The Earth system Scale dependence, Feedbacks and Global Change

ESS 20306

Practicals, excursions and exercises course: 2010-2011

Part 1

Bart Kruijt (Co-ordinator)1) Laurens Ganzeveld1)

Pavel Kabat1) Marja Duizendstraal2)

Hans Fransen2)

1) Earth System Science and Climate Change Group,

WUR 2)

Central Library, WUR

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Table of contents Part 1

1- introduction and course objectives 4 2- Administrative and marking 5 3- course schedule 6 4- opening practical: what do you already know? 7 5- Daisyworld 9 6- The Ocean-Atmosphere system 13 7- Carbon cycle research in practice: Gas exchange measurements 19 8- Study guide 23

In part 2 (forthcoming)

9- Final project: build your own earth system model a. Introduction and checklist procedure b. Information searching: literature c. Information searching: datasets and databases d. Introduction to the SMART modelling environment e. Examples and suggestions for earth system models

10- Questions and answers from the book (2nd edition) 11- Example exam exercises

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1 - Introduction and course objectives Introduction The components of the Earth system, the atmosphere, hydrosphere, lithosphere, cryosphere and biosphere are all intricately linked through processes and feedbacks, such as the carbon cycle, that operate at different spatial scales and time scales in response to the external forcing by the Sun and Moon. What does it mean if we say that the Earth is a stable place, that it is in equilibrium? Why and when does stability occur, how variable has the Earth system been over geological timescales and how vulnerable is it, for example in view of current disturbances by human activities? This course will introduce the systems approach, oversee the most important components of the Earth system and, in particular, increase the understanding of process interactions, disturbances and the importance of feedbacks, occurring at a multitude of time- and spatial scales. You will learn how data are collected to improve understanding of the Earth system. It will place current climate and global change and Biodiversity loss and the role of our modern society in a broader context. It will become clear why current global change is extremely urgent even though Earth has experienced big changes before, and you will be introduced to what should be done to limit Climate Change (mitigation) and what is being done to prepare for change (adaptation).

The course will integrate knowledge from preceding BBW courses (atmosphere, chemical interactions, geology and soils), introduce new components of the Earth system, spanning the 4.5 billion years of Earth history and looking into the future but focus on current functioning and the interaction between all components. Starting from what you already know, through lectures, an excursion, simple modeling and practical exercises we will help to link these elements together. The final part of the course is dedicated to building your own concept of an Earth system model. For this, you will be trained to define and narrow down your research questions and objectives, gathering information from different data sources to finally translate this information into a really functioning model.

Objectives At the end of this course, you are expected to: understand and apply the systems approach in the context of the Earth system

and Global Change issues; have knowledge of the major Earth compartments and associated physical and

biological processes; recognize and understand feedbacks and the spatial and temporal scales at

which Earth system components and Global Change operate; have insight into the regulation of environmental processes by biosphere -

hydrosphere - atmosphere feedback systems; be able to distinguish between natural and anthropogenic factors affecting the

climate system. have knowledge of the various ways data are collected in Earth Systems science,

and how this is applied in models. be able to formulate a conceptual and a simple computer model of components of

the earth system be able to generate focused questions, find the relevant information and feed

these into a model concept.

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2 - Administrative information and marking criteria Course timing Period 2 (1-11-2010 till 23-12-2010) second year BBW Classes ( C ) start 13:30 and end 15:15 (on 23 November until 17:15)

o Practicals (SW and PI) also start 13:30 but end 17:15

Teaching staff Bart Kruijt, Atlas B.617, tel. (0317-4)86440, bart.kruijt@wur.nl (CO-ORDINATOR)

Prof. Pavel Kabat, Atlas A.613, pavel.kabat@wur.nl Laurens Ganzeveld, Atlas B.611, laurens.ganzeveld@wur.nl Marja Duizendstraal, Central Library, Forum, marja.duizendstraal@wur.nl Hans Fransen, Central Library, Forum, hans.fransen@wur.nl Robbert Biesbroek, Obbe Tuinenburg and Maleen Vermeulen, ESS, modeling Eef Velthorst, Jan Elbers and Wilma Jans, ESS, laboratory assistance

Documentation 1) Book: L.R. Kump, J.F. Kasting, R.G. Crane. 2004. The Earth System (second edition or third edition). Pearson Education, Inc. Upper Saddle River, NJ, USA. ISBN 0-13-142059-3 buy at: WUR shop or internet (Amazon.com) see: ttp://vig.prenhall.com/catalog/academic/product/0,1144,0131420593,00.html 2) This manual; Powerpoints and pdfs at Eduweb

Assumed knowledge All previous BBW courses. We will skip the following chapters from the book, assuming you already have this knowledge and/or get it later during the curriculum: - Ch 3 Global energy balance: The greenhouse effect - Ch 4 The atmospheric circulation system

Marking criteria The final mark will be determined by the results of the last two weeks practical (1/6) and the Information literature test (1/6) and the final exam (2/3). All marks have to be at least a 5 (five). ATTENDENCE TO ALL PRACTICALS IS OBLIGATORY.

Book and lectures for final exam You are expected to learn the contents of the book, the lectures and the theory and skills of the practicals. Refer to chapter 9 below for a more detailed study guide. Note that we can indicate changed requirements during the lectures!

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3 - Course schedule (Changes possible!) Date C SW PI EE room Lecturer subject

maandag 1 november 2010 2 C85 (geb 531 Zodiac)

Kruijt + Kabat +Ganzeveld

Introduction, then Ch 1 Global Change

dinsdag 2 november 2010 4 P631,635 Kruijt + Ganzeveld+ Vermeulen

Practical conceptual modelling

woensdag 3 november 2010 2 C218 Ganzeveld Ch 2 Daisyworld: An introduction to systemsdonderdag 4 november 2010 4 PC25,26 Ganzeveld +

BiesbroekDaisyworld modelling

vrijdag 5 november 2010 2 C217 Ganzeveld Ch 5 The circulation of the oceanszaterdag 6 november 2010

zondag 7 november 2010maandag 8 november 2010 2 C85 (geb 531

Zodiac)Ganzeveld The atmosphere - ocean system (Ch 6 old edition /

photocopies)dinsdag 9 november 2010 4 PC25,26 Ganzeveld +

BiesbroekCh 6 Modeling practical

woensdag 10 november 2010 2 C218 Kruijt Ch 7 and 8: tectonics and carbon cycle, ADD large-scale hydrological cycles (eg Amazon)

donderdag 11 november 2010 4 PC25,26 Ganzeveld+ Janssen continuation of modeling pratical

vrijdag 12 november 2010 2 C221 Kruijt Ch 8 and 9: biological part C cycle, role of biotazaterdag 13 november 2010

zondag 14 november 2010maandag 15 november 2010 2 C85 Ganzeveld (Ch 17) Ozone and reactive chemistry in the

atmospheredinsdag 16 november 2010 2 C214

woensdag 17 november 2010 2 C218 Kruijt Ch 10, origin of earth&life, Ch 11& Ch 13 Effect of life on the atmosphere: The rise of oxygen and ozone; Biodiversity through earth history

donderdag 18 november 2010 4 P832, P836 Kruijt + Velthorst + Elbers+Jans

Practical: gas exchange mesurement. Two shifts!

vrijdag 19 november 2010 C217 OPTIONALzaterdag 20 november 2010

zondag 21 november 2010maandag 22 november 2010 2 C85 Ganzeveld Ch 12, 14: long-term climate variability

dinsdag 23 november 2010 2 2 C214 Kabat (Ch 16) Global warming and adaptation (+ additional material! )

woensdag 24 november 2010 2 C218 Ganzeveld Ch 12, 14: long-term climate variabilitydonderdag 25 november 2010 2 C217 Kruijt Ch 15, ch 19 Short-term climate variability and future

climatevrijdag 26 november 2010 4 PC25,26, C85 Kruijt + Ganzeveld +

Tuinenburgintroduction modelling project and SMART

zaterdag 27 november 2010zondag 28 november 2010

maandag 29 november 2010 4 (C85,) PC25,26 Duizendstraal + Fransen

Intro Information literacy Two shifts 2x2 groups

dinsdag 30 november 2010 4 PC25,26 Duizendstraal + Fransen

assignment Information Literacy

woensdag 1 december 2010 4 (C218,) PC25, 26 Fransen + Duizendstraal

Assignment & Test Information Literacy

donderdag 2 december 2010 4 PC 25, 26 Kruijt + Tuinenburg introduction data sets; practice with SMART, set-up project and questions

vrijdag 3 december 2010 PC 25, 26 OPTIONALzaterdag 4 december 2010

zondag 5 december 2010maandag 6 december 2010 4 (C217,) PC25, 26 Ganzeveld +

Tuinenburgmodel set-up

dinsdag 7 december 2010 4 PC25,26 Kruijt + Tuinenburg + Van Vliet

Build ESS model

woensdag 8 december 2010 4 PC25,26 Kruijt + Tuinenburg + Van Vliet

Build ESS model

donderdag 9 december 2010 4 (C8,) PC25,26 (C8)

Kruijt + Tuinenburg + Van Vliet

Build ESS model

vrijdag 10 december 2010 4 PC25,26 (C217) Kruijt + Tuinenburg + Van Vliet

model presentations and evaluation

zaterdag 11 december 2010zondag 12 december 2010

maandag 13 december 2010dinsdag 14 december 2010 study week

woensdag 15 december 2010 P635 question timedonderdag 16 december 2010

vrijdag 17 december 2010zaterdag 18 december 2010

zondag 19 december 2010maandag 20 december 2010

dinsdag 21 december 2010 C63 (Leeuwenborgh)

Kruijt Exam 14:00-17:00

woensdag 22 december 2010donderdag 23 december 2010

vrijdag 24 december 2010

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4 - Opening practical: what do you already know?

Introduction You have by now followed courses in a broad range of subjects that all have something to do with the earth system. In this course, you will learn how this all fits into an even bigger picture and you will learn about climate change. In this first practical we would like to ask you to show to us what you already know about the earth system, and especially how you think it all links together.

How do you think the earth system works? Some of you may have a lot of ideas yourself. This is your chance to show us your own theory of everything.. well, of the earth..!

If you do not have a theory ready, then think of one of the following questions: - what controls the amount of carbon in the oceans/atmosphere/on land? - What controls the atmospheric oxygen concentration, or that in the ocean? - Similar questions for other gases, or water, temperature, vegetation or

animals - Which are the interactions between polar ice and climate? - Which might be the effect of continental drift on life? - How would sun, moon and planets affect the climate/biosphere? - Which might be the role of earthquakes and tsunamis in the water cycle? - What controls the (agricultural, forest) productivity of a region, country,

continent? - Which elements of the earth system affect a wealthy economy; and vice versa?

Objective After this practical you will have made your conceptual view on the earth system more explicit. During the rest of the course you can look back at this model and find out what you did not yet know, and possibly you can use the model developed today towards the end of the course when you will build a more quantitative model.

We ask you to think of a question and give your answer. This does not have to be the correct answer, as long as it shows your logic and reflects what you (think) you know. Be imaginative! During the rest of course there is enough time to learn about the real systems!

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Air temperature

Soil moisture

Evaporation

Soil temperature

Soil heating

radiation clouds

weather

Ground water

rainfall

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Procedure 1) form small groups of preferably three persons. If you want you can also work out your own idea, alone, or work in a larger group, as long as everyone has a clear task. Find lab table space to work on.

2) formulate a question or hypothesis

3) show your theory in one of these forms: - a box-and-arrow model or flow diagram(simulating the state of quantities and

flows) - a simulation game (simulating the path of particles or objects, or simulating

patterns) - a map or series of maps (show how spatial patterns change, or showing

spatial connections) - if you have another idea, that is fine, as long as you show logic and address a

clear question.

4) write a brief report (one page maximum), describing your model. We will collect these reports, and also your models (if possible!).

5) prepare a short presentation about your model to the whole group (end of the afternoon). Address: question, hypothesis, how does your model work, what does it predict, and: how could we test this model?.

In general: - include links between different parts of the earth system, make the model

interdisciplinary - include one or more feed-back loops - if possible indicate the relative importance of states, flows and effects - include the factor TIME: which processes are slow and which are fast

Material You can use the following materials: - large flip-over sheets - paper cards - felt pens. - paint and paint brushes - tape - cotton thread - dice (for a game) - ANY OTHER MATERIALS YOU BRING YOURSELF

Time You have one afternoon for this, including presentations, that is 2.5 hours work plus 1 hour group presentations.

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5 - Daisyworld Daisyworld is a simulation of a hypothetical planet orbiting around a sun whose temperature and radiation is slowly increasing. Daisyworld was introduced by James Lovelock and Andrew Watson to illustrate the plausibility of the Gaia hypothesis1 in a paper published in 1983. The simulated planet is seeded with two different species of Daisies as its only life form: black and white Daisies. White daisies have white flowers which reflect light, and the other species has black flowers that absorb light. Both species have the same growth curve (that is, their reproduction rate is the same function of temperature) but the black Daisies are themselves warmer than the White daisies and bare earth. A planet dominated by white Daisy cover is cooler than one with more black ones. Daisyworld simulation is an analogy2 which shows that life which is adapted to certain kind of environmental conditions regulates its own environment toward living conditions which are suitable for life. Life has to do so because otherwise the species exposed to average conditions could not live at all but would die away if they could not affect their own living conditions toward better conditions. The point here is that if this effect spreads to the environment, like in the Daisyworld example, or if the effect comes via affecting the environment, then life really regulates the living conditions also in our own planet Earth too toward what is beneficial to life. (Source: Wikipedia) Studying the hypothetical planet Daisyworld will show you that planetary climate systems, like that of system Earth, are not passive and respond to internal or external influences with the response being dependent on role of negative or positive feedback loops. Positive feedback loops will strengthen the response of the system to an internal or external influence whereas a negative feedback loop will dampen the response of the system to the influence. Examples of internal influences are perturbations, which is temporary disturbance of the system, such as volcanic eruptions or increases in the deposition of mineral dust to the oceans whereas an example of an external influence, a forcing, defined as a more persistent disturbance of the system, is the change in solar luminosity. It is interesting to note that, also referring to criticism being raised after the Gaia hypothesis was first published, that natural systems can be selfregulating on a global scale without the need for intelligent intervention. Many scientists criticized the approach being teleological; a belief that all things have a predetermined purpose. Lovelock has firmly opposed most of that criticism stating that "Nowhere in our writings do we express the idea that planetary selfregulation is purposeful, or involves foresight or planning by the biota." (Lovelock, J. E. 1990).

1 The Gaia hypothesis is an ecological hypothesis that proposes that living and nonliving parts of the

earth are a complex interacting system that can be thought of as a single organism. Named after the Greek earth goddess, this hypothesis postulates that all living things have a regulatory effect on the Earth's environment that promotes life overall.

2 Analogy expressed the process of transferring information from a particular subject (the analogue or

source) to another particular subject (the target). For example, Niels Bohr's model of the atom made an analogy between the atom and the solar system.

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Exercises

1. Read the original paper by Watson and Lovelock (1983) (you can find the pdf in subdirectory

/manual and extra files). You can check some of the equations but it is more essential to

get the main takehome message focusing on section 3, steady state behaviour, section 4, removing the negative feedback and 5, relevance to the Earth. Try to summarize the main conclusions of this paper and, possibly, also write down some of the features that you do not completely understand. Hopefully, the next exercises might help in understanding the key features of Daisyworld

2. What are the main input parameters needed to calculate the cover by Daisies and other

Daisyworld parameters?

In order to study how Daisyworld functions we have made a model to study Daisyworld using the programming tool Matlab. This is software being used in some of the Earth system courses such as the MSc course Earth system modeling (ESS32306). However, here we dont want you yet to get involved too deeply in how to program models like Daisyworld but rather want you to focus on using this model to study the role of various parameters in this selfregulating mechanism of system Earth. Consequently, you will run the model only changing the input parameters to study how this affects the system. The input parameters are defined in an Excel spreadsheet being read by the Matlab code.

Copy the spreadsheet DaisyWorldparameters.xls from the directory: w:\Student\Shares\Omgeving\ESS20306\practicals\DaisyWorld (copying them to the desktop or some directory that you prefer to use for saving these files). You also have to

copy two Matlab files: DaisyWorld.m and DaisiesversusS.m (to the same directory where you put the Excel file!). We will do first a number of exercises with Daisyworld.m. In order to use this script you have to open Matlab by clicking on the Matlab icon, then you

go to the top toolbar, click on File and then on Open.. and select the location where you

can find the file so that is opened by Matlab.

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You can now actually check the Matlab code if you like but for the exercises you only need

to run the model by clicking on the Run icon on the top toolbar of the Matlab Editor.

The first time you will run the model the following message will popup and simply click on ok to confirm that the path where the model script is found is recognized by Matlab;

Running the model will include reading the Excel file DaisyWorldparameters.xls and you can conduct the following exercises changing the parameter values in the spreadsheet.

3. Try to predict what would happen when there are initially no daisies at the planet (just a few

seeds). What does this imply for the climate on an earth without life? 4. Run the model and discuss the results. If you want to put the figures that have been

produced by Matlab into this document to illustrate your answers, go to upper toolbar on

top of the Figure frame and click on Edit and then on Copy figure. You can now simply paste the figure here.

5. Explore the behavior of the Daisyworld model (predict first, then run the model) by changing

(a) the albedos of the Daisies. Change e.g. from the current values of 0.6 to higher and to lower values, smaller than the albedo of bare soil. (b) the incoming solar radiation. (c) the optimum growing temperatures of the daisies. (d) the growing range of the daisies. What are the effects of these changes on the area covered by Daisies and the planets

temperature? 6. We are interested in the equilibrium behavior of the planet as a function of the solar

luminosity. Predict what would happen with the global temperature and number of white Daisies on the planet when the solar radiation increases from zero?

7. Check your predictions with the Matlab routine DaisiesversusS.m. In order to do so you have to open this Matlab script, similar to how you opened Daisyworld.m (see instructions Exercise 2), and run the script.

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8. Explore the equilibrium behavior of the planet Daisyworld and perform the above described

experiments (First predict, then run the model). 9. How will the studied feedbacks including the biological and physical (and chemical)

processes work in the real world (think about scales, other processes involved, for example, those relevant to the hydrological cycle; transpiration, clouds, precipitation).

10. Can you think of any real world organisms that regulate their own environmental conditions

to favor their growth (not necessarily on a planetary scale)? How do they do that? And what effects does that have on the local climate?

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6 The Ocean-Atmosphere system The ocean is a crucial component of system Earth providing a huge reservoir for the storage of energy, water and matter, e.g., carbon. In the lecture on ocean circulation you have learned about the processes that control surface and deep ocean circulation and its relevance in the redistribution of energy between the Equator and the Poles, determining to a large extent the different climates experienced in different regions of the world. A good understanding of the oceans is also crucial to study potential future climate change recognizing the fact that fast responses in the atmosphere will be modulated by the relative slow response of the oceans. You could actually make a firstorder estimate of the response time of the oceans estimating the amount of water in the oceans, the heat capacity of water and an estimate of the input of heat into the ocean. The role of the ocean energy transport and storage in climate change will actually be studied in this practicals using a relatively simple atmosphereocean model to estimate the global temperature increase due to a change in radiative forcing3 (Q) caused by the increase of atmospheric CO2. The heat capacity of the ocean is much larger than that of the atmosphere. Therefore we may neglect the amount of energy that is used to heat up the atmosphere and assume that Q is going totally to the surface layer of the ocean. The ocean is divided into two parts, the well mixed surface layer, having a constant depth of about 100m and uniform temperature, and a deep ocean being represented by 15 layers. Due to Q, the surface layer temperature will increase with an amount of T and due to this increase there will be a heat flux from the mixed layer into the atmosphere and deep ocean which will also warm up. The heat flux into the atmosphere is due to e.g. the an increase in longwave radiation and decrease in albedo due to the melting of ice. The heat transport from the mixed layer to the deep ocean and further on deeper into the deep ocean is assumed to be due to diffusion and proportional to the temperature gradient and a diffusion coefficient K. Without studying in detail the way this model has been setup you will conduct some analysis with the model to study the role of the ocean in climate change modifying some of the input parameters. Similar to the Daisyworld exercises, the values of these input

parameters are defined in a spreadsheet that can be found in the subdirectory model

codes and input files/.

3 In climate science, radiative forcing is (loosely) defined as the change in net irradiance at the

tropopause. "Net irradiance" is the difference between the incoming radiation energy and the outgoing radiation energy in a given climate system and is thus measured in Watts per square meter. The change is computed based on "unperturbed" values; the IPCC measures change relative to the year 1750. A positive forcing (more incoming energy) tends to warm the system, while a negative forcing (more outgoing energy) tends to cool it. Possible sources of radiative forcing are changes in insolation (incident solar radiation), or the effects of variations in the amount of radiatively active gases and aerosols present (source Wikipedia).

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Exercises

1. Estimate the amount of water in the ocean (being creative on estimating the dimensions of

this big bathtub). If we use a specific heat capacity of 4200 J/kg/K and a density of 1000 kg/m3 how much time will it take to warm up the ocean by 1K if we have an input of heat of 1 W m2? You can compare this with the atmosphere which has a specific heat capacity of ~700 J/kg/K an taking an average density of the troposphere (lower 1015km) of ~0.1 kg/m3.

2. The model was implemented in Matlab (file OceanAtmosphereModel.m in subdirectory model codes and input files/). Run the model and discuss the results checking the

changes in the mixed layer and the deep ocean temperature (you will see a vertical profile of the deep ocean temperature changing in time) as a function of the imposed climate forcing.

3. Study how the results are dependent on the assumptions on the ratio of the radiative forcing

and temperature change (Q/T), called climate sensitivity () by choosing different values for T2x and discuss shortly the results. There is still a lot of uncertainty about the climate sensitivity. One assumes that the climate sensitivity parameter is between 0.5 and 4 W/m2/K.

4. Study how the results change if the heat storage of the ocean is neglected. You could do

this by changing the heat capacity of the ocean (setting it to zero) but this doesnt seem to be an appropriate modification since an amount of water can simply store an amount of energy. Instead you should do this analysis by reducing the heat transport into the deep ocean. You can also check what happens if the heat transport in the ocean is very fast. Discuss shortly the results.

5. In the model we have added the option to study the response to an transient as well as an

abrupt change of the forcing. By changing the value for the parameter experiment in the

spreadsheet from 1 to 2 you can analyze the impact of assuming that after 2000 there is no further change in the forcing due to a stabilization of the atmospheric CO2

concentrations. Setting the parameter experiment at the value 3 results in a simulation of an abrupt change in the forcing to Q2x reflecting a decrease in the atmosphere CO2 concentrations to preindustrial levels. Discuss the results of the 2 different experiments. As always, first predict before running the models.

6. Discuss how the temperature change of the ocean could influence the atmospheric CO2

concentration. If there is a feedback interaction, is it positive or negative?.

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The DMS feedback (also know as CLAW feedback)

The CLAW hypothesis proposes a feedback loop that operates between ocean ecosystems and the Earth's climate. The hypothesis specifically proposes that particular phytoplankton that produce dimethyl sulfide (DMS) are responsive to variations in climate forcing, and that these responses lead to a negative feedback loop that acts to stabilize the temperature of the Earth's atmosphere. The CLAW hypothesis was originally proposed by Robert Charlson, James Lovelock, Meinrat Andreae and Stephen Warren, and takes its acronym from the first letter of their surnames.

The hypothesis describes a feedback loop that begins with an increase in the available energy from the sun acting to increase the growth rates of phytoplankton by either a physiological effect (due to elevated temperature) or enhanced photosynthesis (due to increased solar irradiance). Certain phytoplankton synthesize dimethylsulfoniopropionate (DMSP), and their enhanced growth increases its production. In turn, this leads to an increase in the concentration of its breakdown product, dimethyl sulfide (DMS), first in seawater, and then in the atmosphere. DMS is oxidized in the atmosphere to form sulfur dioxide, and this leads to the production of sulfate aerosols. These aerosols act as cloud condensation nuclei and increase cloud droplet number. This acts to increase cloud albedo, leading to greater reflection of incident sunlight, and a decrease in the forcing that initiated this chain of events. The figure below shows a summarizing schematic diagram. Note that the feedback loop can operate in reverse, such that a decline in solar energy leads to reduced cloud cover and thus to an increase in the amount of solar energy reaching the Earth's surface.

A significant feature of the chain of interactions described above is that it creates a negative feedback loop, whereby a change to the climate system (increased/decreased solar input) is ultimately counteracted and damped by the loop. As such, the CLAW hypothesis posits an example of planetary-scale homeostasis, consistent with the Gaia hypothesis framed by one of the original authors of the CLAW hypothesis, James Lovelock.

Figure 1: schematic diagram of the DMS-feedback

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The model

In this practical, we use a simple model of the DMS-feedback to demonstrate its effect. In the model, all components of the feedback are included in a simplified way, which makes the model computationally efficient and therefore easy to analyze. It differs from a complex earth system model in three ways: it is one-dimensional, so horizontal transport of water and air is not taken into account and vertical transport only implicitly (an average value for the whole atmosphere is assumed), it contains an ecosystem model that contains only 2 plankton species and many processes that may influence the feedback are left out, such as vertical mixing of the upper ocean. Still, it represents the state-of-art of how we at this moment think the feedback works, but future observations may lead to different thoughts. .

Figure 2: DMS-model structure with the ecosystem variables (in squares), the sulphur species DMS and DMSP (in circles) and the atmospheric part of the feedback (in octagons)

In essence the model consists of an ecosystem model coupled with chemistry/physics feedback. The model consist of 5 differential equations: 3 of them represent the dynamics of the ecosystem and 2 of them the production and release of DMS and its precursor DMSP by the plankton. There are 2 plankton species, Phytoplankton (P) and Zooplankton (Z), a prey and a predator species, respectively. The third equation represents nitrogen (N), which is dissolved in the water and is taken up by the Phytoplankton. When plankton dies, it is returned to the ecosystem as nitrogen. In this way, the total amount of nitrogen in the system is conserved.

This ecosystem is comparable to one in which there is grass (nitrogen), which is eaten by rabbits (phytoplankton) which are on their turn eaten by foxes (zooplankton), all of which influence the presence of each other and the state of the ecosystem. This interdepence causes the dynamics of the ecosystem to move to one stable equilibrium, but on its way to this equilibrium from the initial conditions it shows some cyclic behavior.

Both plankton species produce (a precursor to) DMS, which consequently influences the growth of the plankton by modifying cloud albedo and incoming solar radiation

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and in turn plankton growth. With this model, this effect and the consequences of this feedback will be demonstrated.

Exercises

1. Read the following sections of the original paper by Charlson et al. (1987) (you can find the pdf in subdirectory /manual and extra files): abstract & introduction, global climate and DMS emission geophysiology and homeostasis future research needs Hopefully, the next exercises might help in understanding the key features of the DMS-feedback.

2. Test run, open Matlab and open file: DMS_test.m. fixed parameters, evolution of the system in time: NPZ & DMS variables Run the model and describe what happens. After finishing the model run, Matlab creates two plots. What do these show? Has the model reached equilibrium? If not, increase end time (te in DMS_test.xls (save before running the model!)) and run the model again. If necessary, repeat this step until the model reaches equilibrium values. Is sulphur a conserved variable? Does this make sense? Why (not)? Why is it logical that nitrogen is a conserved variable in the model ecosystem? Can you think of circumstances under which it is not conserved?

3. Sensitivity analysis: biology, chemistry, physics In this step, you will analyze the sensitivity of the model to various parameters. The Matlab program DMS_sensitivity.m will calculate equilibrium values of the models variables for parameter values that you can adjust yourself. The calculation may take a while. Figure 1 will show you the dynamics of the ecosystem, leading to a point in time at which N, P and Z do not change anymore and equilibrium is reached. The program does this calculation automatically for many values of the parameter that you selected in DMS_sensitivity.xls. At the end, you will see that in Figure 2 for each value of the chosen parameter, the equilibrium values of the models variables are plotted. Test the sensitivity of the model by performing a sensitivity analysis of the model for the following parameters:

Biology-related a. k3: the grazing (predation) rate of Z on P (m3 mgN-1 day-1), set ps = 1 Which fundamental change can be seen in the ecosystem when increasing this parameter? What has happened to the state of the ecosystem and why? How can you explain that Zooplankton has an optimum around k3=0.005?

Chemistry-related b. m3: DMSP-DMS conversion rate (d-1), set ps = 2 Describe what happens. Why doesnt the ecosystem state change? How does this chemical term affect the strength of the feedback?

Physics-related c. k8: ratio between DMS-flux and aerosol concentration (m2d mgS-1), set ps = 3 What happens to the DMS-flux (mind the scale of the y-axis!) and what to the cloud albedo? Please explain. How does this physical parameter affect the strength of the feedback?

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Additional question: so far the model only includes ecosystem dynamics. What will happen if we include a seasonal cycle in the meteorological forcings, for example the solar insolation? How does this change the concept of the equilibrium state of the ecosystem?

4. perturbations analysis The resilience (in Dutch: veerkracht) of an (eco)system is the amount of perturbation that it can absorb without collapsing or shifting to another state. A resilient system will be better able to absorb perturbations and return to its equilibrium. Here we use the return time after a perturbation as an indicator of the model ecosystems resilience: the faster the ecosystem returns to its original equilibrium state, the more resilient it is. We will demonstrate how the negative feedback decreases the return time compared with the ecosystem without the feedback after a perturbation. We will use two model versions which are identical except for the fact that one is with and the other without feedback. Contrary to the sensitivity analysis, we now use fixed parameters values to study the influence that the feedback has on the resilience of the ecosystem. From its initial conditions, the model is run until equilibrium is reached. Then, we perturb it by adding some nutrients. After that we will take a look at the time it takes for the system to return to its equilibrium again. Open DMS_sensitivtiy.m in the Matlab-editor and run it with the feedback switched on and off, using the DMS_sensitivity.xls file for setting the switch. Questions: compare the return times after perturbation for the model with and without feedback. Which return time is the smallest? Can you explain this?

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7 - Carbon cycle research in practice: Gas exchange measurements

Introduction During this practical you will get acquaintaned with a few methods to measure the exchange of a gas, such as CO2 or H2O between the Earths surface or ecosystems and the atmosphere.

First, there is a general introduction with a few questions to help you think about the subject.

Second, we have prepared a number of demonstration measurements on soil and plants under a range of conditions (wet and dry, humic and clean soil; wet and dry plants, in dark and in light conditions). The data that come out of these demonstrations will be available immediately for you to analyse and to calculate exchange rate.

We will work in two shifts, due to limited laboratory space: The fist from 13:30 till 15:15; the second from 15: 30 till 17:15.

Schedule: 1) Introduction by Bart Kruijt (10 min) 2) answer questions in introduction text (30 min) 3) discuss answers (10 min) 4) attend demonstration measurements (60 min) 5) calculate gas exchange for plants and soil in a range of conditions, using the demonstration data (60 min) 6) discuss results (10 min)

Principles of gas exchange measurement - Cuvettes, chambers, open or closed If we want to establish the rate of exchange (uptake, emission) of a gas between a surface and the air, there are two basic ways of doing this. The first possibility is to directly measure the transport rate of the gas: quantity and direction. This is effectively what we do on towers above ecosystems, where we measure vertical air flow rate and the associated gas concentrations in the air, and the covariance between the two signals gives us a vertical transport rate (eddy correlation method). The instruments used for this method are demonstrated in this practical.

Area

Quantity of gas transported per unit time and unit surface

Diffusion,mixing

source

sink

areatimeQuantityFlux

=

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surface

Up w.c down w.c

Flux=average

This is very hard to do at smaller scales, however, and there is a second possibility: the budget method. In this case, we measure the rate of change in gas concentration within a known volume of air, making sure (or assuming!) that there is only one plane of exchange between this volume and the surroundings: the surface.

This can be a leaf, a soil surface, or anything else.

In practice we use chambers or cuvettes. Basically these are closed boxes, or bottles, in which we put the material we want to measure the exchange with, and then we observe the concentration change inside or the concentration difference between outside and inside. This can be done either by sampling air and analysing these samples separately (fig1), or by pumping air between the cuvette and a gas analyzer (fig 2, fig 3).

Fig 1. Closed system, manual sampling

Fig. 2 closed system, automatic sampling

sample

[concentration change]

Extract & analyse

sample

[concentration change]

IRGA

display

sample

[concentration] IRGA

display

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Fig 3 open system

Question 1: if the cuvette and the gas analyzer are connected in a closed loop (fig 2), how will the CO2 concentration change after you put soil material in the cuvette? What if you insert a plant leaf?

Question 2: If this cuvette and gas analyzer are just connected through an open tube (fig. 3), how will the CO2 concentration develop over time, then?

- Infra-Red Gas Analysers (IRGA) To measure the concentration of gases such as CO2 or H2O in air, there are several methods. Traditional methods include dissolution in water followed by chemical analysis (e.g. using NaOH). Nowadays we use the principle that infra-red light is absorbed by these gases. Thus, we use instruments in which the air is led through a volume (tube) through which an infrared light beam is cast (fig. 4). At one end there is a light source, and at the other end a light detector. An electronic circuit measures the intensity at the detector and calculates concentrations from this.

Question 3: how does the detected IR intensity depend on concentration (qualitatively)?

Fig 4 IRGA cell

- Tubing To connect cuvette and IRGA we need tubes and a pump. Of course any material in between the object of measurement and the point of measurement will introduce errors and uncertainty.

Question 4: what would be important in choosing materials to build cuvettes and for tubing? Which kind of errors would you expect?

- Units of measurement, equations So, the gas molecules in the IRGA tube absorb light, which we measure. Question 5: Which would be the primary unit in which we quantify our concentration?

Question 6: Can you recall the universal Gas Law? Given that law, how (qualitatively) would the measured gas concentration change with temperature, and with air pressure? In case you need it, the value of universal gas constant is 8.314 J mol-1K1

IR source Analysis tube

Gas in Gas out

detector

Electronics and display

pump

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Question 7: If we want to quantify a gas exchange flux in moles per square metre of soil, or of leaf area, per second, and if you measure a concentration change over time in a closed cuvette (fig 2), what else do you need to know to get to this answer? Assume the equation as:

Flux = (t[C])/x *a/b

In which t [C] is the change of concentration over time, and we ask you to define x, a and b.

In case of an open cuvette system, the equation is: Flux = (i,o [C]) *b*f In which i,o [C] is the difference in concentration between outflow and inflow, b the same as above, and f is the flow rate. In addition to above, which would be the unit of f?

Note: in the demonstration measurements and data that follow, CO2 concentration is usually given in ppm. This is the same as micromol (CO2) per mol (air). To convert units, assume that there are 40 moles of air in one m3.

Demonstration measurements

We will demonstrate the use of several field techniques and instruments for measuring gas exchange on soils and plants. The raw data that come out of these measurements are time series of CO2 concentrations. The assignment for you is to calculate from these time series the fluxes for the various conditions.

We have: (Instruments)

- Eddy correlation equipment (display only) - Soil respiration chamber and gas analysers - Leaf photosynthesis equipment

(conditions) - humic soil, moist and dry - bare sand, moist and dry - well-watered plant, in light and in dark - drought-stressed plant, in light and dark

After attending the demonstrations, you will receive the data and calculate the respiration or photosynthesis fluxes from these objects, and we will compare them as a group:

- Open Excel on the computer at your bench and fill in/import the measured variables in adjacent columns - Plot the variables against time - Calculate the mean exchange rate (flux), using the equations from the introduction. If you dont understand them, ASK US! - Register your exchange rates on the Flipover sheets or whiteboard

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8 - Study guide with System Earth, ESS 20306

General The book is the basis for the exam, plus the extra issues covered in the presentations. In general, look at what we covered in the lectures, and those issues that are not covered there you can also consider less important in the book. We do, however ask questions about additional material presented in the lectures and practicals.

We do not ask for very precise numbers, ages, equations, etc, but you do need to know the approximate numbers: age of earth, archean, life, oxygen, ice ages, etc, and quantities such as major flows and stocks of carbon and water. We put muchasis on your understanding of systems diagrams and feedbacks and your ability to draw up such models yourself.

Note: this guide still refers to the 2nd edition of the book.

Chapter 1 Very general Global change in scope of issues covered by Pavel Kabat Ozone: see chapter 17 Deforestation: see carbon cycle and biodiversity: very general Long time scales: read only, link to later chapters

Chapter 2: Essential. Systems analysis and feed-backs Box stability as example (not equation)

Chapter 3 Assumed knowledge, no direct exam questions

Chapter 4 Assumed knowledge, no direct exam questions

Chapter 5 Important.

Chapter 6 Important. Principles, roles and use of models. Check with Larens Ganzeveld for 3rd edition.

Chapter 7 The role of the rock cycle in carbon cycling and climate. Build-up of the earth interior, principles of mechanics and drivers of continental drift. Not so important: seismology.

Chapter 8 See also lecture.Important. Main flows and stocks, primary and net productivity (see lecture!), Long term cycle, Role and principles of carbonate and silicate weathering.

Chapter 9 Role of life on earth, main characteristics of life and a planet with life. Metabolic pathways, Structure of ecosystems and species interactions is NOT so important

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here but we DO want you to be able to specify the roles of ecosystems in the larger earth system (systems approach). Skip box on physiological vs ecological optima. Role of biodiversity. Not: methods to quantify biodiversity Chapter 10 Important

Chapter 11 Important. You do not need to know by heart all the elements of evidence for theories on oxygen rise, but the underlying principles and questions are important.

Chapter 12 Important. Principles of the Archean atmosphere, systems diagrams for that period. Different types of and causes for ice ages. Cenozoic climate. Read but dont learn by heart the boxes.

Chapter 13 Variation of biodiversity over time, role of (mass) extinctions. NOT all the details of the evidence for the K-T mass extinction, but get the general idea of how conclusions were and are bing drawn on this. Periodicity of mass extinctions and possible causes.

Chapter 14 Important. Causes and role of various feed-backs. Again the emphasis is on systems approach, diagrams, etc and less on exact nubers and ages, but we do want you to know whether the ice ages lasted millions of years, hunders of thousands or tens of thousands.

Chapter 15 check for 3rd edition Important. See lecture. Age and timing of Holocene at precision of k-years. Again, roles of feedbacks, various causes of climate variation and difference with causes at longer time scales. Importance of the solar forcing. Modern climate change characteristics and causes. Only read through sections on ENSO and other short-term dynamics.

Chapter 16 check for 3rd edition Read through, box on chemistry of CO2 uptake: in scope of chapter 8. Understand future climate and how current climate change fits in longer time scales picture. We expect you to know the most important principles of current climate change. For the rest refer to the lectures by Pavel Kabat and the issues on adaptation the he presented.

Chapter 17 Refer to lecture by Laurens Ganzeveld.

Chapter 18 Skip. Pay attention to aspects of human disturbance in other chapters. Chapter 19 Understand thinking on the long-term future of Earth. Differences between Earh and other planets, in terms of life suitability. Principles of habitability of planets in other solar systems, know what you wuld look for if you look for life. Not all the details of the Drake equation.