Deep convective cloud systems are central to the global water and energy cycle, and yet their representation in climate models remains challenging. This study explores the potential of machine learning to classify and characterize cloud structures inside cloud systems using radiometric measurements from the planned C²OMODO (Convective Core Observation through MicrOwave Derivative in the trOpics) mission. The relationships between cloud structure (anvil, stratiform, convective, and deep convective) and geophysical variables such as ice water path as well as integrated vertical ice momentum are investigated using a gradient boosting algorithm both for classification and regression purposes. The gradient boosting classification method achieves an overall accuracy (True Positive) above 70%. Retrievals of the geophysical variables yield R² ranging from 0.60 to 0.99. Furthermore, it is shown that applying a prior classification of the scenes improves the performances of the retrieval. This study highlights the potential of the forthcoming C²OMODO mission in advancing our understanding of convective systems and paves the way for in-depth studies on alternative or refined classification schemes and inputs, which could deliver even better results.

Convective systems are responsible for energy transfers between the lower and upper atmospheric layers and play a fundamental role in the water cycle, weather and climate evolution. With a tandem of high resolution and wide swath all-sky atmospheric sounders, the C2OMODO concept allows the estimation of vertical dynamics within deep convective systems.

Convective systems are responsible for energy transfers between the lower and upper atmospheric layers and play a fundamental role in the water cycle, weather and climate evolution. With a tandem of high resolution and wide swath all-sky atmospheric sounders, the C2OMODO concept allows the estimation of vertical dynamics within deep convective systems.

In the continuity of the existing SAPHIR microwave radiometer on-board Megha-Tropiques, in operation since 2011, a new generation atmospheric sounder is currently under study. SAPHIR-NG is designed to provide enhanced observations of clear sky water vapor and profiles of hydrometeors. The scientific objectives and requirements, as well as the instrumental implementation are described.

SAPHIR-NG is a new generation atmospheric sounder concept based on the existing SAPHIR instrument, onboard Megha-Tropiques, which has been operating since 2011. Its improvements with respect to SAPHIR are presented hereafter, both in terms of scientific objectives and instrumental architecture.

Infrared (IR) observations from the fleet of multiagencies meteorological geostationary satellites have a great potential to support scientific and operational investigations at a quasi-global scale. In particular, such a data record, defined as the GEOring data set, is well suited to document the tropical convective systems life cycles by applying cloud tracking algorithms. Yet, this GEOring data set is far from being homogeneous, preventing the realization of its potential. A number of sources of inhomogeneities are identified ranging from spatiotemporal resolutions to spectral characteristics of the IR channels and calibration methodologies. While previous efforts have attempted to correct such issues, the adjustment of the cold part of the IR spectrum remains unfit for cold cloud studies. Here, a processing method is introduced to minimize the inhomogeneities against a reference observational data set from the Scanner for Radiation Budget (ScaRaB) instrument onboard the Megha-Tropiques satellite. The method relies on the collocations between the geostationary observations and the reference. The techniques exhibit significant sensitivity to the selection of the relevant pairs of observations requiring a dedicated filtering of the data. A second effort is then proposed to account for the limb-darkening effect and a method is developed to correct the brightness temperature (BT) dependence on the geostationary viewing zenith angle (VZA). Overall, results show a residual after the processing of 0 K between any of the geostationary data and the ScaRaB reference. The final calibrated and limb-adjusted IR observations are then homogeneous for cold BT lower than 240 K with a standard deviation lower than 1.5 K throughout the GEOring.

The availability of rainfall-related measurements from space has greatly increased from the late 1980s with the Defense Meteorological Satellite Program and the launch of the Tropical Rainfall Measuring Mission in 1997 to the forthcoming Global Precipitation Measurement (GPM) program (GPM mission) whose core satellite is to be launched in 2014. The rainfall observing systems have become a constellation enhancing the frequency of measurements all over the globe. In this letter, the Megha-Tropiques TAPEER-BRAIN level-4 rainfall product is considered to explore what impacts the configuration of a microwave imager constellation has on accumulated rainfall and associated sampling error estimates at one-degree/one-day resolution in the tropics. One of the main findings of this letter is that sun-synchronous satellites providing observations separated of time intervals close to rainfall autocorrelation periods result only in small improvements of TAPEER-BRAIN quantitative precipitation estimations (i.e., rain and error estimations). By comparison, it is shown that the GPM constellation of satellites, particularly with satellites on low-inclination “equatorial” orbits, has a high contribution to the improvements of rain and error estimates. The methodology developed in this letter could be also useful to explore the sensitivity of rainfall estimates at finer space and timescales.

This paper focuses on the tracking of mesoscale convective systems (MCS) from geostationary satellite infrared data in the tropical regions. In the past, several automatic tracking algorithms have been elaborated to tackle this problem. However, these techniques suffer from limitations in describing convection at the “true” scale and in depicting coherent MCS life cycles (split and merge artifacts). To overcome these issues, a new algorithm called Tracking Of Organized Convection Algorithm through a 3-D segmentatioN has been developed and is presented in this paper. This method operates in a time sequence of infrared images to identify and track MCS and is based on an iterative process of 3-D segmentation of the volume of infrared images. The objective of the new tracking algorithm is to associate the convective core of an MCS to its anvil cloud in the spatiotemporal domain. The technique is applied on various case studies over West Africa, Bay of Bengal, and South America. The efficiency of the new algorithm is established from an analysis of the case studies and via a statistical analysis showing that the cold cloud shield defined by a 235-K threshold in the spatiotemporal domain is decomposed into realistic MCSs. In comparison with an overlap-based tracking algorithm, the analysis reveals that MCSs are detected earlier in life cycle and later in their dissipation stages. Moreover, MCSs identified are not anymore affected by split and merge events along their life cycles, allowing a better characterization of their morphological parameters along their life cycles.

The CERES Flight Model 5 was placed in orbit aboard the NPP spacecraft in October 2011 to replace the CERES FM-1 through -4 aboard the Terra and Aqua spacecraft which have provided Earth radiation budget measurement for eight to ten years. The SCAnner for RAdiation Budget (ScaRaB) 3 instrument aboard the Megha-Tropique spacecraft was put in orbit in September 2011. The CERES instruments can be rotated in azimuth so the CERES can observe the same scene in the same direction as ScaRaB, so that both instruments measure the same radiance for shortwave (reflected solar) radiance and for longwave (Earth-emitted) radiance. The data collected in this manner serves to validate all of these instruments. The geometry of the operation of CERES as constrained by the orbits is described. Special operations of CERES instruments were begun on 17 April 2012.