scholarly journals Biases caused by the instrument bandwidth and beam width on simulated brightness temperature measurements from scanning microwave radiometers

2012 ◽  
Vol 5 (6) ◽  
pp. 8085-8130
Author(s):  
V. Meunier ◽  
U. Löhnert ◽  
P. Kollias ◽  
S. Crewell
Keyword(s):  
Water Vapor ◽  
Liquid Water ◽  
Beam Width ◽  
Liquid Water Path ◽  
Water Path ◽  
Antenna Beam ◽  
Atmospheric Propagation ◽  
W Band ◽  
The Impact ◽  
Receiver Bandwidth

Abstract. More so than the traditional fixed radiometers, the scanning radiometer requires a careful design to ensure high quality measurements. Here the impact of the radiometer characteristics (e.g. antenna beam width, receiver bandwidth) and atmospheric propagation (e.g. curvature of the earth and refractivity) on the scanning radiometer measurements are presented. A forward radiative transfer model that includes all these effects to represent the instrument measurements is used to estimate the biases as differences between the measurement with and without these characteristics for three commonly used frequency bands: K, V and W-band. The receiver channel bandwidth errors are not so important in K-band and W-band. Thus, the use of a wider bandwidth to improve detection at low signal-to-noise conditions is acceptable. The impact of the antenna beam width is higher than the receiver bandwidth, but, for V-band where they are of similar importance. Using simple regression algorithms, the effects of the bandwidth and beam width biases in liquid water path, integrated water vapor, and temperature are also examined. The largest errors in liquid water path and integrated water vapor are associated with the beam width errors.

scholarly journals Biases caused by the instrument bandwidth and beam width on simulated brightness temperature measurements from scanning microwave radiometers

2013 ◽  
Vol 6 (5) ◽  
pp. 1171-1187 ◽  
Author(s):  
V. Meunier ◽  
U. Löhnert ◽  
P. Kollias ◽  
S. Crewell
Keyword(s):  
Water Vapour ◽  
Liquid Water ◽  
Beam Width ◽  
Liquid Water Path ◽  
Water Path ◽  
Antenna Beam ◽  
W Band ◽  
Integrated Water Vapour ◽  
The Impact ◽  
Receiver Bandwidth

Abstract. More so than the traditional fixed radiometers, the scanning radiometer requires a careful design to ensure high quality measurements. Here the impact of the radiometer characteristics (e.g., antenna beam width and receiver bandwidth) and atmospheric propagation (e.g. curvature of the Earth and vertical gradient of refractive index) on scanning radiometer measurements are presented. A forward radiative transfer model that includes all these effects to represent the instrument measurements is used to estimate the biases. These biases are estimated using differences between the measurement with and without these characteristics for three commonly used frequency bands: K, V and W-band. The receiver channel bandwidth errors are less important in K-band and W-band. Thus, the use of a wider bandwidth to improve detection at low signal-to-noise conditions is acceptable at these frequencies. The biases caused by omitting the antenna beam width in measurement simulations are larger than those caused by omitting the receiver bandwidth, except for V-band where the bandwidth may be more important in the vicinity of absorption peaks. Using simple regression algorithms, the effects of the bandwidth and beam width biases in liquid water path, integrated water vapour, and temperature are also examined. The largest errors in liquid water path and integrated water vapour are associated with the beam width errors.

scholarly journals Integrated water vapor and liquid water path retrieval using a single-channel radiometer

2020 ◽  
Author(s):  
Anne-Claire Billault-Roux ◽  
Alexis Berne
Keyword(s):  
Water Vapor ◽  
Liquid Water ◽  
Single Channel ◽  
Geographical Information ◽  
Single Frequency ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
The Impact

Abstract. Microwave radiometers are widely used for the retrieval of Liquid Water Path (LWP) and Integrated Water Vapor (IWV) in the context of cloud and precipitation studies. This paper presents a new site-independent retrieval algorithm for LWP and IWV, relying on a single-frequency 89-GHz ground-based radiometer. A statistical approach is used, based on a neural network, which is trained and tested on a synthetic data set constructed from radiosonde profiles worldwide. In addition to 89-GHz brightness temperature, the input features include surface measurements of temperature, pressure and humidity, as well as geographical information and, when available, estimates of IWV and LWP from reanalysis data. An analysis of the algorithm is presented to assess its accuracy, the impact of the various input features, as well as its sensitivity to radiometer calibration and its stability across geographical locations. The new method is then implemented on real data that were collected during a field deployment in Switzerland and during the ICE-POP 2018 campaign in South Korea. The new algorithm is shown to be quite robust, especially in mid-latitude environments with a moderately moist climate, although its accuracy is inevitably lower than that obtained with state-of-the-art multi-channel radiometers.

scholarly journals Integrated water vapor and liquid water path retrieval using a single-channel radiometer

2021 ◽  
Vol 14 (4) ◽  
pp. 2749-2769
Author(s):  
Anne-Claire Billault-Roux ◽  
Alexis Berne
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Liquid Water ◽  
Geographical Information ◽  
Single Frequency ◽  
Training Dataset ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Water Path ◽  
The Impact

Abstract. Microwave radiometers are widely used for the retrieval of liquid water path (LWP) and integrated water vapor (IWV) in the context of cloud and precipitation studies. This paper presents a new site-independent retrieval algorithm for LWP and IWV, relying on a single-frequency 89 GHz ground-based radiometer. A statistical approach is used based on a neural network, which is trained and tested on a synthetic dataset constructed from radiosonde profiles worldwide. In addition to 89 GHz brightness temperature, the input features include surface measurements of temperature, pressure, and humidity, as well as geographical information and, when available, estimates of IWV and LWP from reanalysis data. An analysis of the algorithm is presented to assess its accuracy, the impact of the various input features, its sensitivity to radiometer calibration, and its stability across geographical locations. While 89 GHz brightness temperature is crucial to LWP retrieval, it only moderately contributes to IWV estimation, which is more constrained by the additional input features. The algorithm is shown to be quite robust, although its accuracy is inevitably lower than that obtained with state-of-the-art multi-channel radiometers, with a relative error of 18 % for LWP (in cloudy cases with LWP >30 g m−2) and 6.5 % for IWV. The highest accuracy is obtained in midlatitude environments with a moderately moist climate, which are more represented in the training dataset. The new method is then implemented and evaluated on real data that were collected during a field deployment in Switzerland and during the ICE-POP 2018 campaign in South Korea.

scholarly journals MBL drizzle properties and their impact on cloud property retrievals

2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.

Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Liquid Water ◽  
Weather Prediction ◽  
Wrf Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Ice Water Path ◽  
Ice Water ◽  
The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

scholarly journals The Impact of Low Clouds on Surface Shortwave Radiation in the ECMWF Model

2012 ◽  
Vol 140 (11) ◽  
pp. 3783-3794 ◽  
Author(s):  
Maike Ahlgrimm ◽  
Richard Forbes
Keyword(s):  
Great Plains ◽  
Liquid Water ◽  
Shortwave Radiation ◽  
Fair Weather ◽  
Liquid Water Path ◽  
Water Path ◽  
Surface Irradiance ◽  
Low Clouds ◽  
Low Cloud ◽  
The Impact

Abstract The long-term measurement records from the Atmospheric Radiation Measurement site on the Southern Great Plains show evidence of a bias in the ECMWF model’s surface irradiance. Based on previous studies, which have suggested that summertime shallow clouds may contribute to the bias, an evaluation of 146 days with observed nonprecipitating fair-weather cumulus clouds is performed. In-cloud liquid water path and effective radius are both overestimated in the model with liquid water path dominating to produce clouds that are too reflective. These are compensated by occasional cloud-free days in the model such that the fair-weather cumulus regime overall does not contribute significantly to the multiyear daytime mean surface irradiance bias of 23 W m−2. To further explore the origin of the bias, observed and modeled cloud fraction profiles over 6 years are classified and sorted based on the surface irradiance bias associated with each sample pair. Overcast low cloud conditions during the spring and fall seasons are identified as a major contributor. For samples with low cloud present in both observations and model, opposing surface irradiance biases are found for overcast and broken cloud cover conditions. A reduction of cloud liquid to a third for broken low clouds and an increase by a factor of 1.5 in overcast situations improves agreement with the observed liquid water path distribution. This approach of combining the model shortwave bias with a cloud classification helps to identify compensating errors in the model, providing guidance for a targeted improvement of cloud parameterizations.

scholarly journals Synergetic use of millimeter- and centimeter-wavelength radars for retrievals of cloud and rainfall parameters

2010 ◽  
Vol 10 (7) ◽  
pp. 3321-3331 ◽  
Author(s):  
S. Y. Matrosov
Keyword(s):  
Liquid Water ◽  
Rain Rate ◽  
Wet Season ◽  
Liquid Water Path ◽  
Vertical Column ◽  
Suggested Approach ◽  
Ka Band ◽  
Water Path ◽  
Climate Research ◽  
W Band

Abstract. A remote sensing approach for simultaneous retrievals of cloud and rainfall parameters in the vertical column above the US Department of Energy's (DOE) Climate Research Facility at the Tropical Western Pacific (TWP) Darwin site in Australia is described. This approach uses vertically pointing measurements from a DOE Ka-band radar and scanning measurements from a nearby C-band radar pointing toward the TWP Darwin site. Rainfall retrieval constraints are provided by data from a surface impact disdrometer. The approach is applicable to stratiform precipitating cloud systems when a separation between the liquid hydrometeor layer, which contains rainfall and liquid water clouds, and the ice hydrometeor layer is provided by the radar bright band. Absolute C-band reflectivities and Ka-band vertical reflectivity gradients in the liquid layer are used for retrievals of the mean layer rain rate and cloud liquid water path (CLWP). C-band radar reflectivities are also used to estimate ice water path (IWP) in regions above the melting layer. The retrieval uncertainties of CLWP and IWP for typical stratiform precipitation systems are about 500–800 g m−2 (for CLWP) and a factor of 2 (for IWP). The CLWP retrieval uncertainties increase with rain rate, so retrievals for higher rain rates may be impractical. The expected uncertainties of layer mean rain rate retrievals are around 20%, which, in part, is due to constraints available from the disdrometer data. The applicability of the suggested approach is illustrated for two characteristic events observed at the TWP Darwin site during the wet season of 2007. A future deployment of W-band radars at the DOE tropical Climate Research Facilities can improve CLWP estimation accuracies and provide retrievals for a wider range of stratiform precipitating cloud events.

scholarly journals Investigating the liquid water path over the tropical Atlantic with synergistic airborne measurements

2019 ◽  
Author(s):  
Marek Jacob ◽  
Felix Ament ◽  
Manuel Gutleben ◽  
Heike Konow ◽  
Mario Mech ◽  
...  
Keyword(s):  
Water Vapor ◽  
Liquid Water ◽  
Critical Role ◽  
Dry Season ◽  
Passive Microwave ◽  
Variable Component ◽  
Wet Season ◽  
Liquid Water Path ◽  
Water Path ◽  
Airborne Measurements

Abstract. Clouds are a strongly variable component of the climate system and several studies have identified especially marine low level clouds to play a critical role for the climate. Liquid water path (LWP) is an important quantity to characterize clouds. Passive microwave satellite sensors provide the most direct estimate on global scale, but suffer from high uncertainties due to large footprints and the superposition of cloud and precipitation signals. Here, we use high spatial resolution airborne microwave radiometer (MWR) measurements together with cloud radar and lidar observations to better understand LWP of warm clouds over the tropical North Atlantic. The nadir measurements were taken by the German High Altitude and Long range research aircraft (HALO) in December 2013 (dry season) and August 2016 (wet season) during two Next generation Advanced Remote sensing for VALidation campaigns (NARVAL). Microwave retrievals of integrated water vapor (IWV), LWP and rain water path (RWP) are developed using artificial neural network techniques and a unique database based on cloud-resolving model simulations with 1.25 km grid spacing. The IWV and LWP retrievals share the same eight MWR frequency channels as their sole input. The comparison of retrieved IWV with coincident dropsondes and water vapor lidar measurements shows root-mean-square deviations below 1.4 kg m−2 over the range from 20 to 60 kg m−2. This comparison raises the confidence in LWP retrievals which can only be assessed theoretically. The theoretical analysis shows the dependency of the uncertainty on LWP itself as the error is below 20 g m−2 for LWP below 100 g m−2 and below 20 % above. The identification of clear sky scenes by ancillary measurements, here backscatter lidar, is crucial for thin clouds (LWP < 12 g m−2) as the microwave retrieved LWP uncertainty is higher than 100 %. The RWP retrieval combines active and passive microwave observations and is able to detect drizzle and light precipitation. The analysis of both campaigns reveals that clouds were more frequent in the dry than in the wet season and their LWP and RWP were higher, but microwave scattering of ice was observed more frequently in the wet season (1.6 % vs. 0.5 % of the time). As to be expected, the observed IWV clearly shows that the wet season (mean IWV = 41 kg m−2) is more humid than the dry season (mean IWV = 28 kg m−2). The results reveal that the observed frequency distributions of IWV are strongly affected by the choice of the flight pattern. Therefore, the airborne observations need to be used carefully to mediate between long-term ground-based and spaceborne measurements to draw statistically sound conclusions.

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