The VOCALS (VAMOS Ocean-Cloud-Atmosphere-Land Study - VAMOS is the Variability of the American Monsoon System project) region within the Southeast Pacific is a globally important regional coupled climate regime involving equatorward winds, orographic channeling, arid land margins, upwelling currents, oceanic biogeochemical cycling, marine stratus clouds, and aerosols. A principal motivation for the VOCALS project is that global model errors in this region degrade the quality of their simulations throughout the tropical Pacific, with substantial impacts on the modeled and predicted global climate. It is difficult or impossible to address these errors directly in global models with currently available computational resources, because the mechanisms that determine the mean state and variability have much finer spatial scales than global models can resolve. Moreover, these mechanisms do not lend themselves to unique and physically constrained treatments. A further complication is that the mechanisms involve interactions among all major components of the Earth system, including physical processes in the atmosphere, ocean, and land surface, as well as natural and anthropogenic influences on marine and atmospheric chemistry. Simulating these interlocking processes requires high resolution (several kilometers) with coupled atmosphere, ocean, and land components in both physical and chemical submodels. In this project a regional Earth-system modeling framework will be developed, with an atmospheric model coupled to a land surface model and an oceanic model. The atmospheric model includes chemical transport and process models, while the regional oceanic model contains full biogeochemistry. This framework will be used to explicate the climate dynamics of the VOCALS region and to leverage VOCAL REx (Regional Experiment) measurements through careful experimental design and model-validation and data-interpretation studies.
First, meteorological and aerosol forecasts will be provided for VOCALS REx during the campaign. After VOCALS REx, a retrospective simulation of the VOCAL REx period will be carried out using the full Earth-system model. The simulation's high resolution is intended to increase the interpretability of measurements by placing them in geographical and climate-variability context and to enhance the usefulness of measurements for model validation and evaluation. A simulation of the VOCALS region covering the past 60 years will place the VOCALS-REx observations and simulations in the context of climate variability. Finally, the VOCALS region will be downscaled from an NCAR CCSM (National Center for Atmospheric Research Community Climate System Model) global solution, placing the realism gained through careful development and VOCALS-REx-based validation of the regional model in the context of the errors in a major global climate model. All these simulations will be performed on the same model grid to allow for systematic comparison of model solutions with observations and with each other. The simulations will provide opportunities for analyses of interlocking physical and chemical processes that determine the climate of the VOCALS region. These include studies of the geographical distribution of natural and anthropogenic aerosols; the impact of these aerosols on cloud properties and the effects of clouds on aerosol scavenging; the intricate and highly-structured couplings in the physical system determining key climate variables such as stratus amount and upwelling; and the oceanographic processes controlling air-sea fluxes of DMS (dimethyl sulfide).
Broader impacts of this project are in its contributions to building human infrastructure for science research. Through interactions with colleagues in Peru and Chile, the investigators will foster international scientific collaboration, and they will train graduate students and postdoctoral fellows. The project will leave a legacy of modeling infrastructure, as the first time a holistic regional Earth-systems approach has been applied so systematically to any region. The modeling framework to be developed can serve as a prototype for Earth-system modeling in the service of climate prediction and climate applications. Finally, the PIs propose to capitalize on the unique measurements to be taken during the VOCALS-REx field campaign to understand the interlocking physical and chemical dynamics of the VOCALS region and to diagnose the causes of large, persistent errors in global models errors, potentially paving the way for improvements in climate predictions.
PI: Gregory Carmichael Awardee: University of Iowa Award Number: 0748012 Award Expires:02/29/2012 Program Officer Name: Eric T. DeWeaver Program Officer Email Address: edeweave@nsf.gov Program Officer Phone Number: (703)292-8527 Researchers at the University of Iowa, in collaboration with UCLA and the Universidad Nacional Andrés Bello, Chile, participated in the VOCALS REx field study focused on better understanding how fine particles in the atmosphere impact cloud properties. The field campaign was conducted off the coast of Chile and Peru in October 2008 and included measurements of aerosol composition and size and cloud properties from airborne and ship platforms. Our team developed a regional air quality and meteorology forecasting system and provided daily briefings that helped in planning and implementing the field experiments. Understanding how aerosols affect clouds in this region is important, as problems in the ability of global and regional weather models to accurately represent marine stratocumulus clouds has been shown to negatively impact weather prediction worldwide and to increase uncertainties in global and regional climate assessments. To support the modeling activities we developed, evaluated, and publically released a new emission inventory for the region. After the experiment was conducted, we analyzed the data obtained to test and improve our capabilities to model the impacts of aerosols on clouds. Results using a community model that couples air pollution and weather prediction (WRF-Chem) were compared with the observations. After extensive analysis and modification, we found that the improved model had skill in predicting regional weather, atmospheric chemistry, and aerosol-cloud interactions. Both the observations and predictions showed that near the coast there were more fine particles (primarily from pollution sources) and that the number of particles decreased over the sea as the distance from the coast increased. The number and size of cloud droplets varied with the number of particles, respectively increasing and decreasing as the particle number increased. The sources of the particles interacting with the clouds include urban pollution from Santiago, Chile as well as large smelters and power plants in Chile and Peru. We further found that the microphysical effects of these aerosols improved the ability to predict other features of clouds, including their height, brightness, and rainfall. The effects of these particles on clouds reduces the amount of light reaching the surface, which may partially explain the observed surface cooling in the region in the late 20th century. We used the documented and improved capabilities in predicting aerosol-cloud interactions to develop a new method to increase skill in numerical weather forecasting over the oceans and coastal areas. The idea is if we can improve predictions of the number of particles, we will improve the prediction of clouds and weather. The common way to improve the predictions of particles is to use information from optical sensors on satellites. Unfortunately, this information can only be obtained under cloud-free conditions, and many coastal regions are almost always covered by clouds. To overcome this limitation, we used satellite information on the number of cloud droplets to update the number of particles in the region before a forecast model run. We showed that using these new estimates at the start of the prediction improves the weather forecast for more than 24 hours. Building upon our modeling experiences in this region, we designed and tested an urban-scale version of the model to forecast air quality in Santiago. Santiago, Chile’s capital city of 7 million people, has severe wintertime air quality problems because it is located in a mountain valley. The government provides air quality forecasts and imposes emissions cut-backs when pollution episode alerts are issued. Working with local authorities, we have demonstrated that our system is capable of forecasting air pollution events with skill better than persistence and equivalent to or better than the statistical meteorological models currently used operationally in Santiago. We have also demonstrated that emissions from previous days dominate episode concentrations, so effective air quality management requires that emissions control decisions be made 48 hours in advance, requiring accurate 2-3 day forecasts. Prior to our study, the government only used a 24-hour forecast and reduced emissions the day of the predicted event, which is too late to be most effective. In 2011, this was installed at the Chilean Meteorological Service, where it is now used in operational air quality forecasts.
