Identifying reliable geochemical signals that reflect crustal stress evolution remains a major challenge in earthquake monitoring. Spring fluids, due to their deep circulation and rapid response, provide an important window into fault-zone processes. This study presents three years (May 2022–March 2025) of hourly hydrogen gas (H₂) concentration monitoring in spring gases from the Muji Basin on the northern Pamir Plateau, integrated with meteorological and seismic data. H₂ concentrations exhibited a stable diurnal pattern, positively correlated with water and air temperatures and negatively correlated with atmospheric pressure. Short-term anomalies during seismically quiet periods may reflect a combination of temperature-dependent solubility effects and transient degassing caused by localized gas accumulation and sudden release under heterogeneous fault and aquifer conditions. During seismically active phases, sustained increases in H₂ concentrations were also recorded; however, such anomalies did not consistently precede earthquakes, instead reflecting broader phases of tectonic instability and episodic fault-zone degassing. These findings highlight the potential of long-term H₂ monitoring to improve our understanding of the coupling between crustal stress, fluid transport, and degassing processes in tectonically active regions.

The Pattern Informatics Method (PI) was initially developed for medium-to-long-term earthquake prediction by analyzing changes in seismic activity. It has since been refined and extended to identify ionospheric anomalies associated with earthquakes. Notable advancements include the development of modified and improved methods, which have demonstrated their capability to detect significant short-term and ionospheric anomalies preceding earthquake events. In this study, the IPI method was applied to infrared satellite observation data for the first time, and a new algorithm for extracting short-term and imminent anomalies from infrared earthquakes was explored based on the IPI method, from which we obtained the MIPI (Modified Improved Pattern Informatics Method). Using 1° × 1° nighttime Outgoing Longwave Radiation (OLR) data from NOAA_18 satellites of the National Oceanic and Atmospheric Administration’s Climate Prediction Center (NOAA-CPC) of the United States, the evolution of OLR anomalies before the Ridgecrest Ms 6.9 earthquake in the United States on 6 July 2019 as recorded by the China Earthquake Networks Center (CENC) and the Maduo Ms 7.4 earthquake in China on 21 May 2021 as recorded by the China Earthquake Networks Center (CENC) were studied. In order to make the IPI method suitable for the calculation of OLR data, two modifications were made to the IPI algorithm: (1) the quartile method was applied for automatically determining the abnormal changes in the OLR observation data and they were used as the input data instead of ionospheric data; (2) the standard deviation of the multi-year OLR residual data of each grid was used instead of the maximum anomaly index used in the original method to re-assign and obtain the relative anomaly index, and finally the anomaly evolution time series diagram was drawn. The results show the following: (1) The MIPI method can effectively extract short-term and imminent OLR anomalies prior to earthquakes. (2) Short-term and imminent OLR anomalies appeared about two weeks before each earthquake and lasted until the earthquake occurrence, disappearing after the earthquake. During this process, the anomalies exhibited a certain evolutionary trend. (3) The short-term and imminent OLR anomalies prior to each earthquake were distributed near the epicenter or near the seismogenic fault, about 200 KM away from the epicenters. The above results are similar to the spatiotemporal evolution characteristics of seismic infrared short-term anomalies previously studied, which indicates that the MIPI method can effectively extract seismic infrared anomalies and might provide a practical method for the extraction of seismic infrared short-term and imminent anomalies.