Weather

Using measurements of cloud ice to evaluate frozen particle scattering models


By: Karina McCusker

How will we measure cloud ice, and why do we have to?

Ice particles in clouds have advanced geometries, making them extra obscure than droplets. In consequence, ice clouds are a supply of uncertainty in climate and local weather simulations. To enhance this, high-quality world observations are required. Microwave distant sensing devices, corresponding to radars and radiometers, enable observations of cloud over giant areas on a steady foundation. This knowledge is beneficial for bettering microphysical schemes and evaluating numerical climate prediction and local weather fashions.

Measurements of atmospheric cloud ice might also be assimilated into forecasts. For a few years a significant limitation to forecasts was that solely clear-sky radiances have been assimilated into numerical climate prediction fashions, and cloudy cells have been discarded. This implies quite a lot of helpful info was misplaced, thus lately a whole lot of focus was put into enabling all-sky assimilation of satellite tv for pc radiances. On the ECMWF, all-sky assimilation of microwave knowledge has been proven to have the most important relative influence on the standard of the 24-hour operational climate forecasts of all observations. Presently microwave knowledge is assimilated utilizing a mix of clear-sky and all-sky strategies, however by October an solely all-sky assimilation framework will likely be used for microwave observations.

To deal with the above factors it’s needed to grasp the connection between the scale and form of an ice particle and its microwave scattering properties. To acquire info on particle properties, corresponding to dimension, form, and mass, direct measurements are additionally required. Thus, a novel dataset has been obtained as a part of the PICASSO marketing campaign, involving co-located in-situ plane observations with distant sensing measurements from ground-based radar. Distinctive monitoring was used to make sure the identical cloud was sampled by the plane devices and the radars. Knowledge from synchronized 3, 35, and 94 GHz radars was collected, permitting research of how scattering by snowflakes modifications with wavelength. Additional particulars will be discovered on this blog post. Right here we use the plane probes and multi-frequency radar info from the PICASSO dataset to start to guage completely different ice particle form fashions.

What are the advantages of utilizing a number of radar frequencies?

Ice particles in clouds have a variety of sizes, from frozen cloud droplets of about 10 μm to giant aggregates of crystals that may attain 4-5 cm. At 3 GHz (i.e. 10 cm wavelength), the particle dimension is at all times lower than the wavelength. This implies the particles scatter within the Rayleigh regime. If we have been to contemplate the case of homogeneous spheres within the Rayleigh regime, the quantity of scattering would improve because the sixth energy of particle dimension (D6). This is a little more delicate for ice, the place typically scattering is proportional to mass2. Both means, bigger particles are inclined to scatter rather more than smaller particles. For larger frequencies corresponding to 94 GHz (shorter wavelengths), small particles scatter within the Rayleigh regime, however bigger particles (that are comparable in dimension to the wavelength) will scatter within the Mie regime. Which means that by utilizing a mix of measurements at two completely different frequencies (i.e. the dual-frequency ratio; DFR), we will get a greater indication of the scale of the particles, consequently bettering estimations of ice water content material (IWC). Triple-frequency measurements have proven potential for offering info on particle form/construction and density (e.g Kneifel et al. (2011; 2015)), together with potential to establish areas of aggregation, melting, and riming (Dias Neto et al., 2019). Stein et al. (2015) used triple-frequency observations to guage particle fashions, and we will carry out comparable experiments utilizing the PICASSO dataset.

Why do we have to consider particle fashions?

RTTOV-SCATT is a quick multiple-scattering radiative switch mannequin designed to assimilate all-sky MW radiances in numerical climate prediction (Bauer et al., 2006; Saunders et al., 2020; Geer et al., 2021). Assimilation of observations requires correct hydrometeor scattering fashions, and optimisation of particle illustration is important with a view to lengthen all-sky capabilities to incorporate larger frequencies and observations from new sensors, e.g. the Ice Cloud Imager. The default in model 13 of RTTOV-SCATT is to make use of a variety of life like, non-spherical particles to symbolize frozen hydrometeors (i.e. snow, graupel, and cloud ice). These are obtained from the ARTS scattering database (Eriksson et al., 2018), as outlined in desk 1 of Geer et al. (2021). Right here we study 4 particle mixtures from the ARTS scattering database – plates, columns, block columns, and ICON snow.

Examples of experiments carried out
Outcomes of the simulated IWC and radar reflectivity (Z) are proven in Fig. 1 for one of many plane runs on thirteenth February 2018. The in-situ measured particle-size distributions (PSDs) have been used to carry out the simulations. The crimson strains present the measurements obtained from the Nevzorov probe and the CAMRa 3 GHz radar, respectively. We discover that not one of the 4 particle mixtures concurrently present match to IWC and Z. Nonetheless, the block combination tends to overestimate measurements of each portions, and the column combination underestimates measurements.

Determine 1: – (a) Simulated and measured IWC. The IWC measured utilizing the Nevzorov probe is proven in crimson, with the IWC simulated utilizing the in-situ measured PSDs and the 4 particle mixtures proven by the opposite colors, as outlined within the determine legend. (b) Identical as panel (a) however for the three GHz radar reflectivity.

We additionally appeared on the dual-frequency ratio, and located that columns predict a bigger worth of DFR(3,35) than the opposite mixtures (Fig. 2a), whereas ICON snow predicts a decrease worth of DFR(35,94) than the opposite shapes (Fig. 2b). Fig. 2c exhibits the DFRs calculated for all of the runs throughout this case examine, plotted in triple-frequency house with DFR(35,94) on the x-axis and DFR(3,35) on the y-axis. The dots are the values simulated utilizing the in-situ measured PSDs, and the strains are simulated utilizing exponential PSDs. The massive variation of the dots from the strains exhibits that even when the chosen form mannequin is life like, commonly-used parameterisations of the PSD (corresponding to assumptions of exponential and gamma distributions) should still introduce a big error to the calculations.

We’re presently within the technique of evaluating the DFR simulations to measurements with a view to consider the particle fashions and decide whether or not any of them are life like. This work will likely be helpful to information microphysical schemes and assumptions which might be utilized in climate and local weather fashions, and in knowledge assimilation.

Determine 2:  (a) Simulated DFR calculated at 3 and 35 GHz for one of many plane runs. (b) Identical as panel (a) however for 35 and 94 GHz. (c) The 2 DFRs calculated for all of the runs throughout this case examine, plotted in triple-frequency house with DFR(35,94) on the x-axis and DFR(3,35) on the y-axis. The dots are the values simulated utilizing the in-situ measured PSDs, and the strains present the outcomes calculated utilizing exponential PSDs.

References:
Kneifel, S., M. S. Kulie, and R. Bennartz, 2011: A triple‐frequency method to retrieve microphysical snowfall parameters, J. Geophys. Res., 116, D11203, https://doi.org/10.1029/2010JD015430.

Kneifel, S., A. von Lerber, J. Tiira, D. Moisseev, P. Kollias, and J. Leinonen, 2015: Noticed relations between snowfall microphysics and triple-frequency radar measurements. J. Geophys. Res. Atmos., 120, 6034– 6055, https://doi.org/10.1002/2015JD023156.

Dias Neto, J., and Coauthors, 2019: The TRIple-frequency and Polarimetric radar Experiment for bettering course of observations of winter precipitation, Earth Syst. Sci. Knowledge, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019.

Stein, T. H. M., C. D. Westbrook, and J. C. Nicol, 2015: Fractal geometry of combination snowflakes revealed by triple-wavelength radar measurements, Geophys. Res. Lett., 42, 176–183, https://doi.org/10.1002/2014GL062170.

Bauer, P., E. Moreau, F. Chevallier, and U. O’Keeffe, 2006: A number of-scattering microwave radiative switch for knowledge assimilation functions, Quarterly Journal of the Royal Meteorological Society, Wiley, 132 (617), pp.1259-1281, https://doi.org/10.1256/QJ.05.153.

Saunders, R., J., and Coauthors, 2020: RTTOV-13 science and validation report, EUMETSAT NWP-SAF.

Geer, A. J., and Coauthors, 2021: Bulk hydrometeor optical properties for microwave and sub-mm radiative switch in RTTOV-SCATT v13.0, Geosci. Mannequin Dev. Talk about. [preprint], https://doi.org/10.5194/gmd-2021-73, in assessment.

Eriksson, P., R. Ekelund, J. Mendrok, M. Brath, O. Lemke, and S. A. Buehler, 2018: A common database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths, Earth Sys. Sci. Knowledge, 10, 1301–1326, https://doi.org/10.5194/essd-10-1301-2018.

 



Source link

news7g

News7g: Update the world's latest breaking news online of the day, breaking news, politics, society today, international mainstream news .Updated news 24/7: Entertainment, Sports...at the World everyday world. Hot news, images, video clips that are updated quickly and reliably

Related Articles

Back to top button