described. It is characterized by a parameter that multiplies the hydrostatic terms in the vertical equation of motion. Models of this type are referred to generically as “quasi-nonhydrostatic.” The quasi-nonhydrostatic parameter gives the model a character that is essentially nonhydrostatic, but with properties that are theoretically thought to result in smoother, more accurate, and stable predictions. The model is unique in a number of other aspects, such as its treatment of lateral boundary conditions, the use of explicit calculation in the vertical direction, and the use of the bounded derivative theory for initialization. This paper reports on the design and test of the QNH model, which represents the first time the applicability of this type of model has been demonstrated for full-physics, mesoscale weather prediction. The dynamic formulation, discretization, numerical formulation, and physics packages of the model are described. The results of a comprehensive validation of the model are presented. The validation includes barotropic, baroclinic (Eady wave), mountain wave, tropical storm, and sea breeze tests. A simulation of a winter storm (with updated lateral boundary conditions) is presented, which shows that the model has significant skill in forecasting terrain-forced heavy precipitation. It is concluded that the QNH model may be valuable for mesoscale weather prediction.
Abstract
A new mesoscale weather prediction model, called QNH, is described. It is characterized by a parameter that multiplies the hydrostatic terms in the vertical equation of motion. Models of this type are referred to generically as “quasi-nonhydrostatic.” The quasi-nonhydrostatic parameter gives the model a character that is essentially nonhydrostatic, but with properties that are theoretically thought to result in smoother, more accurate, and stable predictions. The model is unique in a number of other aspects, such as its treatment of lateral boundary conditions, the use of explicit calculation in the vertical direction, and the use of the bounded derivative theory for initialization. This paper reports on the design and test of the QNH model, which represents the first time the applicability of this type of model has been demonstrated for full-physics, mesoscale weather prediction. The dynamic formulation, discretization, numerical formulation, and physics packages of the model are described. The results of a comprehensive validation of the model are presented. The validation includes barotropic, baroclinic (Eady wave), mountain wave, tropical storm, and sea breeze tests. A simulation of a winter storm (with updated lateral boundary conditions) is presented, which shows that the model has significant skill in forecasting terrain-forced heavy precipitation. It is concluded that the QNH model may be valuable for mesoscale weather prediction.
Abstract
The seasonal change in the development of Aleutian low pressure systems from early fall to early winter is analyzed using a combination of meteorological reanalysis fields, satellite sea surface temperature (SST) data, and satellite wind data. The time period of the study is September–December 2002, although results are shown to be representative of the long-term climatology. Characteristics of the storms were documented as they progressed across the North Pacific, including their path, central pressure, deepening rate, and speed of translation. Clear patterns emerged. Storms tended to deepen in two distinct geographical locations—the Gulf of Alaska in early fall and the western North Pacific in late fall. In the Gulf of Alaska, a quasi-permanent “notch” in the SST distribution is argued to be of significance. The signature of the notch is imprinted in the atmosphere, resulting in a region of enhanced cyclonic potential vorticity in the lower troposphere that is conducive for storm development. Later in the season, as winter approaches and the Sea of Okhotsk becomes partially ice covered and cold, the air emanating from the Asian continent leads to enhanced baroclinicity in the region south of Kamchatka. This corresponds to enhanced storm cyclogenesis in that region. Consequently, there is a seasonal westward migration of the dominant lobe of the Aleutian low. The impact of the wind stress curl pattern resulting from these two regions of storm development on the oceanic circulation is investigated using historical hydrography. It is argued that the seasonal bimodal input of cyclonic vorticity from the wind may be partly responsible for the two distinct North Pacific subarctic gyres.
Abstract
The seasonal change in the development of Aleutian low pressure systems from early fall to early winter is analyzed using a combination of meteorological reanalysis fields, satellite sea surface temperature (SST) data, and satellite wind data. The time period of the study is September–December 2002, although results are shown to be representative of the long-term climatology. Characteristics of the storms were documented as they progressed across the North Pacific, including their path, central pressure, deepening rate, and speed of translation. Clear patterns emerged. Storms tended to deepen in two distinct geographical locations—the Gulf of Alaska in early fall and the western North Pacific in late fall. In the Gulf of Alaska, a quasi-permanent “notch” in the SST distribution is argued to be of significance. The signature of the notch is imprinted in the atmosphere, resulting in a region of enhanced cyclonic potential vorticity in the lower troposphere that is conducive for storm development. Later in the season, as winter approaches and the Sea of Okhotsk becomes partially ice covered and cold, the air emanating from the Asian continent leads to enhanced baroclinicity in the region south of Kamchatka. This corresponds to enhanced storm cyclogenesis in that region. Consequently, there is a seasonal westward migration of the dominant lobe of the Aleutian low. The impact of the wind stress curl pattern resulting from these two regions of storm development on the oceanic circulation is investigated using historical hydrography. It is argued that the seasonal bimodal input of cyclonic vorticity from the wind may be partly responsible for the two distinct North Pacific subarctic gyres.
