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Yousuke Sato, Kentaroh Suzuki, Takamichi Iguchi, In-Jin Choi, Hiroyuki Kadowaki, and Teruyuki Nakajima

Abstract

Three-dimensional downscaling simulations using a spectral bin microphysics (SBM) model were conducted to investigate the effects of aerosol amount and dynamical stabilities of the atmosphere on the correlation statistics between cloud droplet effective radius (RE) and cloud optical thickness (COT) of warm clouds off the coast of California. The regeneration process of aerosols was implemented into the SBM and was found to be necessary for simulating the satellite-observed microphysical properties of warm clouds by the SBM model used in this study.

The results showed that the aerosol amount changed the correlation statistics in a way that changes the cloud particle number concentration, whereas the inversion height of the boundary layer, which is related to the atmospheric stability and the cloud-top height, changed the correlation statistics in a way that changes the liquid water path. These results showed that the dominant mechanisms that control the correlation statistics are similar to those suggested by previous modeling studies based on two-dimensional idealized simulations. On the other hand, the present three-dimensional modeling was also able to simulate some realistic patterns of the correlation statistics, namely, mixtures of characteristic patterns and the “high-heeled” pattern as observed by satellite remote sensing.

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Takamichi Iguchi, Toshihisa Matsui, Zhining Tao, Dongchul Kim, Charles M. Ichoku, Luke Ellison, and Jun Wang

Abstract

Series of aerosol transport hindcasts for West Africa were conducted using the Weather Research and Forecasting (WRF) Model coupled to chemistry within the NASA-Unified WRF (NU-WRF) framework. The transport of biomass-burning aerosols in April and December 2009 was investigated over two types of simulation domains. One-month simulations with 9-km grid spacing for April or December 2009 covered most of North and West Africa and were evaluated by comparison with measurements of the total-column aerosol optical depth, Ångström exponent, and horizontal wind components at various pressure levels. The horizontal wind components at 700 hPa were identified as key factors in determining the transport patterns of biomass-burning aerosols from sub-Saharan West Africa to the Sahel. The vertical accumulation of biomass-burning aerosols close to 700 hPa was demonstrated in 1-day simulations with 1-km horizontal grid spacing. A new simple parameterization for the effects of heat release by biomass burning was designed for this resolution and tested together with the conventional parameterization based on fixed smoke injection heights. The aerosol vertical profiles were somewhat sensitive to the selection of parameterization, except for cases with the assumption of excessive heating by biomass burning. The new parameterization works reasonably well and offers flexibility to relate smoke transport to biomass-burning plume rise that can be correlated with the satellite fire radiative power measurements, which is advantageous relative to the conventional parameterization.

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Toshi Matsui, Brenda Dolan, Takamichi Iguchi, Steven A. Rutledge, Wei-Kuo Tao, and Stephen Lang

Abstract

This study contrasts midlatitude continental and tropical maritime deep convective cores using polarimetric radar observables and retrievals from selected deep convection episodes during the MC3E and TWPICE field campaigns. The continental convective cores produce stronger radar reflectivities throughout the profiles, while maritime convective cores produce more positive differential reflectivity Z dr and larger specific differential phase K dp above the melting level. Hydrometeor identification retrievals revealed the presence of large fractions of rimed ice particles (snow aggregates) in the continental (maritime) convective cores, consistent with the Z dr and K dp observations. The regional cloud-resolving model simulations with bulk and size-resolved bin microphysics are conducted for the selected cases, and the simulation outputs are converted into polarimetric radar signals and retrievals identical to the observational composites. Both the bulk and the bin microphysics reproduce realistic land and ocean (L-O) contrasts in reflectivity, polarimetric variables of rain drops, and hydrometeor profiles, but there are still large uncertainties in describing Z dr and K dp of ice crystals associated with the ice particle shapes/orientation assumptions. Sensitivity experiments are conducted by swapping background aerosols between the continental and maritime environments, revealing that background aerosols play a role in shaping the distinct L-O contrasts in radar reflectivity associated with raindrop sizes, in addition to the dominant role of background thermodynamics.

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Takamichi Iguchi, Teruyuki Nakajima, Alexander P. Khain, Kazuo Saito, Toshihiko Takemura, Hajime Okamoto, Tomoaki Nishizawa, and Wei-Kuo Tao

Abstract

Numerical weather prediction (NWP) simulations using the Japan Meteorological Agency Nonhydrostatic Model (JMA-NHM) are conducted for three precipitation events observed by shipborne or spaceborne W-band cloud radars. Spectral bin and single-moment bulk cloud microphysics schemes are employed separately for an intercomparative study. A radar product simulator that is compatible with both microphysics schemes is developed to enable a direct comparison between simulation and observation with respect to the equivalent radar reflectivity factor Ze, Doppler velocity (DV), and path-integrated attenuation (PIA). In general, the bin model simulation shows better agreement with the observed data than the bulk model simulation. The correction of the terminal fall velocities of snowflakes using those of hail further improves the result of the bin model simulation. The results indicate that there are substantial uncertainties in the mass–size and size–terminal fall velocity relations of snowflakes or in the calculation of terminal fall velocity of snow aloft. For the bulk microphysics, the overestimation of Ze is observed as a result of a significant predominance of snow over cloud ice due to substantial deposition growth directly to snow. The DV comparison shows that a correction for the fall velocity of hydrometeors considering a change of particle size should be introduced even in single-moment bulk cloud microphysics.

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Baijun Tian, Huikyo Lee, Duane E. Waliser, Robert Ferraro, Jinwon Kim, Jonathan Case, Takamichi Iguchi, Eric Kemp, Di Wu, William Putman, and Weile Wang

Abstract

Several dynamically downscaled climate simulations with various spatial resolutions (24, 12, and 4 km) and spectral nudging strengths (0, 600, and 2000 km) have been run over the contiguous United States from 2000 to 2009 using the high-resolution NASA Unified Weather and Research Forecasting (NU-WRF) regional model initialized and constrained by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). This paper summarizes the authors’ efforts on the development of a model performance metric and its application to assess summer precipitation over the U.S. Great Plains (USGP) in these downscaled climate simulations. A new model performance metric T was first developed that uses both the linear correlation coefficient and mean square error and is consistent with other commonly used metrics, but gives a bigger separation between good and bad simulations. This metric T was then applied to the summer mean precipitation spatial pattern, diurnal Hovmöller diagram, and diurnal spatial pattern over the USGP from the simulations focusing on the summer precipitation diurnal cycle related to mesoscale convective systems (MCSs). The metric T skill scores increase significantly from the control simulation to the nudged simulations and from the nudged simulations with shorter wavelengths to the nudged simulations with longer wavelengths, but do not change much from MERRA-2 to the downscaled simulations or between the various downscaled simulations with different spatial resolutions. Thus, there is some credibility, but no significant value added compared to MERRA-2, of the downscaled climate simulations of the summer precipitation over the USGP.

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Takamichi Iguchi, Toshihisa Matsui, Wei-Kuo Tao, Alexander P. Khain, Vaughan T. J. Phillips, Chris Kidd, Tristan L’Ecuyer, Scott A. Braun, and Arthur Hou

Abstract

Two mixed-phase precipitation events were observed on 21 September and 20 October 2010 over the southern part of Finland during the Light Precipitation Validation Experiment (LPVEx). These events have been simulated using the Weather Research and Forecasting Model coupled with spectral bin microphysics (WRF–SBM). The detailed ice-melting scheme with prognosis of the liquid water fraction during melting enables explicit simulation of microphysical properties in the melting layer. First, the simulations have been compared with C-band 3D radar measurements for the purpose of evaluating the overall profiles of cloud and precipitation. The simulation has some artificial convective patterns and errors in the forecast displacement of the precipitation system. The overall overestimation of reflectivity is consistent with a bias toward the range characterized by large-diameter droplets in the surface drop size distribution. Second, the structure of the melting bands has been evaluated against vertically pointing K-band radar measurements. A peak in reflectivity and a gradual change in Doppler velocity are observed and similarly simulated in the common temperature range from approximately 0° to 3°C. The effectiveness of the time-dependent melting scheme has been justified by intercomparison with a corresponding simulation using an instantaneous melting scheme. A weakness of the new melting scheme is that melting particles having high liquid water fractions on the order of 80%–90% cannot be simulated. This situation may cause underestimation of radar reflectivity in the melting layer because of the assumptions of melting-particle structure used to calculate the scattering properties.

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Takamichi Iguchi, Wei-Kuo Tao, Di Wu, Christa Peters-Lidard, Joseph A. Santanello, Eric Kemp, Yudong Tian, Jonathan Case, Weile Wang, Robert Ferraro, Duane Waliser, Jinwon Kim, Huikyo Lee, Bin Guan, Baijun Tian, and Paul Loikith

Abstract

This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June–August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.

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Toshihisa Matsui, Takamichi Iguchi, Xiaowen Li, Mei Han, Wei-Kuo Tao, Walter Petersen, Tristan L'Ecuyer, Robert Meneghini, William Olson, Christian D. Kummerow, Arthur Y. Hou, Mathew R. Schwaller, Erich F. Stocker, and John Kwiatkowski
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