scholarly journals An Automated Detection Methodology for Dry Well-Mixed Layers

2019 ◽  
Vol 36 (5) ◽  
pp. 761-779
Author(s):  
Stephen D. Nicholls ◽  
Karen I. Mohr
Keyword(s):  
Water Vapor ◽  
Vertical Profile ◽  
Input Data ◽  
Profile Analysis ◽  
Potential Temperature ◽  
Data File ◽  
Mixing Ratio ◽  
Land Surfaces ◽  
Water Vapor Mixing Ratio ◽  
Mixed Layers

AbstractThe intense surface heating over arid land surfaces produces dry well-mixed layers (WML) via dry convection. These layers are characterized by nearly constant potential temperature and low, nearly constant water vapor mixing ratio. To further the study of dry WMLs, we created a detection methodology and supporting software to automate the identification and characterization of dry WMLs from multiple data sources including rawinsondes, remote sensing platforms, and model products. The software is a modular code written in Python, an open-source language. Radiosondes from a network of synoptic stations in North Africa were used to develop and test the WML detection process. The detection involves an iterative decision tree that ingests a vertical profile from an input data file, performs a quality check for sufficient data density, and then searches upward through the column for successive points where the simultaneous changes in water vapor mixing ratio and potential temperature are less than the specified maxima. If points in the vertical profile meet the dry WML identification criteria, statistics are generated detailing the characteristics of each layer in the profile. At the end of the vertical profile analysis, there is an option to plot analyzed profiles in a variety of file formats. Initial results show that the detection methodology can be successfully applied across a wide variety of input data and North African environments and for all seasons. It is sensitive enough to identify dry WMLs from other types of isentropic phenomena such as subsidence layers and distinguish the current day’s dry WML from previous days.

scholarly journals A Lagrangian Objective Analysis Technique for Assimilating In Situ Observations with Multiple-Radar-Derived Airflow

2007 ◽  
Vol 135 (7) ◽  
pp. 2417-2442 ◽  
Author(s):  
Conrad L. Ziegler ◽  
Michael S. Buban ◽  
Erik N. Rasmussen
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Potential Temperature ◽  
Cloud Base ◽  
Mixing Ratio ◽  
Lagrangian Analysis ◽  
Analysis Technique ◽  
Virtual Potential Temperature ◽  
Water Vapor Mixing Ratio

Abstract A new Lagrangian analysis technique is developed to assimilate in situ boundary layer measurements using multi-Doppler-derived wind fields, providing output fields of water vapor mixing ratio, potential temperature, and virtual potential temperature from which the lifting condensation level (LCL) and relative humidity (RH) fields are derived. The Lagrangian analysis employs a continuity principle to bidirectionally distribute observed values of conservative variables with the 3D, evolving boundary layer airflow, followed by temporal and spatial interpolation to an analysis grid. Cloud is inferred at any grid point whose height z > zLCL or equivalently where RH ≥ 100%. Lagrangian analysis of the cumulus field is placed in the context of gridded analyses of visible satellite imagery and photogrammetric cloud-base area analyses. Brief illustrative examples of boundary layer morphology derived with the Lagrangian analysis are presented based on data collected during the International H2O Project (IHOP): 1) a dryline on 22 May 2002; 2) a cold-frontal–dryline “triple point” intersection on 24 May 2002. The Lagrangian analysis preserves the sharp thermal gradients across the cold front and drylines and reveals the presence of undulations and plumes of water vapor mixing ratio and virtual potential temperature associated with deep penetrative updraft cells and convective roll circulations. Derived cloud fields are consistent with satellite-inferred cloud cover and cloud-base locations.

scholarly journals Predictability of an Advection Fog Event over North China. Part I: Sensitivity to Initial Condition Differences

2014 ◽  
Vol 142 (5) ◽  
pp. 1803-1822 ◽  
Author(s):  
Huiqin Hu ◽  
Qinghong Zhang ◽  
Baoguo Xie ◽  
Yue Ying ◽  
Jiping Zhang ◽  
...  
Keyword(s):  
Water Vapor ◽  
North China ◽  
Potential Temperature ◽  
Meteorological Variable ◽  
Horizontal Wind ◽  
Initial Condition ◽  
Mixing Ratio ◽  
Water Vapor Mixing Ratio ◽  
Major Factors ◽  
Advection Fog

Abstract The predictability of a dense advection fog event on 21 February 2007 over north China (NC) is investigated with ensemble simulations using the Weather Research and Forecasting Model (WRF). Members with the best and worst simulation are selected from the ensemble, and their initial condition (IC) differences are explored. To test the sensitivity of fog simulation to those differences, the model is initialized with ICs that change linearly from the worst member to the best member, and the changes in simulated results are examined. The improvement in simulations due to the linear improvement of ICs is found to be monotonic. The IC differences at lower levels are of more influence to the simulation than IC differences at higher levels. By removing the IC differences of each meteorological variable individually, it is found that improvements in potential temperature and horizontal wind are more important than that of water vapor mixing ratio in this case. Additionally, the linear improvement in each meteorological variable also contributes monotonically to the simulated results. The budget analyses of the tendency of potential temperature and water vapor mixing ratio show that turbulence mixing and advection are the major factors contributing to the formation of fog. The correct initial temperature field ensures the formation and maintenance of an inversion, and the correct initial wind field ensures the correct transport of temperature and moisture in this case. Further discussion examines the reasons for the monotonic behavior in the simulation improvement.

scholarly journals Aircraft Evaluation of Ground-Based Raman Lidar Water Vapor Turbulence Profiles in Convective Mixed Layers

2014 ◽  
Vol 31 (5) ◽  
pp. 1078-1088 ◽  
Author(s):  
D. D. Turner ◽  
R. A. Ferrare ◽  
V. Wulfmeyer ◽  
A. J. Scarino
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Southern Great Plains ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Convective Mixed Layer ◽  
Water Vapor Mixing Ratio ◽  
Mixed Layers

AbstractHigh temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed.Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally.

Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection

2019 ◽  
Vol 77 (3) ◽  
pp. 1081-1100 ◽  
Author(s):  
Neil P. Lareau
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Latent Heat ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Mixing Ratio ◽  
Convective Boundary ◽  
Water Vapor Mixing Ratio

Abstract Doppler and Raman lidar observations of vertical velocity and water vapor mixing ratio are used to probe the physics and statistics of subcloud and cloud-base latent heat fluxes during cumulus convection at the ARM Southern Great Plains (SGP) site in Oklahoma, United States. The statistical results show that latent heat fluxes increase with height from the surface up to ~0.8Zi (where Zi is the convective boundary layer depth) and then decrease to ~0 at Zi. Peak fluxes aloft exceeding 500 W m−2 are associated with periods of increased cumulus cloud cover and stronger jumps in the mean humidity profile. These entrainment fluxes are much larger than the surface fluxes, indicating substantial drying over the 0–0.8Zi layer accompanied by moistening aloft as the CBL deepens over the diurnal cycle. We also show that the boundary layer humidity budget is approximately closed by computing the flux divergence across the 0–0.8Zi layer. Composite subcloud velocity and water vapor anomalies show that clouds are linked to coherent updraft and moisture plumes. The moisture anomaly is Gaussian, most pronounced above 0.8Zi and systematically wider than the velocity anomaly, which has a narrow central updraft flanked by downdrafts. This size and shape disparity results in downdrafts characterized by a high water vapor mixing ratio and thus a broad joint probability density function (JPDF) of velocity and mixing ratio in the upper CBL. We also show that cloud-base latent heat fluxes can be both positive and negative and that the instantaneous positive fluxes can be very large (~10 000 W m−2). However, since cloud fraction tends to be small, the net impact of these fluxes remains modest.

scholarly journals A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals

2019 ◽  
Vol 12 (7) ◽  
pp. 3943-3961 ◽  
Author(s):  
Ali Jalali ◽  
Shannon Hicks-Jalali ◽  
Robert J. Sica ◽  
Alexander Haefele ◽  
Thomas von Clarmann
Keyword(s):  
Water Vapor ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Mixing Ratio ◽  
A Priori Information ◽  
Fine Grid ◽  
Large Power ◽  
Priori Information ◽  
Water Vapor Mixing Ratio

Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.

scholarly journals Quantifying the Imprint of a Severe Hector Thunderstorm during ACTIVE/SCOUT-O3 onto the Water Content in the Upper Troposphere/Lower Stratosphere

2009 ◽  
Vol 137 (8) ◽  
pp. 2493-2514 ◽  
Author(s):  
Charles Chemel ◽  
Maria R. Russo ◽  
John A. Pyle ◽  
Ranjeet S. Sokhi ◽  
Cornelius Schiller
Keyword(s):  
Water Vapor ◽  
Water Content ◽  
Lower Stratosphere ◽  
Horizontal Resolution ◽  
Convective Transport ◽  
Mixing Ratio ◽  
Field Campaign ◽  
Upper Troposphere ◽  
Ice Particles ◽  
Water Vapor Mixing Ratio

Abstract The development of a severe Hector thunderstorm that formed over the Tiwi Islands, north of Australia, during the Aerosol and Chemical Transport in Tropical Convection/Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere (ACTIVE/SCOUT-O3) field campaign in late 2005, is simulated by the Advanced Research Weather Research and Forecasting (ARW) model and the Met Office Unified Model (UM). The general aim of this paper is to investigate the role of isolated deep convection over the tropics in regulating the water content in the upper troposphere/lower stratosphere (UT/LS). Using a horizontal resolution as fine as 1 km, the numerical simulations reproduce the timing, structure, and strength of Hector fairly well when compared with field campaign observations. The sensitivity of results from ARW to horizontal resolution is investigated by running the model in a large-eddy simulation mode with a horizontal resolution of 250 m. While refining the horizontal resolution to 250 m leads to a better representation of convection with respect to rainfall, the characteristics of the Hector thunderstorm are basically similar in space and time to those obtained in the 1-km-horizontal-resolution simulations. Several overshooting updrafts penetrating the tropopause are produced in the simulations during the mature stage of Hector. The penetration of rising towering cumulus clouds into the LS maintains the entrainment of air at the interface between the UT and the LS. Vertical exchanges resulting from this entrainment process have a significant impact on the redistribution of atmospheric constituents within the UT/LS region at the scale of the islands. In particular, a large amount of water is injected in the LS. The fate of the ice particles as Hector develops drives the water vapor mixing ratio to saturation by sublimation of the injected ice particles, moistening the air in the LS. The moistening was found to be fairly significant above 380 K and averaged about 0.06 ppmv in the range 380–420 K for ARW. As for UM, the moistening was found to be much larger (about 2.24 ppmv in the range of 380–420 K) than for ARW. This result confirms that convective transport can play an important role in regulating the water vapor mixing ratio in the LS.

scholarly journals Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)<sup>2</sup> Observational Prototype Experiment

2015 ◽  
Vol 15 (5) ◽  
pp. 2867-2881 ◽  
Author(s):  
E. Hammann ◽  
A. Behrendt ◽  
F. Le Mounier ◽  
V. Wulfmeyer
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Temperature Gradient ◽  
Atmospheric Boundary Layer ◽  
Average Power ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Backscatter Signal ◽  
Low Background ◽  
Water Vapor Mixing Ratio

Abstract. The temperature measurements of the rotational Raman lidar of the University of Hohenheim (UHOH RRL) during the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observation Prototype Experiment (HOPE) in April and May 2013 are discussed. The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10 W average power at 50 Hz, a two-mirror scanner, a 40 cm receiving telescope, and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor. The main measurement variable of the UHOH RRL is temperature. For the HOPE campaign, the lidar receiver was optimized for high and low background levels, with a novel switch for the passband of the second rotational Raman channel. The instrument delivers atmospheric profiles of water vapor mixing ratio as well as particle backscatter coefficient and particle extinction coefficient as further products. As examples for the measurement performance, measurements of the temperature gradient and water vapor mixing ratio revealing the development of the atmospheric boundary layer within 25 h are presented. As expected from simulations, a reduction of the measurement uncertainty of 70% during nighttime was achieved with the new low-background setting. A two-mirror scanner allows for measurements in different directions. When pointing the scanner to low elevation, measurements close to the ground become possible which are otherwise impossible due to the non-total overlap of laser beam and receiving telescope field of view in the near range. An example of a low-level temperature measurement is presented which resolves the temperature gradient at the top of the stable nighttime boundary layer 100 m above the ground.

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