I am not an expert in the field, so perhaps I will express in many words some well-known facts --- sorry for that.
I will get some intrinsic description of Dyck permutations; however, I am not sure whether it is satisfactory for you.
!. I will write the Bruhat decomposition of $C_D$ in the form $P=U_1C_DU_2$, where $U_1$ and $U_2$ are upper-triangular matrices. In this case, $U_1C_D$ is a matrix such that, if we denote by $\sigma(i)$ the leading position in row $i$, then $\sigma$ is a permutation; moreover, it is exactly the Dyck permutation $\sigma_D$ corresponding to $D$. We start with an explicit construction of such $\sigma$ and $U_1$ for a given Cartan matrix $C_D$.
The $i$th row of $C_D$ contains ones at the segment of positions $\{j_i+1,j_i+2,\dots,i\}$ where $j_1=0$, $j_i<i-1$ for $i>1$ and $j_1\leq j_2\leq\dots\leq j_n$. Construct a graph $G$ on the vertex set $V=\{0,1,\dots,n\}$ with edge set $\{g_1,g_2,\dots,g_n$}; the edge $g_i$ connects $j_i\to i$ for each $i=1,2,\dots,n$. The graph is directed, as this provides a convenient language (of in- and out-edges); however, when we will speak about the paths in this graph, we will mean paths disregarding directions of the edges; similarly, the (connected) components will be the weak connected components.
Set $U=\{j_1,j_2,\dots,j_n\}$ (refarded as a set but not multiset). Then (i) each vertex $i>0$ has exactly one in-edge (coming from a smaller vertex), (ii) each vertex not in $U$ has zero out-edges, (iii) the out-neighbours of $0$ are of the form $\{1,2,\dots,q\}$ for some $q\geq 2$, and (iv) all out-neighbourd of $0\neq j\in U$ are of the form $\{p,p+1,\dots,q\}$ for some $j+1<p\leq q$. Moreover, (v) the larger $j\in U$ is, the larger are its our-neighbours.
In particular, our graph is a tree rooted at $0$, where the vertices of $U$ are exactly non-leaves.
For $i\in V$, denote by $G_i$ the spanning subgraph of $G$ with edges $\{g_{i+1},g_{i+2},\dots,g_n\}$. In particularm, $G_n$ has no edges, and $G_0=G$. In each component of $G_i$, choose the maximum vertex, and let $M_i$ be the set of those vertices. Then $|M_i|=i+1$, and $\{n\}=M_0\subset M_1\subset \dots\subset M_n=V$. Denote $M_i\setminus M_{i-1}=\{m_i\}$.
Claim. $\sigma_D(i)=m_i+1$.
Proof. Clearly, $\sigma$ is a permutation of $\{1,2,\dots,n\}$; so we need to construct a matrix $U_1$ such that $U_1C_D$ has the required form.
In order to construct the $i$th row of $U_1$, we need to represent some row with the leading position $\sigma(i)=m_i+1$ as a linear combination of the rows $i,i+1,\dots,n$ of $C_D$ (taking row $i$ with a nonzero coefficient).
When we pass from $G_i$ to $G_{i-1}$, we add an edge corresponding to row $i$ of $C_D$, and two components merge into one; one of them had maximum element $m_i$, another one had maximum element $n_i>m_i$. Now, in $G_i$, there is a path $e_1e_2\dots e_k$ joining $m_i$ to $n_i$ (and passint through the added edge). This path corresponds to a desired linear combination: if $e_s$ corresponds to the row $i_s$, we take this row with coefficient $1$ if this edge in our path is traversed in the direction $j_{i_s}\to i_s$, and $-1$ otherwise. The resulting linear combination provides the row with zeroes and ones, with ones exactly at positions $\{m_i+1,m_i+2,\dots,n_i\}$, as desired. $\Box$
Further we will also use the notion of $n_i$ introduced in this proof.
2. Let us analyze a bit the obtained permutation. Consider an arbitrary $1\leq i\leq n$.
Case 1. Assume first that $j_{i+1}>j_i$ (so, in particular, $i>1$). This means that, in $G$, $i$ is the maximal out-neighbour of $j_i$. Hence, the vertex $j_i$ has no out-neighbours in $G_i$, so $j_i\in M_i$. On the other hand, in $G_{i-1}$ it has an out-neighbour, so $j_i\notin M_{i-1}$; therefore, $j_i=m_i=\sigma(i)-1$ and $\sigma_D(i)=j_i+1<i$ (as $i>1$).
Case 2. Now assume that $j_{i+1}=j_i$. Then, when we pass from $G_i$ to $G_{i-1}$, we connect a component containing $i$ with a component containing $j_i$; the latter also contans $i+1$, so we definitely have $m_i\geq i$ and hence $\sigma_D(i)>i$.
In particular, we have seen that $\sigma$ indeed has no fixed points. Moreover, the mapping $i\mapsto j_i$ (and hence the Dyck path $D$) can be completely reconstructed from the set $F(\sigma)$ of all pairs $(i,\sigma(i)$ with $\sigma(i)<i$ as follows. Choose the minimal $\mu_i\geq i$ such that $\sigma(\mu_i)<\mu_i$. Then $j_i=\sigma(i')-1$.
Notice also that, if we want to get a Dyck path, we need exactly two additional constraints: (a) $j_i<i-1$ for all $i>1$, and (b) if $(i_1,\sigma(i_1))$ and $(i_2,\sigma(i_2))$ are two elements in $F(\sigma)$ with $i_1<i_2$, then also $\sigma(i_1)<\sigma(i_2)$.
This shows the way how to recognize whether $\sigma$ is a Dyck permutation. By $\sigma$ (having no fixed points0, we construct the set $$ F(\sigma)=\{(i,\sigma(i))\colon \sigma(i)<i\} $$ By this set, we reconstruct the mapping $i\mapsto j_i$, check whether it obeys (a) and (b) (obtaining a Dyck path $D$ if they are satisfied), and check whether $\sigma=\sigma_D$ for the obtained $D$.
3. To make this a bit more explicit, we may notice the following.
Condition (b) is easily verifiable for a permutation $\sigma$. Condition (a) merely means that, if $1<\sigma(i)<i$, then there is an $i'$ strictly between $\sigma(i)$ and $i$ such that $\sigma(i')<i'$ (and hence $\sigma(i')<\sigma(i)$ by (b)).
Now, how to check that $\sigma_D=\sigma$. Denote the mapping $i\mapsto j_i$ obtained from $F(\sigma)$ by $\tau$ (in fact, the graph $G$ will contain exactly the edges of the form $\tau(i)\to i$), and revall the notion of $\mu_i$ introduced in the definition of that mapping. Denote $$ Q(i)=\{a\colon \tau^k(a)=i \quad\text{for some $k\geq 0$}\}. $$ Then, for every $i$ with $\sigma(i)>i$, we need to check the following condition. Let $$ m=\max Q(i), \quad n=\max\bigcup_{i<a\leq \mu_i}Q(a). $$ Then $\sigma(i)=\min\{m,n\}+1$.