###### Abstract  
The atmospheric total water vapor content (_TWVC_) affects climate change, weather patterns, and radio signal propagation. Recent techniques such as global navigation satellite systems (GNSS) are used to measure _TWVC_ but with either compromised accuracy, temporal resolution, or spatial coverage. This study demonstrates the feasibility of predicting, mapping, and measuring _TWVC_ using spread spectrum (SS) radio signals and software-defined radio (SDR) technology on low Earth-orbiting (LEO) satellites. An intersatellite link (ISL) communication network from a constellation of small satellites is proposed to achieve three-dimensional (3D) mapping of _TWVC_. However, the calculation of _TWVC_ from satellites in LEO contains contribution from the ionospheric total electron content (_TEC_). The _TWVC_ and _TEC_ contribution are determined based on the signal propagation time delay and the satellites' positions in orbit. Since _TEC_ is frequency dependent unlike _TWVC_, frequency reconfiguration algorithms have been implemented to distinguish _TWVC_. The novel aspects of this research are the implementation of time stamps to deduce time delay, the unique derivation of _TWVC_ from a constellation setup, the use of algorithms to remotely tune frequencies in real time, and ISL demonstration using SDRs. This mission could contribute to atmospheric science, and the measurements could be incorporated into the global atmospheric databases for climate and weather prediction models. t 1 2023 10 807 10 20  
observation infrastructure such as surface meteorology, Raman light detection and ranging instruments (R Lidar), differential absorption Lidar, microwave radiometry, and sun photometers have proven successful in mapping the _TWVC_ distribution with high temporal resolution and adequate precision [1; 5; 6; 7; 8; 9; 10; 11]. However, these techniques are usually immovable, costly, require continuous maintenance, and have small spatial coverage. Also, surface meteorology-related data are closely tied to land-air data and cannot sufficiently map the complete boundary of atmospheric water vapor. Moreover, meteorological sensors for microwaves, Lidar instruments, and sun photometers are greatly affected by rain, clouds, and the intensity of sun, respectively. These effects greatly limit the efficiency and effectiveness of using these techniques in measuring parameters of the atmosphere. Very-long baseline interferometry is another ground-based technique that can detect atmospheric water vapor based on the delay of a radio signal when observing extragalactic radio emitters such as quasars using at least two ground-based radio antennas [10; 12]. Nevertheless, it is usually characterized by low temporal resolution depending on the operation schedule. Meteorological station data from 1966 to 2017 and ERA5 reanalysis data from 1979 to 2020 over Russia were used to study the scaling correlation between daily precipitation extremes and surface air temperature (SAT) as represented by the Clausius-Clapeyron (C-C) equation [13]. Northern Eurasia has not been adequately examined, despite major temperature shifts and a rapid transition from large-scale to convective precipitation. Reanalysis data might have inconsistencies and station data might have limited spatial coverage, especially in remote regions, potentially leading to spatial bias. Gaining insight into the mechanisms driving intense precipitation allows for improved weather predictions and climate projections that rely on enhanced satellite technologies for improved accuracy. Polar orbiting satellites, radiosondes, interferometric synthetic aperture radar (InSAR), imaging spectroradiometers such as the moderate and medium resolution imaging (MODIS onboard Terra and Aqua and MERIS onboard ENVISAT), remotely piloted vehicles, instrumented aircrafts, and global navigation satellite systems (GNSS) satellites are among the air and space-inclined techniques utilized to detect and measure _TWVC_[1; 14; 15; 16; 17; 18; 19; 20; 21; 22].