Thermal Infrared Brightness Temperature Research Articles

Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign

Abstract. The high temporal resolution of thermal infrared imagery from the Geostationary Operational Environmental Satellites R-series (GOES-R) presents an opportunity to observe mountain snow and forest temperatures over the full diurnal cycle. However, the off-nadir views of these imagers may impact or bias temperature observations, especially when viewing a surface composed of both snow and forests. We used GOES-16 and -17 thermal infrared brightness temperature observations of a flat snow- and forest-covered study site at Grand Mesa, Colorado, USA, to characterize how forest coverage and view angle impact these observations. These two geostationary satellites provided views of the study area from the southeast (134.1° azimuth, 33.5° elevation) and southwest (221.2° azimuth, 35.9° elevation), respectively. As part of the NASA SnowEx field campaign in February 2020, coincident brightness temperature observations from ground-based and airborne IR sensors were collected to compare with those from the geostationary satellites. Observations over the course of 2 cloud-free days spanned the entire study site. The brightness temperature observations from each dataset were compared to find their relative differences and how those differences may have varied over time and/or as a function of varying forest cover across the study area. GOES-16 and -17 brightness temperatures were found to match the diurnal cycle and temperature range within ∼ 1 h and ± 3 K of ground-based observations. GOES-16 and -17 were both biased warmer than nadir-looking airborne IR and ASTER observations. The warm biases were higher at times when the sun–satellite phase angle was near its daily minimum. The phase angle, the angle between the direction of incoming solar illumination and the direction from which the satellite is viewing, reached daily minimums in the morning for GOES-16 and afternoon for GOES-17. In morning observations, warm biases in GOES-16 brightness temperature were greater for pixels that contained more forest coverage. The observations suggest that a “thermal infrared shadow-hiding” effect may be occurring, where the geostationary satellites are preferentially seeing the warmer sunlit sides of trees at different times of day. These biases are important to understand for applications using GOES-R brightness temperatures or derived land surface temperatures (LSTs) over areas with surface roughness features, such as forests, that could exhibit a thermal infrared shadow-hiding effect.

Cross-Calibration of HY-1D/COCTS Thermal Emissive Bands in the South China Sea

Haiyang-1D (HY-1D) is the second operational satellite in China’s Haiyang-1 series of satellites, carrying the Chinese Ocean Color and Temperature Scanner (COCTS) to provide ocean color and temperature observations. The radiometric calibration is a prerequisite to guarantee the quality of the satellite observations and the derived products, and the radiometric calibration of the thermal emissive bands of HY-1D/COCTS can effectively improve the accuracy of sea surface temperature (SST) derived from the thermal infrared data. In this paper, a study on the regional cross-calibration of the COCTS thermal emissive bands is conducted for high-accuracy SST observations in the South China Sea. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the NOAA-20 satellite launched by the National Oceanic and Atmospheric Administration (NOAA) is selected as the calibration reference sensor, and a double-difference cross-calibration method is used for HY-1D/COCTS thermal infrared brightness temperature (BT) evaluation. The results show that the bias of the 11 µm and 12 µm thermal emissive bands of COCTS and VIIRS in the South China Sea are 0.101 K and 0.892 K, respectively, and the differences in BTs between the two sensors show temperature dependence. The cross-calibration coefficients are obtained and used to correct the BT of the COCTS thermal emissive bands. The bias of the BT of the 11 µm and 12 µm bands of COCTS are about 0.01 K after cross-calibration. To further validate the results, COCTS post-calibration data were examined using the NOAA-20 Cross-track Infrared Sounder (CrIS) data as a third-party source. The BT is calculated with the spectral response functions of the COCTS thermal emissive bands using the convolution calculation of the CrIS hyperspectral region observations. The comparison shows a small bias between the post-calibration COCTS thermal emissive band observations and CrIS, which is consistent with the comparison between VIIRS and CrIS. The accuracy of the post-calibration COCTS thermal emissive band BT data in the South China Sea has been significantly improved.

Simulation of Thermal Infrared Brightness Temperatures from an Ocean Color and Temperature Scanner Onboard a New Generation Chinese Ocean Color Observation Satellite

Since 2002, China has launched four Haiyang-1 (HY-1) satellites equipped with the Chinese Ocean Color and Temperature Scanner (COCTS), which can observe the sea surface temperature (SST). The planned new generation ocean color observation satellites also carry a sensor for observing the SST represented by the payload in this paper. We analyze the spectral brightness temperature (BT) difference between the payload and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra for the thermal infrared channels (11 and 12 µm) based on atmospheric radiative transfer simulation. The bias and standard deviation (SD) of spectral BT difference for the 11 µm channel are −0.12 K and 0.15 K, respectively, and those for the 12 µm channel are −0.10 K and 0.03 K, respectively. When the total column water vapor (TCWV) decreases from the oceans near the equator to high-latitude oceans, the spectral BT difference of the 11 µm channel varies from a positive deviation to a negative deviation, and that of the 12 µm channel basically remains stable. By correcting the MODIS BT observation using the spectral BT differences, we produce the simulated BT data for the thermal infrared channels of the payload, and then validate it using the Infrared Atmospheric Sounding Interferometer (IASI) carried on METOP-B. The validation results show that the bias of BT difference between the payload and IASI is −0.22 K for the 11 µm channel, while it is −0.05 K for the 12 µm channel. The SD of both channels is 0.13 K. In this study, we provide the simulated BT dataset for the 11 and 12 µm channels of a payload for the retrieval of SST. The simulated BT dataset corrected may be used to develop SST-retrieval algorithms.

A new calibration correction method for INSAT-3D/3DR brightness temperatures to improve rainfall estimation

ABSTRACT Importance of continuous monitoring of rainfall from Indian geostationary satellites INSAT-3D/3DR over India and surrounding oceans is not only necessary to monitor the performance of the monsoon, but is extremely useful in disaster mitigation support system as well. It has been observed that rain products from INSAT-3D/3DR often show overestimation in certain areas with unrealistic instances of intense rain, which need a closer examination. With this objective, the present study is carried out, which suggests that a non-linear calibration equation for thermal infrared brightness temperatures (Tb) of INSAT-3D/3DR is more appropriate than routinely applied linear equation for rainfall estimation. The study elaborates a new calibration correction method and addresses the requirement of such calibration. To evaluate the performance of proposed method, Hydro-Estimator (HE) operational rainfall products from INSAT-3D/3DR are re-estimated from the newly calibrated Tbs during Indian summer monsoon (June-September), 2020. The re-estimated HE rain not only substantially reduces the instances of overestimation, but also show remarkable improvement in capturing rainfall distribution over India and surrounding ocean. Improvement in RMSE from 8.56 mm/hr to 3.23 mm/hr, when compared with the concurrent IMERG (Integrated Multi-satellitE Retrieval for Global Precipitation Mission (GPM)) rain, shows reliability of the new method. Furthermore, the re-estimated HE rain compares better with in-situ rain gauges observations than the operational HE product with RMSE (bias) reduced from 85.43 mm/day (30.23 mm/day) to 40.02 mm/day (17.07 mm/day), and correlation improved from 0.28 to 0.32. The significance of the new calibration method is also recognized in the rain monitoring over complex hilly terrain and coastal regions of India.

Thermal environment of the Chang’E-5 landing site and its effect on the external temperature of the lander

<p indent="0mm">The thermal environment of the lunar surface is extremely important to the thermal design of the lander, the placement of the detection instruments, and the interpretation of scientific exploration data. Clarifying the source and intensity of radiation on the outer surface of the lander is the key to its thermal management. In this paper, we first reported continuous temperature records over a 47.2 h period from five thermal couple sensors mounted on the auxiliary pillars of the landing gear of Chang’E-5 (CE-5). The recorded temperatures varied from a relatively small range of <sc>245.68–272.52 K</sc> at the beginning to a considerably wider range of <sc>284.86–369.76 K</sc> at the end of the recording period. To analyze the obtained CE-5 temperature records, we first developed a lunar surface thermal environment model with a layered regolith and temperature-dependent thermal physical properties. The model calculated that the ambient temperature of the CE-5 landing site over the sensor recording period increased from 341.40 to <sc>356.15 K.</sc> The calculated temperature was comparable to the estimates based on the <italic>in</italic>-<italic>situ</italic> spectral measurement, whereas it was systematically <sc>6–12 K</sc> higher than Diviner thermal infrared brightness temperature. We further developed a heat conduction model of the sensor-mounted auxiliary pillar and considered the surface temperature and the pillar geometry with respect to the Sun’s and the Earth’s orbital parameters. By introducing an impact factor<italic> F</italic> and via trial and error, we fitted the five CE-5 lunar temperature records with the RMESs of 0.72, 2.14, 0.53, 1.35, and <sc>3.36 K,</sc> respectively. Our analysis showed that the lunar surface thermal environment has a significant effect on the temperatures of both the shaded and sunny sides of the lunar lander. The environmental impact on the shaded side even exceeds that on the sunny side during the CE-5 recording period. The results of this paper are of great significance to both the theoretical research on the mechanism of the lunar thermal environment and the engineering applications in the thermal management design of a lunar lander, site selection of a lunar exploration mission, and temperature-related data interpretations, such as <italic>in</italic>-<italic>situ</italic> spectral data analysis.

Analytical Study of the Changes in Brightness Temperature Based on the Tectonic Field Associated With Three Earthquakes in the Eastern Tibetan Plateau

The thermal infrared brightness temperature (BT) of the eastern Tibetan Plateau (TP) was retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) level-1B data. The multiyear averaged BT background field was subtracted from the punctual BT data to yield monthly BT spatial anomaly, and calculated time series of BT for the secondary blocks. Then, the spatial and temporal changes in the BT of the study area before the Menyuan M6.4, Zaduo M6.2, and Jiuzhaigou M7.0 earthquakes were investigated and analyzed based on the tectonic setting. The results show the following. The spatial BT radiation enhancement frequency rose remarkably before strong earthquakes; each of the three earthquakes was preceded by marked spatiotemporal continuous BT anomalies. The tectonic setting significantly influences the BT anomaly feature. The spatial BT anomaly was not notable in the Qaidam and Qilian block before the Menyuan earthquake; the spatial BT anomaly mainly appeared in the Qiangtang and Bayan Har blocks before the Zaduo and Jiuzhaigou earthquakes. The Qiangtang and Bayan Har block’s BT time series curves have similar features. The Qaidam and Qilian block’s BT time series curves have analogous shapes. The three earthquakes may be regarded as one seismic event induced by a stage of tectonic stress enhancement rather than three independent occasions. The spatial BT anomalous behavior before earthquakes is, to a great extent, like the result of the rock stress loading experiment; the rock compression and the lithosphere-atmosphere-ionosphere coupling (LAIC) may be the main reasons for the intensification of the BT radiation.

Quality Assessment of FY-3D/MERSI-II Thermal Infrared Brightness Temperature Data from the Arctic Region: Application to Ice Surface Temperature Inversion

The Arctic region plays an important role in the global climate system. To promote the application of Medium Resolution Spectral Imager-II (MERSI-II) data in the ice surface temperature (IST) inversion, we used the thermal infrared channels (channels 24 and 25) of the MERSI-II onboard Chinese FY-3D satellite and the thermal infrared channels (channels 31 and 32) of the Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautical and Space Administration (NASA) Aqua satellite for data analysis. Using the Observation–Observation cross-calibration algorithm to cross-calibrate the MERSI and MODIS thermal infrared brightness temperature (Tb) data in the Arctic, channel 24 and 25 data from the FY-3D/MERSI-II on Arctic ice were evaluated. The thermal infrared Tb data of the MERSI-II were used to retrieve the IST via the split-window algorithm. In this study, the correlation coefficients of the thermal infrared channel Tb data between the MERSI and MODIS were &gt;0.95, the mean bias was −0.5501–0.1262 K, and the standard deviation (Std) was &lt;1.3582 K. After linear fitting, the MERSI-II thermal infrared Tb data were closer to the MODIS data, and the bias range of the 11 μm and 12 μm channels was −0.0214–0.0119 K and the Std was &lt;1.2987 K. These results indicate that the quality of the MERSI-II data is comparable to that of the MODIS data, so that can be used for application to IST inversion. When using the MERSI thermal infrared Tb data after calibration to retrieve the IST, the results of the MERSI and MODIS IST were more consistent. By comparing the IST retrieved from the MERSI thermal infrared calibrated Tb data with MODIS MYD29 product, the mean bias was −0.0612–0.0423 °C and the Std was &lt;1.3988 °C. Using the MERSI thermal infrared Tb data after calibration is better than that before calibration for retrieving the IST. When comparing the Arctic ocean sea and ice surface temperature reprocessed data (L4 SST/IST) with the IST data retrieved from MERSI, the bias was 0.9891–2.7510 °C, and the Std was &lt;3.5774 °C.

Evaluating GOES-16 ABI surface brightness temperature observation biases over the central Sierra Nevada of California

Thermal infrared imagery from NOAA's Geostationary Operational Environmental Satellites (GOES) R-series presents an opportunity to observe mountain surface temperatures at high temporal resolution. These observations are needed to better understand the transient surface energy balance, influenced by near-surface air temperatures and water fluxes ranging from evapotranspiration to snowmelt. From geostationary orbit, the GOES Advanced Baseline Imager (ABI) instrument views the Earth from a fixed longitude above the equator. ABI images therefore have increasingly off-nadir view angles and increasingly larger pixel dimensions the further a point on the Earth's surface is from the sub-satellite point. In thermal infrared imagery from ABI, these 2+ km pixels blur together the different surface temperatures of heterogeneous mountain landscapes. We compared GOES-16 ABI band 14 (11.2 μm) brightness temperatures to 90 m spatial resolution ASTER band 14 (11.3 μm) and 1 km spatial resolution MODIS band 31 (11.03 μm) brightness temperatures and investigated how differences change over space and time for a study region in the central Sierra Nevada of California for the 2017–2020 snow seasons. We demonstrated the necessity of orthorectifying ABI imagery of mountain terrain to correct for the parallax effect in off-nadir imagery. This reduced the mean difference between ABI and ASTER ~11 μm brightness temperatures from 1.6 °C to 1.0 °C and increased the r-squared value between ABI and ASTER thermal infrared brightness temperatures from 0.43 to 0.93. The ABI brightness temperatures were found to more closely match those of forest canopy temperatures than snow surface (with RMS differences of 1.2 °C and 3.0 °C respectively), and those of sunlit slopes as opposed to slopes facing away from the sun (with RMS differences of 1.6 °C and 3.4 °C respectively), in coincident ASTER imagery. This work demonstrates the use of GOES ABI, and associated challenges, for observing surface temperatures of forested mountain environments with seasonal snow.

Sea ice surface temperatures from helicopter-borne thermal infrared imaging during the MOSAiC expedition

The sea ice surface temperature is important to understand the Arctic winter heat budget. We conducted 35 helicopter flights with an infrared camera in winter 2019/2020 during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The flights were performed from a local, 5 to 10 km scale up to a regional, 20 to 40 km scale. The infrared camera recorded thermal infrared brightness temperatures, which we converted to surface temperatures. More than 150000 images from all flights can be investigated individually. As an advanced data product, we created surface temperature maps for every flight with a 1 m resolution. We corrected image gradients, applied an ice drift correction, georeferenced all pixels, and corrected the surface temperature by its natural temporal drift, which results in time-fixed surface temperature maps for a consistent analysis of one flight. The temporal and spatial variability of sea ice characteristics is an important contribution to an increased understanding of the Arctic heat budget and, in particular, for the validation of satellite products.

A large-region fog detection algorithm at dawn and dusk for high-frequency Himawari-8 satellite data

ABSTRACT Satellite remote sensing provides effective methods for fog detection at large scales. At dawn or dusk, however, the separation of fog from the surface remains a great challenge because of the minor radiation difference between fog and the surface. This study develops a novel algorithm for fog detection suitable for dawn and dusk from high-frequency data of the Himawari-8 satellite. Methodologically, the area was divided into three subregions according to the distance of the terminator line. In regions at daytime that are far from the terminator line, a fog detection index of the low solar altitude angle (FDI LSAA) was built to isolate the fog through the relationship between the mid-infrared (MIR) brightness temperature (I MIR ) and its difference with the thermal infrared (TIR) brightness temperature (BTD = I MIR – I TIR , where I MIR and I TIR are the brightness temperatures at the MIR and TIR bands). In regions near the terminator line, the fog was extracted from the surface by a Gaussian mixture model (FD-GMM NTL) by the differences in MIR and TIR radiation changes. After that, the fog was further extracted from the low and mid-high clouds by the enhanced low cloud detection index (ELCDI) and by the difference in BTD and TIR characteristics. In regions at night, a BTD threshold value was adopted to detect fog. Validation results demonstrated that the algorithm in this study could precisely detect large-region radiation fog including dawn and dusk, with the overall probability of detection (POD) accuracies range from 76.3% to 89.2% at dawn and 67.3% to 77.0% at dusk. The relatively low accuracy at dusk was mainly attributed to desert in the study area, which has a similar BTD with fog after a day of solar radiation. Results of this study provide new insight for fog detection at dawn and dusk, which enhances the application of remote sensing in meteorology forecasting.

Variation of Thermal Infrared Brightness Temperature Anomalies in the Madoi Earthquake and Associated Earthquakes in the Qinghai-Tibetan Plateau (China)

We processed MODIS data received from ground receiving stations into the spatial range of the Qinghai-Tibetan Plateau (China) and the eastern margin of the plateau, and then 283 K was set as the threshold value to remove the area covered by clouds. The monthly background field was calculated based on 17 years’ data, then we obtained the spatial Brightness Temperature anomaly of the current month by deducting the background field. Furthermore, the Brightness Temperature anomaly curves for secondary tectonic blocks in the plateau were calculated. The data indicated that since June 2020, the Brightness Temperature radiation within the Qinghai-Tibetan Plateau began to increase abnormally, starting from the western part of the study area and expanding eastward to cover the entire plateau. In January 2021, such an anomaly was seen again, extending to the Sichuan-Yunnan Block in the easternmost part of the study area in april. With the ongoing anomaly, a series of moderate and strong earthquakes occurred in the Qinghai-Tibetan Plateau, and finally, on 22 May 2021, the M7.4 earthquake struck the Madoi County. Moreover, according to the internal Brightness Temperature time series curves of the different secondary tectonic blocks, the Brightness Temperature has increased simultaneously since the beginning of 2020. A twofold standard deviation was found in the middle-east segment of the Bayanhar Block and the Qiangtang Block in October 2020, and an almost twofold standard deviation was found in March, while a twofold standard deviation was found in the Sichuan-Yunnan Block in april 2021. The occurrence of earthquakes in the plateau before the Madoi earthquake coincided with an upward trend of the time series curve. The spatial anomaly of Brightness Temperature over the Qinghai-Tibetan Plateau disappeared and the Brightness Temperature time series curve dropped drastically after the Madoi earthquake. The development of spatial anomaly of Brightness Temperature and the time series curve both coincide with the occurrence of earthquakes and are consistent with the generation of tectonic stress in the Qinghai-Tibetan Plateau. Our study showed that thermal infrared Brightness Temperature radiation reasonably reflects regional stress development and enables the detection of anomalies prior to moderate and strong earthquakes.

Rain Area Detection in South-Western Kenya by Using Multispectral Satellite Data from Meteosat Second Generation.

This study presents a rain area detection scheme that uses a gradient based adaptive technique for daytime and nighttime rain area detection and correction from reflectance and infrared (IR) brightness temperatures data of the Meteosat Second Generation (MSG) satellite. First, multiple parametric rain detection models developed from MSG’s reflectance and IR data were calibrated and validated with rainfall data from a dense network of rain gauge stations and investigated to determine the best model parameters. The models were based on a conceptual assumption that clouds characterised by the top properties, e.g., high optical thickness and effective radius, have high rain probabilities and intensities. Next, a gradient based adaptive correction technique that relies on rain area-specific parameters was developed to reduce the number and sizes of the detected rain areas. The daytime detection with optical (VIS0.6) and near IR (NIR1.6) reflectance data achieved the best detection skill. For nighttime, detection with thermal IR brightness temperature differences of IR3.9-IR10.8, IR3.9-WV73 and IR108-WV62 showed the best detection skill based on general categorical statistics. Compared to the Global Precipitation Measurement (GPM) Integrated Mult-isatellitE Retrievals for GPM (IMERG) and the gauge station data from the southwest of Kenya, the model showed good agreement in the spatial dynamics of the detected rain area and rain rate.

Characteristics of Thermal Infrared Anomalies during the Earthquakes in Wenchuan, Lushan in Ya’an and Jiuzhaigou

Satellite thermal infrared observation has advantages over other earthquake observation techniques. With MODIS remote-sensing images from the TERRA satellite, the thermal infrared brightness temperature difference variation rate was used to analyze the observation data prior to three Magnitude-7-and-above earthquakes along the fracture zone of Longmen Mountain, and the result showed that there were thermal infrared brightness temperature anomalies one to two months before these three Magnitude-7-and-above earthquakes, and the earthquakes took place along the boundaries of the area where the anomalies occurred. The observation data show that there have been five times of substantial anomalies in the study area, among which four times were correlated to earthquakes.

Efficient radiative transfer model for thermal infrared brightness temperature simulation in cloudy atmospheres.

An efficient radiative transfer model (ERTM) is developed to simulate thermal infrared brightness temperatures observed by the Advanced Himawari Imager (AHI) in this study. The ERTM contains an alternate mapping correlated k-distribution (AMCKD) scheme, a parameterization for cloud optical property, and a rapid infrared radiative transfer scheme. The AMCKD is employed to calculate the gaseous absorption in the inhomogeneous thermodynamic atmosphere. The optical properties of clouds are parameterized by the effective length for ice clouds based on the Voronoi model, and by the effective radius for water clouds based on the Lorenz-Mie theory. The adding method of four-stream discrete ordinates method (4DDA) is extended to be able to calculate the thermal infrared radiative intensity varying with the zenith angle in ERTM. The efficiency and accuracy of ERTM are evaluated by comparing with the benchmark model which is composed of discrete ordinate radiative transfer (DISORT) and line-by-line radiative transfer model (LBLRTM). Under the standard atmospheric profiles, the root mean square error (RMSE) of simulated brightness temperatures reaches a maximum of 0.21K at the B16 (13.28 µm) channel of AHI. The computational efficiency of ERTM is approximately five orders of magnitude higher than that of the benchmark model. Moreover, the simulated brightness temperatures by ERTM are highly consistent with the rigorous results and AHI observations in the application to the Typhoon Mujigae case.

Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records

The Vegetation Health Index (VHI) is widely used for monitoring drought using satellite data. VHI depends on vegetation state and thermal stress, respectively assessed via (i) the Vegetation Condition Index (VCI) that usually relies on information from the visible and near infra-red parts of the spectrum (in the form of Normalized Difference Vegetation Index, NDVI); and (ii) the Thermal Condition Index (TCI), based on top of atmosphere thermal infrared (TIR) brightness temperature or on TIR-derived Land Surface Temperature (LST). VHI is then estimated as a weighted average of VCI and TCI. However, the optimum weights of the two components are usually not known and VHI is usually estimated attributing a weight of 0.5 to both. Using a previously developed methodology for the Euro-Mediterranean region, we show that the multi-scalar drought index (SPEI) may be used to obtain optimal weights for VCI and TCI over the area covered by Meteosat satellites that includes Africa, Europe, and part of South America. The procedure is applied using clear-sky Meteosat Climate Data Records (CDRs) and all-sky LST derived by combining satellite and reanalysis data. Results obtained present a coherent spatial distribution of VCI and TCI weights when estimated using clear- and all-sky LST. This study paves the way for the development of a future VHI near-real time operational product for drought monitoring based on information from Meteosat satellites.

TRMM-Based Optical and Microphysical Features of Precipitating Clouds in Summer Over the Yangtze–Huaihe River Valley, China

The optical and microphysical features of precipitating clouds are key information for studying the satellite-based precipitation estimation, cloud radiative effects, aerosol–cloud–precipitation interactions, cloud and precipitation parameterization in weather and climate models. In this study, 15-year synchronous spectral and radar observations from the TRMM satellite were used to statistically explore the optical and microphysical features of precipitating clouds (PCs), including cloud effective radius (CER), cloud optical thickness (COT), cloud water path (CWP), thermal infrared brightness temperature at channel 4 (TB4) of cloud top, and storm top height (STH) and their relationships with surface rain rates in summer over Yangtze–Huaihe River Valley (YHRV). Results show that the optical and microphysical features of PCs/stratiform PCs/convective PCs vary with geographical locations in summer over YHRV, due to the different ambient meteorological and topographical conditions. Higher CER/COT/CWP/STH and lower TB4 mainly locate at areas of bigger rain rates. For PCs, their spatial distribution of CER is mainly dominated by stratiform PCs, while their spatial distribution of COT/CWP is mainly dominated by convective PCs. Moreover, stratiform precipitation is the dominant form in summer over YHRV and, thus, most PCs present vertical structures of optical and microphysical features as stratiform PCs. Stratiform PCs are usually thicker and contain more water vapor with bigger cloud particles than convective PCs (including deep and shallow convective PCs). In addition, existing shallow convective PCs are associated with lower storm heights and warmer cloud tops. Finally, surface rain rates of PCs (convective/stratiform PCs) increase gradually with the increment of CER/COT/CWP/STH, especially under 5 (15/5) mm/h. Similar relationship between surface rain rates and COT/CWP for shallow convective PCs is also found under 0.75 mm/h. Surface rain rate of PCs (convective/stratiform PCs) with cold cloud tops (TB4 264 K), surface rain rate usually increases as CER decreases, which suggests that aerosol indirect effects are dominant in lower PCs, because over pollution regions abundant aerosols enter into lower clouds more easily and then suppress the development of shallow convective PCs.

FengYun-3C VIRR Active Fire Monitoring: Algorithm Description and Initial Assessment Using MODIS and Landsat Data

The Visible and Infra-Red Radiometer (VIRR) is an improved third-generation earth observation sensor that has channels ranging from the visible to thermal bands and is carried on board the Chinese FengYun-3C satellite. The VIRR instrument provides full global coverage at a spatial resolution of 1 km. It is neither appropriate nor correct to simply duplicate the parameters used in algorithms designed for other sensors. Hence, this paper proposes an active fire-monitoring algorithm designed for the VIRR sensor. A newly proposed concept—the “infrared channel slope”—is employed in the algorithm, which can detect active fire pixels by identifying deviations in their mid-infrared and thermal infrared brightness temperatures. “Dynamic thresholds” are also used to allow the algorithm to adapt to different situations. Different fire events that occurred in different parts of the world between 2014 and 2016 are selected to test the robustness of the algorithm. The testing consists of two parts: a rough assessment using products of a similar spatial resolution and then a detailed assessment based on fine spatial resolution images. In the rough assessment part, the results are compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) Fire and Thermal Anomaly product (MOD14A1) and the China Meteorological Administration’s Global Fire References (GFR) products from the National Satellite Meteorological Center. In the detailed assessment, imagery acquired by the Landsat-7/Enhanced Thematic Mapper Plus and the Landsat-8/Operational Land Imager is used. The MODIS and Landsat data are utilized as reference data to validate the accuracy while the comparison with the GFR products is carried out to demonstrate the advantages of this method. The assessment demonstrates that the algorithm produces comparable results to those obtained using MOD14A1 and is a significant improvement compared with GFR.

Tracking of Thermal Infrared Anomaly before One Strong Earthquake-In the Case of Ms6.2 Earthquake in Zadoi, Qinghai on October 17th, 2016

The detection and tracking process of thermal infrared anomaly before Ms6.2 earthquake in Zadio, Qinghai on October 17th, 2016, are reviewed and analyzed; then the different characteristics of thermal infrared brightness temperature data before this earthquake is described in details. According to these characteristics, the tracking process of thermal anomaly is divided into four stages, respectively identification stage, pre-judgment stage, tracking and approaching stage and verification stage. The anomaly forms and turning signals focused in each stage can provide clear indication information for earthquake pre-judgment; finally, the prediction efficiency and technical issues of this method are illustrated and discussed.

Scale dependence of cirrus horizontal heterogeneity effects on TOA measurements – Part I: MODIS brightness temperatures in the thermal infrared

Abstract. This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 m to 10 km. A realistic 3-D cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloud-top and base altitudes at 10 and 12 km, respectively, consisting of aggregate column crystals of Deff = 20 µm), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB) and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial-resolution results (above ∼ 250 m) with averaged values of up to 5–7 K, while the IPAE mainly impacts the high-spatial-resolution results (below ∼ 250 m) with average values of up to 1–2 K. A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 m. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

Suomi NPP VIIRS/DNB imagery of nightglow gravity waves from various sources over China

Observation of atmospheric gravity waves provides critical insight to weather and climate researches. Some gravity waves survive middle-atmospheric filtering as they propagate upward to the mesopause region and disturb the nightglow emission layer near 90km AMSL, making the waves visible to both ground and space sensors. Based on the high-resolution images obtained by Day/Night Band on NOAA/NASA Suomi National Polar-orbiting Partnership environmental satellite, four representative gravity wave events over China are analyzed. With the help of VIIRS thermal infrared brightness temperature and MERRA wind data, we surmise that these waves originated from orography, thunderstorm, typhoon and baroclinic, respectively. Nadir viewing satellite observations cover a wide area and unlike the surface-based perspective, do not suffer from cloud obscuration. These new observations over remote areas provide important guidance for future deployment of ground based camera systems in China.