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David H. Bromwich
,
John J. Cassano
,
Thomas Klein
,
Gunther Heinemann
,
Keith M. Hines
,
Konrad Steffen
, and
Jason E. Box

Abstract

Verification of two months, April and May 1997, of 48-h mesoscale model simulations of the atmospheric state around Greenland are presented. The simulations are performed with a modified version of The Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5), referred to as the Polar MM5. Global atmospheric analyses as well as automatic weather station and instrumented aircraft observations from Greenland are used to verify the forecast atmospheric state. The model is found to reproduce the observed atmospheric state with a high degree of realism. Monthly mean values of the near-surface temperature and wind speed predicted by the Polar MM5 differ from the observations by less than 1 K and 1 m s−1, respectively, at most sites considered. In addition, the model is able to simulate a realistic diurnal cycle for the surface variables, as well as capturing the large-scale, synoptically forced changes in these variables. Comparisons of modeled profiles of wind speed, direction, and potential temperature in the katabatic layer with aircraft observations are also favorable, with small mean errors. The simulations of the katabatic winds are found to be sensitive to errors in the large-scale forcing (e.g., the large-scale pressure gradient) and to errors in the representation of key physical processes, such as turbulence in the very stable surface layer and cloud–radiation interaction.

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Linette N. Boisvert
,
Melinda A. Webster
,
Alek A. Petty
,
Thorsten Markus
,
Richard I. Cullather
, and
David H. Bromwich

Abstract

Precipitation is a major component of the hydrologic cycle and plays a significant role in the sea ice mass balance in the polar regions. Over the Southern Ocean, precipitation is particularly uncertain due to the lack of direct observations in this remote and harsh environment. Here we demonstrate that precipitation estimates from eight global reanalyses produce similar spatial patterns between 2000 and 2010, although their annual means vary by about 250 mm yr−1 (or 26% of the median values) and there is little similarity in their representation of interannual variability. ERA-Interim produces the smallest and CFSR produces the largest amount of precipitation overall. Rainfall and snowfall are partitioned in five reanalyses; snowfall suffers from the same issues as the total precipitation comparison, with ERA-Interim producing about 128 mm less snowfall and JRA-55 about 103 mm more rainfall compared to the other reanalyses. When compared to CloudSat-derived snowfall, these five reanalyses indicate similar spatial patterns, but differ in their magnitude. All reanalyses indicate precipitation on nearly every day of the year, with spurious values occurring on an average of about 60 days yr−1, resulting in an accumulation of about 4.5 mm yr−1. While similarities in spatial patterns among the reanalyses suggest a convergence, the large spread in magnitudes points to issues with the background models in adequately reproducing precipitation rates, and the differences in the model physics employed. Further improvements to model physics are required to achieve confidence in precipitation rate, as well as the phase and frequency of precipitation in these products.

Free access
Megan E. Jones
,
David H. Bromwich
,
Julien P. Nicolas
,
Jorge Carrasco
,
Eva Plavcová
,
Xun Zou
, and
Sheng-Hung Wang

Abstract

Temperature trends across Antarctica over the last few decades reveal strong and statistically significant warming in West Antarctica and the Antarctic Peninsula (AP) contrasting with no significant change overall in East Antarctica. However, recent studies have documented cooling in the AP since the late 1990s. This study aims to place temperature changes in the AP and West Antarctica into a larger spatial and temporal perspective by analyzing monthly station-based surface temperature observations since 1957 across the extratropical Southern Hemisphere, along with sea surface temperature (SST) data and mean sea level pressure reanalysis data. The results confirm statistically significant cooling in station observations and SST trends throughout the AP region since 1999. However, the full 60-yr period shows statistically significant, widespread warming across most of the Southern Hemisphere middle and high latitudes. Positive SST trends broadly reflect these warming trends, especially in the midlatitudes. After confirming the importance of the southern annular mode (SAM) on southern high-latitude climate variability, the influence is removed from the station temperature records, revealing statistically significant background warming across all of the extratropical Southern Hemisphere. Antarctic temperature trends in a suite of climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are then investigated. Consistent with previous work the CMIP5 models warm Antarctica at the background temperature rate that is 2 times faster than that observed. However, removing the SAM influence from both CMIP5 and observed temperatures results in Antarctic trends that differ only modestly, perhaps due to natural multidecadal variability remaining in the observations.

Open access
Flavio Justino
,
Aaron B. Wilson
,
David H. Bromwich
,
Alvaro Avila
,
Le-Sheng Bai
, and
Sheng-Hung Wang

Abstract

Large-scale objectively analyzed gridded products and satellite estimates of sensible (H) and latent (LE) heat fluxes over the extratropical Northern Hemisphere are compared to those derived from the regional Arctic System Reanalysis version 2 (ASRv2) and a selection of current-generation global reanalyses. Differences in H and LE among the reanalyses are strongly linked to the wind speed magnitudes and vegetation cover. Specifically, ASRv2 wind speeds match closely with observations over the northern oceans, leading to an improved representation of H compared to the global reanalyses. Comparison of evaporative fraction shows that the global reanalyses are characterized by a similar H and LE partitioning from April through September, and therefore exhibit weak intraseasonal variability. However, the higher horizontal resolution and weekly modification of the vegetation cover based on satellite data in ASRv2 provides an improved snow–albedo feedback related to changes in the leaf area index. Hence, ASRv2 better captures the small-scale processes associated with day-to-day vegetation feedbacks with particular improvements to the H over land. All of the reanalyses provide realistic dominant hemispheric patterns of H and LE and the locations of maximum and minimum fluxes, but they differ greatly with respect to magnitude. This is especially true for LE over oceanic regions. Therefore, uncertainties in heat fluxes remain that may be alleviated in reanalyses through improved representation of physical processes and enhanced assimilation of observations.

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Linette N. Boisvert
,
Melinda A. Webster
,
Alek A. Petty
,
Thorsten Markus
,
David H. Bromwich
, and
Richard I. Cullather

Abstract

Precipitation over the Arctic Ocean has a significant impact on the basin-scale freshwater and energy budgets but is one of the most poorly constrained variables in atmospheric reanalyses. Precipitation controls the snow cover on sea ice, which impedes the exchange of energy between the ocean and atmosphere, inhibiting sea ice growth. Thus, accurate precipitation amounts are needed to inform sea ice modeling, especially for the production of thickness estimates from satellite altimetry freeboard data. However, obtaining a quantitative estimate of the precipitation distribution in the Arctic is notoriously difficult because of a number of factors, including a lack of reliable, long-term in situ observations; difficulties in remote sensing over sea ice; and model biases in temperature and moisture fields and associated uncertainty of modeled cloud microphysical processes in the polar regions. Here, we compare precipitation estimates over the Arctic Ocean from eight widely used atmospheric reanalyses over the period 2000–16 (nominally the “new Arctic”). We find that the magnitude, frequency, and phase of precipitation vary drastically, although interannual variability is similar. Reanalysis-derived precipitation does not increase with time as expected; however, an increasing trend of higher fractions of liquid precipitation (rainfall) is found. When compared with drifting ice mass balance buoys, three reanalyses (ERA-Interim, MERRA, and NCEP R2) produce realistic magnitudes and temporal agreement with observed precipitation events, while two products [MERRA, version 2 (MERRA-2), and CFSR] show large, implausible magnitudes in precipitation events. All the reanalyses tend to produce overly frequent Arctic precipitation. Future work needs to be undertaken to determine the specific factors in reanalyses that contribute to these discrepancies in the new Arctic.

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Israel Silber
,
Johannes Verlinde
,
Sheng-Hung Wang
,
David H. Bromwich
,
Ann M. Fridlind
,
Maria Cadeddu
,
Edwin W. Eloranta
, and
Connor J. Flynn

Abstract

The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

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Jonathan D. Wille
,
David H. Bromwich
,
John J. Cassano
,
Melissa A. Nigro
,
Marian E. Mateling
, and
Matthew A. Lazzara

Abstract

Accurately 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.

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Jonathan D. Wille
,
David H. Bromwich
,
Melissa A. Nigro
,
John J. Cassano
,
Marian Mateling
,
Matthew A. Lazzara
, and
Sheng-Hung Wang

Abstract

Flight operations in Antarctica rely on accurate weather forecasts aided by the numerical predictions primarily produced by the Antarctic Mesoscale Prediction System (AMPS) that employs the polar version of the Weather Research and Forecasting (Polar WRF) Model. To improve the performance of the model’s Mellor–Yamada–Janjić (MYJ) planetary boundary layer (PBL) scheme, this study examines 1.5 yr of meteorological data provided by the 30-m Alexander Tall Tower! (ATT) automatic weather station on the western Ross Ice Shelf from March 2011 to July 2012. Processed ATT observations at 10-min intervals from the multiple observational levels are compared with the 5-km-resolution AMPS forecasts run daily at 0000 and 1200 UTC. The ATT comparison shows that AMPS has fundamental issues with moisture and handling stability as a function of wind speed. AMPS has a 10-percentage-point (i.e., RH unit) relative humidity dry bias year-round that is highest when katabatic winds from the Byrd and Mulock Glaciers exceed 15 m s−1. This is likely due to nonlocal effects such as errors in the moisture content of the katabatic flow and AMPS not parameterizing the sublimation from blowing snow. AMPS consistently overestimates the wind speed at the ATT by 1–2 m s−1, in agreement with previous studies that attribute the high wind speed bias to the MYJ scheme. This leads to reduced stability in the simulated PBL, thus affecting the model’s ability to properly simulate the transfer of heat and momentum throughout the PBL.

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Jordan G. Powers
,
Andrew J. Monaghan
,
Arthur M. Cayette
,
David H. Bromwich
,
Ying-Hwa Kuo
, and
Kevin W. Manning

In support of the United States Antarctic Program (USAP), the National Center for Atmospheric Research and the Byrd Polar Research Center of The Ohio State University have created the Antarctic Mesoscale Prediction System (AMPS): an experimental, real-time mesoscale modeling system covering Antarctica. AMPS has been designed to serve flight forecasters at McMurdo Station, to support science and operations around the continent, and to be a vehicle for the development of physical parameterizations suitable for polar regions. Since 2000, AMPS has been producing high-resolution forecasts (grids to 3.3 km) with the “Polar MM5,” a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model tuned for the polar atmosphere. Beyond its basic mission of serving the USAP flight forecasters at McMurdo, AMPS has assisted both in emergency operations to save lives and in programs to explore the extreme polar environment. The former have included a medical evacuation from the South Pole and a marine rescue from the continental margin. The latter have included scientific field campaigns and the daily activities of international Antarctic forecasters and researchers. The AMPS program has been a success in terms of advancing polar mesoscale NWP, serving critical logistical operations of the USAP, and, most visibly, assisting in emergency rescue missions to save lives. The history and performance of AMPS are described and the successes of this unique real-time mesoscale modeling system in crisis support are detailed.

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Dan Lubin
,
Biao Chen
,
David H. Bromwich
,
Richard C. J. Somerville
,
Wan-Ho Lee
, and
Keith M. Hines

Abstract

A sensitivity study to evaluate the impact upon regional and hemispheric climate caused by changing the optical properties of clouds over the Antarctic continent is conducted with the NCAR Community Model version 2 (CCM2). Sensitivity runs are performed in which radiation interacts with ice clouds with particle sizes of 10 and 40 μm rather than with the standard 10-μm water clouds. The experiments are carried out for perpetual January conditions with the diurnal cycle considered. The effects of these cloud changes on the Antarctic radiation budget are examined by considering cloud forcing at the top of the atmosphere and net radiation at the surface. Changes of the cloud radiative properties to those of 10-μm ice clouds over Antarctica have significant impacts on regional climate: temperature increases throughout the Antarctic troposphere by 1°–2°C and total cloud fraction over Antarctica is smaller than that of the control at low levels but is larger than that of the control in the mid- to upper troposphere. As a result of Antarctic warming and changes in the north–south temperature gradient, the drainage flows at the surface as well as the meridional mass circulation are weakened. Similarly, the circumpolar trough weakens significantly by 4–8 hPa and moves northward by about 4°–5° latitude. This regional mass field adjustment halves the strength of the simulated surface westerly winds. As a result of indirect thermodynamic and dynamic effects, significant changes are observed in the zonal mean circulation and eddies in the middle latitudes. In fact, the simulated impacts of the Antarctic cloud radiative alteration are not confined to the Southern Hemisphere. The meridional mean mass flux, zonal wind, and latent heat release exhibit statistically significant changes in the Tropics and even extratropics of the Northern Hemisphere. The simulation with radiative properties of 40-μm ice clouds produces colder surface temperatures over Antarctica by up to 3°C compared to the control. Otherwise, the results of the 40-μm ice cloud simulation are similar to those of the 10-μm ice cloud simulation.

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