scholarly journals Analisis Tailwind Penyebab Go-Around pada 38 Bandara di Indonesia dalam Periode Januari-Februari 2020

2020 ◽  
Vol 32 (2) ◽  
Author(s):  
Achmad Fahruddin Rais ◽  
Bambang Wijayanto ◽  
Erika Meinovelia
Keyword(s):  
Brightness Temperature ◽  
Satellite Imagery ◽  
Temperature Difference ◽  
High Speed ◽  
Lower Troposphere ◽  
Wind Gust ◽  
Surface Observation

Studi ini berfokus pada analisis tailwind penyebab go-around pada 38 bandara di Indonesia dalam periode Januari-Februari 2020. Dalam studi ini dilakukan perbandingan tailwind laporan pilot, tailwind observasi permukaan (10 m), dan tailwind pada ketinggian 1000 ft untuk mengetahui akurasi tailwind yang dilaporkan oleh pilot. Literatur menyebutkan bahwa angin kecepatan tinggi di troposfer bawah berkaitan dengan wind gust yang berasal dari awan cumulonimbus (Cb). Dengan dasar tersebut maka dilakukan analisis perbandingan laporan pilot terhadap keberadaan awan Cb sampai sejauh 40 km dari runway in use dengan menggunakan kombinasi kriteria brightness temperature difference (BTD) kanal IR1-IR2 dan brightness temperature (BT) kanal IR1 citra satelit Himawari-8. Hasil penelitian menunjukkan bahwa tailwind laporan pilot lebih besar daripada tailwind angin permukaan dan 1000 ft, serta kebanyakan tailwind laporan pilot tersebut berkaitan dengan potensi wind gust yang muncul dari awan Cb baik di sekitar atau di luar runway.Kata kunci: Cumulonimbus, go-around, tailwind, wind gust. AbstractAn Analysis of Go-Around-Causing Tailwind at 38 Airports in Indonesia in the Period of January-February 2020: This study focused on analyzing the tailwind that causing go-around at 38 airports in Indonesia in the period of January to February 2020. We made a tailwind comparison of the pilot report, surface observation (10 m), and observation of 1000 ft to determine the accuracy of the tailwind reported by the pilot. The literature stated that high-speed winds in the lower troposphere were related to wind gust coming from cumulonimbus (Cb) clouds, so we compared pilot report to the presence of Cb clouds as far as 40 km from the runway in use by using a combination of brightness temperature difference (BTD) IR1-IR2 channels and brightness temperature (BT) IR1 channel of Himawari-8 satellite imagery. The results showed that the tailwind of the pilot report was larger than the tailwind of surface and 1000 ft observations and most of the tailwind was related to the potential wind gust that emerged from the Cb clouds either around or outside the runway.Keywords: Cumulonimbus, go-around, tailwind, wind gust.

Relationship between the Brightness Temperature Anomalies of the Lower Troposphere and the Climate Indices in the Southern Urals

2019 ◽  
Vol 55 (9) ◽  
pp. 975-985
Author(s):  
D. Yu. Vasil’ev ◽  
N. V. Velikanov ◽  
V. V. Vodopyanov ◽  
N. N. Krasnogorskaya ◽  
V. A. Semenov ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Lower Troposphere ◽  
Southern Urals ◽  
Climate Indices ◽  
The Southern Urals ◽  
Temperature Anomalies

The infrared measurement cascade: Connecting large scale meteorologically induced surface temperature perturbations to local spatial velocity structures

2020 ◽  
Author(s):  
Benjamin Schumacher ◽  
Marwan Katurji ◽  
Jiawei Zhang
Keyword(s):  
Boundary Layer ◽  
Velocity Field ◽  
Brightness Temperature ◽  
High Speed ◽  
Surface Brightness ◽  
Large Scale ◽  
Mean Velocity ◽  
Near Surface ◽  
Multi Scale ◽  
Infrared Cameras

<p>The evolution of micrometeorological measurements has been recently manifested by developments in methodological and analytical techniques using spatial surface brightness temperature captured by infrared cameras (Schumacher et al. 2019, Katurji and Zawar-Reza 2016). The Thermal Image Velocimetry (TIV) method can now produce accurate 2D advection-velocities using high speed (>20Hz) infrared imagery (Inagaki 2013, Schumacher 2019). However, to further develop TIV methods and achieve a novel micrometeorological measurement technique, all scales of motion within the boundary layer need to be captured.</p><p>Spatial observations of multi-frequency and multi-scale temperature perturbations are a result from the turbulent interaction of the overlying atmosphere and the surface. However, these surface signatures are connected to the larger scales of the atmospheric boundary layer (McNaughton 2002, Träumner 2015). When longer periods (a few hours to a few days) of spatial surface brightness temperatures are observed, the larger scale information needs to be accounted for to build a comprehensive understanding of surface-atmospheric spatial turbulent interactions. Additionally, the time-frequency decomposition of brightness temperature perturbations shows longer periods of 4-15 minutes superimposed over shorter periods of ~ 4–30 seconds. This suggests that that boundary layer dynamic scales (of longer periods) can influence brightness temperature perturbations on the local turbulent scale. An accurate TIV algorithm needs to account for all scales of motion when analysing the time-space variability of locally observed spatial brightness temperature patterns.</p><p>To analyse these propositions temporally high resolved geostationary satellite infrared data from the Himawari 8 satellite was compared to near-surface and high speed (20 Hz) measured air and brightness temperature using thermocouple measurements and infrared cameras. The satellite provides a temporal resolution of 10-minutes and a horizontal resolution of 2 by 2 km per pixel and therefore captures the atmospheric meso γ and micro α scale which signals are usually active for ~10 minutes to < 12 hours. Moreover, the Himawari 8 brightness temperature was used to create the near-surface mean velocity field using TIV. Afterwards, the velocity field was compared to the in-situ measured wind velocity over several days during January 2019.</p><p>The results show that the atmospheric forcing from the micro α scale to lower atmospheric scales has a major impact on the near-surface temperature over several minutes. A significant (p-value: 0.02) positive covariance between the Himawari 8 measurement and the local measured temperature 1.5 cm above the ground on a 10 minute average, specifically concerning cooling and heating patterns, has been found.</p><p>Further analysis demonstrates that the retrieved near-surface 2-D velocity field calculated from the Himawari 8 brightness temperature perturbations is correctly representing the mean velocity. This finding allows the classification of meso-scale atmospheric forcing and its direct connection to local scale turbulent 2-D velocity measurements. This extends the TIV algorithm by a multi-scale component which allows to address inter-scale boundary layer analysis from a new point of view. In respect to the current findings a new experiment will focus on the repeated induced local velocity patterns from large scale forcing which will be measured through the surface brightness temperature.</p>

scholarly journals A new mobile and portable scanning lidar for profiling the lower troposphere

2015 ◽  
Vol 4 (1) ◽  
pp. 35-44 ◽  
Author(s):  
C.-W. Chiang ◽  
S. K. Das ◽  
H.-W. Chiang ◽  
J.-B. Nee ◽  
S.-H. Sun ◽  
...  
Keyword(s):  
Atmospheric Aerosols ◽  
High Speed ◽  
Stimulated Raman Scattering ◽  
Layer Structure ◽  
Lower Troposphere ◽  
Sea Breeze ◽  
Industrial Area ◽  
Atmospheric Pollutants ◽  
Lidar System ◽  
Scanning Lidar

Abstract. An in-house developed mobile and portable three-dimensional scanning lidar system is discussed in this work. The system uses a stimulated Raman-scattering technique for the continuous observation of atmospheric aerosols, clouds and trace gases. This system has a fast scanning technique with a high-speed data acquisition, and permits the real-time measurement of atmospheric pollutants with the temporal resolution of 1 min. This scanning lidar system provides typical horizontal coverage of about 8–10 km while scanning; however, in zenith mode, good quality backscattered signals can be from 20 km, depending upon the laser power and sky conditions. This versatile lidar system has also overcome the drawbacks which are popular in the traditional scanning lidar systems such as complicated operation, overlap height between laser beam and telescope field of view In this system, the optical damage is reduced by using an integral coaxial transmitter and receiver. Some of the initial results obtained from the scanning lidar system are also presented. This study shows that boundary-layer structure and land–sea breeze circulation can be resolved from the developed scanning lidar system. The application of this lidar system to measure the pollutants over an industrial area is also discussed.

scholarly journals Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

2015 ◽  
Vol 15 (23) ◽  
pp. 34497-34532
Author(s):  
C. Pettersen ◽  
R. Bennartz ◽  
M. S. Kulie ◽  
A. J. Merrelli ◽  
M. D. Shupe ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Temperature Difference ◽  
Liquid Water ◽  
High Frequency ◽  
Passive Microwave ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Radar ◽  
Brightness Temperatures ◽  
High Frequency Microwave

Abstract. Multi-instrument, ground-based measurements provide unique and comprehensive datasets of the atmosphere for a specific location over long periods of time and resulting data compliments past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland from 2010–2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 g m−2 or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. This measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single scattering properties for several ice habits. Initial model results compare well against the four years of summer season isolated ice signature in the high-frequency microwave channels.

scholarly journals Towards Objective Identification and Tracking of Convective Outflow Boundaries in Next-Generation Geostationary Satellite Imagery

2019 ◽  
Author(s):  
Jason M. Apke ◽  
Kyle A. Hilburn ◽  
Steven D. Miller ◽  
David A. Peterson
Keyword(s):  
Optical Flow ◽  
Satellite Imagery ◽  
Numerical Models ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Primary Source ◽  
False Alarms ◽  
Identification Algorithm ◽  
Next Generation ◽  
Rapid Variation

Abstract. Sudden wind direction and speed shifts from outflow boundaries (OFBs) associated with deep convection significantly affect weather in the lower troposphere. Specific OFB impacts include rapid variation in wildfire spread rate and direction, the formation of convection, aviation hazards, and degradation of visibility and air quality due to mineral dust aerosol lofting. Despite their recognized importance to operational weather forecasters, OFB characterization (location, timing, intensity, etc.) in numerical models remains challenging. Thus, there remains a need for objective OFB identification algorithms to assist decision support services. With two operational next-generation geostationary satellites now providing coverage over North America, high-temporal and spatial resolution satellite imagery provides a unique resource for OFB identification. A system is conceptualized here designed around the new capabilities to objectively derive dense mesoscale motion flow fields in the Geostationary Operational Environmental Satellite (GOES)-16 imagery via optical flow. OFBs are identified here by isolating linear features in satellite imagery, and back-tracking them using optical flow to determine if they originated from a deep convection source. This objective OFB identification is tested with a case study of an OFB triggered dust storm over southern Arizona. Results highlight the importance of motion discontinuity preservation, revealing that standard optical flow algorithms used with previous studies underestimate wind speeds when background pixels are included in the computation with cloud targets. The primary source of false alarms is incorrect identification of line-like features in the initial satellite imagery. Future improvements to this process are described to ultimately provide a fully automated OFB identification algorithm.

scholarly journals Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery

2020 ◽  
Vol 13 (3) ◽  
pp. 1593-1608 ◽  
Author(s):  
Jason M. Apke ◽  
Kyle A. Hilburn ◽  
Steven D. Miller ◽  
David A. Peterson
Keyword(s):  
Optical Flow ◽  
Satellite Imagery ◽  
Numerical Models ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Primary Source ◽  
False Alarms ◽  
Identification Algorithm ◽  
Next Generation ◽  
Rapid Variation

Abstract. Sudden wind direction and speed shifts from outflow boundaries (OFBs) associated with deep convection significantly affect weather in the lower troposphere. Specific OFB impacts include rapid variation in wildfire spread rate and direction, the formation of convection, aviation hazards, and degradation of visibility and air quality due to mineral dust aerosol lofting. Despite their recognized importance to operational weather forecasters, OFB characterization (location, timing, intensity, etc.) in numerical models remains challenging. Thus, there remains a need for objective OFB identification algorithms to assist decision support services. With two operational next-generation geostationary satellites now providing coverage over North America, high-temporal- and high-spatial-resolution satellite imagery provides a unique resource for OFB identification. A system is conceptualized here designed around the new capabilities to objectively derive dense mesoscale motion flow fields in the Geostationary Operational Environmental Satellite 16 (GOES-16) imagery via optical flow. OFBs are identified here by isolating linear features in satellite imagery and backtracking them using optical flow to determine if they originated from a deep convection source. This “objective OFB identification” is tested with a case study of an OFB-triggered dust storm over southern Arizona. The results highlight the importance of motion discontinuity preservation, revealing that standard optical flow algorithms used with previous studies underestimate wind speeds when background pixels are included in the computation with cloud targets. The primary source of false alarms is the incorrect identification of line-like features in the initial satellite imagery. Future improvements to this process are described to ultimately provide a fully automated OFB identification algorithm.

Application of nighttime fog detection method using MSG8 SEVIRI in an arid environment

2020 ◽  
Author(s):  
Michael Weston ◽  
Marouane Temimi
Keyword(s):  
Brightness Temperature ◽  
United Arab Emirates ◽  
Temperature Difference ◽  
Land Surface ◽  
Visual Inspection ◽  
Detection Method ◽  
Arid Environment ◽  
Desert Region ◽  
Channel Ratio ◽  
Low Cloud

<p class="western"><span>The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology. Current methods make use of one or a combination of channel differencing from satellite instruments, surface observations, model data or artificial intelligence. An alternative to the brightness temperature difference method was developed for the GOES-R advanced baseline imager (ABI) which makes use of a channel ratio instead of a channel difference. We apply this method, the so called pseudo emissivity of the 3.9 µm channel, to SEVIRI MSG8 data over the United Arab Emirates, a desert region of the Arabian Peninsula. Low cloud is removed using temperature difference between ERA5 land surface temperature and 10.8 µm channel brightness temperature. Visual inspection of the final fog only mask shows that this method works well over this region. Verification at three sites where METAR data is available returned POD (FAR) of 0.77 (0.27), 0.50 (0.65) and 0.83 (0.26) respectively. Application of this method can be further developed to represent seasonal fog distribution and frequency across the United Arab Emirates.</span></p>

scholarly journals Limb Correction of Geostationary Infrared Imagery in Clear and Cloudy Regions to Improve Interpretation of RGB Composites for Real-Time Applications

2019 ◽  
Vol 36 (8) ◽  
pp. 1675-1690
Author(s):  
Nicholas J. Elmer ◽  
Emily Berndt ◽  
Gary Jedlovec ◽  
Kevin Fuell
Keyword(s):  
Brightness Temperature ◽  
Real Time ◽  
Satellite Imagery ◽  
Robust Method ◽  
Correction Algorithm ◽  
Infrared Imagery ◽  
Air Mass ◽  
Statistical Comparison ◽  
Correction Technique ◽  
Real Time Applications

AbstractRed–green–blue (RGB) composites are increasingly used by operational forecasters to interpret vast amounts of satellite imagery by reducing several bands into a single, easily understood product which identifies important atmospheric features with unique colors. Limb effects, a result of an increase in optical pathlength of the absorbing atmosphere between the satellite and Earth as viewing zenith angle increases, adversely affects RGB composite interpretation by causing anomalous reductions in brightness temperature, thus changing the color interpretation of the RGB composites. In a previous paper, Elmer et al. demonstrated a limb correction technique that effectively removes limb effects from polar-orbiting infrared channels in both clear and cloudy regions using latitudinally and seasonally varying correction coefficients. This study applies the Elmer et al. limb correction to Air Mass RGB composites derived from geostationary sensors and compares the limb-corrected geostationary imagery to limb-corrected polar-orbiter imagery and satellite-derived atmospheric profiles. A statistical comparison in overlapping regions shows that the limb correction reduces the absolute mean brightness temperature difference from 4–12 K to 0–2 K for all infrared bands, demonstrating that the Elmer et al. limb correction algorithm is a robust method of removing limb effects from infrared imagery derived from both geostationary and polar-orbiting sensors. The limb-corrected RGB composites derived from geostationary sensors present several advantages, including the improved depiction of atmospheric features and enabling wider use of imagery from overlapping geostationary coverage regions where viewing zenith angles are large for both geostationary sensors.

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