Recent increases in computational resources have led to the application of kilometre- and sub-kilometre-scale simulations in research, numerical weather prediction, and climate modelling alike. Despite anticipated improvements with resolution, there is still considerable work needed to evaluate how well such models improve the representation of intense convection. In this study we conduct ensemble simulations with kilometre- and sub-kilometre-scale horizontal grids to investigate intense convective events in the tropical island thunderstorm system Hector, which frequently occurs over the Tiwi Islands in North Australia. To avoid losing information through spatio-temporal averaging we apply a tracking algorithm to simulated and observed storms. When compared with observations, the model storms exhibit a lack of propagation across the study domain. In general, simulated storms are too intense but too small and too short-lived. This is especially true for the sub-kilometre simulations, where storms are more intense, smaller, and more numerous than in the kilometre-scale counterparts. We argue that size and duration errors compensate for storm number and intensity errors, which could lead to misleading interpretations when only comparing time and space averages of rainfall fields. Investigating some properties of the simulated storms suggests that storms with high rainfall intensities have stronger updrafts in the sub-kilometre model and are accompanied by an increase in cold pool intensity. The results and their resolution sensitivities highlight that the remaining parametrisations and their many tuning parameters in high-resolution set-ups influence the representation of convective storms in such models.
Abstract. The validation of convective processes in global climate models (GCMs) could benefit from the use of large datasets that provide long-term climatologies of the spatial statistics of convection. To that regard, echo top heights (ETHs), convective areas, and frequencies of mesoscale convective systems (MCSs) from 17 years of data from a C-band polarization (CPOL) radar are analyzed in varying phases of the Madden–Julian Oscillation (MJO) and northern Australian monsoon in order to provide ample validation statistics for GCM validation. The ETHs calculated using velocity texture and reflectivity provide similar results, showing that the ETHs are insensitive to various techniques that can be used. Retrieved ETHs are correlated with those from cloud top heights retrieved by Multifunctional Transport Satellites (MTSATs), showing that the ETHs capture the relative variability in cloud top heights over seasonal scales. Bimodal distributions of ETH, likely attributable to the cumulus congestus clouds and mature stages of convection, are more commonly observed when the active phase of the MJO is over Australia due to greater mid-level moisture during the active phase of the MJO. The presence of a convectively stable layer at around 5 km altitude over Darwin inhibiting convection past this level can explain the position of the modes at around 2–4 km and 7–9 km. Larger cells were observed during break conditions compared to monsoon conditions, but only during the inactive phase of the MJO. The spatial distributions show that Hector, a deep convective system that occurs almost daily during the wet season over the Tiwi Islands, and sea-breeze convergence lines are likely more common in break conditions. Oceanic MCSs are more common during the night over Darwin. Convective areas were generally smaller and MCSs more frequent during active monsoon conditions. In general, the MJO is a greater control on the ETHs in the deep convective mode observed over Darwin, with higher distributions of ETH when the MJO is active over Darwin.
Abstract We present an integrated framework that leverages multiple weather radar calibration and monitoring techniques to provide real-time diagnostics on reflectivity calibration, antenna pointing, and dual-polarization moments. This framework uses a volume-matching technique to track the absolute calibration of radar reflectivity with respect to the Global Precipitation Measurement (GPM) spaceborne radar, the relative calibration adjustment (RCA) technique to track relative changes in the radar calibration constant, the solar calibration technique to track daily change in solar power and antenna pointing error, and techniques that track properties of light-rain medium to monitor the differential reflectivity and dual-polarization moments. This framework allows for an evaluation of various calibration and monitoring techniques. For example, we found that a change in the RCA is highly correlated to a change in absolute calibration, with respect to GPM, if a change in antenna pointing can first be ruled out. It is currently monitoring 67+ radars from the Australian radar network. Because of the diverse and evolving nature of the Australian radar network, flexibility and modularity are at the core of the calibration framework. The framework can tailor its diagnostics to the specific characteristics of a radar (band, beamwidth, etc.). Because of its modularity, it can be expanded with new techniques to provide additional diagnostics (e.g., monitoring of radar sensitivity). The results are presented in an interactive dashboard at different level of details for a wide and diverse audience (radar engineers, researchers, forecasters, and management), and it is operational at the Australian Bureau of Meteorology. Significance Statement Weather radars, like all instruments, require maintenance and upgrades. Rainfall measurements are highly variable and sensitive to change, and this can lead to inconsistencies within a radar network. Calibration is the process to counteract those inconsistencies. Any calibration requires a fixed standard to which the changed/upgraded radar can be compared. The SCAR calibration framework presented herein makes use of several standards to retrieve a full set of diagnostics about the radar data. We apply these techniques over the entire Australian weather radar network and demonstrate that, by using this integrated approach, absolute calibration can be achieved to within 1 dB Z of reflectivity, antenna pointing can be monitored within 0.1°, and the various measurements of the radars can be quality controlled.
This article deals with the tropospheric water vapour distribution at Niamey (Niger) observed with a high‐temporal‐resolution (14 s) microwave radiometric profiler. Data were collected during the whole year 2006 in the framework of the African Monsoon Multidisciplinary Analysis (AMMA) campain. Two seasonal periods are considered: the dry season, when the northeasterly Harmattan is flowing at low tropospheric level, and the wet season, associated with the southwesterly monsoon circulation. The fine vertical structure of temperature, convective air stability and water vapour for each seasonal period is described in detail and differences are emphasized. Typical temporal series and monthly averaged diurnal cycles are presented. It is shown that a diurnal cycle of water vapour is present throughout the year, including the dry season. The diurnal cycle of water vapour is controlled mainly by the nocturnal low‐level jet (NLLJ). During the dry season, the diurnal cycle of water vapour is organized into two layers: a lower layer (LL) from the surface up to 0.6–1.4 km above ground level (agl) and an upper layer (UL) from 1.4 up to 5–6 km agl. The water vapour distributions in the LL and UL are anticorrelated, with a half‐day temporal shift. As a result, the vertically integrated water vapour (IWV), which displays a quasi‐sinusoidal diurnal cycle when computed separately for the LL and UL, appears almost flat for the total tropospheric height, due to the half‐day period shift. This structure of two layers is not observed during the wet season. Probability density functions (pdfs) of water vapour content are presented. In dry conditions, the pdfs are well fitted by a log‐normal distribution, while the Weibull distribution fits the pdfs for wet conditions better.
The detection of dangerous convective precipitating system is crucial for the civil aviation safety. In this work, we develop applications for the aviation safety by using active (radar) and passive (radiometer) microwave instrumentation in order to detect precipitating systems, notably hail area. We also develop applications for the meteorology, i.e. a climatology of water vapor and the anomalous propagation of the microwave signal that is inducted by water vapor.In the first part, we study the best configuration for civil aviation airborne radars for the observation of precipitating systems, notably the frequency and the beamwidth. We have applied the constrain on the radar antenna of civil aviation that its size and its weight. Then we study the results of the dual-wavelength technic for the detection of hailstorm. This part aims to improve the quality of the observations made by civil aviation airborne radars. In the second part, we study the climatology of the water vapor diurnal cycle, and its seasonnal variations, in West Africa. Water vapor is one of the most important atmospheric gases (greenhouse effect, radiation, hydrological cycle, etc.), it is thus necessary to know in details the water vapor distribution in the troposphere. Based on this water vapor study, we then analyse the impact of the water vapor on the air refractivity and the propagation of microwaves. A climatology of anomalous propagation has been built for the instrumentation that uses microwaves.
Abstract Doppler radars measure Doppler velocity within the [− V N , V N ] range, where V N is the Nyquist velocity. Doppler velocities outside this range are “folded” within this interval. All Doppler “unfolding” techniques use the folded velocities themselves. In this work, we investigate the potential of using velocities derived from optical flow techniques applied to the radar reflectivity field for that purpose. The analysis of wind speed errors using six months of multi-Doppler wind retrievals showed that 99.9% of all points are characterized by errors smaller than 26 m s −1 below 5-km height, corresponding to a failure rate of less than 0.1% if optical flow winds were used to unfold Doppler velocities for V N = 26 m s −1 . These errors largely increase above 5-km height, indicating that vertical continuity tests should be included to reduce failure rates at higher elevations. Following these results, we have developed the Two-step Optical Flow Unfolding (TOFU) technique, with the specific objective to accurately unfold Doppler velocities with V N = 26 m s −1 . The TOFU performance was assessed using challenging case studies, comparisons with an advanced Doppler unfolding technique using higher Nyquist velocities, and 6 months of high V N (47.2 m s −1 ) data artificially folded to 26 m s −1 . TOFU failure rates were found to be very low. Three main situations contributed to these errors: high low-level wind shear, elevated cloud layers associated with high winds, and radar data artifacts. Our recommendation is to use these unfolded winds as the first step of advanced Doppler unfolding techniques. Significance Statement The potential of using optical flow winds operationally to accurately unfold Doppler velocities is demonstrated in this work. The operational significance is that the Nyquist velocity can confidently be reduced to 26 m s −1 , allowing for extended first trip radar maximum range and reduced contamination from dual pulse repetition frequency artifacts.
This archive consists of the post-processed data of C-Band Doppler Radar (CDR) over Jakarta and surrounding regions for the studies of "Variability of Jakarta Rain-Rate Characteristics Associated with the Madden-Julian Oscillation and Topography" and "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar". The dataset is a gridded rainfall data derived from the local relationship of Z (reflectivity) from the CDR and rainfall (R) from stations. The derived rainfall data are in daily estimates from 2009 to 2012 with the format in NetCDF files. The CDR data were obtained from the projects “Hydrometeorological Array for Intraseasonal Variation-Monsoon Automonitoring (HARIMAU)” (JFY 2005-2009), and the Science Technology Research Partnership for Sustainable Development (SATREPS) “Maritime Continent Center of Excellence (MCCOE) (JFY 2009-2013) of the Japan Science and Technology Agency (JST)/Japan International Cooperation Agency(JICA) under a collaboration of the Agency for the Assessment and Application of Technology (BPPT)-Indonesia and Japan Agency for Marine-earth Science and Technology (JAMSTEC)-Japan.
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