Potential of millimeter- and submillimeter-wave satellite observations for hydrometeor studies

The distribution of hydrometeors is highly variable in space and time, since it is the result of a complex chain of processes with scales from microphysical (1e-6 m) to synoptical (1e3 m). It is a challenging task to observe these highly variable atmospheric constituents on a global scale with a temporal and spatial resolution sufficient for numerical weather prediction (NWP) and hydrological purposes. This study investigates the potential of the millimeter- and submillimeter-wavelength range on space-borne sensors for hydrometeor and surface precipitation rate observations. The approach is based on simulations with cloud resolving models (CRMs) coupled to a radiative transfer (RT) model. The simulations are performed for mid-latitude cases covering a broad band of precipitation events such as heavy convective and light stratiform winter precipitation. Realistic atmospheric conditions were simulated with two mesoscale CRMs: the Meso-scale NonHydrostatic model (Meso-NH) on a 10 km and the COSMO-DE (COnsortium for Small-scale MOdeling-DEutschland) on a 2.8 km horizontal resolution. When calculating brightness temperatures for satellite observations with the one-dimensional radiative transfer model MWMOD (MicroWave MODel), the detailed cloud microphysics and the three-dimensional fields of temperature, humidity, and pressure of the CRMs are considered in the calculation of the interaction parameters. The model framework has been evaluated by comparing the simulated brightness temperature fields to observations of the Special Sensor Microwave Imager (SSM/I) as well as to those of the Advanced Microwave Sounding Unit-B (AMSU-B). The results show a good agreement as long as the CRMs capture the atmospheric situation correctly. Consequently, by coupling the radiative transfer model for microwave radiation to CRMs it is possible to evaluate these models through comparison to microwave satellite observations. Brightness temperatures for frequencies between 50 and 428 GHz at nine observation angles have been simulated for five mid-latitude cases at two time steps. In combination with the vertically integrated hydrometeor contents, these brightness temperature simulations have been used to set up a database. On the basis of this database simple retrieval algorithms have been developed to estimate the potential of the millimeter- and submillimeter-wavelength region for precipitation and hydrometeor observations. The results show, that especially for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 20% in stratiform precipitation cases over land and ocean surfaces. The performance for rain water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain water path are larger especially over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain water path. Algorithms with a reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval. These are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces

Characterization of snowfall using ground-based passive and active remote sensors.

Snowfall is a key quantity in the global hydrological cycle and has an impact on the global energy budget as well. In sub-polar and polar latitudes, snowfall is the predominant type of precipitation and rainfall is often initiated via the ice phase. Currently, the spatial distribution of snowfall is poorly captured by numerical weather prediction and climate models. In order to evaluate the models and to improve our understanding of snowfall microphysics, global observations of snowfall are needed. This can only be obtained by space-borne active and passive remote sensors. In order to be able to penetrate even thick snow clouds, sensors operating in the microwave frequency region are favoured. The challenge for snowfall retrieval development lies first in the complexity of snowfall microphysics and its interactions with liquid cloud water. Secondly, comprehensive knowledge is needed about the interaction of electromagnetic radiation with snowfall in order to finally relate the radiative signatures to physical quantities. A general advantage of ground-based observations is that simultaneous measurements of in-situ and remote sensing instruments can be obtained. Such a six-month dataset was collected within this thesis at an alpine site. The instrumentation included passive microwave radiometers that covered the frequency range from 22 up to \unit[150]{GHz} as well as two radar systems operating at 24.1 and 35.5 GHz. These data were complemented by optical disdrometer, ceilometer and various standard meteorological measurements. State-of-the-art single scattering databases for pristine ice crystals and complex snow aggregates were used within this thesis to investigate the sensitivity of ground--based passive and active remote sensors to various snowfall parameters such as vertical snow and liquid water distribution, snow particle habit, snow size distribution and ground surface properties. The comparison of simulations with measurements within a distinct case study revealed that snow particle scattering can be measured with ground--based passive microwave sensors at frequencies higher than 90 GHz. Sensitivity experiments further revealed that ground-based sensors have clear advantages over nadir measuring instruments due to a stronger snow scattering signal and lower sensitivity to variable ground surface emissivity. However, passive sensors were also found to be highly sensitive to liquid cloud water that was frequently observed during the entire campaign. The simulations indicate that the uncertainties of sizes distribution and snow particle habit are not distinguishable with a passive-only approach. In addition to passive microwave observations, data from a low-end radar system that is commonly used for rainfall were investigated for its capabilities to observe snowfall. For this, a snowfall specific data processing algorithm was developed and the re-processed data were compared to collocated measurements of a high-end cloud radar. If the focus can be narrowed down to medium and strong snowfall within the lowest 2-3 km height, the reflectivity and fall velocity measurements of the low-end system agree well with the cloud radar. The cloud radar dataset was used to estimate the uncertainty of retrieved snowfall rate and snow accumulation of the low-end system. Besides the intrinsic uncertainties of single-frequency radar retrievals the estimates of total snow accumulation by the low-end system lay within 7% compared to the cloud radar estimates. In a more general approach, the potential of multi-frequency radar systems for derivation of snow size distribution parameters and particle habit were investigated within a theoretical simulation study. Various single-scattering databases were combined to test the validity of dual-frequency approaches when applied to non-spheroid particle habits. It was found that the dual-frequency technique is dependent on particle habit. It could be shown that a rough distinction of snow particle habits can be achieved by a combination of three frequencies. The method was additionally tested with respect to signal attenuation and maximum particle size. The results obtained by observations and simulations within this thesis strongly suggest the further development of simultaneous ground-based in-situ and remote sensing observations of snowfall. Extending the sensitivity studies of this study will help to define the most suitable set of sensors for future studies. A combination of these measurements with a further development of single-scattering databases will potentially help to improve our understanding of snowfall microphysics

A Physical Model to Estimate Snowfall over Land using AMSU-B Observations

In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures

A database of single scattering properties for hydrometeors at microwave and sub-millimetre frequencies

Remote sensing observations of hydrometeors (ice or liquid water particles) at microwave and sub-millimetre wavelengths provide important input to numerical weather forecasting through data assimilation and give insight to cloud processes that are relevant for climate prediction. The utilization of such measurements requires information on the single scattering properties (SSP), i.e., knowledge on how single hydrometeors scatter, absorb, and emit radiation. However, SSP are dependant on the particle orientation, shape, and size which in the case of ice hydrometeors are highly variable in nature. Furthermore, simulating the SSP of hydrometeors is challenging and computationally costly. These are the main challenges that this thesis aims to address. In the first study of this thesis, a new publicly available SSP database for randomly oriented ice hydrometeors was developed. In terms of covered frequencies, temperatures, sizes, and particle models it is the most extensive to date. Particle models include aggregates that were generated using a semi-realistic, stochastic aggregation simulator. The next study utilised the simulator for a more detailed investigation on the dependence of SSP upon aggregate characteristics. For instance, the size and aspect ratio of the constituent crystals were found to have a significant impact on the extinction and back-scattering cross-sections of the aggregates. The third study analysed the ability of the SSP database to reproduce a combination of real passive and active satellite observations, by the GPM (Global Precipitation Measurements) Microwave Imager (GMI) and the CloudSat Cloud Profiling Radar, in radiative transfer (RT) simulations. While the tested particle models could accurately reproduce the real observations, it was difficult to find a particle model that performed better than the others. However, complementary simulations show promise with respect to the upcoming Ice Cloud Imager. In the fourth study, SSP of ice particles that have a preference towards horizontal orientation were calculated and applied to passive RT simulations at 166 GHz. The characteristic polarization signals present in GMI observations of clouds were successfully reproduced by RT simulations. The final study provides SSP of non-spheroidal rain drops, accounting for the effect of aerodynamic pressure upon the drop shape. It was found that this effect can have a small, but non-negligible, impact on passive and active microwave observations

Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation

Numerical weather prediction systems still employ many simplifications when assimilating microwave radiances under all-sky conditions (clear sky, cloudy, and precipitation). For example, the orientation of ice hydrometeors is ignored, along with the polarization that this causes. We present a simple approach for approximating hydrometeor orientation, requiring minor adaption of software and no additional calculation burden. The approach is introduced in the RTTOV (Radiative Transfer for TOVS) forward operator and tested in the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). For the first time within a data assimilation (DA) context, this represents the ice-induced brightness temperature differences between vertical (V) and horizontal (H) polarization-the polarization difference (PD). The discrepancies in PD between observations and simulations decrease by an order of magnitude at 166.5 GHz, with maximum reductions of 10-15 K. The error distributions, which were previously highly skewed and therefore problematic for DA, are now roughly symmetrical. The approach is based on rescaling the extinction in V and H channels, which is quantified by the polarization ratio. Using dual-polarization observations from the Global Precipitation Mission microwave imager (GMI), suitable values for were found to be 1.5 and 1.4 at 89.0 and 166.5 GHz, respectively. The scheme was used for all the conical scanners assimilated at ECMWF, with a broadly neutral impact on the forecast but with an increased physical consistency between instruments that employ different polarizations. This opens the way towards representing hydrometeor orientation for cross-track sounders and at frequencies above 183.0 GHz where the polarization can be even stronger

Microwave and submillimeter wave scattering of oriented ice particles

Microwave (1-300GHz) dual-polarization measurements above 100GHz are so far sparse, but they consistently show polarized scattering signals of ice clouds. Existing scattering databases of realistically shaped ice crystals for microwaves and submillimeter waves (&gt; 300GHz) typically assume total random orientation, which cannot explain the polarized signals. Conceptual models show that the polarization signals are caused by oriented ice particles. Only a few works that consider oriented ice crystals exist, but they are limited to microwaves only. Assuming azimuthally randomly oriented ice particles with a fixed but arbitrary tilt angle, we produced scattering data for two particle habits (51 hexagonal plates and 18 plate aggregates), 35 frequencies between 1 and 864GHz, and 3 temperatures (190, 230 and 270K). In general, the scattering data of azimuthally randomly oriented particles depend on the incidence angle and two scattering angles, in contrast to total random orientation, which depends on a single angle. The additional tilt angle further increases the complexity. The simulations are based on the discrete dipole approximation in combination with a self-developed orientation averaging approach. The scattering data are publicly available from Zenodo (https://doi.org/10.5281/zenodo.3463003). This effort is also an essential part of preparing for the upcoming Ice Cloud Imager (ICI) that will perform polarized observations at 243 and 664GHz. Using our scattering data radiative transfer simulations with two liquid hydrometeor species and four frozen hydrometeor species of polarized Global Precipitation Measurement (GPM) Microwave Imager (GMI) observations at 166GHz were conducted. The simulations recreate the observed polarization patterns. For slightly fluttering snow and ice particles, the simulations show polarization differences up to 11K using plate aggregates for snow, hexagonal plates for cloud ice and totally randomly oriented particles for the remaining species. Simulations using strongly fluttering hexagonal plates for snow and ice show similar polarization signals. Orientation, shape and the hydrometeor composition affect the polarization. Ignoring orientation can cause a negative bias for vertically polarized observations and a positive bias for horizontally polarized observations

A Database of Microwave Single Scattering Properties of Ice Hydrometeors

Microwave remote sensing by satellites is important for global observations of ice hydrometeors. Interpretation of the measurements requires sufficiently accurate knowledge of hydrometeors’ interaction with photons, i.e.\ua0 article scattering and absorption. This presents a challenge for several reasons. Liquid hydrometeors can typically be modelled by spheroids, while the shapes of ice hydrometeors are known to be significantly more complex and variable. Also, the shapes can from a remote sensing perspective generally not be known exactly, as they vary from case to case. Finally, calculating the light scattering properties is challenging and computationally costly.This thesis presents work related to recent efforts in improving the representation of light scattering by ice hydrometeors. A new single scattering database is presented, which includes 34 frequencies in between 1 and 874 GHz, and supports both passive and active microwave applications. A total of 34 different particle models were included, ranging from pristine crystals to aggregates. Complete random orientation is assumed throughout, slightly limiting its usefulness with respect to polarimetric measurements. Most aggregates were generated through simulation of aggregation, by letting particles collide randomly. The database can be considered the most extensive of this type to date, and future versions are intended to include oriented and melting particles. The general intention is to aid existing and future satellite retrievals, and satellite data assimilation into weather prediction models, all requiring accurate modelling of measured radiances. Special attention has been given to the upcoming Ice Cloud Imager (ICI), part of Europe’s next generation of weather satellites.Using the aggregation simulation tools developed for the database, a more dedicated case study was performed, which looked at the impact of different aggregate shape parameters on the resulting scattering properties. Both the amount and aspect ratio of the aggregate constituent crystals was found to have a high impact on both extinction (183, 325 and 664 GHz) and back-scattering (13, 36 and 94 GHz). Effective density and aerodynamic area had a high impact as well. Calculated radar triple frequency signatures were seen to clearly depend on the particle shape, consistent with previous studies. Overall, the results indicate that the particle shape should be considered in both passive and active applications above 13 GHz, and future database development will consider this. A potential application is also retrieval of ice particle shape through remote sensing

Using passive and active observations at microwave and sub-millimetre wavelengths to constrain ice particle models

Satellite microwave remote sensing is an important tool for determining the distribution of atmospheric ice globally. The upcoming Ice Cloud Imager (ICI) will provide unprecedented measurements at sub-millimetre frequencies, employing channels up to 664 GHz. However, the utilization of such measurements requires detailed data on how individual ice particles scatter and absorb radiation, i.e. single scattering data. Several single scattering databases are currently available, with the one by Eriksson et al. (2018) specifically tailored to ICI. This study attempts to validate and constrain the large set of particle models available in this database to a smaller and more manageable set. A combined active and passive model framework is developed and employed, which converts CloudSat observations to simulated brightness temperatures (TBs) measured by the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and ICI. Simulations covering about 1 month in the tropical Pacific Ocean are performed, assuming different microphysical settings realized as combinations of the particle model and particle size distribution (PSD). Firstly, it is found that when the CloudSat inversions and the passive forward model are considered separately, the assumed particle model and PSD have a considerable impact on both radar-retrieved ice water content (IWC) and simulated TBs. Conversely, when the combined active and passive framework is employed instead, the uncertainty due to the assumed particle model is significantly reduced. Furthermore, simulated TBs for almost all the tested microphysical combinations, from a statistical point of view, agree well with GMI measurements (166, 186.31, and 190.31 GHz), indicating the robustness of the simulations. However, it is difficult to identify a particle model that outperforms any other. One aggregate particle model, composed of columns, yields marginally better agreement with GMI compared to the other particles, mainly for the most severe cases of deep convection. Of the tested PSDs, the one by McFarquhar and Heymsfield (1997) is found to give the best overall agreement with GMI and also yields radar dBZ–IWC relationships closely matching measurements by Protat et al. (2016). Only one particle, modelled as an air–ice mixture spheroid, performs poorly overall. On the other hand, simulations at the higher ICI frequencies (328.65, 334.65, and 668.2 GHz) show significantly higher sensitivity to the assumed particle model. This study thus points to the potential use of combined ICI and 94 GHz radar measurements to constrain ice hydrometeor properties in radiative transfer (RT) using the method demonstrated in this paper