On the role of horizontal resolution over the Tibetan Plateau in the REMO regional climate model

A number of studies have shown that added value is obtained by increasing the horizontal resolution of a regional climate model to capture additional fine-scale weather processes. However, the mechanisms leading to this added value are different over areas with complicated orographic features, such as the Tibetan Plateau (TP). To determine the role that horizontal resolution plays over the TP, a detailed comparison was made between the results from the REMO regional climate model at resolutions of 25 and 50 km for the period 1980–2007. The model was driven at the lateral boundaries by the European Centre for Medium-Range Weather Forecasts Interim Reanalysis data. The experiments differ only in representation of topography, all other land parameters (e.g., vegetation characteristics, soil texture) are the same. The results show that the high-resolution topography affects the regional air circulation near the ground surface around the edge of the TP, which leads to a redistribution of the transport of atmospheric water vapor, especially over the Brahmaputra and Irrawaddy valleys—the main water vapor paths for the southern TP—increasing the amount of atmospheric water vapor transported onto the TP by about 5. This, in turn, significantly decreases the temperature at 2 m by > 1.5 °C in winter in the high-resolution simulation of the southern TP. The impact of topography on the 2 m temperature over the TP is therefore by influencing the transport of atmospheric water vapor in the main water vapor paths. © 2018 Springer-Verlag GmbH Germany, part of Springer Natur

Seasonal temperature response over the Indochina Peninsula to a worst-case high-emission forcing: a study with the regionally coupled model ROM

Changes of surface air temperature (SAT) over the Indochina Peninsula (ICP) under the Representative Concentration Pathway (RCP) 8.5 scenario are projected for wet and dry seasons in the short-term (2020–2049) and long-term (2070–2099) future of the twenty-first century. A first analysis on projections of the SAT by the state-of-the-art regionally coupled atmosphere-ocean model ROM, including exchanges of momentum, heat, and water fluxes between the atmosphere (Regional Model) and ocean (Max Planck Institute Ocean Model) models, shows the following results: (i) In both seasons, the highest SAT occurs over the southern coastal area while the lowest over the northern mountains. The highest warming magnitudes are located in the northwestern part of the ICP. The regionally averaged SAT over the ICP increases by 2.61 °C in the wet season from short- to long-term future, which is slightly faster than that of 2.50 °C in the dry season. (ii) During the short-term future, largest SAT trends occur over the southeast and northwest ICP in wet and dry seasons, respectively. On regional average, the wet season is characterized by a significant warming rate of 0.22 °C decade−1, while it is non-significant with 0.11 °C decade−1for the dry season. For the long-term future, the rapid warming is strengthened significantly over whole ICP, with trends of 0.51 °C decade−1and 0.42 °C decade−1in wet and dry seasons,respectively. (iii) In the long-term future, more conspicuous warming is noted, especially in the wet season, due to the increased downward longwave radiation. Higher CO2concentrations enhancing the greenhouse effect can be attributed to the water vapor–greenhouse feedback, which, affecting atmospheric humidity and counter radiation, leads to the rising SAT

Added value of the regionally coupled model ROM in the East Asian summer monsoon modeling

The performance of the regional atmosphere-ocean coupled model ROM (REMO-OASIS-MPIOM) is compared with its atmospheric component REMO in simulating the East Asian summer monsoon (EASM) during the time period 1980–2012 with the following results being obtained. (1) The REMO model in the standalone configuration with the prescribed sea surface conditions produces stronger low-level westerlies associated with the South Asian summer monsoon, an eastward shift of the western Pacific subtropical high (WPSH) and a wetter lower troposphere, which jointly lead to moisture pathways characterized by stronger westerlies with convergence eastward to the western North Pacific (WNP). As a consequence, the simulated precipitation in REMO is stronger over the ocean and weaker over the East Asian continent than in the observational datasets. (2) Compared with the REMO results, lower sea surface temperatures (SSTs) feature the ROM simulation with enhanced air-sea exchanges from the intensified low-level winds over the subtropical WNP, generating an anomalous low-level anticyclone and hence improving simulations of the low-level westerlies and WPSH. With lower SSTs, ROM produces less evaporation over the ocean, inducing a drier lower troposphere. As a result, the precipitation simulated by ROM is improved over the East Asian continent but with dry biases over the WNP. (3) Both models perform fairly well for the upper level circulation. In general, compared with the standalone REMO model, ROM improves simulations of the circulation associated with the moisture transport in the lower- to mid-troposphere and reproduces the observed EASM characteristics, demonstrating the advantages of the regionally coupled model ROM in regions where air-sea interactions are highly relevant for the East Asian climate

Impact of COVID-19 Lockdown and Atmospheric Circulation on the Air Quality in Wuhan During Early 2020

Previous studies indicated that the air quality was improved in Wuhan during COVID-19 lockdown. However, the impact of atmospheric general circulation on the changes of air quality has not been taken into account. The present study aims to discuss the improvement of air quality in Wuhan and its possible reasons during COVID-19 lockdown. The results showed that all air pollutants except O3 decreased in Wuhan during early 2020. The occurrence days of A, C, W and NW types’ circulation pattern during early 2020 are more than those during the same period of 1979-2020. The occurrence days of SW type’s circulation pattern is slightly less than those during early 1979-2020. With more occurrence days of these dominant atmospheric circulation patterns, the number of polluted days could rise in Wuhan during early 2020. Nevertheless, this scenario didn’t occur. The COVID-19 lockdown did improve the air quality in Wuhan during early 2020

Probabilistic Forecasting of the 500 hPa Geopotential Height over the Northern Hemisphere Using TIGGE Multi-model Ensemble Forecasts

Bayesian model averaging (BMA) and ensemble model output statistics (EMOS) were used to improve the prediction skill of the 500 hPa geopotential height field over the northern hemisphere with lead times of 1–7 days based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and UK Met Office (UKMO) ensemble prediction systems. The performance of BMA and EMOS were compared with each other and with the raw ensembles and climatological forecasts from the perspective of both deterministic and probabilistic forecasting. The results show that the deterministic forecasts of the 500 hPa geopotential height distribution obtained from BMA and EMOS are more similar to the observed distribution than the raw ensembles, especially for the prediction of the western Pacific subtropical high. BMA and EMOS provide a better calibrated and sharper probability density function than the raw ensembles. They are also superior to the raw ensembles and climatological forecasts according to the Brier score and the Brier skill score. Comparisons between BMA and EMOS show that EMOS performs slightly better for lead times of 1–4 days, whereas BMA performs better for longer lead times. In general, BMA and EMOS both improve the prediction skill of the 500 hPa geopotential height field

A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System

Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical downscaling of global ensemble perturbations. One month consecutive tests are implemented to evaluate the performance of both methods in the operational REPS environment. The perturbation characteristics are analyzed and ensemble forecast verifications are conducted; furthermore, a TC case is investigated. The main conclusions are as follows: the ETKF perturbations contain more power at small scales while the ones derived from downscaling contain more power at large scales, and the relative difference of the two types of perturbations on scales become smaller with forecast lead time. The growth of downscaling perturbations is more remarkable, and the downscaling perturbations have larger magnitude than ETKF perturbations at all forecast lead times. However, the ETKF perturbation variance can represent the forecast error variance better than downscaling. Ensemble forecast verification shows slightly higher skill of downscaling ensemble over ETKF ensemble. A TC case study indicates that the overall performance of the two systems are quite similar despite the slightly smaller error of DOWN ensemble than ETKF ensemble at long range forecast lead times

International Meteorological and Hydrological Training and Its Evaluation at WMO RTC Nanjing peer-review under responsibility of [name organizer]

Abstract This paper deals with the international meteorological and hydrological training issue and its evaluation approach based on the teaching practice and experience during last twenty years at World Meteorological Organization Regional Training Centre (WMO RTC) in Nanjing. The success of the training courses which are organized by the RTC Nanjing in the framework of Guidelines for the Education and Training of Personnel in Meteorology and Operational Hydrology (WMO-No. 258) has been widely recognized by those countries which benefit from the training programs as well as the WMO and other related international organizations. The design of the training syllabuses fulfils the Member's training requirements of WMO. Some new training courses which reflect the advances in meteorology and hydrology have also been offered in order to enhance the capabilities of trainees in the use of the up-to-date numerical products. In addition to face-to-face teaching, blended learning has been introduced for some training courses to enhance the training efficiency. Based on the "CIPP model" and "Kirkpatrick Four Levels Model", a more efficient evaluation system for the international meteorological and hydrological training has been established. Results show that this evaluation system is capable of assessing the training target, the training results as well as training itself. The evaluation index system consists of six indices which focus on the training subjects and trainees, respectively. The application of this evaluation system in the international meteorological and hydrological training has significantly improved the training efficiency and training itself at RTC Nanjing

Prediction Skill of Extended Range 2-m Maximum Air Temperature Probabilistic Forecasts Using Machine Learning Post-Processing Methods

The extended range temperature prediction is of great importance for public health, energy and agriculture. The two machine learning methods, namely, the neural networks and natural gradient boosting (NGBoost), are applied to improve the prediction skills of the 2-m maximum air temperature with lead times of 1–35 days over East Asia based on the Environmental Modeling Center, Global Ensemble Forecast System (EMC-GEFS), under the Subseasonal Experiment (SubX) of the National Centers for Environmental Prediction (NCEP). The ensemble model output statistics (EMOS) method is conducted as the benchmark for comparison. The results show that all the post-processing methods can efficiently reduce the prediction biases and uncertainties, especially in the lead week 1–2. The two machine learning methods outperform EMOS by approximately 0.2 in terms of the continuous ranked probability score (CRPS) overall. The neural networks and NGBoost behave as the best models in more than 90% of the study area over the validation period. In our study, CRPS, which is not a common loss function in machine learning, is introduced to make probabilistic forecasting possible for traditional neural networks. Moreover, we extend the NGBoost model to atmospheric sciences of probabilistic temperature forecasting which obtains satisfying performances

Possible Relationships between the Interdecadal Anomalies of Heavy Rainfall under Northeastern China Cold Vortexes and the Sea Surface Temperature (SST)

As an important component of the East Asian monsoon system, the northeast cold vortex (NECV) exerts a significant impact on weather and climate, especially in Northeast China. This study investigated the interdecadal spatiotemporal variability of heavy rainfall under the cold vortex of Northeast China (NECVHR) and its relationship with sea surface temperature (SST) during 1961–2019 over Northeast China. To investigate the dominant factors affecting variability in the heavy rainfall between May and September, an empirical orthogonal function (EOF) analysis was performed. To detect the trends and changes, a Mann-Kendall (MK) test was used. The sliding t-test was used to identify the change points and the significance. Pearson correlation analysis was used to analyze the relationship between SST and NECVHR, and the t-test was used to verify the significance. The results showed that the total amount of cold vortex heavy rainfall during May–September ranged from 153 to 12,509 mm for 1961–2019. An abrupt interdecadal change was seen after 2014 in Northeast China. The EOF analyses revealed that the first, second, and third EOFs explain 76%, 12.1%, and 5.5% of the total variance, respectively. The EOF followed the heavy rainfall pattern, with increases in the south (southeast) and decreases in the north (northwest) over Northeast China. Heavy rainfall over Northeast China positively correlated with the Atlantic multidecadal oscillation (AMO) index. The heavier rainfall under cold vortex (MCVHR) years revealed that the equipotential height was obviously located over the Sea of Japan, west of Northeast China and the Qinghai Tibet plateau. The cyclonic circulation over the East China Sea and north (northeasterly) wind prevails over Northeast China during less heavy rainfall under cold vortex (LCVHR) years. A high anticyclonic circulation over the Qinghai Tibet plateau resulted in stronger cold advection over Northeast China. The anticyclonic circulations over the East China Sea and the Sea of Japan (east), and the western (southwesterly) winds prevail over Northeast China, with a relatively shallow cold trough over the Qinghai Tibet plateau. The findings in this paper provided a better understanding of the interdecadal variability of NECVHR over Northeast China. The findings can be helpful for several stakeholders regarding agricultural production, water resource management, and natural habitat conversation in Northeast China