The Role of Thermodynamic Phase Shifts in Cloud Optical Depth Variations With Temperature

2019 ◽  
Vol 46 (8) ◽  
pp. 4502-4511
Author(s):  
Ivy Tan ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho
2012 ◽  
Vol 12 (8) ◽  
pp. 21241-21266
Author(s):  
M. Antón ◽  
L. Alados-Arboledas ◽  
J. L. Guerrero-Rascado ◽  
M. J. Costa ◽  
J. C. Chiu ◽  
...  

Abstract. This paper evaluates the relationship between the cloud modification factor (CMF) in the ultraviolet erythemal range and the cloud optical depth (COD) retrieved from the Aerosol Robotic Network (AERONET) "cloud mode" algorithm under overcast cloudy conditions (confirmed with sky images) at Granada (Spain). Empirical CMF showed a clear exponential dependence on experimental COD values, decreasing approximately from 0.7 for COD = 10 to 0.25 for COD = 50. In addition, these COD measurements were used as input in the LibRadtran radiative transfer code allowing the simulation of CMF values for the selected overcast cases. The modeled CMF exhibited a dependence on COD similar to the empirical CMF, but modeled values present a strong underestimation with respect to the empirical factors (mean bias of 22%). To explain this high bias, an exhaustive comparison between modeled and experimental UV erythemal irradiance (UVER) data was performed. This exercise revealed that a significant part of the bias (~8%) may be related to code's overestimation of the experimental data for clear-sky conditions. The rest of the bias (~14%) may be attributed to the substantial underestimation of modeled UVER with respect to experimental UVER under overcast conditions, although the correlation between both dataset was high (R2 ~0.93). A sensitive test showed that the main responsible for that underestimation is the experimental AERONET COD used as input in the simulations, which has been retrieved from zenith radiances in the visible range. In this sense, effective COD in the erythemal interval were derived from an iteration procedure based on searching the best match between modeled and experimental UVER values for each selected overcast case. These effective COD values were smaller than AERONET COD data in about 80% of the overcast cases with a mean relative difference of 22%.


2010 ◽  
Vol 10 (6) ◽  
pp. 14557-14581
Author(s):  
J. C. Chiu ◽  
A. Marshak ◽  
Y. Knyazikhin ◽  
W. J. Wiscombe

Abstract. A previous paper discovered a surprising spectral-invariant relationship in shortwave spectrometer observations taken by the Atmospheric Radiation Measurement (ARM) program. Here, using radiative transfer simulations, we study the sensitivity of this relationship to the properties of aerosols and clouds, to the underlying surface type, and to the finite field-of-view (FOV) of the spectrometer. Overall, the relationship is mostly sensitive to cloud properties and has little sensitivity to the other factors. At visible wavelengths, the relationship primarily depends on cloud optical depth regardless of cloud thermodynamic phase and drop size. At water-absorbing wavelengths, the slope of the spectral-invariant relationship depends primarily on cloud optical depth; the intercept, by contrast, depends primarily on cloud absorption properties, suggesting a new retrieval method for cloud drop effective radius. These results suggest that the spectral-invariant relationship can be used to infer cloud properties even with insufficient or no knowledge about spectral surface albedo and aerosol properties.


2010 ◽  
Vol 10 (22) ◽  
pp. 11295-11303 ◽  
Author(s):  
J. C. Chiu ◽  
A. Marshak ◽  
Y. Knyazikhin ◽  
W. J. Wiscombe

Abstract. In a previous paper, we discovered a surprising spectrally-invariant relationship in shortwave spectrometer observations taken by the Atmospheric Radiation Measurement (ARM) program. The relationship suggests that the shortwave spectrum near cloud edges can be determined by a linear combination of zenith radiance spectra of the cloudy and clear regions. Here, using radiative transfer simulations, we study the sensitivity of this relationship to the properties of aerosols and clouds, to the underlying surface type, and to the finite field-of-view (FOV) of the spectrometer. Overall, the relationship is mostly sensitive to cloud properties and has little sensitivity to other factors. At visible wavelengths, the relationship primarily depends on cloud optical depth regardless of cloud phase function, thermodynamic phase and drop size. At water-absorbing wavelengths, the slope of the relationship depends primarily on cloud optical depth; the intercept, by contrast, depends primarily on cloud absorbing and scattering properties, suggesting a new retrieval method for cloud drop effective radius. These results suggest that the spectrally-invariant relationship can be used to infer cloud properties near cloud edges even with insufficient or no knowledge about spectral surface albedo and aerosol properties.


2018 ◽  
Vol 11 (10) ◽  
pp. 5837-5864 ◽  
Author(s):  
Hiren Jethva ◽  
Omar Torres ◽  
Changwoo Ahn

Abstract. Aerosol–cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of adequate knowledge of the complex microphysical and radiative processes of the aerosol–cloud system. Situations when light-absorbing aerosols such as carbonaceous particles and windblown dust overlay low-level cloud decks are commonly found in several regions of the world. Contrary to the known cooling effects of these aerosols in cloud-free scenario over darker surfaces, an overlapping situation of the absorbing aerosols over the cloud can lead to a significant level of atmospheric absorption exerting a positive radiative forcing (warming) at the top of the atmosphere. We contribute to this topic by introducing a new global product of above-cloud aerosol optical depth (ACAOD) of absorbing aerosols retrieved from the near-UV observations made by the Ozone Monitoring Instrument (OMI) onboard NASA's Aura platform. Physically based on an unambiguous “color ratio” effect in the near-UV caused by the aerosol absorption above the cloud, the OMACA (OMI above-cloud aerosols) algorithm simultaneously retrieves the optical depths of aerosols and clouds under a prescribed state of the atmosphere. The OMACA algorithm shares many similarities with the two-channel cloud-free OMAERUV algorithm, including the use of AIRS carbon monoxide for aerosol type identification, CALIOP-based aerosol layer height dataset, and an OMI-based surface albedo database. We present the algorithm architecture, inversion procedure, retrieval quality flags, initial validation results, and results from a 12-year long OMI record (2005–2016) including global climatology of the frequency of occurrence, ACAOD, and aerosol-corrected cloud optical depth. A comparative analysis of the OMACA-retrieved ACAOD, collocated with equivalent accurate measurements from the HSRL-2 lidar for the ORACLES Phase I operation (August–September 2016), revealed a good agreement (R = 0.77, RMSE = 0.10). The long-term OMACA record reveals several important regions of the world, where the carbonaceous aerosols from the seasonal biomass burning and mineral dust originated over the continents are found to overlie low-level cloud decks with moderate (0.3 < ACAOD < 0.5, away from the sources) to higher levels of ACAOD (> 0.8 in the proximity to the sources), including the southeastern Atlantic Ocean, southern Indian Ocean, Southeast Asia, the tropical Atlantic Ocean off the coast of western Africa, and northern Arabian sea. No significant long-term trend in the frequency of occurrence of aerosols above the clouds and ACAOD is noticed when OMI observations that are free from the “row anomaly” throughout the operation are considered. If not accounted for, the effects of aerosol absorption above the clouds introduce low bias in the retrieval of cloud optical depth with a profound impact on increasing ACAOD and cloud brightness. The OMACA aerosol product from OMI presented in this paper offers a crucial missing piece of information from the aerosol loading above cloud that will help us to quantify the radiative effects of clouds when overlaid with aerosols and their resultant impact on cloud properties and climate.


2021 ◽  
Author(s):  
Caterina Peris-Ferrús ◽  
José Luís Gómez-Amo ◽  
Francesco Scarlatti ◽  
Roberto Román ◽  
Claudia Emde ◽  
...  

2014 ◽  
Vol 14 (16) ◽  
pp. 8389-8401 ◽  
Author(s):  
J. C. Chiu ◽  
J. A. Holmes ◽  
R. J. Hogan ◽  
E. J. O'Connor

Abstract. We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40% and at least 10% higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.


2008 ◽  
Vol 6 (6) ◽  
pp. 454-457 ◽  
Author(s):  
陈勇航 陈勇航 ◽  
Yonghang Chen Yonghang Chen ◽  
白鸿涛 白鸿涛 ◽  
Hongtao Bai Hongtao Bai ◽  
黄建平 黄建平 ◽  
...  

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