Microwave Radiometer Profiler Research Articles

Retrieval of atmospheric temperature and humidity profiles over a tropical coastal station from ground-based Microwave Radiometer using deep learning technique

Ground-based multi-frequency microwave radiometer Profiler (Microwave Radiometer Profiler-MRP) provides valuable information on the altitude distribution of atmospheric humidity and temperature in the troposphere (upto ∼10 km) with high temporal resolution (of ∼1 min) under all-weather condition. These information are vital inputs for characterization of the atmospheric boundary layer, convective cloud systems, local weather modification and for studying the atmospheric dynamics. Potential of such radiometers are well established over the mid-latitude region. Thiruvananthapuram, located in the Indian peninsular region, is one of the first stations in the equatorial region where such an instrument made continuously operational for seven years since 2010 at the tropical coastal station. The instrument measures the brightness temperatures (Tb in Kelvin) at Ka- and V-band frequencies with a temporal resolution of ∼1 min. A trained back-propagation neural network technique based on the radiosonde ascends data for more than one decade obtained by India Meteorological station at Thiruvananthapuram, was used to derive the atmospheric humidity and temperature profiles. This paper presents the implementation of another retrieval technique based on deep learning approach - batch normalization and neural network (BNN) to retrieve temperature and water vapour density (WVD) profiles from Tb values during clear sky conditions and validation of the retrieval accuracies. This inversion model, much faster in computation, consists of two hidden layers and the rectified linear unit (ReLU) is used as the activation function as it can overcome the problems of saturation and vanishing gradients. The Tbs observed by radiometer are corrected by reducing the bias between the simulated Tb, using forward radiative transfer model, and the observed Tb. The validation of retrieved profiles with the radiosonde demonstrates a good retrieval capability, showing a root-mean-square error of 1.8K for temperature, <2 g/m3 for WVD and ∼14% for RH.

Characteristics of a pre-monsoon dryline atmospheric boundary layer over the rain shadow region: A case study

A dryline is the zone of distinct moisture gradient separating warm, moist, and hot, dry air masses. It is usually associated with mesoscale phenomena and plays a significant role in atmospheric boundary layer (ABL) dynamics including initiation of convection/thunderstorms. In the tropical Indian region, these dryline conditions are normally associated with the pre-monsoon season. In the present study, dryline characteristics over a rain shadow region in the Indian subcontinent were investigated utilizing observations and Weather Research and Forecasting (WRF) model from 28 to 30 May 2019. Based upon Wind Profiler Radar and MicroWave Radiometer Profiler measurements, the ABL characteristics were investigated. Interestingly, the ABL height was found to evolve up to 5 km with the horizontal wind vectors oscillating between north-westerly and north-easterly flow. During the intense ABL deepening, stronger downdraft cores were observed in comparison with the updraft cores. The stronger downdrafts entrained free-tropospheric dry air thereby further deepening the ABL. Based upon the entrainment velocity estimates at the ABL top and the variations in potential temperature, the dynamic entrainment fluxes were estimated and further implemented for evaluating two slab models to recreate the ABL growth. With this analysis, we demonstrate the significant contribution of entrainment fluxes on ABL growth during dryline conditions.

The Impact of Nonzenith Elevation Angles on Ground-Based Infrared Thermodynamic Retrievals

Abstract Observing thermodynamic profiles within the planetary boundary layer is essential to understanding and predicting atmospheric phenomena because of the significant exchange of sensible and latent heat between the land and atmosphere within that layer. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based infrared spectrometer used to obtain the vertical profiles of temperature and water vapor mixing ratio. Most AERIs are only capable of zenith views, although the Marine AERI (M-AERI) has a design that allows it to view various elevation angles. In this study, we quantify the improvement in the information content and accuracy of the retrieved profiles when nonzenith angles are included, as is common with microwave radiometer profilers. The impacts of the additional scan angles are quantified through both a synthetic study and with M-AERI observations from the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) campaign. The simulation study shows that low elevation angles contain more information content for temperature whereas high elevation angles have more information content for water vapor. Outside of very humid environments, the addition of low elevation angles also results in lower root-mean-square errors when compared with high angles for both temperature and water vapor mixing ratio, although this is primarily a result of averaging multiple observations together to reduce instrument noise. Real-world results from the ACAPEX dataset indicate similar results as were found for the simulation study, although not all predicted benefits are realized because of the small sample size and observational uncertainties.

A Retrospective Satellite Analysis of the June 2012 North American Derecho

The North American Derecho of 29–30 June 2012 exhibits many classic progressive and serial derecho features. It remains one of the highest-impact derecho-producing convective systems (DCS) over CONUS since 2000. This research effort enhances the understanding of the science of operational forecasting of severe windstorms through examples of employing new satellite and ground-based microwave and vertical wind profile data. During the track of the derecho from the upper Midwestern U.S. through the Mid-Atlantic region on 29 June 2012, clear signatures associated with a severe MCS were apparent in polar-orbiting satellite imagery, especially from the EPS METOP-A Microwave Humidity Sounder (MHS), Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager Sounder (SSMIS), and NASA TERRA Moderate Resolution Imaging Spectroradiometer (MODIS). In addition, morning (descending node) and the evening (ascending node) METOP-A Infrared Atmospheric Sounding Interferometer (IASI) soundings are compared to soundings from surface-based Radiometrics Corporation MP-3000 series microwave radiometer profilers (MWRPs) along the track of the derecho system. The co-located IASI and MWRP soundings revealed a pre-convective environment that indicated a favorable volatile tropospheric profile for severe downburst wind generation. An important outcome of this study will be to formulate a functional relationship between satellite-derived parameters and signatures, and severe convective wind occurrence. Furthermore, a comprehensive approach to observational data analysis involves both surface- and satellite-based instrumentation. Because this approach utilizes operational products available to weather service forecasters, it can feasibly be used for monitoring and forecasting local-scale downburst occurrence within derecho systems, as well as larger-scale convective wind intensity associated with the entire DCS.

Radiative Transfer Model Simulations for Ground-Based Microwave Radiometers in North China

Ground-based microwave radiometer profilers (MWRPs) are widely used to provide high-temporal resolution atmospheric temperature and humidity profiles. The quality of the observed brightness temperature (TB) from MWRPs is key for retrieving accurate atmospheric profiles. In this study, TB simulations derived from a radiative transfer model (RTM) were used to assess the quality of TB observations. Two types of atmospheric profile data (conventional radiosonde and ERA5 reanalysis) were combined with the RTM to obtain TB simulations, then compared with corresponding observations from three MWRPs located in different places in North China to investigate the influence of input atmospheric profiles on TB simulations and evaluate the quality of TB observations from the three MWRPs. The comparisons of the matching samples under clear-sky conditions showed that TB simulations derived from both radiosonde and ERA5 profiles were very close to the TB observations from most of the MWRP channels; however, the correlation was lower and the bias was obvious at 51.26 GHz and 52.28 GHz, which indicates that the oxygen absorption component in the RTM needs to be improved for lower-frequency temperature channels. The difference in location of the radiosonde and MWRP sites affected the TB simulations for the water vapor channels, but had little impact on temperature channels that are insensitive to humidity. Comparisons of both simulations (ERA5 and Radiosonde) and the corresponding TB observations from the three sites indicated that the water vapor channels observation quality for the MWRP located in southern Beijing needs improvement. For the two types of profile data, ERA5 profiles have a more positive effect on TB simulations in the water vapor channels, such as enhanced consistence, reduced bias and standard deviation between simulations and observations for those MWRPs located away from the radiosonde station. Therefore, hourly ERA5 data are an optimal option in terms of compensating for limited radiosonde measurements and enhancing the monitoring quality of MWRP observations within 24 h.

The Performance of Commonly Used Surface-Based Instruments for Measuring Visibility, Cloud Ceiling, and Humidity at Cold Lake, Alberta

Data from automated meteorological instruments are used for model validation and aviation applications, but their measurement accuracy has not being adequately tested. In this study, a number of ground-based in-situ, remote-sensing instruments that measure visibility (VIS), cloud base height (CBH), and relative humidity (RH) were tested against data obtained using standard reference instruments and human observations at Cold Lake Airport, Alberta, Canada. The instruments included the Vaisala FS11P and PWD22 (FSPW), a profiling microwave radiometer (MWR), the Jenoptik ceilometer, Rotronic, Vaisala WXT520, AES-Dewcell RH, and temperature sensors. The results showed that the VIS measured using the FSPWs were well correlated with a correlation coefficient (R) of 0.84 under precipitation conditions and 0.96 during non-precipitating conditions (NPC), indicating very good agreement. However, the FS11P on average measured higher VIS, particularly under NPC. When the FSPWs were compared against human observation, a significant quantization in the data was observed, but less was noted during daytime compared to nighttime. Both probes measured higher VIS compared to human observation, and the calculated R was close to 0.6 for both probes. When the FSPWs were compared against human observation for VIS &lt; 4 km, the calculated mean difference (MD) for the PWD22 (MD ≈ 0.98 km) was better than the FS11P (MD ≈ 1.37 km); thus, the PWD22 was slightly closer to human observation than the FS11P. No significant difference was found between daytime and nighttime measured VIS as compared to human observation; the instruments measured slightly higher VIS. Two extinction parameterizations as functions of snowfall rate were developed based on the VFPs measurements, and the results were similar. The Jenoptik ceilometer generally measured lower CBH than human observation, but the MWR measured larger CBHs for values &lt;2 km, while CBHs were underestimated for higher CBHs.

Factors Governing Cloud Growth and Entrainment Rates in Shallow Cumulus and Cumulus Congestus During GoAmazon2014/5

AbstractShallow cumulus and cumulus congestus clouds play an important role in the large‐scale tropical circulation by mixing heat and moisture vertically and preconditioning the environment for deeper convection. Different representations of these shallow clouds account for much of the spread in General Circulation Model (GCMs) climate sensitivity, potentially because of how entrainment is represented in GCM parameterizations. This study uses observations from the Department of Energy's Atmospheric Radiation Measurement (ARM) mobile facility deployed at Manacapuru, Brazil, during the Green Ocean Amazon (GoAmazon2014/5) Campaign. Environmental thermodynamic profiles and observations of cloud top height (CTH) are used to constrain an entraining plume model to estimate bulk entrainment rates (ERs). Estimates of CTH are obtained from a combination of vertically pointing W‐band ARM cloud radar and 1,290 MHz Radar Wind Profiler observations. A combination of radiosonde, microwave radiometer profiler, and microwave radiometer observations provides new best estimates of the environmental thermodynamic state. We quantify uncertainty in ERs considering uncertainties in estimated CTH, environmental thermodynamic properties, and assumed initial parcel characteristics. We find ERs ranging from 0.16 to 2.8 km−1 with an average of 0.58 ± 0.10 km−1 over a selected population of 469 shallow cumulus and cumulus congestus clouds. Using the retrieved estimates of ER, we evaluate several entrainment closures that are currently used in atmospheric models or have been proposed based on theory or large eddy simulation. Entrainment rates in cumulus clouds are weakly correlated with low‐level buoyancy, cloud depth, and cloud size.

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

The objective of this work is to evaluate GOES-R (Geostationary Operational Environmental Satellites-R series) data-based fog conditions which occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. The C-FOG campaign was designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve predictability. The project took place along coastlines and open water environments of eastern Canada (Nova Scotia, and the Island of Newfoundland) during August−October of 2018 where environmental conditions play an important role for late season fog formation. During the C-FOG field campaign, coastal instruments were mainly located at the Ferryland supersite, Newfoundland, with two main sites, and five satellite sites, as well as on the Research Vessel Hugh R. Sharp. Key in-situ measurement instruments included microphysical, meteorological, radiation, and aerosol sensors. A fog spectral probe was used for measuring droplet spectra from 1–50 µm at the Ferryland supersite. A laser precipitation monitor with 100 µm to 10 mm size range and an optical particle counter with 0.3–17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms, e.g. profiling microwave radiometer, ceilometer, microwave rain radar, lidar, meteorological towers, tethered balloons, and GOES-R products for fog coverage, and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and the profiling microwave radiometer are comparable to ground-based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short-term local fog predictions.

Improving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profiling

Abstract. Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate atmospheric attenuation at relative transparent channels for radio propagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at channels other than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing 1 year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K- and V–W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at the V band (54–58 GHz). The retrieval coefficients are then applied to a 1-year dataset of real V-band observations, and the estimated TMR at the K and V–W band is compared with estimates from nearly colocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32 %–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10 %–20 % for K-band channels and ∼30 % for V–W-band channels.

High-accuracy short-term precipitable water-vapour operational forecast at the Very Large Telescope and perspectives for sky background forecast

ABSTRACT In this article, we present the first results ever obtained by applying the autoregressive (AR) technique to precipitable water vapour (PWV). The study is performed at the Very Large Telescope (VLT). The AR technique was proposed recently to provide forecasts of atmospheric and astroclimatic parameters on short time-scales (up to a few hours) by achieving much better performance with respect to the ‘standard forecasts’ provided in early afternoon for the coming night. The AR method uses real-time measurements of the parameter of interest to improve the forecasts performed with atmospherical models. Here, we used measurements provided by the Low Humidity And Temperature PROfiling microwave radiometer (LHATPRO), a radiometer measuring the PWV at the VLT continuously. When comparing the AR forecast at 1h with the standard forecast, we observe a gain factor of ∼8 (i.e. ∼800 per cent) in terms of forecast accuracy. In the PWV ≤ 1 mm range, which is extremely critical for infrared astronomical applications, the RMSE of the predictions is of the order of just a few hundredth of millimetres (0.04 mm). We therefore proved that the AR technique provides an important benefit to VLT science operations for all instruments sensitive to PWV. Also, we show how such an ability to predict PWV can also be useful to predict the sky background in the infrared range [extremely appealing for Mid-infrared ELT Imager and Spectrograph (METIS)]. We quantify such an ability by applying this method to the New Earth in the Alpha Cen region (NEAR) project supported by the European Southern Observatory (ESO) and Breakthrough Initiatives.

Effect of Clouds on the Diurnal Evolution of the Atmospheric Boundary-Layer Height Over a Tropical Coastal Station

The growth of the daytime convective atmospheric boundary layer, which plays a pivotal role in the vertical mixing and dispersal of water vapour and pollutants, is modulated by cloud radiative effects. Assessment of this cloud effect is sparse in any geographical region and non-existent over tropical coastal regions. We investigate the effect of clouds on the diurnal evolution of boundary-layer height over tropical coastal location Thumba (8.5°N, 77°E) during onshore and offshore flow using multi-year (2010–2016) microwave radiometer profiler observations. The boundary-layer height during both cloudy and clear-sky periods increases rapidly from 0800 LT (local time = UTC + 5.1 h) to attain a daytime peak around noon (400–1500 m). The seasonal mean noontime boundary layer height during cloudy periods is lower than that during clear-sky periods by > 900 m (> 400 m) when offshore (onshore) flow prevails during winter and pre-monsoon seasons. The forenoon growth rate of the boundary-layer height during clear-sky offshore flow is rapid (> 380 m h−1) compared to that during cloudy offshore (160 m h−1), clear-sky onshore (160–250 m h−1), and cloudy onshore (> 100 m h−1) flow. Effects of shortwave cloud radiative forcing and soil temperature on the noontime boundary-layer height and their interdependencies are presented. These observations reveal the contrasting and significant effect of clouds on the growth of the daytime boundary layer during onshore and offshore flow, and the coupled effects of cloud radiative forcing and soil temperature on boundary-layer height over tropical coastal regions, which provide essential constraints for evaluating model simulations.

Identification and Characterization of Persistent Cold Pool Events from Temperature and Wind Profilers in the Columbia River Basin

AbstractCold pool events occur when deep layers of stable, cold air remain trapped in a valley or basin for multiple days, without mixing out from daytime heating. With large impacts on air quality, freezing events, and especially on wind energy production, they are often poorly forecast by modern mesoscale numerical weather prediction (NWP) models. Understanding the characteristics of cold pools is, therefore, important to provide more accurate forecasts. This study analyzes cold pool characteristics with data collected during the Second Wind Forecast Improvement Project (WFIP2), which took place in the Columbia River basin and Gorge of Oregon and Washington from fall 2015 until spring 2017. A subset of the instrumentation included three microwave radiometer profilers, six radar wind profilers with radio acoustic sounding systems, and seven sodars, which together provided seven sites with collocated vertical profiles of temperature, humidity, wind speed, and wind direction. Using these collocated observations, we developed a set of criteria to determine if a cold pool was present based on stability, wind speed, direction, and temporal continuity, and then developed an automated algorithm based on these criteria to identify all cold pool events over the 18 months of the field project. Characteristics of these events are described, including statistics of the wind speed distributions and profiles, stability conditions, cold pool depths, and descent rates of the cold pool top. The goal of this study is a better understanding of these characteristics and their processes to ultimately lead to improved physical parameterizations in NWP models, and consequently improve forecasts of cold pool events in the study region as well at other locations that experiences similar events.

Case Study of a Convective Cluster Over the Rain Shadow Region of Western Ghats Using Multi-platform Observations and WRF Model

Unique observational features of a convective cluster, occurred on 12-Sept-2015, over the rain shadow region in the leeward side of Western Ghats have been presented in this study. The synoptic environment had preconditioned the formation of a convergence zone over the study area. Moisture transport from the Arabian Sea was responsible for the moistening in the lower layers. Boundary layer convective thermals contributed to middle level moistening and subsequent onset of the cloud cluster was accompanied by a sudden surge of moist and warm air into the middle troposphere, and subsequent lifting of freezing level (FL) and wet bulb temperature zero (WBT0) levels. Sudden changes in the FL and WBT0 levels in association with the gust front prior to the initiation of the cloud system has been documented with high-resolution measurements using microwave radiometer and wind profiler. Thermodynamical parameters from radiometer illustrate the percussive conditions for formation of the cloud system. The cloud cluster had resulted in 25.50 mm rainfall, attributing to ~ 91% of convective rain. Intense fall velocity (10–12 ms−1) was noted up to ~ 7 km during the convective rain and the fall velocity was reduced to ~ 7 ms−1 (below the melting layer) during the stratiform counterpart. The cloud system was forecasted using WRF model (version 3.6.1), which was reproduced reasonably well as in the observations and the model output has been analyzed to understand the morphology of the system. The features such as formation of a cold pool, initiation of convective rainfall from the system were well forecasted by the model. Microphysical characteristics of the cloud cluster have also been examined. Riming was the dominant microphysical process within the convective regime. A major contribution to precipitation was from melting of ice hydrometeors especially graupel and snow was noted. Deep warm layer and associated production of supercooled liquid by the lifting of liquid water above the freezing level in updrafts exceeding 15 ms−1 was important for the production of a mixed-phase cloud system. Vapor deposition and aggregation process was noted in the stratiform/anvil counterpart, which also contained mixed phase hydrometeors, primarily of snow.

Analysing the characteristic features of a pre-monsoon thunderstorm event over Pune, India, using ground-based observations and WRF model

In the present work, the characteristic features and factors contributed to the formation of a typical pre-monsoon thunderstorm that occurred over Pune has been studied using various ground-based observations, such as microwave radiometer profiler, wind lidar and surface eddy covariance flux measurements along with weather research and forecast (WRF) model. Initially, the thermodynamic state of atmosphere, variation in fluxes, as well as convective updrafts and downdrafts associated with the thunderstorm event, has been studied using ground-based observations. Thermodynamic indices derived from ground-based microwave radiometer observations showed significant variation before, during and after the development of thunderstorm such as smaller humidity index and higher values of total total index and K-index during the storm. Convective available potential energy (CAPE) and equivalent potential temperature have also shown an increase prior to the event. It is noted that sensible heat flux is higher than latent heat flux before the initiation of storm, however, the latent heat flux increased significantly during the storm. Wind lidar-derived vertical velocities showed strong variation i.e., exceeding \(3 \,\hbox {m} \,\hbox {s}^{-1}\) during the event. Signatures of veering effect indicated the transport of moisture to higher levels was noticed from the altitude variability of wind vector. Ground observations suggested strong crosswind wind shear, convergence of moisture that originated at elevated levels in the boundary layer and enhancement of moist static energy in the elevated layer above the surface was pre-storm characteristics that conducive for the storm enhancement. Secondly, the capabilities of a WRF model in simulating the storm development, structure and evolution have been verified. The WRF model was able to recreate major features of the environment in which the storm was developed. The model output was compared with ground observations, which showed that the model has well captured the sensible heat and friction velocity as that of observation compared to mixing ratio and latent heat. It is observed that the water vapour variation in the model is having a lag, about an hour, with that of observations. The detailed analysis of model output did not show triggering of a thunderstorm as noted in the observation at the same location, which may be probably due to model bias in the moisture transport or moisture convergence was weaker in the model.

Retrieval of Atmospheric Profiles in the New York State Mesonet Using One‐Dimensional Variational Algorithm

AbstractA one‐dimensional variational (1DVAR) algorithm was developed, which combines measurements taken by the ground‐based microwave radiometer profiler (MWRP) with the Rapid Refresh (RAP) model to retrieve a more accurate temperature and humidity profiles under clear sky. The passive and active microwave‐vector radiative transfer model was used to simulate brightness temperatures and calculate weighting functions for 22 channels of the MWRP. As MWRP measurements are mainly weighted in the lower atmosphere, a measurement adjustment is performed to reduce the contribution from above 10 km. The results of the 1DVAR algorithm have been compared with the MWRP built‐in neural network (NN) retrievals and radiosonde observations, which show that the 1DVAR method outperforms the NN retrieval both in temperature and water vapor. Our statistical study further shows that the water vapor profiles from RAP are biased higher than the radiosonde observations, while the 1DVAR‐retrieved humidity values show significant improvements throughout the entire 10‐km range. The improvements in temperature profiles occur mainly within the lowest 4‐km atmosphere, while upper level retrievals are mostly influenced by initial values. This is consistent with the characteristics of the Jacobian matrix and the background error covariance matrix. The outcomes of 44 clear‐sky cases show that the maximum mean retrieval error of the 1DVAR algorithm is less than 0.2 K for temperature below 4 km and less than 0.15 g/m3 in water vapor density. These results are shown to be significantly better than the NN retrieval (3.0 K and 1.25 g/m3) and also superior to the RAP reanalysis (0.3 K and 0.5 g/m3).

Diurnal and seasonal variations in surface methane at a tropical coastal station: Role of mesoscale meteorology

In view of the large uncertainties in the methane (CH4) emission estimates and the large spatial gaps in its measurements, studies on near-surface CH4 on regional basis become highly relevant. This paper presents the first time observational results of a study on the impacts of mesoscale meteorology on the temporal variations of near-surface CH4 at a tropical coastal station, in India. It is based on the in-situ measurements conducted during January 2014 to August 2016, using an on-line CH4 analyzer working on the principle of gas chromatography. The diurnal variation shows a daytime low (1898–1925ppbv) and nighttime high (1936–2022ppbv) extending till early morning hours. These changes are closely associated with the mesoscale circulations, namely Sea Breeze (SB) and Land Breeze (LB), as obtained through the meteorological observations, WRF simulations of the circulations and the diurnal variation of boundary layer height as observed by the Microwave Radiometer Profiler. The diurnal enhancement always coincides with the onset of LB. Several cases of different onset timings of LB were examined and results presented. The CH4 mixing ratio also exhibits significant seasonal patterns being maximum in winter and minimum in pre-monsoon/monsoon with significant inter-annual variations, which is also reflected in diurnal patterns, and are associated with changing synoptic meteorology. This paper also presents an analysis of in-situ measured near-surface CH4, column averaged and upper tropospheric CH4 retrieved by Atmospheric Infrared Sounder (AIRS) onboard Earth Observing System (EOS)/Aqua which gives insight into the vertical distribution of the CH4 over the location. An attempt is also made to estimate the instantaneous radiative forcing for the measured CH4 mixing ratio.

Water vapour retrieval using the Precision Solar Spectroradiometer

Abstract. The Precision Solar Spectroradiometer (PSR) is a new spectroradiometer developed at Physikalisch-Meteorologisches Observatorium Davos – World Radiation Center (PMOD–WRC), Davos, measuring direct solar irradiance at the surface, in the 300–1020 nm spectral range and at high temporal resolution. The purpose of this work is to investigate the instrument's potential to retrieve integrated water vapour (IWV) using its spectral measurements. Two different approaches were developed in order to retrieve IWV: the first one uses single-channel and wavelength measurements, following a theoretical water vapour high absorption wavelength, and the second one uses direct sun irradiance integrated at a certain spectral region. IWV results have been validated using a 2-year data set, consisting of an AERONET sun-photometer Cimel CE318, a Global Positioning System (GPS), a microwave radiometer profiler (MWP) and radiosonde retrievals recorded at Meteorological Observatorium Lindenberg, Germany. For the monochromatic approach, better agreement with retrievals from other methods and instruments was achieved using the 946 nm channel, while for the spectral approach the 934–948 nm window was used. Compared to other instruments' retrievals, the monochromatic approach leads to mean relative differences up to 3.3 % with the coefficient of determination (R2) being in the region of 0.87–0.95, while for the spectral approach mean relative differences up to 0.7 % were recorded with R2 in the region of 0.96–0.98. Uncertainties related to IWV retrieval methods were investigated and found to be less than 0.28 cm for both methods. Absolute IWV deviations of differences between PSR and other instruments were determined the range of 0.08–0.30 cm and only in extreme cases would reach up to 15 %.

Data integration from intensive observation period in 2016 to detect extreme weather in the vicinity of Jakarta region

Meteorological hazard has been frequently occurred in Indonesia due to torrential rains. It is important to examine the characteristics of the atmosphere during rainy seasons for hazard mitigation. National Laboratory of Weather Modification Technology has conducted a short Intensive Observation Program (IOP) from January 18th to February 16th, 2016 to collect meteorological data in the vicinity of Jakarta Region. During that period several instruments have been used, such as Radar, Microwave Profiling Radiometer, Automatic Weather Station, and Radiosonde. This paper examines the comparison of atmospheric parameters obtained from Radiosonde and Profiling Radiometer during extreme weather days. The results showed that there were significant differences of instability indices of Radiosonde and Profiling Radiometer data: 15 points for KI, 6 points for TT and 100 points for SWEAT. The atmospheric stability indices of the Profiling Radiometer tended to be lower than Radiosonde. A radar image showing a rainstorm as well as rain rate information validates atmospheric index stability data. Radar and atmospheric instability indices data integration can be used as one of the parameters to forecast extreme weather events and as an early warning system of hazard mitigation.

Atmospheric Boundary Layer Characterization Using Multiyear Ground-Based Microwave Radiometric Observations Over a Tropical Coastal Station

The continuous ground-based microwave radiometer profiler (MRP) observations of lower atmospheric temperature and humidity profiles are used to investigate the diurnal evolution of atmospheric boundary layer height (BLH) over a tropical coastal station. The BLH estimated from the MRP observations is compared with concurrent and collocated measurements of mixing layer height using a Micropulse Lidar and the BLH derived from radiosonde ascends. The monthly mean diurnal variation of the BLH derived from the multiyear (2010–2013) MRP observations exhibits strong diurnal variation with the highest around the local afternoon (~12:00–15:00 IST) and the lowest during the nighttime (~100–200 m). The daytime convective BLH is maximum during the premonsoon season (March–May) with the peak value (~1300 m) occurring in April and minimum in the month of July (~600 m). This paper presents the potential of MRP observations to investigate the continuous diurnal evolution of the BLH over a tropical coastal region manifested by a thermal internal boundary layer (TIBL) at much better time resolution, which is essential for understanding the rapid growth of the boundary layer and the TIBL during the forenoon period.

Validation of a Water Vapor Micropulse Differential Absorption Lidar (DIAL)

AbstractA water vapor micropulse differential absorption lidar (DIAL) instrument was developed collaboratively by the National Center for Atmospheric Research (NCAR) and Montana State University (MSU). This innovative, eye-safe, low-power, diode-laser-based system has demonstrated the ability to obtain unattended continuous observations in both day and night. Data comparisons with well-established water vapor observing systems, including radiosondes, Atmospheric Emitted Radiance Interferometers (AERIs), microwave radiometer profilers (MWRPs), and ground-based global positioning system (GPS) receivers, show excellent agreement. The Pearson’s correlation coefficient for the DIAL and radiosondes is consistently greater than 0.6 from 300 m up to 4.5 km AGL at night and up to 3.5 km AGL during the day. The Pearson’s correlation coefficient for the DIAL and AERI is greater than 0.6 from 300 m up to 2.25 km at night and from 300 m up to 2.0 km during the day. Further comparison with the continuously operating GPS instrumentation illustrates consistent temporal trends when integrating the DIAL measurements up to 6 km AGL.