Water vapor and temperature lapse rate feedbacks in the mid-latitude seasonal cycle

1996 ◽  
Vol 23 (14) ◽  
pp. 1761-1764 ◽  
Author(s):  
Haijun Hu
Keyword(s):  
Water Vapor ◽  
Seasonal Cycle ◽  
Lapse Rate ◽  
Temperature Lapse Rate

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 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 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 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.

Using Radio Occultation to Detect Clouds in the Middle and Upper Troposphere

2021 ◽  
Author(s):  
Jeana Mascio ◽  
Stephen S. Leroy ◽  
Robert P. d’Entremont ◽  
Thomas Connor ◽  
E. Robert Kursinski
Keyword(s):  
Relative Humidity ◽  
High Performance ◽  
Radio Occultation ◽  
Three Dimensional ◽  
Roc Curves ◽  
Lapse Rate ◽  
Cloud Detection ◽  
Upper Troposphere ◽  
Temperature Lapse Rate ◽  
Direct Sensitivity

AbstractRadio occultation (RO) measurements have little direct sensitivity to clouds, but recent studies have shown that they may have an indirect sensitivity to thin, high clouds that are difficult to detect using conventional passive space-based cloud sensors. We implement two RO-based cloud detection (ROCD) algorithms for atmospheric layers in the middle and upper troposphere. The first algorithm is based on the methodology of a previous study, which explored signatures caused by upper tropospheric clouds in RO profiles according to retrieved relative humidity, temperature lapse rate, and gradients in log-refractivity (ROCD-P), and the second is based on inferred relative humidity alone (ROCD-M). In both, atmospheric layers are independently predicted as cloudy or clear based on observational data, including high performance RO retrievals. In a demonstration, we use data from 10 days spanning seven months in 2020 of FORMOSAT-7/COSMIC-2. We use the forecasts of NOAA GFS to aid in the retrieval of relative humidity. The prediction is validated with a cloud truth dataset created from the imagery of the GOES-16 Advanced Baseline Imager (ABI) satellite and the GFS three-dimensional analysis of cloud state conditions. Given these two algorithms for the presence or absence of clouds, confusion matrices and receiver operating characteristic (ROC) curves are used to analyze how well these algorithms perform. The ROCD-M algorithm has a balanced accuracy, which defines the quality of the classification test that considers both the sensitivity and specificity, greater than 70% for all altitudes between 6 and 10.25 km.

Generalized lapse rate formulas for use in entraining CAPE calculations

2021 ◽  
Author(s):  
John M. Peters ◽  
Jake P. Mulholland ◽  
Daniel R. Chavas
Keyword(s):  
Large Eddy Simulations ◽  
Mixed Phase ◽  
Lapse Rate ◽  
Temperature Lapse Rate ◽  
Large Eddy ◽  
Energy Sink ◽  
Entropy Conservation ◽  
Hydrostatic Balance ◽  
New Formula ◽  
Non Equilibrium

AbstractCommon assumptions in temperature lapse rate formulas for lifted air parcels include neglecting mixing, hydrostatic balance, the removal of all condensate once it forms (pseudoadiabatic), and/or the retention of all condensate within the parcel (adiabatic). These formulas are commonly derived from the conservation of entropy, which leads to errors when non-equilibrium mixed-phase condensate is present. To evaluate these assumptions, a new general lapse rate formula is derived from an expression for energy conservation, rather than entropy conservation. This new formula incorporates mixing of the parcel with its surroundings, relaxes the hydrostatic assumption, allows for non-equilibrium mixed-phase condensate, and can be formulated for pseudoadiabatic or adiabatic ascent. The new formula is shown to exactly conserve entropy for reversible ascent. Predictions by the new formula are compared to that of older and less general formulas. The errors in previous formulas arise from the assumption of hydrostatic balance, which results in considerable warm biases due to the neglect of the energy sink from buoyancy. Predictions of ascent with entrainment using the new formula are then compared to parcel properties along trajectories in large eddy simulations. Simulated parcel properties are better predicted by the formula using a diluted analogy to adiabatic ascent, wherein condensate is diluted at the same rate as other parcel properties, than by the diluted analogy to pseudoadiabatic ascent, wherein all condensate is removed. These results suggest that CAPE should be computed with adiabatic, rather than pseudoadiabatic, parcel ascent.

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