Differences between revisions 12 and 16 (spanning 4 versions)
⇤ ← Revision 12 as of 2014-01-10 06:44:46 →
Size: 4586
Editor: AlexanderLoew
Comment:
← Revision 16 as of 2014-01-10 13:37:49 → ⇥
Size: 5077
Editor: anonymous
Comment:
Deletions are marked like this. Additions are marked like this.
Line 5: Line 5:
Line 8: Line 7:
= 63-953 Climate and Satellite Data Analysis = = 63-953 Climate and Satellite Data Analysis =
'''Lars Kaleschke, Alexander Loew'''
Line 14: Line 14:
Place: Geom 1536c  Place: Geom 1536c
Line 17: Line 17:

The participants will learn to practically work with climate model, reanalysis, in-situ station and satellite data. Organized as a group project, the participants will further learn the principles of project management and shared software development. 		 The participants will learn to practically work with climate model, reanalysis, in-situ station and satellite data. Organized as a group project, the participants will further learn the principles of project management and shared software development.
Line 22: Line 21:
Line 25: Line 23:
 * [[/PM|Project management and documentation]]   * [[Climate_and_Satellite_Data_Analysis_2014/PM|Project management and documentation]]
Line 27: Line 25:
 * [[DataIO|Access to data sets]] 
 * [[/Plotting|Plotting]] [[attachment:Seawater plot.ipynb]]
 * [[GenMaps|Data Visualization: Generating maps]] 
 * [[http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html|IPython Notebooks]] [[https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks|Gallery of interesting IPython Notebooks]] 		  * [[DataIO|Access to data sets]]
 * [[Climate_and_Satellite_Data_Analysis_2014/Plotting|Plotting]] [[attachment:Seawater plot.ipynb]]
 * [[GenMaps|Data Visualization: Generating maps]]
 * [[http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html|IPython Notebooks]] [[https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks|Gallery of interesting IPython Notebooks]]
Line 32: Line 30:
Line 41: Line 38:
Line 47: Line 43:
Line 53: Line 48:
Line 59: Line 53:
Line 62: Line 55:
Afternoon: evaluation and preparation of final report   Afternoon: evaluation and preparation of final report
Line 66: Line 58:
  
Line 68: Line 59:
Line 71: Line 61:
Kevin Cowtan and Robert Way fill the gaps of the HadCRUT temperature data set by using satellite data. Compare their new reconstruction of surface temperature data to independent in-situ observations and reanalysis data.  Kevin Cowtan and Robert Way fill the gaps of the HadCRUT temperature data set by using satellite data. Compare their new reconstruction of surface temperature data to independent in-situ observations and reanalysis data.
Line 73: Line 63:
Cowtand and Way (2013) methods and data are freely available: Cowtan and Way (2013) methods and data are freely available:
Line 78: Line 68:
Surface temperatures are available from the International Arctic Buoy Programme (IABP) website:  Surface temperatures are available from the International Arctic Buoy Programme (IABP) website:
Line 83: Line 73:
Line 86: Line 75:
 * Review methods of Cowtan and Way (2013)
 * Write code to read and plot the data
 * Calculate trends and variabilites		  * Review methods of Cowtan and Way (2013)
 * Analyse their reconstructed dataset of surface air temperature (seasonal cycle, anomalies, trends etc.)
 * Are the trends significant?
Line 91: Line 80:
Line 94: Line 82:
 * Review methods of Rigor et al. (2000)
 * Write code to read and plot the gridded buoy data
 * Calculate trends and variabilites 		 * Review methods of Rigor et al. (2000)
 * Analyse the surface air temperature measured by the drift buoys (seasonal cycle, anomalies, trends etc.)
 * Are the trends significant?
Line 98: Line 86:
Reference:
Line 102: Line 89:
Use the buoy measurements of surface air temperature as ground truth
Line 103: Line 91:
(advanced programming skills needed)

 * Write code to interpolate the different datasets in a common grid
 * Compare CW2013, buoy and reanalysis data (variability and trends)		  * Write code to interpolate the different datasets in a common grid
 * Compare CW2013, buoy and reanalysis data
 * How large is the correlation of the datasets?
 * Are there biases or jumps in the data?
 * Was the data gap in the Arctic filled reasonably?
Line 110: Line 99:
Line 112: Line 100:

* [[http://www.hoaps.org | HOAPS climatology]] of ocean surface fluxes 		  * [[http://www.hoaps.org|HOAPS climatology]] of ocean surface fluxes
Line 118: Line 105:
 
Line 120: Line 107:
Line 124: Line 110:
Line 128: Line 113:
 * Bouy data :-)   * Bouy data :-)
Line 132: Line 117:
Line 137: Line 121:
 * Methods and data   * Methods and data
Line 143: Line 127:
Line 146: Line 129:

= Examples from the past =

== How significant are observations of Arctic temperature trends? ==

 * https://wiki.zmaw.de/lehre/Climate_and_Satellite_Data_Analysis_2013/ProjectA

Contents

  1. 63-953 Climate and Satellite Data Analysis
    1. Course objectives
    2. Schedule
      1. Monday
      2. Tuesday
      3. Wednesday
      4. Thursday
      5. Friday
  2. Topics for group work
    1. Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends
      1. Cowtan and Way (CW2013) reconstruction
      2. Variations in Surface Air Temperature Observations in the Arctic
      3. Data intercomparison
    2. HOAPS ocean flux sampling bias
  3. TODOs
    1. Data
    2. Final report
    3. References
  4. Examples from the past
    1. How significant are observations of Arctic temperature trends?

63-953 Climate and Satellite Data Analysis

Lars Kaleschke, Alexander Loew

MS Integrated Climate System Sciences

Date: 3.2.2014-7.2.2014

Place: Geom 1536c

Course objectives

The participants will learn to practically work with climate model, reanalysis, in-situ station and satellite data. Organized as a group project, the participants will further learn the principles of project management and shared software development.

Schedule

Monday

General Introduction

Group work: develop a project plan and write a short technical proposal for your project.

Final report due by 15. March 2014

Obtain data and do preliminary analysis (e.g. data coverage).

Tuesday

Morning: Group presentations of project plan and preliminary analysis.

Afternoon: implementation and project work

Wednesday

Morning: Group presentations of methods and code implementations

Afternoon: Project work

Thursday

Morning: Group presentations of preliminary results

Afternoon: Project work

Friday

Morning: final presenation of results and discussion

Afternoon: evaluation and preparation of final report

Topics for group work

media_summary.png

Kevin Cowtan and Robert Way fill the gaps of the HadCRUT temperature data set by using satellite data. Compare their new reconstruction of surface temperature data to independent in-situ observations and reanalysis data.

Cowtan and Way (2013) methods and data are freely available:

Surface temperatures are available from the International Arctic Buoy Programme (IABP) website:

Cowtan and Way (CW2013) reconstruction

/ProjectA

  • Review methods of Cowtan and Way (2013)
  • Analyse their reconstructed dataset of surface air temperature (seasonal cycle, anomalies, trends etc.)
  • Are the trends significant?

Variations in Surface Air Temperature Observations in the Arctic

/ProjectB

Data intercomparison

Use the buoy measurements of surface air temperature as ground truth

  • Write code to interpolate the different datasets in a common grid
  • Compare CW2013, buoy and reanalysis data
  • How large is the correlation of the datasets?
  • Are there biases or jumps in the data?
  • Was the data gap in the Arctic filled reasonably?

/ProjectC

HOAPS ocean flux sampling bias

  • HOAPS climatology of ocean surface fluxes

  • HOAPS is sampled twice a day
  • What is the impact of undersampling the dirnal cycle on monthly means?
  • What is the impact of sea ice gaps on monthly means?
  • How do HOAPS surface flux estimates compare to literature values of global mean ocean surface fluxes?

/ProjectD

TODOs

Data

  • CW2013 :-)

  • ERA-Interim :-)

  • NCEP :-)

  • Bouy data :-)

  • HOAPS data :-)

Final report

Template structure:

  • Abstract
  • Introduction: state of the art (literature), statement of the problem
  • Methods and data
  • Results
  • Discussion
  • Conlcusion

References

  • Python at KlimaCampus

  • Python Scripting for Computational Science, Hans Petter Langtangen, Springer (available in the ZMAW library)

Examples from the past

How significant are observations of Arctic temperature trends?

LehreWiki: Climate_and_Satellite_Data_Analysis_2014 (last edited 2014-02-05 09:14:16 by anonymous)