Weather prediction has always been an integral part of determining the human activities that rely upon weather changes, such as farming. Knowing the right time to plant to have a successful harvest is crucial to the success of crop farming. Moreover, air transport depends on the accuracy of weather forecasting for the planes to fly and land safely. Therefore, interpreting weather patterns correctly plays a significant role in ensuring secure space transportation with fewer accidents.
History of Weather Satellites
For a long time, remote sensing was referred to as aerial photography and photogrammetry using optical instruments. Progressively, the race to become more advanced in space technology boosted technological advancement in remote sensing. As a result, space technology has significantly progressed since the space race competition between the former Soviet Union and the United States for dominant spaceflight capability (Erickson et al.,2018). Ideally, the United States of America and the Soviet Union sought to dominate in advancing space technology because it was necessary for national security and an image of ideological superiority.
Initially, the space competition started with the launch of Sputnik on 4 October 1957, which had no camera on board. According to Siddiqui et al. (2022), between 1957 and 1978, the space race left a legacy of rapid development of communication satellites and various earth-observing remote-sensing satellites. Primarily, the launch of Sputnik boosted the research on meteorology because it had a camera that could provide aerial images of our planet’s surface and atmosphere.
Over time, through its research program, the United States launched its first meteorological satellite, the Television Infrared Observation Satellite (TIROS). This advancement in remote satellite technology provided a better capability to quickly observe large areas of the Earth more accurately (Qi et al., 2020). As a result, full images of clouds related to large weather systems became visible. Hence, the weather program developed more rapidly, enabling the TIROS to be launched by the United States in April 1960.
TIROS-1 had two cameras that sent images of weather patterns to scientists on Earth. The images captured in the TIROS-1 cameras detailed weather changes, different cloud patterns, and data on forming storms. This technology provided more accurate data to weather forecast scientists enabling them to make better interpretations. Zhang et al. (2018) assert that before satellites, scientists captured photos of the Earth from the ground and aerial photographs from above the clouds on an airplane. Compared to TIROS-1, aerial photography needed sufficient data to make many interpretations.
In addition, software applications, especially for landscape surveys, had specific data sources because there were no other sources of land data from remote satellites. According to Khorchani et al. (2018), different technologies can be used for various purposes as opposed to technology that cannot be used for a purpose other than what was developed, such as the AVHRR. It was first developed for weather forecasting, providing data on land and sea surface temperature measurements, cloud cover, snow, ice cover, and soil moisture. The AVHRR is a radiometer meant to be flown on the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites for weather forecasting duties. Many decades later, other countries, including China, have also been able to launch satellite technologies (Borowitz, 2023). Progressively, since the AVHRR was launched, weather forecasting has undergone much research to improve better methods of getting data. Interpretations are being made, enabling scientists to make crucial decisions based on the data gathered (Eyre et al., 2020). These developments help to save lives because they detect impending natural disasters such as hurricanes, tornadoes, or tsunamis earlier, and safety measures can be taken based on this information.
Existing Problems of Weather Satellites and How to Fix Them
Weather satellites are a vital technology because it helps to retrieve and relay data information about the Earth’s weather patterns and atmospheric changes. However, every technology has disadvantages that should be addressed to ensure its performance improves. One of those issues is that satellites have a short shelf life, typically between 5 to 10 years, because of a limited onboard fuel capacity. According to Kumar et al. (2022), scientists can solve this issue by developing more satellites that can last longer and improving the present capabilities to make them more serviceable. Ideally, some satellites may malfunction due to software or hardware issues, which is very dangerous because it leads to inaccurate data for interpretation (Massey et al., 2020). Such malfunctions may occur due to factors like being hit by debris in space. Thus, routine equipment checks should be done to check for any damages.
Another serious problem occurs when orbits start moving further away, bringing up the issue of inaccuracy by reducing the distance covered by the weather satellite. Pardini and Anselmo (2020) postulate that a propulsion system will increase the orbit’s radius and adjust the orbital speed to stabilize the rotation. Hence, transferring data from space to Earth can encounter some issues, especially when there is interference in the waves involved in sharing the data, damaging or corrupting the data. Scientists can fix this issue by developing better communication equipment to receive more accurate data.
Moreover, unreliable power can cause problems sometimes since satellites get their power through solar technology. According to Qi et al. (2020), solar equipment may get damaged, thus failing to generate power as required. These damage risks can be prevented by frequently ensuring that the solar panels function correctly and developing batteries that can store more energy to increase reliability. Other factors, such as solar flares, radiation, and space objects, can prevent weather satellites from functioning well. Proper maintenance protects the weather satellites from damage from these factors. In addition, satellites are massive and technologically advanced equipment, making them very costly to develop and deploy to space (Kopacz et al., 2020). Therefore, countries can carry out a joint satellite development program where they can contribute to the cost, reducing the cost burden of developing a weather satellite.
Most significantly, weather satellites process a considerable amount of data, which can cause the issue of overloading the data being processed and might cause a system failure. Cintineo et al. (2020) suggest that preventing system failure can be managed using advanced algorithms that analyze the data faster. Implementing cloud computing will assist in managing the bulk of data. Besides, common system failures due to periodic maintenance can also occur, and they can be solved by ensuring a regular system checkup to ensure every software runs smoothly. Furthermore, not all satellites are large enough to provide extensive observation, thus relaying limited data for interpretation. Hence, deploying more satellites will ensure adequate coverage to retrieve enough data for processing.
Proposal to Improve Knowledge or Performance of Weather Satellites
With the weather satellites significantly enhancing weather forecast accuracy, their continuous improvement will ensure sustainable benefits. Foremost, developing better data processing techniques will ensure that weather satellites’ data are fully used to make the correct interpretations. According to Geer et al. (2018), algorithms can significantly help identify patterns in large datasets, producing better and more accurate weather forecasting. Fundamentally, the methods used in assimilating data can be used to combine observations or meteorological variables, such as temperature and atmospheric pressure, with other forecasts to create numerical forecast models which are more accurate.
Secondly, using the Hyper Microwave Sounder, a more advanced technology, will improve the accuracy of projections. Lawrence et al. (2018) affirm that using modern technology like geostationary satellites helps to constantly monitor fast weather changes because they revolve at the same speed as the Earth and focus on the same area. Since these technologies can get images of the Earth quickly, they can help measure land temperature and provide real-time cloud coverage, thus facilitating cyclone prediction. In addition, the geostationary satellite can be used simultaneously with polar satellites, which orbit the Earth at a low altitude, enabling them to cover a wider area (Jiang et al., 2019). Thus, meteorological experts can use the data from the two satellites to produce more accurate and detailed information.
Furthermore, using hyperspectral sensors will ensure data capturing in different spectral bands, thus enabling exact measurements of the Earth’s surface. With crowdsourcing, enhanced data storage systems will improve weather forecasting by providing new data sources (Kishi, 2021). Weather forecasting will improve due to the recent advancements in crowdsourcing, including the collection and quality control of atmospheric pressure. The data is captured in smartphones used by scientists.
Conclusion
Advanced technology in weather forecasting has enabled scientists to have more accurate predictions. Weather satellite technology has continued to advance since its first development, making predicting patterns in weather changes easier and making life better. Accuracy in the interpretation of data has enabled countries to mitigate disasters and sometimes prevent death. Ultimately, scientists can now predict climate change and advice farmers when to plant, thus avoiding losses when the rain does not fall.
References
Borowitz, M. (2023). Let’s just talk about the weather: Weather satellites and space diplomacy. The Hague Journal of Diplomacy, 1(aop), 1–28. Web.
Cintineo, J. L., Pavolonis, M. J., Sieglaff, J. M., Wimmers, A., Brunner, J., & Bellon, W. (2020). A deep-learning model for automated detection of intense midlatitude convection using geostationary satellite images. Weather and Forecasting, 35(6), 2567–2588. Web.
Erickson, A. S. (2018). Revisiting the U.S.-Soviet space race: Comparing two systems in their competition to land a man on the moon. Acta Astronautica, 148, 376–384. Web.
Eyre, J. R., English, S. J., & Forsythe, M. (2020). Assimilation of satellite data in numerical weather prediction. Part I: The early years. Quarterly Journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain), 146(726), 49–68. Web.
Geer, A. J., Lonitz, K., Weston, P., Kazumori, M., Okamoto, K., Zhu, Y., Liu, E. H., Collard, A., Bell, W., Migliorini, S., Chambon, P., Fourrié, N., Kim, M.-J., Köpken-Watts, C., & Schraff, C. (2018). All‐sky satellite data assimilation at operational weather forecasting centers. Quarterly Journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain), 144(713), 1191–1217. Web.
Jiang, H., Lu, N., Qin, J., Tang, W., & Yao, L. (2019). A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data. Renewable and Sustainable Energy Reviews, 114(109327), 109327. Web.
Khorchani, M., Vicente-Serrano, S. M., Azorin-Molina, C., Garcia, M., Martin-Hernandez, N., Peña-Gallardo, M., El Kenawy, A., & Domínguez-Castro, F. (2018). Trends in LST over the peninsular Spain as derived from the AVHRR imagery data. Global and Planetary Change, 166, 75–93. Web.
Kishi, N. (2021). Satellite data and crowdsourcing. Space Policy, 56(101423), 101423. Web.
Kopacz, J. R., Herschitz, R., & Roney, J. (2020). Small satellites an overview and assessment. Acta Astronautica, 170, 93–105. Web.
Kumar, A., Tewari, B. S., & Pandey, K. (2022). Quantum Computing Application for Satellites and Satellite Image Processing. In Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network (pp. 63–81). CRC Press.
Lawrence, H., Bormann, N., Geer, A. J., Lu, Q., & English, S. J. (2018). Evaluation and assimilation of the microwave sounder MWHS-2 onboard FY-3C in the ECMWF numerical weather prediction system. IEEE Transactions on Geoscience and Remote Sensing: A Publication of the IEEE Geoscience and Remote Sensing Society, 56(6), 3333–3349. Web.
Massey, R., Lucatello, S., & Benvenuti, P. (2020). The challenge of satellite megaconstellations. Nature Astronomy, 4(11), 1022–1023. Web.
Pardini, C., & Anselmo, L. (2020). Environmental sustainability of large satellite constellations in low earth orbit. Acta Astronautica, 170, 27–36. Web.
Qi, R., Zhang, Y., Lu, S., Hu, Q., & Zhong, R. (2020). Tethered towing of defunct satellites with solar panels. Acta Astronautica, 175, 1–10. Web.
Siddiqui, S. J., Bhatia, M., & Sachdeva, S. (2022). Quantum computer in space exploration. EPRA International Journal of Multidisciplinary Research (IJMR), 8(2), 21–28. Web.
Zhang, J., Zhu, S., & Li, C. (2018). Research on key technologies of space integrated information network. 2018 IEEE 18th International Conference on Communication Technology (ICCT), 1104–1108.