Accurate Liquid Water Path Retrieval from Low-Cost Microwave Radiometers Using Additional Information from a Lidar Ceilometer and Operational Forecast Models

2007 ◽  
Vol 24 (9) ◽  
pp. 1562-1575 ◽  
Author(s):  
Nicolas Gaussiat ◽  
Robin J. Hogan ◽  
Anthony J. Illingworth

Abstract Water clouds have an important impact on the radiative balance of the earth. The use of ground-based dual-frequency microwave radiometers to derive both liquid water path (LWP) and water vapor path (WVP) is well established, but uncertainties over the dry, water vapor, and liquid water absorption coefficients and the radiometric calibration can lead to errors in the retrieved LWP. A method in which additional information from a lidar ceilometer is used to identify the presence of liquid water clouds and their altitude is described. When such clouds are absent, the radiometric calibrations of the two frequencies are optimally adjusted so that the retrieved LWP is forced to zero; when they are present the calibrations are interpolated from the nearest clear-sky periods before and after, and the temperature of the cloud is used to refine the liquid water absorption coefficient (with the temperature profile taken from a forecast model). This procedure is insensitive to the choice of absorption model, removes the troublesome negative values of LWP that can be retrieved, and provides more accurate values of low LWP in thin clouds. Analysis shows that LWP as low as 10 g m−2 can be reliably retrieved, 90% of the time the error being less than 50%, and for LWP greater than 20 g m−2 the error is less than 10%. An additional advantage is that the retrieval can tolerate uncertainties in the various absorption coefficients and is unaffected by slow drifts in brightness temperature errors of up to 5 K. Previous techniques have required that these temperatures be accurate to 0.5 K or better, which entails careful calibration and can be quite difficult to achieve.

2012 ◽  
Vol 5 (6) ◽  
pp. 8085-8130
Author(s):  
V. Meunier ◽  
U. Löhnert ◽  
P. Kollias ◽  
S. Crewell

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.


2019 ◽  
Author(s):  
Marek Jacob ◽  
Felix Ament ◽  
Manuel Gutleben ◽  
Heike Konow ◽  
Mario Mech ◽  
...  

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.


2019 ◽  
Vol 12 (6) ◽  
pp. 3237-3254 ◽  
Author(s):  
Marek Jacob ◽  
Felix Ament ◽  
Manuel Gutleben ◽  
Heike Konow ◽  
Mario Mech ◽  
...  

Abstract. Liquid water path (LWP) is an important quantity to characterize clouds. Passive microwave satellite sensors provide the most direct estimate on a 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 the 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 (NARVAL) campaigns. Microwave retrievals of integrated water vapor (IWV), LWP, and rainwater path (RWP) are developed using artificial neural network techniques. A retrieval database is created using unique cloud-resolving simulations with 1.25 km grid spacing. The IWV and LWP retrievals share the same eight MWR frequency channels in the range from 22 to 31 GHz and at 90 GHz as their sole input. The RWP retrieval combines active and passive microwave observations and is able to detect drizzle and light precipitation. 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 that the LWP error is constant with 20 g m−2 for LWP below 100 g m−2. While the absolute LWP error increases with increasing LWP, the relative one decreases from 20 % at 100 g m−2 to 10 % at 500 g m−2. 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 analysis of both campaigns reveals that clouds were more frequent (47 % vs. 30 % of the time) in the dry than in the wet season. Their average LWP (63 vs. 40 g m−2) and RWP (6.7 vs. 2.7 g m−2) were higher as well. Microwave scattering of ice, however, was observed less frequently in the dry season (0.5 % vs. 1.6 % of the time). We hypothesize that a higher degree of cloud organization on larger scales in the wet season reduces the overall cloud cover and observed LWP. As to be expected, the observed IWV clearly shows that the dry season is on average less humid than the wet season (28 vs. 41 kg m−2). The results reveal that the observed frequency distributions of IWV are substantially affected by the choice of the flight pattern. This should be kept in mind when using the airborne observations to carefully mediate between long-term ground-based and spaceborne measurements to draw statistically sound conclusions.


2018 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul R. Field ◽  
Gregory S. Elsaesser ◽  
Alejandro Bodas-Salcedo ◽  
Brian H. Kahn ◽  
...  

Abstract. Extratropical cyclones provide a unique set of challenges and opportunities in understanding variability in cloudiness over the extratropics (poleward of 30°). We can gain insight into the shortwave cloud feedback from examining cyclone variability. Here we contrast global climate models (GCMs) with horizontal resolutions from 7 km up to hundreds of kilometers with Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992–2015. We find that inter-cyclone variability in both observations and models is strongly driven by moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances liquid water path (LWP) within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. In the southern hemisphere (SH) oceans 28–42 % of the observed interannual variability in cyclone LWP may be explained by WCB moisture flux variability. This relationship is used to propose two cloud feedbacks acting within extratropical cyclones: a negative feedback driven by Clausius-Clapeyron increasing water vapor path (WVP), which enhances the amount of water vapor available to be fluxed into the cyclone; and a feedback moderated by changes in the life cycle and vorticity of cyclones under warming, which changes the rate at which existing moisture is imported into the cyclone. We show that changes in moisture flux drive can explain the observed trend in Southern Ocean cyclone LWP over the last two decades. Transient warming simulations show that the majority of the change in cyclone LWP can be explained by changes in WCB moisture flux, as opposed to changes in cloud phase. The variability within cyclone composites is examined to understand what cyclonic regimes the mixed phase cloud feedback is relevant to. At a fixed WCB moisture flux cyclone LWP increases with increasing SST in the half of the composite poleward of the low and decreases in the half equatorward of the low in both GCMs and observations. Cloud-top phase partitioning observed by the Atmospheric Infrared Sounder (AIRS) indicates that phase transitions may be driving increases in LWP in the poleward half of cyclones.


2020 ◽  
Vol 59 (7) ◽  
pp. 1153-1170
Author(s):  
Maria Toporov ◽  
Ulrich Löhnert

AbstractAtmospheric stability plays an essential role in the evolution of weather events. While the upper troposphere is sampled by satellite sensors, and in situ sensors measure the atmospheric state close to the surface, only sporadic information from radiosondes or aircraft observations is available in the planetary boundary layer. Ground-based remote sensing offers the possibility to continuously and automatically monitor the atmospheric state in the boundary layer. Microwave radiometers (MWR) provide temporally resolved temperature and humidity profiles in the boundary layer and accurate values of integrated water vapor and liquid water path, and the differential absorption lidar (DIAL) measures humidity profiles with high vertical and temporal resolution up to 3000-m height. Both instruments have the potential to complement satellite observations by additional information from the lowest atmospheric layers, particularly under cloudy conditions. This study presents a neural network retrieval for stability indices, integrated water vapor, and liquid water path from simulated satellite- and ground-based measurements based on the COSMO regional reanalysis (COSMO-REA2). Focusing on the temporal resolution, the satellite-based instruments considered in the study are the currently operational Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the future Infrared Sounder (IRS), both in geostationary orbit. Relative to the retrieval based on satellite observations, the additional ground-based MWR/DIAL measurements provide valuable improvements not only in the presence of clouds, which represent a limiting factor for infrared SEVIRI/IRS, but also under clear-sky conditions. The root-mean-square error for convective available potential energy, for instance, is reduced by 24% if IRS observations are complemented by ground-based MWR measurements.


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