Jacopo Grazioli

Multifrequency Radar Observations Collected in Southern France during HyMeX-SOP1

An ambitious radar deployment to collect high-quality observations of heavy precipitation systems developing over and in the vicinity of a coastal mountain chain is discussed.

Improved Estimation of the Specific Differential Phase Shift Using a Compilation of Kalman Filter Ensembles

A new algorithm for the accurate estimation of the specific differential phase shift on propagation (Kdp) from noisy total differential phase shift (Ψdp) measurements is presented for data acquired with a polarimetric weather radar. The new approach, which is based on the compilation of ensembles of Kalman filter estimates, does not rely on additional data like the reflectivity or the differential reflectivity in order to constrain the solution, and it is based on Ψdp only. The dependence of the solution on Ψdp only allows one to apply the algorithm in various environmental conditions without reducing its performance. Drawbacks that are usually inherent in algorithms of this kind (like the loss of the small-scale structure and the smoothing of high peak values) are partially overcome by a two-step algorithm design, which first determines an ensemble of possible solutions and then selects and averages the ensemble members such that the estimated Kdp profile has a better agreement with the truth. The algorithm is thoroughly evaluated and compared with a commonly used algorithm on stochastically simulated profiles of raindrop size distribution. It is found that the accuracy of the Kdp values estimated with the new algorithm significantly increases. The algorithm is also experimentally evaluated by applying it on X-band radar data that were acquired in northern Brazil during the CHUVA campaign and at a high alpine site in Switzerland during snowfall. Results show that the spatial fine structure and the high values of precipitation are better represented with the new method.

Deployment and Performance Analyses of High-Resolution Iowa XPOL Radar System during the NASA IFloodS Campaign

AbstractThis article presents the data collected and analyzed using the University of Iowa’s X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from...

Katabatic winds diminish precipitation contribution to the Antarctic ice mass balance

Significance Precipitation over Antarctica remains largely unknown, despite its crucial role in the surface mass balance of the Antarctic ice sheet. Using unprecedented observations covering an entire year, this work describes a previously unknown mechanism that leads to the sublimation of a large fraction of snowfall in the lower atmosphere, resulting from the interaction of precipitation and katabatic winds. Snowfall sublimation in the atmosphere, caused by katabatic winds, is in the order of 35% in the margins of East Antarctica. This process critically affects the interpretation of satellite-based remote sensing observations close to the ground and suggests that snowfall sublimation in a warming climate may counterbalance the expected increase of precipitation. Snowfall in Antarctica is a key term of the ice sheet mass budget that influences the sea level at global scale. Over the continental margins, persistent katabatic winds blow all year long and supply the lower troposphere with unsaturated air. We show that this dry air leads to significant low-level sublimation of snowfall. We found using unprecedented data collected over 1 year on the coast of Adélie Land and simulations from different atmospheric models that low-level sublimation accounts for a 17% reduction of total snowfall over the continent and up to 35% on the margins of East Antarctica, significantly affecting satellite-based estimations close to the ground. Our findings suggest that, as climate warming progresses, this process will be enhanced and will limit expected precipitation increases at the ground level.

Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data

The specific differential phase shift on propagation Kdp is widely employed in the study of precipitation, although little is known about the effective accuracy of its estimates. The aim of this letter is to analyze the quality of Kdp estimates, using realistic simulated fields of drop size distributions. Two classical and one recently proposed estimation algorithms are tested, which are chosen among the algorithms that use the measured and noisy total differential phase shift Ψdp as their main input. A data set of six simulated rain events, from which polarimetric radar variables can be derived, is employed in this letter. The mean normalized absolute error in the estimation of Kdp at the radar resolution volume scale ranges from 27% to 30% for all the algorithms proposed, and significant negative biases up to -50% emerge at the highest values of Kdp for the most biased algorithm. The new algorithm, which is based on Kalman filtering, is able to keep these localized bias values around -25% and outperforms the classical algorithms in terms of efficiency, correlation, and root-mean-square error.

Evaluation of the CloudSat surface snowfall product overAntarctica using ground-based precipitation radars

Before addressing the comments of the reviewer, it must be noted that during the revision process there was detected that a small part of erroneous MRR data at the PE station was included in the analysis. This erroneous data was recorded during the 2015-2016 austral winter season and was caused by interference from other instruments. It was removed from the sample lowering the period of concurrent data availability of the MRR and CloudSat from 928 to 851 days for the PE station (Fig. 2 in the main paper). This mainly affects Fig. 6 in the main paper where a clear lowering of both the MRR and CloudSat total precipitation amount is observed. However, as the total snowfall amount for both the MRR and CloudSat lowered with an equal amount, results and conclusions are not affected significantly.