Government and commercial airborne light detection and ranging (lidar) systems have enabled extensive measurements of the Earth's surface and land cover over the past decade. There is much interest, however, in employing smaller lidar systems that require less power to enable sensing from small unmanned aerial vehicles or satellites. Technological advances in the performance of small microlasers and photodetector sensitivity have recently enabled the development of experimental airborne lidar systems with low signal-to-noise ratios (LSNRs). Recent government and academic prototypes have indicated that LSNR airborne lidars could significantly increase the fidelity of terrain reconstruction over what is possible with existing conventional lidars. Thus, there is a need to build up a modeling capability for such systems in order to aid in future system and mission design. A numerical sensor simulator has been developed to model the expected returns from LSNR microlaser altimeter systems and predict their performance. Both optical and signal processing system components are considered, along with other factors, including atmospheric effects and surface conditions. Topographic (solid Earth) and bathymetric (littoral zone) measurement scenarios are considered. The analysis of topographic simulation data focuses on the effect of solar noise on SNR and elevation accuracy while bathymetric performance is evaluated with regard to water depth and scan angle for different water clarities. The mission conditions chiefly responsible for limiting the performance of LSNR lidar are discussed in detail, along with suggestions for further algorithm development and system performance evaluation.