Changes between Version 8 and Version 9 of 2019WP/ENHANCE05_SimonMHarmonic_Analysis
 Timestamp:
 20190827T14:54:14+02:00 (4 years ago)
Legend:
 Unmodified
 Added
 Removed
 Modified

2019WP/ENHANCE05_SimonMHarmonic_Analysis
v8 v9 29 29 Rather than adapting and upgrading an existing implementation of harmonicanalysis diagnostics (the current implementation in the trunk version or an existing alternative implementation) for the latest reference version of NEMO, the development of generic multiple linear leastsquares regression analysis diagnostics for NEMO as outlined below in the form of a new module `diamlr` (source:/NEMO/trunk/src/OCE/DIA/diamlr.F90), additional XIOS configuration, and an offline tool is proposed. This new diagnostics would readily allow for tidal harmonic analysis, and module `diaharm` (source:/NEMO/trunk/src/OCE/DIA/diaharm.F90) could be removed. In addition to tidal harmonic analysis the new development would facilitate nontidal applications, such as the identification of the seasonal cycle or linear trends in model fields. 30 30 31 === The use of XIOS for regression diagnostics 32 33 In general, leastsquares linear regression can be formulated in terms of scalar products of all possible pairings between the dependent variable, y>, and the regressors, x,,m,,> (the index identifies the regressor), where each vector component represents the corresponding value at each of the time steps included in the analysis. In particular, during the model run, it suffices to accumulate the scalar products <x,,m,,y> and <x,,m,,x,,n,,> by summing up the respective products for each time step; at the end of the analysis interval, which does not need to be known in advance, the regression analysis can be finalised using precomputed scalar products. 34 35 The computation of the regressors formulated as functions of time, the computation of the scalar products, and the output of the scalar products in model runs with enabled linear regression analysis can be delegated to the I/O server XIOS. This would have three main benefits: 36 37 * as the fields of dependent variables selected for regression analysis are typically already available in XIOS processes for regular model output, the NEMO processes would no longer have to access the large fields selected for analysis directly; 38 39 * the potentially large additional amounts of temporary storage required for the computation of the scalar products would be provided by XIOS processes, and so the memory footprint of the NEMO processes would hardly be affected when enabling linear regression analysis; and 40 41 * output files of partial scalar products for partial model runs can readily be generated by XIOS and recombined later (through addition) in order to prepare sets of scalar products for various analysis intervals, including analysis intervals that span across model restarts. 42 43 31 44 == Tests 32 45