The Global Precipitation Measurement (GPM) core observatory satellite launched in 2014 features more extended latitudinal coverage (65°S-65°N) than its predecessor Tropical Rainfall Measuring Mission (TRMM, 35°S-35°N). The Ku-band radar onboard the GPM is known to be capable of characterizing the 3D structure of deep convection globally. In this study, the GPM's capability for detecting mesoscale convective systems (MCSs) is evaluated. Extreme convective echoes seen by GPM are compared against an MCS database that tracks convective entities over the contiguous US. The tracking is based on a geostationary satellite and ground-based Next Generation Radar (NEXRAD) network data obtained during the 2014-2016 warm seasons. Results indicate that more than 70 % of the GPM-detected deep–wide convective core (DWC) and wide convective core (WCC) objects are part of NEXRAD identified MCSs, indicating that GPM-classified DWCs and WCCs correlate well with typical MCSs containing large convective features. By applying this method to the rest of the world, a global view of MCS distribution is obtained. This work reveals GPM's potential in MCS detection at the global scale, particularly over remote regions without a dense observation network.
Summer heat waves are a significant public health threat in China. This paper took Wuhan (one of the four hottest furnace cities in China) as an example to explore several strategies for mitigating the surface urban heat island (UHI), measured by the land surface temperature, including green roofs, cool roofs, bright pavements, and altered urban building patterns. The offline urbanized High-Resolution Land Data Assimilation System (u-HRLDAS) was used to conduct 1-km resolution numerical simulations, which also accounts for the effects of Wuhan's abundant lakes on UHI evolution, with a dynamic lake model. The diurnal cycle and spatial distribution of simulated UHI were analyzed under different mitigation strategies. Results show that considering lake effects reduces daytime (nighttime) UHI intensity by about 1.0 K (0.5 K). Green roofs and cool roofs are more effective in mitigating daytime UHI than bright pavements. The maximum UHI reduction is about 2.1 K at 13:00 local time by replacing 80 % of conventional roofs with green roofs. The UHI mitigation efficiency increases with larger fractions of green roofs, and increased albedo of roofs and roads. In contrast to green roofs, cool roofs and bright pavements are ineffective during nighttime, changing the urban building pattern to mitigate UHI is effective throughout the day. “Height-driven building structure changing” (raising the building height while changing the fraction of impervious surface in each grid to keep the total building volume intact) can reduce surface UHI intensity by 0.4-0.9 K, and “density-driven building structure changing” (distributing building density uniformly and modifying the building height to make the total building volume unchanged) reduces UHI by 1.2-2.6 K. These results showed new insights in mitigating UHIs for mega cities, like Wuhan, and provides a practical guideline for policymakers to offer more habitable cities.
Since January 2016, RIKEN has run an extrapolation-based nowcasting system of global precipitation in real time. Although our previous paper reported the effectiveness of using data assimilation in a limited verification period, the long-term stability of the forecast accuracy through different seasons has not been investigated. In addition, the algorithm was updated seven times between January 2016 and March 2018. Therefore, this paper aims to examine how motion vectors can be derived more accurately, and how data assimilation can stably constrain an advection-diffusion model for extrapolation for the long-term operation. The Japan Aerospace Exploration Agency's Global Satellite Mapping of Precipitation (GSMaP) near-real-time product is the only input to the nowcasting system. The motion vectors of precipitation areas are computed by a cross-correlation method, and the Local Ensemble Transform Kalman Filter is used to generate a smooth, complete set of motion vectors. Precipitation areas are extrapolated in time up to 12 hours ahead, and the product, called GSMaP RIKEN Nowcast, is disseminated on a webpage in real time. Most of the algorithmic updates involved improving the estimation of the motion vectors, and the forecast accuracy was gradually and consistently improved by these updates. In particular, the threat scores increased the most at approximately 40°S and 40°N. A performance decrease in the northern hemisphere winter was also reduced by reducing noise in advection. The time series of the ensemble spread demonstrated that an increase in the number of available motion vectors by a system update led to a decrease in the ensemble spread, and vice versa.
The charge structure evolution of a mesoscale convective system with an anomalous or inverted charge structure, observed in the Severe Thunderstorm Electrification and Precipitation Study, a field project on the Colorado–Kansas border in summer 2000, is simulated using the Weather Research and Forecasting (WRF) model coupled with electrification and discharge processes. Two noninductive electrification schemes are used, based on the liquid water content (LWC) and the graupel rime accretion rate (RAR). The simulation with the LWC-based electrification scheme cannot reproduce the inverted charge structure with a positive charge region sandwiched by two negative charge layers, while the RAR-based electrification scheme produces the evolution process of a normal–inverted–normal charge structure in the convective region, which is consistent with the observations. In the low RAR (< 2 g m−2 s−1) region, graupel is mainly negatively charged when it bounces off ice crystals, while the ice crystals take up positive charge. However, in the zone where the inverted charge structure forms, a strong updraft (> 16 m s−1), high LWC (> 2 g m−3), and high RAR (> 4.5 g m−2 s−1) region appears above the height of the −20°C layer, so that a positive graupel charging region is generated above the −20°C layer of the convective region, resulting in a negative dipole charge structure with negatively charged ice crystals above the positively charged graupel. The negative dipole is superposed on the positive dipole (positive above negative) charge structure at the lower position to form an inverted tripole charge structure.
The Tibetan Plateau (TP) and the atmospheric conditions over it strongly affect downstream regional weather. Advanced Microwave Sounding Unit-A (AMSU-A) brightness temperature observations provide temperature sounding information and have long been successfully assimilated for numerical weather prediction. AMSU-A brightness temperatures observed from the polar-orbiting NOAA-15 and 18 satellites during July and August 2016 were collected. During these months, the equator crossing time of these particular satellites was approximately 0600 local time. Observations collected within the 3-h periods centered at 0000 UTC and 1200 UTC, covering the TP, were assimilated. The weighting coefficients for mid-tropospheric AMSU-A channels 6 and 7 were significantly reduced over areas with terrain heights greater than 2 km and 4 km, respectively, in the National Centers for Environmental Prediction Gridpoint Statistical Interpolation system. The assimilation of AMSU-A observations was improved to better exploit the role of AMSU-A channels 6 and 7 over the TP. This was achieved by not decreasing the weighting coefficients of the two channels over the grassy surface of the TP's high terrain such that they were consistent with the inverse error variances. This modification produced larger positive impacts of satellite data assimilation on the 48-h forecasts of the mid-tropospheric trough, water vapor, and quantitative precipitation forecasts downstream of the TP. This study also suggests the importance of AMSU-A observations from early-morning satellite orbits for numerical weather prediction downstream of the TP.
In this study, the climatological characteristics of object-based precipitation systems (OPSs) and moisture development are analyzed over the South China Sea (SCS) during the sharp transition of the summer monsoon onset. The satellite-observed statistics of the OPSs showed that over the 20-day pre-onset period, OPSs of small (< 100 km) to medium size (100-300 km) are active over the lands surrounding the SCS. The pre-onset composite mean shows a basin-scale (∼ 1000 km) local circulation with anomalous subsidence over the ocean, and ocean convection is mostly suppressed. Over the 20-day post-onset period, large (> 300 km) OPSs develop over the coastal ocean and contribute to over 60 % of the total precipitation. The number of large OPSs observed significantly increases along with the sharp moisture buildup within 10 days after the onset. The moisture budget suggests that the local contribution from convective vertical mixing is the major moisture source during the first pentad after the onset. The relationship between moisture buildup and convection organization is then examined using a set of idealized cloud-resolving model (CRM) experiments, with a land–ocean configuration approximating the SCS basin. The CRM appropriately represents the observed development of coastal convection. In the no-shear environment, a strong basin-scale circulation is formed, which suppresses the ocean moisture development. When large-scale vertical wind shear is imposed to represent the changes of large-scale circulation during the onset pentad, organized convection systems are increased over the coastal ocean and propagate toward the open ocean, accompanied by fast ocean moistening within 5-10 days.
This paper proposes a new verification metric, the Pattern Similarity Index (PSI), that can simultaneously evaluate location errors and shapes of rainfall areas. Pixel-by-pixel verification methods such as the threat score and root mean squared error involve difficulties in evaluating location errors and shapes of rainfall areas and in addition small rainfall areas. To address these difficulties, various object-based methods have been developed. However, object-based methods tend to be complicated and computationally expensive. Therefore, PSI adopts a simpler, computationally more efficient algorithm, as follows: Firstly, bounding rectangles of individual rainfall areas are computed, and neighboring rectangles are combined so that they are treated as a single precipitation system to mimic how human recognizes. Next, shape parameters are computed for each integrated bounding rectangle. For each pair of the observed and forecasted rainfall areas, the location error weighted by the differences of the shape parameters is used as the verification score. If no observed rainfall area with a similar size exists near a forecasted rainfall area, this location-error-based score of the forecasted area is set to a large value. The integration method of the bounding rectangle and the precipitation threshold are the only tunable parameters in this method, and we repeat computing the verification score by varying these parameters. The best value is used as the final verification score.
Idealized cases showed the ability of PSI to evaluate location errors and differences in the shape parameters. A real case with global precipitation nowcasting showed that the proposed evaluation value increased almost linearly with the forecast time, whereas the threat score and root mean squared error tended to saturate as the forecast time increased, showing a potential advantage of PSI. Comparison of PSI with another object-based method revealed its advantage in its computational efficiency, while providing similar verification scores.
A multi-scale data assimilation method for the ensemble Kalman filter (EnKF) is proposed for atmospheric models in cases with insufficient observations of fast variables. This method is based on the conservation and invertibility of potential vorticity (PV). The dynamical state variables in the free atmosphere of forecast ensemble members are decomposed into balanced and unbalanced parts by applying PV inversion to the PV anomalies computed from spatially smoothed state variables. The mass variables of the two parts are adjusted to remove additional sampling errors introduced by the decomposition. The forecast error covariances between those parts are ignored in the Kalman gain to suppress spurious error correlations. This approximation makes it possible to apply different covariance localizations to each part. The Kalman gain thus obtained is used to assimilate observations.
The performance of the proposed method is demonstrated with a shallow water model through twin experiments in a perfect model scenario. The results using the same localization radius for the two parts reveal that the proposed EnKF is superior in the accuracy of the analysis to a conventional EnKF unless the ensemble size is sufficiently large. It is found that the adjustment of mass variables is necessary to outperform the conventional EnKF. The benefits of the PV inversion using the Bolin–Charney balance over the quasi-geostrophic inversion are marginal in the experiments.
Accurate aerosol optical thickness is indispensable for estimating the radiative forcing of aerosols in the atmosphere. Sun photometry is one of the most popular methods, which is simple and easy to use, but it should be noted that some errors due to forward scattering effect can be introduced in the observation of direct normal irradiance. Consequently, the estimated optical thickness of aerosols can be underestimated even if the calibration constant is correct. This possibility depends on an optical geometry of the measuring instrument as well as aerosol characteristics. This report assesses these effects by assuming several aerosol types and instrumental parameters quantitatively.
Forward scattering ratio γλ.fwd, which is defined as a ratio of the forward scattering part to the true direct normal irradiance (Iλ), by Iλ.obs = Iλ(1 + γλ.fwd), is approximately proportional to the product of the optical thickness (τλ.aer) and the single scattering albedo (ωλ) of aerosols and the relative air mass (m), γλ.fwd ≈ ελωλτλaerm. The coefficient ελ is a proportional constant which is dependent on the opening angle of the instrument as well as the optical characteristics of aerosols. The variation of ελ is tabulated for several aerosol types and opening angles. Then, the error of the estimate of τλaer can be approximately expressed by Δτλ ≈ −ελωλτλaer.
During the recent catastrophic heavy rainfall event in western Japan in July 2018, both the Hiroshima and Keihanshin areas were subjected to unusual total rainfall amounts in 72 hours from 1200 UTC 4 July to 1200 UTC 7 July. However, the number of sediment disasters was significantly larger in the Hiroshima area. We explore possible reasons for this difference in the sediment disaster occurrences between the Hiroshima and Keihanshin areas, focusing on the different rainfall characteristics in these two areas during the heavy rainfall event. Based on the radar observations, we investigate the characteristics of precipitation systems striking the Hiroshima and Keihanshin areas and find that significantly large precipitation systems, with areas equal to or larger than 104 km2, dominated the Hiroshima area, causing rapid accumulation of the rainfall amount and enhancing the risk of deadly sediment disasters in this area. On the other hand, in the Keihanshin area, moderately intense rainfall and relatively small precipitation systems were dominant. We suggest that the difference in the amount of damage between the Hiroshima and Keihanshin areas was mainly caused by the differently-sized precipitation systems striking these two areas. Statistics relating to the background atmospheric conditions for the precipitation systems in the heavy rainfall event reveal that a high vertical wind shear environment provides preferable conditions for the formation of large precipitation systems.