scholarly journals A Self-Organizing-Map-Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica

2017 ◽  
Vol 32 (1) ◽  
pp. 223-242 ◽  
Author(s):  
Melissa A. Nigro ◽  
John J. Cassano ◽  
Jonathan Wille ◽  
David H. Bromwich ◽  
Matthew A. Lazzara
Keyword(s):  
Weather Prediction ◽  
Atmospheric Stability ◽  
Static Stability ◽  
Prediction System ◽  
Ice Shelf ◽  
Mechanical Mixing ◽  
Near Surface ◽  
Ross Ice Shelf ◽  
Stable Conditions ◽  
The Antarctic

Abstract Accurate representation of the stability of the surface layer in numerical weather prediction models is important because of the impact it has on forecasts of surface energy, moisture, and momentum fluxes. It also impacts boundary layer processes such as the generation of turbulence, the creation of near-surface flows, and fog formation. This paper uses observations from a 30-m automatic weather station on the Ross Ice Shelf, Antarctica, to evaluate the near-surface layer in the Antarctic Mesoscale Prediction System (AMPS), a numerical weather prediction system used for forecasting in Antarctica. The method of self-organizing maps (SOM) is used to identify characteristic potential temperature anomaly profiles observed at the 30-m tower. The SOM-identified profiles are then used to evaluate the performance of AMPS as a function of atmospheric stability. The results indicate AMPS underpredicts the frequency of near-neutral profiles and instead overpredicts the frequency of weakly unstable and weak to moderately stable profiles. AMPS does not forecast the strongest statically stable patterns observed by Tall Tower, but in the median, the AMPS forecasts are more statically stable across all wind speeds, indicating a possible mechanical mixing error or a negative radiation bias. The SOM analysis identifies a negative radiation bias under near-neutral to weakly stable conditions, causing an overrepresentation of the static stability in AMPS. AMPS has a positive wind speed bias in moderate to strongly stable conditions, which generates too much mechanical mixing and an underrepresentation of the static stability. Model errors increase with increasing atmospheric stability.

scholarly journals Evaluation of the AMPS Boundary Layer Simulations on the Ross Ice Shelf, Antarctica, with Unmanned Aircraft Observations

2017 ◽  
Vol 56 (8) ◽  
pp. 2239-2258 ◽  
Author(s):  
Jonathan D. Wille ◽  
David H. Bromwich ◽  
John J. Cassano ◽  
Melissa A. Nigro ◽  
Marian E. Mateling ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Relative Humidity ◽  
High Wind ◽  
Ice Shelf ◽  
High Wind Speed ◽  
Near Surface ◽  
Ross Ice Shelf ◽  
Low Cloud ◽  
The Antarctic

AbstractAccurately predicting moisture and stability in the Antarctic planetary boundary layer (PBL) is essential for low-cloud forecasts, especially when Antarctic forecasters often use relative humidity as a proxy for cloud cover. These forecasters typically rely on the Antarctic Mesoscale Prediction System (AMPS) Polar Weather Research and Forecasting (Polar WRF) Model for high-resolution forecasts. To complement the PBL observations from the 30-m Alexander Tall Tower! (ATT) on the Ross Ice Shelf as discussed in a recent paper by Wille and coworkers, a field campaign was conducted at the ATT site from 13 to 26 January 2014 using Small Unmanned Meteorological Observer (SUMO) aerial systems to collect PBL data. The 3-km-resolution AMPS forecast output is combined with the global European Centre for Medium-Range Weather Forecasts interim reanalysis (ERAI), SUMO flights, and ATT data to describe atmospheric conditions on the Ross Ice Shelf. The SUMO comparison showed that AMPS had an average 2–3 m s−1 high wind speed bias from the near surface to 600 m, which led to excessive mechanical mixing and reduced stability in the PBL. As discussed in previous Polar WRF studies, the Mellor–Yamada–Janjić PBL scheme is likely responsible for the high wind speed bias. The SUMO comparison also showed a near-surface 10–15-percentage-point dry relative humidity bias in AMPS that increased to a 25–30-percentage-point deficit from 200 to 400 m above the surface. A large dry bias at these critical heights for aircraft operations implies poor AMPS low-cloud forecasts. The ERAI showed that the katabatic flow from the Transantarctic Mountains is unrealistically dry in AMPS.

Evaluation of the Antarctic Mesoscale Prediction System based on snow accumulation observations over the Ross Ice Shelf

2017 ◽  
Vol 34 (5) ◽  
pp. 587-598
Author(s):  
Yihui Liu ◽  
Yetang Wang ◽  
Minghu Ding ◽  
Weijun Sun ◽  
Tong Zhang ◽  
...  
Keyword(s):  
Snow Accumulation ◽  
Prediction System ◽  
Ice Shelf ◽  
Ross Ice Shelf ◽  
The Antarctic

scholarly journals Changes in Antarctic temperature, wind and precipitation in response to the Antarctic Oscillation

2004 ◽  
Vol 39 ◽  
pp. 119-126 ◽  
Author(s):  
Michiel R. van den Broeke ◽  
Nicole P. M. van Lipzig
Keyword(s):  
Climate Model ◽  
Weddell Sea ◽  
East Antarctica ◽  
Antarctic Oscillation ◽  
West Antarctica ◽  
Ice Shelf ◽  
Near Surface ◽  
Ross Ice Shelf ◽  
Temperature And Precipitation ◽  
The Antarctic

AbstractOutput of a 14 year integration with a high-resolution (55 km ×55 km) regional atmospheric climate model is used to study the response of Antarctic near-surface climate to the Antarctic Oscillation (AAO), the periodical strengthening and weakening of the circumpolar vortex in the Southern Hemisphere. In spite of the relatively short record, wind, temperature and precipitation show widespread and significant AAO-related signals. When the vortex is strong (high AAO index), northwesterly flow anomalies cause warming over the Antarctic Peninsula (AP) and adjacent regions in West Antarctica and the Weddell Sea. In contrast, cooling occurs in East Antarctica, the eastern Ross Ice Shelf and parts of Marie Byrd Land. Most of the annual temperature signal stems from the months March–August. The spatial distribution of the precipitation response to changes in the AAO does not mirror temperature changes but is in first order determined by the direction of flow anomalies with respect to the Antarctic topography. When the vortex is strong (high AAO index), the western AP becomes wetter, while the Ross Ice Shelf, parts of West Antarctica and the Lambert Glacier basin, East Antarctica, become drier.

scholarly journals A Satellite-Based Climatology of Wind-Induced Surface Temperature Anomalies for the Antarctic

2019 ◽  
Vol 11 (13) ◽  
pp. 1539 ◽  
Author(s):  
Günther Heinemann ◽  
Lukas Glaw ◽  
Sascha Willmes
Keyword(s):  
Surface Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Weddell Sea ◽  
Model Data ◽  
Ice Shelf ◽  
Near Surface ◽  
Surface Stability ◽  
Ross Ice Shelf ◽  
The Antarctic

It is well-known that katabatic winds can be detected as warm signatures in the surface temperature over the slopes of the Antarctic ice sheets. For appropriate synoptic forcing and/or topographic channeling, katabatic surges occur, which result in warm signatures also over adjacent ice shelves. Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) data are used to detect warm signatures over the Antarctic for the winter periods 2002–2017. In addition, high-resolution (5 km) regional climate model data is used for the years of 2002 to 2016. We present a case study and a climatology of wind-induced IST anomalies for the Ross Ice Shelf and the eastern Weddell Sea. The IST anomaly distributions show maxima around 10–15K for the slopes, but values of more than 25K are also found. Katabatic surges represent a strong climatological signal with a mean warm anomaly of more than 5K on more than 120 days per winter for the Byrd Glacier and the Nimrod Glacier on the Ross Ice Shelf. The mean anomaly for the Brunt Ice Shelf is weaker, and exceeds 5K on about 70 days per winter. Model simulations of the IST are compared to the MODIS IST, and show a very good agreement. The model data show that the near-surface stability is a better measure for the response to the wind than the IST itself.

scholarly journals The Climate of the McMurdo, Antarctica, Region as Represented by One Year of Forecasts from the Antarctic Mesoscale Prediction System*

2005 ◽  
Vol 18 (8) ◽  
pp. 1174-1189 ◽  
Author(s):  
Andrew J. Monaghan ◽  
David H. Bromwich ◽  
Jordan G. Powers ◽  
Kevin W. Manning
Keyword(s):  
Ross Sea ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Cloud Fraction ◽  
Important Influence ◽  
Limited Area ◽  
Dry Valleys ◽  
Prediction System ◽  
Near Surface ◽  
The Antarctic

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.

Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System (AMPS)*

2005 ◽  
Vol 133 (3) ◽  
pp. 579-603 ◽  
Author(s):  
David H. Bromwich ◽  
Andrew J. Monaghan ◽  
Kevin W. Manning ◽  
Jordan G. Powers
Keyword(s):  
Surface Pressure ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Surface Wind ◽  
Windward Side ◽  
Prediction System ◽  
Free Atmosphere ◽  
Near Surface ◽  
The Antarctic ◽  
The Impact

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).

scholarly journals Southern High-Latitude Ensemble Data Assimilation in the Antarctic Mesoscale Prediction System

2005 ◽  
Vol 133 (12) ◽  
pp. 3431-3449 ◽  
Author(s):  
D. M. Barker
Keyword(s):  
Data Assimilation ◽  
Sampling Error ◽  
Forecast Error ◽  
Weather Prediction ◽  
Forecast Errors ◽  
Prediction System ◽  
Spatial Covariance ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
The Antarctic

Abstract Ensemble data assimilation systems incorporate observations into numerical models via solution of the Kalman filter update equations, and estimates of forecast error covariances derived from ensembles of model integrations. In this paper, a particular algorithm, the ensemble square root filter (EnSRF), is tested in a limited-area, polar numerical weather prediction (NWP) model: the Antarctic Mesoscale Prediction System (AMPS). For application in the real-time AMPS, the number of model integrations that can be run to provide forecast error covariances is limited, resulting in an ensemble sampling error that degrades the analysis fit to observations. In this work, multivariate, climatologically plausible forecast error covariances are specified via averaged forecast difference statistics. Ensemble representations of the “true” forecast errors, created using randomized control variables of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) three-dimensional variational (3DVAR) data assimilation system, are then used to assess the dependence of sampling error on ensemble size, data density, and localization of covariances using simulated observation networks. Results highlight the detrimental impact of ensemble sampling error on the analysis increment structure of correlated, but unobserved fields—an issue not addressed by the spatial covariance localization techniques used to date. A 12-hourly cycling EnSRF/AMPS assimilation/forecast system is tested for a two-week period in December 2002 using real, conventional (surface, rawinsonde, satellite retrieval) observations. The dependence of forecast scores on methods used to maintain ensemble spread and the inclusion of perturbations to lateral boundary conditions are studied.

scholarly journals Wind plants can impact long-term local atmospheric conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Patrick Moriarty
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Weather Prediction ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Direct Observations ◽  
Stable Conditions ◽  
Weather And Climate ◽  
Central United States

AbstractLong-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30  km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

scholarly journals Surface melt magnitude retrieval over Ross Ice Shelf, Antarctica using coupled MODIS near-IR and thermal satellite measurements

2009 ◽  
Vol 3 (3) ◽  
pp. 1069-1107 ◽  
Author(s):  
D. J. Lampkin ◽  
C. C. Karmosky
Keyword(s):  
Meteorological Data ◽  
Temporal Variations ◽  
Katabatic Wind ◽  
Ice Shelf ◽  
Water Fraction ◽  
Ross Ice Shelf ◽  
Near Ir ◽  
Coarse Spatial Resolution ◽  
Surface Melt ◽  
The Antarctic

Abstract. Surface melt has been increasing over recent years, especially over the Antarctic Peninsula, contributing to disintegration of shelves such as Larsen. Unfortunately, we are not realistically able to quantify surface snowmelt from ground-based methods because there is sparse coverage of automatic weather stations. Satellite based assessments of melt from passive microwave systems are limited in that they only provide an indication of melt occurrence and have coarse spatial resolution. An algorithm was developed to retrieve surface melt magnitude using coupled near-IR/thermal surface measurements from MODIS were calibrated by estimates of liquid water fraction (LWF) in the upper 1 cm of the firn derived from a one-dimensional physical snowmelt model (SNTHERM89). For the modeling phase of this study, SNTHERM89 was forced by hourly meteorological data from automatic weather station data at reference sites spanning a range of melt conditions across the Ross Ice Shelf during a relatively intense melt season (2002). Effective melt magnitude or LWF<eff> were derived for satellite composite periods covering the Antarctic summer months at a 4 km resolution over the entire Ross Ice Shelf, ranging from 0–0.5% LWF<eff> in early December to areas along the coast with as much as 1% LWF<eff> during the time of peak surface melt. Spatial and temporal variations in the magnitude of surface melt are related to both katabatic wind strength and advection during onshore flow.

Simulations of Föhn in Antarctica with WRF for the Antarctic Mesoscale Prediction System AMPS

2021 ◽  
Author(s):  
Amélie Kirchgaessner ◽  
John King ◽  
Alan Gadian ◽  
Phil Anderson
Keyword(s):  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Ice Shelf ◽  
Cloud Properties ◽  
Surface Melt ◽  
Mixed Phase Clouds ◽  
The Antarctic

&lt;p&gt;We examine the representation of F&amp;#246;hn events across the Antarctic Peninsula Mountains during 2011 as they were observed in measurements by an Automatic Weather Station, and in simulations with the Weather Research and Forecasting Model (WRF) as run for the Antarctic Mesoscale Prediction System (AMPS). On the Larsen Ice Shelf (LIS) in the lee of this mountain range F&amp;#246;hn winds are thought to provide the atmospheric conditions for significant warming over the ice shelf thus leading to the initial firn densification and subsequently providing the melt water for hydrofracturing. This process has led to the dramatic collapse of huge parts of the LIS in 1995 and 2002 respectively.&lt;/p&gt;&lt;p&gt;Measurements obtained at a crest AWS on the Avery Plateau (AV), and the analysis of conditions upstream using the Froude number help to put observations at CP into a wider context. We find that, while the model generally simulates meteorological parameters very well, and shows good skills in capturing the occurrence, frequency and duration of F&amp;#246;hn events realistically, it underestimates the temperature increase and the humidity decrease during the F&amp;#246;hn significantly, and may thus underestimate the contribution of F&amp;#246;hn to driving surface melt on the LIS.&lt;/p&gt;&lt;p&gt;Our results indicate that the misrepresentation of cloud properties and particularly the absence of mixed phase clouds in AMPS, affects the quality of weather simulation under normal conditions to some extent, and to a larger extent the model&amp;#8217;s capability to simulate the strength of F&amp;#246;hn conditions - and thus their contribution to driving surface melt on the LIS - adequately. Most importantly our data show that F&amp;#246;hn conditions can raise the air temperature to above freezing, and thus trigger melt/sublimation even in winter.&lt;/p&gt;

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