Artificial intelligence (AI) -- and specifically machine learning (ML) -- applications for climate prediction across timescales are proliferating quickly. The emergence of these methods prompts a revisit to the impact of data preprocessing, a topic familiar to the climate community, as more traditional statistical models work with relatively small sample sizes. Indeed, the skill and confidence in the forecasts produced by data-driven models are directly influenced by the quality of the datasets and how they are treated during model development, thus yielding the colloquialism "garbage in, garbage out." As such, this article establishes protocols for the proper preprocessing of input data for AI/ML models designed for climate prediction (i.e., subseasonal to decadal and longer). The three aims are to: (1) educate researchers, developers, and end users on the effects that preprocessing has on climate predictions; (2) provide recommended practices for data preprocessing for such applications; and (3) empower end users to decipher whether the models they are using are properly designed for their objectives. Specific topics covered in this article include the creation of (standardized) anomalies, dealing with non-stationarity and the spatiotemporally correlated nature of climate data, and handling of extreme values and variables with potentially complex distributions. Case studies will illustrate how using different preprocessing techniques can produce different predictions from the same model, which can create confusion and decrease confidence in the overall process. Ultimately, implementing the recommended practices set forth in this article will enhance the robustness and transparency of AI/ML in climate prediction studies.

This study presents an orbital phase-dependent analysis of three black widow spider millisecond pulsars (BW MSPs), aiming to investigate the magnetic field within the eclipse environment. The ultra-wide-bandwidth low-frequency receiver (UWL) of the Parkes 'Murriyang' radio telescope is utilised for full polarisation observations covering frequencies from 704-4032 MHz. Depolarisation of pulsed emission is observed during the eclipse phase of three BW MSPs namely, J0024-7204J, J1431-4715 and PSR J1959+2048, consistent with previous studies of other BW MSPs. We estimated orbital phase dependent RM values for these MSPs. The wide bandwidth observations also provided the constraints on eclipse cutoff frequency for these BW MSPs. For PSR J0024-7204J, we report temporal variation of the eclipse cutoff frequency coupled with changes in the electron column density within the eclipse medium across six observed eclipses. Moreover, the eclipse cutoff frequency for PSR J1431-4715 is determined to be 1251 $\pm$ 80 MHz, leading to the conclusion that synchrotron absorption is the primary mechanism responsible for the eclipsing. Additionally, for PSR J1959+2048, the estimated cutoff frequency exceeded 1400 MHz, consistent with previous studies. With this investigation, we have doubled the sample size of BW MSPs with orbital phase-resolved studies allowing a better probe to the eclipse environment.