diff --git a/CHANGELOG b/CHANGELOG
index 7792759c4bc9e396164dfe9a8a7d535aff048e26..669467266b8355f6611de1fef7f3a1395e606cf3 100644
--- a/CHANGELOG
+++ b/CHANGELOG
@@ -1,3 +1,16 @@
+2018-08-21  Axel Schnitger  <axel.schnitger@aei.mpg.de>
+
+	* CHANGELOG, README.md,
+	function_gfr/batch_processor_partitioned.m: Update documentation.
+
+	* commit 072c386874e366e6c23641cc45db2dea75b6f047
+
+2018-08-20  Axel Schnitger  <axel.schnitger@aei.mpg.de>
+
+	* CHANGELOG: Add CHANGELOG.
+
+	* commit 29983b4997d3999bec01f0a8fe56ac37586825e7
+
 2018-08-20  Axel Schnitger  <axel.schnitger@aei.mpg.de>
 
 	* README.md, continue_gfr_par_from_iteration.m, get_input_data.sh:
diff --git a/README.md b/README.md
index 852ccd58ce4060136e9c1fa140c9f3b7a0f51b80..b1ebcbca524bc146d06a2b319dedfcdc7cc1bfd2 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 
 ## Overview
 
-GRACETOOLS is an archive of MATLAB software that can be used for gravity field
+GRACETOOLS is a collection of MATLAB scripts that can be used for gravity field
 recovery using GRACE type satellite observations.
 
 **Features**
@@ -14,48 +14,45 @@ recovery using GRACE type satellite observations.
 - This code can be easily modified to run on the user's local parallel
   computations clusters.
 
-## Content
+**Content**
 
 <!-- vim-markdown-toc GitLab -->
 
 * [Usage](#usage)
-    * [Example dataset](#example-dataset)
-        * [Linux & Mac](#linux-mac)
-        * [Manually](#manually)
 * [Performance](#performance)
 * [Files](#files)
-* [Acknowledgments](#acknowledgments)
 * [Contributors](#contributors)
 
 <!-- vim-markdown-toc -->
 
-## Usage
+GRACETOOLS is open source software and licensed under
+[GPLv3](https://gitlab.aei.uni-hannover.de/geoq/gracetools/blob/master/LICENSE).
+Please reference this article if you use GRACETOOLS:
+
+**Darbeheshti N., Wöske F., Weigelt M., McCullough C., Wu H. (2018) GRACETOOLS - GRACE gravity field recovery tools, Geosciences.**
 
-The main m-files to run are: `gfr_parallel.m` and
-`continue_gfr_par_from_iteration.m`.
 
-### Example dataset
+## Usage
 
-To be able to run these scripts you need an example data-set.
+The main m-files to run are:
 
-#### Linux & Mac
+- `gfr_parallel.m`
+- `continue_gfr_par_from_iteration.m`
 
-If you're working with Linux or MacOS simply use the `get_input_data.sh` script
-to get the dataset:
+You need an example dataset to run these scripts. If you're on Linux or MacOS
+use the `get_input_data.sh` script to get the dataset:
 
 ```
 $ ./get_input_data.sh
 ```
 
-#### Manually
-
-Download the following dataset:
+If you prefer the manual way download the dataset:
 
 - [Download dataset](https://seafile.projekt.uni-hannover.de/f/3ee8fef6c6cb485489b4/?dl=1)
 
-Move the dataset into the `input_data` directory and extract it. Then delete
-the `input_data.zip` file. In a terminal the commands look like this from the
-GRACETOOLS main directory:
+Move the zip file into the `input_data` directory, extract it and delete the
+now unnecessary `input_data.zip` file. For completeness here are the terminal
+commands:
 
 ```
 $ mv ~/Downloads/input_data.zip input_data/
@@ -64,14 +61,7 @@ $ unzip input_data.zip
 $ rm -f input_data.zip
 ```
 
-Again from the GRACETOOLS main directory you can check the directory structure
-of the input_data/ directory with the following command:
-
-```
-$ tree input_data/
-```
-
-The output should look like this:
+The directory structure of `input_data/` should look like this:
 
 ```
 input_data
@@ -96,55 +86,62 @@ input_data
 └── GGM05S.gfc
 ```
 
-
 ## Performance
 
-With an older intel i5 (4 cores) a test case with degree and order 10 with 4
+With an older Intel i5 (4 cores) a test case with degree and order 10 with 4
 days of observation, each iteration takes about 1h 10min.
 
 ## Files
 
-| m-file                          | Description                                                                                                           |
-| :------------------------------ | :-------------------------------------------------------------------------------------------------------------------- |
-| `batch_processor_partitioned.m` | batch processing algorithm for GRACE range-rate observations.                                                         |
-| `cs2sc.m`                       | converts the square containing spherical harmonics coefficients storage format into a rectangular format.             |
-| `cs2vec`                        | rearranges a field of spherical harmonic coefficients in cs-or sc-format to a vector shape.                           |
-| `deriv.m`                       | calculates equation of motion and all partials.                                                                       |
-| `dv_geoidn.m`                   | reads an Earth's gravity field model and plots the degree variances.                                                  |
-| `dv_geoidn_no_plot`             | reads an Earth's gravity field model and gives the degree variances without plotting.                                 |
-| `grtenpshs.m`                   | calculates the gradient and the tensor of the gravity field.                                                          |
-| `hmat.m`                        | makes the Hi_tilda matrix.                                                                                            |
-| `importGravityField.m`          | import numeric data from a text file as a matrix.                                                                     |
-| `initplm.m`                     | initialzes a plm calculation.                                                                                         |
-| `inter_sat_dist.m`              | calculates range and range rate from position and velocity.                                                           |
-| `llpartialgradV.m`              | determines the partial derivative of the gradient of the gravity field w.r.t. the coefficients.                       |
-| `multmatvek.m`                  | mulitplicates a matrix and a vector.                                                                                  |
-| `odeint.m`                      | integrates one step with step size dt from t0 and initial values y0.                                                  |
-| `odeint_abm.m`                  | integrates one step with step size h from t0 and initial values y0.                                                   |
-| `odeint_dp8.m`                  | integrates one step with step size h from t0 and initial values y0 with Runge-Kutta (RK) integrator.                  |
-| `odeint_dp8_abm_init.m`         | integrates one step with step size h from t0 and initial values y0 with Runge-Kutta (RK) integrator.                  |
-| `odeint_rk4.m`                  | integrates one step with step size h from t0 and initial values y0 with simple 4th order Runge-Kutta (RK) integrator. |
-| `odeint_rk4_abm_init.m`         | integrates one step with step size h from t0 and initial values y0 with simple 4th order Runge-Kutta (RK) integrator. |
-| `plm.m`                         | fully normalized associated Legendre functions for a selected order M.                                                |
-| `plmsp.m`                       | fully normalized associated Legendre functions for all degree and order but in a single points.                       |
-| `readACC.m`                     | Read GRACE ACC1B data                                                                                                 |
-| `readGFC.m`                     | Read gfc files                                                                                                        |
-| `readGNV.m`                     | Read GRACE GNV1B data                                                                                                 |
-| `readKBR.m`                     | Read GRACE KBR1B data                                                                                                 |
-| `readSCA.m`                     | Read GRACE SCA1B data                                                                                                 |
-| `Ri2e.m`                        | returns the rotation matrix from an inertial frame to an Earth-fixed coordinate system.                               |
-| `Ri2e_dot.m`                    | returns the derivative of the rotation matrix from inertial frame to an Earth-fixed Earth-centered coordinate system. |
-| `save_vars2continue_itr.m`      | save all important variables of a gravity estimation.                                                                 |
-| `vec2cs.m`                      | rearranges a vector shaped set of spherical harmonic coefficients into cs-format.                                     |
-
-## Acknowledgments
-
-- GRACETOOLS is open source software (LICENSE GPLv3).
-- Please reference this article if you use GRACETOOLS:
-
-```
-Darbeheshti N., Wöske F., Weigelt M., Mccullough C., Wu H. (2018) GRACETOOLS - GRACE gravity field recovery tools, Geosciences.
-```
+- `batch_processor_partitioned.m` - batch processing algorithm for GRACE
+  range-rate observations
+- `cs2sc.m`- converts the square containing spherical harmonics coefficients
+  storage format into a rectangular format
+- `cs2vec`- rearranges a field of spherical harmonic coefficients in cs-or
+  sc-format to a vector shape
+- `deriv.m`- calculates equation of motion and all partials
+- `dv_geoidn.m`- reads an Earth's gravity field model and plots the degree
+  variances
+- `dv_geoidn_no_plot`- reads an Earth's gravity field model and gives the
+  degree variances without plotting
+- `grtenpshs.m`- calculates the gradient and the tensor of the gravity field
+- `hmat.m`- makes the Hi_tilda matrix
+- `importGravityField.m`- import numeric data from a text file as a matrix
+- `initplm.m`- initializes a plm calculation
+- `inter_sat_dist.m`- calculates range and range rate from position and
+  velocity
+- `llpartialgradV.m`- determines the partial derivative of the gradient of the
+  gravity field w.r.t. the coefficients
+- `multmatvek.m`- mulitplicates a matrix and a vector
+- `odeint.m`- integrates one step with step size dt from t0 and initial values
+  y0
+- `odeint_abm.m`- integrates one step with step size h from t0 and initial
+  values y0
+- `odeint_dp8.m`- integrates one step with step size h from t0 and initial
+  values y0 with Runge-Kutta (RK) integrator
+- `odeint_dp8_abm_init.m`- integrates one step with step size h from t0 and
+  initial values y0 with Runge-Kutta (RK) integrator
+- `odeint_rk4.m`- integrates one step with step size h from t0 and initial
+  values y0 with simple 4th order Runge-Kutta (RK) integrator
+- `odeint_rk4_abm_init.m`- integrates one step with step size h from t0 and
+  initial values y0 with simple 4th order Runge-Kutta (RK) integrator
+- `plm.m`- fully normalized associated Legendre functions for a selected order
+  M
+- `plmsp.m`- fully normalized associated Legendre functions for all degree and
+  order but in a single points
+- `readACC.m`- Read GRACE ACC1B
+- `readGFC.m`- Read GFC file
+- `readGNV.m`- Read GRACE GNV1B
+- `readKBR.m`- Read GRACE KBR1B
+- `readSCA.m`- Read GRACE SCA1B
+- `Ri2e.m`- returns the rotation matrix from an inertial frame to an
+  Earth-fixed coordinate system
+- `Ri2e_dot.m`- returns the derivative of the rotation matrix from inertial
+  frame to an Earth-fixed Earth-centered coordinate system
+- `save_vars2continue_itr.m`- save all important variables of a gravity
+  estimation
+- `vec2cs.m`- rearranges a vector shaped set of spherical harmonic coefficients
+  into cs-format
 
 ## Contributors
 
diff --git a/function_gfr/batch_processor_partitioned.m b/function_gfr/batch_processor_partitioned.m
index a8e174b098c7257a08bf7e73d68bb76d801877d3..07776113fef54b406288958ffb0c63a620fde3a4 100644
--- a/function_gfr/batch_processor_partitioned.m
+++ b/function_gfr/batch_processor_partitioned.m
@@ -1,10 +1,11 @@
 function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm,GM,ae,lmaxf,state,timeKBR,observation,x0x)
 
-% Batch processing algorithm for GRACE range-rate observations. 
-% separation between local and global parameters, which are estimated for
-% different arcs. E.g. Initial states daily and spherical harmonics 
-% coefficients for the whole time. Using Partitioned Normal Equations
-% based on:
+% BATCH_PROCESSOR_PARTITIONED provides a batch processing algorithm for GRACE
+% range-rate observations. 
+%
+% Separation between local and global parameters, which are estimated for
+% different arcs. E.g. Initial states daily and spherical harmonics
+% coefficients for the whole time. Using Partitioned Normal Equations based on:
 % - Gunter's MSc(2000)thesis, page 27
 % - Statistical Orbit Determination (Tapley et al., 2004), page 196-197
 % 
@@ -23,7 +24,7 @@ function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm,
 %           x0x = state deviation [12x1]
 % 
 % Output:   function has no output, output is saved in file for easy
-%           paralleization
+%           parallelization
 % 
 % Example: see gfr_parallel.m
 %