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.

scholarly journals Marine boundary layer drizzle properties and their impact on cloud property retrieval

2015 ◽  
Vol 8 (9) ◽  
pp. 3555-3562 ◽  
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Marine Boundary Layer ◽  
Microwave Radiometer ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Cloud Base ◽  
Liquid 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 retrieval in Dong et al. (2014a) from ground-based measurements at the ARM Azores facility 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 4.73 (1.25) g m−2, 61.5 (36.4) μm, and 0.38 (0.79) cm−3. The seasonal mean LWPd values are less than 3 % of the LWP values retrieved by the microwave radiometer (MWR). The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.75 and 2.35 %, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle below the cloud base on cloud property retrieval is insignificant for a solar-transmission-based method, but significant for any retrievals using radar reflectivity.

scholarly journals Cloud droplet size and liquid water path retrievals from zenith radiance measurements: examples from the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

2012 ◽  
Vol 12 (8) ◽  
pp. 19163-19208 ◽  
Author(s):  
J. C. Chiu ◽  
A. Marshak ◽  
C.-H. Huang ◽  
T. Várnai ◽  
R. J. Hogan ◽  
...  
Keyword(s):  
Droplet Size ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Atmospheric Radiation ◽  
Liquid Water Path ◽  
Relative Deviation ◽  
Retrieval Method ◽  
Water Path ◽  
Atmospheric Radiation Measurement

Abstract. The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a non-water-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g m−2 and horizontal resolution of 201 m, the retrieval method underestimates the mean effective radius by 0.8 μm, with a root-mean-squared error of 1.7 μm and a relative deviation of 13%. For actual observations with a liquid water path less than 450 g m−2 at the ARM Oklahoma site during 2007–2008, our 1.5 min-averaged retrievals are generally larger by around 1 μm than those from combined ground-based cloud radar and microwave radiometer at a 5 min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 μm and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 μm. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Exploring satellite-derived relationships between cloud droplet number concentration and liquid water path using a large-domain large-eddy simulation

2021 ◽  
Author(s):  
Sudhakar Dipu ◽  
Matthias Schwarz ◽  
Annica Ekman ◽  
Edward Gryspeerdt ◽  
Tom Goren ◽  
...  
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Liquid Water Path ◽  
Large Domain ◽  
Water Path ◽  
Large Eddy ◽  
Cloud Droplet Number Concentration ◽  
Les Model ◽  
The Relationship

<div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>Important aspects of the adjustments to aerosol-cloud interactions can be examined using the relationship between cloud droplet number concentration (Nd) and liquid water path (LWP). Specifically, this relation can constrain the role of aerosols in leading to thicker or thinner clouds in response to adjustment mechanisms. This study investigates the satellite retrieved relationship between Nd and LWP for a selected case of mid-latitude continental clouds using high-resolution Large-eddy simulations (LES) over a large domain in weather prediction mode. Since the satellite retrieval uses adiabatic assumption to derive the Nd (NAd), we have also considered NAd from the LES model for comparison. The NAd-LWP relationship in the satellite and the LES model show similar, generally positive, but non-monotonic relations. This case over continent thus behaves differently compared to previously-published analysis of oceanic clouds, and the analysis illustrates a regime dependency (marine and continental) in the NAd-LWP relation in the satellite retrievals. The study further explores the impact of the satellite retrieval assumptions on the Nd-LWP relationship. When considering the relationship of the actually simulated cloud-top Nd, rather than NAd, with LWP, the result shows a much more nonlinear relationship. The difference is much less pronounced, however, for shallow stratiform than for convective clouds. Comparing local vs large-scale statistics from satellite data shows that continental clouds exhibit only a weak nonlinear Nd-LWP relationship. Hence a regime based Nd-LWP analysis is even more relevant when it comes to continental clouds.</p> </div> </div> </div>

Impact of Holuhraun volcano aerosol on clouds in cloud-system resolving simulations

2021 ◽  
Author(s):  
Mahnoosh Haghighatnasab ◽  
Johannes Quass
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Volcanic Eruptions ◽  
Cloud Fraction ◽  
Number Concentration ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Droplet Number Concentration ◽  
Cloud Liquid Water Path ◽  
Cloud Response

<p>Since increased anthropogenic aerosol result in an enhancement in cloud droplet number concentration, cloud and precipitation process are modified. It is unclear how exactly cloud liquid water path (LWP) and cloud fraction respond to aerosol perturbations. A large volcanic eruption may help to better understand and quantify the cloud response to external perturbations, with a focus on the short-term cloud adjustments . Volcloud is one of the research projects in the Vollmpact collaborative German research unit which aims to the improve understanding of how the climate system responds to volcanic eruptions. This includes skills in satellite remote sensing of atmospheric composition, stratospheric aerosol parameters and clouds as well as in modelling of aerosol microphysical and cloud processes, and in climate modelling. The goal of VolCloud is to understand and quantify the response of clouds to volcanic eruptions and to thereby advance the fundamental understanding of the cloud response to external forcing, particularly aerosol-cloud interactions. In this study we used ICON-NWP atmospheric model at a cloud-system-resolving resolution of 2.5 km horizontally, to simulate the region around the Holuhraun volcano for the duration of one week (1 – 7 September 2014). The pair of simulations, with and without the volcanic aerosol emissions allowed us to assess the simulated effective radiative forcing and its mechanisms as well as its impact on adjustments of cloud liquid water path and cloud fraction to the perturbations of cloud droplet number concentration. In this case studies liquid water path positively correlates with enhanced cloud droplet concentration.</p>

scholarly journals The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

2013 ◽  
Vol 13 (19) ◽  
pp. 9997-10003 ◽  
Author(s):  
D. Painemal ◽  
P. Minnis ◽  
S. Sun-Mack
Keyword(s):  
Liquid Water ◽  
Vertical Structure ◽  
Cloud Fraction ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Warm Cloud ◽  
Southeast Pacific ◽  
The Impact

Abstract. The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8–re2.1 differences are positive (<1 μm) for homogeneous scenes (Hσ < 0.2) and LWP > 45 gm−2, and negative (up to −4 μm) for larger Hσ. While re3.8–re2.1 differences in homogeneous scenes are qualitatively consistent with in situ microphysical observations over the region of study, negative differences – particularly evinced in mean regional maps – are more likely to reflect the dominant bias associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

scholarly journals Cloud droplet size and liquid water path retrievals from zenith radiance measurements: examples from the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

2012 ◽  
Vol 12 (21) ◽  
pp. 10313-10329 ◽  
Author(s):  
J. C. Chiu ◽  
A. Marshak ◽  
C.-H. Huang ◽  
T. Várnai ◽  
R. J. Hogan ◽  
...  
Keyword(s):  
Droplet Size ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Atmospheric Radiation ◽  
Liquid Water Path ◽  
Relative Deviation ◽  
Retrieval Method ◽  
Water Path ◽  
Atmospheric Radiation Measurement

Abstract. The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a liquid-water-absorbing wavelength (i.e., 1640 nm) with a non-water-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g m−2 and horizontal resolution of 201 m, the retrieval method underestimates the mean effective radius by 0.8 μm, with a root-mean-squared error of 1.7 μm and a relative deviation of 13%. For actual observations with a liquid water path less than 450 g m−2 at the ARM Oklahoma site during 2007–2008, our 1.5-min-averaged retrievals are generally larger by around 1 μm than those from combined ground-based cloud radar and microwave radiometer at a 5-min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 μm and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 μm. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

scholarly journals The impact of horizontal heterogeneities, cloud fraction, and cloud dynamics on warm cloud effective radii and liquid water path from CERES-like Aqua MODIS retrievals

2013 ◽  
Vol 13 (5) ◽  
pp. 12725-12742 ◽  
Author(s):  
D. Painemal ◽  
P. Minnis ◽  
S. Sun-Mack
Keyword(s):  
Liquid Water ◽  
Vertical Structure ◽  
Cloud Fraction ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Warm Cloud ◽  
Cloud Dynamics ◽  
Southeast Pacific ◽  
The Impact

Abstract. The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES Edition 4 algorithms are averaged at the CERES footprint resolution (~ 20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8 – re2.1 differences are positive (< 1 μm) for homogeneous scenes (Hσ < 0.2) and LWP > 50 g m−2, and negative (up to −4 μm) for larger Hσ. Thus, re3.8 – re2.1 differences are more likely to reflect biases associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

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.

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