scholarly journals Review of Reid et al, Observations and hypotheses related to low to middle free tropospheric aerosol, water vapor and altocumulus cloud layers within convective weather regimes: A SEAC4RS case study

2019 ◽  
Author(s):  
Anonymous
Keyword(s):  
Water Vapor ◽  
Weather Regimes ◽  
Tropospheric Aerosol ◽  
Convective Weather

scholarly journals A case study of convectively sourced water vapor observed in the overworld stratosphere over the United States

2017 ◽  
Vol 122 (17) ◽  
pp. 9529-9554 ◽  
Author(s):  
Jessica B. Smith ◽  
David M. Wilmouth ◽  
Kristopher M. Bedka ◽  
Kenneth P. Bowman ◽  
Cameron R. Homeyer ◽  
...  
Keyword(s):  
United States ◽  
Water Vapor ◽  
The United States

scholarly journals Rehydration of Dried-Out Specimens: a New Approach

2020 ◽  
Vol 34 (1) ◽  
pp. 73-86
Author(s):  
F. Neisskenwirth
Keyword(s):  
Water Vapor ◽  
Soft Tissue ◽  
Second Step ◽  
Phosphate Solution ◽  
Glycerol Solution ◽  
New Approach ◽  
The Third ◽  
Demineralized Water ◽  
Chemically Induced

Abstract Different procedures are proposed in the literature for the rehydration of dried-out specimens. These procedures vary greatly in their efficiency and application. This work describes a new procedure that is inspired by the literature but that avoids heating the specimens. This method was applied to reconditioning dried-out specimens from a historical collection (Swiss freshwater fishes, bird brains, and bird eyes), stored at the Naturhistorisches Museum Bern in Switzerland. The procedure consists of five steps. The first step is the softening of hardened soft tissue with benzaldehyde and demineralized water. The second step is an indirect rehydration with water vapor. The third step is a chemically induced direct hydration using a trisodium phosphate solution that allows the specimen to swell in size before being washed with water to remove all additives. Finally, the rehydrated specimen is transferred into new preserving fluid. Because the dehydrating properties of ethanol as a preservative are problematic, this paper presents the results of an experimental case study using a glycerol solution as a preservation fluid.

Raman Lidar Measurements during the International H2O Project. Part II: Case Studies

2006 ◽  
Vol 23 (2) ◽  
pp. 170-183 ◽  
Author(s):  
D. N. Whiteman ◽  
B. Demoz ◽  
G. Schwemmer ◽  
B. Gentry ◽  
P. Di Girolamo ◽  
...  
Keyword(s):  
Water Vapor ◽  
Case Studies ◽  
The United States ◽  
Back Trajectory ◽  
Cirrus Cloud ◽  
Raman Lidar ◽  
Cloud Optical Depth ◽  
Back Trajectory Analysis ◽  
Cloud Modeling

Abstract The NASA GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June 2002 in the midwestern part of the United States. The SRL system configuration and methods of data analysis were described in Part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of Lidar Atmospheric Sensing Experiment (LASE) airborne water vapor lidar and chilled-mirror radiosonde are performed. Two case studies are then presented: one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the daytime SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in its meteorological context. Upper-tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud optical depth, extinction-to-backscatter ratio, ice water content, cirrus particle size, and both particle and volume depolarization ratios. A stability and back-trajectory analysis is performed to study the origin of wave activity in one of the cloud layers. These unprecedented cirrus cloud measurements are being used in a cirrus cloud modeling study.

scholarly journals Multisensor Comparison and Numerical Modeling of Atmospheric Water Fields: A VOLTAIRE Case Study over Cyprus

2008 ◽  
Vol 23 (4) ◽  
pp. 674-701 ◽  
Author(s):  
Stefano Mariani ◽  
Christophe Accadia ◽  
Nazario Tartaglione ◽  
Marco Casaioli ◽  
Marco Gabella ◽  
...  
Keyword(s):  
Water Vapor ◽  
Mediterranean Sea ◽  
Rain Gauge ◽  
Limited Area ◽  
Atmospheric Water ◽  
Limited Area Model ◽  
Trmm Pr ◽  
Rain Gauge Network ◽  
Total Column

Abstract This paper presents a study performed within the framework of the European Union’s (EU) VOLTAIRE project (Fifth Framework Programme). Among other tasks, the project aimed at the integration of the Tropical Rainfall Measuring Mission (TRMM) data with ground-based observations and at the comparison between water fields (precipitation and total column water vapor) as estimated by multisensor observations and predicted by NWP models. In particular, the VOLTAIRE project had as one of its main objectives the goal of assessing the application of satellite-borne instrument measures to model verification. The island of Cyprus was chosen as the main “test bed,” because it is one of the few European territories covered by the passage of the TRMM Precipitation Radar (PR) and it has a dense rain gauge network and an operational weather radar. TRMM PR provides, until now, the most reliable space-borne spatial high-resolution precipitation measurements. Attention is focused on the attempt to define a methodology, using state-of-the-art diagnostic methods, for a comprehensive evaluation of water fields as forecast by a limited area model (LAM). An event that occurred on 5 March 2003, associated with a slow cyclone moving eastward over the Mediterranean Sea, is presented as a case study. The atmospheric water fields were forecast over the eastern Mediterranean Sea using the Bologna Limited Area Model (BOLAM). Data from the Cyprus ground-based radar, the Cyprus rain gauge network, the Special Sensor Microwave Imager (SSM/I), and the TRMM PR were used in the comparison. Ground-based radar and rain gauge data were merged together in order to obtain a better representation of the rainfall event over the island. TRMM PR measurements were employed to range-adjust the ground-based radar data using a linear regression algorithm. The observed total column water vapor has been employed to assess the forecast quality of large-scale atmospheric patterns; such an assessment has been performed by means of the Hoffman diagnostic method applied to the entire total column water vapor field. Subsequently, in order to quantify the spatial forecast error at the finer BOLAM scale (0.09°), the object-oriented contiguous rain area (CRA) analysis was chosen as a comparison method for precipitation. An assessment of the main difficulties in employing CRA in an operational framework, especially over such a small verification domain, is also discussed in the paper.

Using the GOES-16 Split Window Difference to Detect a Boundary prior to Cloud Formation

2018 ◽  
Vol 99 (8) ◽  
pp. 1541-1544 ◽  
Author(s):  
Daniel T. Lindsey ◽  
Dan Bikos ◽  
Lewis Grasso
Keyword(s):  
Water Vapor ◽  
Infrared Spectrum ◽  
Temporal Resolution ◽  
Cloud Formation ◽  
Operational Forecast ◽  
Low Level ◽  
Spectral Bands ◽  
The Difference ◽  
Local Water

AbstractGeostationary Operational Environmental Satellite-16 (GOES-16) was launched into geostationary orbit in late 2016 and began providing unprecedented spatial and temporal resolution imagery early in 2017. Its Advanced Baseline Imager has additional spectral bands including two in the “clear” window and “dirty window” portion of the infrared spectrum, and the difference of these two bands, sometimes called the split window difference, provides unique information about low-level water vapor. Under certain conditions, low-level convergence along a boundary can cause local water vapor pooling, and the signal of this pooling can sometimes be detected by GOES-16 prior to any cloud formation. This case study from 15 June 2017 illustrates how the technique might be used in an operational forecast setting. A boundary in western Kansas was detected using the split window difference more than 2 h before the first cloud formed.

scholarly journals Reconstruction of the Radar Reflectivity of Convective Storms Based on Deep Learning and Himawari-8 Observations

2021 ◽  
Vol 13 (16) ◽  
pp. 3330
Author(s):  
Mingshan Duan ◽  
Jiangjiang Xia ◽  
Zhongwei Yan ◽  
Lei Han ◽  
Lejian Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Universal Coverage ◽  
Radar Reflectivity ◽  
Test Dataset ◽  
Convective Storms ◽  
Imbalance Problem ◽  
Channel Input ◽  
Convective Weather ◽  
Radiance Data

Radar reflectivity (RR) greater than 35 dBZ usually indicates the presence of severe convective weather, which affects a variety of human activities, including aviation. However, RR data are scarce, especially in regions with poor radar coverage or substantial terrain obstructions. Fortunately, the radiance data of space-based satellites with universal coverage can be converted into a proxy field of RR. In this study, a convolutional neural network-based data-driven model is developed to convert the radiance data (infrared bands 07, 09, 13, 16, and 16–13) of Himawari-8 into the radar combined reflectivity factor (CREF). A weighted loss function is designed to solve the data imbalance problem due to the sparse convective pixels in the sample. The developed model demonstrates an overall reconstruction capability and performs well in terms of classification scores with 35 dBZ as the threshold. A five-channel input is more efficient in reconstructing the CREF than the commonly used one-channel input. In a case study of a convective event over North China in the summer using the test dataset, U-Net reproduces the location, shape and strength of the convective storm well. The present RR reconstruction technology based on deep learning and Himawari-8 radiance data is shown to be an efficient tool for producing high-resolution RR products, which are especially needed for regions without or with poor radar coverage.

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