Changes In Meteorological Variables Research Articles

Impact of paddy on groundwater declination in Central Punjab

Abstract Central Punjab includes over 40% of the state of Punjab. In Central Punjab, groundwater levels are dropping by more than 1 m every year. The primary cause of groundwater depletion in Central Punjab between 1998 and 2019 is presented in this paper. In order to detect any sudden changes in the area under paddy and the depth of groundwater, Pettitt's test was used. Based on change points and trends, the entire duration was split into two time periods: 1998–2008 (T1) and 2009–2019 (T2); rainfall, potential evapotranspiration, and paddy area were assessed in both periods with 1998–2019 (T3). The slope methodology developed by Mann–Kendall and Sen demonstrated the trend analysis. The findings showed that changes in climate were caused by humans during the 1998–2008 era, changes in meteorological variables were caused by humans during the 2008–2019 period, and changes in climate were caused by humans during the T3 period. The major growing trend of groundwater depth loss is thought to be caused by the combined effects of rainfall variations, an increase in the maximum temperature, cropping intensity, and the number of pumping units.

Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015–2021

Surface ozone (O3) concentrations in China have increased largely in the past decade. An accurate understanding of O3 pollution evolution is critical for making effective regulatory policies. Here we integrate data- and process-based models to explore the drivers of the observed summertime surface O3 change in the North China Plain (NCP) over 2015–2021. The data-based model by the deep learning (DL) suggests the reverse of meteorological contributions to the observed O3 change, i.e., 0.14 ppb/y in 2015–2019 and −1.74 ppb/y in 2019–2021. This is mainly resulted from the reversed changes in meteorological variables in surface air temperature and relative humidity. The simulations from a global chemical transport model, GEOS-Chem, also support those results, i.e., the meteorological contribution to O3 changes are 0.26 ppb/y in 2015–2019 and −0.74 ppb/y in 2019–2021. Furthermore, our analysis exhibits possible weakened anthropogenic contributions to surface O3 rise, for example, 1.53 and 0.54 ppb/y by DL in 2015–2019 and 2019–2021, respectively. Similarly, GEOS-Chem simulations suggest an accelerated decrease in surface O3 concentrations driven by the decline in nitrogen dioxide (NO2) concentrations, i.e., approximately 0.4 and 1.2 ppb in 2015–2019 and 2019–2021, respectively. The combined effects of meteorological and anthropogenic contributions led to a significant decrease in surface O3 concentrations by −1.20 ppb/y in 2019–2021. The findings in this work offer valuable insights to mitigate O3 pollution in China.

Spatio-temporal characteristics and driving factors of flash drought recovery: From the perspective of soil moisture and GPP changes

Flash drought recovery is significant to evaluate the impact of flash drought and the resilience of ecosystem. However, the definition of flash drought recovery stage and its mechanism remain unclear, with limited research in this area. This study proposes the definitions of flash drought recovery stage based on soil moisture change and gross primary productivity (GPP) change. The spatio-temporal characteristics, driving factors and differences between two identifications are investigated in Xiang River Basin (XRB) and Wei River Basin (WRB), two typical humid and semiarid basins in China. The main results are as follows: (1) XRB has a slightly longer recovery time and a higher recovery rate in terms of soil moisture-based definition, while GPP-based definition shows similar recovery times for both basins, with WRB having a higher recovery rate. (2) Based on soil moisture-based definition, the recovery time and recovery rates of different flash drought events in the same basin vary greatly, while most flash drought events in both basins recover within 2*8 days in terms of GPP-based definition. (3) Under both definitions, regions with relatively higher precipitation, lower average temperature and lower solar radiation tend to have higher recovery rates and shorter recovery time. Besides, grasslands tend to recover more quickly from flash drought than forests with GPP-based definition. (4) The recovery stage with soil moisture-based definition begins with the changes in associated meteorological variables, while the recovery stage with GPP-based definition begins 8 to 2*8 days after the changes of meteorological variables occur. This study proposes preliminary definitions for the recovery stage of flash drought and reveals the mechanism underlying the flash drought recovery, which are crucial for understanding the evolution of flash drought and reducing the risks resulting from it.

A comparative analysis of the sea breeze on the Texas Gulf Coast and its impact on precipitation

An analysis of the sea breeze, its mechanisms and correlation with precipitation was performed in two cases for an urban city on the Gulf Coast where the first case examined pure sea breezes and the second investigated those associated with a likelihood for appreciable inland precipitation. Adjacent study areas to the east and west were used as background conditions to determine if changes in Houston's sea breeze are controlled by urbanization or climate change. Sea breeze days were selected by a three-filter algorithm using the difference in land and sea surface temperatures, ΔTSB, as well as geostrophic and surface winds. Results showed a decrease of 3–21% in sea breeze days between cases in the Houston area. Case 2 exhibited the most (e.g., 524 sea breeze days) and greatest increase (0.63 day yr−1) in sea breeze days in Beaumont, driven by an increase in land surface temperature which is statistically significant (p-value = 0.02) and decrease in sea surface temperature leading to an increase in ΔTSB, again with statistical significance (p-value = 0.01). Precipitation has increased by at least 1.07 × 10−8 mm day−1, with the greatest increase of 2.59 × 10−8 mm day−1 in Beaumont. The only increase in precipitation that was not found to be statistically significant existed for the most inland station in Houston. Based on an areal analysis of land cover, Houston is significantly more urban than the adjacent study areas: 65.8% of its area falls into the four developed classes, and these classes have increased by 11.4% between 2001 and 2019. Comparatively, Beaumont and Victoria are 16.8% and 7.16% developed, and urban development increased by 1.20% and 0.61%, respectively, over the same period. This indicates the possibility that the roughness elements in Houston's built environment interfere with the sea breeze, while climate change has driven its increase in Beaumont and decrease in Victoria as evidenced by our reported changes in meteorological variables.

Local and global sensitivity analysis and its contributing factors in reference crop evapotranspiration

Abstract Sensitivity analysis (SA) intends to identify the key meteorological variables that affect the performance of reference crop evapotranspiration (ET0) models. It is of importance in assessing the variability of meteorological variables and ET0, especially in the face of increasing climate uncertainties. However, the surging of inconsistencies resulting from global changes in meteorological conditions due to climate change have impacted the ET0 model estimation in different regions, with detrimental effects on water resources and crop production. Therefore, efficient SA is necessary to evaluate the impact of changes in meteorological variables that influence ET0 model estimation. This mini review analyses the various SA methods applied in the field of ET0, based on a comprehensive and comparative analysis of existing SA methods from all around the world. The study discusses the advantages and disadvantages of each SA method, as well as the factors affecting the SA of ET0. The study also provides future prospects that may contribute to more solid and powerful analysis for ET0 model estimations and conclusions.

Wetting trend in Northwest China reversed by warmer temperature and drier air

Northwest China has experienced a warming-wetting climate featured by increasing temperature and precipitation during the past six decades. Recent studies suggested that the climate may have shifted from wetting to drying after the 1990s if changes in energy supply were considered. However, how the change in energy supply affects the dryness remains unclear. In this study, we quantified the dryness in Northwest China based on the Standardized Precipitation Evapotranspiration Index (SPEI) which considers the impact of potential evapotranspiration estimated by the Penman-Monteith equation on dryness during 1961–2018. Then, the contributions of changes in meteorological variables (precipitation, temperature, relative humidity, wind speed, and net radiation) to the dryness changes were estimated using a detrending technique. The results indicated that Northwest China experienced a wetting period (1961–1989) and then a drying period (1989–2018). During 1961–1989, increased precipitation and slowed wind were the main drivers of the wetting trend. During 1989–2018, although the increased precipitation and decline in solar radiation favored a wetting condition, warmer temperature, drier air (decrease in relative humidity), together with rebounded wind speed offset the wetting trend and resulted in significantly increasing dryness in Northwest China. The dryness would further increase if current climate trends continue in the future, which may have important implications for water management in Northwest China.

Impacts of dams and reservoirs on local climate change: a global perspective

As a primary artificial project in a river basin, the role of large dams and related reservoirs in mitigating the hydrological and meteorological extremes has been widely recognized. Moreover, construction of additional large dams is considered as one of the best available options to meet future increases in water, food, and energy demands, although this may drastically affect the surrounding natural environment. However, the issue about the degree of such effects is still unclear, although the interactive impacts of dams and related reservoirs on the changes in meteorological variables are of great scientific importance. Therefore, this study aims to explore the impacts of reservoir characteristic factors (RCFs) on local climate change near the reservoir through examining the correlations between the RCFs of selected dams and related reservoirs and meteorological variables all over the world. The major findings are: (a) the correlations of the RCFs with evaporation are the opposite of those with precipitation; (b) dams and related reservoirs can have completely opposite (weakening or enhancing) effects on different meteorological variables; and (c) the RCFs outperform the geographical factors in terms of the impact on precipitation, whereas the variation of evaporation is more sensitive to geographical factors. Overall, the outcomes of this study will be useful for policymakers to have a more informed understanding of local climate change affected by large dams and related reservoirs in the future.

Use of a multiscalar GRACE-based standardized terrestrial water storage index for assessing global hydrological droughts

A multiscalar standardized terrestrial water storage index (STI) is proposed to assess global hydrological droughts in this study. STI is defined as the standardized statistical deviation of terrestrial water storage (TWS) measured by GRACE to the climatology at multiple time scales. Because of the statistical nature of its definition, the proposed index is comparable to other standardized drought indices in different time scales, e.g., standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) across different regions at multiple time scales. Our comparisons of STI with multiscalar drought indices (i.e. SPI and SPEI) and uni-scalar indices (i.e. self-calibrating palmer drought severity index [scPDSI], standardized soil moisture index [SM-Z], standardized runoff index [R-Z], and GRACE-based drought severity index [DSI]) show that STI can capture drought events with less noise than other indicators in persistent drought events. As a hydrological drought index based on TWS (which includes groundwater, soil moisture, etc.), STI at short-term time scales (e.g. 3 and 6 months) have higher correlations (mostly > 0.7) with SPI/SPEI at long-term scales (e.g. 18 and 24 months). Since the TWS measured by GRACE incorporates the impacts of the accumulated changes in meteorological variables, hydrological processes, and human activities as well as the advantage of multiscale, STI better represents vegetation growth reflected by Normalized Difference Vegetation Index (NDVI) than uni-scalar drought indices including the GRACE-based DSI, suggesting STI is a robust indicator for hydrological droughts and vegetation changes.

Assessing the effects of climate change on urban watersheds: a review and call for future research

Considerable efforts have been made to control and manage the hydrology and water quality of watersheds impacted by urban development through the construction of stormwater control measures (SCMs). Climate change (CC) could, however, undermine these efforts by intensifying precipitation and hydrologic extremes. Although the impact of CC on water resources has been well-documented, its impact on urban hydrology remains less studied. CC may complicate sustainable urban hydrology, which can cause a reduction in the efficiency of SCMs with changes in precipitation patterns (i.e., changes in duration, frequency, depth, and intensity). More intense precipitation may result in reduced runoff reduction and treatment efficiency, given that SCMs have a finite surface storage volume and surface infiltration capacity. Determining the functionality of various SCMs under future climate projections is important to better understand the impact of CC on urban stormwater and how well these practices can build resiliency into our urban environment. The purpose of this review is to provide the needs and opportunities for future research on quantifying the effect of CC on urban SCMs and to characterize the performance and effectiveness of these systems under existing and projected climate scenarios. A summary of the modeled constituents as well as the stormwater and climate models applied in these studies is provided. We concluded that there are still limitations in exploring the impact of future changes in meteorological variables that will influence the operation of SCMs in the long-term. Previous studies mostly focused on the impacts of CC on urban runoff quantity, and only a handful of studies have explored water quality impacts from CC, such as potential changes in water temperature, metals, and pathogens. Assessing the pollutant-removal efficiency of SCMs, such as bioretention, infiltration trenches, dry and wet swales, rooftop disconnections, and wet and dry ponds, which are common practices in urban watersheds, also needs more attention. Analysis of the cost of adapting SCMs for CC to maintain the same performance as current climate conditions is also recommended for future research.

Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data.

Seasonal changes in meteorological factors [e.g., ambient temperature (Ta), humidity, and sunlight] could significantly influence a person's sleep, possibly resulting in the seasonality of sleep properties (timing and quality). However, population-based studies on sleep seasonality or its association with meteorological factors remain limited, especially those using objective sleep data. Japan has clear seasonality with distinctive changes in meteorological variables among seasons, thereby suitable for examining sleep seasonality and the effects of meteorological factors. This study aimed to investigate seasonal variations in sleep properties in a Japanese population (68,604 individuals) and further identify meteorological factors contributing to sleep seasonality. Here we used large-scale objective sleep data estimated from body accelerations by machine learning. Sleep parameters such as total sleep time, sleep latency, sleep efficiency, and wake time after sleep onset demonstrated significant seasonal variations, showing that sleep quality in summer was worse than that in other seasons. While bedtime did not show clear seasonality, get-up time varied seasonally, with a nadir during summer, and positively correlated with the sunrise time. Estimated by the abovementioned sleep parameters, Ta had a practically meaningful association with sleep quality, indicating that sleep quality worsened with the increase of Ta. This association would partly explain seasonal variations in sleep quality among seasons. In conclusion, Ta had a principal role for seasonality in sleep quality, and the sunrise time chiefly determined the get-up time.

Lagged Association between Climate Variables and Hospital Admissions for Pneumonia in South Africa.

Pneumonia is a leading cause of hospitalization in South Africa. Climate change could potentially affect its incidence via changes in meteorological conditions. We investigated the delayed effects of temperature and relative humidity on pneumonia hospital admissions at two large public hospitals in Limpopo province, South Africa. Using 4062 pneumonia hospital admission records from 2007 to 2015, a time-varying distributed lag non-linear model was used to estimate temperature-lag and relative humidity-lag pneumonia relationships. Mean temperature, relative humidity and diurnal temperature range were all significantly associated with pneumonia admissions. Cumulatively across the 21-day period, higher mean daily temperature (30 °C relative to 21 °C) was most strongly associated with a decreased rate of hospital admissions (relative rate ratios (RR): 0.34, 95% confidence interval (CI): 0.14–0.82), whereas results were suggestive of lower mean daily temperature (12 °C relative to 21 °C) being associated with an increased rate of admissions (RR: 1.27, 95%CI: 0.75–2.16). Higher relative humidity (>80%) was associated with fewer hospital admissions while low relative humidity (<30%) was associated with increased admissions. A proportion of pneumonia admissions were attributable to changes in meteorological variables, and our results indicate that even small shifts in their distributions (e.g., due to climate change) could lead to substantial changes in their burden. These findings can inform a better understanding of the health implications of climate change and the burden of hospital admissions for pneumonia now and in the future.

Seasonal and diurnal variations of observed convective rain events in Metro Manila, Philippines

The seasonal and diurnal characteristics of localized convective rain events in Metro Manila, Philippines were examined using observations from 16 automated weather stations in the city during the years 2013–2014. After partitioning total rainfall to determine the proportion that is mainly due to localized convection, the diurnal patterns of frequency and intensity of convective rain were then investigated during the northeast monsoon (from November to March), summer (from April to May), and southwest monsoon (from June to October) seasons. Maximum changes in meteorological variables were used to further verify and characterize localized convective rain events over the city. Results show higher rainfall (by ~500 mm) over northern Metro Manila compared to the southern area throughout the period of study. Although total rainfall was highest during the southwest monsoon season, it was during the summer season, when the total rainfall was least, that the largest proportion of rainfall, i.e. 55%, was attributed to convective rain. Almost 45% of the total convective rain events were identified as localized rain events. During the summer season, localized convective rain events in Metro Manila were prominent and vigorous (i.e. greater change in meteorological variables) in the afternoon, and were noted to move along the direction of the prevailing wind, i.e. from the northeastern side of the city towards the west. Increased understanding of the meteorological characteristics of these localized rain events can help improve rainfall forecasting over Metro Manila, leading to better disaster risk reduction and resilience in the city.

Impacts of meteorology and emission control on the abnormally low particulate matter concentration observed during the winter of 2017

As the capital of China, Beijing is the subject of great concern regarding atmospheric pollution, especially that of fine particulate matter (PM2.5). In winter 2017 (i.e., November 2017 to February 2018), PM2.5 concentration in Beijing decreased to its lowest value in the past ten years. In this study, we sought to investigate the impacts of meteorology and emission control on this abnormally low pollution phenomenon. Weather Research and Forecasting coupled with Chemistry (WRF-Chem) simulations show that sensitivity to meteorological factors accounts for approximately 51% of the observed change between winters 2016 and 2017 in Beijing. We further compared the pollution dispersion condition of winters 2016 and 2017 in terms of large-scale circulation patterns and local mixing layer heights (MLHs). The meteorological condition in 2017 was characterized by stronger wind speed (WS) and higher MLH. We classified circulation patterns into two types using the obliquely rotated Principal Component Analysis in T-mode (T-PCA) method. Active weather was found to be associated with high MLH, high near-surface WS, and high ventilation coefficient (VC), which favors the dispersion of pollutants. In contrast, the changes of meteorological variables and pollution conditions are almost opposite for stable weather. Active weather amounted to 73 and 85 days for winters 2016 and 2017, respectively. Stable weather conditions prevailed on 46 days in winter 2016, and 32 days in 2017. Less stable weather during winter 2017 compared with that of winter 2016 possibly favored efficient ventilation of boundary-layer pollution. A lack of persistent stable weather also contributed to low PM2.5 concentration in 2017. This research is important for air-pollution assessment and regional environmental management.

Impact of meteorological parameters on suicide mortality rates: A case-crossover analysis in Southern Germany (1990–2006)

BackgroundThere is evidence for a seasonal pattern of suicides with peaks in spring and early summer; however, only a limited number of studies has investigated whether daily changes in meteorological variables may trigger suicides. MethodsDaily fatal suicide (N = 10,595) and meteorological data were available for four Bavarian cities and ten counties (Germany) for 1990–2006. City/county-specific immediate, delayed and cumulative effects of air temperature, sunshine duration, and cloud cover on suicides were analyzed using a time-stratified case-crossover approach; city/county-specific effects were then combined using random effects meta-analysis. Potential effect modifiers were specific weather conditions, personal or regional characteristics, and season. ResultsA 5 °C increase in air temperature on the day before a suicide compared to the control days was associated with a 5.7% (95% confidence interval (CI): 0.6; 11.0) higher suicide risk. Further, the suicide risk was 6.5% (95% CI: 0.2; 13.3) higher on days with low/medium cloud cover (0–6 oktas) compared to days with high cloud cover (7–8 oktas). While daily changes in temperature were not associated with suicides in spring, we found a higher suicide risk in summer, autumn, and winter in association with temperature increases. The effects of cloud cover were strongest in summer and autumn and on days with temperature above the median (>8.8 °C). Sunshine duration was not associated with suicides. ConclusionWe found a higher risk for suicides in association with short-term increases in air temperature on the day before the event compared to the control days and on days with low to medium cloud cover. This may highlight times when people are more likely to commit suicide.

Different determinants of radiation use efficiency in cold and temperate forests

AbstractAimTo verify which vegetation and environmental factors are the most important in determining the spatial and temporal variability of average and maximum values of radiation use efficiency (RUEann and RUEmax, respectively) of cold and temperate forests.LocationForty‐eight cold and temperate forests distributed across the Northern Hemisphere.Major taxa studiedEvergreen and deciduous trees.Time period2000–2011.MethodsWe analysed the impact of 17 factors as potential determinants of mean RUE (at 8 days interval, annual and interannual level) and RUEmax (at annual and interannual level) in cold and temperate forests by using linear regression and random forests models.ResultsMean annual RUE (RUEann, c. 1.1 gC/MJ) and RUEmax (c. 0.8 gC/MJ) did not differ between cold and temperate forests. However, for cold forests, RUEann was affected by temperature‐related variables, while for temperate forests RUEann was affected by drought‐related variables. Leaf area index (LAI) was important for both forest types, while N deposition only for cold forests and cloud cover only for temperate forest. RUEmax of cold forests was mainly driven by N deposition and LAI, whereas for temperate forests only a weak relationship between RUEmax and CO2 concentration was found. Short‐term variability of RUE was strongly related to the meteorological variables and varied during the season and was stronger in summer than spring or autumn. Interannual variability of RUEann and RUEmax was only weakly related to the interannual variability of the environmental drivers.Main conclusionsCold and temperate forests show different relationships with the environment and vegetation properties. Among the RUE drivers observed, the least anticipated was N deposition. RUE is strongly related to short‐term and seasonal changes in meteorological variables among seasons and among sites. Our results should be considered in the formulation of climate zone‐specific tools for remote sensing and global models.

Regions of influence and environmental effects of Santa Ana wind event

In the present study, we simulated an extreme Santa Ana wind event that affected northwestern Mexico and the southwestern United States in October 2007. The principal aim was to investigate the interaction of Santa Ana winds with the mountain chains of California and Baja California and the resulting meteorological perturbations over the Pacific Ocean. The Weather Research and Forecasting model coupled with a chemistry module (WRF-Chem) were used to analyze changes in meteorological variables and chemical variables such as dust concentration. The Santa Ana wind event analyzed modified meteorological conditions deteriorating climate welfare conditions and causing health threats in several densely populated areas through the formation of dust storms and spread of wildfires. The calculation revealed a decrease in relative humidity from 90% to less than 10% along the coasts of California and Baja California besides increasing temperature. The wind speeds intensified as a result of channeling through terrain gaps, causing the formation of finger-like structures of hot and dry air along the coast. The vertical behavior of the Santa Ana winds over the mountains of California and Baja California suggests that the descent of air masses from 2000 m to the surface could contribute to increasing coastal temperature. The intense winds led to the emission of dust, affecting several areas in Mexico and reducing air quality. Notably, large amounts of dust flowed to the Pacific Ocean off California and Baja California and also to the Gulf of California.

Trends of surface maximum ozone concentrations in Switzerland based on meteorological adjustment for the period 1990–2014

We investigate the temporal trends of peak ozone in Switzerland for the 1990–2014 time period. The meteorological conditions have a large influence on ozone formation and drive a large part of the variability in ozone observations. Therefore, the influence of meteorology on ozone was estimated using generalized additive models and removed from the ozone observations. A variable selection method was used for model building allowing the detection of the meteorological variables that have the largest effect on the variability of daily maximum ozone at each considered station. It was found that peak concentrations of ozone have been reducing in most of the stations, indicating a positive effect of implemented air pollution control measures on locally produced ozone. In the remote, high alpine site of Jungfraujoch a small upward trend of peak ozone was observed, most likely due to influence of hemispheric background ozone. In the most polluted traffic sites, peak ozone has for a different reason also been increasing until around 2003, when this trend started to level off. In traffic sites the increasing ozone concentrations due to reduced titration by nitrogen monoxide was the dominating process. One of the advantages of meteorological correction of ozone observations for trend estimation is that the uncertainty in the calculated trends is reduced. In addition, trend estimation based on meteorologically corrected ozone is less influenced by exceptional meteorological events during a specific time period, such as heat waves or by temporal changes in meteorological variables.

Prediction of airborne pollen concentrations for the plane tree as a tool for evaluating allergy risk in urban green areas

The different species of the genus Platanus, commonly known as plane trees, are widely grown as an ornamental species in Mediterranean cities over recent years. The pollen of these species is a major source of allergens. However, surprisingly little published research has addressed methods for predicting the allergy risk prompted by this pollen. In this work, we developed models for predicting airborne Platanus pollen concentrations constructed using data from central Spain. Predictions are very useful to alert citizens and give allergy patients advanced warning of expected high airborne pollen concentrations. The prediction models indicate that airborne Platanus pollen concentrations can be forecasted up to seven days (one week) in advance, using a method which combines the analysis of long-term aerobiological data (in this case, over the eleven-year study period), in order to detect seasonal trends within time-series, with the modelling of short-term fluctuations in airborne pollen concentrations prompted by daily changes in meteorological variables and pollen concentrations over the previous days. The meteorological variables studied were maximum and minimum temperature, rainfall and relative humidity. The results of the validation of prediction models yielded a coefficient of correlation between observed and predicted values of R = 0.7, indicating that these models predict most of the pollen peaks in the airborne pollen curve.

Translating large-scale climate variability into crop production forecast in Europe

Studies show that climate variability drives interannual changes in meteorological variables in Europe, which directly or indirectly impacts crop production. However, there is no climate-based decision model that uses indices of atmospheric oscillation to predict agricultural production risks in Europe on multiple time-scales during the growing season. We used Fast-and-Frugal trees to predict sugar beet production, applying five large-scale indices of atmospheric oscillation: El Niño Southern Oscillation, North Atlantic Oscillation, Scandinavian Pattern, East Atlantic Pattern, and East Atlantic/West Russian pattern. We found that Fast-and-Frugal trees predicted high/low sugar beet production events in 77% of the investigated regions, corresponding to 81% of total European sugar beet production. For nearly half of these regions, high/low production could be predicted six or five months before the start of the sugar beet harvesting season, which represents approximately 44% of the mean annual sugar beet produced in all investigated areas. Providing early warning of crop production shortages/excess allows decision makers to prepare in advance. Therefore, the use of the indices of climate variability to forecast crop production is a promising tool to strengthen European agricultural climate resilience.

Effects of aerosol-radiation feedback and topography during an air pollution event over the North China Plain during December 2017

The online coupled Weather Research and Forecasting-Chemistry (WRF-Chem) model was used to investigate a regional haze event, which occurred over the North China Plain (NCP) from 27 to 30 December 2017. Modeling scenarios with and without aerosol-radiation feedback within the planetary boundary layer (PBL) were investigated. By adding aerosol-radiation feedback to the model, we captured the spatial and temporal characteristics of the observed temperature and relative humidity (RH), as well as surface PM2.5, SO2, and NO2 concentrations during this event. The primary meteorological driver of this event was stable meteorological conditions, namely, a low PBL, strong temperature inversion, high RH, and a weak wind field. Aerosol-radiation feedback mechanisms affected these meteorological fields, causing reductions in maximum surface solar radiation, the surface energy budget, PBL height, surface 2-m temperature and middle atmosphere RH, while increasing surface 2-m RH, middle atmosphere temperature, and atmospheric stability. Changes in meteorological variables in turn affected air pollutant distributions and concentrations, with PM2.5 increasing by more than 20 μg/m3 over the NCP during this event. Another sensitivity experiment was carried out over the Taihang and Yanshan mountain areas, in which topography was flattened to a 30-m height to explore the impacts of topography on air pollution in the NCP region. Modeling revealed various topographic effects on meteorological variables related to these two mountains, including a lowered PBL height, reduced wind speed, blocked uniform surface winds, and more intense temperature inversion. Consequently, surface air pollutant concentrations increased unevenly over the NCP in this experiment. Implementation of more detailed PBL processes, as well as radiosonde and satellite data products into the WRF-Chem model would improve simulations of haze formation over the NCP.