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...
Abstract. Top-down and bottom-up aerosol–cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol–cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol–cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m−2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m−2 after accounting for cloud-top entrainment and up to 50 W m−2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m−2, even high (> 30 W m−2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).
<p><strong>Abstract.</strong> Top-down and bottom-up aerosol-cloud-radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol-cloud-radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top radiative flux (&#948;RF) by between 30&#8201;W&#8201;m<sup>&#8722;2</sup> and 40&#8201;W&#8201;m<sup>&#8722;2</sup>. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30&#8201;% of simulated CDNC. In cases with a well-mixed boundary layer, &#948;RF is less than 25&#8201;W&#8201;m<sup>&#8722;2</sup> after accounting for cloud-top entrainment, compared to less than 50&#8201;W&#8201;m<sup>&#8722;2</sup> when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and &#948;RF is as high as 88&#8201;W&#8201;m<sup>&#8722;2</sup>, even after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.</p>
The advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves for each pixel its temperature T and cloud drop effective radius re; calculates cloud-base temperature Tb based on the warmest cloudy pixels; calculates cloud-base height Hb and pressure Pb based on Tb and meteorological data; calculates cloud-base updraft Wb based on Hb; calculates cloud-base adiabatic cloud drop concentrations Nd,a based on the T–re relationship, Tb, and Pb; calculates cloud-base maximum vapor supersaturation S based on Nd,a and Wb; and defines Nd,a/1.3 as the cloud condensation nuclei (CCN) concentration NCCN at that S. The results are gridded 36 km × 36 km data points at nadir, which are sufficiently large to capture the properties of a field of convective clouds and also sufficiently small to capture aerosol and dynamic perturbations at this scale, such as urban and land-use features. The results of AMCC are instrumental in observing spatial covariability in clouds and CCN properties and for obtaining insights from such observations for natural and man-made causes. AMCC-generated maps are also useful for applications from numerical weather forecasting to climate models.
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