Reinel Sospedra-Alfonso

Representation of Snow in the Canadian Seasonal to Interannual Prediction System. Part I: Initialization

AbstractThe ability of the Canadian Seasonal to Interannual Prediction System (CanSIPS) to provide realistic forecast initial conditions for snow cover is assessed using in situ measurements and gridded snow analyses. Forecast initial conditions for snow in CanCM3 and CanCM4 employed by CanSIPS are determined by the response of the Canadian Land Surface Scheme (CLASS) used in both models to forcing from model atmospheric fields constrained by assimilation of 6-hourly reanalysis data. These snow initial conditions are found to be representative of the daily climatology of snow water equivalent (SWE) as well as interannual variations in maximum SWE and the timing of snow onset and snowmelt observed at eight in situ measurement sites located across Canada. The level of this agreement is similar to that of three independent gridded snow analyses (MERRA, the European Space Agency’s GlobSnow, and an offline forced version of CLASS). Total Northern Hemisphere snow mass generated by the CanSIPS initialization pro...

Classical solvability of the relativistic Vlasov–Maxwell system with bounded spatial density

In (Arch. Rational. Mech. Anal 1986, 92:59-90), Glassey and Strauss showed that if the growth in the momentum of the particles is controlled, then the relativistic Vlasov-Maxwell system has a classical solution globally in time. Later they proved that such control is achieved if the kinetic energy density of the particles remains bounded for all time (Math. Meth. Appl. Sci. 1987, 9:46-52). Here, we show that the latter assumption can be weakened to the boundedness of the spatial density.

Representation of Snow in the Canadian Seasonal to Interannual Prediction System. Part II: Potential Predictability and Hindcast Skill

AbstractThis paper examines potential predictability (PP) and actual skill for snow water equivalent (SWE) in the Canadian Seasonal to Interannual Prediction System (CanSIPS). A significant PP is found for SWE, with potentially predictable variance over 50% of the total variance at up to a 5-month lead in mid- to high latitudes in forecasts initialized after snow onset. Much, though not all, of this PP stems from a tendency for SWE anomalies to persist through the snow season. Although the spring melt acts as a PP barrier regardless of initialization date, in some regions significant PP reemerges in the following snow season. This is due primarily to ENSO teleconnections that are modeled realistically by CanSIPS, particularly in northwestern North America. Actual skill of CanSIPS in forecasting SWE is assessed using several verification datasets. Highest skills are obtained using a blend of five such datasets, consistent with the hypothesis that skill scores are degraded by errors in the verification data...

Influences of Temperature and Precipitation on Historical and Future Snowpack Variability over the Northern Hemisphere in the Second Generation Canadian Earth System Model

AbstractThis study examines the changing roles of temperature and precipitation on snowpack variability in the Northern Hemisphere for Second Generation Canadian Earth System Model (CanESM2) historical (1850–2005) and future (2006–2100) climate simulations. The strength of the linear relationship between monthly snow water equivalent (SWE) in January–April and precipitation P or temperature T predictors is found to be a sigmoidal function of the mean temperature over the snow season up to the indicated month. For P predictors, the strength of this relationship increases for colder snow seasons, whereas for T predictors it increases for warmer snow seasons. These behaviors are largely explained by the daily temperature percentiles below freezing during the snow accumulation period. It is found that there is a threshold temperature (−5±1°C, depending on month in the snow season and largely independent of emission scenario), representing a crossover point below which snow seasons are sufficiently cold that P...

Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (approximately 2.8× 2.8) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms – the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm (Ankerst et al., 1999; Daszykowski et al., 2002) and the algorithm of (Sander et al., 2003) – to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures; however, differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant-available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global-scale simulations using a simple gridmean value.

Initialization and Potential Predictability of Soil Moisture in the Canadian Seasonal to Interannual Prediction System

AbstractThe initialization and potential predictability of soil moisture in CanCM4 hindcasts during 1981–2010 is assessed. CanCM4 is one of the two global climate models employed by the Canadian Se...