Models are powerful tools for understanding the coupling of physical processes. We illustrate this using averages from ERA-40 for the Madeira River, a southwestern basin of the Amazon, which has a large seasonal cycle with a dry season in the austral winter. Daily-mean land-surface fluxes and state variables can be used to map the transitions of the surface climate of a model and to quantify the links between the soil moisture, the mean cloud-base and cloud field, the shortwave and longwave radiation fields at the surface, the vertical motion field, the atmospheric precipitable water, and the surface precipitation. The links that are visible on a daily timescale can also be seen on the seasonal timescale. Several important surface processes are strongly influenced by soil moisture: relative humidity, which gives the mixed subcloud layer depth, low cloud cover, and the surface net long-wave flux. The link between soil moisture and equivalent potential temperature can therefore be clearly seen once the temperature dependence is filtered. Surface evaporation is controlled as much by the feedback of the cloud field on the surface radiation budget as by soil moisture. Above the surface the cloud field and precipitation are coupled to the large-scale dynamics, specifically the midtropospheric omega field. The shortwave cloud forcing of the atmosphere and the surface is given by the cloud field albedo at the top of the atmosphere to better than 1%. We have developed a new methodology for understanding the coupling and feedbacks between physical processes in models, so that different models can be compared with each other and with data.