scholarly journals Comparison of Arctic clouds between European Center for Medium-Range Weather Forecasts simulations and Atmospheric Radiation Measurement Climate Research Facility long-term observations at the North Slope of Alaska Barrow site

2010 ◽  
Vol 115 (D23) ◽  
Author(s):  
Ming Zhao ◽  
Zhien Wang
Keyword(s):  
North Slope ◽  
Research Facility ◽  
Arctic Clouds ◽  
Weather Forecasts ◽  
Climate Research ◽  
The North ◽  
Medium Range ◽  
North Slope Of Alaska ◽  
Atmospheric Radiation Measurement

scholarly journals Visitor’s Guide to Oliktok Point Atmospheric Radiation Measurement Climate Research Facility, North Slope of Alaska

2016 ◽  
Author(s):  
Darin Desilets ◽  
Fred M. Helsel ◽  
Al O. Bendure ◽  
Daniel A. Lucero ◽  
Mark D. Ivey ◽  
...  
Keyword(s):  
North Slope ◽  
Atmospheric Radiation ◽  
Radiation Measurement ◽  
Research Facility ◽  
Climate Research ◽  
North Slope Of Alaska ◽  
Atmospheric Radiation Measurement

scholarly journals The influence of local oil exploration and regional wildfires on summer 2015 aerosol over the North Slope of Alaska

2018 ◽  
Vol 18 (2) ◽  
pp. 555-570 ◽  
Author(s):  
Jessie M. Creamean ◽  
Maximilian Maahn ◽  
Gijs de Boer ◽  
Allison McComiskey ◽  
Arthur J. Sedlacek ◽  
...  
Keyword(s):  
Cloud Microphysics ◽  
Department Of Energy ◽  
The Arctic ◽  
North Slope ◽  
The North ◽  
The Us ◽  
Range Transport ◽  
North Slope Of Alaska ◽  
Atmospheric Radiation Measurement ◽  
Arctic Atmosphere

Abstract. The Arctic is warming at an alarming rate, yet the processes that contribute to the enhanced warming are not well understood. Arctic aerosols have been targeted in studies for decades due to their consequential impacts on the energy budget, both directly and indirectly through their ability to modulate cloud microphysics. Even with the breadth of knowledge afforded from these previous studies, aerosols and their effects remain poorly quantified, especially in the rapidly changing Arctic. Additionally, many previous studies involved use of ground-based measurements, and due to the frequent stratified nature of the Arctic atmosphere, brings into question the representativeness of these datasets aloft. Here, we report on airborne observations from the US Department of Energy Atmospheric Radiation Measurement (ARM) program's Fifth Airborne Carbon Measurements (ACME-V) field campaign along the North Slope of Alaska during the summer of 2015. Contrary to previous evidence that the Alaskan Arctic summertime air is relatively pristine, we show how local oil extraction activities, 2015's central Alaskan wildfires, and, to a lesser extent, long-range transport introduce aerosols and trace gases higher in concentration than previously reported in Arctic haze measurements to the North Slope. Although these sources were either episodic or localized, they serve as abundant aerosol sources that have the potential to impact a larger spatial scale after emission.

scholarly journals Statistical Analysis of Forecasting Models across the North Slope of Alaska during the Mixed-Phase Arctic Clouds Experiment

2009 ◽  
Vol 24 (6) ◽  
pp. 1644-1663 ◽  
Author(s):  
Victor T. Yannuzzi ◽  
Eugene E. Clothiaux ◽  
Jerry Y. Harrington ◽  
Johannes Verlinde
Keyword(s):  
Cloud Cover ◽  
Atmospheric Modeling ◽  
Mixed Phase ◽  
North Slope ◽  
Model Errors ◽  
Unique Challenge ◽  
Arctic Clouds ◽  
Forecasting Models ◽  
The North ◽  
North Slope Of Alaska

Abstract The National Centers for Environmental Prediction’s (NCEP) Eta Model, the models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration’s (NASA) Global Modeling and Assimilation Office (GMAO) models, and the Regional Atmospheric Modeling System (RAMS) model are all examined during the Mixed-Phase Arctic Clouds Experiment (MPACE) that took place from 27 September through 22 October 2004. During two intensive observation periods, soundings were launched every 6 h from four sites across the North Slope of Alaska (NSA): Barrow, Atqasuk, Oliktok Point, and Toolik Lake. Measurements of temperature, moisture, and winds, along with surface measurements of radiation and cloud cover, were compared to model outputs from the Eta, ECMWF, GMAO, and RAMS models using the bootstrap statistical technique to ascertain if differences in model performance were statistically significant. Ultimately, three synoptic regimes controlled NSA weather during the MPACE period for varying amounts of time. Each posed a unique challenge to the forecasting models during the study period. Temperature forecasts for all models were good at the MPACE sites with mean bias errors generally under 2 K, and the models had the fewest significant errors predicting temperature. Forecasting moisture and wind proved to be more difficult for the models, especially aloft in the 500–300-hPa layer. The largest errors occurred in the GMAO model, with significant moist biases of 40% and wind errors of 10 m s−1 or more. The RAMS, Eta, and ECMWF models had smaller moist biases in this layer. Both the Eta and RAMS models overestimated the surface incident shortwave radiation, underestimated longwave radiation, and underestimated cloud cover fraction. Overall, the bootstrapping results coincided with findings from conventional statistical comparisons as model outputs with the largest errors were most likely to be captured and declared statistically significant in the bootstrapping process. The significant model errors during MPACE were predominantly traced to the inability of the models to simulate disturbances in synoptic regime I, warm or cold biases over higher inland terrain, a warm bias along the NSA coastal waters in the Beaufort Sea, and difficulty in forecasting the intensity of the explosive cyclone in synoptic regime III.

scholarly journals Analysis of Radiosonde and Ground-Based Remotely Sensed PWV Data from the 2004 North Slope of Alaska Arctic Winter Radiometric Experiment

2007 ◽  
Vol 24 (3) ◽  
pp. 415-431 ◽  
Author(s):  
V. Mattioli ◽  
E. R. Westwater ◽  
D. Cimini ◽  
J. C. Liljegren ◽  
B. M. Lesht ◽  
...  
Keyword(s):  
Microwave Radiometer ◽  
Precipitable Water ◽  
North Slope ◽  
Remote Sensors ◽  
The North ◽  
Global Positioning ◽  
North Slope Of Alaska ◽  
Atmospheric Radiation Measurement ◽  
Sensor Temperature ◽  
Better Than

Abstract During 9 March–9 April 2004, the North Slope of Alaska Arctic Winter Radiometric Experiment was conducted at the Atmospheric Radiation Measurement Program’s (ARM) “Great White” field site near Barrow, Alaska. The major goals of the experiment were to compare microwave and millimeter wavelength radiometers and to develop forward models in radiative transfer, all with a focus on cold (temperature from 0° to −40°C) and dry [precipitable water vapor (PWV) < 0.5 cm] conditions. To supplement the remote sensors, several radiosonde packages were deployed: Vaisala RS90 launched at the ARM Duplex and at the Great White and Sippican VIZ-B2 operated by the NWS. In addition, eight dual-radiosonde launches were conducted at the Duplex with Vaisala RS90 and Sippican GPS Mark II, the latter one modified to include a chilled mirror humidity sensor. Temperature comparisons showed a nighttime bias between VIZ-B2 and RS90, which reached 3.5°C at 30 hPa. Relative humidity comparisons indicated better than 5% average agreement between the RS90 and the chilled mirror. A bias of about 20% for the upper troposphere was found in the VIZ-B2 and the Mark II measurements relative to both RS90 and the chilled mirror. Comparisons in PWV were made between a microwave radiometer, a microwave profiler, a global positioning system receiver, and the radiosonde types. An RMS agreement of 0.033 cm was found between the radiometer and the profiler and better than 0.058 cm between the radiometers and GPS. RS90 showed a daytime dry bias on PWV of about 0.02 cm.

Dispersive noise removal in t-x space: Application to Arctic data

Geophysics ◽  
1988 ◽  
Vol 53 (3) ◽  
pp. 346-358 ◽  
Author(s):  
Greg Beresford‐Smith ◽  
Rolf N. Rango
Keyword(s):  
Signal To Noise Ratio ◽  
Noise Analysis ◽  
Noise Removal ◽  
North Slope ◽  
Frequency Bandwidth ◽  
The North ◽  
North Slope Of Alaska ◽  
Seismic Records ◽  
Time Offset ◽  
Undersampled Data

Strongly dispersive noise from surface waves can be attenuated on seismic records by Flexfil, a new prestack process which uses wavelet spreading rather than velocity as the criterion for noise discrimination. The process comprises three steps: trace‐by‐trace compression to collapse the noise to a narrow fan in time‐offset (t-x) space; muting of the noise in this narrow fan; and inverse compression to recompress the reflection signals. The process will work on spatially undersampled data. The compression is accomplished by a frequency‐domain, linear operator which is independent of trace offset. This operator is the basis of a robust method of dispersion estimation. A flexural ice wave occurs on data recorded on floating ice in the near offshore of the North Slope of Alaska. It is both highly dispersed and of broad frequency bandwidth. Application of Flexfil to these data can increase the signal‐to‐noise ratio up to 20 dB. A noise analysis obtained from a microspread record is ideal to use for dispersion estimation. Production seismic records can also be used for dispersion estimation, with less accurate results. The method applied to field data examples from Alaska demonstrates significant improvement in data quality, especially in the shallow section.

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

scholarly journals Ice processes and growth history on Arctic and sub-Arctic lakes using ERS-1 SAR data

Polar Record ◽  
1995 ◽  
Vol 31 (177) ◽  
pp. 115-128 ◽  
Author(s):  
K. Morris ◽  
M. O. Jeffries ◽  
W. F. Weeks
Keyword(s):  
Arctic Lakes ◽  
Polar Regions ◽  
Lake Ice ◽  
Sar Images ◽  
The North ◽  
Growth History ◽  
North Slope Of Alaska ◽  
Term Monitoring ◽  
Selection Of

AbstractA survey of ice growth and decay processes on a selection of shallow and deep sub-Arctic and Arctic lakes was conducted using radiometrically calibrated ERS-1 SAR images. Time series of radar backscatter data were compiled for selected sites on the lakes during the period of ice cover (September to June) for the years 1991–92 and 1992–93. A variety of lake-ice processes could be observed, and significant changes in backscatter occurred from the time of initial ice formation in autumn until the onset of the spring thaw. Backscatter also varied according to the location and depth of the lakes. The spatial and temporal changes in backscatter were most constant and predictable at the shallow lakes on the North Slope of Alaska. As a consequence, they represent the most promising sites for long-term monitoring and the detection of changes related to global warming and its effects on the polar regions.

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