home.md

-h1. Bayesian uncertainty analysis
+h1. N2O emission from nitrification
 
-{{>toc}}
+# Math markup
 
-h2. Description
+Here is some math markup: $`a^2 + b^2 = c^2`$
 
-$x^{yield}_{t}$
+Or more complicated:
+$`\sum_{i=1}^n i^3 = \left( \frac{n(n+1)}{2} \right)^2`$
 
-Parameter determination for processes in LPJmL is mostly achieved by
-literature values. In case, data are available, the estimation of
-uncertainties and evaluation of current parameterization is possible by
-Bayesian analysis. Here, we give an example how to use data for a better
-grass parametrization.
+It's based on $`\KaTeX`$
 
-h2. Details
+# GitLab-specific markup
+I can refer to a specific commit, just by pasting the hash here: b3ede2e52b64026c68d90519d93b3bce58f4c46d
 
-a more detailed description of it (data sources, data preparation,
-meaning, usage...). Refer to references if you have any using
-footnotes\[1\]
+Or here: 80fbf7b1627d45d8d857481585d23430fb9b354b
 
-h2. Technical Note
+I can refer to an issue, starting with the $`#`$: #2 
 
-What you need are \* data \* the R package FME\[1\]
+Here is another wiki page about [Something Else](something-else)
 
-Following the procedure there, you can \* define a cost function that
-gives the deviation of the model output from the observations \*
-determine the local sensitivity to a large set of parameters \* evaluate
-the most prominent parameters that should be included in the Monte Carlo
-simulations by determining the collinearity \* fit the model to the data
-using the chosen subset of parameters \* perform the Markov chain
-Monte-Carlo simulations \* evaluate the uncertainty of the model output
-due to the parameter values accepted in the Monte Carlo chain.
+# Another heading
+- [ ] a task
+- [x] a completed task
 
-h2. Developer(s)
+========================================
 
-Susanne Rolinski, Anja Rammig, Werner von Bloh
+# h1
 
-h2. See Also
+#  N2O emission from nitrification
 
-\[\[Upscaling\]\], \[\[Downscaling\]\], \[\[Wiki\]\], \[\[Mathematical
-Description\]\], \[\[Missing wiki page\]\]
+"Parton et al. 1996":http://onlinelibrary.wiley.com/doi/10.1029/96GB01455/abstract gives function
 
-Links to other Wiki pages, that are related. It doesn't matter if the
-wiki page already exists or not. Also link pages that do not exist yet!
-Links to existing pages are written blue, links to non-existing pages
-are writtn in red.
+$`N_{N2O} = N_{H2O} \cdot N_{pH} \cdot N_T \cdot (Kmx + Nmx \cdot N_{NH4})`$
 
-h2. References
+with
+$N_{N2O} = ((WFPS-b)/(a-b))^{d\cdot (b-a)/(a-c)} \cdot ((WFPS-c)/(a-c))^d$
+* $WFPS$ is water filled pore space of the soil
+* parameters $a$ to $d$ given for sandy and medium soil
+* source for functions given as Doran et al. 1988
 
-fn1. K. Soetaert and T. Petzoldt (2010): Inverse Modelling, Sensitivity
-and Monte Carlo Analysis in R Using Package FME. Journal of Statistical
-Software, 33, 3, 1-28.
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+$N_{pH} = 0.56+1/\pi\cdot \arctan(\pi\cdot 0.45 \cdot(pH-5))$
+* we ignore this limitation
+
+$N_T = -0.06+0.13\cdot \exp(0.07 \cdot T_{soil})$
+* based on data by Sabey et al. (1959)
+
+$Kmx = 0.00038$ gN m$^{-2}$ d$^{-1}$
+* N turnover coefficient
+* site specific but given for different sites
+* for natural soils given as 3.8 and 3.9 (gN ha$^{-1}$ d$^{-1}$)
+
+$Nmx = 0.003$ gN m$^{-2}$ d$^{-1}$
+* maximum nitrification flux of N$_2$O with excess NH$_4$.
+
+$N_{NH4} = 1 - \exp(-0.0105\cdot NH4)$
+* NH4 here given as $\mu$g N per g soil
+* in the same range as gN m$^{-2}$ so that formula taken as it is
+
+Process is incorporated in source:branches/nitrogen_rev2142/src/soil/littersom.c after mineralization.
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