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The Kansas Mesonet is a multipurpose network consisting of 62 automated environmental monitoring stations (as of 2019) covering the state of Kansas. Each station is equipped with research-grade instrumentation and measures precipitation, air temperature, air relative humidity, barometric pressure, wind speed and direction, solar radiation, soil temperature, and soil moisture. Observations are transferred to dedicated computer servers every 5 min via cellular modems. Data are archived and subjected to periodic quality control tests and are disseminated in near–real time through a dedicated web portal. The observations collected by the Kansas Mesonet are widely used for irrigation water management, crop modeling, pest management, wildland fire management, drought monitoring, wind energy production, environmental research, and animal management. This paper provides a technical overview of the Kansas Mesonet and includes a complete description of the instrumentation, siting criteria, instrument verification procedures, and value-added products. [ABSTRACT FROM AUTHOR]

This paper discusses the application of principal component analysis and stepwise regression in the retrieval of vertical profiles of temperature and humidity based on the measurements of a 35-channel microwave radiometer. It uses the radiosonde data of 6 yr from Hong Kong, China, and the monochromatic radiative transfer model (MonoRTM) to calculate the brightness temperatures of the 35 channels of the radiometer. The retrieval of the atmospheric profile is then established based on principal component analysis and stepwise regression. The accuracy of the retrieval method is also analyzed. Using an independent sample, the root-mean-square error of the retrieved temperature is less than 1.5 K, on average, with better retrieval results in summer than in winter. Likewise, the root-mean-square error of the retrieved water vapor density reaches a maximum value of 1.4 g m−−3 between 0.5 and 2 km, and is less than 1 g m−−3 for all other heights. The retrieval method is then applied to the actual measured brightness temperatures by the 35-channel microwave radiometer at a station in Nansha, China. It is shown that the statistical model as developed in this paper has better retrieval results than the profiles obtained from the neural network as supplied with the radiometer. From numerical analysis, the error with the water vapor density retrieval is found to arise from the treatment of cloud liquid water. Finally, the retrieved profiles from the radiometer are studied for two typical weather phenomena during the observation period, and the retrieved profiles using the method discussed in the present paper is found to capture the evolution of the atmospheric condition very well. [ABSTRACT FROM AUTHOR]

Automated quality control is a necessity for meteorological measurement networks because of an ever-increasing number of measurements. One of the basic quality control tests is to check that the observations fall into a range of acceptable values. This paper proposes an algorithm for the automatic determination of maximum and minimum thresholds for such a test. The automated algorithm results in more statistically justified thresholds compared to the operator-fed values, which some quality control systems normally use. The suggested algorithm is a tuning-free method for the determination of daily minimum and maximum limits. The basis of the algorithm is, first, to collect the essential statistics of observations during their annual cycle and, second, to use these statistics to determine the acceptable observation range. This paper introduces a semirecursive version with lower computational requirements and discusses additional algorithmic details. The algorithm is demonstrated through numerical examples, which show that limits converge to satisfactory values in a few years. [ABSTRACT FROM AUTHOR]

Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist's smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.038-0.058C for temperature and of 0.18%-0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect. [ABSTRACT FROM AUTHOR]

The observation accuracy of the surface air temperature less than 0.1K is a requirement, stated by the meteorological and climatological community. However, the accuracy of a temperature sensor inside a shield is affected by a number of factors including solar radiation, wind speed, upwelling longwave radiation, air density, sun elevation angle, sun azimuth angle, underlying surface, precipitation, moisture, structure, and coating of the radiation shield. Due to these factors, the temperature error of the temperature sensor may be much larger than 1K under adverse conditions. To improve the observation accuracy, this paper proposed a spherical temperature sensor array. A series of analytical calculations based on a computational fluid dynamics (CFD) method is performed to verify the design principle of this sensor array. The calculation results show that the temperature error ratio can be assumed as a constant. To verify the accuracy of this sensor array, simulations and observation experiments are conducted. The simulation results show that the mean difference between the temperature provided by this sensor array and the reference air temperature is 0.072 K. The field experiment results show that a root-mean-square error (RMSE) and a mean absolute error (MAE) between the temperature provided by this sensor array and the reference air temperature are 0.173 and 0.153 K, respectively. [ABSTRACT FROM AUTHOR]

The scattering of microwaves at frequencies between 50 and 200 GHz by ice particles in the atmosphere is an essential element in the retrieval of instantaneous surface precipitation from spaceborne passive radiometers. This paper explores how the variable distribution of solid and liquid hydrometeors in the atmospheric column over land surfaces affects the brightness temperature (TB) measured by GMI at 89 GHz through the analysis of Dual-Frequency Precipitation Radar (DPR) reflectivity profiles along the 89-GHz beam. The objective is to refine the statistical relations between observed TBs and surface precipitation over land and to define their limits. As GMI is scanning with a 53° Earth incident angle, the observed atmospheric volume is actually not a vertical column, which may lead to very heterogeneous and seemingly inconsistent distributions of the hydrometeors inside the beam. It is found that the 89-GHz TB is mostly sensitive to the presence of ice hydrometeors several kilometers above the 0°C isotherm, up to 10 km above the 0°C isotherm for the deepest convective systems, but is a modest predictor of the surface precipitation rate. To perform a precise mapping of atmospheric ice, the altitude of the individual ice clusters must be known. Indeed, if variations in the altitude of ice are not accounted for, then the high incident angle of GMI causes a horizontal shift (parallax shift) between the estimated position of the ice clusters and their actual position. We show here that the altitude of ice clusters can be derived from the 89-GHz TB itself, allowing for correction of the parallax shift. [ABSTRACT FROM AUTHOR]

This paper presents a unique instrument for characterizing the impact of wet radomes in radar systems. The proposed technique enables full radio frequency (RF) characterization of the radome, by evaluating its performance under a variety of conditions, including dirtiness, wetness, ice formation, and varying temperature, and providing a potential solution for future wet radome calibration methods. The reflections generated from the wet radome surface, measured from a high-resolution probe, are combined with an estimation of water absorption as a function of the precipitation rain rate, to calculate the attenuation introduced by the wet radome. This instrument is a cost-effective solution that can be integrated into an existing or new radar system. [ABSTRACT FROM AUTHOR]

Satellite observations in the shortwave infrared (SWIR) part of spectrum between 3.5 and 4.0 μm deliver critically important information for many applications. The satellite signal in this spectral band consists of solar-reflected radiation and thermal radiation emitted by surface, clouds, and atmosphere. Accurate retrievals require precise knowledge of solar irradiance values within a channel's bandwidth. The magnitudes of solar irradiance for shortwave infrared channels (3.7–3.9 μm) for the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration-7 (NOAA-7) to NOAA-18 satellites and the Geostationary Operational Environmental Satellite-8 (GOES-8) to GOES-12 are considered in this paper. Four recent solar reference spectra [those of Kurucz, Gueymard, the American Society for Testing and Materials (ASTM), and Wehrli] are analyzed to determine uncertainties in the knowledge of solar irradiance values for SWIR channels of the listed sensors. Because thermal radiation is frequently converted to effective blackbody temperature for analysis, computations, and calibration purposes, it is proposed here to express band-limited solar irradiance values in terms of brightness temperature as well. It is shown that band-limited solar irradiance for AVHRR radiometers expressed in terms of blackbody equivalent brightness temperature correspond to the range 355–360 K, and vary around 345 K for the SWIR channels of the GOES imagers. The values of band-limited solar irradiance and brightness temperatures are provided for various reference solar spectra. The relative differences in band-limited solar irradiance computed for the considered reference solar spectra are between 0% and 2.5%. Differences expressed in terms of brightness temperatures may reach 0.8 K. The results for the ASTM and the Kurucz reference spectra agree within 0.1% relative difference. Parameters of linear fits relating effective brightness temperatures and spectral radiance equivalent temperatures are also determined for all sensors. They are required for precise radiance–temperature and temperature–radiance conversion through Planck's functions in the case of the finite spectral response of real sensors. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement (GPM) Core Observatory was launched on 27 February 2014. One of the principal instruments on the spacecraft is the GPM Microwave Imager (GMI). This paper describes the absolute calibration of the GMI antenna temperature ( T A) and the earth brightness temperature ( T B). The deep-space observations taken on 20 May 2014, supplemented by nadir-viewing data, are used for the T A calibration. Data from two backlobe maneuvers are used to determine the primary reflector's cold-space spillover, which is required to convert the T A into T B. The calibrated GMI observations are compared to predictions from an ocean radiative transfer model (RTM) using collocated WindSat ocean retrievals as input. The mean difference when averaged globally over 13 months does not exceed 0.1 K for any of the nine channels from 11 to 89 GHz. The RTM comparisons also show that there are no significant solar intrusion errors in the GMI hot load. The absolute accuracy of the GMI instrument is defined as the average ocean-viewing error of the measured T A or T B relative to the true T A or T B. Based on the analyses herein, the GMI absolute accuracy for T A is estimated to be about 0.1 K rms over all channels and 0.25 K rms over all channels for T B. [ABSTRACT FROM AUTHOR]

A new approach to passive microwave retrievals of precipitation is described that relies on an objective dimensional reduction procedure to filter, normalize, and decorrelate geophysical background noise while retaining the majority of radiometric information concerning precipitation. The dimensional reduction also sharply increases the effective density of any a priori database used in a Bayesian retrieval scheme. The method is applied to passive microwave data from the Tropical Rainfall Measuring Mission (TRMM), reducing the original nine channels to three 'pseudochannels' that are relatively insensitive to most background variations occurring within each of seven surface classes (one ocean plus six land and coast) for which they are defined. These pseudochannels may be used in any retrieval algorithm, including the current standard Goddard profiling algorithm (GPROF), in place of the original channels. The same methods are also under development for the Global Precipitation Measurement (GPM) Core Observatory Microwave Imager (GMI). Starting with the pseudochannel definitions, a new Bayesian algorithm for retrieving the surface rain rate is described. The algorithm uses an a priori database populated with matchups between the TRMM precipitation radar (PR) and the TRMM Microwave Imager (TMI). The explicit goal of the algorithm is to retrieve the PR-derived best estimate of the surface rain rate in portions of the TMI swath not covered by the PR. A unique feature of the new algorithm is that it provides robust posterior Bayesian probabilities of pixel-averaged rain rate exceeding various thresholds. Validation and intercomparison of the new algorithm is the subject of a companion paper. [ABSTRACT FROM AUTHOR]

NASA's Clouds and the Earth's Radiant Energy System (CERES) project is responsible for operation and data processing of observations from scanning radiometers on board the Tropical Rainfall Measuring Mission (TRMM), Terra, Aqua, and Suomi National Polar-Orbiting Partnership (NPP) sateliites. The clouds and radiative swath (CRS) CERES data product contains irradiances computed using a radiative transfer model for nearly all CERES footprints in addition to top-of-atmosphere (TOA) irradiances derived from observed radiances by CERES instruments. This paper describes a method to constrain computed irradiances by CERES-derived TOA irradiances using Lagrangian multipliers. Radiative transfer model inputs include profiles of atmospheric temperature, humidity, aerosols and ozone, surface temperature and albedo, and up to two sets of cloud properties for a CERES footprint. Those inputs are adjusted depending on predefined uncertainties to match computed TOA and CERES-derived TOA irradiance. Because CERES instantaneous irradiances for an individual footprint also include uncertainties, primarily due to the conversion of radiance to irradiance using anisotropic directional models, the degree of the constraint depends on CERES-derived TOA irradiance as well. As a result of adjustment, TOA computed-minus-observed standard deviations are reduced from 8 to 4 W m-2 for longwave irradiance and from 15 to 6 W m-2 for shortwave irradiance. While agreement of computed TOA with CERES-derived irradiances improves, comparisons with surface observations show that model constrainment to the TOA does not reduce computation bias error at the surface. After constrainment, shortwave down at the surface has an increased bias (standard deviation) of 1% (0.5%) and longwave increases by 0.2% (0.1%). Clear-sky changes are negligible. [ABSTRACT FROM AUTHOR]

This paper presents the design and evaluates the performance of a double-walled electrically aspirated radiation shield for thermometers measuring air temperature and its gradients in the atmospheric surface layer. Tests were performed to quantify its solar radiation error and wake production, and to characterize the observer effect of the forced aspiration on vertical temperature gradients in the calm and stable boundary layer. Construction requirements were to design a unit that uses inexpensive off-the-shelf components, to assemble easily, to facilitate reconfiguration to accommodate various sensors, and to reduce power consumption with the goal of reducing costs and enabling use in sensor networks in remote locations. The custom-aspirated shield was evaluated in reference to a triple-walled commercially available model and subjected to rigorous testing in a wind tunnel and field experiments. The relative radiation error of air temperature measurements in the custom-aspirated shield was equal to or smaller than that in the reference shield within ±0.08 K for solar irradiances ≥1000 W m−2 and calm winds. At night, thermal imagery revealed no significant differences in surface temperatures of both shields and the air temperature. Both shields produced significant wake within a ±30° sector of incident flow. Even for weak flows ≤0.7 m s−1, higher-order moments were increased by a factor of 3, while the mean airflow speed was reduced by up to 30% compared to uncontaminated directions. Careful inspection of the spatiotemporal dynamics of air temperatures in a vertical profile showed negligible impact of the forced aspiration on the finescale structure of the observations for the nocturnal and transitional calm surface layers. [ABSTRACT FROM AUTHOR]

The occurrence of a bright band, a layer of enhanced reflectivity due to melting of aggregated snow, increases uncertainties in radar-based quantitative precipitation estimation (QPE). The height of the brightband layer is an indication of 0°C isotherm and can be useful in identifying areas of potential icing for aviation and in the data assimilation for numerical weather prediction (NWP). Extensive analysis of vertical profiles of reflectivity (VPRs) derived from the Weather Surveillance Radar-1988 Doppler (WSR-88D) base level data showed that the brightband signature could be easily identified from the VPRs. As a result, an automated brightband identification (BBID) scheme has been developed. The BBID algorithm can determine from a volume scan mean VPR and a background freezing level height from a numerical weather prediction model whether a bright band exists and the height of the brightband layer. The paper presents a description of the BBID scheme and evaluation results from a large dataset from WSR-88D radars in different geographical regions and seasons. [ABSTRACT FROM AUTHOR]

This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from ∼0.3 to 0.9 K (0.5–0.8 g m-3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined. [ABSTRACT FROM AUTHOR]

Geostationary infrared sounding missions offer good temporal coverage; however, because of the large distance to the observed earth targets, the effect of diffraction is increased compared to sounding from a low earth orbit (LEO). Because of the wavelength dependence of diffraction, the spectral channels do not sample the same volume of air, as is generally assumed by retrieval algorithms for LEO infrared (IR) sounder data. This additional error introduced in the retrieval by diffraction-limited instruments is called pseudonoise throughout the paper. One such diffraction-limited geostationary system is the candidate Infrared Sounder (IRS) mission on the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteosat Third Generation (MTG) satellites with a planned need date in 2015, due to the expected lifetime of the current Meteosat Second Generation (MSG) satellites. A simplified point spread function (PSF) is applied. To represent the channels within natural conditions, measured spectra from the LEO Atmospheric Infrared Sounder (AIRS) are used as an underlying scene when integrating over the PSF. As the AIRS spatial resolution is 15 km, the basic assumption made was that the meteorological and surface features can be regarded as fractal to the extent that they can be downscaled to at least 4 km, making them useful for these investigations. The results show that the pseudonoise is highly dependent on wavelength, and highest in the window and CO2 regions (within the broader 700–1200 cm-1, or 8.3–14.3-μm, region). The worst-case pseudonoise values are approximately 1 K for these regions. A case study of the impact of the obtained pseudonoise values on temperature and water vapor retrievals shows that only with the worst-case assumptions (uncorrelated noise) is there a quantifiable impact on the results. For temperature retrievals, this ranged from 0.1 to 0.3 K in the lower and upper troposphere, respectively. [ABSTRACT FROM AUTHOR]

During 30 days in May and June 2003, the R/V Southern Surveyor was operating in the Gulf of Carpentaria, northern Australia. Measurements of sea surface temperature (SST) were made with an accurate single-channel infrared radiometer as well as with the ship’s thermosalinograph. These ship-based measurements have been used to assess the quality of the SST derived from nine satellite-borne instruments. The satellite dataset compiled during this period also allows the intercomparison of satellite-derived SST fields in areas not covered by the ship’s track. An assessment of the SST quality from each satellite instrument is presented, and suggestions for blending ground and satellite measurements into a single product are made. These suggestions are directly applicable to the international Global Ocean Data Assimilation Experiment (GODAE) High Resolution SST Pilot Project (GHRSST-PP) that is currently developing an operational system to provide 6-hourly global fields of SST at a spatial resolution close to 10 km. The paper demonstrates how the Diagnostic Datasets (DDSs) and Matchup Database (MDB) of the GHRSST-PP can be used to monitor the quality of individual and blended SST datasets. Recommendations for future satellite missions that are critical to the long-term generation of accurate blended SST datasets are included. [ABSTRACT FROM AUTHOR]

Rawinsonde heights and temperatures have been quality controlled using complex quality control at the National Centers for Atmospheric Prediction since December 1988 when an algorithm using only hydrostatic checking was introduced for the checking of mandatory level heights and temperatures. The quality control of significant level temperatures was added to the hydrostatic code in April 1990. In November 1991, the mandatory level checking was greatly expanded and improved by the inclusion of additional checks: increment (observation minus 6-h forecast), horizontal, and vertical. This paper describes a major improvement to the significant level quality control, introduced in May 1994, using complex quality control techniques. The philosophy of the method and the various checks are described. The principles of the decision-making algorithm are stated, examples are shown, and some statistics of the use of the significant level checking are presented. [ABSTRACT FROM AUTHOR]

A mobile profiling system has been developed that is capable of probing the atmosphere from the surface to over 30 km. The Mobile Profiling System (MPS) combines ground-based instruments, including a five-beam 924-MHz radar wind profiler, a radio acoustic sounding system, and two passive microwave sounders, with a receiver and processor for meteorological satellite data. Software in the MPS produces profiles from the surface to the highest satellite sounding level by combining surface data and profiles generated from the suite of ground-based sensors with those from a meteorological satellite. The algorithms generate soundings of temperature, humidity, wind velocity, and other meteorological variables. The method for combining data from the separate sources is not site specific and requires no a priori information. The MPS has the potential for a variety of applications, including detailed analysis of meteorological variables for research and operations over mesoscale areas, such as regional pollution studies and severe storm forecasting. This paper describes the method for merging data from satellite and ground-based remote sensing systems, and presents results from a series of field tests of both individual sensors and combined soundings. Accuracy of the combined soundings appears comparable to that from rawinsonde with the exception of wind velocity at satellite sounding altitudes. The MPS has operated successfully in several different climates: in the Los Angeles Free Radical Experiment at Claremont, California, and in tests at White Sands Missile Range, New Mexico; Erie, Colorado; Ft. Sill, Oklahoma; and Wallops Island, Virginia. [ABSTRACT FROM AUTHOR]

Presents an algorithm for obtaining the rate of turbulent kinetic energy dissipation by fitting the theoretical Batchelor spectrum to the temperature gradient spectrum at high wavenumbers. Features of temperature gradient spectra; Examples of fitting to data; Accuracy; Statistical stationarity.

Obtaining quality air temperature measurements in complex mesoscale environments, such as thunderstorms or frontal zones, is problematic and is particularly challenging from a moving platform. For some time, mobile weather platforms known as mobile mesonets (MMs) have used custom aspirated temperature shields. The original design was known as the "J-tube," which addresses some but not all of the unique problems associated with mobile temperature measurements. For VORTEX2 2009, a second, well-documented shield, the R.M. Young (RMY) 43408, was included but was also found to have certain shortcomings in some severe weather environments. Between the end of VORTEX2 2009 and the start of VORTEX2 2010, a third and new shield called the "U-tube" was designed, tested, and installed. Reported here are the results of efforts to better characterize the J-Tube, RMY 43408, and U-tube. Several tests designed to isolate key aspects of a radiation shield's performance, such as performance in rain, high solar radiation, varying wind conditions, and general response time, were completed. A period of intercomparison among the three shields during the 2010 season of VORTEX2 is also used to highlight each shield being used in "real world" conditions. Results indicate that the U-tube has several significant advantages over the J-tube and 43408 in terms of aspiration rate, sampling efficiency, performance during rain, variable winds, and high solar radiation periods, as well as response time. Given these results, the U-tube should be utilized for mobile observations going forward. Significance Statement: Observations of the atmosphere are a critical component of research, particularly that involving severe weather. Errors, biases, and incorrect readings of these observations can cause problems during analysis or lead to incomplete or even incorrect conclusions. Radiation shields used for temperature observations are used to protect sensors but can have a significant effect on the observations themselves. Older radiation shields such as the "J-tube" are shown here to have some potential problem areas when using them to house temperature sensors. A new shield, the "U-tube," has been created to mitigate these effects and to provide a functional radiation shield capable of performing in a wide range of conditions, from severe weather (thunderstorms, hurricanes, etc.) to more calm weather. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System (GNSS) radio occultation (RO) is a remote sensing technique that uses International System of Units (SI) traceable GNSS signals for atmospheric limb soundings. The retrieved atmospheric temperature profile is believed to be more accurate and stable than those from other remote sensing techniques, although rigorous comparison between independent measurements is difficult because of time and space differences between individual RO events. Typical RO comparisons are based on global statistics with relaxed matchup criteria (within 3 h and 250 km) that are less than optimal given the dynamic nature and spatial nonuniformity of the atmosphere. This study presents a novel method that allows for direct comparison of bending angles when simultaneous RO measurements occur near the simultaneous nadir overpasses (SNO) of two low-Earth-orbit satellites receiving the same GNSS signal passing through approximately the same atmosphere, within minutes in time and less than 125 km in distance. Using this method, we found very good agreement between Formosa Satellite 7 (FORMOSAT-7)/second Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) satellite measurements and those from MetOp-A/B/C, COSMIC-1, Korea Multi-Purpose Satellite 5 (KOMPSAT-5), and Paz, although systematic biases are also found in some of the intercomparisons. Instrument and processing algorithm performances at different altitudes are also characterized. It is expected that this method can be used for the validation of GNSS RO measurements for most missions and would be a new addition to the tools for intersatellite calibration. This is especially important given the large number of RO measurements made available both publicly and commercially, and the expansion of receiver capabilities to all GNSS systems. [ABSTRACT FROM AUTHOR]

A linear inversion algorithm to derive changes of surface skin temperature and atmospheric temperature and specific humidity vertical profiles using spatially and temporally averaged spectral radiance differences is developed. The algorithm uses spectral radiative kernels, which is the top-of-atmosphere spectral radiance change caused by perturbations of skin temperature and air temperature and specific humidity in the atmosphere, and is an improved version of the algorithm used in earlier studies. Two improvements are the inclusion of the residual and cloud spectral kernels in the form of eigenvectors of principal components. Three and six eigenvectors are used for, respectively, the residual and cloud spectral kernels. An underlying assumption is that the spectral shape of the principal components is constant and their magnitude varies temporally and spatially. The algorithm is tested using synthetic spectral radiances with the spectral range of the Atmospheric Infrared Sounder averaged over 16 days and over a 108 × 108 grid box. Changes of skin temperature, air temperature, and specific humidity vertical profiles are derived from the difference of nadir-view all-sky spectral radiances. The root-mean-square difference of retrieved and true skin temperature differences is 0.59 K. The median of absolute errors in the air temperature change is less than 0.5K above 925 hPa. The median of absolute errors in the relative specific humidity changes is less than 10% above 825 hPa. [ABSTRACT FROM AUTHOR]

Screen-level air temperature measurements at surface observation stations are influenced by local-site-scale factors. These local influences may affect global-scale climate change studies. This study investigated the influence of surface obstacles on air temperature measurements at the screen level at climate observation stations in Japan. Screen-level air temperature was measured simultaneously at two neighboring sites (<100 m apart) that differed in terms of their openness. Daytime air temperature was 0°–1°C higher at the narrower site, and theoretical analysis revealed that this warming was caused by poor ventilation. At night, poor ventilation at the narrower site caused the air temperature to be 0°–0.2°C lower, which was demonstrated experimentally and by theoretical analysis. The range of temperature changes due to site narrowing shown in this study is not negligible in climate change studies. Guidelines for site maintenance and metadata recoding were consequently proposed in terms of site openness. [ABSTRACT FROM AUTHOR]

The temperature of Earth's atmosphere has been monitored continuously since late 1978 by the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit (AMSU) flown on polar-orbiting weather satellites. It is well known that these measurements are affected by the scattering and emission from hydrometeors, including cloud water, precipitation, and ice particles. In this study the hydrometeor effects on MSU/AMSU temperature observations are investigated by comparing satellite-observed temperature of the middle troposphere (TMT) with synthetic TMT constructed using temperature fields from ECMWF Interim [ERA-Interim (ERA-I)]. Precipitation data have been used to estimate how much of the difference between these two TMT fields is due to hydrometeor contamination effects. It is shown that there exists a robust linear proportionality between TMT deficit (i.e., the measured TMT minus the synthetic TMT) and precipitation at individual grid points in monthly mean fields. The linear correlation is even stronger in the annual mean and seasonally varying climatology and also in the spatial pattern of ENSO-related anomalies. The linear regression coefficient obtained in all of these analyses is virtually identical: -0.042K (mm day-1)-1. The channel that senses lower-tropospheric temperature (TLT) is more sensitive to precipitation than the TMT channel: the regression coefficient is 20.059K (mm day-1)-1. It is shown that correcting the TMT or TLT monthly anomalies by removing the hydrometeor contamination does not significantly influence estimates of tropical mean temperature trends, but it could affect the pattern of temperature trend over the tropical oceans. [ABSTRACT FROM AUTHOR]

Two comparative studies have been performed to evaluate the accuracy of Chinese Aircraft Meteorological Data Relay (AMDAR) weather reports. The comparison between AMDAR reports and radiosonde observations shows that the root-mean-square differences (RMSDs) in temperature, wind speed, and wind direction are 1.06°C, 1.95ms-1, and 22°, respectively, within a spatial range of ≤20 km and a temporal window of ≤15 min. The comparison between AMDAR reports collected by different aircraft reveals that observation uncertainties in temperature, wind speed, and wind direction are 0.59°C, 0.90ms-1, and 12°, respectively. The spatial and temporal representativeness as well as the environmental factors that may affect the evaluation results are also discussed in detail in the two comparative studies. The results of the present study provide valuable information on and high confidence in the application of Chinese AMDAR in numerical weather prediction models. [ABSTRACT FROM AUTHOR]

Open-path eddy covariance systems are widely used for measuring the CO2 flux between land and atmosphere. A common problem is that they often yield negative fluxes or physiologically unreasonable CO2 uptake fluxes in the nongrowing season under cold conditions. In this study, a meta-analysis was performed on the eddy flux data from 64 FLUXNET sites and the relationship between the observed CO2 flux and the sensible heat flux was analyzed. In theory, these two fluxes should be independent of each other in cold conditions (air temperature lower than 0°C) when photosynthesis is suppressed. However, the results show that a significant and negative linear relationship existed between these two fluxes at 37 of the sites. The mean linear slope value is −0.008 ± 0.001 µmol m−2 s−1 per W m−2 among the 64 sites analyzed. The slope value was not significantly different among the three gas analyzer models (LI-7500, LI-7500A, IRGASON/EC150) used at these sites, indicating that self-heating may not be the only reason for the apparent wintertime net CO2 uptake. These results suggest a systematic bias toward larger carbon uptakes in the FLUXNET sites that deploy open-path eddy covariance systems. [ABSTRACT FROM AUTHOR]

Thermodynamic retrievals can derive pressure and temperature information from kinematic measurements in regions where no in situ observations are available. This study presents a new retrieval technique called SAMURAI-TR (Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation-Thermodynamic Retrieval) that derives three-dimensional fields of pressure and density potential temperature from multiple-Doppler radar data using a variational approach. SAMURAI-TR advances existing methods by 1) allowing for a horizontal variation in the reference-state definition and 2) representing the retrieved quantities of pressure and temperature as three-dimensional functions consisting of a series of finite-element cubic B-splines. The first advancement enables the retrieval to explicitly account for the large radial gradient of the mean thermodynamic state in tropical cyclones and other rapidly rotating vortices. The second advancement allows for specification of the three-dimensional pressure and temperature gradients as pseudo-observations from Doppler-derived winds, effectively linking the vertical levels without the use of the thermodynamic equation or a microphysical closure. The retrieval uses only the horizontal and vertical momentum equations, their derivatives, and low-pass filters. The accuracy and sensitivity of the retrieval are assessed using a WRF simulation of a tropical cyclone. SAMURAI-TR has good accuracy compared to prior techniques and retrieves pressure to within 0.25 hPa and temperature to within 0.7 K RMSE. The application of the method to real data is demonstrated using multiple-Doppler data from Hurricane Rita (2005). [ABSTRACT FROM AUTHOR]

An analysis is conducted for the first time to statistically quantify the relationship between the evaporation duct and oceanic evaporation. Through sensitivity analysis, under unstable conditions (air-sea temperature difference less than zero), evaporation duct and evaporation are found to maintain a similar trend with variations in air-sea variables, indicating a possible inherent connection. Furthermore, scatterplots of relevant historical data reveal that the evaporation duct generally increases in a power-law manner with evaporation. Therefore, logarithmic transformation is performed on the data, and then linear regression is adopted to derive the analytical expression of the linear trend. Additionally, based on this analytical expression, a three-parameter empirical model is proposed to estimate the temporal clustering, and the estimated result shows good agreement with the real distribution. The spatial variations of the parameters modeled over different focus areas reflect the influence of geophysical parameters. [ABSTRACT FROM AUTHOR]

The natural sound generated by an unmanned aerial vehicle is used in conjunction with tomography to remotely sense the virtual temperature and wind profiles of the atmosphere in a horizontal plane up to an altitude of 1200 m and over a baseline of 600 m. Sound fields recorded on board the aircraft and by an array of microphones on the ground are compared and converted to sound speed estimates for the ray paths intersecting the intervening medium. Tomographic inversion is then used to transform these sound speed values into two-dimensional profiles of virtual temperature and wind vector, which enables the atmosphere to be visualized and monitored over time. The wind vector and temperature estimates are compared to measurements taken by a collocated midrange Doppler sodar and sensors on board the aircraft. Large-eddy simulations of daytime atmospheric boundary layers and error models of the tomographic inversion and sodar are also used to assess the magnitude and nature of anticipated differences. Both the simulations and field trials data show similar levels of correspondence between the tomographically derived and independently observed measurements. [ABSTRACT FROM AUTHOR]

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where routine weather observations are scarce. Previous studies showed that smartphone battery temperature readings can be used to estimate the daily and citywide air temperature via a direct heat transfer model. This work extends model estimates by studying smaller temporal and spatial scales. The study finds the number of battery readings influences the accuracy of temperature retrievals. Optimal results are achieved for 700 or more retrievals. An extensive dataset of over 10 million battery temperature readings for estimating hourly and daily air temperatures is available for São Paulo, Brazil. The air temperature estimates are validated with measurements from a WMO station, an Urban Flux Network site, and data from seven citizen weather stations. Daily temperature estimates are good (coefficient of determination ρ2 of 86%), and the study shows they improve by optimizing model parameters for neighborhood scales (<1 km2) as categorized in local climate zones (LCZs). Temperature differences between LCZs can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, the model requires a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking. [ABSTRACT FROM AUTHOR]

Upscaling point measurements from micrometeorological towers is a challenging task that is important for a variety of applications, for example, in process studies of convection initiation, carbon and energy budget studies, and the improvement of model parameterizations. In the present study, a technique was developed to determine the horizontal variability in sensible heat flux H surrounding micrometeorological towers. The technique was evaluated using 15-min flux observations, as well as measurements of land surface temperature and air temperature obtained from small unmanned aircraft systems (sUAS) conducted during a one-day measurement campaign. The computed H was found to be comparable to the micrometeorological measurements to within 5-10 W m−2. Furthermore, when comparing H computed using this technique with H determined using large-eddy simulations (LES), differences of <10 W m−2 were typically found. Thus, implementing this technique using observations from sUAS will help determine sensible heat flux variability at horizontal spatial scales larger than can be provided from flux tower measurements alone. [ABSTRACT FROM AUTHOR]

Results are presented from an intercomparison of temperature, humidity, and wind velocity sensors of the Tempest unmanned aircraft system (UAS) and the National Severe Storms Laboratory (NSSL) mobile mesonet (NSSL-MM). Contemporaneous evaluation of sensor performance was facilitated by mounting the Tempest wing with attached sensors to the NSSL-MM instrument rack such that the Tempest and NSSL-MM sensors could collect observations within a nearly identical airstream. This intercomparison was complemented by wind tunnel simulations designed to evaluate the impact of the mobile mesonet vehicle on the observed wind velocity. The intercomparison revealed strong correspondence between the temperature and relative humidity (RH) data collected by the Tempest and the NSSL-MM with differences generally within sensor accuracies. Larger RH differences were noted in the presence of heavy precipitation; however, despite the exposure of the Tempest temperature and humidity sensor to the airstream, there was no evidence of wet bulbing within precipitation. Wind tunnel simulations revealed that the simulated winds at the location of the NSSL-MM wind monitor were ~4% larger than the expected winds due to the acceleration of the flow over the vehicle. Simulated vertical velocity exceeded 1 m s−1 for tunnel inlet speeds typical of a vehicle moving at highway speeds. However, the theoretical noncosine reduction in winds that should result from the impact of vertical velocity on the laterally mounted wind monitor was found to be negligible across the simulations. Comparison of the simulated and observed results indicates a close correspondence, provided the crosswind component of the flow is small. [ABSTRACT FROM AUTHOR]

The objectives of this study were to compare average monthly and seasonal maximum and minimum temperatures of the Georgia Automated Environmental Monitoring Network (AEMN) to those of geographically close (i.e., paired) manual observations from U.S. Historical Climatology Network (USHCN) stations and Cooperative Observer Program (COOP) stations for the period 2002-13, and to evaluate the extent to which differences in siting characteristics of paired AEMN-USHCN stations contribute to the temperature differences. Correlations for monthly and seasonal maximum and minimum temperatures of paired AEMN-USHCN and AEMN-COOP stations were high and almost always significant, although the correlations for seasonal minimum temperatures were slightly lower than those of maximum temperatures, especially for summer. Monthly maximum and minimum temperatures and seasonal maximum temperatures of paired AEMN-USHCN and AEMN-COOP stations were significantly different in only a few instances, while seasonal minimum temperatures were more often significantly different, particularly for summer. The stronger relationship between maximum temperatures than minimum temperatures for paired stations is logical given that minimum temperatures typically occur when a shallow, decoupled nocturnal boundary layer is more sensitive to local conditions [e.g., land use/land cover (LULC)]. Stepwise regressions confirmed that a portion of the variance of seasonal minimum temperatures of paired AEMN-USHCN stations was explained by differences in LULC, while the variance in seasonal maximum temperatures was explained better by differences in elevation. Despite the generally close relationships between temperatures of paired stations and a portion of the differences being explained, an abrupt change from manual networks to the AEMN without data adjustments would change the Georgia climate record on monthly and seasonal time scales. [ABSTRACT FROM AUTHOR]

If the acoustic signature of an unmanned aerial vehicle (UAV) is observed as it overflies an array of ground microphones, then the projected and observed Doppler shifts in frequency of the narrowband tones generated by its engine may be compared and converted into effective sound speed values. This allows 2D and 3D spatially varying atmospheric temperature and wind velocity fields to be estimated using tomography. Errors in estimating sound speed values are inversely proportional to the rate of change in the narrowband tones received on the ground. As this rate of change typically approaches zero at least twice per microphone during the UAV's overflight, errors in the time of flight estimates are typically too large to deliver useful precision to the tomographically derived temperature and wind fields. However, these errors may be reduced by one or two orders of magnitude by continuously varying the engine throttle rate, thereby making the tomographic technique potentially feasible. This is demonstrated through reconstruction of realistic simulated conditions for a weakly sheared daytime convective atmospheric boundary layer. [ABSTRACT FROM AUTHOR]

A near-surface specific humidity (Qa) and air temperature (Ta) climatology on daily and 0.25° grids was constructed by the objectively analyzed air-sea fluxes (OAFlux) project by objectively merging two recent satellite-derived high-resolution analyses, the OAFlux existing 1° analysis, and atmospheric reanalyses. The two satellite products include the multi-instrument microwave regression (MIMR) Qa and Ta analysis and the Goddard Satellite-Based Surface Turbulent Fluxes, version 3 (GSSTF3), Qa analysis. This study assesses the degree of improvement made by OAFlux using buoy time series measurements at 137 locations and a global empirical orthogonal function (EOF) analysis. There are a total of 130 855 collocated daily values for Qa and 283 012 collocated daily values for Ta in the buoy evaluation. It is found that OAFlux Qa has a mean difference close to 0 and a root-mean-square (RMS) difference of 0.73 g kg−1, and Ta has a mean difference of −0.03°C and an RMS difference of 0.45°C. OAFlux shows no major systematic bias with respect to buoy measurements over all buoy locations except for the vicinity of the Gulf Stream boundary current, where the RMS difference exceeds 1.8°C in Ta and 1.2 g kg−1 in Qa. The buoy evaluation indicates that OAFlux represents an improvement over MIMR and GSSTF3. The global EOF-based intercomparison analysis indicates that OAFlux has a similar spatial-temporal variability pattern with that of three atmospheric reanalyses including MERRA, NCEP-1, and ERA-Interim, but that it differs from GSSTF3 and the Climate Forecast System Reanalysis (CFSR). [ABSTRACT FROM AUTHOR]

Two submerged autonomous launch platforms (SALPs) were deployed at 500-m depth on a deep-water mooring in the northeastern Labrador Sea from 2007 to 2009 to automatically release profiling floats into passing warm-core anticyclonic Irminger Rings (IRs). The objective was to investigate the rings' vertical structure and evolution as they drifted from their formation site near the western coast of Greenland to the area of deep convection in the south-central part of the basin. Mechanically and electronically, the SALP worked well: 10 out of 11 floats were successfully released from the mooring over 2 years. However, getting floats trapped in eddy cores using a preprogrammed release algorithm based on temperature and pressure (a proxy for current speed) measured by the SALPs met with limited success mainly because 1) the floats settled at a park pressure that was initially too deep, below the volume of water trapped in the eddy core; 2) the eddies translated past the mooring much more quickly than anticipated; and 3) there is a seasonal cycle in both background and eddy core temperature that was not known a priori and therefore not accounted for in the release algorithm. The other mooring instruments (100-3000 m) revealed that 12 anticyclones passed by the mooring in the 2-yr monitoring period. Using this independent information, the authors assessed and improved the release algorithm, still based on ocean conditions measured at one depth, and found that much better performance could have been achieved with an algorithm that allowed for faster eddy translation rates and the seasonal temperature cycle. [ABSTRACT FROM AUTHOR]

A network of ship-mounted real-time Automatic Weather Stations integrated with Indian geosynchronous satellites [ Indian National Satellites ( INSATs)] 3A and 3C, named Indian National Centre for Ocean Information Services Real-Time Automatic Weather Stations (I-RAWS), is established. The purpose of I-RAWS is to measure the surface meteorological-ocean parameters and transmit the data in real time in order to validate and refine the forcing parameters (obtained from different meteorological agencies) of the Indian Ocean Forecasting System (INDOFOS). Preliminary validation and intercomparison of analyzed products obtained from the National Centre for Medium Range Weather Forecasting and the European Centre for Medium-Range Weather Forecasts using the data collected from I-RAWS were carried out. This I-RAWS was mounted on board oceanographic research vessel Sagar Nidhi during a cruise across three oceanic regimes, namely, the tropical Indian Ocean, the extratropical Indian Ocean, and the Southern Ocean. The results obtained from such a validation and intercomparison, and its implications with special reference to the usage of atmospheric model data for forcing ocean model, are discussed in detail. It is noticed that the performance of analysis products from both atmospheric models is similar and good; however, European Centre for Medium-Range Weather Forecasts air temperature over the extratropical Indian Ocean and wind speed in the Southern Ocean are marginally better. [ABSTRACT FROM AUTHOR]

A new technique to estimate three major biases of XBT probes (improper fall rate, start-up transient, and pure temperature error) has been developed. Different from the well-known and standard ''temperature error free'' differential method, the new method analyses temperature profiles instead of vertical gradient temperature profiles. Consequently, it seems to be more noise resistant because it uses the integral property over the entire vertical profile instead of gradients. Its validity and robustness have been checked in two ways. In the first case, the new integral technique and the standard differential method have been applied to a set of simulated XBT profiles having a known fall-rate equation to which various combinations of pure temperature errors, random errors, and spikes have been added for the sake of this simulation. Results indicated that the single pure temperature error has little impact on the fall-rate coefficients for both methods, whereas with the added random error and spikes the simulation leads to better results with the new integral technique than with the standard differential method. In the second case, two sets of profiles from actual XBT versus CTD comparisons, collected near Barbados in 1990 and in the western Mediterranean (2003--04 and 2008--09), have been used. The individual fall-rate coefficients and start-up transient for each XBT profile, along with the overall pure temperature correction, have been calculated for the XBT profiles. To standardize procedures and to improve the terms of comparison, the individual start-up transient estimated by the integral method was also assigned and included in calculations with the differential method. The new integral method significantly reduces both the temperature difference between XBT and CTD profiles and the standard deviation. Finally, the validity of the mean fall-rate coefficients and the mean start-up transient, respectively, for DB and T7 probes as precalculated equations was verified. In this case, the temperature difference is reduced to less than 0.1°°C for both datasets, and it randomly distributes around the null value. In addition, the standard deviation on depth values is largely reduced, and the maximum depth error computed with the datasets near Barbados is within 1.1%% of its real value. Results also indicate that the integral method has a good performance mainly when applied to profiles in regions with either a very large temperature gradient, at the thermocline or a very small one, toward the bottom. [ABSTRACT FROM AUTHOR]

A new instrument designed to measure precipitation, the ''hotplate precipitation gauge,'' is described. The instrument consists of a heated thin disk that provides a reliable, low-maintenance method to measure precipitation rate every minute without the use of a wind shield. The disk consists of two heated, thermally isolated identical aluminum plates--one facing upward and the other downward. The two plates are heated independently, and both are maintained at constant temperature above 75°°C by electronic circuitry that heats the plates depending on the deviation from the set temperature. Precipitation rate is estimated by calculating the power required to either melt or evaporate snow or to evaporate rain on the upward-facing plate, compensated for wind effects by subtracting out the power on the lower, downward-facing plate. Data from the World Meteorological Organization reference standard for liquid-equivalent snowfall rate measurements, the Double Fence Intercomparison Reference (DFIR) shield system, were used as the truth to develop the hotplate algorithm. The hotplate measures the liquid-equivalent precipitation rate from 0.25 to 35 mm h−−1 within the National Weather Service standard for solid precipitation measurement. The hotplate was also shown to measure wind speed during severe icing conditions and during vibration. The high update rate (precipitation rate, wind speed, and temperature every 1 min), make this an ideal gauge for real-time applications, such as aircraft deicing and road weather conditions. It serves as an accumulation gauge by integrating the 1-min rates over time. It can also be used as a rain gauge for rainfall rates up to 35 mm h−−1. [ABSTRACT FROM AUTHOR]

The present study applies the range imaging (RIM) technique to radio acoustic sounding system (RASS) measurements in an attempt to improve the vertical resolution of temperature profiles obtained by RASS measurements. When an FM-chirped acoustic wave is used for RASS observations, the transmitted radio wave is backscattered from the section of the FM-chirped acoustic pulse where the Bragg condition between the radar and acoustic wavelengths is satisfied. The Bragg resonance region propagates upward with the upward movement of the acoustic pulse. To improve the height resolution of the RIM results, complex time series are extracted for an adequate period corresponding to the effective scattering length of the RASS echo. In the RIM analysis for RASS echo, a model temperature profile is required to compensate the Doppler shift bias due to the shape of range-gate weighting. To remove this bias, an iteration algorithm was developed so that the temperature profiles of the previous RIM results could be used for the bias correction of the next RIM step. The RIM technique was applied to RASS imaging measurements performed using the middle and upper atmosphere (MU) radar on 29--31 October 2006 in an attempt to improve the height resolution to approximately 60 m from the nominal range gate width of 150 m. The temperature profiles inside the radar range volume with a temporal resolution of 26 min were successfully retrieved. The detailed temperature structure, which cannot be revealed by conventional RASS observations, was clarified in the RIM results. In particular, the small-scale inversion layers inside the radar range gate were clearly revealed by the MU radar--RASS imaging data. These detailed temperature variations within the radar range gate agreed well with the simultaneous rawinsonde results. [ABSTRACT FROM AUTHOR]

Warm target effect and diurnal drift errors are the main sources of uncertainties in the trend determination from the NOAA Microwave Sounding Unit (MSU) observations. Currently, there are two methods to correct the warm target effect: 1) finding a best root-level (level-1c) calibration nonlinearity using simultaneous nadir overpass (SNO) matchups to minimize this effect for each scene radiance, and 2) finding a best-fit empirical relationship between the correction term of the end-level gridded brightness temperature and warm target temperature and then removing the best fit from the unadjusted time series. The former corrects the warm target effect before the diurnal drift adjustment and provides more accurate, warm target effect--minimized, level-1c scene radiances for reanalysis applications. The latter corrects the warm target effect at the end-level merging step, which depend on the diurnal drift correction that occurred at a previous step. Although minimized, the first method still leaves small residual warm target--related errors due to imperfect calibrations. This study demonstrates that when the diurnal drift effect is negligible, a combination of the two methods completely removes warm target effect and produces an invariant trend that is independent of the level-1c calibration in the SNO framework. The conclusion is directly applicable to the MSU channel-2 oceanic midtropospheric temperature ( T2) and global channel-3 upper-tropospheric temperature ( T3) and channel-4 lower-stratospheric temperature ( T4), which satisfy the condition of negligible diurnal drift effect. On the basis of these results, version 1.2 of the National Environmental Satellite, Data, and Information Service (NESDIS)--Center for Satellite Applications and Research (STAR) multisatellite MSU time series was constructed, including all T2, T3, and T4 products. In addition, a diurnal drift correction based on the Remote Sensing Systems diurnal anomalies was applied to the T2 product, which produces consistent climate trends between land and ocean. The global long-term climate trends for T2 and T4 derived from the STAR V1.2 dataset are, respectively, 0.18 ±± 0.05 and −−0.39 ±± 0.36 K decade−−1 during 1979--2006; the T3 trend is 0.11 ±± 0.08 K decade−−1 for 1981--2006. [ABSTRACT FROM AUTHOR]

The Thorpe analysis is a recognized method used to identify and characterize turbulent regions within stably stratified fluids. By comparing an observed profile of potential temperature or potential density to a reference profile obtained by sorting the data, overturns resulting in statically unstable regions, mainly because of turbulent patches and Kelvin–Helmholtz billows, can be identified. However, measurement noise may induce artificial inversions of potential temperature or density, which can be very difficult to distinguish from real (physical) overturns. A method for selecting real overturns is proposed. The method is based on the data range statistics; the range is defined as the difference between the maximum and the minimum of the values in a sample. A statistical hypothesis test on the range is derived and evaluated through Monte Carlo simulations. Basically, the test relies on a comparison of the range of a data sample with the range of a normally distributed population of the same size as the data sample. The power of the test, that is, the probability of detecting the existing overturns, is found to be an increasing function of both trend-to-noise ratio (tnr) and overturns size. A threshold for the detectable size of the overturns as a function of tnr is derived. For very low tnr data, the test is shown to be unreliable whatever the size of the overturns. In such a case, a procedure aimed to increase the tnr, mainly based on subsampling, is described. The selection procedure is applied to atmospheric data collected during a balloon flight with low and high vertical resolutions. The fraction of the vertical profile selected as being unstable (turbulent) is 47% (27%) from the high (low) resolution dataset. Furthermore, relatively small tnr measurements are found to give rise to a poor estimation of the vertical extent of the overturns. [ABSTRACT FROM AUTHOR]

Measurements made by microwave sounding instruments provide a multidecadal record of atmospheric temperature change. Measurements began in late 1978 with the launch of the first Microwave Sounding Unit (MSU) and continue to the present. In 1998, the first of the follow-on series of instruments—the Advanced Microwave Sounding Units (AMSUs)—was launched. To continue the atmospheric temperature record past 2004, when measurements from the last MSU instrument degraded in quality, AMSU and MSU measurements must be intercalibrated and combined to extend the atmospheric temperature data records. Calibration methods are described for three MSU–AMSU channels that measure the temperature of thick layers of the atmosphere centered in the middle troposphere, near the tropopause, and in the lower stratosphere. Some features of the resulting datasets are briefly summarized. [ABSTRACT FROM AUTHOR]

The absolute accuracy of the thermal infrared (IR) radiances and brightness temperatures derived from the Advanced Very High Resolution Radiometer (AVHRR) is still unknown, with major sources of error not yet fully understood. This is despite the fact that data from the AVHRR IR channels are widely used in deriving important atmospheric and surface parameters as well as in weather prediction, climate modeling, and other environmental studies. Central to the problem are possible errors introduced by the calibration test procedures and methodologies that can range up to approximately 0.5 K, much larger than the instrument electronic and detector noise characteristics. Further, there are known issues with the current calibration including a large mismatch of up to 0.7 K between the measured physical temperature of the internal calibration target (ICT) and its radiometric temperature estimated by using the AVHRR-observed counts. In an effort to improve this, a new approach to the calibration has been adopted that is dependent on physical instrument parameters. It is shown that this new calibration method can explain the ICT temperature mismatch as a combination of an incorrect assumption that the AVHRR was kept at a constant temperature during testing combined with the effect of scattered radiation from the test chamber and other sources. This new calibration also reduces the total biases and errors that exist when using the current operational calibration on the prelaunch data. Comparing the external calibration target temperatures to the temperatures derived using the AVHRR measurements, this new calibration can reduce an up to 0.7-K bias seen currently to an essentially zero bias with a scatter of less than 0.05 K in the SST regime. This marks an improvement of up to an order of magnitude in accuracy over the current operational calibration. [ABSTRACT FROM AUTHOR]

The authors present a new algorithm to retrieve aerosol optical depth (AOD) over a desert using the window channels centered at 8.7, 10.8, and 12.0 μm of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation satellite. The presence of dust aerosols impacts the longwave outgoing radiation, allowing the aerosols over the desert surfaces to be detected in the thermal infrared (IR) wavelengths. To retrieve the aerosol properties over land, the surface contribution to the satellite radiance measured at the top of the atmosphere has to be taken into account. The surface radiation depends on the surface temperature, which is characterized by a strong diurnal variation over the desert, and the surface emissivity, which is assumed to be constant over a time span of 24 h. The surface emissivity is based on clear-sky observations that are corrected for atmospheric absorption and emission. The clear-sky image is a composite of pixels that is characterized by the highest brightness temperature (BT) of the SEVIRI channel at 10.8 μm, and by a negative BT difference between the channels at 8.7 and 10.8 μm. Because of the lower temperatures of clouds and aerosols compared to clear-sky conditions, the authors assume that the selected pixel values are obtained for a clear-sky day. A forward model is used to simulate the thermal IR radiation transfer in the dust layer. The apparent surface radiation for the three window channels in the presence of aerosols is calculated as a function of the surface emissivity and the surface temperature, the aerosol layer temperature, and the AOD for different aerosol loadings. From these simulations two emissivity ratios, which are stored in lookup tables (LUT), are calculated. The retrieval algorithm consists of processing the clear-sky image and computing the surface emissivity, processing the instantaneous image, and computing the apparent surface radiation for the three window channels. The two emissivity ratios are computed using the radiances at 8.7 and 10.8 μm and at 8.7 and 12.0 μm, respectively. The SEVIRI AOD is obtained by the inversion of these emissivity ratios using the corresponding LUT. The algorithm is applied to a minor dust event over the Sahara between 19 and 22 June 2007. For the validation the SEVIRI AOD is compared with the AOD from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) along the satellite track. [ABSTRACT FROM AUTHOR]

In this study, a penalized maximal F test (PMFT) is proposed for detecting undocumented mean shifts that are not accompanied by any sudden change in the linear trend of time series. PMFT aims to even out the uneven distribution of false alarm rate and detection power of the corresponding unpenalized maximal F test that is based on a common-trend two-phase regression model (TPR3). The performance of PMFT is compared with that of TPR3 using Monte Carlo simulations and real climate data series. It is shown that, due to the effect of unequal sample sizes, the false alarm rate of TPR3 has a W-shaped distribution, with much higher than specified values for points near the ends of the series and lower values for points between either of the ends and the middle of the series. Consequently, for a mean shift of certain magnitude, TPR3 would detect it with a lower-than-specified level of confidence and hence more easily when it occurs near the ends of the series than somewhere between either of the ends and the middle of the series; it would mistakenly declare many more changepoints near the ends of a homogeneous series. These undesirable features of TPR3 are diminished in PMFT by using an empirical penalty function to take into account the relative position of each point being tested. As a result, PMFT has a notably higher power of detection; its false alarm rate and effective level of confidence are very close to the nominal level, basically evenly distributed across all possible candidate changepoints. The improvement in hit rate can be more than 10% for detecting small shifts (Δ ≤ σ, where σ is the noise standard deviation). [ABSTRACT FROM AUTHOR]

TempVal is a spatial component of data quality assurance algorithms applied by the National Climatic Data Center (NCDC), and it has been used operationally for about 4 yr. A spatial regression test (SRT) approach was developed at the regional climate centers for climate data quality assurance and was found to be superior to currently used quality control (QC) procedures for the daily maximum and minimum air temperature. The performance of the spatial quality assessment procedures has been evaluated by assessing the rate with which seeded errors are identified. A complete dataset with seeded errors for the year 2003 for the contiguous United States was examined for both the maximum and minimum air temperature. The spatial regression quality assessment component (SRT), originating in the Automated Climate Information System (ACIS), and TempVal, originating in the NCDC database, were applied separately and evaluated through the ratio of identified seeded errors to the total number of seeds. The spatial regression test applied in the ACIS system was found to perform better in identifying the seeded errors. For all months, the relative frequency of correct identification of wrong data is 0.72 and 0.83 for TempVal and SRT, respectively. The goal of the comparison was to evaluate quality assurance techniques that could improve data quality assessment at the NCDC, and the results of the comparison led to the recommendation that the SRT be included in the NCDC quality assessment methodology. [ABSTRACT FROM AUTHOR]

Various interests desire information and data on heavy snowfalls to define their spatial and temporal occurrences. Historical data at the nation’s 208 first-order stations for events with 15.2 cm or more snowfall in 2 days or less was assessed, and revealed various serious data problems at 118 stations with climatological quality data available for 90 stations. The data problems are described as guidelines for those seeking to utilize heavy snowfall data, and stations with quality data are listed. [ABSTRACT FROM AUTHOR]

During the spring seasons of 2003 and 2004, an infrared thermal camera was deployed in and around supercell thunderstorms in an attempt to retrieve the temperature at the cloud base of a mesocyclone prior to tornadogenesis. The motivation for this exercise was to obtain temperature information that might indicate the thermal structure, timing, and extent of the rear-flank downdraft (RFD) and possibly elucidate its relationship to tornadogenesis. An atmospheric transmissivity study was conducted to account for the effects of atmospheric transmission on the measured temperatures, and to determine an ideal range of distances from which infrared images of a wall cloud or a tornado could be safely captured while still retrieving accurate cloud temperatures. This range was found to be 1.5–3 km. Two case days are highlighted in which the infrared camera was deployed within 1.5–3 km of a tornado; the visible and infrared images are shown side by side for comparison. On the single occasion on which the tornadogenesis phase was captured, the infrared images show no strong horizontal temperature gradients. From the infrared images taken of tornadoes, it can be inferred that the infrared signal from the tornado consisted primarily of infrared emissions from lofted dust particles or cloud droplets, and that the infrared signal from the tornado condensation funnel was easily obscured by infrared emissions from lofted dust particles or intervening precipitation curtains. The deployment of the infrared camera near supercell thunderstorms and the analysis of the resulting images proved challenging. It is concluded that the infrared camera is a useful tool for measuring cloud-base temperature gradients provided that distance and viewing angle constraints are met and that the cloud base is unobscured by rain or other intervening infrared emission sources. When these restrictions were met, the infrared camera successfully retrieved horizontal temperature gradients along the cloud base and vertical temperature gradients (close to the moist adiabatic lapse rate) along the tornado funnel. [ABSTRACT FROM AUTHOR]

A modeling approach is proposed to predict the impact of high-altitude clouds on the detection performance of an airborne electro-optical surveillance sensor. The sensor is dedicated to target detection, and it may be disturbed by cloud presence along the line of sight. The targets are supposed to be dim artificial sources in the atmosphere or stars, and the viewing conditions lead to lines of sight close to horizontal paths. The model is suitable to determine sensor performance for various locations in the earth’s atmosphere and for different seasons. It is based on cloud statistics data determined by the inversion of NOAA satellite observations. Computations of clear line-of-sight probabilities are based on geometric and statistical approaches, and the major hypothesis used here is that all clouds can be considered opaque. Seasonal and diurnal/nocturnal cloud cover variations strongly change the probability of a clear line of sight for a fixed viewing geometry, and the maximal range without clouds that can be reached for a fixed viewing angle and a fixed observer altitude has large temporal variations. These results can be used to reduce the sensor’s field of view to a line of sight having a sufficiently high probability of being cloud free. [ABSTRACT FROM AUTHOR]