scholarly journals Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

2008 ◽  
Vol 47 (6) ◽  
pp. 1634-1650 ◽  
Author(s):  
Mircea Grecu ◽  
William S. Olson
Keyword(s):  
Field Experiment ◽  
Millimeter Wave ◽  
Synthetic Data ◽  
Optimal Estimation ◽  
Physical Models ◽  
Retrieval Algorithm ◽  
The Sea Of Japan ◽  
Cloud Radar ◽  
Cloud Resolving Model ◽  
Millimeter Wave Radiometer

Abstract An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

scholarly journals Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the lower stratosphere

2009 ◽  
Vol 9 (6) ◽  
pp. 23719-23753
Author(s):  
D. Wurl ◽  
R. G. Grainger ◽  
A. J. McDonald ◽  
T. Deshler
Keyword(s):  
Particle Size ◽  
Near Infrared ◽  
Lower Stratosphere ◽  
Synthetic Data ◽  
Optimal Estimation ◽  
Retrieval Algorithm ◽  
Extinction Data ◽  
Data Set ◽  
Microphysical Properties ◽  
Aerosol Properties

Abstract. A new retrieval algorithm is presented, which is based on the Optimal Estimation (OE) approach and aimed to improve current estimates of aerosol microphysical properties under non-volcanic conditions. The new OE algorithm retrieves log-normal particle size distribution parameters and associated uncertainties from multi-wavelength aerosol extinction data at visible to near infrared wavelengths. The algorithm was tested on synthetic data and then applied to SAGE (Stratospheric Aerosol and Gas Experiment) II data measured in 1999 in the lower stratosphere between 10 and 35 km. Model validation based on synthetic data shows that the new algorithm is able to retrieve the particle size of typical background aerosols accurately and that the retrieved uncertainties are a good estimate of the true errors. Aerosol properties retrieved from measured SAGE II extinction data (recorded in 1999) using the OE approach were compared to Principal Component Analysis (PCA) results retrieved from the same SAGE II data set. The OE surface area and volume densities are observed to be larger than the PCA values by 20–50% and 10–40% whereas the OE effective radii tend to be smaller by about 10–40%. An examination of the OE algorithm biases with in situ data indicates that the new OE estimates are likely to be more realistic than the PCA results. Based on the results of this study we suggest that the new OE retrieval algorithm provides improved estimates of aerosol properties in the lower stratosphere under low aerosol loading conditions.

scholarly journals Ozone profiles above Kiruna from two ground-based radiometers

2016 ◽  
Author(s):  
Niall J. Ryan ◽  
Kaley A. Walker ◽  
Uwe Raffalski ◽  
Rigel Kivi ◽  
Jochen Gross ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Ozone Concentration ◽  
Microwave Radiometer ◽  
Correlation Coefficients ◽  
Optimal Estimation ◽  
Concentration Profiles ◽  
Altitude Range ◽  
Ozone Profile ◽  
Millimeter Wave Radiometer ◽  
Winter Time

Abstract. This paper presents new atmospheric ozone concentration profiles retrieved from measurements made with two ground-based millimeter wave radiometers in Kiruna, Sweden. The instruments are the Kiruna Microwave Radiometer (KIMRA) and the Millimeter wave Radiometer 2 (MIRA 2). The ozone concentration profiles are retrieved using an optimal estimation inversion technique, and they cover an altitude range of ~ 16–56 km with an altitude resolution of, at best, 8 km. The KIMRA and MIRA 2 measurements are compared to each other, to measurements from balloon-borne ozonesonde measurements at Sodankylä, Finland, and to measurements made by the Microwave Limb Sounder (MLS) aboard the Aura satellite. KIMRA is low-biased with respect to the ozonesonde data due to a general low bias in the KIMRA profiles around 22 km altitude, and MIRA 2 shows a smaller magnitude low bias and a high correlation coefficient. Both radiometers are in general agreement with MLS data, showing high correlation coefficients. An oscillatory bias with a peak of ±1 ppmv is present in the KIMRA ozone profiles over an altitude range of ~ 20–35 km, and is believed to be due to standing wave features that are present in the spectra. A time series analysis of KIMRA ozone for winters 2008–2013 shows a local winter-time minimum in the ozone profile at approximately 35 km above Kiruna. The measurements are ongoing at Kiruna since 2002 and late 2012 for KIMRA and MIRA 2, respectively.

scholarly journals BOREAS – a new MAX-DOAS profile retrieval algorithm for aerosols and trace gases

2018 ◽  
Author(s):  
Tim Bösch ◽  
Vladimir Rozanov ◽  
Andreas Richter ◽  
Enno Peters ◽  
Alexei Rozanov ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Trace Gases ◽  
A Priori ◽  
Synthetic Data ◽  
Optimal Estimation ◽  
Iterative Solution ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Night Time

Abstract. We present a new MAX-DOAS profiling algorithm for aerosols and trace gases, BOREAS, which utilizes an iterative solution method including Tikhonov regularization and the optimal estimation technique. Performance tests are separated into two parts. First, we address the general sensitivity of the retrieval on the example of synthetic data calculated with the radiative transfer model SCIATRAN. In a second part of the study, we demonstrate BOREAS profiling accuracy by validating results with the help of ancillary measurements carried out during the CINDI-2 campaign in Cabauw, the Netherlands in 2016. The synthetic sensitivity tests indicate, that the regularization between measurement and a priori constraints is insufficient when knowledge of the true state of the atmosphere is poor. We demonstrate a priori pre-scaling and extensive regularization tests as a tool for the optimization of retrieved profiles. The comparison of retrieval results with in situ, ceilometer, NO2 LIDAR, sonde and long path DOAS measurements during the CINDI-2 campaign always shows high correlations with coefficients greater than 0.79. The largest differences can be found in the morning hours, when the planetary boundary layer is not yet fully developed and the concentration of trace gases and aerosol, as a result of a low night-time boundary layer having formed, is focused in a shallow, surface near layer.

Millimeter wave radiometer installation in Río Gallegos, southern Argentina

2011 ◽  
Author(s):  
P. F. Orte ◽  
J. Salvador ◽  
E. Wolfram ◽  
R. D'Elia ◽  
T. Nagahama ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Millimeter Wave Radiometer

scholarly journals A Robust Dual-Frequency Radar Profiling Algorithm

2011 ◽  
Vol 50 (7) ◽  
pp. 1543-1557 ◽  
Author(s):  
Mircea Grecu ◽  
Lin Tian ◽  
William S. Olson ◽  
Simone Tanelli
Keyword(s):  
Synthetic Data ◽  
Optimization Procedure ◽  
Correction Method ◽  
Single Frequency ◽  
Retrieval Algorithm ◽  
Dual Frequency ◽  
Ka Band ◽  
Radar Observations ◽  
Distribution Shape ◽  
Ku Band

AbstractIn this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar–radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dual-frequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth’s surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld–Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference technique–based path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

LIDAR and Millimeter-Wave Cloud RADAR (MWCR) techniques for joint observations of cirrus in Shouxian (32.56°N, 116.78°E), China

2016 ◽  
Vol 148 ◽  
pp. 64-73 ◽  
Author(s):  
Lingbing Bu ◽  
Honglin Pan ◽  
K. Raghavendra Kumar ◽  
Xingyou Huang ◽  
Haiyang Gao ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Cloud Radar

Validation of TROPOMI nadir ozone profile retrievals: Methodology and first results

2021 ◽  
Author(s):  
Arno Keppens ◽  
Jean-Christopher Lambert ◽  
Daan Hubert ◽  
Steven Compernolle ◽  
Tijl Verhoelst ◽  
...  
Keyword(s):  
Near Infrared ◽  
Stratospheric Ozone ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Data Retrieval ◽  
Atmospheric Composition ◽  
Retrieval Algorithm ◽  
Validation Data ◽  
Ozone Profile ◽  
Early Afternoon

<p>Part of the space segment of EU’s Copernicus Earth Observation programme, the Sentinel-5 Precursor (S5P) mission is dedicated to global and European atmospheric composition measurements of air quality, climate and the stratospheric ozone layer. On board of the S5P early afternoon polar satellite, the imaging spectrometer TROPOMI (TROPOspheric Monitoring Instrument) performs nadir measurements of the Earth radiance within the UV-visible and near-infrared spectral ranges, from which atmospheric ozone profile data are retrieved. Developed at the Royal Netherlands Meteorological Institute (KNMI) and based on the optimal estimation method, TROPOMI’s operational ozone profile retrieval algorithm has recently been upgraded. With respect to early retrieval attempts, accuracy is expected to have improved significantly, also thanks to recent updates of the TROPOMI Level-1b data product. This work reports on the initial validation of the improved TROPOMI height-resolved ozone data in the troposphere and stratosphere, as collected both from the operational S5P Mission Performance Centre/Validation Data Analysis Facility (MPC/VDAF) and from the S5PVT scientific project CHEOPS-5p. Based on the same validation best practices as developed for and applied to heritage sensors like GOME-2, OMI and IASI (Keppens et al., 2015, 2018), the validation methodology relies on the analysis of data retrieval diagnostics – like the averaging kernels’ information content – and on comparisons of TROPOMI data with reference ozone profile measurements. The latter are acquired by ozonesonde, stratospheric lidar, and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch and its contributing networks NDACC and SHADOZ. The dependence of TROPOMI’s ozone profile uncertainty on several influence quantities like cloud fraction and measurement parameters like sun and scan angles is examined and discussed. This work concludes with a set of quality indicators, enabling users to verify the fitness-for-purpose of the S5P data.</p>

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