The dynamic emissivity retrieved from window channels of the microwave humidity sounder II (MWHS-2) onboard the China Meteorological Administration&#x2019;s FengYun (FY)-3C polar orbiting satellite can provide more realistic emissivity over lands and potentially improve the numerical weather prediction (NWP) forecasts. However, whether the assimilation with the dynamic emissivity works for the precipitation forecasts over the complex geography is less investigated. In this paper, a typical precipitating case generated by the Southwest Vortex is selected and the Weather Research and Forecasting data assimilation (WRFDA) system is applied to examine the impacts of assimilating MWHS-2/FY-3C with the uses of the emissivity atlas and the dynamic emissivity on the forecasts. The results indicate that the use of the dynamic emissivity retrieved from the 89&#x2009;GHz channel of MWHS-2/FY-3C apparently increases the used data number for assimilation and does improve the initial fields and the 24-hour forecasts (from 0000 UTC 24 June 2016 to 0000 UTC 25 June 2016) of precipitation distribution and intensity except for the rainfall over 100&#x2009;mm. But these positive impacts are not evidently better than those with the emissivity atlas. In general, these results still suggest that the future use of the dynamic emissivity in the assimilation over the complex terrain is promising.

Keyi Chen

Jiao Fan

Zhipeng Xian

Assimilation of MWHS-2/FY-3C 183&#x2009;GHz Channels Using a Dynamic Emissivity Retrieval and Its Impacts on Precipitation Forecasts: A Southwest Vortex Case

The growing demand for Global Navigation Satellite System (GNSS) technology has necessitated the establishment of a vast and ever-growing network of International GNSS Service (IGS) tracking stations worldwide. The IGS provides highly accurate and highly reliable daily time-series Zenith Tropospheric Delay (ZTD) products using data from the member sites towards the use of GNSS for precise geodetic, climatological, and meteorological applications. However, if for reasons like poor internet connectivity, equipment failure, and power outages, the IGS station is inaccessible or malfunctioning, and gaps are created in the data archive resulting in degrading the quality of the ZTD and precipitable water vapour (PWV) estimation. To address this challenge as a means of providing an alternative data source to improve the continuous availability of ZTD data and as a backup data in the event that the IGS site data are missing or unavailable in West Africa, this paper compares the sitewise operational Vienna Mapping Functions 3 (VMF3) ZTD product with the IGS final ZTD product over five IGS stations in West Africa. Eight different statistical evaluation metrics, such as the mean bias (MB), mean absolute error (MAE), root mean squared error (RMSE), Pearson correlation coefficient (r), coefficient of determination (r2), refined index of agreement (IAr), Nash&#x2013;Sutcliffe coefficient of efficiency (NSE), and the fraction of prediction within a factor of two (FAC2), are employed to determine the degree of agreement between the VMF3 and IGS tropospheric products. The results show that the VMF3-ZTD product performed excellently and matches very well with the IGS final ZTD product with an average MB, MAE, RMSE, r, r2, NSE, IAr, and FAC2 of 0.38&#x2009;cm, 0.87&#x2009;cm, 1.11&#x2009;cm, 0.988, 0.976, 0.967, 0.992, and 1.00 (100&#x0025;), respectively. This result is an indication that the VMF3-ZTD product is accurate enough to be used as an alternative source of ZTD data to augment the IGS final ZTD product for positioning and meteorological applications in West Africa.

Samuel Osah

Akwasi A. Acheampong

Collins Fosu

Isaac Dadzie

Evaluation of Zenith Tropospheric Delay Derived from Ray-Traced VMF3 Product over the West African Region Using GNSS Observations

Dynamical downscaling of General Circulation Model (GCM) data for any region has been made possible due to a set of physics options and model dynamics within the Weather Research and Forecasting (WRF) model. This study evaluated the performance of an ensemble of physics options in simulating rainfall during wet and dry seasons of Lao PDR. The model evaluation criteria focused on identifying the optimum physics options for a range of scenarios. No single combination of physics options performed well in all scenarios reflecting the importance of using different parameterizations according to the geographic location and the intended application of the results. For the dry season, none of the ensemble members performed satisfactorily for the southern region of Lao PDR, while all the ensemble members performed well for the northern and central regions. While almost all the WRF simulations overestimated the rainfall during the wet season, BMJ for cumulus physics performed better in the northern and central regions, and KF performed better in the south region. The YSU scheme performed best as the planetary boundary layer for both wet and dry seasons, while WSM5 for the wet season and Lin for the dry season gave the best model performance as the microphysics option.

Rajitha Athukorala

Thaileng Thol

Panduka Neluwala

Monica Petri

Sorlaty Sengxeu

Larxoy Lattada

Sengkeo Keomanivong

Viengkham Sithivong

Evaluating the Performance of a WRF Physics Ensemble in Simulating Rainfall over Lao PDR during Wet and Dry Seasons

Since January 1, 2018, ships berthed at all ports of the three designated emission control areas (ECAs) in China are required to use fuel with sulfur content not exceeding 0.5&#x0025; (m/m), excluding one hour postarrival and one hour predeparture. To understand changes in SO2 due to this policy, two observation stations were established on Waigaoqiao Dock in the Yangtze River estuary. Three data types were collected from March 2018 to May 2018, namely, wind speed and direction, SO2 concentration, and ships&#x2019; arrival and departure times. The statistics indicate that the wind direction changed little during the observation period and SO2 concentration was below 5&#x2009;&#xb5;g/m3 77.47&#x0025; of the time. Meanwhile, ships&#x2019; arrival and departure at the dock had a distinct influence on overall SO2 distribution, including occurrence of concentrations &#x2265;5&#x2009;&#xb5;g/m3. The three types of data were divided into six groups and a difference-in-difference model was used for analysis. The result shows that SO2 concentration increases due to the use of high-sulfur fuel and is especially significant when the wind is southwesterly. Furthermore, there was a positive correlation between increases in SO2 concentrations over 5&#x2009;&#xb5;g/m3 and the number of ships arriving or departing from the port. This study reports the positive impact of fuel switching on air quality and can be used to evaluate adherence to the ECA policy.

Fan Zhou

Yunli Fan

Determination of the Influence of Fuel Switching Regulation on the Sulfur Dioxide Content of Air in a Port Area Using DID Model

This study evaluates the spatiotemporal rainfall variability over the semimountainous Soan River Basin (SRB) of sub-Himalayan Pothwar region, Pakistan. The temporal rainfall trend analysis of sixteen rain gauges was performed on annual basis with long-term (1981&#x2013;2016) data. The results depicted that there is substantial year-to-year and season-to-season variability in rainfall patterns, and rainfall patterns are generally erratic in nature. The results highlight that most of the highland rainfall stations showed decreasing trends on annual basis. The central and lowland stations of the study area recorded an increasing trend of rainfall except for Talagang station. The average annual rainfall of the study area ranges between 492&#x2009;mm and 1710&#x2009;mm in lowland and high-altitude areas, respectively. Of the whole year&#x2019;s rainfall, about 70 to 75&#x0025; fall during the monsoon season. The rainfall spatial distribution maps obtained using the inverse distance weighting (IDW) method, through the GIS software, revealed the major rainfall range within the study area. There is a lack of water during postmonsoon months (November&#x2013;February) and great differences in rainfall amounts between the mountainous areas and the lowlands. There is a need for the rational management of mountainous areas using mini and check dams to increase water production and stream regulation for lowland areas water availability. The spatiotemporal rainfall variability is crucial for better water resource management schemes in the study area of Pothwar region, Pakistan.

Fiaz Hussain

Ghulam Nabi

Ray-Shyan Wu

Spatiotemporal Rainfall Distribution of Soan River Basin, Pothwar Region, Pakistan

With the outbreak of the COVID-19 pandemic around the world, many countries announced lockdown measures, including Thailand. Several scientific studies have reported on improvements in air quality due to the impact of these COVID-19 lockdowns. This study aims to investigate the effects of the COVID-19 lockdown and its driving influencing factors on air pollution in Greater Bangkok, Thailand, using in situ measurements. Overall, PM2.5, PM10, O3, and CO concentrations presented a significant decreasing trend during the COVID-19 outbreak year based on three periods: the Before Lockdown, Lockdown, and After Lockdown periods, for PM2.5: &#x2212;0.7&#x0025;, &#x2212;15.8&#x0025;, and &#x2212;20.7&#x0025;; PM10: &#x2212;4.1&#x0025;, &#x2212;31.7&#x0025;, and &#x2212;6.1&#x0025;; and O3: &#x2212;0.3&#x0025;, &#x2212;7.1&#x0025;, and &#x2212;4.7&#x0025;, respectively, compared to the same periods in 2019. CO concentrations, especially which had increased by 14.7&#x0025; Before Lockdown, decreased by &#x2212;8.0&#x0025; and &#x2212;23.6&#x0025; during the Lockdown and After Lockdown periods, respectively. Meanwhile, SO2 increased by 54.0&#x0025;, 41.5&#x0025;, and 84.6&#x0025;, and NO2 increased by 20.1&#x0025;, 3.2&#x0025;, and 26.6&#x0025;, respectively, for the Before Lockdown, Lockdown, and After Lockdown periods. PCA indicated a significant combination effect of atmospheric mechanisms that were strongly linked to emission sources such as traffic and biomass burning. It has been demonstrated that the COVID-19 lockdown did pause some of these anthropogenic emissions, i.e., traffic and commercial and industrial activities, but not all of them. Even low traffic emissions, on their own, did not cause an absolute reduction in air pollution since there are several primary emission sources that dominate the air quality over Greater Bangkok. Finally, these findings highlight the impact of COVID-19 lockdown measures not only on air pollution levels but on their effects on air pollution characteristics, as well.

Parichat Wetchayont

Investigation on the Impacts of COVID-19 Lockdown and Influencing Factors on Air Quality in Greater Bangkok, Thailand

The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Yunnan Province, so it is very important to further study the relationship between vegetation and climate. In this study, we explored the temporal changes of normalized difference vegetation index (NDVI) in different seasons based on MOD13Q1 NDVI by the maximum value composite and then analyzed spatial distribution characteristics of vegetation using Sen&#x2019;s tendency estimation, Mann&#x2013;Kendall significance test, and coefficient of variation model (CV) combined with terrain factors. Finally, the concurrent and lagged effects of NDVI on climate factors in different seasons and months were discussed using the Pearson correlation coefficient. The results indicate that (1) the temporal variation of the NDVI showed that the NDVI values of different vegetation types increased at different rates, especially in growing season, spring, and autumn; (2) for spatial patterns, the NDVI, CV, and NDVI trends had strong spatial heterogeneity owning to the influence of altitudes, slopes, and aspects; and (3) the concurrent effect of vegetation on climate change indicates that the positive effect of temperature on NDVI was mainly in growing season and autumn, whereas spring NDVI was mainly influenced by precipitation. In addition, the lag effect analysis results revealed that spring precipitation has a definite inhibition effect on summer and autumn vegetation, but spring and summer temperature can promote the growth of vegetation. Meanwhile, the precipitation in the late growing season has a lag effect of 1-2 months on vegetation growth, and air temperature has a lag effect of 1 month in the middle of the growing season. Based on the above results, this study provided valuable information for ecosystem degradation and ecological environment protection in the Yunnan Province.

Huaizhang Sun

Jiyan Wang

Junnan Xiong

Jinhu Bian

Huaan Jin

Weiming Cheng

Ainong Li

Vegetation Change and Its Response to Climate Change in Yunnan Province, China

The devastating effects of drought on agriculture, water resources, and other socioeconomic activities have severe consequences on food security and water resource management. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. In this study, meteorological droughts over six coastal synoptic stations were investigated using three-month Standardized Precipitation Index (SPI). The dry seasons of November-December-January (NDJ), December-January-February (DJF), and January-February-March (JFM) were the focal seasons for the study. Trends of dry seasons SPIs were evaluated using seasonal Mann&#x2013;Kendall test. The relationship between drought SPI and ocean-atmosphere climate indices and their predictive ability were assessed using Pearson correlation and Akaike Information Criterion (AIC) stepwise regression method to select best climate indices at lagged timestep that fit the SPI. The SPI exhibited moderate to severe drought during the dry seasons. Accra exhibited a significant increasing SPI trend in JFM, NDJ, and DJF seasons. Besides, Saltpond during DJF, Tema, and Axim in NDJ season showed significant increasing trend of SPI. In recent years, SPIs in dry seasons are increasing, an indication of weak drought intensity, and the catchment areas are becoming wetter in the traditional dry seasons. Direct (inverse) relationship was established between dry seasons SPIs and Atlantic (equatorial Pacific) ocean's climate indices. The significant climate indices modulating drought SPIs at different time lags are a combination of either Nino 3.4, Nino 4, Nino 3, Nino 1&#x2009;+&#x2009;2, TNA, TSA, AMM, or AMO for a given station. The AIC stepwise regression model explained up to 48&#x0025; of the variance in the drought SPI and indicates Nino 3.4, Nino 4, Nino 3, Nino 1&#x2009;+&#x2009;2, TNA, TSA, AMM, and AMO have great potential for seasonal drought prediction over Coastal Ghana.

Martin Addi

Kofi Asare

Samuel Kofi Fosuhene

Theophilus Ansah-Narh

Kenneth Aidoo

Comfort Gyasiwaa Botchway

Impact of Large-Scale Climate Indices on Meteorological Drought of Coastal Ghana

In this study, an experimental hydrometeorological forecasting system was developed based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model. The system downloads global real-time ocean, atmosphere, and wave forcing data, producing regional forecasts every day. A coastal area in South China, encompassing Hainan Island, Leizhou Peninsula, and surrounding sea areas, was chosen as the study domain. A series of 72-hour forecasting simulations were conducted in the area, lasting from July 27 to August 31, 2019. The forecasts throughout August were chosen for evaluation with station observations, along with two sets of reanalysis data, ERA5 and CLDAS. The evaluation results revealed that the COAWST model had high potential for routine forecasting operations. The 24&#x2009;h forecasts, with a lead time of 24 hours, had high accuracy, while the 48&#x2009;h and 72&#x2009;h forecasts did not differ greatly in terms of performance. The distributions of bias between forecast and reanalysis data showed obvious differences between land and sea, with more forecasted precipitation and lower temperatures in land grids than in sea grids. In most cases, the forecasts were closer to ERA5 in terms of means and other statistical measures. The forecasts enlarged the land-sea differences of temperature when compared with ERA5 and strengthened summer monsoon with more moisture transported to land areas. Resulting from that, a forecasted bias of lower surface pressure, higher air humidity, stronger south wind, and so forth was also detected over the domain but at low values.

Jing Zou

Chesheng Zhan

Haiqing Song

Tong Hu

Zhijin Qiu

Bo Wang

Zhiqian Li

Development and Evaluation of a Hydrometeorological Forecasting System Using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Model

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Advances in Meteorology publishes research in all areas of meteorology and climatology. Topics include forecasting techniques and applications, meteorological modelling, data analysis, atmospheric chemistry and physics, and climate change.

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James Cleverly, the journal’s Chief Editor, is based at the University of Technology in Sydney, Australia. His research interests include carbon, water and energy fluxes of arid-land Acacia swales; physics of the atmospheric surface layer and interactions with terrestrial ecosystems.

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