Toshihisa Matsui

Role of atmospheric aerosol concentration on deep convective precipitation: Cloud‐resolving model simulations

[i] A two-dimensional cloud-resolving model with detailed spectral bin microphysics is used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: south Florida, Oklahoma, and the central Pacific. A pair of model simulations, one with an idealized low cloud condensation nuclei (CCN) (clean) and one with an idealized high CCN (dirty environment), is conducted for each case. In all three cases, rain reaches the ground earlier for the low-CCN case. Rain suppression is also evident in all three cases with high CCN. However, this suppression only occurs during the early stages of the simulations. During the mature stages of the simulations the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case to almost no effect in the Florida case to rain enhancement in the Pacific case. The model results suggest that evaporative cooling in the lower troposphere is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN. A comparison and review of other modeling studies are also presented.

Effects of biomass-burning-derived aerosols on precipitation and clouds in the Amazon Basin: a satellite-based empirical study

[1] Biomass burning in the Amazon provides strong input of aerosols into the atmosphere, with potential effects on precipitation, cloud properties, and radiative balance. However, few studies to date have systematically examined these effects at the scale of the Amazon Basin, over an entire burning season, using available data sets. We empirically study the relationships of aerosol optical depth (ta) versus rainfall and cloud properties measured from satellites over the entire Brazilian Amazon during the dry, biomass burning seasons (August–October) of 2000 and 2003. Elevated ta was associated with increased rainfall in both 2000 and 2003. With enhanced ta, cloud cover increased significantly, and cloud top temperature/pressure decreased, suggesting higher cloud tops. The cloud droplet effective radius (Re) exhibited minimal growth with cloud height under background levels of ta, while distinct increases in Re at cloud top temperatures below � 10C, indicative of ice formation, were observed with aerosol loading. Although empirical correlations do not unequivocally establish the causal link from aerosols, these results are consistent with previous observational and modeling studies that pointed to dynamical effects from aerosols that invigorate convection, leading to higher clouds, enhanced cloud cover, and stronger rainfall. We speculate that changes in precipitation and cloud properties associated with aerosol loading observed in this study could have important radiative and hydrological effects on the Amazonian climate system. The accelerated forest burning for agricultural land clearing and the resulting enhancements in aerosols and rainfall may even partially account for the observed positive trend in Amazonian precipitation over the past several decades. Citation: Lin, J. C., T. Matsui, R. A. Pielke Sr., and C. Kummerow (2006), Effects of biomass-burning-derived aerosols on precipitation and clouds in the Amazon Basin: a satellite-based empirical study, J. Geophys. Res., 111, D19204,

Evaluation of Long-Term Cloud-Resolving Model Simulations Using Satellite Radiance Observations and Multifrequency Satellite Simulators

This paper proposes a methodology known as the Tropical Rainfall Measuring Mission (TRMM) TripleSensor Three-Step Evaluation Framework (T3EF) for the systematic evaluation of precipitating cloud types and microphysics in a cloud-resolving model (CRM). T3EF utilizes multisensor satellite simulators and novel statistics of multisensor radiance and backscattering signals observed from the TRMM satellite. Specifically, T3EF compares CRM and satellite observations in the form of combined probability distributions of precipitation radar (PR) reflectivity, polarization-corrected microwave brightness temperature (Tb), and infrared Tb to evaluate the candidate CRM. T3EF is used to evaluate the Goddard Cumulus Ensemble (GCE) model for cases involving the South China Sea Monsoon Experiment (SCSMEX) and the Kwajalein Experiment (KWAJEX). This evaluation reveals that the GCE properly captures the satellite-measured frequencies of different precipitating cloud types in the SCSMEX case but overestimates the frequencies of cumulus congestus in the KWAJEX case. Moreover, the GCE tends to simulate excessively large and abundant frozen condensates in deep precipitating clouds as inferred from the overestimated GCE-simulated radar reflectivities and microwave Tb depressions. Unveiling the detailed errors in the GCE’s performance provides the better direction for model improvements.

WRF Simulations of the 20–22 January 2007 Snow Events over Eastern Canada: Comparison with In Situ and Satellite Observations

Abstract One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Sat...

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

AmerIcAN meTeOrOLOGIcAL SOcIeTY | 1625 AffiliAtions: Masunaga—Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan; Matsui, tao, Hou, and olson—NASA Goddard Space Flight Center, Greenbelt, Maryland; KuMMerow—Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado; te. naKajiMa—Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan; Bauer—European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom; seKigucHi—Faculty of Marine Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan; ta. Y. naKajiMa— Research and Information Center, Tokai University, Tokyo, Japan Corresponding Author: Hirohiko Masunaga, Hydrospheric Atmospheric Research Center, Nagoya University, F3-1(200) Furocho Chikusa-ku, Nagoya 464-8601, Japan E-mail: masunaga@hyarc.nagoya-u.ac.jp

Measurement-based estimation of the spatial gradient of aerosol radiative forcing

[1] This paper diagnoses the spatial mean and the spatial gradient of the aerosol radiative forcing in comparison with those of well-mixed green-house gases (GHG). Unlike GHG, aerosols have much greater spatial heterogeneity in their radiative forcing. The heterogeneous diabatic heating can modulate the gradient in horizontal pressure field and atmospheric circulations, thus altering the regional climate. For this, we diagnose the Normalized Gradient of Radiative Forcing (NGoRF), as a fraction of the present global heterogeneous insolation attributed to human activity. Although the GHG has a larger forcing (+1.7 Wm � 2 )a s measured than those of aerosol direct (� 1.59 Wm � 2 ) and possible indirect effect (� 1.38 Wm � 2 ) in terms of a spatially averaged top-of-atmosphere value, the aerosol direct and indirect effects have far greater NGoRF values (� 0.18) than that of GHG (� 0.003). Citation: Matsui, T., and R. A. Pielke (2006), Measurement-based estimation of the spatial gradient of aerosol radiative forcing, Geophys. Res. Lett., 33, L11813, doi:10.1029/2006GL025974.

Global Precipitation Estimates from Cross-Track Passive Microwave Observations Using a Physically Based Retrieval Scheme

AbstractThe estimation of precipitation across the globe from satellite sensors provides a key resource in the observation and understanding of our climate system. Estimates from all pertinent satellite observations are critical in providing the necessary temporal sampling. However, consistency in these estimates from instruments with different frequencies and resolutions is critical. This paper details the physically based retrieval scheme to estimate precipitation from cross-track (XT) passive microwave (PM) sensors on board the constellation satellites of the Global Precipitation Measurement (GPM) mission. Here the Goddard profiling algorithm (GPROF), a physically based Bayesian scheme developed for conically scanning (CS) sensors, is adapted for use with XT PM sensors. The present XT GPROF scheme utilizes a model-generated database to overcome issues encountered with an observational database as used by the CS scheme. The model database ensures greater consistency across meteorological regimes and sur...

Estimating the Ice Crystal Enhancement Factor in the Tropics

AbstractThe ice crystal enhancement (IE) factor, defined as the ratio of the ice crystal to ice nuclei (IN) number concentrations for any particular cloud condition, is needed to quantify the contribution of changes in IN to global warming. However, the ensemble characteristics of IE are still unclear. In this paper, a representation of the IE factor is incorporated into a three-ice-category microphysical scheme for use in long-term cloud-resolving model (CRM) simulations. Model results are compared with remote sensing observations, which suggest that, absent a physically based consideration of how IE comes about, the IE factor in tropical clouds is about 103 times larger than that in midlatitudinal ones. This significant difference in IE between the tropics and middle latitudes is consistent with the observation of stronger entrainment and detrainment in the tropics. In addition, the difference also suggests that cloud microphysical parameterizations depend on spatial resolution (or subgrid turbulence pa...

Introducing multisensor satellite radiance‐based evaluation for regional Earth System modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Impact of assimilated and interactive aerosol on tropical cyclogenesis

This article investigates the impact of Saharan dust on the development of tropical cyclones in the Atlantic. A global data assimilation and forecast system, the NASA GEOS-5, is used to assimilate all satellite and conventional data sets used operationally for numerical weather prediction. In addition, this new GEOS-5 version includes assimilation of aerosol optical depth from the Moderate Resolution Imaging Spectroradiometer. The analysis so obtained comprises atmospheric quantities and a realistic 3-D aerosol and cloud distribution, consistent with the meteorology and validated against Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation and CloudSat data. These improved analyses are used to initialize GEOS-5 forecasts, explicitly accounting for aerosol direct radiative effects and their impact on the atmospheric dynamics. Parallel simulations with/without aerosol radiative effects show that effects of dust on static stability increase with time, becoming highly significant after day 5 and producing an environment less favorable to tropical cyclogenesis.