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.

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.

Evaluation of the GOES-R ABI LAP Retrieval Algorithm Using the GOES-13 Sounder

2014 ◽  
Vol 31 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Yong-Keun Lee ◽  
Zhenglong Li ◽  
Jun Li ◽  
Timothy J. Schmit
Keyword(s):  
Microwave Radiometer ◽  
Precipitable Water ◽  
Retrieval Algorithm ◽  
Earth Observing System ◽  
Radiosonde Observation ◽  
Global Positioning ◽  
Atmospheric Radiation Measurement ◽  
Atmospheric Profile ◽  
Infrared Radiances ◽  
Environmental Prediction

Abstract A physical retrieval algorithm has been developed for deriving the legacy atmospheric profile (LAP) product from infrared radiances of the Advanced Baseline Imager (ABI) on board the next-generation Geostationary Operational Environmental Satellite (GOES-R) series. In this study, the GOES-R ABI LAP retrieval algorithm is applied to the GOES-13 sounder radiance measurements (termed the GOES-13 LAP retrieval algorithm in this study) for its validation as well as for potential transition of the GOES-13 LAP retrieval algorithm for the operational processing of GOES sounder data. The GOES-13 LAP retrievals are compared with five different truth measurements: radiosonde observation (raob) and microwave radiometer–measured total precipitable water (TPW) at the Atmospheric Radiation Measurement Cloud and Radiation Testbed site, conventional raob, TPW measurements from the global positioning system–integrated precipitable water NOAA network, and TPW measurements from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). The results show that with the GOES-R ABI LAP retrieval algorithm, the GOES-13 sounder provides better water vapor profiles than the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) forecast fields at the levels between 300 and 700 hPa. The root-mean-square error (RMSE) and standard deviation (STD) of the GOES-13 sounder TPW are consistently reduced from those of the GFS forecast no matter which measurements are used as the truth. These substantial improvements indicate that the GOES-R ABI LAP retrieval algorithm is well prepared to provide continuity of quality to some of the current GOES sounder products, and the algorithm can be transferred to process the current GOES sounder measurements for operational product generation.

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).

Underbalanced Drilling with Coiled Tubing: A Case Study on the Alaskan North Slope, Which Proves the Benefits of Drilling a Straight Hole

2021 ◽  
Author(s):  
Antoni Miszewski ◽  
Adam Miszewski ◽  
Richard Stevens ◽  
Matteo Gemignani
Keyword(s):  
Relative Effectiveness ◽  
Shallow Depth ◽  
North Slope ◽  
Coiled Tubing ◽  
The North ◽  
North Slope Of Alaska ◽  
Minimum Requirements ◽  
Bottom Hole Assembly ◽  
Alaskan North Slope ◽  
Future Work

Abstract A set of 5 wells were to be drilled with directional Coiled Tubing Drilling (CTD) on the North Slope of Alaska. The particular challenges of these wells were the fact that the desired laterals were targeted to be at least 6000ft long, at a shallow depth. Almost twice the length of laterals that are regularly drilled at deeper depths. The shallow depth meant that 2 of the 5 wells involved a casing exit through 3 casings which had never been attempted before. After drilling, the wells were completed with a slotted liner, run on coiled tubing. This required a very smooth and straight wellbore so that the liner could be run as far as the lateral had been drilled. Various methods were considered to increase lateral reach, including, running an extended reach tool, using friction reducer, increasing the coiled tubing size and using a drilling Bottom Hole Assembly (BHA) that could drill a very straight well path. All of these options were modelled with tubing forces software, and their relative effectiveness was evaluated. The drilling field results easily exceeded the minimum requirements for success. This project demonstrated record breaking lateral lengths, a record length of liner run on coiled tubing in a single run, and a triple casing exit. The data gained from this project can be used to fine-tune the modelling for future work of a similar nature.

Changes in tall shrub abundance on the North Slope of Alaska, 2000–2010

2018 ◽  
Vol 219 ◽  
pp. 221-232 ◽  
Author(s):  
Rocio R. Duchesne ◽  
Mark J. Chopping ◽  
Ken D. Tape ◽  
Zhuosen Wang ◽  
Crystal L.B. Schaaf
Keyword(s):  
North Slope ◽  
The North ◽  
North Slope Of Alaska ◽  
Tall Shrub
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