Humidity Profiles Research Articles

The Precursors of High Rainfall Intensity During June in Southern Central Java: A Case Study of Flash Floods 18 June 2016 in Purworejo

High rainfall intensity during the dry season can cause floods and landslides that cause a lot of loss of property and life as happened in Purworejo. Generally, the dry season with little rainfall, heavy rain in June is very rare, therefore disaster anticipation will be better if the precursor can be identified. This research aims to obtain high-intensity rain precursors in the south of Central Java, especially Purworejo. Identification used classifying rainfall for 10 years and related to atmospheric phenomena that impact to Indonesian rainfall variability. The results show that if there are very heavy rainfall and evenly distributed, precursors, can be identified in 3 days before the incident such as low OLR which value of <150 Wm-2. Moreover, an analysis of the average 3 days before the incident, the value of the OLR anomaly in the Central Java region is between –20 to –60 Wm-2. Meanwhile, the vertical humidity profile with more than 80% reached the 500 mb level, as well as spots where the temperature was more than 30.20C, three to four days before the incident with a value of more than 30.20C in the Indian Ocean adjacent to the southern part of Java Island. Existing low air pressure in the northern part of Kalimantan and in the southern part of Java, which persists for a long time, can support very heavy rains in June in Purworejo. Especially if the wind speed decreases to less than 4 m/s and occurs in phases 3 and 4 of the MJO.

An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties

Abstract. A new generation of cloud radars, with the ability to make observations close to the surface, presents the possibility of observing fog properties with better insight than was previously possible. The use of these instruments as part of an operational observation network could improve the prediction of fog events, something which is still a problem for even high-resolution numerical weather prediction models. However, the retrieval of liquid water content (LWC) profiles from radar reflectivity alone is an under-determined problem, something which ground-based microwave radiometer observations can help to constrain. In fact, microwave radiometers are not only sensitive to temperature and humidity profiles but are also known to be instruments of reference for the liquid water path. By providing the thermodynamic state of the atmosphere, to which the formation and evolution of fog events are highly sensitive, in addition to accurate liquid water path, which can be used to constrain the LWC retrieval from the cloud radar alone, combining microwave radiometers with cloud radars seems a natural next step to better understand and forecast fog events. To that end, a newly developed one-dimensional variational (1D-Var) algorithm designed for the retrieval of temperature, specific humidity and liquid water content profiles with both cloud radar and microwave radiometer (MWR) observations is presented in this study. The algorithm was developed to evaluate the capability of cloud radar and MWR to provide accurate LWC profiles in addition to temperature and humidity in view of assimilating the retrieved profiles into a 3D- and 4D-Var operational assimilation system. The algorithm is firstly tested on a synthetic dataset, which allows the evaluation of the developed algorithm in idealised conditions. This dataset was constructed by perturbing a high-resolution forecast dataset of fog and low-cloud cases by its expected errors. The algorithm is then tested with real data from the recent field campaign SOFOG-3D, carried out with the use of LWC measurements made from a tethered balloon platform. As expected, results from the synthetic dataset study were found to contain lower errors than those found from the retrievals on the dataset of real observations. It was found that LWC can be retrieved in idealised conditions with an uncertainty of less than 0.04 g m−3. With real data, as expected, retrievals with a good correlation (0.7) to in situ measurements were found but with a higher uncertainty than the synthetic dataset of around 0.06 g m−3 (41 %). This was reduced to 0.05 g m−3 (35 %) when an accurate droplet number concentration could be prescribed to the algorithm. A sensitivity study was conducted to discuss the impact of different settings used in the 1D-Var algorithm and the forward operator. Additionally, retrievals of LWC from a real fog event observed during the SOFOG-3D field campaign were found to significantly improve the operational background profiles of the AROME (Application of Research to Operations at MEsoscale) model, showing encouraging results for future improvement of the AROME model initial state during fog conditions.

Sounding Data from Ground-Based Microwave Radiometers for a Hailstorm Case: Analyzing Spatiotemporal Differences and Initializing an Idealized Model for Prediction

Atmospheric physical sounding data from three ground-based microwave radiometers located in Xi’an were analyzed to explore the temporal and spatial differences of a hailstorm event and were initialized into an idealized Weather Research and Forecasting (WRF) model to predict the total evolution of the event, which occurred on 29 July 2019. Liquid water and relative humidity profiles revealed a consistent sequence of hailstorm intensity among observations from surface meteorological stations and the FY-4A satellite, where the precipitation and cloud top temperature intensified from north to south, corresponding to the locations of the ground-based microwave radiometers in Gaoling, Weiyang, and Chang’an. Compared with those of a similar storm without hail that occurred on 9 August 2018, the humidity profiles and heights at 0 °C and −20 °C exhibited more dramatic changes. The heights at 0 °C and −20 °C obviously increased with a low-value zone in the relative humidity profiles during the strongest stage of the hailstorm in Chang’an and Weiyang. Later, the heights sharply dropped in Chang’an when strong, downward ice-phased hydrometers occurred with hail production in the storm. A time-saving, idealized WRF simulation, initialized with pre-3-h sounding data from ground-based microwave radiometers, was designed to qualitatively predict this hailstorm. The simulations consistently showed a strong-to-weak intensity of storms from Chang’an to Weiyang to Gaoling. Although the first attempt at this model has uncertainties in both the observations and the model, it provides a potential new method for single-point fine hailstorm prediction.

A dataset of temperature, humidity, and liquid water path retrievals from a network of ground-based microwave radiometers dedicated to fog investigation

The database presented in this study has been acquired during the SOuth west FOGs 3D (SOFOG3D) experiment for processes study. This international campaign led by Météo-France during the winter 2019–2020 aimed at deploying a unique network of both in situ and remote sensing measurements in order to document spatial and temporal variabilities of fog events. To support this scientific objective but also to conduct first data assimilation experiments within the French convective scale model AROME, an un-precedented network of 8 ground-based microwave radiometers (MWR) has been deployed in 7 different locations known to be prone to fog occurrences. The database gives access to vertical profiles of temperature and humidity (both absolute and relative) from the surface up to 10 km altitude as well as integrated water vapor and liquid water path estimates. The retrieved profiles offer a very large database that can be exploited for several scientific purposes: fog process studies at specific location, documentation on the variability of fog properties at the regional scale, better understanding of the atmospheric boundary layer (ABL) height and dynamics during wintertime conditions, development of nowcasting products dedicated to fog alerts, data assimilation experiments to improve fog forecasts, development of synergetical advanced products, and evaluation of new model configurations with advanced parameterization or resolutions.

Understanding Changes in the Tropical Circulation under Global Warming Using a Cloud-Resolving Model and a Conceptual Model

Abstract A cloud-resolving model (CRM) is used to investigate how a prototype tropical circulation driven by a sea surface temperature (SST) contrast changes in a warmer climate. The CRM is used to simulate a region of the atmosphere with a positive SST anomaly, and the large-scale circulation in this region is represented using the weak temperature gradient (WTG) and damped gravity wave (DGW) parameterizations, where the large-scale vertical velocity within the domain is related to the deviation of the simulated density profile from a reference profile representative of the tropical mean state. The behavior of the circulation in response to an increase in SST of both the domain and reference state (i.e., uniform warming) is examined. While the vertical velocity shows an increase in its maximum strength with warming, its value in the lower to midtroposphere decreases. Since the water vapor concentration is largest in the lower troposphere, this leads to a dynamic weakening of precipitation under warming. To understand these results, a simple model for the thermodynamic structure of a convecting atmosphere based on a bulk entraining plume is employed. The model uses a fixed entrainment rate and the relative humidity profiles from the CRM to predict the temperature profiles of the domain and reference state. The vertical velocity profiles calculated from these predicted temperature profiles reproduce important aspects of those simulated with the CRM. This simple modeling framework reveals that the effect of entrainment is crucial to understanding the dynamic response of precipitation to warming, providing a stepping stone to understanding the factors driving changes to the tropical precipitation distribution in a future warmer climate.

Passive ground-based remote sensing of radiation fog

Abstract. Accurate boundary layer temperature and humidity profiles are crucial for successful forecasting of fog, and accurate retrievals of liquid water path are important for understanding the climatological significance of fog. Passive ground-based remote sensing systems such as microwave radiometers (MWRs) and infrared spectrometers like the Atmospheric Emitted Radiance Interferometer (AERI), which measures spectrally resolved infrared radiation (3.3 to 19.2 µm), can retrieve both thermodynamic profiles and liquid water path. Both instruments are capable of long-term unattended operation and have the potential to support operational forecasting. Here we compare physical retrievals of boundary layer thermodynamic profiles and liquid water path during 12 cases of thin (LWP<40 g m−2) supercooled radiation fog from an MWR and an AERI collocated in central Greenland. We compare both sets of retrievals to in-situ measurements from radiosondes and surface-based temperature and humidity sensors. The retrievals based on AERI observations accurately capture shallow surface-based temperature inversions (0–10 m a.g.l.) with lapse rates of up to −1.2 ∘C m−1, whereas the strength of the surface-based temperature inversions retrieved from MWR observations alone are uncorrelated with in-situ measurements, highlighting the importance of constraining MWR thermodynamic profile retrievals with accurate surface meteorological data. The retrievals based on AERI observations detect fog onset (defined by a threshold in liquid water path) earlier than those based on MWR observations by 25 to 185 min. We propose that, due to the high sensitivity of the AERI instrument to near-surface temperature and small changes in liquid water path, the AERI (or an equivalent infrared spectrometer) could be a useful instrument for improving fog monitoring and nowcasting, particularly for cases of thin radiation fog under otherwise clear skies, which can have important radiative impacts at the surface.

Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC

The microwave radiometers HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds - Passive) continuously measured radiation emitted from the atmosphere throughout the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition on board the research vessel Polarstern. From the measured brightness temperatures, we have retrieved atmospheric variables using statistical methods in a temporal resolution of 1 s covering October 2019 to October 2020. The integrated water vapour (IWV) is derived individually from both radiometers. In addition, we present the liquid water path (LWP), temperature and absolute humidity profiles from HATPRO. To prove the quality and to estimate uncertainty, the data sets are compared to radiosonde measurements from Polarstern. The comparison shows an extremely good agreement for IWV, with standard deviations of 0.08–0.19 kg m−2 (0.39–1.47 kg m−2) in dry (moist) situations. The derived profiles of temperature and humidity denote uncertainties of 0.7–1.8 K and 0.6–0.45 gm−3 in 0–2 km altitude.

Fire hazard identification on the flight deck of a short-take-off/vertical-landing type aircraft carrier: fire scenarios selection

ABSTRACT The flight deck of aircraft carriers in operation is exposed to fire risks which must be mitigated by fire safety measures such as firefighting and suppression systems. To develop advanced fire safety measures, the quantitative risk assessment and management is essential, where fire hazards must be identified in a probabilistic manner considering operational conditions (e.g. sortie generation rates) and site-specific ocean environmental conditions (e.g. humidity, wave and wind profiles). In this paper, a set of realistic fire scenarios on the flight deck of a hypothetical short take-off/vertical landing (STOVL) type aircraft carrier are selected, which shall be used for the quantitative fire risk assessment and management. Potential fire hazards are formulated as a function of random parameters associated with operational and ocean environmental conditions, and probabilistic sampling technique is used to select hundred fire scenarios. Fire exceedance diagrams are established in association with fire-impacted (leak) area through the selected fire scenarios.

Validation of IMERG Oceanic Precipitation over Kwajalein

The integrated Multi-satellitE Retrievals for GPM (IMERG) Version V05B and V06B precipitation products from the Global Precipitation Measurement (GPM) mission are validated against ground-based observations from the Kwajalein Polarimetric S-band Weather Radar (KPOL) deployed at Kwajalein Atoll in the central Pacific Ocean. Such a validation is particularly important as comprehensive surface measurements over the oceans are practically infeasible, which hampers the identification of possible errors, and improvement of future versions of IMERG and other satellite-based retrieval algorithms. The V05B and V06B IMERG products are validated at their native 0.1°, 30 min resolution from 2014 to 2018 based on both volumetric and categorical metrics. This validation study indicates that precipitation rates from both IMERG V05B and V06B are underestimated with respect to radar surface estimates, but the underestimation is much reduced from V05B to V06B. IMERG V06B outperforms V05B with reduced systematic bias and improved precipitation detectability. The IMERG performance is further traced back to its individual sensors and morphing-based algorithms. The overall underestimation in V05B is mainly driven by the negative relative biases from morphing-based algorithms which are largely corrected in V06B. Imagers perform generally better than sounders because of the usage of low-frequency channels in imagers which can better detect emission signals by the hydrometeors. Among imagers, the GPM Microwave Imager (GMI) and Advanced Microwave Scanning Radiometer Version 2 (AMSR2) are the best, followed by Special Sensor Microwave Imager/Sounder (SSMIS). Among sounders, the Microwave Humidity Sounder (MHS) is the best, followed by Advanced Technology Microwave Sounder (ATMS) and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) for V06B. Among all categories, morph-only and IR + morph only perform better than SAPHIR. SAPHIR shows the worst performance among all categories, likely due to its limited channel selection. It is envisaged that these results will improve our understanding of IMERG performance over oceans and aid in the improvement of future versions of IMERG.

Impact of Madden Julian Oscillation on the diurnal cycle of precipitation over the west coast of India

Madden Julian Oscillation (MJO) is an eastward propagating convective system that passes over the Indian and Pacific Oceans with a periodicity of 30–90 days and influences most of the tropical weather systems. This study investigates and quantifies the impact of MJO on the diurnal cycle of precipitation over the west coast of India. The work uses TRMM precipitation, profiles of wind and humidity from ERA5 re-analysis and satellite Infrared window channel measurements from GridSat-B1 for the period 2000–2019. Real-time Multivariate MJO index has been used for the identification of active and suppressed MJO phases. Harmonic analysis is used to derive the diurnal and semi-diurnal amplitudes of precipitation. The active MJO phases enhance the diurnal amplitude of precipitation over the west coast with respect to the climatological diurnal cycle, whereas the suppressed phases reduce it. Active phases help in the formation of mesoscale convective cloud systems with much more spatial extension and temporal duration than that in suppressed phase. This kind of convective organization is observed especially during the active MJO phases of monsoon and post-monsoon seasons. The vertical structure of wind and humidity in the troposphere are modified by MJO where the active (suppressed) phase enhances (decreases) them. The overall modification of tropospheric dynamics, thermodynamics and deep convection by MJO can cause anomalous rainfall activity over the west coast.

On the Interaction between Moist Convection and Large-Scale Ascent in the Tropics

Abstract A simple steady-state model is constructed for the interaction between moist convection and large-scale ascent in the tropics. The model is based on a bulk-plume representation of convection, and it is coupled to the large-scale circulation using methods developed for limited-area numerical models that are consistent with the weak temperature gradient approximation. Given the midtropospheric temperature anomaly in the ascent region, the model solves for the profiles of temperature, relative humidity, and large-scale vertical velocity in this region, as well as the tropical-mean profiles of temperature and relative humidity, as a function of two parameters representing the importance of entrainment and condensate re-evaporation in moist convection. According to the simple model, the ascent region is characterized by an anomalously moist and stable free troposphere with a top-heavy vertical velocity profile that peaks in the upper troposphere. These results are shown to be consistent with simulations using a cloud system–resolving model in which the large-scale circulation is parameterized. Furthermore, it is shown that, due to the effect of entrainment on the tropospheric lapse rate, the predicted vertical velocity profile is more top-heavy than the first-baroclinic mode profile used in previous reduced-complexity models of tropical dynamics. The simple model therefore provides a framework to link mixing and microphysical processes in moist convection to the large-scale structure of the tropical overturning circulation.

A 25-year climatology of low-tropospheric temperature and humidity inversions for contrasting synoptic regimes at Neumayer Station, Antarctica.

A 25-year set of daily radiosonde data was used to investigate temperature and humidity inversions at Neumayer Station, coastal Dronning Maud Land, Antarctica. For the first time, inversions were studied differentiating between different synoptic conditions and different height levels. It was shown that, generally, inversions occurred on the majority (78%) of the days, with simultaneous occurrence of humidity and temperature inversions being observed on approximately two thirds of all days. Multiple inversions are common in all seasons for cyclonic and noncyclonic conditions, however, typically occur more frequently under cyclonic conditions. The seasonality of inversion occurrence and features, that is, inversion strength, depth and vertical gradients, was analysed statistically. Different formation mechanisms depending on inversion levels and prevailing weather situations are related to typical annual courses of certain inversion features. Winter maxima were found for the features that are mostly connected to the temperature close to the surface, which is mainly a result of the negative energy balance, thus influencing surface-based inversions. At the second level, both temperature and humidity inversions are often caused by advection of comparably warm and moist air masses related to the passage of cyclones and their frontal systems. Hence, maxima in several inversion features are found in spring and fall, when cyclonic activity is strongest. Monthly mean profiles of humidity and temperature inversions reveal that elevated inversions are often obscured in average profiles due to large variations in inversion height and depth.

Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC

Abstract. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed-wing uncrewed aircraft system (UAS). These in situ observations of the central Arctic atmosphere are some of the most extensive to date and provide unique insight into the atmospheric boundary layer (ABL) structure. The ABL is an important component of the Arctic climate, as it can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previously published automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL in the central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are the Liu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficial for upcoming observational and modeling efforts regarding the central Arctic ABL.

Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process

Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM10 is the main pollutant and the ratio of PM2.5/PM10 is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.

CFD simulation of updrafts initiated by a vertically directed jet fed by the heat of water vapor condensation

This paper presents the results of the development of a mathematical model and numerical simulation of the ascent in the atmosphere of a vertically directed jet fed by the heat of condensation of water vapor on a hygroscopic aerosol introduced into the jet at the start. The possibility of creating artificial convective clouds depending on jet parameters, condensation heat value and vertical profiles of wind speed, air temperature and humidity has been evaluated. Numerical experiments showed that the motion of a high-speed and high-temperature jet in the atmosphere has a complex turbulent nature. As the jet ascends, it expands, losing superheat and velocity. The temperature of the jet decreases faster than the velocity, so the jet rises slightly above the level at which its superheat disappears. The jet's ascent height increases as the humidity of the air and the vertical temperature gradient increase. Wind causes the jet to deform, bend, and decrease the height of ascent. Feed the jet with condensation heat results in a significant increase in jet lift height. This is particularly effective in the case of introducing into the jet two-layer NaCl/TiO2 nanoaerosol, which is capable of absorbing water vapor in an amount significantly greater than its mass. The simulation results are encouraging in the possibility of creating artificial updrafts that can lead to the formation of convective clouds and precipitation on days with favorable atmospheric conditions, when wind speed in the sub-cloud layer is < 6 m/s, air humidity is > 65%, and the temperature lapse rate is > 7.5 °C/km.

Water vapor and cloud microphysical characteristics of a sea-effect snowstorm in Shandong Peninsula, China

Sea-effect snowfall is a special form of snow in the coastal areas of the Bohai Sea in China. However, a quantitative understanding of its water vapor and cloud microphysical mechanisms is still lacking. In this study, the Weather Research and Forecasting model version 4.0 with three microphysics schemes was employed to investigate a sea-effect snowstorm that occurred in the north of Shandong Peninsula on 9–10 January 2018. The simulated snowfall amount, temperature and humidity profiles, and radar reflectivity were in general agreement with the observations. The moisture budget revealed that the water vapor came completely from evaporation of the surface of Bohai Sea. The largest water vapor sink term was the moisture advection, followed by the deposition and condensation (accounting for only 15% of the sea surface evaporation). This phenomenon is analogous to heating water in a kettle and then the water vapor drifting away with the wind. In the main snowfall area, the total water vapor transport was positive (i.e., inflow) below the height of 1.5 km, and was almost zero above 3.0 km. The period of maximum moisture inflow in the low layer was about 30 min ahead of the maximum surface snowfall. In addition, the hydrometeor distributions in this sea-effect snowstorm were relatively simple compared to those in non-sea-effect snowstorm; the snow content was the most (0.09 g kg−1), followed by the supercooled cloud water (0.01 g kg−1), owing to the weak convection in it. Snow growth was dominated by the vapor deposition, and the process of rimming accounted for only 1/4 of the vapor deposition. The evidently weaker vapor condensation than vapor deposition is quite different from that in summertime heavy rainfall.

Observing the Microwave Radiation of the Sun during a Solar Eclipse with a Ground-Based Multichannel Microwave Radiometer

A ground-based multichannel microwave radiometer (GMR) is commonly used to observe the atmospheric radiation brightness temperature (TB) in order to retrieve atmospheric temperature and humidity profiles. At present, GMRs are used only in meteorology and climate monitoring. However, theoretical analysis showed that GMRs can be also used to observe the solar radiation. Therefore, we tried to improve the antenna servo control system of a GMR so that it could track and observe the sun, and the results showed that the GMR could respond to the variation of solar radiation. A further question was: can a GMR observe the variation of the sun during a solar eclipse? Fortunately, two solar eclipse events were captured by the GMR on 26 December 2019 and 21 June 2020 in Xi’an, China. We used the upgraded GMR to observe the variation of solar radiation during the two solar eclipses. The observation and analysis results showed that (1) the GMR could accurately track the sun and respond to the variation of solar radiation during the solar eclipse. We analyzed the variation features of the solar radiation by combining the solar phase during the two solar eclipses. (2) We found that the GMR could respond to the variation of the solar radiation arising from the Earth–Sun distance, and we further propose a novel method to measure the eccentricity of earth orbit with the GMR by using the passive solar observation. The results show that the eccentricity measured was 0.0169, which agreed quite well with the value of 0.0167 in the literature. (3) The average variation percentages of both the Earth–Sun distance and the intensity of the incident solar radiation throughout the year were estimated to be 3.44% and 6.6%, respectively. According to these results, the solar observation techniques can broaden the field usage of GMR.

A Comprehensive Clear-Sky Database for the Development of Land Surface Temperature Algorithms

Land surface temperature is linked to a wide range of surface processes. Given the increased development of earth observation systems, a large effort has been put into advancing land surface temperature retrieval algorithms from remote sensors. Due to the very limited number of reliable in situ observations matching the spatial scales of satellite observations, algorithm development relies on synthetic databases, which then constitute a crucial part of algorithm development. Here we provide a database of atmospheric profiles and respective surface conditions that can be used to train and verify algorithms for land surface temperature retrieval, including machine learning techniques. The database was built from ERA5 data resampled through a dissimilarity criterion applied to the temperature and specific humidity profiles. This criterion aims to obtain regular distributions of these variables, ensuring a good representation of all atmospheric conditions. The corresponding vertical profiles of ozone and relevant surface and vertically integrated variables are also included in the dataset. Information on the surface conditions (i.e., temperature and emissivity) was complemented with data from a wide array of satellite products, enabling a more realistic surface representation. The dataset is freely available online at Zenodo.

Relative Merits of Optimal Estimation and Non-Linear Retrievals of Sea-Surface Temperature from MODIS

We compared the results of an Optimal Estimation (OE) based approach for the retrieval of the skin sea surface temperature (SSTskin) with those of the traditional non-linear sea surface temperature (NLSST) algorithm. The retrievals were from radiance measurements in two infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA satellite Aqua. The OE used a reduced state vector of SST and total column water vapor (TCWV). The SST and atmospheric profiles of temperature and humidity from ERA5 provided prior knowledge, and we made reasonable assumptions about the variance of these fields. An atmospheric radiative transfer model was used as the forward model to simulate the MODIS measurements. The performances of the retrieval approaches were assessed by comparison with in situ measurements. We found that the OESST reduces the satellite–in situ bias, but mostly for retrievals with an already small bias between in situ and the prior SST. The OE approach generally fails to improve the SST retrieval when that difference is large. In such cases, the NLSST often provides a better estimate of the SST than the OE. The OESST also underperforms NLSST in areas that include large horizontal SST gradients.

Observations of the lower atmosphere from the 2021 WiscoDISCO campaign

Abstract. The mesoscale meteorology of lake breezes along Lake Michigan impacts local observations of high-ozone events. Previous manned aircraft and UAS observations have demonstrated non-uniform ozone concentrations within and above the marine layer over water and within shoreline environments. During the 2021 Wisconsin's Dynamic Influence of Shoreline Circulations on Ozone (WiscoDISCO-21) campaign, two UAS platforms, a fixed-wing (University of Colorado RAAVEN) and a multirotor (Purdue University DJI M210), were used simultaneously to capture lake breeze during forecasted high-ozone events at Chiwaukee Prairie State Natural Area in southeastern Wisconsin from 21–26 May 2021​​​​​​​. The RAAVEN platform (data DOI: https://doi.org/10.5281/zenodo.5142491, de Boer et al., 2021) measured temperature, humidity, and 3-D winds during 2 h flights following two separate flight patterns up to three times per day at altitudes reaching 500 m above ground level (a.g.l.). The M210 platform (data DOI: https://doi.org/10.5281/zenodo.5160346, Cleary et al., 2021a) measured vertical profiles of temperature, humidity, and ozone during 15 min flights up to six times per day at altitudes reaching 120 ma.g.l. near a Wisconsin DNR ground monitoring station (AIRS ID: 55-059-0019). This campaign was conducted in conjunction with the Enhanced Ozone Monitoring plan from the Wisconsin DNR that included Doppler lidar wind profiler observations at the site (data DOI: https://doi.org/10.5281/zenodo.5213039, Cleary et al., 2021b).