Seminar: Madalina Surcel and Dominik Jacques

Madalina Surcel and Dominik Jacques have combined efforts to bring you a
special student seminar tomorrow at 14:35. Please join us for cookies and coffee before at
2:15 preceding the talk.

Abstract

For our student seminar, we have prepared something special. When
discussing our respective talks, we realized that we were touching many
similar concepts from different points of view. Instead of working out a
bridge between our presentation, we have interlaced them in order to
make a story. We think this will make it easier (and more interesting)
to understand the concepts presented. For us, it make a nice change from
the more formal conference presentations that we are accustomed to.

In the same spirit, here is our common abstract,

*Mesoscale prediction of precipitation: current status and future work*

It is widely accepted that whereas the performance of Numerical Weather
Prediction (NWP) models is continuously improving, precipitation still
remains very difficult to forecast and quantitative precipitation
forecasting (QPF) skill is generally low. This talk discusses the
ability of current generation mesoscale models (with dx~1km) to forecast
rainfall. Emphasis is put on the main factors affecting forecast quality
and on the methods that could improve QPF.

Through the evaluation of high-resolution ensemble
precipitation forecasts it is shown that models have generally very
little skill in forecasting rainfall at scales lower than 100km.
Furthermore, while ensemble methods can increase predictability at
scales larger than 100km, for small scales, the spread is too large to
provide useful forecasts.

At storm scales, assimilation of radar observations has the potential to
improve model predictions. So far, demonstrating the improvements
brought by assimilation has proven very challenging as forecasts show
great sensitivity to small errors in initial conditions. This is
especially true for humidity, which is not corrected significantly
through assimilation. As a solution to this problem, an alternative
method for the assimilation of radar observations based on a combination
of variational techniques and statistical analysis of model output is
discussed here.

Another pathway for the improvement of forecasts is through the use of
more accurate model physics. However, sensitivity tests show that
despite large dependence of results on various model parameters at small
scales, no single parameter explains the largest forecast errors.

The work presented here seems to indicate the existence of
a critical spatial scale situated around 100km. Above this scale,
forecasting results are satisfactory, while below it QPF skill is poor.
The effect of radar data assimilation is limited to scales smaller than
the critical scale such that improvements due to assimilation are
expected to be short-lived.

Seminar: Dr. Robert Rabin

Dr. Robert Rabin of NOAA’s National Severe Storm Laboratory NSSL in Oklahoma will be joining us Thursday, January 10, 2013 at 3:30 p.m. in Burnside Hall, room 934 to discuss “Research activities at the NOAA National Severe Storms Laboratory: Ideas for collaboration”

Abstract

A brief history of National Severe Storms Laboratory and the evolution of research activities there. The use of Doppler radar and GOES satellite data as an observation tool for detecting thunderstorm initiation and precipitation systems, land-use interaction with the boundary layer, monitoring surface wetness and wildfires, and challenges in numerical weather forecasting will be discussed. Ideas for collaboration with projects will be explored.

Seminar: Joowan Kim

Please join us tomorrow, Wednesday at 14:35 in Burnside 934 for a student seminar by Joowan Kim. Abstract is as follows:

 

Climatology of ERA-Interim and ensemble of CMIP5 models.

Annual-mean climatology (1979-2005) of 100-hPa temperature from a) ERA-Interim and b) ensemble of CMIP5 models. White contours denote OLR from observation and model ensemble respectively. c) Taylor diagram of the temperature field within 15S-15N for individual models (open and closed circles) and their ensemble (cross).

Thermal characteristics of the tropical tropopause layer in CMIP5 models: historical simulations

The climatology and variability of temperatures in the tropical tropopause layer are investigated in 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models for historical simulations. The climatology of 100-hPa temperatures compare well with ERA-Interim reanalysis. The models possess reasonable temperature minima in the deep tropics, but some models also have a warm bias or a bias in the location of the temperature minima. The CMIP5 models generally capture the phase of the seasonal cycle in 100-hPa temperatures, but the amplitude of the seasonal cycle varies greatly among models. The interannual variability in 100-hPa temperature is associated with the El Niño-Southern Oscillation (ENSO) and volcanic forcing in observation and CMIP5 models. Most of models successfully capture the ENSO-related large scale response, but the response to volcanic forcing is overestimated in many models. On intraseasonal timescales, observed and modeled variability is dominated by equatorial waves (Kelvin, inertio-gravity, and mixed Rossby-gravity waves) and the Madden-Julian Oscillation (MJO). Most models show variability related to the equatorial waves, but significant biases are found in the phase speeds of the waves when compared to ERA-Interim. The MJO signature is weak and non-distinguishable from the Kelvin wave power in most CMIP5 models.

Student Seminar: Amélie Bouchat

Energy dissipation in viscous-plastic sea ice models

Energy dissipation in viscous-plastic sea ice models

Energy dissipation in viscous-plastic sea ice models by Amélie Bouchat

Most current sea ice models are based on the viscous approximation introduced by Hibler (1979). These viscous-plastic (VP) models approximate the small elastic deformations by the viscous deformations of a creeping flow. The resulting numerical treatment is much more simple than in earlier sea ice models, but viscous deformations introduce a non-physical energy sink in the model since they are not reversible as the elastic deformations. The project is aimed at assessing the consequences, physically speaking, of this non-physical energy dissipation in the models and therefore verifying the validity of the VP approximation. The dissipation is studied using the kinetic energy balance that is derived using the continuity and momentum equations for sea ice. This analysis allows us to evaluate the different terms of the balance and look at the relative importance of the viscous dissipation. The results will be presented for a 40km-resolution run of 1 year. The dependence of the viscous dissipation on the number of Newton loops of the numerical solver of the momentum equation is also studied. Preliminary results at 20km-resolution will also be shown.

Student Seminar: Melissa Gervais

Please join us tomorrow in Burnside 934 at 14:35 for a student seminar by Melissa Gervais. Abstract follows.

How Well is the Distribution of Precipitation Represented? Part I: Impacts of Station Density and Resolution Changes on Gridded Station Data

Precipitation is one of the most important variables to predict in future climate change owing to the socio-economic implications for water resources. However, it has historically been a very challenging variable for climate models to predict. Newer versions of Community Climate System Model (CCSM) from the National Center for Atmospheric Research (NCAR) have seen great improvements in their representation of the distribution of precipitation, with results now very close to observations (Gent 2011). The accuracy of precipitation observations used to validate the GCM output is thus becoming increasingly important. Results will be presented from the first of two studies on examining the ability of observations, reanalysis, the CCSM4 fully coupled model, and the NCAR Community Atmosphere Model (CAM5), to represent the distribution of precipitation. Here, we focus on the accuracy of interpolating station data in terms of the method of interpolation and the station density.

Station data from the Global Historical Climatology Network – Daily Version 1.0, within the United States, will be used to create and test gridded precipitation products. The goal is firstly to examine what the impact of gridding station data is on the precipitation statistics and whether the gridding method used is important. Secondly, an experiment will be conducted to determine how dense an observation network needs to be, in different climatic regions, in order to produce an accurate distribution of precipitation. This allows us to identify regions where station density is not high enough to trust the gridded precipitation data for validating GCMs.

Student Seminar: Ayako Yamamoto

NAO Positive Negative Number Density Gridded

Please join us tomorrow, Wednesday Oct 3 for a seminar by Ayako Yamamoto entitled “On the source of European winter temperature variability.” in Burnside Hall room 934 at 14:35 . Her abstract follows:

The traditional view that ocean heat transport causes warmer winters in Western Europe relative to those in western North America (e.g., Maury, 1855), was challenged in a provocative study by Seager et al. (2002). They offer the alternative hypothesis that the zonal asymmetry in Northern Hemisphere climatological temperatures is instead set by the orographically-forced southwesterly winds over the Atlantic Ocean, with the annually-integrated net ocean heat transport playing a small role. However, neither paradigm addresses the role of air mass trajectory versus ocean heat transport on the variability in Western European temperatures. In this project, we quantitatively evaluate the source of wintertime temperature variability in Western Europe, examining the contribution of the trajectory of the air parcels arriving in Western Europe, the sea surface temperature (SST) over which these air parcels travel, and the role of the coupling between the two mechanisms. To tackle this question, a novel Lagrangian approach is used: we track air particles backward in time using the atmospheric dispersion model, FLEXPART (Stohl et al. 2005), driven with meteorological data from the National Centers of Environmental Prediction each January over the period from 1981 to 2009. The dispersion model is the appropriate tool to study this question because it accounts for turbulence in the planetary boundary layer. We then conduct a suite of idealized experiments that explicitly separates the role of SST and trajectory variability. Our preliminary results suggest that pathway variability is a much better predictor of interannual variability in the along-pathway heat fluxes than SST. However, SST also appears to be necessary in reconstructing the true heat fluxes on longer than interannual time scale.

Welcome Party

The Atmospheric and Oceanic Sciences department is having a welcome party on Friday September 14 at 4pm in Burnside Hall 942. All are invited!

Homecoming

Homecoming 2012

The Chair of Atmospheric and Oceanic Sciences, John Gyakum, cordially invites all alumni and friends to a special cocktail reception. Come meet former classmates, professors and current students as you recall old times and learn about recent changes in the department.

Friday, October 12, 2012 4:00 PM to 6:00 PM
Graduate Lounge (Room 942),
Burnside Hall, 805 rue Sherbrooke Ouest
Montreal, Quebec, H3A-0B9

Please RSVP by October 2, 2012 by contacting the Event Registrar via email at homecoming.alumni@mcgill.ca or via telephone at (514) 398-8288.

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