Comments to manuscript amt-2017-153 The effect of cloud liquid water on tropospheric temperature retrievals from microwave measurements

2017 ◽  
Author(s):  
Anonymous
2017 ◽  
Author(s):  
Leonie Bernet ◽  
Francisco Navas-Guzmàn ◽  
Niklaus Kämpfer

Abstract. Microwave radiometry is a suitable technique to measure atmospheric temperature profiles with high temporal resolution during clear sky and cloudy conditions. In this study, we included cloud models in the inversion algorithm of the microwave radiometer TEMPERA (TEMPErature RAdiometer) to determine the effect of cloud liquid water on the temperature retrievals. The cloud models were built based on measurements of cloud base altitude and integrated liquid water (ILW), all performed at the aerological station (MeteoSwiss) in Payerne (Switzerland). Cloud base altitudes were detected using ceilometer measurements while the ILW was measured by a HATPRO (Humidity And Temperature PROfiler) radiometer. To assess the quality of the TEMPERA retrieval when clouds were considered, the resulting temperature profiles were compared to two years of radiosonde measurements. The TEMPERA instrument measures radiation at 12 channels in the frequency range from 51 to 57 GHz, corresponding to the left wing of the oxygen emission line complex. When the full spectral information with all the 12 frequency channels was used, we found a marked improvement in the temperature retrievals after including a cloud model. The chosen cloud model influenced the resulting temperature profile, especially for high clouds and clouds with a large amount of liquid water. Using all 12 channels however presented large deviations between different cases, suggesting that additional uncertainties exist in the lower, more transparent channels. Using less spectral information with the higher, more opaque channels only also improved the temperature profiles when clouds where included, but the influence of the chosen cloud model was less important. We conclude that tropospheric temperature profiles can be optimized by considering clouds in the microwave retrieval, and that the choice of the cloud model has a direct impact on the resulting temperature profile.


2017 ◽  
Vol 10 (11) ◽  
pp. 4421-4437 ◽  
Author(s):  
Leonie Bernet ◽  
Francisco Navas-Guzmán ◽  
Niklaus Kämpfer

Abstract. Microwave radiometry is a suitable technique to measure atmospheric temperature profiles with high temporal resolution during clear sky and cloudy conditions. In this study, we included cloud models in the inversion algorithm of the microwave radiometer TEMPERA (TEMPErature RAdiometer) to determine the effect of cloud liquid water on the temperature retrievals. The cloud models were built based on measurements of cloud base altitude and integrated liquid water (ILW), all performed at the aerological station (MeteoSwiss) in Payerne (Switzerland). Cloud base altitudes were detected using ceilometer measurements while the ILW was measured by a HATPRO (Humidity And Temperature PROfiler) radiometer. To assess the quality of the TEMPERA retrieval when clouds were considered, the resulting temperature profiles were compared to 2 years of radiosonde measurements. The TEMPERA instrument measures radiation at 12 channels in the frequency range from 51 to 57 GHz, corresponding to the left wing of the oxygen emission line complex. When the full spectral information with all the 12 frequency channels was used, we found a marked improvement in the temperature retrievals after including a cloud model. The chosen cloud model influenced the resulting temperature profile, especially for high clouds and clouds with a large amount of liquid water. Using all 12 channels, however, presented large deviations between different cases, suggesting that additional uncertainties exist in the lower, more transparent channels. Using less spectral information with the higher, more opaque channels only also improved the temperature profiles when clouds where included, but the influence of the chosen cloud model was less important. We conclude that tropospheric temperature profiles can be optimized by considering clouds in the microwave retrieval, and that the choice of the cloud model has a direct impact on the resulting temperature profile.


2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  

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.


2010 ◽  
Vol 10 (20) ◽  
pp. 9851-9861 ◽  
Author(s):  
X. Ma ◽  
K. von Salzen ◽  
J. Cole

Abstract. Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.


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