Jussi Leinonen

Radar Backscattering from Snowflakes: Comparison of Fractal, Aggregate, and Soft Spheroid Models

AbstractThe sensitivity of radar backscattering cross sections on different snowflake shapes is studied at C, Ku, Ka, and W bands. Snowflakes are simulated using two complex shape models, namely, fractal and aggregate, and a soft spheroid model. The models are tuned to emulate physical properties of real snowflakes, that is, the mass–size relation and aspect ratio. It is found that for particle sizes up to 5 mm and for frequencies from 5 to 35 GHz, there is a good agreement in the backscattering cross section for all models. For larger snowflakes at the Ka band, it is found that the spheroid model underestimates the backscattering cross sections by a factor of 10, and at W band by a factor of 50–100. Furthermore, there is a noticeable difference between spheroid and complex shape models in the linear depolarization ratios for all frequencies and particle sizes.

A Climatology of Disdrometer Measurements of Rainfall in Finland over Five Years with Implications for Global Radar Observations

AbstractTo improve the understanding of high-latitude rain microphysics and its implications for the remote sensing of rainfall by ground-based and spaceborne radars, raindrop size measurements have been analyzed that were collected over five years with a Joss–Waldvogel disdrometer located in Jarvenpaa, Finland. The analysis shows that the regional climate is characterized by light rain and small drop size with narrow size distributions and that the mutual relations of drop size distribution parameters differ from those reported at lower latitudes. Radar parameters computed from the distributions demonstrate that the high latitudes are a challenging target for weather radar observations, particularly those employing polarimetric and dual-frequency techniques. Nevertheless, the findings imply that polarimetric ground radars can produce reliable “ground truth” estimates for space observations and identify dual-frequency radars utilizing a W-band channel as promising tools for observing rainfall in the high-...

Mapping Radar Reflectivity Values of Snowfall Between Frequency Bands

Motivated by the use of a Ku/Ka-band radar in the Global Precipitation Measurement core satellite due to launch in 2013, we have studied the use of techniques to simulate radar observations of snowfall at these bands from data at C/W-bands by using scattering simulations to derive the approximate relationships of radar observables at the C/W-bands and those at Ku/Ka-bands. In this paper, we form the cross-band relationships by simulating radar reflectivity and attenuation in snowfall. The relations can be used to simulate observations at given bands from measurements at other bands. When measurements are available at multiple frequencies, the consistency of the model and the measurements can be used as a measure of the validity of the underlying assumptions of snowflake shape and constitution, which have been an important topic in recent snowfall remote sensing research. We also present mapping functions that can be used to perform cross-band analysis of snowfall observations and examine the use of these for practical cases of combined ground- and space-based (CloudSat) radar measurements as well as airborne radar data from the 2003 Wakasa Bay experiment.

Modeling Radar Attenuation by a Low Melting Layer With Optimized Model Parameters at C-Band

At northern latitudes, it is not uncommon for a melting layer of precipitation to touch or be close to the ground. For a low elevation angle, radio waves from a surveillance weather radar scan can travel a long distance through a melting layer. The resulting attenuation can be significant and must be taken into account when radar observations are interpreted. In this paper, we use a melting layer model to derive the relations between the specific attenuation caused by propagation through a melting layer and the reflectivity factor associated with this layer. The relations derived in this paper are based on modeled attenuation values for a variety of conditions and input parameters, i.e., rain rate, snow density, and rain drop size distribution parameters. The model parameters were constrained by vertically pointing Doppler C-band radar measurements of two events. The fitting procedure is presented for two different cases, of unrimed and rimed snow, and case-specific estimates of the expected attenuation of the horizontal scanning are suggested. Based on measurements of precipitation collected on December 10, 2011, by the University of Helsinki Kumpula radar, we also demonstrate that radar signal attenuation due to propagation through a low melting layer can be on the order of 7 dB or higher over a distance of 40 km.

Improved Retrieval of Cloud Liquid Water from CloudSat and MODIS

AbstractA revised version of the CloudSat–MODIS cloud liquid water retrieval algorithm is presented. The new algorithm, which combines measurements of radar reflectivity and cloud optical depth, addresses issues discovered in the current CloudSat–MODIS cloud water content (CWC) product. This current product is shown to be underconstrained by observations and to be too dependent on prior information incorporated into the Bayesian optimal-estimation algorithm. The most significant change made to the algorithm in this study was decreasing the number of independent variables to allow the observations to constrain the retrieved values better. The retrieval was also reformulated for improved compliance with the mathematical assumptions of the optimal-estimation algorithm. To validate the accuracy of the revised algorithm, the path-integrated attenuation (PIA) of the CloudSat radar signal was computed from the algorithm results. These modeled values were compared with independent measurements of the PIA that wer...