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The physics of the stable isotopes of water is incorporated into a two‐dimensional, kinematic, bulk cloud microphysical model. The model is run for several idealized, classical stratiform and convective storm situations, and the resulting isotope ratios of precipitation and water vapor are diagnosed and compared to observations. For stratiform snow, the model produces low isotope ratios that decrease rapidly poleward of the warm front. The lowest isotope ratios occur when the atmosphere is cold and when the vertical velocity attains its maximum value high in the troposphere. For stratiform rains, the model produces much higher isotope ratios without a significant poleward gradient as a result of isotope exchange between the falling rain and the surrounding vapor. Isotope ratios of rain are lowest when the melting level is near the ground and isotope exchange is minimized. For air mass thunderstorms, isotope ratios are uniformly high in warm air, no matter what the cloud height, unless hail approaches or reaches the ground. The model also produces a significant amount effect for rain, in which isotope ratios decrease with increasing rainfall, totals. Isotope ratios are particularly low when the rain derives from a recirculation process in which air previously charged by vapor from falling rain subsequently rises. Under such conditions, the model sometimes produces isotope ratios that decrease from the periphery to the core of the precipitation shield. It is suggested that this recirculation process is responsible for extraordinarily low isotope ratios observed in some hurricanes and organized thunderstorms. The dominant cloud microphysical processes can sometimes be inferred from isotope ratios of precipitation. The model produces ice pellets with isotope ratios close to those of rain when the pellets are produced by homogeneous freezing of rain and close to those of snow when the pellets are produced by refreezing of partially melted snow. A climatology of isotope values that matches the main features of the observed global data set and of a seven‐year record of storms at Mohonk Lake, New York is generated by running the model for a wide range of conditions. This includes the deuterium excess (d ≡ δD ‐ 8*δ18O) for Antarctic snows that increases markedly as δD falls below −300‰ and the deuterium deficit observed for rain in warm, dry regions.

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