TRNSCLIMED

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TRNSCLIMA
TRNSCLIMA
Time Series of Meteorological Data for System
Simulation Region Iberia Version 1.0
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Overview

• People involved in numerical system simulation,
  e.g. with TRNSYS, often require hourly time
  series of meteorological data for a specific
  place as input.
• TRNSCLIMA provides Typical Year and Extreme Year
  time series data for
• solar irradiation (direct and diffuse components)
• ambient temperature
• ambient humidity
• wind intensity and direction
• adequate for thermal simulation of buildings and
  solar energy systems,
• as well as for simulation of numerous other
  devices and analysis of problems in such fields
  as agronomy, forestal fires or corrosion of
  weather-exposed materials.

The area surveyed at present is Iberia. Time
series data in two formats for 113 sites are
stored in the CD. They may be accessed directly,
or interactively via an user friendly HTML
interface.
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Locations
( Las Palmas and Casablanca)
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Data preparation - IClimatic Data

• The data set must be both
• representative of long term conditions
• coherent in time and space for the entire area
• cross-correlated as regards irradiation,
  temperature and humidity
• This constrains very much the possible
  approaches.
• The approach taken was to use ground data only
  and solar irradiation data H was estimated from
  sunshine hours S.

Long term data from Portugal, Spain and some
other territories was obtained, quality
controlled and additional parameters were
estimated.

• Data sources were mainly publications regarding
  1961-90 records of the classic meteorological
  networks of ground stations, by
• the Spanish national meteorological service
  (INM)
• the Portuguese national meteorological service
  (IM)
• the Catalan Energy Agency (ICAEN)

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Data preparation - IClimatic Data

• The Suehrcke methodology was used H
  (S/S0)1/2 Hcs
• In comparison with the better known Angstrom
  linear regression H a b (S/S0) H0
• it features similar bias and lower rms errors
• it does not need preliminar studies to find
  coeffs. a and b
• it does not need geographical extrapolation of a
  and b values
• requires clear sky irradiation Hcs estimates
• The European Solar Radiation Atlas clear sky
  irradiation model was used. It requires estimates
  of only one parameter, TL2, the Linke turbidity
  coeff. for airmass 2. Following validation
  studies, seasonal profiles of TL2 were assigned
  for the region surveyed.
• The irradiation estimates were verified and
  cross-checked with ground data and remote sensing
  data with good results.

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Data preparation - IIAssembling Typical Years

• A variation of the technique of the "Typical
  Reference Year approach is used.
• Classic Typical Years are assembled from a pool
  of recorded data.
• But records of long time series hourly data are
  very rare indeed, especially if solar irradiation
  is involved. Also they span small periods, and
  there are other problems.
• Typical Years can also be assembled using
  statistical and stochastic models of
  the meteorological time series.
• They require as input only long term monthly data
  (and as explained before).
• Well known published statistical and stochastic
  models, tuned for the region surveyed, were used
  
• a cascade of models leads from monthly to daily
  to hourly values
• daily and hourly variability are included
• diffuse irradiation is estimated with models
  tunned for Iberia
• cross-correlations for solar irradiation and
  thermal amplitude are included
• wind speed patterns are very sensitive to
  location and microclimates (including urban) the
  series provided should be considered only as
  indicative.

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Data preparation - IIIAssembling Extreme Years

• As a bonus from the procedures used, Extreme
  Years are provided, for conditions departing from
  the long term behaviour, enabling users to
  address issues like
• interannual variability
• climate change
• in general, sizing for extreme conditions during
  system lifetime
• For systems sensitive to both solar irradiation
  and ambient temperature, the joint probability of
  occurrence of monthly mean values of these
  parameters should be considered. As there are
  many system types it is impracticable to supply a
  huge number of extreme years, and some choice
  must be made.
• In the current product version a pair of high /
  low threshold Extreme Years is provided for each
  site
• equal system sensitivity to solar irradiation
  and temperature is assumed
• joint 25-year return period monthly means of
  higher / lower values were estimated (in a
  studied proportion to the standard deviations of
  the monthly values)

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Data Formats

• The data is supplied in TRNSYS Type 89 compatible
  format

The data is supplied as well in the European TRY
format. An user friendly HTML interface is also
provided to facilitate examination of the
climatology and retrieving of Typical Year and
Extreme Year data
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In Conclusion...

• Thus the TRNSCLIMA main features are

• no missing data or spurious values
• additional parameters (e.g. direct/diffuse
  irradiation components)
• monthly statistics exactly match long term
  climatic values
• reproduces those weather features that the
  systems really feel
• both Typical and Extreme years, useful for
  design and sizing
• high spatial resolution (indeed, for the
  largest majority of the sites in the data bank
  there is simply no alternative adequate hourly
  data source!)
• easy access, high compatibility
• Extension to other geographical areas is in view.

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FOR FURTHER INFORMATION
E-mail trnsys_at_aiguasol.com http//www.aiguas
ol.com Address AIGUASOL ENGINYERIA C/ Palau,
4, 2n 2a E-08002 BARCELONA Spain Tel 34
93 342 47 55 Fax [phone]
_at_
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