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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
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Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
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The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
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Block diagrams serve as a visual representation of the input-output relationships within a system. An illustrative example is a heating system, where the set temperature activates the furnace to warm the room to the desired level. Block diagrams are versatile, modeling linear systems through Laplace transform variables and nonlinear systems using time domain variables.
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Blocking representation in the ERA-Interim driven EURO-CORDEX RCMs.

Martin Wolfgang Jury1, Sixto Herrera2, José Manuel Gutiérrez3

  • 11Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria.

Climate Dynamics
|April 9, 2019
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Summary

Regional Climate Models (RCMs) struggle to accurately simulate atmospheric blocking events, impacting European temperature and precipitation. Biases in non-blocking conditions largely drive overall model error.

Keywords:
Atmospheric blockingEURO-CORDEXPrecipitation biasReanalysis drivenRegional climate modelsTemperature bias

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Area of Science:

  • Climate Science
  • Atmospheric Science
  • Meteorology

Background:

  • Regional Climate Models (RCMs) offer improved climate simulations over General Circulation Models (GCMs).
  • The representation of large-scale atmospheric phenomena, such as atmospheric blocking, in RCMs remains under-investigated.
  • Atmospheric blocking significantly influences European weather patterns, affecting temperature and precipitation.

Purpose of the Study:

  • To evaluate the capability of RCMs to simulate atmospheric blocking events.
  • To analyze the impact of blocking representation on European 2-m air temperature (TAS) and precipitation rate (PR) biases.
  • To compare blocking simulation performance across different RCM configurations and resolutions.

Main Methods:

  • Utilized five EURO-CORDEX ensemble RCMs and three WRF models, all driven by ERA-Interim reanalysis (1981-2010).
  • Detected and allocated atmospheric blocking systems to three Euro-Atlantic sectors for anomaly analysis.
  • Compared RCM-simulated blocking with driving reanalysis data and analyzed associated TAS and PR anomalies.

Main Results:

  • Most RCMs underestimated atmospheric blocking frequency compared to the driving reanalysis.
  • Stronger nudging in RCMs reduced blocking misdetection, while higher resolution did not improve blocking representation.
  • All RCMs reproduced the fundamental anomaly structures for TAS and PR associated with blocking.

Conclusions:

  • RCMs exhibit misrepresentation of atmospheric blocking, with underestimation being common.
  • The primary source of overall model bias stems from surface parameter biases during non-blocking situations.
  • While blocking biases have a secondary influence, they can be significant when blocking is strongly underestimated.