Satellite retrieval of convective cloud base temperature based on the NPP/VIIRS Imager

Zhu, Yannian; Yu, Xiangyao; Liu, Guihua; Dai, Jianlong; Xu, Xiaohong

doi:10.1002/2013gl058970

Cited by 33 publications

(33 citation statements)

References 9 publications

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“…We used the value of r e = 1.08 r v (31). The adiabatic water is obtained from the VIIRS-measured T b , which is simply the warmest cloudy pixel, based on a specially developed cloud mask (33). The LWC a is calculated based on an adiabatic parcel that rises from cloud base at T b and P b to the isotherm T, where multiple pairs of T and r ea are retrieved for different cloudy pixels of the same cloud cluster at different heights above cloud base.…”

Section: Methodsmentioning

confidence: 99%

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Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

Rosenfeld

Zheng

Hashimshoni

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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122

130

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Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (W b ). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and W b of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by W b and the satellite-retrieved cloud base drop concentrations (N db ), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25°restricts the satellite coverage to ∼25% of the world area in a single day. (1) states that the uncertainty in aerosol/cloud interactions dominates the uncertainty about the degree of influence that human activities have on climate. Because clouds form in ascending air currents, whereas cloud droplets nucleate on aerosols that serve as cloud condensation nuclei (CCN), we need accurate measurements of both updrafts and CCN supersaturation (S) spectra before we can disentangle aerosol effects on cloud radiative forcing (CRF) from dynamical effects. Need for Global Measurements of Cloud Base Updrafts and CCN(S)Tackling the global change problems as identified by the IPCC requires that these quantities be measured on a global scale. However, satellites have not been able to measure updraft speed of the air that forms the clouds or the concentrations of aerosols that are capable of forming cloud drops, which are ingested into the clouds as they grow. Lack of such fundamental quantities has greatly hindered our capability of disentangling the effects of meteorology and anthropogenic aerosol emissions on cloud properties (2). This situation is starting to change with our recently developed methodology to retrieve updrafts at cloud base (3, 4) using the Visible/Infrared Imager Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (NPP) satellite. This satellite is sun-synchronous, with an overpass time near 13:30 solar time.Missing such fundamental quantities as CCN(S) and cloud base updraft W b has been preventing us from disentangling the effects of aerosols from atmospheric dynamics (i.e., meteorology). Their absence also has limited our ability to validate the hypothesized impacts of added aerosols on a large range of phenomena, including (i) maintaining full cloud cover in marine stratocumulus, thus incurring a str...

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Section: Methodsmentioning

confidence: 99%

“…1 (33). H b and T b were calculated for conditions of convective clouds that developed from well-mixed boundary layer at the early afternoon satellite overpass time (33), before the peak of the convective rain and the resultant cooling and moistening of the boundary layer by evaporating precipitation.…”

Section: Methodsmentioning

confidence: 99%

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

Rosenfeld

Zheng

Hashimshoni

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

122

130

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“…d The determination of cloud-base temperature is based on the algorithm developed by Zhu et al (2014), who utilized the visible reflectance and a homogeneity parameter of 11.45-mm brightness temperature from the Suomi-NPP VIIRS imager to determine cloudbase temperature. Note that this method is not valid for all clouds but convective ones of certain size.…”

Section: Methodsmentioning

confidence: 99%

“…(ii) Cloud-base temperature T cb is retrieved using the method developed by Zhu et al (2014). The method is based on finding the warmest cloudy pixels from a running window of Suomi-NPP VIIRS.…”

Section: ) Satellite-based Datamentioning

confidence: 99%

Satellite Inference of Thermals and Cloud-Base Updraft Speeds Based on Retrieved Surface and Cloud-Base Temperatures

Zheng

2015

Journal of the Atmospheric Sciences

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Updraft speeds of thermals have always been difficult to measure, despite the significant role they play in transporting pollutants and in cloud formation and precipitation. In this study, updraft speeds in buoyancydriven planetary boundary layers (PBLs) measured by Doppler lidar are found to be correlated with properties of the PBL and surface over the Southern Great Plains (SGP) site operated by the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM). Based on the relationships found here, two approaches are proposed to estimate both maximum (W max ) and cloud-base (W cb ) updraft speeds using satellite data together with some ancillary meteorological data of PBL depth, wind speed at 10-m height, and air temperature at 2-m height. The required satellite input data are cloud-base and surface skin temperatures. PBL depth can be determined by using cloud-base temperature in combination with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data. Validation against lidar-measured updraft speeds demonstrated the feasibility of retrieving W max and W cb using high-resolution Suomi-National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi-NPP VIIRS) measurements over land for PBLs with thermally driven convective clouds during the satellite overpass time. The root-meansquare errors (RMSE) of W max and W cb are 0.32 and 0.42 m s 21 , respectively. This method does not work for a stable or a mechanically driven PBL.

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“…At present, direct satellite measurements of updraft speeds do not exist. An indirect inference of W b was developed recently (80,81) by retrieving the properties that propel air vertically, such as ground skin versus air temperature and cloud base height (82). Satellite retrieval of CCN(S) is made possible by combining the inferred W b with retrieved convective cloud base drop concentrations (83), for example, multispectral data as taken by the Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-orbiting Partnership polar orbiting satellite (84).…”

Section: Observations Of Aerosol−cloud Relationshipsmentioning

confidence: 99%

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

Seinfeld

Bretherton

Carslaw

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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611

474

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The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.climate | aerosol−cloud effects | general circulation models | radiative forcing | satellite observations Clouds play a key role in Earth's radiation budget, and aerosols serve as the seeds upon which cloud droplets form. Anthropogenic activity has led to an increase in aerosol particle concentrations globally and an increase in those particles that act as cloud condensation nuclei (CCN) and ice nucleating particles (INP). The effect of an increase in aerosols on cloud optical properties, and associated radiative forcing, is the most uncertain component of historical radiative forcing of Earth's climate caused by greenhouse gases (GHGs) and aerosols. The Intergovernmental Panel on Climate Change (IPCC) AR5 assessment of climate forcing factors (Fig. S1) ascribes "high" confidence to the estimate of direct aerosol radiative forcing (mean

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Satellite retrieval of convective cloud base temperature based on the NPP/VIIRS Imager

Cited by 33 publications

References 9 publications

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

Satellite Inference of Thermals and Cloud-Base Updraft Speeds Based on Retrieved Surface and Cloud-Base Temperatures

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

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