AGU2010_monday

Posters
  Ty Ferre:
    the Mariotte Bottle at Wikipedia: en.wikipedia.org—Mariotte's_bottle en.wikipedia.org—Mariotte's_bottle
    his paper: www.agu.org —2007WR005889.shtml www.agu.org—2007WR005889.shtml
  Geophysics and K
Peter Gleick
  peak water; nothing really new to me
  see old planetwater.org post: Bottled and Sold planetwater.org—bottled-and-sold
Charles C. Eriksen: The Autonomous Revolution: Transforming Ocean Observation with Mobile Platforms
  U Washington, Seattle
  developed gliders
  AUVs and Gliders
  Piping Diagram
    Stommel's (1958) steady abyssal circulation
    Broeker's conveyer belt cartoon
  Eddy diagram
    NAVOCEANO 3.5km resolution
    depending on the colour scale you find eddies everywhere
    lots of motion around the equator
  expensive access is the principle impediment to ocean observation
    mobile platforms (occasional long sections)
    persistence - moorings
    combine persistence with mobility
    used to be very expensive
  Webb, Rosby float
  Bower et al 2009 Nature 459
    Piping diagram and what is really happening...
    Eddies diffused most of the floats
    3239 floats in the ocean US Argo led by NOAA Argo Profiling Float Project
      1 float per area the size of state of virginia
    Atlantic meridional Overturning at 41degree north
  Gliders
    go slowly
    gps is until late 80's available
    Iridium went bancrupt: perfect system for places in the world where nobody lives; was bought and then established. Then bidirectional 200 byte/sec
    Lithium batteries needed to be there (highest energy densitiy available)
    low power sleep mode processor
    longest mission: 292 days & 5528 km
  periodic structure in space vs. periodic structure in time
  ice-covered → more salinity
  sliding into the abyss is easy; sliding back up is hard
  smart, small, mobile, persistent, inexpensive
Krajewski - merging radar with rain gauge data
  history
    80's: Crawford: objective analysis; co-kriging, deterministic interpolation
    90's: bias adjustment, range-dependent bias correction
    last 20 years: a lot of work; many national weather radar networks
    to properly address the problem you need to understand the errors in both processes
  different error structures
  issue of merging both types: purpose and application
    "just give me the best estimates"
    what do you mean by this?
      there are multiple performance criteria
      non-linearities; problems if you go from scale to scale
        trade-off estimation bias vs. estimation variance
    order of magnitude difference in scales between bucket and radar
  approaches
    linear combination
    non-linear
    dynamic linear combination (KF)
    Physics-based data (observables) assimilation
    any of the last three: requires statistical qunatification of the involved uncertainties
  very dense cluster of rain gauges
    ARS micronet data
    piconet data
    Variance Partitioning
  Methods
    Var(RR-RG) = Var(RT-RR) + V(RT-RG) - 2Cov
      2Cov = 0 ???
    what's V(RT-RG)
    variance (?) consists of 3 parts: Relative covariance, correlation, variance ratio
  Super-resolution
    Nat Weather Service: 250m x 0.5degree
  Question:
    should we just use radar and calibrate to rain gauge
Ed Sudicky - impacts of climate change in Canada
  not just surface water, but also groundwater
  science based strategies to mitigate deterious effects
  physically based integrated model; integrated: solve system implicitly at each time-step; driven by potential gradients for flow
  San Joaquin: what might the system have looked in glod rush period
  Challenges
    very different timeframe respond: atmosphere, surface flow, subsurface flow
    very large meshes, typically unstructured
    strong non-linearities in differential equations
    data availability and upscaling issues; particularly in subsurface
  DEM: Hydro1k from USGS
  currently: 2Million elements, 15 layers
Paleochannels
  ~100Mtons/year CO2
Julia Slingo - UK Met office
  this year's extreme events
    volcano Eyjafjallajökull - en.wikipedia.org—Eyjafjallaj en.wikipedia.org—Eyjafjallaj ökull
    Pakistan flooding - Floods in Pakistan planetwater.org—floods-in-pakistan
    Russia heat wave
    flooding china

    storm in the universe/solar storm -- threat to communications
    "space weather event"

    snow and severe cold in the UK
  not only meteorology but met + sth. else
  Risk
    natural hazard - exposure / vulnerability - socio economic impact
    "we have to take concepts of probabilities through to our model"
    Non of the models we use are perfect - because of scales
    if we predict into the future, things get even more complicated
    volkano on iceland: we haven't done a full risk assessment, because we have never looked at the effects that unfavourable weather conditions might have on a not so unusual eruption
    North Atlantic Oscillation; positive mode and negative mode -- "Blocking"; in the negative more, the UK is "in the firing line"
    if the volcano is in your sector, the volcano belongs to you even if the ash leaves your sector