scholarly journals A Method for Calculating the Height of Overshooting Convective Cloud Tops Using Satellite-Based IR Imager and CloudSat Cloud Profiling Radar Observations

2016 ◽  
Vol 55 (2) ◽  
pp. 479-491 ◽  
Author(s):  
Sarah M. Griffin ◽  
Kristopher M. Bedka ◽  
Christopher S. Velden
Keyword(s):  
Brightness Temperature ◽  
Characteristic Temperature ◽  
Weather Prediction ◽  
Convective Cloud ◽  
Detection Algorithm ◽  
Lapse Rate ◽  
Temperature Lapse Rate ◽  
Cloud Tops ◽  
Height Assignment ◽  
Vertical Level

AbstractAssigning accurate heights to convective cloud tops that penetrate into the upper troposphere–lower stratosphere (UTLS) region using infrared (IR) satellite imagery has been an unresolved issue for the satellite research community. The height assignment for the tops of optically thick clouds is typically accomplished by matching the observed IR brightness temperature (BT) with a collocated rawinsonde or numerical weather prediction (NWP) profile. However, “overshooting tops” (OTs) are typically colder (in BT) than any vertical level in the associated profile, leaving the height of these tops undetermined using this standard approach. A new method is described here for calculating the heights of convectively driven OTs using the characteristic temperature lapse rate of the cloud top as it ascends into the UTLS region. Using 108 MODIS-identified OT events that are directly observed by the CloudSat Cloud Profiling Radar (CPR), the MODIS-derived brightness temperature difference (BTD) between the OT and anvil regions can be defined. This BTD is combined with the CPR- and NWP-derived height difference between these two regions to determine the mean lapse rate, −7.34 K km−1, for the 108 events. The anvil height is typically well known, and an automated OT detection algorithm is used to derive BTD, so the lapse rate allows a height to be calculated for any detected OT. An empirical fit between MODIS and geostationary imager IR BT for OTs and anvil regions was performed to enable application of this method to coarser-spatial-resolution geostationary data. Validation indicates that ~75% (65%) of MODIS (geostationary) OT heights are within ±500 m of the coincident CPR-estimated heights.

scholarly journals Thermal structure of intense convective clouds derived from GPS radio occultations

2012 ◽  
Vol 12 (12) ◽  
pp. 5309-5318 ◽  
Author(s):  
R. Biondi ◽  
W. J. Randel ◽  
S.-P. Ho ◽  
T. Neubert ◽  
S. Syndergaard
Keyword(s):  
Thermal Structure ◽  
Deep Convection ◽  
Lapse Rate ◽  
Orthogonal Polarization ◽  
Cold Temperatures ◽  
Temperature Lapse Rate ◽  
Convective Systems ◽  
Convective Clouds ◽  
Strong Inversion ◽  
Cloud Tops

Abstract. Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS occultations with CALIPSO profiles over deep convection. Results show a sharp spike in GPS bending angle highly correlated to the top of the clouds, corresponding to anomalously cold temperatures within the clouds. Above the clouds the temperatures return to background conditions, and there is a strong inversion at cloud top. For cloud tops below 14 km, the temperature lapse rate within the cloud often approaches a moist adiabat, consistent with rapid undiluted ascent within the convective systems.

scholarly journals Thermal structure of intense convective clouds derived from GPS radio occultations

2011 ◽  
Vol 11 (10) ◽  
pp. 29093-29116 ◽  
Author(s):  
R. Biondi ◽  
W. J. Randel ◽  
S.-P. Ho ◽  
T. Neubert ◽  
S. Syndergaard
Keyword(s):  
Thermal Structure ◽  
Deep Convection ◽  
Lapse Rate ◽  
Orthogonal Polarization ◽  
Cold Temperatures ◽  
Temperature Lapse Rate ◽  
Convective Systems ◽  
Convective Clouds ◽  
Strong Inversion ◽  
Cloud Tops

Abstract. Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS occultations with CALIPSO profiles over deep convection. Results show a sharp spike in GPS bending angle highly correlated to the top of the clouds, corresponding to anomalously cold temperatures within the clouds. Above the clouds the temperatures return to background conditions, and there is a strong inversion at cloud top. For cloud tops below 14 km, the temperature lapse rate within the cloud often approaches a moist adiabat, consistent with rapid undiluted ascent within the convective systems.

scholarly journals IMPROVEMENT OF FOREST FIRE DETECTION ALGORITHM USING BRIGHTNESS TEMPERATURE LAPSE RATE CORRECTION IN HIMAWARI-8 IR CHANNELS: APPLICATION TO THE 6 MAY 2017 SAMCHEOK CITY, KOREA

2018 ◽  
Vol XLII-3 ◽  
pp. 1353-1354
Author(s):  
S. H. Park ◽  
W. Park ◽  
H. S. Jung
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Continuous Monitoring ◽  
Fire Detection ◽  
Detection Algorithm ◽  
Time Of Day ◽  
Lapse Rate ◽  
Mountainous Areas ◽  
Temperature Lapse Rate ◽  
Forest Fire Detection

Forest fires are a major natural disaster that destroys a forest area and a natural environment. In order to minimize the damage caused by the forest fire, it is necessary to know the location and the time of day and continuous monitoring is required until fire is fully put out. We have tried to improve the forest fire detection algorithm by using a method to reduce the variability of surrounding pixels. We focused that forest areas of East Asia, part of the Himawari-8 AHI coverage, are mostly located in mountainous areas. The proposed method was applied to the forest fire detection in Samcheok city, Korea on May 6 to 10, 2017.

scholarly journals Characterizing and correcting the warm bias observed in AMDAR temperature observations

2021 ◽  
Author(s):  
Siebren de Haan ◽  
Paul M. A. de Jong ◽  
Jitze van der Meulen
Keyword(s):  
Meteorological Data ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Lapse Rate ◽  
Warm Bias ◽  
Temperature Lapse Rate ◽  
Additional Information ◽  
Temperature Bias ◽  
Temperature Observations ◽  
Nwp Model

Abstract. Some aircraft temperature observations, retrieved through the Aircraft Meteorological Data Relay (AMDAR), suffer from a significant warm bias when comparing observations with numerical weather prediction (NWP) model. In this manuscript we show that this warm bias of AMDAR temperature can be characterized and consequently reduced substantially. The characterization of this warm bias is based on the methodology of measuring temperature with a moving sensor and can be split into two separate processes. The first process depends on the flight phase of the aircraft and relates to difference of timing, as it appears that the time of measurement of altitude and temperature differ. When an aircraft is ascending or descending this will result in small bias in temperature due to the (on average) presence of an atmospheric temperature lapse rate. The second process is related to internal corrections applied to pressure altitude without feedback to temperature observation measurement. Based on NWP model temperature data combined with additional information on Mach number and true airspeed, we were able to estimate corrections using an 18 months period from January 2017 to July 2018. Next, the corrections were applied on AMDAR observations over the period from September 2018 to mid-December 2019. Comparing these corrected temperatures with (independent) radiosonde temperature observations demonstrates a reduction of the temperature bias from 0.5 K to around zero and reduction of standard deviation of almost 10 %.

scholarly journals Water Vapor Structure Displacements from Cloud-Free Meteosat Scenes and Their Interpretation for the Wind Field

2006 ◽  
Vol 45 (4) ◽  
pp. 556-575 ◽  
Author(s):  
G. Büche ◽  
H. Karbstein ◽  
A. Kummer ◽  
H. Fischer
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Wind Field ◽  
Wind Shear ◽  
Displacement Vector ◽  
Weather Prediction ◽  
Strong Wind ◽  
Atmospheric Layer ◽  
Statistical Point ◽  
Height Assignment

Abstract The evaluation of water vapor (WV) images taken by satellite-borne radiometers has become an essential source of data in modern meteorology. The analysis of structure displacements within sections of WV images is an effective way to get horizontal components of wind vectors. In contrast to intermediate-level and high-level clouds, the height assignment of displacement vectors connected with cloud-free WV structures needs additional information from atmospheric profiles. Nevertheless, interpreting these motion vectors as independent wind vectors and not simply matching them to any model wind field is tried. This contribution reports on the evaluation of structure displacements and how it can be done efficiently in the case of smooth and shallow scenes by the use of appropriate filters. Then, a series of height-assignment methods is tested for altitude-sensitive parameters such as wind shear and brightness contrast of pixels within segments used for structure tracking. The results are verified by comparison with reference wind data from the analysis of a weather prediction model as well as from radiosonde ascents. From a statistical point of view and for cases of strong wind shear it is clearly revealed that methods that use the effective brightness temperature, in particular from the coldest pixels, lead to better height assignment than do others that are based on the contribution function explicitly. From a series of individual cases it is found that the relative minimum of the difference between reference wind and clear-air structure displacement is not related uniquely to either the coldest (or warmest) pixel of the segment or the effective brightness temperature of pixels leading the tracking procedure. A cloud-free WV structure consequently contains information from an atmospheric layer whose displacement vector is a weighted sum over the motions within its specific thickness. Then the individual situation will determine whether a structure displacement reflects the motion at a well-defined height or whether it should be taken as a collective motion within an atmospheric layer that is an essential part of the upper troposphere.

scholarly journals A New Methodology for Estimating the Surface Temperature Lapse Rate Based on Grid Data and Its Application in China

2018 ◽  
Vol 10 (10) ◽  
pp. 1617 ◽  
Author(s):  
Yun Qin ◽  
Guoyu Ren ◽  
Tianlin Zhai ◽  
Panfeng Zhang ◽  
Kangmin Wen
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
North China ◽  
Seasonal Pattern ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Vertical Gradient ◽  
Lapse Rate ◽  
Grid Data ◽  
Temperature Lapse Rate

Land surface temperature (LST) is an important parameter in the study of the physical processes of land surface. Understanding the surface temperature lapse rate (TLR) can help to reveal the characteristics of mountainous climates and regional climate change. A methodology was developed to calculate and analyze land-surface TLR in China based on grid datasets of MODIS LST and digital elevation model (DEM), with a formula derived on the basis of the analysis of the temperature field and the height field, an image enhancement technique used to calculate gradient, and the fuzzy c-means (FCM) clustering applied to identify the seasonal pattern of the TLR. The results of the analysis through the methodology showed that surface temperature vertical gradient inversion widely occurred in Northeast, Northwest, and North China in winter, especially in the Xinjiang Autonomous Region, the northern and the western parts of the Greater Khingan Mountains, the Lesser Khingan Mountains, and the northern area of Northwest and North China. Summer generally witnessed the steepest TLR among the four seasons. The eastern Tibetan Plateau showed a distinctive seasonal pattern, where the steepest TLR happened in winter and spring, with a shallower TLR in summer. Large seasonal variations of TLR could be seen in Northeast China, where there was a steep TLR in spring and summer and a strong surface temperature vertical gradient inversion in winter. The smallest seasonal variation of TLR happened in Central and Southwest China, especially in the Ta-pa Mountains and the Qinling Mountains. The TLR at very high altitudes (>5 km) was usually steeper than at low altitudes, in all months of the year.

scholarly journals Atmospheric boundary layer during northeast monsoon over Tamilnadu and neighbourhood - A study using TOVS data

MAUSAM ◽  
2022 ◽  
Vol 53 (1) ◽  
pp. 75-86
Author(s):  
R. SURESH ◽  
P. V. SANKARAN ◽  
S. RENGARAJAN
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Bay Of Bengal ◽  
Active Phase ◽  
Cloud Layer ◽  
Lapse Rate ◽  
Northeast Monsoon ◽  
Temperature Lapse Rate ◽  
Thermodynamic Structure ◽  
Virtual Temperature

Thermodynamic structure of atmospheric boundary layer during October - December covering southwest and northeast monsoon activities over interior Tamilnadu (ITN), coastal Tamilnadu (CTN) and adjoining Bay of Bengal (BOB) has been studied using  TIROS Operational Vertical Sounder (TOVS) data of 1996-98. Heights of neutral stratified mixed layer, cloud layer and planetary boundary layer (PBL) have been estimated through available standard pressure level data. Highest PBL occurs during active northeast monsoon. Cloud layer thickness during weak northeast monsoon over interior Tamilnadu  is significantly higher than that over coastal Tamilnadu and  also over Bay of Bengal. Convective stability (instability)  of the atmosphere in 850-700 hPa layer is associated with weak / withdrawal (active) phase of northeast monsoon. One of  the plausible reasons for  subdued rainfall activity during weak northeast monsoon over interior Tamilnadu could be convective instability  seen over this region in 850-700 hPa layer. But the same is absent in CTN and BOB where no rainfall activity exists during weak monsoon phase. Virtual temperature lapse rate in 850-700 hPa layer exceeding (less than) 6oK/km is associated with active (weak) phase of northeast monsoon over the interior, coastal Tamilnadu and Bay of Bengal.

scholarly journals FORUM: Unique Far-Infrared Satellite Observations to Better Understand How Earth Radiates Energy to Space

2020 ◽  
Vol 101 (12) ◽  
pp. E2030-E2046 ◽  
Author(s):  
L. Palchetti ◽  
H. Brindley ◽  
R. Bantges ◽  
S. A. Buehler ◽  
C. Camy-Peyret ◽  
...  
Keyword(s):  
Climate Models ◽  
Longwave Radiation ◽  
Far Infrared ◽  
Lapse Rate ◽  
High Spectral Resolution ◽  
Critical Parameters ◽  
Temperature Lapse Rate ◽  
Stratospheric Water Vapor ◽  
Explorer Mission ◽  
Spectrally Resolved

AbstractThe outgoing longwave radiation (OLR) emitted to space is a fundamental component of the Earth’s energy budget. There are numerous, entangled physical processes that contribute to OLR and that are responsible for driving, and responding to, climate change. Spectrally resolved observations can disentangle these processes, but technical limitations have precluded accurate space-based spectral measurements covering the far infrared (FIR) from 100 to 667 cm−1 (wavelengths between 15 and 100 µm). The Earth’s FIR spectrum is thus essentially unmeasured even though at least half of the OLR arises from this spectral range. The region is strongly influenced by upper-tropospheric–lower-stratospheric water vapor, temperature lapse rate, ice cloud distribution, and microphysics, all critical parameters in the climate system that are highly variable and still poorly observed and understood. To cover this uncharted territory in Earth observations, the Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission has recently been selected as ESA’s ninth Earth Explorer mission for launch in 2026. The primary goal of FORUM is to measure, with high absolute accuracy, the FIR component of the spectrally resolved OLR for the first time with high spectral resolution and radiometric accuracy. The mission will provide a benchmark dataset of global observations which will significantly enhance our understanding of key forcing and feedback processes of the Earth’s atmosphere to enable more stringent evaluation of climate models. This paper describes the motivation for the mission, highlighting the scientific advances that are expected from the new measurements.

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