Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data

Abstract

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.

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part I: Maritime Conditions

“…This updrafts-z b relationship has been applied universally regardless of the underlying surface type: land or ocean (e.g., Rosenfeld et al 2016Rosenfeld et al , 2019Yue et al 2019). Experimental data show that the relationship of cloudbase updrafts versus z b is ;20% steeper over land than that over the ocean, but the scatter of the samples, in particular over land, is too large for such a difference to achieve statistical significance (Zheng and Rosenfeld 2015).…”

Examining Conditions Supporting the Development of Anomalous Charge Structures in Supercell Thunderstorms in the Southeastern United States

“…Surface‐based instruments such as ceilometers, sun photometers, and Light Detection and Ranging (LiDAR) may provide aerosol optical depth data from which more specific aerosol concentrations could be derived in limited‐area studies. Techniques utilizing satellite data to estimate CCN in convection may be more widely useful as well (e.g., Rosenfeld et al., 2014; Yue et al., 2019). Storm penetrating aircraft and similar efforts exist among the few avenues by which necessary direct measurements of CCN, LWC, and water vapor in convection may be acquired in the future.…”

Effect of dust on rainfall over the Red Sea coast based on WRF-Chem model simulations

“…CCN number concentrations were retrieved from VI-IRS data following the Automated Mapping of Convective Clouds (AMCC) algorithm (Yue et al, 2019) to validate our model results. The algorithm extends the novel idea proposed by Rosenfeld et al (2016) to simultaneously retrieve the CCN concentrations and the cloud base updraft speeds using visible and infrared satellite data.…”

“…The number of activated CCN in a convective cloud base can be calculated as a function of cloud drop effective radius (varies with altitude as in an adiabatic cloud), which can be retrieved from a satellite imager with high-resolution wave bands such as the VIIRS (Visible Infrared Imaging Radiometer Suite) on board the Suomi NPP (National Polar-Orbiting Satellite) (Freud et al, 2011;Rosenfeld et al, 2016Rosenfeld et al, , 2014. Similarly, the cloud base updraft speeds can be estimated as a linear function of cloud-base height (Zheng and Rosenfeld, 2015;Rosenfeld et al, 2016;Yue et al, 2019).…”