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I would like to here about success factors and failors from other consultancies in climate adaptation for water management
Strategies to get clients really involved in these kind of projects’ development.
Previous experience on downscaling climate indicators in heterogeneous regions.
Key factors (success/failure) when implementing clients-oriented platforms for climate and water planning services.
I´d like to learn from other purveyors what sort of problems and solutions they have. This could bring us new ideas for projects in our region. We also would share ideas and maybe find cooperation in some fields.
like to get and give dta and concepts.
I am hoping to learn how different knowledge purveyors communicate with clients to identify their needs. My experience is that clients rarely know what they need at the beginning…
I can confirm this. But this is a great opportunity for business, as you can “produce” needs in the client.
Me too, I would like to learn from other purveyors what sort of problems and solutions they have. I’d like to know about data sources, tools and methods used.
I would like to learn which is the available information in order to describe the best strategy to be applied according to the obtained indicators for the stakeholders.
How to make data useful for groups that are not experienced with climate data.
Yes, it would be interesting to hear about examples and experiences from similar projects in other regions, successful solutions but also problems and how they were solved.
Ideas, strategies and data for extending our climate adaptation services and products.
The sources, formats and other details (bias correction, downscaling…) about climate information from which we can derive indicators.
1) Ideas on practical applications of available climate change scenarios data.
2) Transfer of know-how on climate change data usage, from climate models to down-scaled information.
Developing the need for such kind of services to possible clients and even raising awareness over this issues could be the real challenge. How can you introduce to market a “product” that could prove useful after, let’s say, at least 10 to 15 years? Climate change data are not appealing to most of clients due to its long-term nature.
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