Evaluation of Biases in JRA-25/JCDAS Precipitation and Their Impact on the Global Terrestrial Carbon Balance

Abstract

Listen

Translate article

Abstract This study evaluates a modeled precipitation field and examines how its bias affects the modeling of the regional and global terrestrial carbon cycle. Spatial and temporal variations in precipitation produced by the Japanese 25-yr reanalysis (JRA-25)/Japan Meteorological Agency (JMA) Climate Data Assimilation System (JCDAS) were compared with two large-scale observation datasets. JRA-25/JCDAS captures the major distribution patterns of annual precipitation and the features of the seasonal cycle. Notable problems include over- and undersimulated areas of precipitation amount in South America, Africa, and Southeast Asia in the 30°N–30°S domain and a large discrepancy in the number of rainfall days. The latter problem was corrected by using a stochastic model based on the probability of the occurrence of dry and wet day series; the monthly precipitation amount was then scaled by the comparison data. Overall, the corrected precipitation performed well in reproducing the spatial distribution of and temporal variations in total precipitation. Both the corrected and original precipitation data were used to simulate regional and global terrestrial carbon cycles using the prognostic biosphere model Vegetation Integrative Simulator for Trace Gases (VISIT). Following bias correction, the model results showed differences in zonal mean photosynthesis uptake and respiration release ranging from −2.0 to +3.3 Pg C yr−1, compared with the original data. The difference in the global terrestrial net carbon exchange rate was 0.3 Pg C yr−1, reflecting the compensation of coincident increases or decreases in carbon sequestration and respiration loss. At the regional scale, the ecosystem carbon cycle and canopy structure, including seasonal variations in autotrophic and heterotrophic respiration and total biomass, were strongly influenced by the input precipitation data. The results highlight the need for precise precipitation data when estimating the global terrestrial carbon balance.