diff --git a/DESCRIPTION b/DESCRIPTION
index 4151ba48204d6c18077b6610edda77ed8ad2c0a8..c40d147025eac27d38f6ebb54ad047cc07ddb829 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -21,8 +21,11 @@ Description: Set of generalised tools for the flexible computation of climate
   predictions, but its methods are also applicable to other time-scales, 
   provided the dimensional structure of the input is maintained. Additionally, 
   the outputs of the functions in this package are compatible with 'CSTools'. 
-  This package was developed in the context of H2020 MED-GOLD (776467) and 
-  S2S4E (776787) projects. Lledó et al. (2019) <doi:10.1016/j.renene.2019.04.135>.
+  This package is described in Pérez-Zanón et al. (2023) 
+  <doi:10.1016/j.cliser.2023.100393> and it was developed in the context of 
+  H2020 MED-GOLD (776467) and S2S4E (776787) projects. See Lledó et al. (2019) 
+  <doi:10.1016/j.renene.2019.04.135> and Chou et al., 2023 
+  <doi:10.1016/j.cliser.2023.100345> for details.
 Depends:
     R (>= 3.6.0)
 Imports:
@@ -40,4 +43,4 @@ URL: https://earth.bsc.es/gitlab/es/csindicators/
 BugReports: https://earth.bsc.es/gitlab/es/csindicators/-/issues
 Encoding: UTF-8
 RoxygenNote: 7.2.0
-Config/testthat/edition: 3
\ No newline at end of file
+Config/testthat/edition: 3
diff --git a/README.md b/README.md
index 5521a516c737721659480633a0a5ef715affd14a..360ecbee9b29b493c8fd2e43e595515612747f72 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,18 @@ CSIndicators
 
 #### Sectoral Indicators for Climate Services Based on Sub-Seasonal to Decadal Climate Predictions
 
-Set of generalised tools for the flexible computation of climate related indicators defined by the user. Each method represents a specific mathematical approach which is combined with the possibility to select an arbitrary time period to define the indicator. This enables a wide range of possibilities to tailor the most suitable indicator for each particular climate service application (agriculture, food security, energy, water management…). This package is intended for sub-seasonal, seasonal and decadal climate predictions, but its methods are also applicable to other time-scales, provided the dimensional structure of the input is maintained. Additionally, the outputs of the functions in this package are compatible with [CSTools](https://earth.bsc.es/gitlab/external/cstools). 
+Set of generalised tools for the flexible computation of climate related indicators defined by the user. Each method represents a specific mathematical approach which is combined with the possibility to select an arbitrary time period to define the indicator. This enables a wide range of possibilities to tailor the most suitable indicator for each particular climate service application (agriculture, food security, energy, water management…). This package is intended for sub-seasonal, seasonal and decadal climate predictions, but its methods are also applicable to other time-scales, provided the dimensional structure of the input is maintained. Additionally, the outputs of the functions in this package are compatible with [CSTools](https://earth.bsc.es/gitlab/external/cstools).  
+
+How to cite
+-----------
+
+> Pérez-Zanón, N., Ho, A. Chou, C., Lledó, L., Marcos-Matamoros, R., Rifà, E. and González-Reviriego, N. (2023). CSIndicators: Get tailored climate indicators for applications in your sector. Climate Services. https://doi.org/10.1016/j.cliser.2023.100393  
+
+For details in the methodologies see:  
+
+> Pérez-Zanón, N., Caron, L.-P., Terzago, S., Van Schaeybroeck, B., Lledó, L., Manubens, N., Roulin, E., Alvarez-Castro, M. C., Batté, L., Bretonnière, P.-A., Corti, S., Delgado-Torres, C., Domínguez, M., Fabiano, F., Giuntoli, I., von Hardenberg, J., Sánchez-García, E., Torralba, V., and Verfaillie, D.: Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information, Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, 2022.  
+Chou, C., R. Marcos-Matamoros, L. Palma Garcia, N. Pérez-Zanón, M. Teixeira, S. Silva, N. Fontes, A. Graça, A. Dell'Aquila, S. Calmanti and N. González-Reviriego (2023). Advanced seasonal predictions for vine management based on bioclimatic indicators tailored to the wine sector. Climate Services, 30, 100343, https://doi.org/10.1016/j.cliser.2023.100343.  
+Lledó, Ll., V. Torralba, A. Soret, J. Ramon and F.J. Doblas-Reyes (2019). Seasonal forecasts of wind power generation. Renewable Energy, 143, 91-100, https://doi.org/10.1016/j.renene.2019.04.135.
 
 Installation
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