DISSERTATION

AEROSOL EFFECTS ON CLOUD-PRECIPITATION AND LAND-SURFACE

PROCESSES

Submitted by

Toshihisa Matsui

Department of Atmospheric Science

In partial fulfillment of the requirements

For the Degree of Doctor of Philosophy

Colorado State University

Fort Collins, Colorado

Spring 2007

ABSTRACT OF DISSERTATION

AEROSOL EFFECTS ON CLOUD-PRECIPITATION AND LAND-SURFACE

PROCESSES

Aerosols not only directly scatter and absorb solar radiation (denoted as the

aerosol direct effects), but also modulate cloud properties by acting as cloud

condensation nuclei (CCN) to form cloud droplets (denoted as the aerosol indirect

effects). High concentrations of aerosols can overseed cloud droplets to reduce the mean

size of cloud droplets, which is hypothesized to increase cloud albedo for the constant

cloud liquid water path thereby slowing the warm-rain processes. The first part of this

dissertation examines the sensitivity of the aerosol indirect effect to different

thermodynamic environments over the tropical ocean. The variability of marine warm

cloud properties is derived from satellite multiple sensors, and is normalized by the

variability of satellite-derived aerosol index (AI) and reanalysis-derived lower-

tropospheric stability (LTS). Global statistics show that increases in AI (polluted air) are

associated with reductions in the cloud droplet effective radius (Re), supporting the

hypothesis of the aerosol indirect effect. Increase in LTS (strong lower-troposphere

stability) is also associated with reductions in the Re, indicating that the stronger

inversion prevents dynamical growth of cloud droplets. Marine warm rain processes are

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estimated from the comparison between cloud-top and column Re, and the global

statistics indicate that the warm-rain processes are minimized regardless of the air

pollution under a strong temperature inversion, while they are inhibited due to air

pollution under unstable thermodynamic conditions. The cloud liquid water path (CLWP)

tends to be decreased for higher AI, which does not support the assumption of constant

CLW associated with the reduction of Re. Global variability of corrected cloud albedo

(CCA: the product of cloud optical depth and cloud fraction) is better explained by the

variability of the LTS than by AI. CCA appear to be highest under the strong-inversion

regions, and is the first-order property that controls the radiation budget. Local variability

of these cloud properties is explained by a combination of AI and LTS better than by

either AI or LTS alone. Finally, the spatial mean and the spatial gradient of the aerosol

direct and indirect radiative forcing are estimated and compared with the forcing

attributed to well-mixed greenhouse gases (GHG) over the tropical ocean.

The aerosol direct effect not only reduces global irradiance but also increases

diffuse radiation. Diffuse radiation is more homogeneously absorbed by the plant canopy

and more efficiently utilized for the plant photosynthesis process than direct radiation.

Thus, aerosol loading is expected to increase plant productivity (the aerosol diffuse-

radiation effect). The second part of this dissertation examines the spatio-temoporal

variability of the aerosol diffuse-radiation effect over the eastern U.S., using a sun-shade

canopy model. First, satellite and model aerosol optical depth (AOD) products are

assimilated via an optimal interpolation technique, and a comparison against the ground-

based observations shows that the satellite-model assimilated AOD product is superior to

either a satellite or model product. Second, surface albedo, surface radiative temperature,

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CO2 flux, and sensible/latent heat fluxes in a sun-shade canopy model (Unified Land

Model: ULM) are compared with corresponding satellite and ground-based observations.

Tuning parameters in ULM are constrained by reducing model-observation discrepancies

via the Gauss-Maquardt-Levemberg automatic optimization algorithm. Third, the well-

calibrated ULM is run in an off-line model for the warm seasons in 2000 and 2001.

Downwelling shortwave radiation is computed with (a control experiment) and without (a

potential experiment) assimilated daily AOD in all-sky conditions. The sensitivity

experiments (control-potential) show that aerosol loading increases plant productivity in

mixed forests and deciduous broadleaf forests in the southeastern U.S., while plant

productivity is decreased over the croplands and grasslands. The spatio-temporal

variability of aerosol diffuse-radiation effect is well explained by the variability of LAI,

cloud optical depth, near-surface atmospheric temperature, and diurnal cycles. Due to the

combination of the positive and negative effects, the aerosol diffuse-radiation effect

increases plant productivity by only +0.5% in 2001 and 0.09% in 2000 from the

potential experiment over the eastern U.S.

Toshihisa Matsui Atmospheric Science Department

Colorado State University Fort Collins, CO 80523

Spring 2007

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Table of Contents

Abstract iii

Table of Contents vi

List of Tables xi

List of Figures xiii

Acknowledgements xxi

1 Introduction 1

1.1 Overview of Aerosol Effects on Climate . . . . . . . . . . . . 1

1.2 Motivations and Overviews of Chapters . . . . . . . . . . . . 4

References . . . . . . . . . . . . . . . . . . . . . . . . 12

2 Satellite-based Assessment of Impact of Aerosols and Atmospheric

Thermodynamics on Warm Rain Process 17

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 17

2.2 TRMM-Derived Cloud Properties . . . . . . . . . . . . . . . 19

2.3 Sensitivity of the Aerosol-Cloud Interaction . . . . . . . . . . . . 23

2.4 Summary and Perspectives . . . . . . . . . . . . . . . . . . 26

References . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3 Satellite-Based Assessment of Marin Low Cloud Variability Associated With

Aerosol, Thermodynamics, and Diurnal Cycle 31

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 31

3.2 Datasets and Method . . . . . . . . . . . . . . . . . . . . . 34

3.2.1 Lower-Tropospheric Stability (LTS) from the NCEP Reanalysis 34

vi

3.2.2 Aerosol Index from MODIS and GOCART . . . . . . . . . 36

3.2.3 Marine Low Cloud Properties from the TRMM Satellite . . . 40

3.2.4 Method of Analysis . . . . . . . . . . . . . . . . . . 42

3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . 45

3.3.1 Global Statistics Among Cloud Properties, LTS and AI . . . 45

3.3.2 Local Statistics Between Cloud Properties, AI and LTS . . . 52

3.3.3 Diurnal Cycle of Cloud Properties in Different LTS and AI Regions 57

3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . 62

Symbols and Terminology . . . . . . . . . . . . . . . . . . 66

References . . . . . . . . . . . . . . . . . . . . . . . . 68

4 Measurement-Based Estimation of The Spatial Mean and Gradient of Aerosol

Radiative Forcing 77

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 77

4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . 78

4.3 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

4.3.1 Aerosol Direct Radiative Forcing (ADRF) . . . . . . . . . 80

4.3.2 Aerosol Indirect Radiative Forcing (AIRF) . . . . . . . . . 82

4.4 Spatial Mean Radiative Forcing . . . . . . . . . . . . . . . 84

4.5 Spatial Gradient of Radiative Forcing . . . . . . . . . . . . 86

4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . 89

References . . . . . . . . . . . . . . . . . . . . . . . . 90

5 Regional Comparison and Assimilation of GOCART and MODIS Aerosol

Optical Depth across the Eastern U.S. 93

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5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 93

5.2 Data . . . . . . .