Effects of reflectivity gradients on rainfall estimates based on specific differential phase measurements

The rainfall estimates RDP based on the specific differential phase shift KDP are unaffected by errors in radar calibration and attenuation along the path. However, due to the signal fluctuations the estimates RDP can be very noisy at low and moderate rain rates. In order to improve the accuracy of the rainfall estimates KDP is to be estimated over a long path. In this way an error due to the reflectivity gradients, which could occur along a long path, can be introduced. In this paper we have analyzed two cases of reflectivity gradients along the path filled with rain; the first one, where the reflectivity varies linearly on dB scale that can be used to approximate regions with a steady increase or decrease of dBZ, and the other corresponding to sharp reflectivity gradient within the measurement cell, where an intense rainshaft is located adjacent in range to weak-echo regions. In both cases the error structure is discussed and the sensitivity of the normalized bias in KDP-based rainfall estimates is evaluated from a theoretical viewpoint and by simulation

Comparison of radar rainfall estimates and raingage measurements over the Central Apennines

Radar measurement of rainfall over mountainous regions is a difficult task due to the requirements of avoiding beam blockage as well as contamination by the melting layer. In this paper the raingage measurements and radar estimates of rainfall over two distinct locations in the central Apennines are compared to study the effect of beam blocking on radar measurements. A simple procedure is developed to estimate the percentage of beam blockage by the mountain ridges and, correspondingly, to correct the radar estimates of rainfall

Operational monitoring of rainfall over the Arno River basin using dual-polarized radar and rain gauges

Includes bibliographical references (page 1230).Reflectivity (ZH) and differential reflectivity (ZDR) measurements collected by Polar 55C over the Amo River basin in Italy are presented. The applicability of dual-polarization (ZDR)-based rainfall algorithms at C band in an operational setting is studied in conjunction with a network of rain gauges. Conventional pointwise comparison of radar and rain gauge estimates of rainfall, as well as statistical comparison of dual-polarization radar and rain gauge data via probability matching procedure, are presented. Error structure of reflectivity rainfall Z-R relation, as well as ZDR-based algorithms, is evaluated as a function of spatial and temporal averaging. Pointwise comparison, as well as statistical evaluation based on cumulative distribution function (CDF) matching, are used to show that in an operational environment with excessive ground-clutter contamination and attenuation problems the dual-polarization-based rainfall algorithm performs better than any arbitrary Z-R relation. In addition, it is shown that a dual-polarization (ZDR) algorithm obtained matching the CDFs performs better than the best possible Z-R relation

Attenuation compensation technique and rainfall rate estimation using C-band dual polarization radar

The effectiveness of an attenuation correction procedure on the error structure of a C-band radar rainfall estimation is studied theoretically and by computer simulation. The iterative procedure to correct the radar observables affected by attenuation is based on the best-fit relationships between the absolute and differential reflectivity and the specific absolute and differential attenuation. This paper evaluates this attenuation correction procedure by a computer simulation to value the rainfall rate estimation errors

A technique to obtain a multiparameter radar rainfall algorithm using the probability matching procedure

The natural cumulative distributions of rainfall observed by a network of rain gauges and a multiparameter radar are matched to derive multiparameter radar algorithms for rainfall estimation. Conventional usage of multiparameter radar measurements for rainfall estimation has been associated with tracking the variability of the raindrop size distribution. The use of multiparameter radar measurements in a statistical framework to estimate rainfall is presented in this paper. The techniques developed in this paper are applied to the radar and rain gauge measurement of rainfall observed in central Florida and central Italy. Conventional pointwise estimates of rainfall are also compared. The probability matching procedure, when applied to the radar and surface measurements, shows that multiparameter radar algorithms can match the probability distribution function better than the reflectivity-based algorithms, thereby indicating the potential of multiparameter radar measurements for statistical approach to rainfall estimation. It is also shown that the multiparameter radar algorithm derived matching the cumulative distribution function of rainfall provides more accurate estimates of rainfall on the ground in comparison to any conventional reflectivity-based algorithm

Comparison between multiparameter radar rainfall estimates and raingauge measurements during convective storms over Po valley

In this paper radar rainfall estimates obtained from C-band Doppler polarimetric weather radar GPM 500C are compared with rain gauge measurements collected by three rain gauge networks during a two months period from September 1 to October 30, 1996 when many convective thunderstorms developed over the Po valley area. In order to verify the capability and the accuracy of radar rainfall estimates two different techniques of comparison with the rain gauges have been analyzed: the first one is based on pointwise comparison of conventional and/or multiparameter radar estimates with the rain gauges measurements, the second utilizes the matching of the cumulative distribution function observed by the two sensors. The results are discussed considering two different areas, where the rain gauges are at a distance less than 40 km and at a distance ranging between 40 and 80 km, respectively

The Impact of Precipitation and Sublimation Processes on Snow Accumulation: Preliminary Results

The need for climate change prediction has focused attention on the Surface Mass Balance (SMB) of the Antarctic continent and on how it influences the sea level. The SMB of the Antarctic plateau is governed by the equilibrium between precipitation and ablation processes such as sublimation and wind-borne snow redistribution. At scales of hundreds of kilometres snowfall variability dominates the snow accumulation process (Dery and Yau, 2002); at smaller scales, postdepositional process such as wind-borne redistribution, surface sublimation and snowdrift sublimation becomes more important. In recent years the sublimation phenomenon has received much attention from the glacial-meteorological community, and some theoretical studies have tried to model it (Bintanja, 1998; Dery & Yau, 2001b; Frezzotti, 2004). There are two different types of sublimation: surface sublimation and blowing snow sublimation. Surface sublimation is mostly determined by the continual exchange of water between the air (in the vapour phase) and the snow pack (in the solid phase) due to solar irradiance. Blowing snow sublimation is possibly the more effective of the two sublimation processes. It occurs when snow particles at the surface are blown by winds exceeding a certain threshold value. Particles suspended in the sub saturated Atmospheric Boundary Layer (ABL) sublimate at a relatively fast rate, cooling air mass transported by the wind and increasing the local atmospheric moisture content. When the first few meters of the ABL are completely saturated, the process is dumped. It takes a long time to meet this condition because katabatic winds transport saturated air masses to the coast, thereby reactivating sublimation. The role of sublimation in snow accumulation and its high variability at local scales are not fully understood due to the few available measurements in Antarctica. Further study and field experiments are required

Ten years of isotopic composition of precipitation at Concordia Station, East Antarctica

Oxygen and Hydrogen isotopic composition (delta18O and deltaD) in ice cores has been widely used as a proxy for reconstructing past temperature variations. However, the atmospheric dynamics determining the precipitation isotopic composition on the Antarctic Plateau are yet to be fully understood, as well as the post-depositional processes modifying the pristine snow isotopic signal: both are fundamental for the interpretation of the isotopic records from deep Antarctic ice cores drilled in low accumulation areas in order to improve past temperature reconstructions. Since 2008, daily precipitation has been continuously collected by the winter-over personnel on raised surfaces (height: 1 m) placed in the clean area of Concordia Station on the East Antarctic plateau. Each sample has been analyzed for 18O, D and deuterium excess (d): this represents a unique record, still ongoing, for the isotopic composition of precipitation in inland Antarctica. In order to better comprehend the relationship between local temperature and the isotopic signal of precipitation, temperature data (T2m) from the Dome C Automatic Weather Station of the Programma Nazionale di Ricerche in Antartide (PNRA) were correlated with precipitation sample delta18O, deltaD and d from 2008 to 2017. A significant positive correlation between delta18O and deltaD of precipitation and T2m is observed when using both daily and monthly-averaged data. The measured precipitation isotopic data were also compared to the simulated delta18O, deltaD and d from the isotope-enabled atmospheric general circulation models ECHAM5-wiso and ECHAM6-wiso, with the latter showing significant improvement in simulating the isotopic data of precipitation

A Nine-year series of daily oxygen and hydrogen isotopic composition of precipitation at Concordia station, East Antarctica

The atmospheric processes determining the isotopic composition of precipitation on the Antarctic plateau are yet to be fully understood, as well as the post-depositional processes altering the snow pristine isotopic signal. Improving the comprehension of these physical mechanisms is of crucial importance for interpreting the isotopic records from ice cores drilled in the low accumulation area of Antarctica, e.g., the upcoming Beyond EPICA drilling at Little Dome C. Up to now, few records of the isotopic composition of precipitation in Antarctica are available, most of them limited in time or sampling frequency. Here we present a 9-year long δ18O and δD record (2008-2016) of precipitation at Concordia base, East Antarctica. The snow is collected daily on a raised platform (1 m), positioned in the clean area of the station; the precipitation collection is still being carried out each year by the winter over personnel. A significant positive correlation between isotopes in precipitation and 2-m air temperature is observed at both seasonal and interannual scale; the lowest temperature and isotopic values are usually recorded during winters characterized by a strongly positive Southern Annular Mode index. To improve the understanding of the mechanisms governing the isotopic composition of precipitation, we compare the isotopic data of Concordia samples with on-site observations, meteorological data from the Dome C AWS of the University of Wisconsin-Madison, as well as with high-resolution simulation results from the isotope-enabled atmospheric general circulation models ECHAM5-wiso and ECHAM6-wiso, nudged with the ERA-Interim and ERA5 reanalyses respectively

The influence of the synoptic regime on stable water isotopes in precipitation at Dome C, East Antarctica

Abstract. The correct derivation of paleotemperatures from ice cores requires exact knowledge of all processes involved before and after the deposition of snow and the subsequent formation of ice. At the Antarctic deep ice core drilling site Dome C, a unique data set of daily precipitation amount, type, and stable water isotope ratios is available that enables us to study in detail atmospheric processes that influence the stable water isotope ratio of precipitation. Meteorological data from both automatic weather station and a mesoscale atmospheric model were used to investigate how different atmospheric flow patterns determine the precipitation parameters. A classification of synoptic situations that cause precipitation at Dome C was established and, together with back-trajectory calculations, was utilized to estimate moisture source areas. With the resulting source area conditions (wind speed, sea surface temperature, and relative humidity) as input, the precipitation stable isotopic composition was modeled using the so-called Mixed Cloud Isotope Model (MCIM). The model generally underestimates the depletion of 18O in precipitation, which was not improved by using condensation temperature rather than inversion temperature. Contrary to the assumption widely used in ice core studies, a more northern moisture source does not necessarily mean stronger isotopic fractionation. This is due to the fact that snowfall events at Dome C are often associated with warm air advection due to amplification of planetary waves, which considerably increases the site temperature and thus reduces the temperature difference between source area and deposition site. In addition, no correlation was found between relative humidity at the moisture source and the deuterium excess in precipitation. The significant difference in the isotopic signal of hoarfrost and diamond dust was shown to disappear after removal of seasonality. This study confirms the results of an earlier study carried out at Dome Fuji with a shorter data set using the same methods