42 research outputs found
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Precipitation and latent heating distributions from satellite passive microwave radiometry. Part I: improved method and uncertainties
A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors
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An accurate and computationally cheap microwave scattering method for ice aggregates: the Independent Monomer Approximation
The Discrete Dipole Approximation (DDA) is widely used to simulate scattering of microwaves by snowflakes, by discretising the snowflake into small “dipoles” which oscillate in response to (i) the incident wave and (ii) scattered waves from all the other dipoles in the particle. It is this coupling between all dipole pairs which makes solving the DDA system computationally expensive, and that cost grows non‐linearly as the number of crystals n within an aggregate is increased.
Motivated by this, many studies have ignored the dipole coupling (the Rayleigh‐Gans Approximation, RGA). However, use of RGA leads to systematic underestimation of both scattering and absorption, and an inability to predict polarimetric properties. To address this, we present a new approach (the Independent Monomer Approximation, IMA) which solves the DDA system for each crystal “monomer” separately, then combines them to construct the full solution. By including intra‐monomer coupling, but neglecting inter‐monomer coupling, we save a factor of n in computation time over DDA.
Benchmarking IMA against DDA solutions indicates that its accuracy is greatly superior to RGA, and provides ensemble scattering cross sections which closely agree with their more expensive DDA counterparts, particularly at size parameters smaller than ∼5. Addition of rime to the aggregates does not significantly degrade the results, despite the increased density.
The use of IMA for radar remote sensing is evaluated, and we show that multi‐wavelength and multi‐polarisation parameters are successfully captured to within a few tenths of a dB for aggregates probed with frequencies between 3 and 200GHz, in contrast to RGA where errors of up to 2.5dB are observed.
Finally we explore the realism of the IMA solutions in greater detail by analysing internal electric fields, and discuss some broader insights that IMA provides into the physical features of aggregates that are important for microwave scattering