Tuesday, September 23, 2014

TOSCA training school hands on

Scratching below the (ocean) surface: identification of atmospheric responses to the 11-yr solar cycle 

The response of the lowermost atmosphere to radiation perturbations in the course of the solar cycle has been traditionally explained in terms of forcing from above. That is, ozone absorption of UV radiation alters the mean state of the stratosphere in solar maximum and stratosphere-troposphere dynamical coupling brings solar signals downward, altering tropospheric circulation. This chain of mechanisms may explain atmospheric responses in winter months but may not be suffice to describe annually averaged signals. This team will focus primarily on solar signals at the ocean surface (and below) both in global and regional scales. Having established robust oceanic responses we are asking whether observed solar signals in the troposphere can be explained by surface changes alone. The main objective of our team is to highlight that the role of the oceans in shaping tropospheric responses to the solar cycle is not well understood and to convince potential funding agencies (and ourselves) that more research is needed to this direction.

Further reading,
White et al., (1997): Response of global upper ocean temperature to changing solar irradiance
Gray et al. (2010) :  Solar Influences on Climate
Roy and Haigh (2010): Solar cycle signals in sea level pressure and sea surface temperature
Misios and Schmidt (2013): The role of the oceans in shaping the tropospheric response to the 11 year solar cycle


datasets and scripts can be found on




HadCRUT4 is a gridded dataset of global historical surface temperature anomalies relative to a 1961-1990 reference period. Data are available for each month since January 1850, on a 5 degree grid. The dataset is a collaborative product of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia. The gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations.(http://www.metoffice.gov.uk/hadobs/hadcrut4/index.html)

Reference paper
Time series of surface temperature

20th Century Reanalysis V2: 1871-2011

The 20th Century Reanalysis version 2 (20CRv2) dataset contains global weather conditions and their uncertainty in six hour intervals from the year 1871 to 2011. Surface and sea level pressure observations are combined with a short-term forecast from an ensemble of integrations of an NCEP numerical weather prediction model using the Ensemble Kalman Filter technique to produce an estimate of the complete state of the atmosphere, and the uncertainty in that estimate.  Additional observations and a newer version of the NCEP model that includes time-varying CO2 concentrations, solar variability, and volcanic aerosols are used in version 2. (http://www.reanalyses.org/)

Reference paper

Time series of surface temperature, air temperature and zonal winds.

SODA v2.2.4

There are several versions of SODA depending on the experiment setup. Version 2.2.4 represents their first assimilation run of over 100 years and uses the 20Crv2 winds. As such it is considered a "beta release" and is currently under evaluation in preparation of another long run. The ocean model is based on Parallel Ocean Program physics with an average 0.25°x0.4°x40-level resolution. Observations include virtually all available hydrographic profile data, as well as ocean station data, moored temperature and salinity time series, surface temperature and salinity observations of various types, and nighttime infrared satellite SST data. (http://apdrc.soest.hawaii.edu/datadoc/soda_2.2.4.php)

Reference paper
Time series of subsurface ocean temperature


NCEP-NCAR (R1) is the original reanalysis effort. It uses a frozen global state-of-the-art global data assimilation system (as of 11 January 1995). The original database was enhanced (additional, quality checked datasets) by NCAR's Data Support Section. Originally planned to span 1957-96 ("40-Year Reanalysis Project"), it was extended back to 1948 and continues to this day.

Reference paper
Time series of monthly zonal mean temperature


ERA-40 is an ECMWF re-analysis of the global atmosphere and surface conditions for 45-years, over the period from September 1957 through August 2002 by ECMWF. Many sources of the meteorological observations were used, including radiosondes, balloons, aircraft, buoyes, satellites, scatterometers. This data was run through the ECMWF computer model at a 40 km resolution (from wikipedia).

Reference paper
Time series of monthly zonal mean temperature

HomeAdditional information about the datasets can be found at https://climatedataguide.ucar.edu/ and http://www.reanalyses.org/



Climate Data Operators (CDO)

CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data.
Supported data formats are GRIB 1/2, netCDF 3/4, SERVICE, EXTRA and IEG. There are more than 600 operators available. (https://code.zmaw.de/projects/cdo)

Reference card

R language

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. (http://www.r-project.org/)

R introduction
Regression with R (online tutorial)
Indices for the multiple linear regression: TSI, AOD @ 550nm, Nino3.4, CO2 concentration.


The NCAR Command Language (NCL), a product of the Computational & Information Systems Laboratory at the National Center for Atmospheric Research (NCAR) and sponsored by the National Science Foundation, is a free interpreted language designed specifically for scientific data processing and visualization. NCL has robust file input and output. It can read and write netCDF-3, netCDF-4 classic, netCDF-4, HDF4, binary, and ASCII data. (http://www.ncl.ucar.edu/)

NCL tutorial