Specific Humidity Research Articles

Moisture sorption isotherm and thermodynamic analysis of egg powders dried by foam-mat-assisted refractance window drying.

In the designed study, the moisture sorption isotherm and thermodynamic properties of refractance-window-dried egg white powder (EWP), egg yolk powder (EYP) and whole egg powder (WEP) were determined. The adsorption isotherm of egg powders was classified as type II, giving a sigmoidal shape. Peleg showed the highest goodness of fitting for egg powder. The monolayer moisture content of egg powders varied between 0.02 and 0.09 g g-1. According to the thermodynamic analysis, an increase in moisture content led to a decrease in net isosteric heat of sorption (qst), and the highest decrease was observed in EWP. The qst of EWP was calculated as 18 637 kJ mol-1, while it decreased to 3104 kJ mol-1 at 0.2 g g-1 moisture content. Like qst, sorption entropy decreased from 52.07 to 7.14 J mol-1 K-1 with increasing water activity (aw) for EWP. Increasing temperature caused a decrease in spreading pressure and was higher in EWP samples. Increasing moisture content and temperature also decreased Gibbs free energy level. Moisture sorption isotherm (MSI) is used to predict the amount of bound water in a material at a specific relative humidity and temperature. To inhibit chemical and microbiological spoilage, the drying process must continue until the monolayer moisture content is reached. In this study, the monolayer moisture content of powdered eggs for safe storage was demonstrated by MSI. Additionally, by determining the thermodynamic functions of egg powder, valuable information was obtained related to predicting the energy requirement in drying processes. © 2024 Society of Chemical Industry.

Ocean Surface Warming and Cooling Responses and Feedback Processes Associated With Polar Lows Over the Nordic Seas

AbstractStrong surface winds induced by polar lows (PLs) may affect the upper ocean. However, understanding of the oceanic responses and feedback processes associated with PLs remains insufficient, especially for observations. Using a combined analysis of satellite‐based sea surface temperature (SST) and PL tracking data, we investigated the oceanic response to 380 PL passages over the Nordic Sea occurring between 1999 and 2018. Consequently, two types of oceanic responses—warming and cooling—occurred in 32% and 40% of the total occurrences, respectively. The average magnitude of SST response was approximately ±0.2 K. Significant differences in upward surface turbulent heat flux (THF) between warming and cooling response cases were found, causing a significant difference in the decay rate after maximum PL development. By analyzing changes in the state variables of the THF, we identified two different feedback processes depending on the oceanic warming/cooling response. During a warming (cooling) response, the atmosphere near the surface becomes more unstable (stable), and the turbulence of the marine atmospheric boundary layer increases (decreases), which strengthens (weakens) the ocean surface wind and decreases (increases) temperature and specific humidity. These changes contribute to increasing (decreasing) the upward THF that influences PL development. The differences between these two responses may be caused by the state of the upper ocean layer, including temperature inversion. The analysis of the in situ observations of the upper ocean supports the hypothesis that a warming response occurs when inversion is strong. This study emphasizes the importance of feedback through oceanic responses for understanding and predicting PL.

The relationship between the tropopause folds and deep convective activities over the Tibetan Plateau

Tropopause folds (TFs) are crucial in the development of certain meteorological events. Using ERA5 reanalysis data from 1979 to 2015 and the “3D-labelling” algorithm for identifying TFs, along with OLR and TRMM precipitation data, this study conducted a composite analysis to explore the relationship between TFs and deep convective activities (DCAs) over Tibetan Plateau (TP) and to investigate the underlying physical mechanisms. The results indicate that TFs have a strong inhibitory effect on DCAs at the locations of folds. Conversely, medium and deep folds significantly enhance DCAs to the northeast of folds, with the degree of enhancement intensifying with the depth of fold. During medium and deep fold occurrences, an increase in specific humidity from the surface to near the tropopause is observed northeast of the folds, coupled with significant lifting of the tropopause east of the deep folds, favoring the initiation and development of DCAs. Positive potential vorticity (PV) anomalies resulting from the downward intrusion of stratospheric air with high PV generate cyclonic circulation in the upper troposphere at the locations of folds. This is complemented by anticyclonic circulations triggered on both sides of medium and deep folds. These circulation anomalies induce upper-level divergence and lower-level convergence, leading to anomalous upward motion northeast of the folds and thereby promoting DCAs. Furthermore, the increased low-level static stability northeast of medium and deep folds aid in accumulating potential instability. The anomalous ascent in this region facilitates the release of this instability, and in conjunction with reduced static stability near the tropopause, enables DCAs to reach higher altitudes.

Spatial downscaling of rainfall from general circulation models: A chaos theory-based framework

The present study proposes a new chaos theory-based local approximation technique for the spatial downscaling of rainfall from GCM outputs. The approach involves: (1) reconstruction of relevant climate data in the state space using an embedding technique; and (2) use of a neighbor search procedure in the reconstructed space and local approximation for downscaling. The approach is implemented for downscaling of monthly rainfall at a spatial resolution of 0.25° × 0.25° across India. The effectiveness of the approach is first demonstrated using the NCEP/NCAR reanalysis dataset (1979–2014) and then tested using the outputs from five CMIP6 GCMs (CMCC-ESM2, CESM2-WACCM, CMCC-CM2-HR4, E3SM-1-1-ECA, and BCC-ESM1) (1961–2014). Eight climate variables (eastward wind, northward wind, relative humidity, specific humidity, surface temperature, air temperature, sea level pressure, and geopotential height) are considered as predictors, with the observed rainfall data from the India Meteorological Department (IMD) as the predictand. Three statistical measures, namely correlation coefficient (CC), Nash-Sutcliffe efficiency (NSE), and normalized root mean square error (NRMSE), are used for evaluation. The results indicate that the local approximation downscaling approach yields promising results for both reanalysis dataset and GCM outputs. Among the five GCMs, the CMCC-ESM2 model yields the best results. Comparison of the results from the chaos theory-based approach with those of the linear regression-based approach indicates better performance of the former. The proposed framework is general and can be applied for any climate variable, GCM, and region.

Anomaly-Based Variable Models: Examples of Unusual Track and Extreme Precipitation of Tropical Cyclones

Tropical cyclones (TCs) can cause severe wind and rain hazards. Unusual TC tracks and their extreme precipitation forecasts have become two difficult problems faced by conventional models of primitive equations. The case study in this paper finds that the numerical computation of the climatological component in conventional models restricts the prediction of unusual TC tracks. The climatological component should be a forcing quantity, not a predictor in the numerical integration of all models. Anomaly-based variable models can overcome the bottleneck of forecast time length or the one-week forecasting barrier, which is limited to less than one week for conventional models. The challenge in extreme precipitation forecasting is how to physically get the vertical velocity. The anomalous moisture stress modulus (AMSM), as an indicator of heavy rainfall presented in this paper, considers the two conditions associated with vertical velocity and anomalous specific humidity in the lower troposphere. Vertical velocity is produced by the orthogonal collision of horizontal anomalous airflows.

Spatio-Temporal Variation of Virtual Temperature in Ilorin, Kwara State, Nigeria

This study investigates the diurnal and vertical variations of virtual temperature (Tv) and ambient temperature (T) from 2013 to 2023 in Ilorin. Data analysis reveals that Tv peaks between 1200 and 1400 hours daily, influenced mainly by relative humidity and inversely by temperature changes, with no significant pressure impact. At the planetary boundary layer, Tv and T exhibit marginal differences, converging higher in the troposphere due to diminishing specific humidity. Temporal trends indicate a surface temperature increase of 0.065 degrees and a Tv increase of 0.016 degrees over the past decade. While no simple linear correlation between Tv and relative humidity was found, seasonal patterns suggest potential underlying correlations. This highlights the complex interplay of atmospheric variables in influencing virtual temperature and underscores the need for further investigation into seasonal effects.

The influence of water vapour on winter humidity‐related extreme cold events in China

AbstractWinter extreme cold events (ECEs) have profound impacts on human health, transportation, energy consumption and the economy, particularly associated with high‐humidity conditions. Recent research has indicated a growing interest in extreme temperature events that account for the presence of water vapour. However, the characteristics of humidity‐related ECEs (HECEs) remain unclear. Given the rise in atmospheric moisture due to global warming, understanding the influence of water vapour on HECEs becomes crucial. This study examined variations in HECEs identified using the wet‐bulb globe temperature (WBGT) in China during 1959–2020 and quantified the impacts of water vapour. The results revealed a decrease in the intensity and frequency of HECEs in China during this period, except for in northern China, where the intensity increased, which contrasts with the trends in traditional ECEs. Furthermore, strong HECEs were found to exhibit greater frequency, duration and intensity in northern China than weak HECEs. Additionally, the specific humidity for all categories of HECEs in China exhibited an upward trend, with a more rapid increase for strong HECEs. The findings indicated that the intensity of HECEs is positively correlated with the increase in water vapour. Defining a water vapour amplification factor revealed amplified intensity and duration at most grid points, particularly across northern China. Therefore, while winter warming reduces traditional ECEs, HECEs persist and even intensify as humidity increases, confirming significant amplification by water vapour. Our results emphasized the importance of increasing water vapour, driven by global warming, which may increase the risk of HECEs in the future.

Field effectiveness of some essential oil emulsions against the whitefly Bemisia tabaci (GENN.) that infest potato plants in Egypt

AbstractWhitefly, Bemisia tabaci, nymphs and sucking sap adults, is one of the most damaging pests of potato, Solanum tuberosum. Excessive use of pesticides causes environmental pollution and the death of beneficial insects, so it is necessary to search for safer controlling alternatives. An experiment was carried out during seasons 2020–2021 and 2021–2022, under field conditions in Egypt. The objective of this study was to identify the main constituent compounds of peppermint and eucalyptus essential oils prepare coarse emulsion (CE) and nanoemulsion (NE) of both peppermint and eucalyptus essential oils and evaluate their efficiency against the whitefly, B. tabaci, in potato cultivars and the effect of these emulsions on the chemical components of potato leaves. The results revealed that the toxicity of the emulsions decreased with increasing time after spraying. The second spray which took place at a 10-day interval was more effective than the first spray. During the season of 2021, three days following the second spray, the tested emulsions' toxicity was highly effective. The reduction percentages of nymph for peppermint coarse emulsion (PCE), peppermint nanoemulsion (PNE), eucalyptus coarse emulsion (ECE), eucalyptus nanoemulsion (ENE) and imidacloprid were 82.64, 84.14, 73.26, 72.72 and 89.03, but they were 78.58, 83.27, 77.85, 69.97 and 89.26 compared with 2022. A moderately positive correlation was identified between temperature, specific humidity, wind speed and the effectiveness of the emulsions. This indicates that higher levels of temperature, humidity and wind speed were associated with increased efficacy of the emulsions. The study of the phytochemicals (total soluble protein, total carbohydrate, total phenolic contents and peroxidase activity). PCE and ECE achieved a slight decrease in protein levels. Also, ECE increased total plant carbohydrates. All treatments did not affect the phenolic compounds of potato leaf plants except ENE, which caused an increase in phenolic compounds. All treatments decreased the nitrogen plants' contents, while PCE, PNE, and ENE increased the potassium content. All treatments increase the activity of peroxidase (POX) compared with untreated plants. The formulations PNE and ENE might be an interesting alternative for integrated pest management of B. tabaci nymphs.

Satellite-Based Estimation of the Role of Cloud-Radiative Interaction in Accelerating Tropical Cyclone Development

Abstract Recent modeling studies have suggested a potentially important role of cloud-radiative interactions in accelerating tropical cyclone (TC) development, but there has been only limited investigation of this in observations. Here, we investigate this by performing radiative transfer calculations based on cloud property retrievals from the CloudSat Tropical Cyclone (CSTC) dataset. We examine the radius–height structure of radiative heating anomalies, compute the resulting radiatively driven circulations, and use the moist static energy variance budget to compute radiative feedbacks. We find that inner-core midlevel ice water content and anomalous specific humidity increase with TC intensification rate, resulting in enhanced inner-core deep-layer longwave warming anomalies and shortwave cooling anomalies in rapidly intensifying TCs. This leads to a stronger radiatively driven deep in-up-and-out overturning circulation and inner-core radiative feedback in rapidly intensifying TCs. The longwave-driven circulation provides radially inward momentum fluxes and upward moisture fluxes, which benefit TC development, while the shortwave-driven circulation suppresses TC development. The longwave anomalies, which dominate the inner-core positive radiative feedback, are mainly generated from cloud-radiative interactions, with ice particles dominating the deep-layer circulation and liquid droplets and water vapor contributing to the shallow circulation. Moreover, the variability in ice water content, as opposed to the variability in liquid water content and the effective radii of ice particles and liquid droplets, dominates the uncertainty in TC-radiative interaction. These results provide observational evidence for the importance of cloud-radiative interactions in TC development and suggest that the amount and spatial structure of ice water content are critical for determining the strength of this interaction. Significance Statement The limited investigation of tropical cyclone (TC)-radiative interaction in observations impedes our understanding of TC development. This study aims to quantitatively show the spatial variation in radiation in TCs and their effect on TC development by using a set of satellite-based observations. We relate TC-radiative interaction to TC intensification and emphasize the inner-core features. Moreover, we quantitatively demonstrate the relative contribution from clouds, liquid droplets, ice particles, and water vapor to TC-radiative interaction as well as the source of the variation in radiative properties. These results provide an additional observational foundation for the importance of cloud-radiative interactions in TC development and support a quantitative validation for numerical modeling.

Hydrometeorological response to afforestation in the UK: findings from a kilometer-scale climate model

Afforestation is of international interest for its positive benefits on carbon storage, ecology, and society, but its impacts on terrestrial and atmospheric processes are still poorly understood. This study presents the first use of a coupled land surface and convection permitting atmospheric model (CPM) to quantify hydrometeorological effects of afforestation across the United Kingdom, focusing on atmospheric processes often missing in hydrological models. Generating a scenario of 93 000 km2 (40%) additional woodland across the UK, the periods of 2042–2052 and 2062–2072 are analysed. Simulated afforestation alters seasonal and regional UK hydrometeorology. Countrywide runoff increases in all seasons (between 5.4–11 mm and 4.3–8.6% per season) due to elevated subsurface flows from greater soil moisture. Evaporation decreases in summer (−20.6 mm, −10%) but increases in winter (8.1 mm, 15%) whereas rainfall increases throughout all seasons (between 2.2–6.86 mm and 0.9%–2.2% per season). Greater winter rainfall is detected along Great Britain’s west coastline as increased surface roughness produces prolonged and heavier rainfall. In the summer, lower albedo increases potential evapotranspiration and reduces near surface specific humidity: water is locked in deeper soil layers as transpiration diminishes and the topsoil dries out. However, the magnitude of hydrometeorological change due to altered land cover is smaller than the uncertainty in local climate change projections. This work sets a precedent in illustrating the impacts of afforestation on hydrology using a high-resolution CPM and highlights the importance of coupled hydrometeorological processes when investigating land cover impacts on hydrological processes.

IoT-Based Machine Learning System for Physical Intrusion Detection Using Dynamic Temperature and Humidity Observations With Raspberry Pi

This paper presents a system that is able to detect physical intrusion in a specific space based on temperature and humidity change. This specific space was housing hardware components important for information security management infrastructure. Presented system is able to predict that two spaces are connected and that there is a physical breach in protected space. The presented prediction approach involves identifying patterns in historical data, where the subsequent outcomes are already known in advance, and validating these patterns using more recent data. System is implemented using k-Nearest Neighbours, Random Forest, and Support Vector Machine algorithms in Python programming language on Raspberry Pi. Real observed data to predict if specific temperature and humidity indicates intrusion were used. This approach can be used to detect intrusions in the room or in other closed space. More specifically thermal equilibrium phenomenon between two spaces after barrier between them are opened was monitored. Through process of supervised learning using labelled data, system was able to detect intrusion by using k-nearest neighbours, random forest, and support vector machine with different accuracy. Presented model shows better results using k-nearest neighbours and support vector machine with accuracy of 100% compared to random forest with accuracy of 95%. The system is low cost because of cheap Raspberry Pi controller and sensors.

Distribution Characteristics of the Short-term Heavy Rainfall of an MCC in Shandong Province

This study employs a comprehensive approach, utilizing conventional meteorological observation data, Fengyun satellite cloud imagery, and ERA5 reanalysis data to examine a short-term heavy rainfall event and its underlying causes in Shandong Province from August 14 to 16, 2020. The findings reveal that: (1) This event represents a typical Mesoscale Convective Complex (MCC)-induced rainfall process, with the primary precipitation zone in central and southern Shandong. The most intense hourly rainfall is observed along the side of the MCC with the steepest Tropical Brightness Temperature Blackbody (TBB) gradient. The heaviest hourly rainfall happens right around the time of the lowest TBB interval. (2) The rainfall event is marked by a vertical atmospheric structure with a high-altitude westerly jet and a low-level southwest jet, which makes it easy for water vapour to move and shear lines to form. Favourable conditions for water vapour convergence and high specific humidity are noted. During episodes of heavy precipitation, there is a marked upward motion in the lower troposphere, aligning with the vertical pattern of low-level convergence and high-level divergence.

High‐Resolution Climate Simulations Over the Eastern Mediterranean Black Sea Region Using the Pseudo‐Global Warming Method With a CMIP6 Ensemble

AbstractThe strong drying expected in the Eastern Mediterranean with climate change could cause mass migration of people already living under water shortages. On the other hand, precipitation is expected to increase toward the region’s north, particularly those along the interior of the eastern Black Sea coasts, which could worsen existing floods. However, this double‐sided adverse phenomenon and its underlying reasons have been investigated by relatively low‐resolution models in the Eastern Mediterranean Black Sea (EMBS) region, where orographic precipitation prevails. This study performs 4 km resolution Weather Research and Forecasting (WRF) model simulations with and without climate change signals retrieved from a CMIP6 GCM ensemble via pseudo‐global‐warming (PGW). The WRF simulations captured the large‐scale dynamics affecting the EMBS fairly well: an anticyclonic low‐level circulation and enhancing subsidence stem from anomalous ridge development over the central Mediterranean in winter (DJF), and a cyclonic low‐level circulation and weakening subsidence rise from heat‐low development over the Eastern Mediterranean in summer (JJA). The resulting picture of future warming and drying over the area generally supports the literature, although new insights emerge in anomalous precipitation increase, especially in the summer season over the Greater Caucasus and nearby regions. Most likely, the warmer‐than‐expected Caspian Sea induces a large increase in specific humidity and, thus, a large moisture source in the lower troposphere and an extension of the heat‐low effect in the mid‐troposphere. In addition, the high‐resolution WRF simulations provide added value over the complex topography of the Caucasian Mountain range for new insights into this region.

Initial evaluation of humidity profiles retrieved by the EOS-07 millimetre-wave humidity sounder

ABSTRACT The vertical profiles of specific humidity in the troposphere measured by the millimetre-wave humidity sounder (MHS) onboard of the Earth Observation Satellite (EOS)-07 (Microsoft 2B) are validated using ground-based radiosonde observations during July-August 2023. MHS onboard EOS-07 (hereafter referred as EOS-07/MHS) is a 6-channel cross-track scanning radiometer operating in the 183.31 ± 16.25 GHz band. The EOS-07 observations are used to retrieve three-dimensional specific humidity profiling from 1000 hPa (surface) to 100 hPa (16 km) atmospheric pressure levels with a spatial resolution of 10 km at nadir. The EOS-07/MHS measurements over India have a high correlation coefficient of 0.98 with the radiosonde observations. The mean relative bias is found to be 0.44 ± 0.55 g kg−1 below 350hPa and 2.8 ± 2.3 g kg−1 above 350 hPa. It is also found that above the 350 hPa level, MHS seems to be systematically overestimating the radiosonde measurements. After that, the EOS-07/MHS measurements are used to construct the diurnal variation of humidity during the active phases of the Indian summer monsoon. The observations are consistent with the present understanding of the Indian summer monsoon system. The present results are very encouraging and demonstrate the great potential of EOS-07/MHS observations of humidity for meteorological application, especially in understanding the hydrological cycle.

New characteristics of Meiyu precipitation changes in the middle and lower reaches of the Yangtze River since 2000

This study comprehensively analyzed the long-term changes of Meiyu in the middle and lower reaches of the Yangtze River with regard to precipitation, precipitation threshold, and interdecadal changes in atmospheric circulation. Results revealed obvious new features of Meiyu precipitation since 2000. (1) Meiyu precipitation shows a significant linear increase trend, with an average increment of 73.5 mm every 10 years. The increase in torrential rain is the most significant, accounting for 61% of the total precipitation increase, and its proportion has been increasing, while the proportions of light, moderate, and heavy rain in the total precipitation have been decreasing. (2) At the interdecadal scale, Meiyu precipitation and the local surface average temperature show opposite changes. Meiyu precipitation decreases by approximately 150 mm for every 1°C increase in the average temperature. This inverse correlation was not evident before 2000. (3) The saturated specific humidity in this area shows a significant increasing trend, indicating that precipitation in this area is caused by a higher threshold of atmospheric saturation and condensation, which may be a reason for the low Meiyu precipitation during high-temperature years. (4) The main atmospheric circulation in East Asia associated with Meiyu shows clear interdecadal changes, including the Western North Pacific Subtropical High and South Asian High having become significantly stronger and having extended westward and eastward, respectively, thereby facilitating the occurrence and persistence of Meiyu precipitation. The atmospheric circulation patterns associated with Meiyu, such as the Western North Pacific Subtropical High and South Asian High, have more significant impacts on Meiyu precipitation.

Evaluation of the retrieved temperature and specific humidity from COSMIC-2 and FY-3D with Radiosonde, reanalysis data, and MetOp

The Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), as the follow-on mission to COSMIC, commenced observations from 25 June 2019. COSMIC-2, with its high signal-to-noise ratio (SNR) and excellent stability, is expected to outperform COSMIC in detecting atmospheric parameters while penetrating the lower atmosphere.Therefore, to verify and analyze the detection capability of COSMIC-2 occultation in the neutral atmosphere, we retrieved temperature and specific humidity from COSMIC-2 and FY-3D based on the Able integral and the one-dimensional variational method. The evaluations are carried out on retrieval parameters at different altitudes using official RO products, radiosonde, reanalysis data, and MetOp. A detailed analysis of errors in the evaluation process is provided. The RMSEs for COSMIC-2 temperature and specific humidity are less than 1.5 K and 36 % respectively when radiosonde as validation data. Compared to FY-3D, accuracy improved by 11.1 % and 18.5 % respectively. FY-3D shows better consistency in the evaluation of the RO official products and radiosonde. Temporal and spatial analysis reveals minimal seasonal differences but significant latitude influence on evaluation outcomes. In the evaluation of reanalysis data, COSMIC-2 temperature and NCEP performed well in the troposphere, with a correlation coefficient greater than 0.9. The RMSE of the COSMIC-2 temperature and specific humidity in the MERRA-2 evaluation increased by 50.59 % and 16.65 % over FY-3D. Besides, derived parameters are more consistent with MetOp than radiosonde. Moreover, the co-localization threshold and resampling have less than 0.1 K and 5 % impact on the accuracy of evaluating temperature and specific humidity.

Modeling Climate Characteristics of Qinghai Lake Ice in 1979–2017 by a Quasi-Steady Model

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons.

Revisiting two indices measuring high‐frequency daily variability

AbstractHigh‐frequency daily variability (HFDV), as a fundamental aspect of climate variability, has drawn increasing attention due to its crucial impacts on public health, regional ecosystems and economic growth rates. The statistical metrics are of great importance to measure the changes in HFDV. In this study, we compared two common statistical metrics of monthly HFDV, including the standard deviation (SD) and the day‐to‐day difference (DTDx), for various variables (temperature, specific humidity and horizontal wind) using the NCEP/NCAR reanalysis dataset. Here, we show that the SD of daily variables includes mainly sub‐semiannual variability (<180 days), while DTDx can separate the synoptic variability (<12 days, DTD1), submonthly variability (<25 days, DTD3) and subseasonal variability (<60 days, DTD5) from other temporal scales. Moreover, a wider dominant timescale of DTDx causes a higher climatological mean and a closer relationship with SD. We also find that the linear trend in SD exhibits remarkable differences from that of the DTDx nearly all over the world, which can be explained by the significant change in the autocorrelation with different lag days under climate change. Our findings highlight that the DTDx is superior to SD in measuring HFDV, especially in a changing climate.

Deciphering multi-temporal scale dynamics in the concentration, sources and processes of near surface ozone over different climatic regions of India.

This study aims to investigate the factors influencing seasonal and long-term (2003-2021) changes in the near surface ozone (850 hpa) concentrations over different climatic sub-regions of India. Detailed comparison of daily (2019-2021) near surface ozone values of ERA-5 and CAAQMS (Continuous Ambient Air Quality Monitoring Stations) ground-based measurements revealed that ERA-5 is temporally in phase with CAAQMS measurements falling indifferent climatic sub-regions of India. ERA-5 near surface ozone shows statistically significant long-term (2003-2021) positive trends [2-4 percent per decade (ppd)] over most of the climatic sub-regions, over Indo-Gangetic Planes (IGPs), Southern and Central India trends are particularly strong. Trends were also estimated for each season separately, which were largely positive (2-6 ppd) over Central and Southern India in the Autumn and Winter seasons. Extensive climatological analysis reveals that the reversal of winds in the Indian monsoonal system plays a vital role in such trend patterns across the Indian subcontinent. South-westerly winds from June through September presumably bring ozone deficit air of marine origin, thus causing a dilution effect while the North-easterly winds during late Autumn and early Winters plausibly bring ozone-rich air from the stratospheric-tropospheric efflux dominated Himalayan region. It allows near surface ozone enhancement over Central and Southern India. Seasonal Principal component analysis (PCA) revealed that precursor gases (CH4 and NO2) and climatic variables especially specific humidity (SH) are the primary drivers of near surface ozone variability in the Winter season, while in Spring, climatic variables like boundary layer height (BLH), temperature (T) and SH have a significant role. Principal component regression (PCR) reveals a long-term increase in near surface ozone levels mostly dominated by precursor concentration over IGPs and Southern sub-regions. Whereas, BLH, T and SH significantly explain near surface ozone trends over North-eastern and Coastal India.

Microphysical Characteristics of Precipitation Over Eastern China and Its Coastal Regions

AbstractMany studies have investigated the macro‐ and micro‐physical properties of precipitation, but few classified precipitation into warm‐ and cold‐topped, which affects precipitation phase and precipitation type significantly. Furthermore, the impact of moisture and dynamics on microphysical characteristics of precipitation has been less studied. Using precipitation data from the GPM 2A DPR between May and September from 2015 to 2023, this study conducts a systematic study on microphysical characteristics of precipitation over eastern China and its coastal areas. This study divides precipitation cases into 20 categories, including warm‐/cold‐topped (CTP/WTP) convective/stratiform light/moderate/heavy/extreme/the most extreme precipitation. The findings reveal distinct differences along with similarities in various precipitation categories between eastern China and its coastal regions. The convection ratio for CTP increases with higher precipitation intensity, while WTP is dominated by convective precipitation. The more CTP, the higher the solid water content. The heavier precipitation, the higher liquid water content contributes. The mass‐weighted diameter (Dm) for CTP shows three variations from high to low with little or slight decrease with altitude at upper‐layer, followed by a rapid increase at middle‐layer and finally decreasing slightly at low‐layer. The CTP Dm grows rapidly with temperature from −18.58 (−13.93)°C for convective (stratiform) precipitation and their maximum growth rate are almost located in melting layer. Dm (raindrop density) is larger (lower) over land than ocean and larger (lower) for CTP than WTP. Dm shows positive relation to vertical velocity and specific humidity, especially sensitive to the middle‐ and upper‐layers meteorological conditions.