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Acta Meteorologica Sinica
Journal Prestige (SJR): 0.638
Citation Impact (citeScore): 1
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0894-0525
Published by Springer-Verlag Homepage  [2467 journals]
  • Interdecadal Variability of Summer Precipitation in Northwest China and
           Associated Atmospheric Circulation Changes

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      Abstract: Daily precipitation data from 149 rain gauge stations in China and NCEP—NCAR reanalysis data during 1961–2018 are used to investigate the interdecadal variability of summer precipitation in Northwest China and related causes. The results suggest that, on the interdecadal timescale, Northwest China shifts into a rainy period from the year 1987, with an increase in the precipitation amount and intensity; an increase in the probability of moderate rain, heavy rain, torrential rain, and extremely heavy rain; and a decrease in the probability of light rain. More than 60% of the increase in precipitation can be attributed to rainfall with intensity above the grade of heavy rain. The associated inter-decadal variability of atmospheric circulations over midlatitude Eurasia in summer is examined and it is found that the interdecadal variability is mainly characterized by the Silk Road pattern (SRP), with a cyclonic circulation anomaly and an anticyclonic circulation anomaly over central Asia and Mongolia, respectively; enhanced ascending motion and atmospheric instability in Northwest China; and strengthened easterly winds caused by the Mongolian anti-cyclonic anomaly along the northern boundary of the Tibetan Plateau. On the south side of the Mongolian anticyclone, the water vapor transported from the Pacific and Indian Oceans as well as the South China Sea to Northwest China by easterly winds increases significantly, providing the main water vapor source for the increase in precipitation in Northwest China on the interdecadal timescale. The transition of the Atlantic multidecadal oscillation to a positive phase may be the main cause of the interdecadal transition of the SRP to a positive phase, resulting in the inter-decadal increase in summer precipitation in Northwest China.
      PubDate: 2022-12-01
       
  • Impacts of the Urban Spatial Landscape in Beijing on Surface and Canopy
           Urban Heat Islands

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      Abstract: How does the urban spatial landscape (USL) pattern affect the land surface urban heat islands (SUHIs) and canopy urban heat islands (CUHIs)' Based on satellite and meteorological observations, this case study compares the impacts of the USL pattern on SUHI and CUHI in the central urban area (CUA) of Beijing using the satellite land-surface-temperature product and hourly temperature data from automatic meteorological stations from 2009 to 2018. Eleven USL metrics—building height (BH), building density (BD), standard deviation of building height (BSD), floor area ratio (FAR), frontal area index (FAI), roughness length (RL), sky view factor (SVF), urban fractal dimension (FD), vegetation coverage (VC), impervious coverage (IC), and albedo (AB)—with a 500-m spatial resolution in the CUA are extracted for comparative analysis. The results show that SUHI is higher than CUHI at night, and SUHI is only consistent with CUHI at spatial—temporal scales at night, particularly in winter. Spatially, all 11 metrics are strongly correlated with both the SUHI and CUHI at night, with stronger correlation between most metrics and SUHI. VC, AB, and SVF have the greatest impact on both the SUHI and CUHI. High SUHI and CUHI values tend to appear in areas with BD ⩾ 0.26, VC ⩽ 0.09, AB ⩽ 0.09, and SVF ⩽ 0.67. In summer, most metrics have a greater impact on the SUHI than CUHI; the opposite is observed in winter. SUHI variation is affected primarily by VC in summer and by VC and AB in winter, which is different for the CUHI variation. The collective contribution of all 11 metrics to SUHI spatial variation in summer (61.8%) is higher than that to CUHI; however, the opposite holds in winter and for the entire year, where the cumulative contribution of the factors accounts for 66.6% and 49.6%, respectively, of the SUHI variation.
      PubDate: 2022-12-01
       
  • Effect of Using Land Use Data with Building Characteristics on Urban
           Weather Simulations: A High Temperature Event in Shanghai

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      Abstract: Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate. In this study, an extreme heat event in Shanghai, China, was simulated by using a WRF/BEP + BEM (Weather Research and Forecasting/Building Effect Parameterization + Building Energy Model) model. We incorporated local climate zone (LCZ) land use data that resolved urban morphology using 10 classes of building parameters. The simulation was compared to a control case based on MODIS (Moderate-resolution Imaging Spectroradiometer) land use data. The findings are as follows: (1) the LCZ data performed better than the MODIS data for simulating 10-m wind speed. An increase in building height led to the wind speed to decrease by 0.6–1.4 m s−1 in the daytime and by 0.2–0.7 m s−1 at nighttime. (2) High-rise buildings warmed the air by trapping radiation in the urban canyon. This warming effect was partially offset by the cooling effect of building shadows in the day. As a result, the 2-m temperature increased by 0.8°C at night but only by 0.4°C during the day. (3) Heterogeneous urban surfaces increased the 50-m turbulent kinetic energy by 0.4 m2 s−2, decreased the 10-m wind speed by 1.8 m s−1 in the daytime, increased the surface net radiation by 45.1 W m−2, and increased the 2-m temperature by 1.5°C at nighttime. (4) The LCZ data modified the atmospheric circulation between land and ocean. The shadowing effect reduced the air temperature differences between land and ocean and weakened the sea breeze. Moreover, high-rise buildings obstructed sea breezes, restricting their impact to a smaller portion (10 km along the wind direction) of inland areas compared to that with MODIS.
      PubDate: 2022-12-01
       
  • Pre-Processing, Quality Assurance, and Use of Global Atmospheric Motion
           Vector Observations in CRA

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      Abstract: Assimilation of atmospheric motion vectors (AMVs) is important in the initialization of the atmospheric state in numerical weather prediction models, especially over oceans and at high latitudes where conventional data are sparse. This paper presents a detailed description of the pre-processing, quality assurance, and use of global AMVs in China’s first generation of the 40-yr (1979–2018) CRA global atmospheric reanalysis product. A new AMV archive is integrated from near real-time operational Global Telecommunication System data and reprocessed AMV datasets released or produced mainly during 2014–2016 according to a priority principle. To avoid the misuse of data with systematic quality problems, the observations of all 18 types of AMVs from 54 satellites are pre-evaluated over the whole time series. The pre-evaluation system developed by the CRA team is based on the NCEP Gridpoint Statistical Interpolation (GSI) three-dimensional variational assimilation system and the ERA-Interim reanalysis product. The AMVs in the new AMV archive are denser than the AMVs prepared for the Climate Forecast System Reanalysis product, the bias and root-mean-square values are smaller, and the time series are steadier. The new AMV archive is assimilated in the CRA product based on the NCEP GSI assimilation procedure and quality control configuration with reference to the pre-evaluation results. This is the first time that the reprocessed AMVs from Fengyun-2 satellites from June 2005 to July 2017 are assimilated in a reanalysis product. The assimilation features inspire confidence in the accuracy and stability of these data. The mean root-mean-square values of the observation minus analysis infrared, water vapor, and visible AMV were 1.5–3.4, 2.7–3.6, and 1.3–2.1 m s−1, respectively. This experience of integrating, pre-evaluating, and assimilating AMV observations is valuable for the next generation of reanalysis products.
      PubDate: 2022-12-01
       
  • Record Flood-Producing Rainstorms of July 2021 and August 1975 in Henan of
           China: Comparative Synoptic Analysis Using ERA5

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      Abstract: This study compares two rainstorms that swept through Henan Province of China in July 2021 and August 1975. The heavy rainfall and related synoptic systems and processes are diagnosed based on hourly ERA5 reanalysis data and precipitation observations from the China Meteorological Administration. It is estimated that most of the daily rainfall in Henan was caused by synoptic-scale precipitation, with the sub-synoptic convective rainfall intermittently dominating some of the hourly total rainfall. The rainband moved at about 2 m s−1 during the July 2021 rainstorm, whereas it was almost stationary during the August 1975 rainstorm when the heavy rainfall was concentrated in southern Henan. A double-typhoon circulation pattern with a subtropical high over the Bohai and Yellow Seas was observed during both rainstorms. The heavy rainfall during the July 2021 event was controlled remotely by Typhoons Cempaka and In-Fa, which provided a path for the transport of moisture via the southerly jet associated with Typhoon Cempaka and the easterly (or southeasterly) jet associated with Typhoon In-Fa. The rainstorm in August 1975 was caused more directly by Typhoon Nina, which made landfall in Fujian Province and moved toward Henan Province. The rainfall around the inverted trough of the motionless Typhoon Nina produced a cumulative effect. The two rainstorms also differed in their circulation patterns in the upper troposphere. The intrusion of high potential vorticity air over Central China occurred in the July 2021 extreme rainstorm, whereas the South Asian high was enhanced and biased further north during the August 1975 rainstorm. Further analysis showed that the northward and westward transport of moisture took place during the July 2021 rainstorm, whereas the westward transport of moisture from the east of Henan dominated near the inverted trough of Typhoon Nina during the August 1975 rainstorm.
      PubDate: 2022-12-01
       
  • An Objective Method for Defining Meiyu Onset in Lower Reaches of the
           Yangtze River Basin

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      Abstract: Meiyu is an important climate phenomenon in East Asia, and predicting its onset is critical for local community. Traditionally, the onset of Meiyu is determined by regional operational meteorological centers with some arbitrary criteria. In this study, an objective Meiyu onset index (MOI) is constructed based on large-scale atmospheric conditions such as temperature and relative humidity over the lower reaches of the Yangtze River basin (LYRB). This objectively determined MOI is in good agreement with an integrated area-weighted onset index provided by regional climate centers. A composite analysis is further carried out to reveal large-scale circulation characteristics associated with an early and a late onset group. A La Niña like sea surface temperature (SST) condition in the Pacific and enhanced convection in Philippines are favorable precursory conditions for the early onset. Accompanied with the tropical signals are a Pacific—Japan (PJ) pattern in June and an anomalous anticyclone near Taiwan. Southerly anomalies to the west of the anticyclone transports high mean moisture northward, favoring the onset of Meiyu in LYRB. A linear regression model is constructed for the MOI forecast with three independent predictors. With 1981–2010 as a training period, the reconstructed MOI time series is able to capture the early and late onset years quite well. An independent forecast for the period of 2011–2020 shows a reliable skill. The correlation between the objectively determined MOI and the forecasted date is 0.6, exceeding the 95% confidence level. The newly developed MOI and the regression model can be easily implemented to operational centers for real-time application.
      PubDate: 2022-12-01
       
  • A New Hybrid Machine Learning Model for Short-Term Climate Prediction by
           Performing Classification Prediction and Regression Prediction
           Simultaneously

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      Abstract: Machine learning methods are effective tools for improving short-term climate prediction. However, commonly used methods often carry out classification and regression prediction modeling separately and independently. Such a single modeling approach may obtain inconsistent prediction results in classification and regression and thus may not meet the needs of practical applications well. To address this issue, this study proposes a selective Naive Bayes ensemble model (SENB-EM) by introducing causal effect and voting strategy on Naive Bayes. The new model can not only screen effective predictors but also perform classification and regression prediction simultaneously. After being applied to the area prediction of summer western North Pacific subtropical high (WNPSH) from 2008 to 2021, it is found that the accuracy classification score (a metric to assess the overall classification prediction accuracy) and the time correlation coefficient (TCC) of SENB-EM can reach 1.0 and 0.81, respectively. After integrating the results of different models [including multiple linear regression ensemble model (MLR-EM), SENB-EM, and Chinese Multi-model Ensemble Prediction System (CMME) used by National Climate Center (NCC)] for 2017–2021, the TCC of the ensemble results of SENB-EM and CMME can reach 0.92 (the highest result among them). This indicates that the prediction results of the summer WNPSH area provided by SENB-EM have a high reference value for the real-time prediction. It is worth noting that, except for the numerical prediction results, the SENB-EM model can also give the range of numerical prediction intervals and predictions for anomalous degrees of the WNPSH area, thus providing more reference information for meteorological forecasters. Overall, as a new hybrid machine learning model, the SENB-EM has a good prediction ability; the approach of performing classification prediction and regression prediction simultaneously through integration is informative to short-term climate prediction.
      PubDate: 2022-12-01
       
  • Assessment of Urban Climate Environment and Configuration of Ventilation
           Corridor: A Refined Study in Xi’an

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      Abstract: Integrating urban spatial landscape (USL) parameters into refined climate environment assessment is important. By taking the central urban area (CUA) of Xi’an, China as an example, this study develops an evaluation method based on Urban Climatic Map (UCMap) technology. We define surface urban heat island intensity (SUHI) and surface ventilation potential coefficient (VPC), which can effectively reflect local urban climate. Based on SUHI and VPC, we analyze the influences of seven typical USL metrics including building height (BH), building density (BD), floor area ratio (FAR), sky view factor (SVF), frontal area index (FAI), surface roughness length (RL), and vegetation cover (VC). Then, we construct a comprehensive evaluation model and create an urban climate zoning map on a 100-m resolution. The climate optimization on the map is performed for configuration of possible ventilation corridors and identification of associated control indicators. The results show that the main factors affecting SUHI in the CUA of Xi’an are VC and BD, which explain 87.9% of the variation in SUHI, while VPC explains 50% of the variation in SUHI. The main factors affecting VPC are BH, FAR, FAI, and RL, all of which contribute to more than 95% of the variation in VPC. The evaluation model constructed by SUHI, VPC, and VC can divide the CUA into climate resource spaces, climate preservation spaces, climate sensitive spaces, and climate restoration spaces. On this basis, a ventilation corridor network of 3 level-1 corridors (each over 500 m wide), 6 level-2 corridors (each over 500 m wide) and 13 level-3 corridors (each over 50 m wide) is established. Meanwhile, the main quantitative control indicators selected from the USL metrics are proved to be capable of ensuring smooth implementation of the planned corridors at different levels.
      PubDate: 2022-12-01
       
  • Evaluation of the Madden-Julian Oscillation in Fengyun-3B Polar-Orbiting
           Satellite Reprocessed OLR Data

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      Abstract: The present study compares the spatial and temporal characteristics of the Madden-Julian Oscillation (MJO) in Fengyun-3B (FY-3B) polar-orbiting satellite reprocessed outgoing longwave radiation (OLR) data and NOAA OLR data during 2011–2020. The spatial distributions of climatological mean and intraseasonal standard deviation of FY-3B OLR during boreal winter (November–April) and boreal summer (May–October) are highly consistent with those of NOAA OLR. The FY-3B and NOAA OLRs display highly consistent features in the wavenumber-frequency spectra, the occurrence frequency of MJO active days, the eastward propagation of MJO along the equator, and the interannual variability of MJO according to diagnoses using the all-season multivariate EOF analysis. These results indicate that the FY-3B OLR produced by the polar-orbiting satellites is of high quality and worthy of global application.
      PubDate: 2022-12-01
       
  • Surface Weather Parameters Forecasting Using Analog Ensemble Method over
           the Main Airports of Morocco

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      Abstract: Surface weather parameters detain high socioeconomic impact and strategic insights for all users, in all domains (aviation, marine traffic, agriculture, etc.). However, those parameters were mainly predicted by using deterministic numerical weather prediction (NWP) models that include a wealth of uncertainties. The purpose of this study is to contribute in improving low-cost computationally ensemble forecasting of those parameters using analog ensemble method (AnEn) and comparing it to the operational mesoscale deterministic model (AROME) all over the main airports of Morocco using 5-yr period (2016–2020) of hourly datasets. An analog for a given station and forecast lead time is a past prediction, from the same model that has similar values for selected predictors of the current model forecast. Best analogs verifying observations form AnEn ensemble members. To picture seasonal dependency, two configurations were set; a basic configuration where analogs may come from any past date and a restricted configuration where analogs should belong to a day window around the target forecast. Furthermore, a new predictors weighting strategy is developed by using machine learning techniques (linear regression, random forest, and XGBoost). This approach is expected to accomplish both the selection of relevant predictors as well as finding their optimal weights, and hence preserve physical meaning and correlations of the used weather variables. Results analysis shows that the developed AnEn system exhibits a good statistical consistency and it significantly improves the deterministic forecast performance temporally and spatially by up to 50% for Bias (mean error) and 30% for RMSE (root-mean-square error) at most of the airports. This improvement varies as a function of lead times and seasons compared to the AROME model and to the basic AnEn configuration. The results show also that AnEn performance is geographically dependent where a slight worsening is found for some airports.
      PubDate: 2022-12-01
       
  • Intensified Impact of the Equatorial QBO in August–September on the
           Northern Stratospheric Polar Vortex in December–January since the Late
           1990s

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      Abstract: This study reveals an intensified impact of the equatorial quasi-biennial oscillation (QBO) in August–September (QBO_AS) on the northern stratospheric polar vortex (SPV) in December–January (SPV_DJ) since the late 1990s. The unstable relationship may be related to the differences in the deep convection anomaly over the tropical western Pacific and Indian Oceans in October–November (ON) related to the QBO_AS prior to and after the late 1990s. During 1998–2017, the easterly phase of the QBO_AS is accompanied by a colder tropical tropopause in ON, which enhances the deep convective activity over the tropical western Pacific and suppresses it over the Indian Ocean. The deep convection anomaly generates anomalous Rossby waves that propagate into the northern mid-to-high latitudes to constructively interfere with the climatological wavenumber-1 and wavenumber-2 components, thereby resulting in enhanced upward-propagating tropospheric planetary-scale waves and a weakened SPV_DJ anomaly. During 1979–1997, however, the deep convection anomaly over the tropical western Pacific and Indian Oceans in ON related to the easterly phase of the QBO_AS is weaker and shifts eastward, which excites the anomalous Rossby waves to constructively/destructively interfere with the climatological wavenumber-1 component in the midlatitudes/high latitudes, thereby weakening the upward-propagating planetary-scale waves and leading to a weaker linkage with the SPV_DJ. Further analyses reveal that the unstable relationship may be associated with the interdecadal differences in deep convection over the tropical western Pacific and Indian Oceans and the upward-propagating tropospheric planetary-scale waves in ON.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2012-7
       
  • Progress and Prospects of Research on Subseasonal to Seasonal Variability
           and Prediction of the East Asian Monsoon

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      Abstract: Subseasonal to seasonal (S2S) variability represents the atmospheric disturbance on the 10–90-day timescale, which is an important bridge linking weather and climate. In 2015, China Meteorological Administration (CMA) listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks. After five years of research, significant progress has been made on the mechanisms of the East Asian monsoon (EAM) S2S variability, related impact of climate change, as well as the predictability on the S2S timescale of numerical models. The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction. However, under the influence of global warming and the interactions among climate systems, the S2S variability of the EAM is so complex that its prediction remains a great challenge. This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction, including characteristics of the main S2S modes of the EAM, their impact on the extreme events in China, effects of external and internal forcing on the S2S variability, as well as uncertainties of climate models in predicting the S2S variability, with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences. The present bottlenecks, future directions, and critical research recommendations are also analyzed and presented.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2059-5
       
  • Interannual Relationship between Summer North Atlantic Oscillation and
           Subsequent November Precipitation Anomalies over Yunnan in Southwest China
           

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      Abstract: The summer North Atlantic Oscillation (SNAO) strongly affects the climate variability over Europe and downstream East Asia similar to its winter counterpart. This study thus investigates the interannual relationship between SNAO and the subsequent autumn precipitation anomalies over Yunnan, Southwest China and related physical mechanisms based on reanalysis data during 1958–2020. The results show that the interannual variations in SNAO exhibit a significant positive correlation with anomalies of Yunnan precipitation in November. Composite analyses demonstrate that for the positive SNAO phase, the positive sea surface temperature anomalies (SSTAs) in midlatitude North Atlantic as part of a tripole SSTA tend to weaken from summer to November through changes in surface heat fluxes. In turn, the predominately negative SSTA in tropical North Atlantic that persists into November induces an anomalous cyclone at midlatitudes, which triggers two middle-upper tropospheric wave trains propagating from midlatitude North Atlantic to Yunnan. The subtropical wave train propagates eastward along the subtropical westerly jet, and the mid-high latitude wave train follows the great circle path across Scandinavia and central Asia to the Tibetan Plateau. Both wave trains favor development of an anomalous cyclone over the southern Tibetan Plateau. The upper-tropospheric divergent condition on the southeastern side of the anomalous cyclone is dynamically conducive to locally ascending motion over Yunnan, thus producing above-normal precipitation. The opposite situation occurs in the negative SNAO phase. A coupled model reproduces well the wave train propagation and thereby confirms the positive relationship between SNAO and Yunnan precipitation in November.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2046-x
       
  • Assessing 10 Satellite Precipitation Products in Capturing the July 2021
           Extreme Heavy Rain in Henan, China

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      Abstract: On 20 July 2021, a sudden rainstorm happened in central and northern Henan Province, China, killing at least 302 people. This extreme precipitation event incurred substantial socioeconomic impacts and resulted in serious losses. Accurate monitoring of such rainstorm events is crucial. In this study, qualitative and quantitative methods are used to comprehensively evaluate the abilities of 10 high-resolution satellite precipitation products [CMORPH-Raw (Climate Prediction Center morphing technique), CMORPH-RT, PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks), GPM IMERG-Early (Integrated Multisatellite Retrievals for Global Precipitation Measurement), GPM IMERG-Late, GSMaP-Now (Global Satellite Mapping of Precipitation), GSMaP-NRT, FY-2F, FY-2G, and FY-2H] in capturing this extreme rainstorm event, as well as their performances in monitoring different precipitation intensities. The results show that these satellite precipitation products are able to capture the spatial distributions of the rainstorm (e.g., its location in central and northern Henan), but all products have underestimated the amount of precipitation in the rainstorm center. With the increase in precipitation intensity, the hit rate decreases, the threat score decreases, and the false alarm rate increases. CMORPH-RT is better at capturing the rainstorm than CMORPH-Raw, and it depictes the rainstorm process well; GPM IMERG-Late is more accurate than GPM IMERG-Early; GSMaP-NRT has performed better than GSMaP-Now; and PERSIANN-CCS and FY-2F perform poorly. Among the products, CMORPH-RT performs the best, which has accurately captured the center of the rainstorm, and is also the closest to the station-based observations. In general, the satellite precipitation products that integrate infrared and passive microwave data are found to be better than those that only make use of infrared data. The satellite precipitation retrieval algorithm and the amount of passive microwave data have a relatively greater impact on the accuracy of satellite precipitation products.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2053-y
       
  • An Empirical Model of Tropical Cyclone Intensity Forecast in the Western
           North Pacific

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      Abstract: The relative impact of environmental parameters on tropical cyclone (TC) intensification rate (IR) was investigated through a box difference index (BDI) method, using TC best track data from Joint Typhoon Warning Center and environmental fields from the NCEP final analysis data over the western North Pacific (WNP) during 2000–2018. There are total 6307 TC samples with a 6-h interval, of which about 14% belong to rapid intensification (RI) category. The analysis shows that RI occurs more frequently with higher environmental sea surface temperature, higher oceanic heat content, and lower upper-tropospheric temperature. A moderate easterly shear is more favorable for TC intensification. TC intensification happens mostly equatorward of 20°N while TC weakening happens mostly when TCs are located in the northwest of the basin. Mid-tropospheric relative humidity and vertical velocity are good indicators separating the intensification and non-intensification groups. A statistical model for TC intensity prediction was constructed based on six environmental predictors, with or without initial TC intensity. Both models are skillful based on Brier skill score (BSS) relative to climatology and in comparison with other statistical models, for both a training period (2000–2018) and an independent forecast period (2019–2020).
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2016-3
       
  • Refined Evaluation of Satellite Precipitation Products against Rain Gauge
           Observations along the Sichuan—Tibet Railway

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      Abstract: Being constructed in southwestern China, the Sichuan—Tibet Railway (STR) travels across the eastern Tibetan Plateau where there is the most complex terrain and changeable weather in the world. Due to sparse ground-based observations over the Tibetan Plateau, precipitation products retrieved by remote sensing are more widely used; however, satellite-based precipitation products (SPPs) have not yet been strictly and systematically evaluated along the STR. This study aims to evaluate the performance of six SPPs by a series of metrics with available ground observations along the STR during 1998–2020. The six SPPs include the datasets derived from the Tropical Rainfall Measuring Mission (TRMM), Climate Prediction Center morphing technique (CMORPH), Global Precipitation Measurement (GPM), Global Satellite Mapping of Precipitation (GSMaP), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Fengyun-2 satellites precipitation estimate (FY2PRE). The results indicate that most of the SPPs can capture the precipitation characteristics on multiple timescales (monthly, daily, hourly, and diurnal cycle) as shown by the evaluated metrics. The probability density functions of the daily and hourly precipitation are also well represented by the SPPs, and 30 mm day−1 and 16 mm h−1 are identified as the daily and hourly thresholds of extreme precipitation events along the STR. The best SPP varies at different timescales: GPM and GSMaP are suitable for the monthly and daily scale, and FY2PRE and GPM are suited to the hourly scale. In general, GPM is relatively optimum on multiple timescales, and PERSIANN gives the worst performance. In addition, the SPPs perform worse at higher altitudes and for more intense precipitation. Overall, the results from this study are expected to provide essential reference for using the SPPs in meteorological services and disaster prevention in the STR construction and its future operation.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-1226-z
       
  • Stochastically Perturbed Parameterizations for the Process-Level
           Representation of Model Uncertainties in the CMA Global Ensemble
           Prediction System

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      Abstract: To represent model uncertainties at the physical process level in the China Meteorological Administration global ensemble prediction system (CMA-GEPS), a stochastically perturbed parameterization (SPP) scheme is developed by perturbing 16 parameters or variables selected from three physical parameterization schemes for the planetary boundary layer, cumulus convection, and cloud microphysics. Each chosen quantity is perturbed independently with temporally and spatially correlated perturbations sampled from log-normal distributions. Impacts of the SPP scheme on CMA-GEPS are investigated comprehensively by using the stochastically perturbed parametrization tendencies (SPPT) scheme as a benchmark. In the absence of initial-condition perturbations, perturbation structures introduced by the two schemes are investigated by analyzing the ensemble spread of three forecast variables’ physical tendencies and perturbation energy in ensembles generated by the separate use of SPP and SPPT. It is revealed that both schemes yield different perturbation structures and can simulate different sources of model uncertainty. When initial-condition perturbations are activated, the influences of the two schemes on the performance of CMA-GEPS are assessed by calculating verification scores for both upper-air and surface variables. The improvements in ensemble reliability and probabilistic skill introduced by SPP and SPPT are mainly located in the tropics. Besides, the vast majority of the reliability improvements (including increases in ensemble spread and reductions in outliers) are statistically significant, and a smaller proportion of the improvements in probabilistic skill (i.e., decreases in continuously ranked probability score) reach statistical significance. Compared with SPPT, SPP generally has more beneficial impacts on 200-hPa and 2-m temperature, along with 925-hPa and 2-m specific humidity, during the whole 15-day forecast range. For other examined variables, such as 850-hPa zonal wind, 850-hPa temperature, and 700-hPa humidity, SPP tends to yield more reliable ensembles at lead times beyond day 7, and to display comparable probabilistic skills with SPPT. Both SPP and SPPT have small impacts in the extratropics, primarily due to the dominant role of the singular vectors-based initial perturbations.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-2011-8
       
  • Direct Radiative Effects of Dust Aerosols over Northwest China Revealed by
           Satellite-Derived Aerosol Three-Dimensional Distribution

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      Abstract: Northwest China is recognized as a main source and a major transport channel of dust aerosols in East Asia. With a fragile ecological environment, this region is quite sensitive to global climate change. Based on the satellite-derived aerosol three-dimensional distribution, the direct radiative effects of dust aerosols over Northwest China are evaluated. Aerosols over Northwest China are mainly distributed in the Tarim Basin, Junggar Basin, Gobi Desert, and Loess Plateau. The aerosol extinction coefficients are greater than 0.36 km−1 over the Tarim Basin and 0.16 km−1 over the Gobi Desert and Loess Plateau, decreasing with height. Aerosols over Northwest China are mainly composed of pure dust and polluted dust. These dust aerosols can modify the horizontal temperature gradient, vertical thermodynamic structure, and diurnal temperature range by absorbing and scattering shortwave radiation and emitting longwave radiation. For the column atmosphere, the radiative effect of dust aerosols shows heating effect of approximately 0.3 K day−1 during the daytime and cooling effect of approximately −0.4 K day−1 at night. In the vertical direction, dust aerosols can heat up the lower atmosphere (0.5–1.5 K day−1) and cool down the upper atmosphere (about −1.0 K day−1) during the daytime, while they cool down the lower atmosphere (−3 to −1.5 K day−1) and heat up the upper atmosphere (1–1.5 K day−1) at night. There are also significant lateral and vertical variations in the dust radiative effects corresponding to their spatial distributions. This study provides some scientific basis for reducing uncertainty in the investigation of aerosol radiative effects and provides observation evidence for simulation studies.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-1212-5
       
  • Assimilation of All-Sky Radiance from the FY-3 MWHS-2 with the Yinhe
           4D-Var System

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      Abstract: Compared with traditional microwave humidity sounding capabilities at 183 GHz, new channels at 118 GHz have been mounted on the second generation of the Microwave Humidity Sounder (MWHS-2) onboard the Chinese FY-3C and FY-3D polar orbit meteorological satellites, which helps to perform moisture sounding. In this study, as the all-sky approach can manage non-linear and non-Gaussian behavior in cloud- and precipitation-affected satellite radiances, the MWHS-2 radiances in all-sky conditions were first assimilated in the Yinhe four-dimensional variational data assimilation (YH4DVAR) system. The data quality from MWHS-2 was evaluated based on observation minus background statistics. It is found that the MWHS-2 data of both FY-3C and FY-3D are of good quality in general. Six months of MWHS-2 radiances in all-sky conditions were then assimilated in the YH4DVAR system. Based on the forecast scores and observation fits, we conclude that the all-sky assimilation of the MWHS-2 at 118- and 183-GHz channels on FY-3C/D is beneficial to the analysis and forecast fields of the temperature and humidity, and the impact on the forecast skill scores is neutral to positive. Additionally, we compared the impacts of assimilating the 118-GHz channels and the equivalent Advanced Microwave Sounding Unit-A (AMSUA) channels on global forecast accuracy in the absence of other satellite observations. Overall, the impact of the 118-GHz channels on the forecast accuracy is not as large as that for the equivalent AMSUA channels. Nevertheless, all-sky radiance assimilation of MWHS-2 in the YH4DVAR system has indeed benefited from the 118-GHz channels.
      PubDate: 2022-10-01
      DOI: 10.1007/s13351-022-1208-1
       
  • Simulations of a Persistent Heat Wave Event in Missouri in Summer 2012
           Using a High-Resolution WRF Model

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      Abstract: An extreme and persistent heat wave event hit Missouri in summer 2012. Current operational forecast models failed to predict such an event at a long lead. The objective of the current study is to simulate this extreme event using a high-resolution Weather Research and Forecasting (WRF) model with eight combined physical (including longwave/shortwave radiation, microphysics, and planetary boundary layer) parameterization packages. Integrated for one month, the model successfully simulates the spatial pattern and temporal evolution of surface air temperature, compared to in-situ observations. The interesting feature is an oscillatory development of the surface air temperature, with a pronounced synoptic timescale. Such a temperature evolution is consistent with the local zonal wind fluctuation, implying the important role of anomalous temperature advection. An overall skill score that combines the performance of 2-m air temperature, relative humidity, and precipitation fields is defined. The result shows that the combination of Thompson, Rapid Radiative Transfer Model for GCMs (RRTMG), and Mellor-Yamada-Nakanishi-Niino level-3 (MYNN3) schemes presents the best WRF simulation. A further analysis of this best simulation shows that the model successfully reproduces the urban heat island (UHI) effect in the Kansas City Metropolitan Area with realistic diurnal variation of 2-m air temperature in the urban and nonurban areas with a larger UHI effect at nighttime.
      PubDate: 2022-08-01
      DOI: 10.1007/s13351-022-2039-9
       
 
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