Abstract

The mesoscale cyclone activity observed in the portion of Antarctica that faces the South Pacific Ocean and Weddell Sea area is summarized from a study of 1991. In general, area-normalized results reveal much greater mesoscale cyclonic activity over the Ross Sea/Ross Ice Shelf and southern Marie Byrd Land than on both sides of the Antarctic Peninsula. More than 50% of the observed mesoscale vortices are of the comma cloud type. The average diameter of mesoscale vortices is approximately 200 km near Terra Nova Bay, 270 km near Byrd Glacier, and 280 km near Siple Coast. Near the Antarctic Peninsula, the average diameter is about 370 km over the Bellingshausen Sea and 380 km on the Weddell Sea side. The largest percentage of deep vortices occurs over the Bellingshausen Sea sector (38% of all cases), where convective instability frequently occurs. Over the Ross Sea/Ross Ice Shelf and Weddell Sea sectors the majority of the mesoscale vortices are low cloud features that probably do not exceed the 700-hPa level due to the prevailing lower-atmospheric stability. The areas identified as sources of mesoscale vortices concur with the locations of enhanced katabatic winds.

A synthesis of the available literature leads to some general characteristics of mesoscale cyclone formation and development. Mesoscale cyclogenesis is associated with areas of warm and/or cold air advection, low-level baroclinicity, and cyclonic vorticity resulting from the stretching mechanism. Subsequent intensification depends on the presence of upper-level support. Spatial and temporal variability in mesoscale cyclone formation is often related to the behavior of synoptic-scale cyclone tracks. Mesoscale cyclones can generate precipitation and severe weather conditions and thus present a critical forecasting challenge.

Abstract

In this study, the GPS radio occultation (RO) data from the Challenging Minisatellite Payload (CHAMP) and Satellite de Aplicaciones Cientificas-C (SAC-C) missions are assimilated. An updated version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) four-dimensional variational data assimilation system (4DVAR) is used to assess the impact of the GPS RO data on analyses and short-range forecasts over the Antarctic. The study was performed during the period of intense cyclonic activity in the Ross Sea, 9–19 December 2001. On average 66 GPS RO soundings were assimilated daily. For the assimilation over a single 12-h period, the impact of GPS RO data was only marginally positive or near neutral, and it varied markedly from one 12-h period to another. The large case-to-case variation was attributed to the low number of GPS RO soundings and a strong dependency of forecast impact on the location of the soundings relative to the rapidly developing cyclone. Despite the moderate general impact, noticeable reduction of temperature error in the upper troposphere and lower stratosphere was found, which demonstrates the value of GPS RO data in better characterizing the tropopause. Significant error reduction was also noted in geopotential height and wind fields in the stratosphere. Those improvements indicate that early detection of the upper-level precursors for storm development is a potential benefit of GPS RO data. When the assimilation period was extended to 48 h, a considerable positive impact of GPS RO data was found. All parameters that were investigated (i.e., temperature, pressure, and specific humidity) showed the positive impact throughout the entire model atmosphere for forecasts extending up to 5 days. The impact increased in proportion to the length of the assimilation period. Although the differences in the analyses as a result of GPS RO assimilation were relatively small initially, the subtle change and subsequent nonlinear growth led to noticeable forecast improvements at longer ranges. Consequently, the positive impact of GPS RO data was more evident in longer-range (e.g., greater than 2 days) forecasts. A correlation coefficient is introduced to quantify the linear relationship between the analysis errors without GPS RO assimilation and the analysis increments induced by GPS RO assimilation. This measure shows that the growth of GPS RO–induced modifications over time is related to the prominent error reduction observed in GPS RO experiments. The measure may also be useful for understanding how cycling analysis accumulates the positive impact of GPS RO data for an extended period of assimilation.

Abstract

There is growing use of limited-area models (LAMs) for high-resolution (<10 km) applications, for which consistent mapping of input terrestrial and meteorological datasets is critical for accurate simulations. The geographic coordinate systems of most input datasets are based on spheroid-shaped (i.e., elliptical) Earth models, while LAMs generally assume a perfectly sphere-shaped Earth. This distinction is often neglected during preprocessing, when input data are remapped to LAM domains, leading to geolocation discrepancies that can exceed 20 km at midlatitudes.

A variety of terrestrial (topography and land use) input dataset configurations is employed to explore the impact of Earth model assumptions on a series of 1-km LAM simulations over Colorado. For the same terrestrial datasets, the ~20-km geolocation discrepancy between spheroidal-versus-spherical Earth models over the domain leads to simulated differences in near-surface and midtropospheric air temperature, humidity, and wind speed that are larger and more widespread than those due to using different topography and land use datasets altogether but not changing the Earth model. Simulated differences are caused by the shift of static fields with respect to boundary conditions, and altered Coriolis forcing and topographic gradients.

The sensitivity of high-resolution LAM simulations to Earth model assumptions emphasizes the importance for users to ensure terrestrial and meteorological input data are consistently mapped during preprocessing (i.e., datasets share a common geographic coordinate system before remapping to the LAM domain). Concurrently, the modeling community should update preprocessing systems to make sure input data are correctly mapped for all global and limited-area simulation domains.

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).

Abstract

To support the forecasting needs of the United States Antarctic Program at McMurdo, Antarctica, a special numerical weather prediction program, the Antarctic Mesoscale Prediction System (AMPS), was established for the 2000–01 field season. AMPS employs the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) that has physics modifications for polar environments. This study assesses the performance of AMPS in forecasting an event of mesoscale cyclogenesis in the western Ross Sea during 13–17 January 2001. Observations indicate the presence of a complex trough having two primary mesoscale lows that merge to the east of Ross Island shortly after 0700 UTC 15 January. In contrast, AMPS predicts one primary mesoscale low throughout the event, incorrectly placing it until the 1800 UTC 15 January forecast, when the observed system carries a prominent signature in the initialization. The model reproduces the evolution of upper-level conditions in agreement with the observations and shows skill in resolving many small-scale surface features common to the region (i.e., katabatic winds; lows and highs induced by wind/topography). The AMPS forecasts can rely heavily on the representation of surface lows and upper-level forcing in the first-guess fields derived from NCEP's Aviation Model (AVN). Furthermore, even with relatively high spatial resolution, mesoscale models face observation-related limitations on performance that can be particularly acute in Antarctica.