Retrieval of All-Sky Land Surface Temperature Considering Penetration Effect Using Spaceborne Thermal and Microwave Radiometry

Thermal infrared (TIR) remote sensing (RS) has been widely adopted for monitoring land surface temperature (LST). However, its application has been limited to cloud-free conditions, resulting in a need for LST retrieval methods that combine microwave (MW) and TIR channels. This is especially crucial in areas frequently covered by clouds. One limitation of the current LST retrieval methods is the absence of considering the penetration effect (PE) of MW, which leads to great uncertainty in barren and sparsely vegetated areas. To address this issue, this study proposes a new perspective that considers the PE to merge the LST retrieved from MW and TIR channels. The soil temperature integral equation is simplified based on the soil temperature and water content profiles. Consequently, a PE-based model is developed to convert the effective soil temperature into LST and merge the LST estimated from passive MW observations with those from moderate resolution imaging spectroradiometer (MODIS) LST products. The model considering PE performs better than the method that does not consider PE, as demonstrated by higher $R$ and lower root-mean-square error (RMSE) values. The PE-based model is then applied to Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, and the estimated LST is found to fit well with the MODIS LST product ( $R$ = 0.91). Using this model, an all-sky LST is retrieved by merging passive MW observations and MODIS LST products. Validation of the model at eight ground-based stations over the Tibetan Plateau (TP) demonstrates its reasonable accuracy in both clear-sky and cloudy conditions.</p

Effects of dust storms on microwave radiation based on satellite observation and model simulation over the Taklamakan desert

International audienceEffects of dust particles on microwave radiation over the Taklamakan desert are studied with use of measurements from the Advanced Microwave Scanning Radiometer (AMSR-E) on the EOS Aqua satellite and a microwave radiation transfer model. Eight observed cases show that the signal from atmospheric dust can be separated from the surface radiation by the fact that the dust particles produce stronger scattering at high frequencies and depolarize the background desert signature. This result of satellite data is consistent with the model simulation

A lake ice phenology dataset for the Northern Hemisphere based on passive microwave remote sensing

Lake ice phenology (LIP) is an essential indicator of climate change and helps with understanding of the regional characteristics of climate change impacts. Ground observation records and remote sensing retrieval products of lake ice phenology are abundant for Europe, North America, and the Tibetan Plateau, but there is a lack of data for inner Eurasia. In this work, enhanced-resolution passive microwave satellite data (PMW) were used to investigate the Northern Hemisphere Lake Ice Phenology (PMW LIP). The Freeze Onset (FO), Complete Ice Cover (CIC), Melt Onset (MO), and Complete Ice Free (CIF) dates were derived for 753 lakes, including 409 lakes for which ice phenology retrievals were available for the period 1978 to 2020 and 344 lakes for which these were available for 2002 to 2020. Verification of the PMW LIP using ground records gave correlation coefficients of 0.93 and 0.84 for CIC and CIF, respectively, and the corresponding values of the RMSE were 11.84 and 10.07 days. The lake ice phenology in this dataset was significantly correlated (P < 0.001) with that obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) data–the average correlation coefficient was 0.90 and the average RMSE was 7.87 days. The minimum RMSE was 4.39 days for CIF. The PMW is not affected by the weather or the amount of sunlight and thus provides more reliable data about the freezing and thawing process information than MODIS observations. The PMW LIP dataset provides the basic freeze–thaw data that is required for research into lake ice and the impact of climate change in the cold regions of the Northern Hemisphere. The dataset is available at http://www.doi.org/10.11922/sciencedb.j00076.00081.Peer reviewe

Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015

A new automated method enabling consistent satellite assessment of seasonal lake ice phenology at 5 km resolution was developed for all lake pixels (water coverage  ≥  90 %) in the Northern Hemisphere using 36.5 GHz H-polarized brightness temperature (Tb) observations from the Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 (AMSR-E/2) sensors. The lake phenology metrics include seasonal timing and duration of annual ice cover. A moving t test (MTT) algorithm allows for automated lake ice retrievals with daily temporal fidelity and 5 km resolution gridding. The resulting ice phenology record shows strong agreement with available ground-based observations from the Global Lake and River Ice Phenology Database (95.4 % temporal agreement) and favorable correlations (R) with alternative ice phenology records from the Interactive Multisensor Snow and Ice Mapping System (R = 0.84 for water clear of ice (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) and Canadian Ice Service (R = 0.86 for WCI dates; R = 0.69 for CFO dates). Analysis of the resulting 12-year (2002–2015) AMSR-E/2 ice record indicates increasingly shorter ice cover duration for 43 out of 71 (60.6 %) Northern Hemisphere lakes examined, with significant (p  \u3c  0.05) regional trends toward earlier ice melting for only five lakes. Higher-latitude lakes reveal more widespread and larger trends toward shorter ice cover duration than lower-latitude lakes, consistent with enhanced polar warming. This study documents a new satellite-based approach for rapid assessment and regional monitoring of seasonal ice cover changes over large lakes, with resulting accuracy suitable for global change studies

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Evaluation of MERRA Land Surface Estimates in Preparation for the Soil Moisture Active Passive Mission

The authors evaluated several land surface variables from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) product that are important for global ecological and hydrological studies, including daily maximum (Tmax) and minimum (Tmin) surface air temperatures, atmosphere vapor pressure deficit (VPD), incident solar radiation (SWrad), and surface soil moisture. The MERRA results were evaluated against in situ measurements, similar global products derived from satellite microwave [the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E)] remote sensing and earlier generation atmospheric analysis [Goddard Earth Observing System version 4 (GEOS-4)] products. Relative to GEOS-4, MERRA is generally warmer (~0.5°C for Tmin and Tmax) and drier (~50 Pa for VPD) for low- and middle-latitude regions (\u3c50°N) associated with reduced cloudiness and increased SWrad. MERRA and AMSR-E temperatures show relatively large differences (\u3e3°C) in mountainous areas, tropical forest, and desert regions. Surface soil moisture estimates from MERRA (0–2-cm depth) and two AMSR-E products (~0–1-cm depth) are moderately correlated (R ~ 0.4) for middle-latitude regions with low to moderate vegetation biomass. The MERRA derived surface soil moisture also corresponds favorably with in situ observations (R = 0.53 ± 0.01, p \u3c 0.001) in the midlatitudes, where its accuracy is directly proportional to the quality of MERRA precipitation. In the high latitudes, MERRA shows inconsistent soil moisture seasonal dynamics relative to in situ observations. The study’s results suggest that satellite microwave remote sensing may contribute to improved reanalysis accuracy where surface meteorological observations are sparse and in cold land regions subject to seasonal freeze–thaw transitions. The upcoming NASA Soil Moisture Active Passive (SMAP) mission is expected to improve MERRA-type reanalysis accuracy by providing accurate global mapping of freeze–thaw state and surface soil moisture with 2–3-day temporal fidelity and enhanced (≤9 km) spatial resolution

Long term soil moisture mapping over the Tibetan plateau using Special Sensor Microwave/Imager

This paper discusses soil moisture retrievals over the Tibetan Plateau from brightness temperature (TB's) observed by the Special Sensor Microwave Imagers (SSM/I's) during the warm seasons of the period from July 1987 to December 2008. The Fundamental Climate Data Record (FCDR) of F08, F11 and F13 SSM/I satellites by the Precipitation Research Group of Colorado State University is used for this study. A soil moisture retrieval algorithm is developed based on a radiative transfer model that simulates top-of-atmosphere TB's whereby effects of atmosphere are calculated from near-surface forcings obtained from a bias-corrected dataset. Validation of SSM/I retrievals against in situ measurements for a two-and-half year period (225 matchups) gives a Root Mean Squared Error of 0.046 m3 m−3. The agreement between retrievals and Noah simulations from the Global Land Data Assimilation System is investigated to further provide confidence in the reliability of SSM/I retrievals at the Plateau-scale. Normalised soil moisture anomalies (N) are computed on a warm seasonal (May–October) and on a monthly basis to analyse the trends present within the products available from July 1987 to December 2008. The slope of linear regression functions between N and time is used to quantify the trends. Both the warm season and monthly N indicate severe wettings of 0.8 to almost 1.6 decade−1 in the centre of the Plateau. Correlations are found by the trend with elevation for the warm season as a whole and the individual months May, September and October. The observed wetting of the Tibetan Plateau agrees with recent findings on permafrost retreat, precipitation increase and potential evapotranspiration decline

Microwave Brightness Temperature Characteristics of Three Strong Earthquakes in Sichuan Province, China

Passive microwave remote sensing technology is an effective means to identify the thermal anomalies associated with earthquakes due to its penetrating capability through clouds compared with infrared sensors. However, observed microwave brightness temperature is strongly influenced by soil moisture and other surface parameters. In the present article, the segmented threshold method has been proposed to detect anomalous microwave brightness temperature associated with the strong earthquakes occurred in Sichuan province, China, an earthquake-prone area with high soil moisture. The index of microwave radiation anomaly (IMRA) computed by the proposed method is found to enhance prior to the three strong earthquakes, 2008 Wenchuan (M = 7.8), 2013 Lushan (M = 6.6), and 2017 Jiuzhaigou (M = 6.5), occurred during 2008-2018 using the Defense Meteorological Space Program Special Sensor Microwave Imager/Sounder F17 satellite data. Our results show that the microwave brightness temperature anomalies appeared about two months prior to the three strong earthquakes. For the Wenchuan and Lushan earthquakes, the enhanced IMRA distributed along the main fault, which is consistent with the variations of our earlier studies of the 1997 Manyi (M = 7.5) and the 2001 Kokoxili (M = 7.8) earthquakes in the region with low soil moisture. For the Jiuzhaigou earthquake, the anomalies distributed around the epicenter and do not indicate the seismogenic structure, which could be due to the presence of a blind fault. It should be noted that quantitative evaluation of IMRA is limited due to infrequent occurrence of earthquakes