Method and apparatus for producing ground vegetation input data for global climate change prediction model

An input data generating apparatus for generating forcing data used as input data for a climate change prediction model, the input data generating apparatus comprising:

• a memory storing instructions;
• and
• a processor configured to, by executing the instructions;
• communicate data with a coupled model inter-comparison project (CMIP) model database storing a CMIP model;
• retrieve existing ground type data from the CMIP model stored in the CMIP model database, wherein:
• the existing ground type data has been generated at a first point in time,
• the existing ground type data comprises vegetation types of data and non-vegetation types of data each arranged in grid,
• the vegetation types of data including one or more of a broad leaf tree type, a needle leaf tree type, a C3 type, a C4 type, or a shrub type, and
• the non-vegetation types of data including one or more of an urban type, an inland-water type, a bare-soil type, and an ice type, is arranged in each grid;
• communicate data with a land-use harmonization (LUH) data database, wherein the LUH data database stores LUH data having a first grid size;
• determine that the first gird size of the LUH data is not compatible with a predetermined climate change prediction model;
• generate new ground type data from the LUH data stored in the LUH data database by converting the first grid size into a second grid size that is compatible with the predetermined climate change prediction model, such that the new ground type data has the second grid size, wherein:
• the new ground type data comprises the C3 type and the C4 type selected from the vegetation types and the urban type selected from the non-vegetation types, and
• the new ground type data reflects changes in ground vegetation according to human activities and time lapse at least between the first point in time and a second point in time later than the first point in time;
• generate aggregated ground type data by data-aggregating the new ground type data and the existing ground type data such that:
• the C3 type and the C4 type of the new ground type data are selected without selecting the C3 type and the C4 type from the vegetation types of data of the existing ground type data,
• the urban type of the new ground type data is selected without selecting the urban type from the non-vegetation types of data of the existing ground type data,
• the C3 type and the C4 type of the new ground type data are combined with one or more of the broad leaf tree type, the needle leaf tree type, or the shrub type selected from the vegetation types of data of the existing ground type data to generate aggregated vegetation types of data, and
• the urban type of the new ground type data is combined with one or more of the inland-water type, the bare-soil type, or the ice type selected from the non-vegetation types of data of the existing ground type data to generate aggregated non-vegetation types of data,
• determine whether the new ground type data and the existing ground type data conflict each other in one or more of the aggregated vegetation types of data or the aggregated non-vegetation types of data;
• in response to determining that the new ground type data and the existing ground type data conflict each other, adjust one or more types of the existing ground type data, without adjusting the new ground type data, to generate the forcing data;
• and
• apply the generated forcing data as an input to the climate prediction model.