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Recent developments indicate that moisture in the lower free troposphere (LFT) strongly affects deep convection. Combining this evidence, we highlight a regime associated with the development of the strongest convection in which moistening of the LFT layer (roughly 1 -4 km) is hypothesized to play a controlling role. The following factors come into play: 1) evidence that deep convection typically includes substantial entrainment of LFT environmental air; 2) dynamic entrainment arguments based on the anelastic equation explain why this deep inflow should be common; 3) buoyancy estimates with incorporation of LFT air suggest a causal effect of LFT moistening; 4) the peak frequency of occurrence of convective precipitation is consistent with a balance between boundary layer and LFT moisture effects on buoyancy. Furthermore, a regime of infrequent high buoyancy and intense precipitation is associated with low subsaturation in the LFT layer. To distinguish from potential external forcing of convection without an active role for LFT moistening, the shorthand “turbocharging” is used for the causal influence of LFT moisture via effects on buoyancy. The high-buoyancy regime appears primarily in organized systems, suggesting a role for organization in protecting convective updrafts from dilution by dry air. Independent of specific hypotheses, the underlying empirical associations suggest the value of designing observing systems that yield simultaneous vertical profiles of moisture (and temperature) in and near convective systems. These—with coordinated information on precipitation/hydrometeors—would enable hypothesis testing for the relationship to the environment including better identification of the key tropospheric layer. It would provide constraints for improving representations of convective precipitation in weather forecast and climate models. We outline properties of a potential cubesat-sized satellite constellation that could yield such observations, leveraging polar

Accurate prediction and modeling of heavy precipitation events remains an issue due to gaps in our understanding of the physical processes underlying them. Such gaps arise from the limited number of good quality observations that constrain the thermodynamic parameters (e.g. temperature, moisture, etc.) within heavy precipitation, since the observations of some space-based sensors are degraded in the presence of thick clouds. The Global Navigation Satellite System (GNSS) Polarimetric Radio Occultation (PRO) technique was recently created to overcome some of these limitations, by providing vertical profiles of temperature, pressure, and water vapor, along with vertical information about hydrometeors (i.e. raindrops, snow, ice crystals, etc), simultaneously. It represents an enhancement of the standard radio occultation technique, that consists on tracking the signals emitted by GPS satellites from a low Earth orbit satellite occulting behind the Earth’s horizon. These signals cross lower and denser layers of the atmosphere as the occultation advances. The augmentation that the polarimetry provides consists on collecting these signals using two linearly and orthogonal polarized antennas (H and V), instead of the circularly polarized one used in the standard technique. Comparing the phase of the signals received at the two antenna ports, we can infer the presence of hydrometeors along the ray paths. Polarimetric Radio Occulation technique is being proved aboard the PAZ satellite, in an experiment led by the Institut de Ciències de l’Espai (ICE-CSIC,IEEC), in collaboration with NOAA, UCAR and NASA/Jet Propulsion Laboratory, operating since 2018. These profiles are obtained globally, through all kinds of clouds and over all kinds of surfaces. Such characteristics are rather unique in the current observing system. For this study, mesoscale convective systems (MCS) are particularly of interest. Given the characteristics of the observational technique and the targeted system

A better understanding of the thermodynamics of heavy precipitation events is necessary towards improving weather and climate models and quantifying the impact of climate variability on precipitation. However, there are limited observations available to assess the model structure within heavy precipitation conditions. Recently, it has also been shown that the Radio Occultations Through Heavy Precipitation (ROHP) GNSS polarimetric radio occultation (GNSS PRO) observations are highly sensitive to hydrometeors above the freezing layer, which expands the potential uses of the GNSS PRO dataset for weather-related science and applications. An exercise is presented to analyze the sensitivity of PRO observations for NWP modeling applications. The ROHP experiment now provides over four years of coincident thermodynamic and precipitation information with high vertical resolution within regions with thick clouds. Murphy et al. (2019) simulated GNSS airborne polarimetric RO (GNSS PRO) events along an atmospheric river. These were modeled by the community WRF mesoscale model using two different microphysical parameterization schemes. The GNSS PRO observables simulated with the two schemes differed significantly, more than the actual GNSS PRO precision. The new exercise presented here reproduces this methodology for spaceborne data, using different global and regional NWP models, and it analyzes the results and divergences with the help of actual GNSS PRO data acquired aboard the PAZ satellite. The objectives of the activity are: (1) To compare simulated GNSS PRO observables, generated with models from different centers and different microphysics schemes, against actual PAZ GNSS PRO observables. Can the models reproduce the main features of the actual data? (2) To assess whether different models/schemes result in different GNSS PRO observables, and whether these differences are larger than the measurement uncertainty. This effort provides insight on future methods to assimilate t

Polarimetric radio occultation (PRO) provides refractivity and phase difference between horizontal and vertical components of the radio occultation signals. This polarimetric phase difference occurs when the occultation ray paths cross an anisotropic medium like a layer of ice particles or non-spherical precipitating droplets. PRO from the PAZ satellite have been proven to capture these effects. PAZ GPS observations are used to correlate the phase difference with the precipitating water path and ice water path. The result presented is a data derived Look-Up Table (LUT) that is compared to the predicted LUT. The empirical LUT is used to infer a non-linear logistic map function that relates the phase difference to the ice/precipitating water path as a function of refractivity. We explored profiles that do not follow the logistic function to understand what physical processes could cause such anomalies. A cluster analysis based on the polarimetric phase difference and refractivity profiles is used to relate different type of profiles to occurrence of precipitation. The analysis presented correlates the different vertical cloud structures associated with different types of precipitation. These vertical structures of radio occultation refractivity profiles inform on the combination of temperature and water vapor at different altitudes inside the clouds, including thick convective clouds. Altitude changes in the polarimetric phase difference within these PRO profiles informs on the levels at which the thermodynamic conditions lead to precipitation or ice.

Convective transition statistics serve as diagnostics for the parameterization of convection in climate and weather forecast models by characterizing the dependence of convection on the humidity-temperature environment. The observed strong pickup of precipitation as a function of layer-averaged water vapor and temperature is captured in models with varying accuracy. For independent observational verification, a low-Earth orbiting satellite constellation of Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) measurements would be spaced such that adjacent RO would capture different profiles within and immediately adjacent to convection. Here, the number of profile observations needed to distinguish between convective transition relations by different tropospheric temperature ranges is determined, over different tropical oceanic basins. To obtain these, orbit simulations were performed by flying different satellite constellations over global precipitation from the Global Precipitation Measurement (GPM) mission, varying the numbers of satellites, orbit altitude, and inclination. A 45-degree orbit inclination was found to be a good tradeoff between maximizing the number of observations collected per day, and the desired 50¿150-km spacing between individual RO ray paths. Assuming a set of reasonable assumptions for net data yield, three tropospheric temperatures can be distinguished by 1 K with a six-month on-orbit duration from a constellation of at least three satellites.