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The classic Vickrey-Clarke-Groves (VCG) mech-anism ensures incentive compatibility, i.e., that truth-telling of all agents is a dominant strategy, for a static one-shot game. However, in a dynamic environment that unfolds over time, the agents’ intertemporal payoffs depend on the expected future controls and payments, and a direct extension of the VCG mechanism is not sufficient to guarantee incentive compati-bility. In fact, it does not appear to be feasible to construct mechanisms that ensure the dominance of dynamic truth-telling for agents comprised of general stochastic dynamic systems. The contribution of this paper is to show that such a dynamic stochastic extension does exist for the special case of Linear-Quadratic-Gaussian (LQG) agents with a careful construction of a sequence of layered payments over time. We propose a layered version of a modified VCG mechanism for payments that decouples the intertemporal effect of current bids on future payoffs, and prove that truth-telling of dynamic states forms a dominant strategy if system parameters are known and agents are rational. An important example of a problem needing such optimal dynamic coordination of stochastic agents arises in power systems where an Independent System Operator (ISO) has to ensure balance of generation and consumption at all time instants, while ensuring social optimality (maximization of the sum of the utilities of all agents). Addressing strategic behavior is critical as the price-taking assumption on market participants may not hold in an electricity market. Agents, can lie or otherwise game the bidding system. The challenge is to determine a bidding scheme between all agents and the ISO that maximizes social welfare, while taking into account the stochastic dynamic models of agents, since renewable energy resources such as solar/wind are stochastic and dynamic in nature, as are consumptions by loads which are influenced by factors such as local temperatures and thermal inertias of facilities. 

The abundance and sources of ice‐nucleating particles, particles required for heterogeneous ice nucleation, are long‐standing sources of uncertainty in quantifying aerosol‐cloud interactions. In this study, we demonstrate near closure between immersion freezing ice‐nucleating particle number concentration (n_INPs) observations andn_INPscalculated from simulated sea spray aerosol and dust. The Community Atmospheric Model with constrained meteorology was used to simulate aerosol concentrations at the Mace Head Research Station (North Atlantic) and over the Southern Ocean to the south of Tasmania (Clouds, Aerosols, Precipitation, Radiation, and atmospherIc Composition Over the southeRN ocean campaign). Model‐predictedn_INPswere within a factor of 10 ofn_INPsobserved with an off‐line ice spectrometer at Mace Head Research Station and Clouds, Aerosols, Precipitation, Radiation, and atmospherIc Composition Over the southeRN ocean campaign, for 93% and 69% of observations, respectively. Simulated vertical profiles ofn_INPsreveal that transported dust may be critical ton_INPsin remote regions and that sea spray aerosol may be the dominate contributor to primary ice nucleation in Southern Ocean low‐level mixed‐phase clouds.