scholarly journals Microwave remote sensing of water vapor in the atmosphere

2003 ◽  
Vol 58 (2) ◽  
pp. 81-89
Author(s):  
N. Kämpfer ◽  
B. Deuber ◽  
D. Feist ◽  
D. Gerber ◽  
C. Mätzler ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Middle Atmosphere ◽  
Microwave Remote Sensing ◽  
Applied Physics ◽  
First Results ◽  
Dimensional Distribution ◽  
Microwave Radiometers ◽  
Remote Sensing Methods ◽  
Vapor Distribution

Abstract. Water vapor in the atmosphere plays a crucial role in climate and in atmospheric processes. Due to its long chemical lifetime it can be used as a tracer for investigations of dynamical processes in the middle atmosphere. Microwave radiometry is one of the few remote sensing methods which is capable of inferring Information on the water vapor content of the troposphere to the mesosphere, however with a different altitude resolution. Different microwave radiometers that can be operated from the ground and from an airborne platform have been built at the Institute of Applied Physics, University of Berne. The paper presents the method of microwave remote sensing and gives an overview of recently achieved results with regard to water vapor distribution as a function of altitude and Iatitude. First results of an imaging radiometer for the two dimensional distribution of liquid water is presented.

scholarly journals A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)

2018 ◽  
Author(s):  
Heike Konow ◽  
Marek Jacob ◽  
Felix Ament ◽  
Susanne Crewell ◽  
Florian Ewald ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Joint Analysis ◽  
Wet Season ◽  
Data Set ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Wide Range ◽  
Research Aircraft ◽  
Microwave Radiometers

Abstract. Cloud properties and their environmental conditions were observed during four aircraft campaigns over the North Atlantic on 37 flights. The Halo Microwave Package (HAMP) was deployed on the German research aircraft HALO (High Altitude LOng range research aircraft) during these four campaigns. HAMP comprises microwave radiometers with 26 channels in the frequency range between 20 and 183 GHz and a 35 GHz cloud radar. The four campaigns took place between December 2013 and October 2016 out of Barbados and Iceland. Measured situations cover a wide range of conditions including the dry and wet season over the tropical Atlantic and the cold and warm sectors of mid-latitude cyclones. The data set we present here contains measurements of the radar reflectivity factor and linear depolarization ratio from cloud radar, brightness temperatures from microwave radiometers, and atmospheric profiles from dropsondes. It represents a unique combination of active and passive microwave remote sensing measurements and 525 in-situ measured dropsonde profiles. The data from these different instruments are quality controlled and unified into one common format for easy combination of data and joint analysis. The data are available from the CERA database for the four campaigns individually (https://doi.org/10.1594/WDCC/HALO_measurements_1, https://doi.org/10.1594/WDCC/HALO_measurements_2, https://doi.org/10.1594/WDCC/HALO_measurements_3, https://doi.org/10.1594/WDCC/HALO_measurements_4). This data set allows for analyses to get insight into cloud properties and atmospheric state in remote regions over the tropical and mid-latitude Atlantic. In this paper, we describe the four campaigns, the data, and the quality control applied to the data.

scholarly journals A New Passive Microwave Tool for Operational Forest Fires Detection: A Case Study of Siberia in 2019

2020 ◽  
Vol 12 (5) ◽  
pp. 835 ◽  
Author(s):  
Costas A. Varotsos ◽  
Vladimir F. Krapivin ◽  
Ferdenant A. Mkrtchyan
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Forest Fires ◽  
Forest Canopy ◽  
Hydrological Model ◽  
Microwave Remote Sensing ◽  
Sensing Platform ◽  
Decision Making System ◽  
Microwave Radiometers

The purpose of this paper is to present a new method for early detection of forest fires, especially in forest zones prone to fires using microwave remote sensing and information-modeling tools. A decision-making system is developed as a tool for operational coupled analysis of modeling results and remote sensing data. The main operating structure of this system has blocks that calculate the moisture of forest canopy, the soil-litter layer, and the forest physical temperature using the observed brightness temperature provided by the flying platform IL-18 equipped with passive microwave radiometers of 1.43, 13.3 and 37.5 GHz frequencies. The hydrological parameters of the forest are assessed with both a developed regional hydrological model and remote sensing observations. The hydrological model allows for the detection of fire-prone zones that are subject to remote sensing when modeling results are corrected and thermal temperatures are evaluated. An approach for the real time forest fires classification via daytime remote sensing observations is proposed. The relative theoretical and experimental results presented here have allowed us to use a new approach to forests monitoring during periods of potential fire. A decision-making algorithm is presented that aims at analyzing data flows from radiometers located on the remote sensing platform to calculate the probability of forest fire occurring in geographical pixels. As case study, the state of forest fires that occurred in Siberia in 2019 using microwave remote sensing measurements conducted by a flying IL-18 laboratory is presented. This remote sensing platform is equipped with optical and microwave tools that allow the optical and microwave images of the observed forest areas. The main operating frequencies of microwave radiometers are 1.43, 13.3 and 37.5 GHz. Microwave radiometers provide data on water content in the forest canopy and on litter and physical temperatures. Based on the long-term measurements made in Siberia, the possible improvement of the proposed decision-making system for future relevant studies is discussed in detail. The basic idea of cost-effective monitoring of forested areas consists of a two-stage exploration of fire risk zones. The first monitoring stage is performed using the hydrological model of the study area to identify low moisture areas of the forest canopy and litter. The second stage of monitoring is conducted using the remote sensing platform only in the local fire-dangerous areas in order to more precisely identify the areas prone to fire and to detect and diagnose real burning zones. The developed algorithm allows the calculation of physical temperatures and the detection of temperature anomalies based on measured brightness temperatures. Finally, the spatial distribution of the probability of forest fire occurrence is given as an example of the decision-making system along with a comparison of this distribution with the satellite images provided by the EOSDIS Land data.

scholarly journals A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)

2019 ◽  
Vol 11 (2) ◽  
pp. 921-934 ◽  
Author(s):  
Heike Konow ◽  
Marek Jacob ◽  
Felix Ament ◽  
Susanne Crewell ◽  
Florian Ewald ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Joint Analysis ◽  
Wet Season ◽  
Data Set ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Wide Range ◽  
Research Aircraft ◽  
Microwave Radiometers

Abstract. Cloud properties and their environmental conditions were observed during four aircraft campaigns over the North Atlantic on 37 flights. The Halo Microwave Package (HAMP) was deployed on the German research aircraft HALO (High Altitude Long Range Research Aircraft) during these four campaigns. HAMP comprises microwave radiometers with 26 channels in the frequency range between 20 and 183 GHz and a 35 GHz cloud radar. The four campaigns took place between December 2013 and October 2016 out of Barbados and Iceland. Measured situations cover a wide range of conditions including the dry and wet season over the tropical Atlantic and the cold and warm sectors of midlatitude cyclones. The data set we present here contains measurements of the radar reflectivity factor and linear depolarization ratio from cloud radar, brightness temperatures from microwave radiometers and atmospheric profiles from dropsondes. It represents a unique combination of active and passive microwave remote sensing measurements and 525 in situ-measured dropsonde profiles. The data from these different instruments are quality controlled and unified into one common format for easy combination of data and joint analysis. The data are available from the CERA database for the four campaigns individually (https://doi.org/10.1594/WDCC/HALO_measurements_1, https://doi.org/10.1594/WDCC/HALO_measurements_2, https://doi.org/10.1594/WDCC/HALO_measurements_3, https://doi.org/10.1594/WDCC/HALO_measurements_4). This data set allows for analyses to gain insight into cloud properties and the atmospheric state in remote regions over the tropical and midlatitude Atlantic. In this paper, we describe the four campaigns, the data and the quality control applied to the data.

Characterization of Crop Canopies and Water Stress Related Phenomena using Microwave Remote Sensing Methods: A Review

2012 ◽  
Vol 11 (2) ◽  
pp. vzj2011.0138ra ◽  
Author(s):  
Harry Vereecken ◽  
Lutz Weihermüller ◽  
François Jonard ◽  
Carsten Montzka
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Microwave Remote Sensing ◽  
Remote Sensing Methods
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