Homepage started: February 20, 2021.
Last update: July 8, 2022.

Climate & Ecology

Gerd A. Esser

Dr. rer. nat., University Professor
for
Systems Ecology, Geo-Ecology and Modelling
Justus-Liebig-University
Giessen, Germany

Models of global biogeochemical cycles.

The models of biogeochemical cycles were developed in the working groups of Gerd Esser at the Universitiy of Osnabrück (Germany), at the International Institute for Applied Systems Analysis (IIASA) at Laxenburg (Austria), and at the Justus-Liebig-University of Gießen (Germany).

These high-resolution models (geographical resolution 0.5 deg. latitude and longitude, time resolution one month or less) include the cycles of carbon, nitrogen, or water.

The following documentations of the models are available for download as pdf-files. The documentations are protected by copyright. The material may be cited or otherwise freely used for scientific purposes with full citation of authorship and sources:

HRBM: High Resolution Biosphere Model (carbon cycle)

NCIM: Nitrogen Carbon Interaction Model (coupled nitrogen and carbon cycles)

GIWACOM: Giessen Global Generic Water Conductance Model (coupled water and carbon cycles)

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Useful results from the carbon cycle research

Here you find some useful results with respect to the present discussions about the use of wood or wood products for energy production. And an analysis of the role of tree planting and afforestation to compensate for the excess emissions of carbon dioxide.

You may download the text, cite it, or use it otherwise. But always cite the Author:

Burning of Wood Products and Reforestation Climate neutral? — An Analysis.

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Trends of observed temperatures.

Monthly observed station data for many stations worldwide were used to calculate annual mean temperature for every year of the available observational period of any station (data basis: Deutscher Wetterdienst, DWD, CDC-OpenData area, long-term monthly temperatures).

Linear trends of annual temperatures were calculated for each station, separately for the periods before 1980 AD and after 1980 AD, using nonlinear least squares methods. The error estimates are obtained from the variance/covariance matrix and may be considered as qualitative estimates of the fit (for detailes see GNUPLOT graphics program).

Most station records are short, beginning in the middle of the 20th century, and frequently years are missing. Longer records are only provided by most japanese stations, Moscow (Russia), and Hohenpeißenberg (Bavaria).

In the tables below you will find the results for stations worldwide, sorted for continents and countries. The tables may be downloaded (pdf-files). The material may be cited or otherwise freely used for scientific purposes with full citation of authorship and sources:

As can easily be recognized there is a strong increase in the temperature slope after the year 1980, for nearly every station. For Europe, the increase in temperature may be summarized since 1980 to about 0.5 °C every ten years. This results in a temperature rise of about 2 °C since 1980 as average. Some stations show a much higher increase, for example Klagenfurt (Austria). Generally, the increase is highest in higher latitudes, i.e. closer to the pole, were it can be up to or more than 1 °C for ten years, for example Barrow (Alaska).

In the period before the year 1980 the picture is non-uniform. Small but diverging trends are observed. Several stations show negative trends before 1980, for one example see Thessaloniki (Greece). If we look a little bit closer to the data of stations with long-term records (see graphics below), the temperature-reduction between 1950 and 1980, if present, seems to be a short-term variance in the long-term trend (compare below: Hohenpeißenberg and, alternatively, Hohenpeißenberg-2). The long-term data before and after 1980 show the well-known "hockeystick" shape (IPCC working group I report, 2013). All graphics in this text may be downloaded and cited or otherwise used for scientific purposes with full citation of authorship and sources:

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Aridity Index.

The components of the climate and weather systems which contribute to the ecological aridity of a location include: the amount of precipitation in relation to the temperature, the number of dry months, the precipitation deficit during a dry month, the distribution of precipitation over the year, and others. All these components vary in time and are subject to climate change in a different way.

This makes it difficult to compare the ecological aridity of different locations or the change in time. An "aridity index" is suggested which considers all the different components which contribute to the ecological aridity. This "aridity index" characterizes the ecological aridity of a location at a given time by just one figure: 0 percent to 100 percent arditiy.

How is the aridity index calculated?

Application of the aridity index.

The aridity index may be used to calculate time-series of the aridity to document climate change. It is also useful for the documentation of spatial gradients of aridity along geographic transections or for the characterization of climatic conditions of habitats.

With a global data set of monthly mean temperatures and monthly sums of precipitation and a resolution of 0.5 degrees longitude and latitude a high resolution global map of the aridity index was produced:

Global Map of the Aridity Index

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