Skip to main content

Ecosystem modeling: a question of chicken or eggs?

Ecosystem modeling generally include three conceptual components: inputs, algorithm and outputs.
For example, we usually need precipitation to estimate surface runoff.
On the other hand, sometimes some outputs are also considered as inputs for other models. For example, vegetation dynamics also change the surface albedo and therefore the incoming radiation.
In another word, the feedback among different processes are often too complex that we generally have to ignore some feedback processes.

The reason is that our computer simulation MUST have a starting point and a sequence of algorithms in order to run the simulation.
For some well-designed models, the differences between different starting points are not significant when using the numerical approach. However, it is a best practice to put all the algorithms in the right orders.

For example, in surface hydrology, the generally order of the water flow is like this: precipitation->interception->snow->infiltration->overland runoff->stream flow, etc. In some case, groundwater also plays a role in this process.
If you map these processes to the actual physical world, these processes occur in the following places: atmosphere->canopy->land surface->soil->stream channel. etc.
Therefore, even though most of the processes occur simultaneously, we still need to break them down due to the time discretization scheme. If you have input data at a second resolution, following above order will not produce any different outputs compared with a different order. But if the time resolution is daily, monthly, or annually, the differences will increase significantly.

Even though the algorithms are placed under a logic order such as water flow, how to design them in a computer program remains unclear. First, in most computer program developments, dependency relationship among components do not always reflect these logical orders. For example, a typical vegetation is consist of canopy, stem and root. However, processes occur in these parts are usually at different time scale and environmental conditions, which makes the dependency relationship of these processes are usually much distorted in computation programs.

I will provide a real live example for review here:
The Community Land Model (CLM) is a widely used ecosystem model.
The core part of the processes simulated has a following order in CLM 4.0.

On the left are the names of the processes or modules, on the right are brief description of them. It appears that the general workflow is from top to bottom. But the question remains unresolved, whether this is the appropriate order for all of these processes. For example, what if the albedo is estimated ahead of the soil flux since energy budget will be potentially different if albedo chanages from snow are considered.

Comments

Popular posts from this blog

Spatial datasets operations: mask raster using region of interest

Climate change related studies usually involve spatial datasets extraction from a larger domain.
In this article, I will briefly discuss some potential issues and solutions.

In the most common scenario, we need to extract a raster file using a polygon based shapefile. And I will focus as an example.

In a typical desktop application such as ArcMap or ENVI, this is usually done with a tool called clip or extract using mask or ROI.

Before any analysis can be done, it is the best practice to project all datasets into the same projection.

If you are lucky enough, you may find that the polygon you will use actually matches up with the raster grid perfectly. But it rarely happens unless you created the shapefile using "fishnet" or other approaches.

What if luck is not with you? The algorithm within these tool usually will make the best estimate of the value based on the location. The nearest re-sample, but not limited to, will be used to calculate the value. But what about the outp…

Numerical simulation: ode/pde solver and spin-up

For Earth Science model development, I inevitably have to deal with ODE and PDE equations. I also have come across some discussion related to this topic, i.e.,

https://www.researchgate.net/post/What_does_one_mean_by_Model_Spin_Up_Time

In an attempt to answer this question, as well as redefine the problem I am dealing with, I decided to organize some materials to illustrate our current state on this topic.

Models are essentially equations. In Earth Science, these equations are usually ODE or PDE. So I want to discuss this from a mathematical perspective.

Ideally, we want to solve these ODE/PDE with initial condition (IC) and boundary condition (BC) using various numerical methods.
https://en.wikipedia.org/wiki/Initial_value_problem
https://en.wikipedia.org/wiki/Boundary_value_problem

Because of the nature of geology, everything is similar to its neighbors. So we can construct a system of equations which may have multiple equation for each single grid cell. Now we have an array of equation…

Lessons I have learnt during E3SM development

I have been involved with the E3SM development since I joined PNNL as a postdoc. Over the course of time, I have learnt a lot from the E3SM model. I also found many issues within the model, which reflects lots of similar struggles in the lifespan of software engineering.

Here I list a few major ones that we all dislike but they are around in almost every project we have worked on.

Excessive usage of existing framework even it is not meant to Working in a large project means that you should NOT re-invent the wheels if they are already there. But more often, developers tend to use existing data types and functions even when they were not designed to do so. The reason is simple: it is easier to use existing ones than to create new ones. For example, in E3SM, there was not a data type to transfer data between river and land. Instead, developers use the data type designed for atmosphere and land to do the job. While it is ok to do so, it added unnecessary confusion for future development a…