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A modeling study on the response of tropical deep convection to the increase of cloud condensation nuclei concentration. 1. Dynamics and microphysics. 2. Radiation and tropospheric chemistry

1) The responses of cloud physical processes of a developing tropical deep convection to the increase of CCN concentration have been studied using a three-dimensional cloud-resolving model. Three sets of model simulations, each consisting of 30 runs initialized using a set of 30 different CCN profiles with maximum concentrations ranging from 50 to 6000/cm3, have been carried out. The finding of this study that cloud droplet number concentration increases while cloud droplet size decreases with aerosol concentration is similar to the previous results mainly revealed in studies of stratiform clouds. However, the responses to increasing aerosol concentration of many other cloud properties illustrated in this study, particularly precipitation, are very different from those found or suggested in studies of stratiform clouds. Increasing CCN concentration causes a stronger convection, added mass of condensed water, and enhanced microphysical conversions, all leading to the increase in precipitation as well as the expansion of the cloud coverage. Interestingly, when initial CCN concentration exceeds a certain level, many of the above effects become insignificant, suggesting a relationship between some cloud properties and the logarithm of CCN concentration and further implying that a more substantial aerosol effect on deep convection could be seen over a clean rather than polluted region. Overall speaking, increasing CCN concentration does not significantly affect the precipitation efficiency. The increase with CCN concentration of upward flux of water vapor entering the cloud thus leads to an enhancement in moistening the free troposphere brought by the modeled cloud, besides adding more precipitation to the ground.

2) The responses of cloud physical processes of a developing tropical deep convection to the increase of CCN concentration have been studied using a three-dimensional cloud-resolving model. Three sets of model simulations, each consisting of 30 runs initialized using a set of 30 different CCN profiles with maximum concentrations ranging from 50 to 6000/cm3, have been carried out. The finding of this study that cloud droplet number concentration increases while cloud droplet size decreases with aerosol concentration is similar to the previous results mainly revealed in studies of stratiform clouds. However, the responses to increasing aerosol concentration of many other cloud properties illustrated in this study, particularly precipitation, are very different from those found or suggested in studies of stratiform clouds. Increasing CCN concentration causes a stronger convection, added mass of condensed water, and enhanced microphysical conversions, all leading to the increase in precipitation as well as the expansion of the cloud coverage. Interestingly, when initial CCN concentration exceeds a certain level, many of the above effects become insignificant, suggesting a relationship between some cloud properties and the logarithm of CCN concentration and further implying that a more substantial aerosol effect on deep convection could be seen over a clean rather than polluted region. Overall speaking, increasing CCN concentration does not significantly affect the precipitation efficiency. The increase with CCN concentration of upward flux of water vapor entering the cloud thus leads to an enhancement in moistening the free troposphere brought by the modeled cloud, besides adding more precipitation to the ground.

© 2005 American Geophysical Union

A new inverse method for trace gas flux estimation. Part II. Application to tropospheric CFCl3 fluxes

A new method for estimating time-varying fluxes of atmospheric trace gases using an atmospheric transport model and observed concentrations is presented. Specifically Kalman filtering is used to estimate inputs from a state-space model identified using unit-pulse response functions from a transport model. The method is new in that no assumptions about initial concentrations in the model are required, although this in turn means that all flux processes must be explicitly modeled as inputs linearly related to concentrations. This also means that at least one extra measuring-site or other measurement variable (e.g. a linear combination of emissions) than the number of input-fluxes being estimated, is required to ensure a stable Kalman filter.

Copyright Journal of Geophysical Research

A Note on Weak Double Dividends

 A weak double-dividend is the proposition that the welfare improvement from a green tax reform, where the revenue from an environmental tax is used to reduce other tax rates, must be greater than the welfare improvement from a reform where the environmental taxes are returned in a lump sum fashion. We show in this note that a weak double-dividend need not hold in a world with multiple distortions. In an economy with multiple distortions one must choose carefully which tax rates to reduce, or one can do worse than a lump sum redistribution of the environmental tax revenues.

Copyright ©1999-2008 The Berkeley Electronic Press

A Numerical Investigation of the Potential for Negative Emissions Leakage

Emissions restrictions in one region may decrease emissions elsewhere (negative leakage), as increased demand for capital and labor to abate emissions in constrained regions may reduce output in unconstrained regions. We investigate leakage in computable general equilibrium (CGE) models under alternative fossil fuel supply elasticity values and factor mobility assumptions. We find that fossil fuel supply elasticities must be equal or close to infinity to generate net negative leakage. As empirical estimates for fossil fuel supply elasticities are less than 1, we conclude that leakage estimates from CGE models are unlikely to be negative.

© 2013 American Economic Association

A Posteriori Analysis of Climate System Properties

Modern climate system models make use of numerous tunable parameters. Uncertainty in these parameter input values should be propagated to model outputs. By matching model outputs with observed climate data (20th-century deep ocean, surface, and upper air temperatures), we perform coherent posterior inference over the model parameters. Our work extends the analysis of Forest et al. (2002) through the application of model interpolation, Markov chain Monte Carlo posterior simulation, and a posteriori model selection. Forest et al. (2002) identified three critical and uncertain input parameters for the MIT 2DLO climate model: climate sensitivity (CS), deep-ocean heat uptake (KV), and net aerosol forcing (FA). Their work sampled the climate model diagnostics on a nonuniform 3D grid. We interpolate the climate model diagnostics over the empty regions of this grid, providing an approximation of a continuous climate model response for use likelihood functions. The likelihood functions applied depend on valid estimation of covariance among the elements of the multivariate diagnostic.

A preliminary field campaign in the Kathmandu Valley, Nepal: An urban photochemistry study

The Kathmandu Valley in Nepal experiences severe winter temperature inversions due to its location as a high altitude plateau situated in a semi-enclosed basin. This combined with a rapid increase in population and vehicle ownership has made air pollution of great concern in the valley within the last decade. Only a few sporadic studies have been done characterizing either the meteorology or the chemistry of the valley. This paper presents preliminary surface measurements of O$_{3}$ and NO$_{x}$ (NO + NO$_{2}$) from a field campaign in the Kathmandu Valley during January and February of 2003 and examines the photochemical processes affecting these trace gases. Peak ozone mole fractions ranged from 40 to 100 ppb, while peak NO$_{x}$ mole fractions were between 20 and 80 ppb. Diurnal variations of ozone, which are substantial, are compared to simultaneous NO$_{x}$ and micrometeorological measurements to infer factors influencing the production and loss rates of surface ozone and NO$_{x}$. A box model parameterizing the major processes thought to affect valley photochemistry and meteorology is used to further distinguish the relative effect of each precursor emission and model parameter on ozone mole fractions. The magnitude of the simulated maximum or minimum ozone mole fractions appears to be largely dependent on the deposition velocity and ozone levels aloft. The time at which simulated maximum or minimum ozone occurs seems to depend more on ultraviolet dissociation rates and the thickness of the surface and mixed layers.

A Process-based Analysis of Methane Exchanges Between Alaskan Terrestrial Ecosystems and the Atmosphere

We developed and used a new version of the Terrestrial Ecosystem Model (TEM) to study how rates of methane (CH4) emissions and consumption in Alaskan soils have changed over the past century in response to observed changes in the state's climate and are likely to change with projected climate changes over this century. We estimate that the current net emissions of CH4 (emissions minus consumption) from Alaskan soils are about 3 Tg CH4 per year. We project that net CH4 emissions will almost double by the end of the century in response to high-latitude warming and associated climate changes. If CH4 emissions from soils of the pan-Arctic region respond to climate changes in the way we project for the Alaskan soils, the net increase in high latitude CH4 emissions could lead to a major positive feedback to the climate system.

A Reduced Form Statistical Climate Model Suitable for Coupling with Economic Emissions Projections

In this work, we use models based on past data and scientific analysis to determine possible future states of the environment. We attempt to improve the equations for temperature and greenhouse gas concentration used in conjunction with the MIT Emissions Prediction and Policy Analysis (EPPA) model or for independent climate analysis based on results from the more complex MIT Integrated Global Systems Model (IGSM). The functions we generate should allow a software system to approximate the environmental variables from the policy inputs in a matter of seconds. At the same time, the estimates should be close enough to the exact values given by the IGSM to be considered meaningful.

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