Cecilia Bitz (Class Instructor) is interested in high latitude climate and climate change in both modern and past climates. My first foray into climate modeling began in 1998 when I ran an EMIC to study North Atlantic-Arctic climate variability. In no time I had taken apart the sea ice component model and rewrote the thermodynamics code from the ground-up. The new physics I developed is still state of the art 10 years later. Now I don't have time to rip models apart so much. Instead I use models for my research and help steer the CCSM project. For this class I hope everyone involved expands their understanding of the basics of climate modeling and gains useful experience running models and hypothesis testing.

LuAnne Thompson (Class Instructor) research is all related to the role that ocean circulation variability plays in climate variability. She was recently called an ocean model slut (not to be repeated) as she uses a variety of ocean models depending on the question at hand. She uses an isopycnal model (HIM, built at GFDL) to investigate how ocean circulation variability can effect ocean biogeochemistry, evaluates POP (the ocean model of CCSM) both in high resolution ocean only simulations, and in standard coupled runs. Graduate students working with her also use ROMS, n coastal ocean model, to investigate sea-ice, ocean circulation and tides in the Okhotsk Sea and WRF, to investigate the role of the Gulf Stream in storm formation. She just got an LGM project funded, so needs to learn how to run CCSM herself, so that is the her first goal of the class. She would also like everyone in the class understand the trade offs that are made anytime you try to model any component of the climate system.

Phil Rasch (Class Instructor #2) is a visitor from NCAR. More to details to follow.

Rei Ueyama is a graduate student in the Department of Atmospheric Sciences. My research interests include large-scale patterns of climate variability with primary focus on the role of tropical atmospheric dynamics. The data I have analyzed for past and present projects have all been "observational" data sets (e.g., satellite, buoy, Reanalysis data). Recently, I started working with a very simple atmospheric dynamical core model to examine the cause of the annual cycle in tropical tropopause temperature. I have found this to be a very daunting but important step in honing my research skills. I hope this class will not only help me ease my way into incorporating a modeling component to my research but also provide me with a better understanding of how models work and their appropriate uses.

Steven Cavallo is a graduate student in atmospheric sciences. His current research examines the dynamics and physical mechanisms that control intensity changes of tropopause based vortices. These vortices are maintained mainly in Arctic regions, poleward of the midlatitude jet stream, can have rather long lifetimes, but can also have a significant impact on midlatitude weather at the surface. This work involves the use of a mesoscale numerical model (WRF), as well as observational data. Results have pointed toward a sensitive role that clouds play in the maintenance of these vortices, in which these effects could be potentially altered as the Arctic climate warms and atmospheric moisture levels increase. In this class, he hopes to gain an understanding of climate models and how to apply them to research problems, as a longer-term goal of his research is to understand the role that these vortices have in climate.

Justin Minder is a graduate student in the department of Atmospheric Sciences. My past work has focused on patterns of mountain precipitation on scales smaller than entire mountain ranges (e.g. the ridge-valley scale). I've looked very closely at precipitation in the southwestern Olympic Mountains of WA by maintaining a dense network of rain-snow gauges and other insturments as well as by looking at output from a high-resolution atmospheric model. I recently finished a side-project examining the impact of precipitation patterns on patterns of landslide hazard. I am currently starting some new research trying to understand how mountain precipitation changes with climate. For this work I hope to use global models to capture the interactions between global constraints on rainfall and the mechanisms of mountain weather. I am interested in gaining a working knowladge of how to use climate models, as well as the ability to critically evaluate their output.

Ed Blanchard is a graduate student in atmospheric sciences. My past work has mainly focused on glacier mass balance and sea ice and their interactions with atmospheric variability at the monthly/seasonal time scale. I intend to use climate models to investigate the response of sea ice and possible feedback mechanisms upon atmospheric variability. I am keen to gain a working knowledge of climate models and try to understand all the processes involved in them, rather than see them just a black box.

Stuart Evans is a graduate student in the Department of Atmospheric Sciences. Prior to joining the department I was in astronomy, working with robotic telescopes for rapid ground-based response to gamma-ray bursts. In the future however, I intend to get into the guts of the cloud resolving models embedded in GCMs in hopes of identifying the atmospheric states under which they function poorly and improving them. As such, I'm looking forward to learning the mechanisms of climate models and the methods by which they are applied to assorted problems.

Ty Robinson is a graduate student in the Astronomy Department and is associated with the Astrobiology program. He was an undergraduate at the University of Arizona where he worked on manufacturing components for ground-based radio telescopes and on feasibility studies for future space-based telescopes capable of detecting terrestrial planets (e.g., TPF, TOPS). At the University of Washington, he is currently working with the Virtual Planetary Laboratory's 3-D spectral Earth model. This model aims to study the Earth as an extrasolar planet analog, helping us to understand what biosignatures may look like on planets similar to the Earth. In the future, he hopes to apply climate models to the early Earth in order to understand what biosignatures were present on the Earth prior to the evolution of oxygenic photosynthesis. He also hopes to use climate models to further explore the idea of the liquid water habitable zone.

Silje Soerland is an exchange student from University of Oslo, Norway. From before I have a bachelor in physics. I don't have any experience withing modeling, but hope to improve my knowledge during this course, since that will help me a lot when I go back to Oslo to do my research. I'm mostly interested in dynamics, and I'm in progress of planning my master theses within that now.

Kelly McCusker is a graduate student in the Department of Atmospheric Sciences. Currently, I am just beginning a project with climateprediction.net to look at climate sensitivity and what parameter combinations, if any, can explain past warm climates, with an eye toward feasibility of such extreme climates happening in the future. This project involves running a climate model as well as studying output from previous runs. Additionally, in the future my work will likely involve using climate models to look at explaining past midlatitude/subpolar climate anomalies with changes in the tropical climate. In this class, I am looking forward to learning how climate models are structured, how to run them, and how to approach analyzing their outputs.

Kyle Armour is a graduate student in the Physics Department, working in the fields of Oceanography and Atmospheric Sciences. My current research involves the use of the regional ocean model ROMS and the sea-ice model CSIM to investigate sea ice formation and ocean circulation in the Sea of Okhotsk. In this class I hope to gain a better understanding of the physics on which climate models are based, and acquire the experience necessary to run various models and evaluate their output.

Kai-Chieh Cathy Yang is a graduate student in physical oceanography. My current research focuses on the meso-scale variation of the Kuroshio. The major tool I use for observation is seaglider, a small, reusable autonomous underwater vehicle designed to glide from the ocean surface to as deep as thousand meters collecting profiles of water properties. Since the Kuroshio is under a special wind system – Asian (seasonal) monsoon, which is considered to play an important role in the mesoscale field associated with the Kuroshio and even Kuroshio itself, the interactions between the Kuroshio and atmospheric variability would be my concerns. I am keen to gain a better understanding of how climate models work and how to use them that would be helpful to my research.

Paul Hezel is a is a graduate student in the Department of Atmospheric Sciences. My research project is focusing on a modeling study of methanesulfonic acid (MSA) as a proxy of sea ice extent. I will estimate ocean emissions of dimethyl sulfide (DMS) in the sea ice zone. These are oxidized in the atmosphere to MSA. A regional chemical transport model over Antarctica will be used to simulate oxidation and deposition on the continent. Once a signal of MSA deposition is determined in the model, these can then be compared to the satellite record of sea ice extent, as well as ice core and snow pit analyses over the continent. My interest is this class is primarily to understand how a model is constructed, as well as to gain better insight into how the GCMs work and the experiments that can be run with them. I have some experience with running CCSM.

Kevin Wood is a graduate student in the department of Earth and Space Science and on staff at the Joint Institute for the Study of Atmosphere and Ocean (JISAO). My research interests are focused on the use of historical information in climatology. The recovery and analysis of instrumental meteorological data in the Arctic and elsewhere is an ongoing project. I hope to become generally familiar with model output and how it may be used to evaluate sampling effects related to sparse network distributions that change over time and to better understand the nature of unforced climate variability reflected in historical data.