We introduce a method for reconstructing macroscopic models of one-dimensional stochastic processes with long-range correlations from sparsely sampled time series by combining fractional calculus and discrete-time Langevin equations. The is illustrated the ARFIMA(1,d,0) process nonlinear autoregressive toy model multiplicative noise. reconstruct daily mean temperature data recorded at Potsdam, ...