The mid-infrared(MIR) atmospheric strong absorption wavelength bands(near 2.7 and 4.3 μm) have the characteristics of suppressing background clutter signals, which are often used on the payload of infrared early warning satellites to achieve stable detection and tracking of targets. The background clutter fluctuation level has an important impact on MIR target detection, and it is of great significance to study the spatial domain fluctuation of surface-atmosphere clutter near the 2.7 and 4.3 μm bands. First, the MODTRAN radiative transfer model is used to iteratively simulate the optical depth (OD) of water vapor and CO₂ under six standard atmospheric models, screen the strong absorption bands according to the criterion of OD>1, and intersect the band calculation results under various atmospheric models. The final strong absorption bands were 2.52～2.83 and 4.18～4.47 μm. Then, global monthly averaged surface and atmosphere background products are produced based on remote sensing satellite data products and data assimilation information. Among them, combined with the monthly average surface reflectance/emissivity products (MYD09A1/ MOD11C3) of MODIS shortwave infrared and mid-infrared bands (2.13, 3.75, 3.96 and 4.05 μm), the non-negative matrix factorization (NMF) method was used to reconstruct global surface reflectance/emissivity products at strongly absorbing bands; Produce monthly-averaged global surface temperature products based on ERA5 reanalysis data; The global monthly average products of water vapor and cloud optical thickness (COT) are obtained by splicing and fusing MODIS atmospheric products (MOD05_L2 and MOD06_L2) respectively; The CO₂ global monthly average product comes from the data assimilation product of the OCO-2 satellite; In order to spatially match various data products and save computing resources, global products are limited to the 60° north and south latitude range and resampled to a spatial resolution of 1°×1°; Next, under cloudy and cloud-free conditions, the background clutter intensity of two strong absorption bands was simulated and calculated pixel by pixel, and the spatial distribution pattern of clutter was analyzed. Finally, the 11×11 square window neighborhood statistics method was used to calculate the clutter spatial domain fluctuation in the simulation results, convert the clutter fluctuation under 95% probability, and conduct histogram statistics. From the perspective of clutter suppression, a comparison of infrared target detection performance in two absorption bands is given. Study results show that under cloud conditions, the fluctuation level of background clutter in the 2.52～2.83 μm band has the characteristics of “a point-like peak, regional enhancement, and overall low values”. In contrast, the clutter fluctuation level in the 4.18～4.47 μm band shows the characteristics of “regional high values, patchy enhancement, and low values at high latitudes”. Under cloud-free conditions, the background clutter fluctuation level in the 2.52～2.83 μm band increases significantly in the low water vapor content area. In contrast, the clutter fluctuation level in the 4.18～4.47 μm band is generally low, and most of them are controlled within 2×10^-4 W/m²/sr/μm. On the global scale, the infrared target detection performance is better in the 2.52～2.83 μm band when there are clouds and in the 4.18～4.47 μm band when there are no clouds. The results of this study can provide a reference basis for detecting infrared targets in terms of spatial domain law and spectral band optimization, which is of great value for enhancing the detectability of targets.