Comment on essd-2021-251

Arthur Endsley

doi:10.5194/essd-2021-251-rc2

Abstract

The concept of plant functional types (PFTs) is shown to be beneficial in representing the complexity of plant characteristics in land use and climate change studies using regional climate models (RCMs). By representing land use and land cover (LULC) as functional traits, responses and effects of specific plant communities can be directly coupled to the lowest atmospheric layers. To meet the requirements of RCMs for realistic LULC distribution, we developed a PFT dataset forEurope (LANDMATE PFT Version 1.0 Reinhart et al., 2021b, ;). The dataset is based on the high-resolution ESA-CCI land cover dataset and is further improved through the the additional use of climate information. Within the LANDMATE PFT dataset, satellite-based LULC information and climate data are combined to achieve the best possible representation of the diverse plant communities and their functions in the respective regional ecosystems while keeping the dataset most flexible for application in RCMs. Each LULC class of ESA-CCI is translated into PFT or PFT fractions including climate information by using the Holdridge Life Zone concept. Through the consideration of regional climate data, the resulting PFT map for Europe is regionally customized. A thorough evaluation of the LANDMATE PFT dataset is done using a comprehensive ground truth database over the European Continent. A suitable evaluation method has been developed and applied to assess the quality of thenew PFT dataset. The assessment shows that the dominant LULC groups, cropland and woodland, are well represented within the dataset while uncertainties are found for some less represented LULC groups. The LANDMATE PFT dataset provides a realistic, high-resolution LULC distribution for implementation in RCMs and is used as basis for the LUCAS LUC dataset introduced in the companion paper by Hoffmann et al. (submitted) which is available for use as LULC change input for RCM experiment setups focused on investigating LULC change impact.

Highlights

Land use and land cover (LULC), including the vegetation type and function, was declared an Essential Climate Variables (ECVs) by the Global Climate Observing System (GCOS) (Bojinski et al, 2014)
The LANDMATE plant functional types (PFTs) dataset provides a 15 realistic, high-resolution land use and land cover (LULC) distribution for implementation in regional climate models (RCMs) and is used as basis for the LUCAS LUC dataset introduced in the companion paper by Hoffmann et al which is available for use as LULC change input for RCM experiment setups focused on investigating LULC change impact
For the preparation of LANDMATE PFT, we developed a cross-walking procedures (CWPs) for the translation of LULC classes of European Space Agency Climate Change Initiative (ESA-CCI) into 16 PFTs according to the needs of regional climate modellers from all over Europe (Bontemps et al, 2013)

Summary

Introduction

Land use and land cover (LULC), including the vegetation type and function, was declared an Essential Climate Variables (ECVs) by the Global Climate Observing System (GCOS) (Bojinski et al, 2014). Changes in ECVs are crucial factors of climate change and need to be monitored and further represented in climate models to be able to assimilate and understand atmospheric processes and feedback effects on different scales. In order to represent impacts and feedbacks of LULC modifications as realistic as possible, regional climate models (RCMs) require an accurate representation of LULC and its changes. In this context, the concept of plant functional types (PFTs) is increasingly used for the representation of LULC in RCMs. A comprehensive review of the subsequent development of PFTs representing vegetation dynamics in climate models was done by Wullschleger et al (2014). The need for applicable global PFT maps for vegetation models that are used with atmospheric models was already well emphasized by Box (1996)

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