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Kevin W. Manning
and
Christopher A. Davis

Abstract

A statistical verification of real-time forecasts from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model version 5 (MM5) examines several model biases noted in numerical forecasts prepared for the Winter Icing and Storms Project’s 1994 field experiment. Verification of MM5 forecasts against satellite and radiosonde data reveals a strong cloudy bias in the mid- to upper troposphere, significant moist biases aloft and near the surface, and a deep cold bias through much of the troposphere.

The cloudy bias and upper-level moist bias are traced to an inappropriate assumption in the microphysical parameterization. Simple changes to the parameterization greatly improve the cloud forecast. A portion of the deep cold bias is attributed to the simple parameterization of atmospheric radiation used for the forecasts. The low-level cold and moist biases are in large part due to the climatological values of soil moisture availability as a function of land-use category. Experiments with a one-dimensional column model further quantify the sensitivity of low-level temperatures to the soil moisture availability values. While an immediate improvement in model results can be achieved by selection of more appropriate values of moisture availability, ultimately a detailed initialization and parameterization of soil moisture is needed.

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Jason C. Knievel
,
David A. Ahijevych
, and
Kevin W. Manning

Abstract

The authors demonstrate that much can be learned about the performance of a numerical weather prediction (NWP) model by examining the temporal modes of its simulated rainfall. Observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network are used to evaluate the rainfall frequency, and its diurnal and semidiurnal modes, in simulations made by a preliminary version of the Weather Research and Forecasting (WRF) model for the conterminous United States during the summer of 2003.

Simulations and observations were broadly similar in the normalized amplitudes of their diurnal and semidiurnal modes, but not in the modes' phases, and not in overall frequency of rain. Simulated rain fell too early, and light rain was too frequent. The model also did not produce the distinct, nocturnal maximum in rainfall frequency that is integral to the hydrologic cycle of the Great Plains. The authors provide evidence that there were regional and phenomenological dependencies to the WRF model's performance.

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Stanley B. Trier
,
Fei Chen
, and
Kevin W. Manning

Abstract

A coupled convection-resolving mesoscale atmosphere–land surface model (LSM) is used to investigate land surface–planetary boundary layer (PBL) interactions responsible for the initiation of deep, moist convection over the southern Great Plains of the United States on 19 June 1998. A high-resolution land data assimilation system provides initial conditions to the LSM, facilitating examination of soil moisture effects on forecasts of deep convection.

During the late morning and early afternoon, the southwestern portion of a simulated southwest–northeast (SW–NE)-oriented surface water vapor gradient zone evolves into an intense dryline, unlike the northeastern portion, which remains relatively weak. Despite these regional differences, midafternoon convection initiation occurs within a ∼100-km-wide region of enhanced PBL depth along much of the SW–NE extent of the water vapor gradient zone. The afternoon PBL depth maximum results from a midmorning-to-early afternoon surface sensible heat flux maximum of similar horizontal scale, and is reinforced by an ensuing mesoscale (L ∼ 100 km) vertical circulation. Finescale (L ∼ 10 km) PBL circulations that directly trigger deep convection are confined within this mesoscale region that contains the deeper and more unstable PBL.

Comparisons among different simulations reveal that thermodynamic stability and simulated convection initiation are affected by details in the initial soil moisture distribution, through differences in the partitioning of the surface heat and moisture fluxes. These differences in convection initiation among simulations occur despite only minor differences in the overall structure of the afternoon surface moisture gradient zone, which has potentially important implications for operational forecasts of deep convection.

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Stanley B. Trier
,
Christopher A. Davis
,
David A. Ahijevych
, and
Kevin W. Manning

Abstract

Herein, the parcel buoyancy minimum (B min) defined in Part I of this two-part paper is used to examine physical processes influencing thermodynamic destabilization in environments of mature simulated mesoscale convective systems (MCSs). These convection-permitting simulations consist of twelve 24-h forecasts during two 6-day periods characterized by two different commonly occurring warm-season weather regimes that support MCSs over the central United States.

A composite analysis of 22 MCS environments is performed where cases are stratified into surface-based (SB), elevated squall (ES), and elevated nonsquall (ENS) categories. A gradual reduction of lower-tropospheric B min to values indicative of small convection inhibition, occurring over horizontal scales >100 km from the MCS leading edge, is a common aspect of each category. These negative buoyancy decreases are most pronounced for the ES and ENS environments, in which convective available potential energy (CAPE) is greatest for air parcels originating above the surface. The implication is that the vertical structure of the mesoscale environment plays a key role in the evolution and sustenance of convection long after convection initiation and internal MCS circulations develop, particularly in elevated systems.

Budgets of B min forcing are computed for the nocturnally maturing ES and ENS composites. Though warm advection occurs through the entire 1.5-km-deep layer comprising the vertical intersection of the largest environmental CAPE and smallest environmental B min magnitude, the net effect of terms involving vertical motion dominate the destabilization in both composites. These effects include humidity increases in air parcels due to vertical moisture advection and the adiabatic cooling of the environment above.

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Stanley B. Trier
,
Christopher A. Davis
,
David A. Ahijevych
, and
Kevin W. Manning

Abstract

A method based on parcel theory is developed to quantify mesoscale physical processes responsible for the removal of inhibition energy for convection initiation (CI). Convection-permitting simulations of three mesoscale convective systems (MCSs) initiating in differing environments are then used to demonstrate the method and gain insights on different ways that mesoscale thermodynamic destabilization can occur.

Central to the method is a thermodynamic quantity B min, which is the buoyancy minimum experienced by an air parcel lifted from a specified height. For the cases studied, vertical profiles of B min using air parcels originating at different heights are qualitatively similar to corresponding profiles of convective inhibition (CIN). Though it provides less complete information than CIN, an advantage of using B min is that it does not require vertical integration, which simplifies budget calculations that enable attribution of the thermodynamic destabilization to specific physical processes. For a specified air parcel, B min budgets require knowledge of atmospheric forcing at only the parcel origination level and some approximate level where B min occurs.

In a case of simulated daytime surface-based CI, destabilization in the planetary boundary layer (PBL) results from a combination of surface fluxes and upward motion above the PBL. Upward motion effects dominate the destabilizing effects of horizontal advections in two different simulated elevated CI cases, where the destabilizing layer occurs from 1 to 2.5 km AGL. In an elevated case with strong warm advection, changes to the parcel at its origination level dominate the reduction of negative buoyancy, whereas for a case lacking warm advection, adiabatic temperature changes to the environment near the location of B min dominate.

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Christopher A. Davis
,
Kevin W. Manning
,
Richard E. Carbone
,
Stanley B. Trier
, and
John D. Tuttle

Abstract

A recent study by Carbone et al. revealed “episodes” of warm-season rainfall over North America characterized as coherently propagating signals often linking multiple mesoscale convective systems over spatial scales of 1000–3000 km and timescales of 1–3 days. The present study examines whether these propagating signals are found in two numerical weather prediction (NWP) models commonly used today, namely, the Eta Model from the National Centers for Environmental Prediction and the newly developed Weather Research and Forecast (WRF) model. The authors find that the diurnal cycle of rainfall over much of the United States east of the Rockies is poorly represented, particularly over the central United States, where a nocturnal rainfall maximum is observed. Associated with this nocturnal maximum is an axis of propagating rainfall emanating from the western High Plains in the late afternoon, extending across the Midwest overnight, and occasionally continuing to the Appalachians on the second day. This propagation is largely unrepresented in NWP models. Only where rainfall maximizes during the late afternoon and remains local do models perform reasonably well. Even in these areas there is a tendency, especially in the Eta Model, for rainfall to occur several hours too early.

Using idealized simulations, the authors demonstrate that fundamental propagation errors arise using cumulus parameterizations contained in NWP models. The authors also show that errors in the timing of convection, combined with propagation errors, lead to a poor phase locking of predicted rainfall to diurnal and orographic forcing. This, in turn, degrades the coherence of propagating signals in diurnally averaged rainfall frequency diagrams. The authors suggest that until these “zeroth-order” statistical shortcomings in NWP models are rectified, prospects for accurate short-range, model-based prediction of warm-season rainfall remain poor.

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David H. Bromwich
,
Andrew J. Monaghan
,
Kevin W. Manning
, and
Jordan G. Powers

Abstract

In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program’s field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model optimized for use over ice sheets. The modeling system consists of several domains ranging in horizontal resolution from 90 km covering a large part of the Southern Hemisphere to 3.3 km over the complex terrain surrounding McMurdo, the hub of U.S. operations. The performance of the 30-km AMPS domain versus observations from manned and automatic weather stations is statistically evaluated for a 2-yr period from September 2001 through August 2003. The simulated 12–36-h surface pressure and near-surface temperature at most sites have correlations of r > 0.95 and r > 0.75, respectively, and small biases. Surface wind speeds reflect the complex topography and generally have correlations between 0.5 and 0.6, and positive biases of 1–2 m s−1. In the free atmosphere, r > 0.95 (geopotential height), r > 0.9 (temperature), and r > 0.8 (wind speed) at most sites. Over the annual cycle, there is little interseasonal variation in skill. Over the length of the forecast, a gradual decrease in skill is observed from hours 0–72. One exception is the surface pressure, which improves slightly in the first few hours, due in part to the model adjusting from surface pressure biases that are caused by the initialization technique over the high, cold terrain.

The impact of the higher-resolution model domains over the McMurdo region is also evaluated. It is shown that the 3.3-km domain is more sensitive to spatial and temporal changes in the winds than the 10-km domain, which represents an overall improvement in forecast skill, especially on the windward side of the island where the Williams Field and Pegasus runways are situated, and in the lee of Ross Island, an important area of mesoscale cyclogenesis (although the correlation coefficients in these regions are still relatively low).

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Jordan G. Powers
,
Kevin W. Manning
,
David H. Bromwich
,
John J. Cassano
, and
Arthur M. Cayette

The Antarctic Mesoscale Prediction System (AMPS) is a real-time numerical weather prediction (NWP) system covering Antarctica that has served a remarkable range of groups and activities for a decade. It employs the Weather Research and Forecasting model (WRF) on varying-resolution grids to generate numerical guidance in a variety of tailored products. While its priority mission has been to support the forecasters of the U.S. Antarctic Program, AMPS has evolved to assist a host of scientific and logistical needs for an international user base. The AMPS effort has advanced polar NWP and Antarctic science and looks to continue this into another decade. To inform those with Antarctic scientific and logistical interests and needs, the history, applications, and capabilities of AMPS are discussed.

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Andrew J. Monaghan
,
David H. Bromwich
,
Jordan G. Powers
, and
Kevin W. Manning

Abstract

In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program’s Antarctic field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs a limited-area model, the Polar fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), optimized for use over ice sheets. Twice-daily forecasts from the 3.3-km resolution domain of AMPS are joined together to study the climate of the McMurdo region from June 2002 to May 2003. Annual and seasonal distributions of wind direction and speed, 2-m temperature, mean sea level pressure, precipitation, and cloud fraction are presented. This is the first time a model adapted for polar use and with relatively high resolution is used to study the climate of the rugged McMurdo region, allowing several important climatological features to be investigated with unprecedented detail.

Orographic effects exert an important influence on the near-surface winds. Time-mean vortices occur in the lee of Ross Island, perhaps a factor in the high incidence of mesoscale cyclogenesis noted in this area. The near-surface temperature gradient is oriented northwest to southeast with the warmest temperatures in the northwest near McMurdo and the gradient being steepest in winter. The first-ever detailed precipitation maps of the region are presented. Orographic precipitation maxima occur on the southerly slopes of Ross Island and in the mountains to the southwest. The source of the moisture is primarily from the large synoptic systems passing to the northeast and east of Ross Island. A precipitation-shadow effect appears to be an important influence on the low precipitation amounts observed in the McMurdo Dry Valleys. Total cloud fraction primarily depends on the amount of open water in the Ross Sea; the cloudiest region is to the northeast of Ross Island in the vicinity of the Ross Sea polynya.

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Morris L. Weisman
,
Christopher Davis
,
Wei Wang
,
Kevin W. Manning
, and
Joseph B. Klemp

Abstract

Herein, a summary of the authors’ experiences with 36-h real-time explicit (4 km) convective forecasts with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) during the 2003–05 spring and summer seasons is presented. These forecasts are compared to guidance obtained from the 12-km operational Eta Model, which employed convective parameterization (e.g., Betts–Miller–Janjić). The results suggest significant value added for the high-resolution forecasts in representing the convective system mode (e.g., for squall lines, bow echoes, mesoscale convective vortices) as well as in representing the diurnal convective cycle. However, no improvement could be documented in the overall guidance as to the timing and location of significant convective outbreaks. Perhaps the most notable result is the overall strong correspondence between the Eta and WRF-ARW guidance, for both good and bad forecasts, suggesting the overriding influence of larger scales of forcing on convective development in the 24–36-h time frame. Sensitivities to PBL, land surface, microphysics, and resolution failed to account for the more significant forecast errors (e.g., completely missing or erroneous convective systems), suggesting that further research is needed to document the source of such errors at these time scales. A systematic bias is also noted with the Yonsei University (YSU) PBL scheme, emphasizing the continuing need to refine and improve physics packages for application to these forecast problems.

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