Ever increasing model resolutions and physical processes in climate models demand continual computing power increases. The IBM Cell processor's order-of- magnitude peak performance increase over conventional processors makes it very attractive for fulfilling this requirement. However, the Cell's characteristics: 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. We selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (~50% total computation time), (2) has a high computational load relative to data traffic to/from main memory, and (3) performs independent calculations across multiple columns. We converted the baseline code (single-precision, Fortran code) to C and ported it to an IBM BladeCenter QS20, manually SIMDizing 4 independent columns, and found that a Cell with 8 SPEs can process more than 3000 columns per second. Compared with the baseline results, the Cell is ~6.76x, ~8.91x, ~9.85x faster than a core on Intel's Xeon Woodcrest, Dempsey, and Itanium2 respectively. Our analysis shows that the Cell could also speed up the dynamics component (~25% total computation time). We believe this dramatic performance improvement makes the Cell processor very competitive, at least as an accelerator. We will report our experience in porting both the C and Fortran codes and will discuss our work in porting other climate model components.