KlimALEZ Toolbox
(beta version)
Climate Insurance Design and Performance Analysis (beta version)
© KlimALEZ, 2022
Cite as: Sarvarbek Eltazarov, Ihtiyor Bobojonov, Lena Kuhn & Thomas Glauben. (2023). Improving risk reduction potential of weather index insurance by spatially downscaling gridded climate data - a machine learning approach, Big Earth Data, https://doi.org/10.1080/20964471.2023.2196830
A web-app was developed for interested parties to design index-based climate insurance and analyze their climate risk reduction potential. The app is fully automatic and does not require any knowledge of statistics or programming languages. The web platform requires the user to enter a period, crop yield and index information. Data can be copy-pasted with any delineation (eg. space, comma). Consequently, the web-app designs index-based climate insurance products based on entered data and calculates descriptive statistics, and conducts performance analysis.
To test our app, please enter the following example data and run the tool.
Step 1
Years: 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015
Crop yield (tonn/ha): 0.69, 1.62, 1.04, 1.11, 1.1, 1.03, 1.22, 0.49, 1.65, 1.01, 1.46, 1.1, 0.97, 0.82, 1.17, 1.38, 1.25, 0.75, 1.41, 0.66, 1.79, 1.1, 0.85, 1.21, 1.19
Index (rainfall, mm): 70, 137, 110, 114, 77, 90, 85, 42, 162, 127, 142, 114, 100, 76, 122, 112, 119, 74, 105, 45, 158, 107, 70, 122, 92
Price (USD): 100
Step 2
Enter new index to calculate payout: 150, 70, 124, 55, 135
(Video tutorial will be available soon)
A web-app was developed for the design of agricultural index-based insurance design and performance analysis to be made available for interested parties in open access, as it does not require any knowledge of statistics or programming languages. The web platform requires the user to enter a period, crop yield and index information. Data can be copy-pasted in any format. Consequently, web-app designs index-based insurance products based on entered data and calculates descriptive statistics, and conducts performance analysis.
This tool has been developed for scientific purposes within the project “KlimALEZ – Increasing climate resilience via agricultural insurance – Innovation transfer for sustainable rural development in Central Asia” implemented by Leibniz Institute of Agricultural Development in Transition Economies (IAMO) and funded by German Federal Ministry of Education and Research (BMBF), Germany.
