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Wheat (Triticum aestivum) yield predictions can be improved by using multispectral remote sensing to identify different genotypes and crop growth stages. We propose an innovative machine learning technique aimed at classifying diverse wheat crop genotypes and providing accurate estimations of plant age. Multispectral reflectance data was obtained from different sites where various wheat genotypes were cultivated. This approach involved analyzing incoming radiation and canopy light reflectance across five distinct spectral bands using a multispectral radiometer. The newly collected remote sensing data was utilized as input for the machine learning algorithm. Impressively, the random forest model achieved an accuracy rate of 98.77% in wheat crop genotype classification. Furthermore, the proposed approach's effectiveness was confirmed through a 10‐fold cross‐validation mechanism. Moreover, a multiple linear regression model for predicting the age of wheat genotypes explained 91% of the observed variation. These findings signify significant progress in wheat crop genotype and age prediction, ultimately leading to enhanced wheat yield. Core Ideas: This research addresses a significant challenge in wheat crop genotype and age prediction.We propose an innovative machine learning methodology to classify different wheat crop genotypes.We collected different wheat seed genotype samples using the multispectral radiometer. [ABSTRACT FROM AUTHOR]

The ground‐based laser heterodyne radiometer (LHR), which exhibits the advantages of small size, high spectral resolution, and easy integration, has been used for the remote sensing detection of several gases to meet a wide range of needs. This study aims to optimize the laser heterodyne system for detecting CO2 gas by focusing on existing research. Firstly, using the all‐fiber laser heterodyne detection system built by our research group, the power spectrum associated with the radio frequency signals of the detection system is discussed under different conditions: under no irradiation, under sunlight only, under sunlight and laser irradiation at the absorption peak, and under a filter in the spectrum range of 185–270 MHz. Signal‐to‐noise ratios (SNRs) of the high‐resolution spectrum have been obtained using different filter bands of 185–270, 225–270, and 225–400 MHz. Finally, the filter in the 225–270 MHz band, which has the highest SNR, is selected. Consequently, the resolution is improved and the system is further optimized. Furthermore, an optical fiber attenuator is used to change the power of the local oscillator light entering the system, and hyperspectral spectra with varying percentages of input energy and total energy are obtained. When the laser attenuation reaches 40%, the optimal SNR of the system is 486 and can be further improved to meet the expected requirements. This study will provide insights for improving the applicability of laser heterodyne technology in atmospheric sounding. [ABSTRACT FROM AUTHOR]

The tropospheric delay acquired by the Global Navigation Position System (GPS) Precise Point Positioning (PPP) is continuous and steady, less affected by rainfall. The Water Vapor Radiometer (WVR) can provide real‐time meteorological parameters but is more sensitive to high‐frequency information in troposphere. To explore the use of WVR‐retrieved tropospheric delay and assist other geodetic techniques for atmospheric correction, the tropospheric delay from WVR and co‐located GPS at Shanghai, Beijing, Kunming, and Urumqi stations in China are compared. For the inconsistent values of WVR‐PPP zenith wet delay, the variations of the tropospheric delay from WVR and GPS before and after the rainfall were statistically analyzed. The results suggest that, for the rain rate ranging from 0.1 to 50 mm/hr, the impact of rainfall on WVR could last from 10 min before to 30 min after the rainfall. With filtering WVR data based on meteorological parameters and rain rate, the zenith wet delay between WVR and PPP at Shanghai shows good consistency, the root mean square (RMS) is 6.11 mm, correlation is 0.997, and the RMS in the other three stations ranges from 16.35 to 25.16 mm (correlation ranges in 0.794–0.951). The analysis indicates that the tropospheric delay of WVR is reliable to be applied to space geodetic techniques correction in real‐time with filtering to reduce the effect of rainfall, water vapor, and liquid water variability. Key Points: Comparison of zenith wet delay(ZWD) from water vapor radiometer, co‐located GPS station observations in high temporal resolutionQuantitative analysis of the magnitude and duration of rainfall effects on the zenith wet delay from water vapor radiometer and GPSSuch data analysis and processing might be valuable for assimilating multi‐source data on tropospheric wet delay [ABSTRACT FROM AUTHOR]

Soiling can greatly reduce both the efficiency of photovoltaic (PV) installations and the signals of radiometers. The knowledge of the current soiling losses of a PV installation can be used to optimize the cleaning schedule and to avoid false alarms related to other issues that might cause underperformance. Underperformance can be detected by comparing measured to modeled PV production derived using pyranometer or reference cell measurements. Soiled pyranometers or reference cells lead to too low modeled PV production so that PV soiling or other errors might not be detected. So far, soiling sensors either require frequent cleaning or they use indirect measurements to derive the soiling loss (e.g., analysis of backscattering signal or imaging of dust on a glass surface). Currently, the soiling loss of pyranometers or outdoor reference cells uses the comparison to another frequently cleaned device of the same model. To avoid time‐consuming maintenance of the sensors and to avoid additional sensors as much as possible, we developed a new method for measuring PV and radiometer soiling losses. The method makes use of a characterized lamp that is protected from soiling by a collimator and that illuminates the pyranometer or reference cell each night for some time. Comparing the signals of one night to the signal obtained at a night shortly after the last cleaning of the sensor, its soiling loss can be derived. To validate the measurements of soiling losses for the pyranometer and the reference cell, the soiling losses of the devices are also derived by comparing their signals to those of a clean sensor of the same type. These reference instruments are calibrated relative to the test devices so that deviations indicate the soiling loss of the test sensors. The first outdoor tests with 4 months of data show a good agreement with the reference measurements of the soiling losses. The accuracy of the method is estimated to be similar to that of the reference method, which involves the daily cleaning of the reference devices. [ABSTRACT FROM AUTHOR]

The management of radiant exposure to ultraviolet (UV) radiation, especially in the wavelength range from 100 nm to 280 nm (i.e. UV‐C), is important for virus inactivation or photobiological safety. Recently, many commercial UV radiometers have been used to measure UV‐C irradiance for industrial and public applications. The accuracy of the four types of commercial UV radiometers was investigated by comparing the reference irradiance values obtained from the spectral irradiance standard. It was found that the displayed values of the UV radiometers have discrepancies, such that the measured value can be more than twice the actual value in a certain case. The spectral mismatch between the calibration and test sources is a major factor in the discrepancies in the UV‐C measurements. With spectral mismatch correction, most corrected values show a tendency to improve the result to approaching the reference values within 20%. Users need to provide spectral information about the source and radiometer used for UV‐C measurement. [ABSTRACT FROM AUTHOR]

This paper examines precipitation retrievals from Kidd et al. (2022, https://doi.org/10.3390/rs14132992) by applying the Precipitation Retrieval and Profiling Scheme to data observed by the NASA Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter‐wave Sounder (TMS) onboard the TROPICS Pathfinder satellite, a precursor to the TROPICS mission. We first compare the TMS precipitation retrieval performance over ocean with those from seven current operational passive microwave radiometers, including four conical scanning sensors [Special Sensor Microwave Imager/Sounders (SSMISs) onboard F16/F17/F18 satellites, and Advanced Microwave Scanning Radiometer 2 (AMSR2)] and three cross track scanning sensors [Microwave Humidity Sounders onboard NOAA19 and MetOpB satellites, and the Advanced Technology Microwave Sounder onboard the National Polar‐orbiting Partnership satellite], using precipitation estimates from Global Precipitation Measurement Mission Microwave Imager (GMI) as the reference. We show that TMS performs similarly to the current operational cross track scanning sensors, while worse than conical scanning sensors largely due to the lack of low frequency channels (e.g., 19 GHz). Second, we create an adjusted TMS precipitation retrievals by combining the original TMS precipitation and the precipitation propagated from AMSR2 and SSMISs to the time/location of the TMS overpass, using our previously developed microwave‐to‐microwave propagation technique. Results show that the adjusted TMS precipitation performs better than the original TMS estimates. For example, the correlation of the original TMS and GMI estimates is 0.35 but increases to 0.49 when the adjusted TMS result is compared to GMI. The propagation technique lays the foundation to improve TMS precipitation when incorporating them into level‐3 merged products. Plain Language Summary: Passive microwave radiometers provide the essential inputs for generating global high‐quality precipitation estimates and can be classified into cross track scanning and conical scanning sensors. While radiometers onboard large satellites currently dominate in providing observations, small satellites are rapidly emerging with novel designs and high‐performance instruments at a much lower cost. The Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) is a small satellite mission funded by NASA and developed at Massachusetts Institute of Technology, Lincoln Laboratory, with its first satellite, the TROICS Pathfinder launched in June 2021. The payload is the TROPICS Millimeter‐wave Sounder (TMS), a cross‐track scanning radiometer. The performance of TMS precipitation retrieval by Precipitation Retrieval and Profiling Scheme has been evaluated over ocean. Using TROPICS Pathfinder observations, we show that TMS performs similarly to current operational cross‐track scanning sensors, while performing worse than conical scanning radiometers. Additionally, we improve TMS's precipitation retrievals by combining the original TMS estimates with precipitation estimates from high‐information‐content conical scanning radiometers propagated to the time/location of the TMS overpass. This study may enhance the usefulness of the TMS precipitation products and is especially useful when incorporating them into widely used global gridded precipitation products. Key Points: TMS retrievals are comparable to current operational cross‐track scanning radiometersTMS retrievals are worse than those from conical scanning radiometersTMS retrievals can be improved by incorporating retrievals from conical scanning radiometers [ABSTRACT FROM AUTHOR]

An integrated optics method, using hollow fibers which easily ensures optimal beam alignment of the local oscillator (LO) and incoherent solar radiation and promotes high photomixing efficiency, is proposed for a compact, rugged, and high‐efficiency all hollow fiber‐coupled photomixing assembly in the mid‐infrared (IR). The method is adopted for the design of an all‐hollow fiber‐coupled mid‐IR laser heterodyne radiometer (LHR) using an 8 µm external‐cavity quantum cascade laser as LO. Coupling efficiency, attenuation coefficients, total‐loss transmission, and output beam divergence of the HE11 mode in hollow fibers for the all hollow fiber‐coupled mid‐IR LHR are discussed in detail and are shown to highly depend on the launch conditions. Meanwhile, the selection of input and output coupling lenses that are associated with the hollow fibers is also studied for achieving the theoretical loss of the HE1m mode in hollow fibers and high heterodyne performance. It shows that using a hollow fiber for photomixing supersedes conventional spatially separated optics. [ABSTRACT FROM AUTHOR]

The Diviner Lunar Radiometer Experiment on the Lunar Reconnaissance Orbiter (LRO) has been mapping the surface temperatures of the Moon since 5 July 2009. Diviner has since collected over 500 billion radiometric measurements with excellent spatial and local time coverage. However, the most recently published high‐resolution Diviner global maps only use data collected from 2009 to 2016. In this work, we compile ∼13 years of Diviner data to produce improved global maps of nighttime brightness temperature, bolometric temperature, regolith temperature, and rock abundance (RA). Errors in Diviner's pointing have been corrected and past effective field of view modeling has been optimized to improve data georeferencing without spatial interpolation. We estimate an effective resolution of ∼330 m longitudinally and ∼700 m latitudinally at the equator, which corresponds to an improvement of ∼3.5× longitudinally and ∼1.3× latitudinally. In addition, we develop a thermal model that accounts for indirect scattering and emission from surrounding topography. The resulting temperature anomaly maps better highlight variations in temperature caused by thermophysical properties by removing most topographic effects. These improvements allow for the identification of smaller and fainter thermal features than was previously possible. The improved effective resolution of Diviner maps allows for excellent spatial correlation with other high‐resolution data sets. To demonstrate this, we compare Diviner RA to a manual survey of boulders in the Apollo 17 landing site region. We show that Diviner RA correlates well with the areal fraction of rocks larger than ∼1–2 m in diameter visible in LRO Camera imagery. Plain Language Summary: The Diviner Lunar Radiometer Experiment on board the Lunar Reconnaissance Orbiter has been mapping the temperature of the lunar surface since 5 July 2009. Past Diviner data has been used to produce global maps of nighttime temperature and to determine the thermal properties of the surface. However, the most recently published global maps only used data collected from 2009 to 2016. We recreate these global maps using all data available through July 2022: over 5 years of additional data. We implement several improvements, including a correction for errors in instrument pointing, which result in an increase in effective resolution of ∼3.5× and ∼1.3× in the longitudinal and latitudinal directions, respectively. This allows lateral brightness temperature variations to be resolved at a finer scale than was previously possible. In addition, we develop a model that mostly removes the effect of topography on nighttime temperatures. The resulting maps better highlight differences in temperature that are caused by variations in the thermal properties of the surface. Key Points: ∼Thirteen years of Diviner data have been compiled to update the previously published Diviner nighttime temperature and rock abundance mapsImproved georeferencing results in sharper maps with an increase in effective resolution of ∼3.5× longitudinally and ∼1.3× latitudinallyThermal modeling which includes terrain scattering and emission removes most of the effects of topography on nighttime temperatures [ABSTRACT FROM AUTHOR]

Porous polymer‐based Terahertz (THz) absorbers possess strong absorption with broadband, lightweight, and flexible features. Thus these are widely desired in THz electromagnetic shielding, radar‐cross‐section reduction, radiometer calibration, etc. However, the harsh environment of humidity, corrosiveness, and dustiness undermines the performance and service lifetime of the porous absorbers. Here, based on Ti3C2Tx MXene sponge composite foam (MSF), a superhydrophobic broadband THz absorber on a large pore‐size porous architecture by a joint hydrophobic strategy is realized. Results show that the apparent contact angles and roll‐off angles of the modified MSF reached 159.0° and 7.6°, while maintaining an ultra‐high absorption rate of 99.6% in the frequency range of 0.3–1.2 THz. Furthermore, the special Micro‐Nano hierarchical structures render the absorber a strong bounce‐off ability to the droplets of an aqueous solution. These water‐repellent properties endow the absorber the versatility of self‐cleaning and anti‐corrosion, thus can be widely applied in many scenarios including THz remote sensing, communication, and security screening as well. [ABSTRACT FROM AUTHOR]

Uncertainty in Arctic top‐of‐atmosphere (TOA) radiative flux observations stems from the low sun angles and the heterogeneous scenes. Advancing our understanding of the Arctic climate system requires improved TOA radiative fluxes. We compare Cloud and Earth's Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation‐IceBridge Sea and Ice Experiment (ARISE) airborne measurements using two approaches: grid box averages and instantaneously matched footprints. Both approaches indicate excellent agreement in the longwave and good agreement in the shortwave (SW), within 2σ uncertainty considering all error sources (CERES and airborne radiometer calibration, inversion, and sampling). While the SW differences are within 2σ uncertainty, both approaches show a ∼−10 W m−2 average CERES‐aircraft flux difference. Investigating the source of this negative difference, we find a substantial sensitivity of the flux differences to the sea ice concentration data set. Switching from imager‐based to passive microwave‐based sea ice data in the CERES inversion process reduces the differences in the grid box average fluxes and in the sea ice partly cloudy scene anisotropy in the matched footprints. In the long‐term, more accurate sea ice concentration data are needed to reduce CERES TOA SW flux uncertainties. Switching from imager to passive microwave sea ice data, in the short‐term, could improve CERES TOA SW fluxes in polar regions, additional testing is required. Our analysis indicates that calibration and sampling uncertainty limit the ability to place strong constraints (<±7%) on CERES TOA fluxes with aircraft measurements. Key Points: Overall, excellent agreement is found between the satellite and aircraft top‐of‐atmosphere (TOA) radiative flux observationsSubstantial sensitivity of the Cloud and Earth's Radiant Energy System (CERES) inversion process is found to the sea ice data set, more accurate sea ice data are neededCalibration and sampling uncertainty limit the ability to place strong constraints (<±7%) on CERES TOA fluxes with aircraft measurements [ABSTRACT FROM AUTHOR]

Lunar collapse pits may provide access to subsurface lava tubes of unknown extent. We present Diviner Lunar Radiometer measurements showing that the Mare Tranquillitatis and Mare Ingenii pits exhibit elevated thermal emission during the night, ∼100 K warmer than the surrounding surface. Using these data, along with computational thermophysical models, we characterize the thermal environment inside pits and potential caves. Near the equator, peak day‐time temperatures on regolith‐covered pit floors can potentially reach >420 K, whereas temperatures beyond the opening in permanent shadow would maintain a nearly constant temperature of ∼290 K, similar to that of a blackbody cavity in radiative equilibrium. Thermal IR measurements such as those of Diviner can readily detect pit thermal signatures but would be insensitive to the existence of caves they may host, as the latter would only induce a 0.1 K increase to night‐time temperatures of the overlying surface. Plain Language Summary: Since the discovery of pits on the Moon by JAXA's SELENE spacecraft in 2009, there has been interest in whether they provide access to caves that could be explored by rovers and astronauts. These features are likely created by the ceiling of a lava tube (or more generally, cave) collapsing. Using data from the Diviner instrument aboard the Lunar Reconnaissance Orbiter, which has been continuously measuring the temperature of the lunar surface for over 11 years, we thoroughly characterized the environment of one prominent pit. Located in Mare Tranquillitatis, the pit's thermal environment is more hospitable compared to anywhere else on the Moon, with temperatures varying minimally around a comfortable 17°C (or 63° F) wherever the Sun does not shine directly. If a cave extends from a pit such as this, it too would maintain this comfortable temperature throughout its length, varying by less than 1°C over an entire lunar day. Although we cannot be completely certain of a cave's existence through remote observations, such features would open the door for future exploration and habitation on the Moon: they could provide shelter from dramatic temperature variations present elsewhere on the lunar surface. Key Points: Lunar pits stay warmer than the surface during the night, with the floor maintaining temperatures >230 K according to computational modelsCaves stemming from lunar pits would behave like blackbody cavities at ∼290 K and have nearly invariable temperatures far from the openingLunar caves would provide a temperate, stable, and safe thermal environment for long term exploration and habitation of the Moon [ABSTRACT FROM AUTHOR]

Irregular mare patches (IMPs) are enigmatic features in the lunar maria that are characterized as having smooth mounds surrounded by uneven or blocky terrain. The IMPs appear anomalously young compared to surrounding maria, with crater counting methods estimating IMPs to be <100 Myr old and established measures of maturity showing that IMPs are relatively immature. Some studies propose that IMPs are the result of recent basaltic volcanism or episodic outgassing of volatiles, while others propose that the IMPs are of a similar age to the surrounding maria and appear geologically young due to unique physical properties resulting from late‐stage eruption dynamics. Here we present observations from the Lunar Reconnaissance Orbiter Diviner Lunar Radiometer Experiment for eight of the largest IMPs. We find that IMPs are slightly rockier than typical mare surfaces, and the fines components of a number of IMPs have relatively low thermal inertia. The IMP Ina has noticeably lower thermal inertia than the other IMPs. We suggest that the other IMPs (which in many cases are smaller and have ambiguous or gradational contacts with the surrounding maria) could contain similarly low thermal inertia material as Ina, but that it is not fully resolvable with Diviner. We interpret lower‐thermal inertia material as being less‐consolidated or containing fewer small rocks than typical regolith. This would be consistent with elements of a number of proposed formation hypotheses; however, higher spatial resolution is needed for a full comparison of the thermophysical properties of the different IMPs and different terrains within each IMP. Plain Language Summary: Irregular mare patches (IMPs) are small volcanic features on the Moon that are suggested by some to have formed relatively recently (within the past 100 Myr) compared with the majority of the lunar surface. Other studies suggest that IMPs are of a similar age to their surrounding maria, but appear young due to their unique physical properties. In this work, we investigate the thermophysical properties of eight of the largest lunar IMPs using data from the Diviner Lunar Radiometer Experiment, an instrument onboard the Lunar Reconnaissance Orbiter. We find that the regolith at a number of the IMPs have relatively low thermal inertia, indicating that the material there is less consolidated or contains fewer small rocks than typical lunar regolith. One IMP in particular (named Ina) has noticeably lower thermal inertia than the other IMPs, which we suggest could be due to the large size and more distinct edges of the units within Ina compared with the other IMPs. Our results are consistent with a number of the proposed formation hypotheses; however, given observational limitations due to the small size of many of the IMPs we cannot definitively constrain the formation mechanism. Key Points: Irregular mare patches (IMPs) generally have higher rock abundance (RA) than typical maria, but lower RA than rocky crater ejectaThe regolith fines component of IMPs generally has lower thermal inertia than expected based on their RAIna has lower thermal inertia than the other IMPs, displaying similar H‐parameter values to a nearby pyroclastic deposit but with higher RA [ABSTRACT FROM AUTHOR]

The ratio between fluorescence (F) and chlorophyll‐a (Chl)—where fluorescence is measured with a saturating fluorometer—is variable in the world's oceans, with the highest ratios and highest variability observed in the Southern Ocean. While species composition and Chl packaging per cell are strong drivers for the observed variability, additional factors, including iron limitation, have to this date not specifically been evaluated. Radiometers on biogeochemical (BGC)‐Argo floats allow for an independent estimate of Chl concentration that is based on the light attenuation coefficient, Kd. Making use of 4,000 radiometry profiles from BGC‐Argo floats in the Southern Ocean, we estimate Chl based on Kd and investigate the variability in F/Chl. Our analysis reveals a positive correlation between F/Chl and a proxy for iron limitation based on non‐photochemical quenching dynamics. The strong influence of iron limitation on F/Chl is further corroborated by data from Southern Ocean phytoplankton cultures. Plain Language Summary: Phytoplankton fluorescence is a relatively easy and consistent measurement that can be made in the ocean. The measured fluorescence stems directly from the chlorophyll contained in phytoplankton cells and is therefore very specific to the tiny plants. Great oceanic coverage of fluorescence measurements is achieved because fluorometers can be mounted on autonomous platforms such as gliders and floats, yielding reliable data for years without human intervention. But there is a problem with this measurement: fluorescence does not equal chlorophyll, and the factor for the conversion of fluorescence to chlorophyll varies almost 10‐fold across the world's oceans. The largest conversion factors, with the highest variability, are observed in the Southern Ocean. We know that things such as phytoplankton species composition, nutrient status, and acclimation to light all affect the conversion factor. Using data from biogeochemical Argo floats and from laboratory studies, we show in this study that iron limitation also significantly increases the fluorescence‐chlorophyll conversion factor, and that iron limitation may indeed be a key driver for the high conversion factors observed in the Southern Ocean. Key Points: Fluorescence/chlorophyll ratios in the Southern Ocean are consistently higher and more variable than the global averageBiogeochemical‐Argo data and phytoplankton culture studies suggest increased fluorescence/chlorophyll ratios are linked to iron limitationThe mean fluorescence/chlorophyll ratio observed was 3.79, and can be used to scale fluorescence data from the Southern Ocean [ABSTRACT FROM AUTHOR]

Microwave remote sensing technology has been applied to produce soil moisture (SM) retrievals on a global scale for various studies and applications. However, due to the limitations of current technology, the native spatial resolution of currently available passive microwave SM products is on the order of tens of kilometers, and this resolution cannot be used to characterize SM variability on a regional scale. To overcome this limitation, a downscaling algorithm based on the thermal inertia theory–derived relationship between SM and temperature difference was developed using outputs from the Global Land Data Assimilation System–Noah Land Surface Model and the land long‐term data record–Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) dataset and applied to the Aqua Moderate Resolution Imaging Spectroradiometer land surface temperature/NDVI data to produce a downscaled 1‐km Soil Moisture Active Passive (SMAP) radiometer daily SM product, respectively, at 6:00 a.m. and 6:00 p.m. on a global scale from 2015 to 2020. The evaluation results reveal that the downscaling model performs better in the middle or low latitudes than in high latitudes. It also performs better in warm months than in cold months. The in situ SM observations from dense networks around the world were used to validate the 1‐km and enhanced 9‐km SMAP SM data. The validation metrics indicated that both the 1‐km and 9‐km SM data have overall overestimation trends, and the unbiased RMSE (0.063 m3 m–3 on average), mean absolute error (0.052 m3 m–3 on average), and spatial standard deviation (0.025 m3 m–3 on average) of the 1 km data are generally more accurate than the metrics of the 9‐km SM data, which indicates that the downscaled data provide reliable observed SM information. Core Ideas: The global scale daily 1‐km SMAP SM data are produced by the visible/infrared downscaling algorithm.The downscaling model performs better in middle/low‐latitude regions and in warm seasons.Validation results show that the 1‐km SM data outperform the 9‐km data. [ABSTRACT FROM AUTHOR]

Supercooled water clouds (SWCs) have significant impacts on the Earth's radiation balance, aircraft ice accretion and precipitation augmentation. This study introduces an efficient algorithm to detect SWCs from passive radiometers, which combines information from the reflectance difference between 1.61 and 2.25 μm channels, the brightness temperature difference between the 8.5 and 11 μm channels, and the cloud top temperature. Validated by space radar and lidar measurements, our algorithm can correctly detect 91% of SWC pixels, better than current Visible Infrared Imager Radiometer Suite operational product. SWCs are found mostly over the mid‐ to high‐latitude oceans and have a global occurrence frequency of ∼8% in cloudy skies. Since the channels used for the detection are available in most current operational polar and geostationary satellite radiometers, this SWC detection algorithm can be easily implemented for operations such as cloud monitoring, aviation safety, and SWC‐related weather modification. Plain Language Summary: Supercooled water clouds (SWCs) are clouds with temperatures under the freezing point but still containing liquid water droplets. The detection of SWCs is crucial for aviation safety as aviation accidents are frequently caused by the accumulation of supercooled water droplets on airplanes. Detecting SWCs is also critical for artificial precipitation because the implementation is highly dependent on SWC contents. Moreover, SWCs are of great importance in the Earth's radiation budget. However, since SWCs from passive radiometer measurements are normally determined with empirical relationships of the channel radiance and cloud properties, the results are often subject to certain biases or required pre‐retrieved cloud properties. This study introduces a simple but efficient detection algorithm to identify SWCs on a global scale from the Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Suomi‐National Polar‐orbiting Partnership (NPP) satellite. Our algorithm is able to detect over 90% occurrence of SWCs, which accounts for ∼8% among all cloudy sky, with most located over the mid‐ to high‐latitude oceans. Our algorithm can be used for geoscience researches, such as estimating the cloud radiative effect, and for applications such as aviation safety and weather modification operations. Key Points: An efficient algorithm to detect supercooled water clouds (SWC) from passive radiometer measurements is developedThe algorithm correctly identifies 91% of SWCs determined by active sensors, significantly better than that in the Visible Infrared Imager Radiometer Suite (VIIRS) operational productThe passive radiometer VIIRS suggests a global SWC occurrence frequency of ∼8% in cloudy skies [ABSTRACT FROM AUTHOR]

In this paper, two improved asymmetric parallel‐coupled microstrip bandpass filters with center frequencies of 89 GHz and 150 GHz were designed and implemented. The improvement of the circuit structure is based on the rotation of several asymmetric parallel‐coupled microstrip line segments, which achieves a great area reduction compared to the conventional structure. The improved bandpass filters were designed and optimized based on the conventional structure. The measured results show that the return loss of the W‐band bandpass filter is better than 16 dB and that of the D‐band bandpass filter is better than 15 dB within the passband. The insertion loss is less than 2.3 dB and 2.5 dB within the passband for W‐band and D‐band bandpass filters, respectively. These results verify the feasibility of the improved asymmetric parallel‐coupled microstrip line bandpass filter as a broadband pre‐filter for the direct detection system of a CubeSat radiometer. [ABSTRACT FROM AUTHOR]

The performance of an atmospheric water vapor radio path delay measurement and correction is reported using observations of the Juno Spacecraft during gravity field mapping of Jupiter. The Juno Gravity Science instrument measures the Doppler shift on the radio signals between the Juno spacecraft and the Earth‐based observing stations of NASA's Deep Space Network (DSN) during times of closest approach to Jupiter in order to map Jupiter's gravity field. These Doppler measurements are affected by noise sources between the spacecraft and DSN which include charged particles plasma and Earth's troposphere. A pair of redundant Advanced Water Vapor Radiometers (AWVR) co‐located at the DSN's DSS‐25 antenna in Goldstone, CA measure the brightness temperatures at the 22.2, 23.8 and 31.4 GHz spectral lines for water vapor content in Earth's atmosphere. The measurements of water vapor content are reduced into a measurement of radio path delay, which provides high‐precision calibrations of tropospheric noise on the radio links. Analyses of AWVR measurements show that spacecraft tracking errors, after removing other measurable errors from charged particles, are reduced by 46% on average and by as much as 70%, depending on local weather conditions near the Goldstone site. Plain Language Summary: The Juno Gravity Science instrument relies on precise measurements of the Doppler shift of the telecommunications radio link signal between the Juno Spacecraft and the Earth‐based Deep Space Network (DSN) antennas. A radiometer system called the Advanced Water Vapor Radiometer (AWVR) is deployed at the DSN's DSS‐25 antenna in Goldstone, California, to measure the tropospheric path delay seen by radio signals received from deep space. The AWVR calibrates the deep‐space Doppler frequency measurements. Troposphere path delay measurements throughout the Juno prime mission are presented and the measurements are shown to improve the Doppler frequency measurements by 46% on average and by as much as 70%, depending on local weather conditions. Key Points: This research presents the impacts of Earth troposphere path delay on Juno Gravity Science Doppler frequency measurementsThe Advanced Water Vapor Radiometer (AWVR) measured short‐term and seasonal variations in troposphere path delay in Goldstone, CaliforniaThe AWVR improved Doppler frequency measurements by 46% on average and up to 70% in optimal conditions [ABSTRACT FROM AUTHOR]

The Diviner Lunar Radiometer Experiment on the Lunar Reconnaissance Orbiter and the Microwave Radiometer (MRM) onboard Chang'e‐2 (CE‐2) orbiter performed nearly coincident measurements of the lunar south polar region in 2010–2011. In this study, we reconcile infrared data from Diviner and microwave data from MRM to reveal thermal behavior of lunar regolith at very low temperatures. Assuming a uniform density structure and dielectric properties across the polar region, we retrieve a relative apparent thermal‐gradient map based on radiative transfer model. The result shows apparent thermal gradients in the permanently shadowed regions (PSRs) are much larger than that in non‐PSRs, which implies a systematic difference in thermal conductivity and/or density of lunar regolith in PSRs. We also model surface temperature and microwave brightness temperature over time in PSR and non‐PSR locations. The modeling results at these representative locations and the thermal gradient map confirm that the regolith in the PSRs is consistent with a much lower thermal conductivity and higher porosity than non‐PSRs. Plain Language Summary: Using data from Lunar Reconnaissance Orbiter's Diviner infrared radiometer and Chang'E‐2 Microwave Radiometer (MRM), we produce an equivalent temperature gradient map of the lunar south polar region as seen from microwave band. We also fit the Diviner data and MRM data by a thermal‐microwave model in a permanently shadowed region (PSR) and a non‐PSR location. Both results imply that PSRs have a higher porosity and lower thermal conductivity regolith than near‐equatorial regions of the Moon. The result could be helpful for calculating the depth to the ice table and constraining the geothermal gradient in these cryogenic regions and may be critical for landed operations within PSR areas. Key Points: We show unexpected thermophysical properties within cold traps in the lunar south polar region based on infrared and microwave observationsTwo year series of surface temperature and microwave brightness temperature in a non‐permanently shadowed region (PSR) location and Shoemaker are modeledThe high apparent thermal gradient in the PSR is explained by temperature‐dependent thermal conductivity and high porosity [ABSTRACT FROM AUTHOR]

Retrieval of snow depth on sea ice from satellite measurements has been challenging especially for multiyear ice. In this study, January‐February‐March monthly averaged snow depth was estimated during the 2003–2020 period from satellite radiometer measurements by combining recently developed retrieval methods for freeboard and snow‐ice thickness ratio. A good agreement between snow depth from this study and that from Operational IceBridge measurements demonstrates that reliable snow depth can be estimated from satellite measurements. From the analysis of wintertime snow depth estimated from this study, a reduction of mean snow depth compared to the modified Warren climatology is noted over the entire Arctic Ocean. In addition, this study found geographically different snow depth trends: positive for multiyear ice area and negative for the other areas. Average snow depth interannual variability on multiyear ice ranges between 3 to 5 cm while smaller variability is found on first‐year ice. Plain Language Summary: Snow on Arctic sea ice plays an important role in the Arctic surface energy balance and hydrological cycle. In this study, the snow depth on Arctic sea ice is retrieved based on the satellite measurements during the January‐February‐March months of the 2003–2020 period. We found a good agreement between snow depth from this study and snow depth measurements from airborne snow radar. Analysis of the mean and trend of snow depth demonstrates that the reduction of snow depth on sea ice occurs in the whole Arctic area compared to the climatological values measured during 1954–1991. In the Eastern and Western Arctic Ocean, there are significant decreasing and increasing snow depth trends, respectively. Key Points: Wintertime Arctic basin‐scale snow depth on sea ice has been retrieved from satellite radiometer measurements from 2003 to 2020Significant snow depth reduction is noted compared to the modified Warren climatological snow depth over the Arctic basinPositive trends of snow depth are found over multiyear sea ice areas during the 2003–2020 period [ABSTRACT FROM AUTHOR]

Measurements from the InSight lander radiometer acquired after landing are used to characterize the thermophysical properties of the Martian soil in Homestead hollow. This data set is unique as it stems from a high measurement cadence fixed platform studying a simple well‐characterized surface, and it benefits from the environmental characterization provided by other instruments. We focus on observations acquired before the arrival of a regional dust storm (near Sol 50), on the furthest observed patch of soil (i.e., ∼3.5 m away from the edge of the lander deck) where temperatures are least impacted by the presence of the lander and where the soil has been least disrupted during landing. Diurnal temperature cycles are fit using a homogenous soil configuration with a thermal inertia of 183 ± 25 J m−2 K−1 s−1/2 and an albedo of 0.16, corresponding to very fine to fine sand with the vast majority of particles smaller than 140 μm. A pre‐landing assessment leveraging orbital thermal infrared data is consistent with these results, but our analysis of the full diurnal temperature cycle acquired from the ground further indicates that near surface layers with different thermophysical properties must be thin (i.e., typically within the top few mm) and deep layering with different thermophysical properties must be at least below ∼4 cm. The low thermal inertia value indicates limited soil cementation within the upper one or two skin depths (i.e., ∼4–8 cm and more), with cement volumes <<1%, which is challenging to reconcile with visible images of overhangs in pits. Plain Language Summary: InSight carried a six‐channel radiometer used to measure diurnal surface temperatures over the duration of the mission. Surface temperatures are controlled by insolation and the microscopic physical properties of the soil (typical grain size, density, degree of soil cementation, or internal layering) that could not be resolved without a microscope or other instruments. Because the InSight lander does not have any systematic way to interrogate the soil, we have instead analyzed these temperature data and characterized the near‐surface soil properties. We found that the soil structure near the lander is homogeneous within the top few cm, and is made of loose sandy material with very little to no cementation. These properties are consistent with those derived from orbit before landing using remote sensing techniques, but difficult to reconcile with visible imagery showing evidence for induration farther from the hollow margin. Key Points: The InSight radiometers measured surface temperatures multiple times per sol over a flat and homogeneous patch of Martian soilThe thermal inertia of the soil in Homestead hollow is ∼183 ± 25 J m−2 K−1 s−1/2, consistent with aeolian fine sand infillingThe presence of a duricrust suggested by imagery is difficult to reconcile with this thermal inertia value [ABSTRACT FROM AUTHOR]

We analyze new aerosol products from NASA satellite retrievals over the western USA during August 2013, with special attention to locally generated wildfire smoke and downwind plume structures. Aerosol optical depth (AOD) at 550 nm from MODerate Resolution Imaging Spectroradiometer (MODIS) (Terra and Aqua Collections 6 and 6.1) and Visible Infrared Imaging Radiometer Suite (VIIRS) Deep Blue (DB) and MODIS (Terra and Aqua) Multi‐Angle Implementation of Atmospheric Correction (MAIAC) retrievals are evaluated against ground‐based AErosol RObotic NETwork (AERONET) observations. We find a significant improvement in correlation with AERONET and other metrics in the latest DB AOD (MODIS C6.1 r2 = 0.75, VIIRS r2 = 0.79) compared to MODIS C6 (r2 = 0.62). In general, MAIAC (r2 = 0.84) and DB (MODIS C6.1 and VIIRS) present similar statistical evaluation metrics for the western USA and are useful tools to characterize aerosol loading associated with wildfire smoke. We also evaluate three novel NASA MODIS plume injection height (PIH) products, one from MAIAC and two from the Aerosol Single scattering albedo and layer Height Estimation (ASHE) (MODIS and VIIRS) algorithm. Both Terra and Aqua MAIAC PIHs statistically agree with ground‐based and satellite lidar observations near the fire source, as do ASHE, although the latter is sensitive to assumptions about aerosol absorption properties. We introduce a first‐order approximation Smoke Height Boundary Layer Ratio (SHBLR) to qualitatively distinguish between aerosol pollution within the planetary boundary layer and the free troposphere. We summarize the scope, limitations, and suggestions for scientific applications of surface level aerosol concentrations specific to wildfire emissions and smoke plumes using these novel NASA MODIS and VIIRS aerosol products. Key Points: Aerosol optical depth and plume injection height products from new collections of Moderate resolution imaging spectroradiometer and Visible Infrared Imaging Radiometer Suite demonstrate improved capabilities for smoke eventsNew Smoke Height Boundary Layer Ratio indicates when wildfire smoke aerosols are likely to be confined within the planetary boundary layerHeterogeneous vertical aerosol profiles were found downwind of wildfires induced by mountainous terrain and complex boundary layer physics [ABSTRACT FROM AUTHOR]

The fire plume height (smoke injection height) is an important parameter for calculating the transport and lifetime of smoke particles, which can significantly affect regional and global air quality and atmospheric radiation budget. To develop an observation‐based global fire plume‐rise data set, a modified one‐dimensional plume‐rise model was used with observation‐based fire size and Maximum Fire Radiative Power (MFRP) data, which are derived from satellite fire hotspot measurements. The resulting data set captured well the observed plume height distribution derived from the Multiangle Imaging SpectroRadiometer (MISR) measurements. The fraction of fire plumes penetrating above the boundary layer is relatively low at 20% at the time of MISR observation (10:30 am LT) but increases to an average of ∼55% in the late afternoon, implying that the MISR observation data sampled in late morning underestimate the average daytime fire plume heights and plume mixing into the free troposphere. Therefore, adjustments are required through dynamic modeling or parameterization of fire plume height as a function of meteorological and fire conditions when the MISR data set is applied in climate model simulations. We conducted sensitivity simulations using the Community Atmospheric Models version 5 (CAM5). Model results show that the incorporation of fire plume rise in the model tends to significantly increase fire aerosol impacted regions. We applied the offline plume‐rise data to develop an online fire plume height parameterization, allowing for simulating the feedbacks of climate/weather on fire plume rise in climate models. Plain Language Summary: The wildfire smoke injection height is important to study the lifetime and transport capacity of smoke particles. This study developed a long‐term global wildfire injection height data set, which has been well evaluated and applied to global climate model simulation. For fully coupled atmosphere‐land simulation purposes, implementation has been developed for the climate model to generate injection height at each time step. The fire plume height (smoke injection height) is important for calculating the transport and lifetime of smoke particles. A modified one‐dimensional plume‐rise model was used with observation‐based fire size and Maximum Fire Radiative Power (MFRP) data. The resulting data set captured well the observed plume height distribution. The simulated plume penetration rate suggests higher fire emission mixed in the free troposphere in the late afternoon. We conducted sensitivity simulations using the Community Atmospheric Models version 5 (CAM5). In downwind regions, model results show that the incorporation of fire plume rise tends to increase fire aerosol transport. Additionally, we develop an online fire plume height parameterization, allowing for simulating the feedbacks of climate/weather on fire plume rise in climate models. Key Points: An observation‐based fire plume height data set is developed for 2002–2010. It is in general agreement with global Multiangle Imaging SpectroRadiomete observationsLate morning satellite observations tend to underestimate the fraction of fire plumes reaching the free troposphere during the dayModeling using online fire plume‐rise parameterizations based on this data set shows extensive free‐tropospheric transport of fire aerosols [ABSTRACT FROM AUTHOR]

Aerosol‐cloud interactions are an important source of uncertainty in current climate models. To understand and quantify the influence of ice‐nucleating particles in cloud glaciation, it is crucial to have a reliable estimation of the hemispheric and seasonal contrast in cloud top phase, which is believed to result from the higher dust aerosol loading in boreal spring. For this reason, we locate and quantify these contrasts by combining three different A‐Train cloud‐phase products for the period 2007–2010. These products rely on a spaceborne lidar, a lidar‐radar synergy, and a radiometer‐polarimeter synergy. We show that the cloud‐phase from the product combination is more reliable and that the estimation of the hemispheric and seasonal contrast has a lower error compared to the individual products. To quantify the contrast in cloud‐phase, we use the hemispheric difference in ice cloud frequency normalized by the liquid cloud frequency in the southern hemisphere between −42 °C and 0 °C. In the midlatitudes, from −15 to −30 °C, the hemispheric contrasts increase with decreasing temperature. At −30 °C, the hemispheric contrast varies from 29% to 39% for the individual cloud‐phase products and from 52% to 73% for the product combination. Similarly, in the northern hemisphere, we assess the seasonal contrast between spring and fall normalized by the liquid cloud frequency during fall. At −30 °C, the seasonal contrast ranges from 21% to 39% for the individual cloud‐phase products and from 54% to 75% for the product combination. Plain Language Summary: The influence of atmospheric particles on clouds is one of the main unknowns in climate predictions. Particularly, the cloud glaciation process and its dependence on desert dust and soot particles are not well‐understood. To better understand the differences in cloud glaciation between hemispheres, we counted liquid and ice cloud tops, as observed from four different satellites, during 4 years. Combining these observations, we could confirm a higher frequency of ice cloud tops during spring in the northern hemisphere. We found that the contrast between hemispheres is higher than previously thought. These results will help to improve our understanding of cloud glaciation processes, which can be valuable for future climate predictions and for understanding the impact of aerosols on radiation and precipitation. Key Points: A satellite product ensemble was used to locate and quantify the hemispheric and seasonal contrast in cloud top thermodynamic phaseAt −30 °C, half of the liquid cloud tops observed in the southern hemisphere would glaciate in the northern hemisphereThe new product ensemble is more reliable than the individual products and suggests a previous underestimation of the cloud‐phase contrasts [ABSTRACT FROM AUTHOR]

The lunar surface temperature (LST) derived from thermal infrared (TIR) measurements can aid in understanding the physical properties of the lunar surface. The Diviner Lunar Radiometer Experiment (herein, Diviner) sensor provides global lunar surface observation in seven TIR channels. However, its retrieval of LST constantly uses a single emissivity value (i.e., 0.95) by ignoring the spatial variation of lunar surface, thereby reducing the accuracy of temperature and day–night temperature difference. To overcome this problem, this study developed a physical method called temperature–emissivity separation (TES) algorithm to retrieve LST and lunar surface emissivity from the daytime observation in three Christiansen Feature (CF) channels (7.55–8.05, 8.10–8.40, and 8.38–8.60 μm) of the Diviner, and then used the emissivity from daytime observation to inverse LST at nighttime observation. Findings showed that the TES algorithm could retrieve LST and emissivity with an error of less than 0.8 K and 0.008, respectively. However, observation noise significantly affected the retrieval accuracy, particularly for the low‐temperature pixels; moreover, high retrieval accuracy requires a surface temperature higher than 240 K. The new algorithm was applied to obtain the daytime and nighttime LST and emissivity from the Diviner images. Results showed that the LST retrieved from the algorithm differed approximately 3.9 K from that calculated from a single emissivity 0.95. Finally, an example of global surface temperature and emissivity were obtained. Consequently, the CF pixels were found to distribute in the latitude range from −60° to 60°; however, they did not have a large distribution in high‐latitude and near‐polar regions. Key Points: A physical algorithm was proposed to estimate lunar surface temperature and emissivity from Diviner daytime and nighttime observationsLunar surface temperature retrieved from the new algorithm differed 3.9 K from that calculated from a fixed emissivity 0.95Global lunar Christiansen Feature pixels were identified and found to mainly distribute in the latitude range from −60° to 60° [ABSTRACT FROM AUTHOR]

Two sources of readily available and non‐overlapping space‐borne data on sea ice thickness over the Arctic (i.e., Ice, Cloud, and land Elevation Satellite [ICESat] and CryoSat‐2 [CS2]) were compared using overlapping thermal microwave radiometer data to examine their respective differences. As a bridge connecting these two data sets, data on the vertically polarized emissivity difference between 10.65 and 18.7 GHz derived from the Advanced Microwave Sounding Radiometer were related to ICESat and CS2 thickness values via regression. The results indicate that there are substantial and systematic differences in the ice thickness between these two data sets over the Arctic; ICESat ice thickness was systematically lower than that of CS2 by ~50 cm, compared to ice thickness from Operation IceBridge and upper looking sonar data. The CS2 thickness observed later than that of ICESat was found to be thicker, contradicting the thinning expected under global warming conditions. Correcting for the 50‐cm difference between ICESat or CS2 data revealed trends in ice volume that are consistent with the expected and modeled declines in the Pan‐Arctic Ice‐Ocean Modeling and Assimilation System data, further corroborating the 50 cm of relative bias observed between the two data sets. Key Points: The ICESat and Cryosat‐2 ice thickness data sets, which have a 24‐month gap, were comparedA systematic and substantial difference of ~50 cm was found between the ICESat and CryoSat‐2 data setsSnow depth used for estimating the ice thickness is found to be one of major sources of uncertainty causing the difference [ABSTRACT FROM AUTHOR]

The leading mode of the global sea surface temperature anomaly (SSTA) on the interannual time scale is a quasi‐quadrennial oscillation mode, corresponding to the El Niño–Southern Oscillation cycle. Using observational data diagnosis and numerical simulations, we show that the global SSTA during the quadrennial cycle has significant impacts on the anomaly of diabatic heating over the Tibetan Plateau (TP) in summer. Idealized atmospheric general circulation model (AGCM) experiments forced by the global SSTA with and without the thermal forcing of the TP diabatic heating anomaly reveal the relative contributions of the SSTA direct effect and the TP feedback to the anomalous response of the East Asian summer monsoon (EASM). During the quadrennial oscillation, in the developing year summer, the diabatic heating weakens over the whole TP, inducing suppressed EASM precipitation accompanied by an anomalous cyclone over the northwestern Pacific and an anticyclone in North China. In the decaying year summer, the TP heating, characterized by an anomalous negative‐positive pattern, induces an anomalous anticyclone in South China and an anomalous cyclone in North China. However, without the anomalous TP thermal forcing, in both developing and decaying years the EASM shows similar response patterns with an anomalous anticyclone over the northwestern Pacific, an anomalous cyclone in North China, and an enhanced main rainfall band. Therefore, the TP thermal feedback plays a key role in the asymmetric responses of the EASM to the global SSTA during the different stages, characterized by suppressed precipitation in developing years and an enhanced main rainfall band in decaying years. Key Points: Quadrennial oscillation of global SST has different impacts on the Tibetan Plateau heating during summer in developing and decaying yearsThe Tibetan Plateau thermal feedback in summer has effects on circulation and precipitation in East Asia during the quadrennial oscillationGlobal SST asymmetrically affects the East Asian summer monsoon mainly through the Tibetan Plateau thermal feedback effect [ABSTRACT FROM AUTHOR]

We investigated the cloud liquid water (CLW) and rain liquid water (RLW) during weak precipitations (rain rate below 12 mm/h) using microwave radiometer and microrain radar measurements collected by the Integrative Monsoon Frontal Rainfall Experiment over central China in 2018. The CLW path increased sharply from 0.6 to 4.1 mm for precipitation clouds. RLW path presented a similar trend, although it had a larger correlation coefficient with rain rate. Precipitation efficiency reached up to ~50% and then clearly decreased as precipitation weakened. Because weak precipitation is mostly formed in stable nimbostratus, CLW content (CLWC) during precipitation tends to has a quasi‐normal distribution with mode at 0.38 g/m3, whereas RLW content (RLWC) shows a positively skewed distribution with mode at 0.06 g/m3. Normalized CLWC initially increases then decreases with height in nonprecipitation clouds but varies slightly in precipitation clouds due to relatively monodispersed droplets in the weaker convective motion. CLWC derived from millimeter‐wave cloud radar (MMCR) shows similar vertical distribution but with larger values. The mean normalized CLWCs are 0.06 and 0.38 g/m3 for nonprecipitation and precipitation clouds, respectively. RLWC varies slightly with height with a mean of 0.22 g/m3 because both the collision and breakup of raindrops are weak. A case study showed different distributions and vertical structures of CLWC and RLWC in various stages of precipitation. Thicker clouds result in larger CLWC and RLWC, which will cause greater rain rate. This qualitatively explains relationships among cloud thickness, CLW, RLW, and rain rate in precipitation during the monsoon. Key Points: Rain liquid water path shows a similar trend to cloud liquid water path during precipitation and has a higher correlation with rain rateBoth normalized cloud and rain liquid water vary slightly with height in weak precipitation conditions but show different distributionsDistributions and vertical structures of cloud liquid water and rain liquid water are different in various stages of precipitation [ABSTRACT FROM AUTHOR]

Creating synthetic ice cloud profiles that are distributed according to realistic probability density functions is fundamentally essential for submillimeter wave radiometer studies. In this paper, we develop an algorithm to create synthetic ice cloud profiles by combing in situ microphysics measurements and spaceborne radar reflectivity observations using Bayesian Monte Carlo Integration (MCI). We first conduct comprehensive studies of the in situ data from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based on a bimodal particle size distribution (PSD) scheme and the realistic particle scattering properties for different crystal habits. Ice water content and radar reflectivity simulations from the in situ PSD are compared with the in situ measurements qualitatively and quantitatively. We then evaluate the Bayesian MCI by applying the algorithm to the Cloud Radar System (CRS) during the TC4 campaign and compare the brightness temperature simulations for the retrievals with the Compact Scanning Submillimeter Imaging Radiometer (CoSSIR) measurements. Finally, we apply the Bayesian MCI to the Cloud Profiling Radar (CPR) measurements on CloudSat, and we use the cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) to preserve the one‐point statistics and the two‐point statistics that allow for the creation of any number of synthetic ice cloud profiles that are statistically consistent with the Bayesian retrieval results. The synthesized profiles are a useful characterization of the ice cloud vertical structure that combines two disparate data sources, and the synthesis algorithm constitutes an essential initial step for producing critical information in submillimeter radiometry studies. Key Points: We propose an algorithm to synthesize ice cloud profiles that are distributed according to realistic probability density functionsThe algorithm combines the in situ microphysics with the radar measurements using Bayesian Monte Carlo IntegrationWe evaluate the synthesis algorithm with the data from the TC4 campaign and the CloudSat radar observations [ABSTRACT FROM AUTHOR]

Current satellite cloud products from passive radiometers provide effective single‐layer cloud properties by assuming a homogeneous cloud in a pixel, resulting in inevitable biases when multiple‐layer clouds are present in a vertical column. We devise a novel method to retrieve cloud vertical properties for ice‐over‐water clouds using passive radiometers. Based on the absorptivity differences of liquid water and ice clouds at four shortwave‐infrared channels (centered at 0.87, 1.61, 2.13, and 2.25 μm), cloud optical thicknesses (COT) and effective radii of both upper‐layer ice and lower‐layer liquid water clouds are inferred simultaneously. The algorithm works most effectively for clouds with ice COT < 7 and liquid water COT > 5. The simulated spectral reflectances based on our retrieved ice‐over‐water clouds become more consistent with observations than those with a single‐layer assumption. This new algorithm will improve our understanding of clouds, and we suggest that these four cloud channels should be all included in future satellite sensors. Plain Language Summary: Over a quarter of clouds in the atmosphere overlap in a vertical column, and ignoring the cloud vertical distribution may significantly influence estimation of their radiative effects. However, information about cloud vertical structures is mostly provided by in situ or active instruments with limited spatiotemporal resolution. Cloud properties from satellite passive radiometer observations are derived by treating a cloud pixel as a single‐layer cloud, resulting in biases in our understanding of clouds and their radiative forcing. This study improves the capabilities of passive radiometers for retrieving properties of ice‐over‐water clouds, including the optical thicknesses and effective radii of both upper ice and lower liquid water clouds simultaneously. Our method provides a new perspective for radiometer‐based retrieval of multilayer cloud properties and will improve the evaluation of cloud radiative effects. Key Points: A cloud microphysical and optical property retrieval algorithm for ice‐over‐water clouds using passive satellite observations is developedThe absorptivity differences of water and ice at three shortwave‐infrared channels are used to differentiate between water and ice cloudsThe retrieved cloud optical properties are found to be significantly improved, compared to MODIS‐derived properties [ABSTRACT FROM AUTHOR]

The asymmetric gravity field measured by the Juno spacecraft has allowed the estimation of the depth of Jupiter's zonal jets, showing that the winds extend approximately 3,000 km beneath the cloud level. This estimate was based on an analysis using a combination of all measured odd gravity harmonics, J3, J5, J7, and J9, but the wind profile's dependence on each of them separately has yet to be investigated. Furthermore, these calculations assumed the meridional profile of the cloud‐level wind extends to depth. However, it is possible that the interior jet profile varies somewhat from that of the cloud level. Here we analyze in detail the possible meridional and vertical structure of Jupiter's deep jet streams that can match the gravity measurements. We find that each odd gravity harmonic constrains the flow at a different depth, with J3 the most dominant at depths below 3,000 km, J5 the most restrictive overall, whereas J9 does not add any constraint on the flow if the other odd harmonics are considered. Interior flow profiles constructed from perturbations to the cloud‐level winds allow a more extensive range of vertical wind profiles, yet when the meridional profiles differ substantially from the cloud level, the ability to match the gravity data significantly diminishes. Overall, we find that while interior wind profiles that do not resemble the cloud level are possible, they are statistically unlikely. Finally, inspired by the Juno microwave radiometer measurements, assuming the brightness temperature is dominated by the ammonia abundance, we find that depth‐dependent flow profiles are still compatible with the gravity measurements. Plain Language Summary: Jupiter's north‐south asymmetric gravity field, as measured by the Juno spacecraft, currently orbiting Jupiter, has been used to determine that the depth of its jet streams (associated with the famous visible cloud bands) are approximately 3,000 km. This estimate was based on all the gravity field measurements combined. However, there is also information about the structure of the flow hidden in each individual measurement. Here we analyze these measurements and show how each of them is sensitive to the flow at a different depth. We also systematically investigate the statistical likelihood of deep wind profiles that differ from the profile observed at the cloud level with various structures at depth. We find that Jupiter's measured cloud‐level jet streams fit with its gravity data for a relatively narrow envelope of vertical structures. Although other jet profiles that are different from the one observed at the cloud level are feasible (still consistent with the gravity data), they are statistically unlikely. Finally, we explore a depth‐dependent wind structure inspired by the Juno microwave radiometer instrument, which indicates that ammonia abundance varies with depth and might be correlated with the jet streams. We find that such a profile can still match the gravity data as long as the variation from the cloud‐level wind is not substantial. Key Points: Jupiter's asymmetric gravity field confines the vertical profile of the flow, with each harmonic constraining the flow at a different depthDeep zonal flows with a meridional profile significantly different from that of the cloud level are possible, but statistically unlikelyA flow profile inspired by the microwave radiometer (MWR) measurements is consistent with the gravity measurements [ABSTRACT FROM AUTHOR]

We present a new characterisation of the three‐dimensional (3D) distribution of dust over the Sahara during summer, exemplified for June 2011. Our approach, called AEROIASI, is based on the innovative retrieval of vertical profiles of the dust extinction coefficient from daily cloud‐free hyperspectral Infrared Atmospheric Sounder Interferometer (IASI) satellite observations. AEROIASI observations clearly agree with other widely used measurements (from lidar and radiometers). The 3D characterisation is focused on the dust maximum in June 2011, located in the central Sahara (17–23°N, 1–7°E) and linked to the major atmospheric dynamical drivers associated with the West African Monsoon (WAM) system. AEROIASI shows the near‐surface dust load to be dominated by five major emission events occurring every 3–4 days. These all occur when the study region is under the influence of northward bursts of the WAM and convection‐related cold pools, likely associated with orographic forcing by the Aïr Mountains. During the earliest (June 10) and the dustiest (June 17) cases, northward advection of moisture over the hotspot is favoured by the superposition of cyclonic circulations related to an extratropical disturbance northwest of the Sahara and to the Saharan heat low over Mauritania, respectively. Convection over the hotspot also triggers wave‐like disturbances that travel westwards. The three dustiest events are characterised by elongated dust fronts moving northwards, with a leading edge spanning 200–300 km horizontally and extending from the surface up to 2 km of altitude. Further south, the dust layer progressively elevates to 3.5 km along the slanted isentropes at the interface of the monsoon and the harmattan, increasingly losing contact with the ground. When northerlies blow over the study region, elevated dust layers at 3–5 km are observed, which are transported southwards within the Saharan air layer and westwards along the northern edge of the African easterly jet (after June 13). [ABSTRACT FROM AUTHOR]

Active fires are considered to be the key contributor to, and critical consequence of, climate change. Quantifying the occurrence frequency and regional variations in global active fires is significant for assessing carbon cycling, atmospheric chemistry, and postfire ecological effects. Multiscale variations in fire occurrence frequencies have still never been fully investigated despite free access to global active fire products. We analyzed the occurrence frequencies of Visible Infrared Imaging Radiometer Suite (VIIRS) active fires at national, pan‐regional (tropics and extratropics) to global scales and at hourly, monthly, and annual scales during 2012–2017. The results revealed that the accumulated occurrence frequencies of VIIRS global active fires were up to 12,193 × 104, yet exhibiting slight fluctuations annually and with respect to the 2014–2016 El Niño event, especially during 2015. About 35.52% of VIIRS active fires occurred from July to September, particularly in August (13.06%), and typically between 10:00 and 13:00 Greenwich Mean Time (GMT; 42.96%) and especially at 11:00 GMT (17.65%). The total counts conform to a bimodal pattern with peaks in 5°–11°N (18.01%) and 5°–18°S (32.46%), respectively, alongside a unimodal distribution in terms of longitudes between 15°E and 30°E (32.34%). Tropical annual average of active fire (1,496.81 × 104) accounted for 75.83%. Nearly 30% were counted in Brazil, the Democratic Republic of the Congo, Indonesia, and Mainland Southeast Asia (MSEA). Fires typically occurred between June (or August) and October (or November) with far below‐average rainfall in these countries, while those in MSEA primarily occurred between February and April during the dry season. They were primarily observed between 00:00 and 02:00 GMT, between 12:00 and 14:00 within each Zone Time. We believed that VIIRS global active fires products are useful for developing fire detection algorithms, discriminating occurrence types and ignition causes via correlation analyses with physical geographic elements, and assessment of their potential impacts. [ABSTRACT FROM AUTHOR]

The Heatflow and Physical Properties Package (HP3) radiometer is currently operating on Mars, observing two spots approximately 1 and 3 m north‐north‐west of the InSight lander. The instrument has primary sensors that are sensitive in the range of 8 to 14 μm and two more sensors with more narrow spectral ranges per field of view. The radiometer underwent radiometric and geometric calibration at DLR—Berlin; and on Mars radiometric self‐calibration is performed regularly. The self‐calibration confirms that one of the two primary sensors has been stable since the ground calibration, but environmental parameters that are likely associated with the thermal contact of sensor and instrument main body may have slightly changed. The other primary sensor has increased in sensitivity for an unknown reason but is still within expectation from the sensor design. The uncertainty of the two primary sensors is approximately 3 K at night, with somewhat larger errors in the late afternoon. This estimate includes the effect of sensitivity changes that would be too small to be reliably detected by the self‐calibration. Key Points: We describe the calibration of the HP3 radiometer measuring surface brightness temperature on Mars next to the Insight landerRegular self‐calibration measurements on Mars ensure an uncertainty of 3 K at night [ABSTRACT FROM AUTHOR]

Toward the Kashi region in northwest of China, the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals from Collection 6 (C6) MYD, Collection 6.1 (C6.1) MOD, and C6.1 MYD during 2016–2017 are compared with ground‐based measurements from the Sun‐sky Radiometer Network (SONET), and the first comprehensive evaluation of the Dark Target (DT) and Deep Blue (DB) retrievals with a 10‐km spatial resolution in the latest C6.1 MYD AOD data set during 2016–2018 is presented. In general, C6.1 MYD AOD products (both of DT and DB algorithm) are the most effective in Kashi of the three collections, and there is an overall underestimation of DB AOD, while DT AOD that slightly outperformed DB AOD in Kashi is overestimated on the whole. As to the factors that influence the accuracy of MODIS AOD, for DB algorithm, the overestimations of the surface reflectance and Single Scattering Albedo that DB aerosol model assumed can cause underestimation of DB AOD retrievals over Kashi, while the ones for DT algorithm are opposite. Besides, the coarse dust particles with lower veracity are predominant in Kashi region, which illustrated that the errors of particle size assumption in C6.1 MYD DT and DB algorithms will make large inversion error of MODIS AOD. Moreover, whatever DB or DT algorithm, the accuracy of AOD is diminished as the aerosol loading increases. The more realistic aerosol models and surface characterizations are necessary during the process of generating the MODIS aerosol retrievals in Kashi region. Key Points: Compared to the performance of MODIS AOD retrievals from C6 MYD and C6.1 MOD in Kashi region, find the C6.1 MYD AOD is more effectivelyThere is an overall underestimation of DB AOD, while DT AOD that is slightly outperformed DB AOD in Kashi is overestimated on the wholeFor the uncertainty of C6.1 MYD AOD retrievals, all of the surface reflectance, aerosol model and loading are contributive [ABSTRACT FROM AUTHOR]

Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the polar regions where uncertainties about the interactions between sea ice, ocean, and atmosphere are driving ongoing monitoring efforts. The Copernicus Imaging Microwave Radiometer (CIMR) is an European Space Agency (ESA) candidate mission which promises to offer high resolution, low uncertainty observation capabilities at the 1.4, 6.9, 10.65, 18.7, and 36.5 GHz frequencies. To assess the potential impact of CIMR for sea ice parameter retrieval, a comparison is made between retrievals based on present AMSR2 observations and a retrieval using future CIMR equivalent observations over a data set of validated sea ice concentration (SIC) values. An optimal estimation retrieval method (OEM) is used which can use input from different channel combinations to retrieve seven geophysical parameters (sea ice concentration, multi‐year ice fraction, ice surface temperature, columnar water vapor, liquid water path, over ocean wind speed, and sea surface temperature). An advantage of CIMR over existing radiometers is that it would provide higher spatial resolution observations at the lower frequency channels (6.9, 10.65, and 18.7 GHz) which are less sensitive to atmospheric influence. This enables the passive microwave based retrieval of SIC and other surface parameters with higher resolution and lower uncertainty than is currently possible. An information content analysis expands the comparison between AMSR2 and CIMR to all retrievable surface and atmospheric parameters. This analysis quantifies the contributions to the observed signal and highlights the differences between different input channel combinations. The higher resolution of the low frequency CIMR channels allow for unprecedented detail to be achieved in Arctic passive microwave sea ice retrievals. The presence of 1.4 GHz channels on board CIMR opens up the possibility for thin sea ice thickness (SIT) retrieval. A combination of collocated AMSR2 and SMOS observations is used to simulate a full CIMR suite of measurements, and the OEM is modified to include SIT as a retrieval parameter. The output from different retrieval configurations is compared with an operational SIT product. The CIMR instrument can provide increased accuracy for SIC retrieval at very high resolutions with a combination of the 18.7 and 36.5 GHz channels while also maintaining sensitivity for atmospheric water vapor retrieval. In combination with the 1.4 GHz channels, SIT can be added as an eighth retrieval parameter with performance on par with existing operational products. Plain Language Summary: In order to improve exiting climate models a number of challenges have to be overcome which have to do with interactions between sea ice, the open ocean, and the atmosphere. One way to address these challenges is to use higher quality satellite observations of these variables for tuning and running these models. The Copernicus Imaging Microwave Radiometer is an European Space Agency candidate mission which promises to offer high resolution and accurate observations at the 1.4, 6.9, 10.65, 18.7, and 36.5 GHz frequencies. At present one of the highest resolution sea ice concentration products is based on the 89 GHz channels of the AMSR2 satellite instrument. This frequency however is not ideal for observing surface parameters as it is sensitive to the presence of clouds. The lower frequency channels of the CIMR instrument are less influenced by the atmosphere. As such these frequencies would be much better suited for observing multiple sea ice parameters like concentration, different ice types, the sea ice thickness, and surface temperature as well as ocean parameters such as sea surface temperature, sea surface salinity, and ocean wind speed. Based on this we perform a performance comparison between the existing AMSR2 89 GHz and different CIMR channel combinations. The analysis is done using a common retrieval method for up to seven different parameters (sea ice concentration, ice types, ice surface temperature, sea surface temperature, ocean wind speed, total water vapor, and cloud liquid water) and which allows for using single or multifrequency channels as input. The focus is on the retrieval of sea ice concentration, but the other atmospheric and surface parameters are discussed as well. The CIMR 6.9 GHz channel offers the best sea ice concentration performance with a resolution of 15 km and an accuracy around 2%. The CIMR channel combination of 18.7 and 36.5 GHz offers good sea ice concentration accuracy at 4% but at a much higher resolution of 5 km, which is comparable with he present day AMSR2 89 GHz high resolution product. Using the CIMR channel combination also provides good sensitivity for retrieving the atmospheric parameters cloud liquid water and water vapor content. By using the full set of CIMR channels, including the two 1.4 GHz ones, sea ice thickness values below 30 cm can be retrieved alongside the other seven parameters. Key Points: A comparison of current and new (CIMR) passive microwave missions is made for sea ice and atmospheric parameter retrieval in the ArcticThe 18.7 + 36.5 GHz channel combination achieves 4% uncertainty for sea ice concentration retrieval at a resolution of 5 kmThe CIMR 1.4 GHz channels allow for retrieval of thin sea ice thickness data alongside other sea ice and atmospheric parameters [ABSTRACT FROM AUTHOR]

Various gaseous constituents present in Venus atmosphere have been detected and measured using in situ and remote sensing instruments. However, the measurements of mesospheric constituents above the cloud level are still scarce and inadequate. This is because constituents above the cloud level have a low abundance and a high level of variability. However, millimeter and submillimeter (mm and sub-mm) frequencies can be used for Venus mesosphere measurements during prolonged Venusian day and night because several minor species in the upper atmosphere have emission/absorption bands in these frequencies owing to the rotational transitions. This study presents brightness temperatures and the corresponding sensitivity at the mm and sub-mm wave frequencies for a limb sounding radiometer. This will be useful in potential payload design, that is, instrument design, frequency, bandwidth selection, and satellite altitude as well as pointing accuracy determination for measurement above Venus clouds. For this study, a simulation based experiment has been performed and presented to determine the mm and sub-mm wave frequencies, optimum for estimation of concentration of water vapor, CO, CO2, SO2, HDO, and HCl present in the mesosphere. The simulations have been performed using a radiative transfer model called Atmospheric Radiative Transfer Simulator. The mm and sub-mm wave measurement frequencies have been determined for both day and night time of Venus. It has been determined that 183, 380, 448, and 556 GHz frequencies are most suitable for water vapor measurements, 115, 230, and 345 GHz are optimum for CO measurements, and 600, 621, and 690 GHz frequency measurements are sensitive for HCl detection. [ABSTRACT FROM AUTHOR]

The Deep Blue (DB) aerosol retrieval algorithm has recently been applied to Advanced Very High Resolution Radiometer (AVHRR) data to produce a first version (V001) of a global aerosol optical thickness (AOT) data set. In this paper, we critically evaluate these AVHRR AOT data over China by comparison with ground‐based reference data from China Aerosol Remote Sensing Network for the period 2006–2011. The evaluation considers the impact of the surface (type and reflectance) and the aerosol properties (aerosol loading, aerosol absorption) on the quality of the retrieved AOT. We also compare the AVHRR‐retrieved AOT with that from Moderate Resolution Imaging Spectroradiometer over major aerosol source regions in China. We further consider seasonal variations and find, in general, a good agreement between AVHRR AOT and the reference data sets. The AVHRR retrieval algorithm performs well over dark vegetated surfaces, but over bright surfaces (e.g., desert regions) the results are less good. The AVHRR algorithm underestimates the AOT, with 32.1% of the values lower than the estimated error envelope of ±0.05 ± 0.25τ. In particular over the desert, the AVHRR‐retrieved AOT is frequently underestimated and for AOT ≤ 0.6 the values are on average 0.05 too low due to the pixel filtering, and dust storms are missed. The comparison of the AVHRR AOT with MODIS collection 6 and CARSNET data indicates that improvements are needed for, for example, AVHRR calibration and cloud/aerosol flagging. The analysis presented in this paper contributes to a better understanding of the AVHRR AOT product over China. Key Points: The 53.5% of the AOT values are within the estimated error envelop of ±0.05 ± 0.25τThe AVHRR‐retrieved AOT is frequently underestimated over the desert regionsAOT biases at 550 and 660 nm are −0.057 and −0.093, respectively [ABSTRACT FROM AUTHOR]

The present article introduces a new sea surface salinity (SSS) retrieval technique from the Soil Moisture Active Passive (SMAP) L–band (1.4 GHz) microwave radiometer. The ocean surface wind speed (WS) correction, which is very critical in any of the SSS retrieval techniques, is accounted for with a different approach. A model function between ΔSSS (the difference between SSS of flat and rough ocean surfaces) and ocean surface WS is developed and used to correct the impact of ocean surface roughness due to the winds on SSS. In addition to WS correction, the retrieval technique appropriately accounts for the effects of atmospheric attenuation on L‐band frequency due to water vapour and oxygen, and ocean surface temperature on SSS. The performance of the estimations is statistically evaluated by comparing the estimations with the in situ Argo, buoy SSS, and SMAP version 3, 70 km resolution SSS observations in global oceans during 2016. The retrieved salinity well captured the global distribution patterns of SSS, including low and high values. Comparison of retrieved salinity with Argo and SMAP products show a root‐mean‐square error (RMSE) of 0.32 and 0.39 psu, a Pearson correlation coefficient of 0.94 and 0.93, and a scatter index of 0.0093 and 0.011 respectively on a monthly time‐scale. In addition, retrieved SSS promisingly captured day‐to‐day variability in SSS observed by tropical moored buoy SSS with RMSE of 0.36 psu and a Pearson correlation coefficient of 0.94. The validation confirms the potential ability of the new retrieval technique in capturing SSS changes on daily and monthly time‐scales. [ABSTRACT FROM AUTHOR]

As uniform and stable objects, deep convective clouds (DCCs) are often used to monitor the calibration stabilities of the reflective solar bands (RSBs) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar‐orbiting Partnership. Traditionally, DCCs are identified by the legacy 11‐μm brightness temperature (BT11) threshold method. With the collocated Cross‐track Infrared Sounder (CrIS), a method of combining the BT difference between a water vapor absorption channel and a window channel to its measurement noise ratio (BNR) is adopted and applied to DCC identification. The BNR method improves the DCC detections over the legacy method because it is less contaminated with high clouds not thick and bright enough. Using observations from 2017 to 2018, the results show BNR has better performances than BT11 for identifying DCCs and monitoring RSBs. When comparing to BT11, BNR has more robust and invariant time series of monthly reflectance for all RSBs; that is, the standard deviation and total variation range (maximum‐minimum) are up to 47% smaller. Because BNR affects more on the left tails (less reflective) than the modes of the histograms of reflectance, the improvement is more significant on the mean reflectance than the mode. BNR detects fewer DCCs than BT11, but with more confidence. This allows the weekly and daily time series for monitoring RSBs in higher temporal frequencies. This method can be applied to other imagers with collocated advanced infrared sounders for detecting DCCs and monitoring the calibration stabilities of RSBs. Key Points: A method of combining CrIS brightness temperature difference to its measurement noise ratio for VIIRS DCC identification is introducedThe methodologies and technical approaches of monitoring VIIRS RSB calibrations using DCC with collocated CrIS measurements are developedThis method can be applied to other imagers with collocated advanced infrared sounders to monitor the calibration stabilities of RSBs [ABSTRACT FROM AUTHOR]

Core Ideas: Expected wheat yield declines exponentially with increasing wheat streak mosaic severity.For reflectance readings taken on 27 April, 4 May, and 10 May, economic threshold reflectance values are 8.3, 9.5, and 9.4, respectively.At the threshold infection severity expected grain yield is approximately 1910 kg ha−1.Wheat growers could potentially save resources by discontinuing input applications and introduce cattle for grazing. Wheat streak mosaic (WSM), caused by Wheat streak mosaic virus, is the most widespread and economically important virus disease affecting winter wheat (Triticum aestivum L.) in the Great Plains of the United States. Using reflectance data from a hand‐held hyperspectral radiometer and yields from a field experiment, this study estimated economic thresholds of WSM beyond which it is uneconomical to continue with mid‐season input applications. Disease severity assessments based on reflectance measurements were taken from 99 plots across the field at three time points, namely 27 April, 4 May, and 10 May in the 2015–2016 wheat season. A log‐linear regression model of yield on reflectance indicates potential yield losses of up to 35% for every unit increase in infection severity (as measured by reflectance readings). Using regression and partial budget analysis, results show varying thresholds of WSM depending on the date of disease severity assessments. The 27 April assessment had the lowest threshold when compared with the other assessment dates. Threshold analysis indicates potential to save resources by discontinuing mid‐season input applications and introducing cattle for grazing, in about 14% of the sampled plots, but only 1% if grazing was not possible. [ABSTRACT FROM AUTHOR]

Soil evaporation (ETs) and vegetation transpiration (ETv) are essential in evaporative demand analyses and agricultural applications. This study estimated ETs and ETv using two trapezoidal models, that is, the conventional trapezoidal model and the end‐member‐based soil and vegetation energy partitioning (ESVEP) model, at three AmeriFlux tower sites. First, the land surface temperature of a Moderate Resolution Imaging Spectroradiometer (MODIS) pixel was decomposed into soil and vegetation temperatures (Ts and Tv, respectively) which involve important information related to ETs and ETv and were compared with corresponding temperatures from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Then ETs and ETv were parameterized, and the total evapotranspiration (ET) was validated with the eddy covariance system measurements after energy imbalance corrections via the residual energy and Bowen ratio methods. The results showed that the ESVEP model partitioned Ts, with a root‐mean‐square error (RMSE) of 1.56–2.70 K (4.98–10.16%), and Tv, with an RMSE of 2.54–2.80 K (9.73–11.11%), indicating a higher accuracy than that from the conventional trapezoidal model, where the RMSE was 2.26–3.64 K (7.31–13.40%) for Ts separation and 2.82–4.62 K (9.80–15.49%) for Tv separation. For the ET estimation, the ESVEP model still performed better. The estimation RMSE was 49.8–58.4 W/m2 (22.8–27.2%) for the ESVEP model and 72.0–89.5 W/m2 (29.8–41.1%) for the conventional trapezoidal model, compared to the RE corrected measurements; the RMSE was 42.6–53.3 W/m2 (24.4–28.1%) for the ESVEP model and 57.5–78.1 W/m2 (32.3–37.9%) for the conventional trapezoidal model, compared to the Bowen ratio corrected measurements. Key Points: Soil evaporation and vegetation transpiration were estimated using two trapezoidal modelsLand surface temperature of MODIS pixel was decomposed into soil and vegetation component temperaturesAnalysis was made over three test sites [ABSTRACT FROM AUTHOR]

Surface temperature data sets for, or including, the Arctic have been derived from various thermal infrared sensors. However, a combined, all surface temperature data set for the Arctic has not been generated previously. Here we present the first combined land, ocean, and ice surface temperature data set for the Arctic produced from Along‐Track Scanning Radiometer ‐ 2 and the Advanced Along‐Track Scanning Radiometer satellite sensors: the Along‐Track Scanning Radiometer Arctic combined Surface Temperature data set. Separate products, produced independently for each sensor and containing quantified uncertainties, together cover the period August 1995 to April 2012. Product validation, utilizing a more extensive in situ database than previous studies, shows that Along‐Track Scanning Radiometer Arctic combined Surface Temperature surface temperatures generally agree with in situ data and are similar to previous validation of input surface temperature retrievals. Biases range from −1.74 to 0.23 K over open ocean, sea ice, snow over land, and the Greenland ice sheet with higher variability over snow/ice. However, there are noticeable outliers in the validation results, particularly over Arctic land in boreal summer for Along‐Track Scanning Radiometer ‐ 2, which are likely due to cloud contamination resulting from a climatologically static snow field being used for that sensor. This study suggests that the Along‐Track Scanning Radiometer Arctic combined Surface Temperature data set presented here is a useful tool for assessment of models in the Arctic. Further work would have clear benefits including improvements to snow cover and cloud clearing to achieve a fully consistently processed, climate quality combined surface temperature data set for the Arctic region. Key Points: This study presents the first combined surface temperature data set for the Arctic, derived here from ATSR thermal infrared satellite dataProduct validation shows data set surface temperatures generally agree with in situ data, but cloud contamination is an issueThis combined surface temperature data set is a useful tool for assessment of models in the Arctic, although further work is required [ABSTRACT FROM AUTHOR]

We present a compact W‐band mixer‐first receiver consisting of a passive single‐balanced mixer, on‐chip balun, and a variable gain amplifier with 1.9 GHz of bandwidth over a gain range of 36 dB in 65 nm CMOS. The W‐band front‐end has been implemented aiming at a compact frequency‐modulated continuous‐wave (FMCW) radar as a proximity sensor, and a down‐converting chain for a total power radiometer combined with external low noise amplifier. The measured gain of the W‐band receiver is 25 dB, and the receiver achieves 2.57 dBm of IIP3. The integrated receiver consumes 14.56 mA from a supply voltage of 1.2 V, and the core chip occupies only 0.39 mm2. [ABSTRACT FROM AUTHOR]

Drizzle is ubiquitous in marine boundary layer stratocumulus clouds with much of it evaporating before reaching the surface. Ten days of observations made at the Atmospheric Radiation Measurement's Eastern North Atlantic site during closed cellular stratocumulus cloud conditions are used to characterize drizzle below the cloud base and its impact on the boundary layer turbulence. Cloud and drizzle microphysical and macrophysical properties were retrieved by combining the data from vertically pointing Doppler cloud radar, ceilometer, and microwave radiometer. On average, the drizzle shafts were 28.14 km wide, with cloud base rain rate and modal diameter of 0.98 mm/day and 138.62 μm, respectively. The rain rate at the surface was negligible yielding an average diabatic cooling of −28.68 W/m2 in the subcloud layer. The liquid water path and turbulence within the boundary layer increased with an increase in the cloud top radiative cooling; however, none of these variables exhibited any relationship with cloud base rain rate. For a similar amount of radiative cooling at the cloud top, the average variance of vertical velocity in the subcloud layer was about 16% lower during strongly precipitating conditions as compared to lightly precipitating conditions. The reduction in the variance of vertical velocity due to drizzle evaporation was primarily confined to the upper half of the subcloud layer and was due to reduction in the strengths of the downdrafts. Collectively, our results show substantial impact of drizzle evaporation on turbulence below stratocumulus clouds, necessitating its accurate representation in the Earth system models. Key Points: On average the drizzle shafts are 28.14 km wide, with cloud base rain rate and modal diameter of 1.26 mm/day and 145.26 micronThe average diabatic cooling due to drizzle evaporation is ‐30.60 W/m2 in the subcloud layerFor similar amount of radiative cooling at the cloud top, drizzle evaporation decreases below cloud turbulence by about 16% [ABSTRACT FROM AUTHOR]

Ten fundamental aerosol models in China are derived from a cluster study based on the ground‐based remote sensing measurements of Sun‐sky radiometer Observation NETwork. The aerosol size distribution decomposition techniques are employed to yield individual fine and coarse mode size distribution functions with independent refractive indices. The total 10,773 records containing 18 kinds of aerosol microphysical parameters are used to yield 10 typical clusters with the verification of clustering robustness. Ten clusters suggest five typical fine particle aerosol models including urban polluted, secondary polluted, combined polluted, polluted fly ash, and continental background, as well as five coarse models including summer fly ash, winter fly ash, primary dust, transported dust, and background dust over China region. The representativeness and coappearance analyses again reveal five dominative aerosol patterns on the base of fundamental models. These models can be used in the chemical model simulation, satellite remote sensing, climate, and environment analyses. Plain Language Summary: The aerosol fundamental characterization model is used to describe the typical aerosol properties in a region which is essential in the radiative transfer calculations and thus is fundamental knowledge for many applications related to Earth's atmosphere. However, the establishment of these models is not easy not only for the hard works on the continuously long‐term, high‐quality observation but also related to analysis methods. However, these essential models are long‐term missed for China regions where is the most important aerosol regions in the world. It has turned to a bottleneck problem for accurately assessing aerosol effects in this important region. In this paper, we use the first‐hand 7‐year aerosol observation from the 16 sites of Chinese local observation network and employ an advanced new technique to first derive 10 fundamental aerosol characterization models over China. The obtained 10 fundamental aerosol models can provide a basis for general description of China aerosols. It is very useful for the climate, environment, and ecology studies. Meanwhile, they can be directly adapted in the development of satellite remote sensing algorithms. These results can be quickly applied to ameliorate accuracy and validity of various applications related to radiative transfer through the atmosphere in China. Key Points: Ten fundamental aerosol models in China are derived from a cluster study based on the ground‐based remote sensing measurements of SONETFive fine‐particle aerosol models include urban polluted, secondary polluted, combined polluted, polluted fly ash, and continental backgroundFive coarse‐particle aerosol models include summer fly ash, winter fly ash, primary dust, transported dust, and background dust [ABSTRACT FROM AUTHOR]

High entry speed (>25 km s−1) and low density (<2500 kg m−3) are the two factors that lower the chance of a meteoroid to drop meteorites. The 26 g carbonaceous (CM2) meteorite Maribo recovered in Denmark in 2009 was delivered by a bright bolide observed by several instruments across northern and central Europe. By reanalyzing the available data, we confirmed the previously reported high entry speed of (28.3 ± 0.3) km s−1 and trajectory with slope of 31° to the horizontal. In order to understand how such a fragile material survived, we applied three different models of meteoroid atmospheric fragmentation to the detailed bolide light curve obtained by radiometers located in Czech Republic. The Maribo meteoroid was found to be quite inhomogeneous with different parts fragmenting at different dynamic pressures. While 30–40% of the (2000 ± 1000) kg entry mass was destroyed already at 0.02 MPa, another 25–40%, according to different models, survived without fragmentation up to the relatively large dynamic pressures of 3–5 MPa. These pressures are only slightly lower than the measured tensile strengths of hydrated carbonaceous chondrite (CC) meteorites and are comparable with usual atmospheric fragmentation pressures of ordinary chondritic (OC) meteoroids. While internal cracks weaken OC meteoroids in comparison with meteorites, this effect seems to be absent in CC, enabling meteorite delivery even at high speeds, though in the form of only small fragments. [ABSTRACT FROM AUTHOR]

A primary goal of the Deep Blue (DB) project is to create consistent long‐term aerosol data records, suitable for climate studies, using multiple satellite instruments. In order to continue Earth Observing System (EOS)‐era aerosol products into the Joint Polar Satellite System era, we have successfully ported the DB algorithm to process data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Although the basic structure of the VIIRS algorithm is similar to that for the Moderate Resolution Imaging Spectroradiometer (MODIS), many enhancements have been made compared to the MODIS collection 6 (C6) version. Most have also been implemented in the latest MODIS Collection 6.1 (C6.1). For example, a new smoke mask was developed based on the spectral curvature of measured reflectance to distinguish biomass burning smoke from weakly absorbing urban/industrial aerosols. Consequently, a new aerosol‐type flag was added into the VIIRS DB data set. In addition, new dust models have been developed to account for the nonsphericity of mineral dust. As a result, a discontinuity in the retrieved aerosol optical depth (AOD) of Saharan dust plumes seen in MODIS C6 products near the boundary between North Africa and the Atlantic has been much reduced. We have also evaluated the VIIRS and MODIS Terra/Aqua C6.1 AOD against Aerosol Robotic Network data. VIIRS and MODIS retrievals show similar performance; around 80% of matchups agree with Aerosol Robotic Network within the expected error of ±(0.05 + 20)%, indicating that DB can provide consistent AOD through the historical EOS and present Joint Polar Satellite System eras. Key Points: The Deep Blue algorithm can now be applied to VIIRS measurements and provide global aerosol information over land and oceanNew aerosol‐type product has been added into VIIRS Deep Blue data suite, which can distinguish biomass burning smoke from other aerosolsThe comparisons between MODIS and VIIRS aerosol time series indicate good consistency in AOD between these sensors [ABSTRACT FROM AUTHOR]

In a histogram of lunar impact ages from the Apollo 16 site, there is a spike circa 3.9 Ga that has been interpreted to represent either a large number of nearly synchronous events or an abundance of samples that were affected slightly differently by the event that produced the Imbrium basin. To further scrutinize those age relationships, we extracted six centimeter‐sized clasts of impact melt from ancient regolith breccia 60016 and performed petrological and geochronological (40Ar‐39Ar) analyses. Three clasts have similar poikilitic textures, while others have porphyritic, aphanitic, or intergranular textures. Compositions and abundances of relict minerals are different in all six clasts and variously imply Mg‐suite and ferroan anorthosite target sequences. Estimated bulk compositions of four clasts are similar to previously defined group 1 Apollo 16 impact melt rocks, while the other two have higher Al2O3 and lower FeO+MgO compositions. All six clasts have similar K2O and P2O5 concentrations, which could have been derived from a KREEP‐bearing component among target sequences. Eighteen 40Ar/39Ar analyses of the six clasts produced an age range from 3823 ± 75 to 4000 ± 23 Ma, consistent with estimates for the proposed late heavy bombardment. Four clasts have multiple temperature steps that define plateau ages. These ages are distinct, so they cannot be explained by a single impact event, such as the one that produced the Imbrium impact basin. The conclusion that these represent distinct ages remains after considering the possibility of artifacts in defining plateaus. [ABSTRACT FROM AUTHOR]

In order to satisfy the requirement of calibration precision and traceability for space remote sensor, the absolute radiance calibration primary radiometer (ARCPR) is investigated for establishing the irradiance calibration standard in orbit. ARCPR is a mechanical cryogenic absolute radiometer for space application, and works at 20 K. The cryogenic environment is obtained by the Stryn-type pulse tube cryocooler. The environment temperature is stable at 23.9658 K by high-precision temperature controllers. The detector of ARCPR is designed and investigated based on the experimental prototype. The experimental results of detector characteristics measurement illustrate that the sensitivity is 3.9526 K/mW, and the thermal time constant is 134 s. The procedure of optical power measurement is optimised for satisfying the requirements of in orbit measurement. ARCPR achieves a relative standard uncertainty of 210 ppm at an optical power level of 0.4 mW. Therefore, ARCPR could be the radiometric standard for optical measurement. Furthermore, the investigation result provides the theoretical and experimental basis for the establishment of radiometric calibration standard in orbit. [ABSTRACT FROM AUTHOR]

In order to satisfy the requirement of calibration precision and traceability for space remote sensor, the absolute radiance calibration primary radiometer (ARCPR) is investigated for establishing the irradiance calibration standard in orbit. ARCPR is a mechanical cryogenic absolute radiometer for space application, and works at 20K. The cryogenic environment is obtained by the Stryn‐type pulse tube cryocooler. The environment temperature is stable at 23.9658K by high‐precision temperature controllers. The detector of ARCPR is designed and investigated based on the experimental prototype. The experimental results of detector characteristics measurement illustrate that the sensitivity is 3.9526K/mW, and the thermal time constant is 134s. The procedure of optical power measurement is optimised for satisfying the requirements of in orbit measurement. ARCPR achieves a relative standard uncertainty of 210ppm at an optical power level of 0.4mW. Therefore, ARCPR could be the radiometric standard for optical measurement. Furthermore, the investigation result provides the theoretical and experimental basis for the establishment of radiometric calibration standard in orbit. [ABSTRACT FROM AUTHOR]