Hasil untuk "Meteorology. Climatology"

K. Knapp, M. Kruk, D. Levinson et al.

H. Christian, R. Blakeslee, D. Boccippio et al.

JaSOn, a., Otkin et al.

Pauline A. Simon, Christopher H. K. Chen, Mathew J. Owens et al.

Forecasting multiscale properties of the solar wind is one of the important aspects of space weather prediction as mesoscales, larger than one minute, can affect the magnetosphere. Amongst forecasting techniques, the Analog Ensemble (AnEn) method allows the forecast of a quantity from its past behavior, is easy and quick to implement, and results in an ensemble of time series. A comparison of optimal AnEn forecasts of \textit{Wind} spacecraft observations of near-Earth solar wind properties with the persistence and climatology baselines allows a quantification of the predictability of the magnetic and velocity components and magnitude. The AnEn predictions were found to be as accurate as persistence for short-term forecasts and climatology for long-term ones, and performed better than both baselines for more than 60\% of the samples for a particular lead time. Furthermore, using an AnEn instead of the baselines enables prediction of the full spectrum of solar wind fluctuations. However, using the standard averaging method to generate a unique forecast from the AnEn ensemble results in a loss of power in the small-scale fluctuations. To prevent this loss, a new spectral reduction method is proposed and compared to the standard averaging method as well as the synodic recurrence baseline. The AnEn spectral-reduced forecast is shown to be more time-accurate than the synodic baseline and more frequency-accurate than the mean-reduced forecasts. Such a reduced forecast is then confirmed to be useful as a comparative baseline in performance diagnostics of space weather models.

Ioannis Prapas, Nikolaos Papadopoulos, Nikolaos-Ioannis Bountos et al.

Forecasting wildfires weeks to months in advance is difficult, yet crucial for planning fuel treatments and allocating resources. While short-term predictions typically rely on local weather conditions, long-term forecasting requires accounting for the Earth's interconnectedness, including global patterns and teleconnections. We introduce TeleViT, a Teleconnection-aware Vision Transformer that integrates (i) fine-scale local fire drivers, (ii) coarsened global fields, and (iii) teleconnection indices. This multi-scale fusion is achieved through an asymmetric tokenization strategy that produces heterogeneous tokens processed jointly by a transformer encoder, followed by a decoder that preserves spatial structure by mapping local tokens to their corresponding prediction patches. Using the global SeasFire dataset (2001-2021, 8-day resolution), TeleViT improves AUPRC performance over U-Net++, ViT, and climatology across all lead times, including horizons up to four months. At zero lead, TeleViT with indices and global inputs reaches AUPRC 0.630 (ViT 0.617, U-Net 0.620), at 16x8day lead (around 4 months), TeleViT variants using global input maintain 0.601-0.603 (ViT 0.582, U-Net 0.578), while surpassing the climatology (0.572) at all lead times. Regional results show the highest skill in seasonally consistent fire regimes, such as African savannas, and lower skill in boreal and arid regions. Attention and attribution analyses indicate that predictions rely mainly on local tokens, with global fields and indices contributing coarse contextual information. These findings suggest that architectures explicitly encoding large-scale Earth-system context can extend wildfire predictability on subseasonal-to-seasonal timescales.

Sunil N. Oulkar, Parmanand Sharma, Bhanu Pratap et al.

Glacier and snow melt are the primary sources of water for streams, and rivers in upper Indus region of the western Himalaya. However, the magnitude of runoff from this glacierized basin is expected to vary with the available energy in the catchment. Here, we used a physically based energy balance model to estimate the surface energy and surface mass balance (SMB) of the upper Chandra Basin glaciers for 7 hydrological years from 2015 to 2022. A strong seasonality is observed, with net radiation being the dominant energy flux in the summer, while latent and sensible heat flux dominated in the winter. The estimated mean annual SMB of the upper Chandra Basin glaciers is −0.51 ± 0.28 m w.e. a−1, with a cumulative SMB of −3.54 m w.e during 7 years from 2015 to 2022. We find that the geographical factors like aspect, slope, size and elevation of the glacier contribute towards the spatial variability of SMB within the study region. The findings reveal that a 42% increase in precipitation is necessary to counteract the additional mass loss resulting from a 1°C increase in air temperature for the upper Chandra Basin glaciers.

Jingyi YANG, Wenshou TIAN, Jiali LUO et al.

Tropospheric ozone is an important air pollutant and greenhouse gas.It is harmful to human health and seriously harm the ecological environment.In this study， we use ozonesondes data from WOUDC （World Ozone and Ultraviolet Radiation Data Centre） during 2007 -2018 to evaluate tropospheric ozone column products from GOME-2A （Global Ozone Monitoring Experiment 2 aboard METOP-A） and Ozone Monitoring Instrument （OMI） satellite， as well as tropospheric ozone products from Updated Tropospheric Chemistry Reanalysis （TCR-2）.The results of the analysis show that in the equatorial American， subtropical， western European and Canadian regions， the correlation coefficients between GOME-2A and ozonesondes observations are up to 0.56， and the absolute values of the relative percentage deviations do not exceed 15%； in the eastern US.and western European regions， the correlation coefficients between OMI and ozonesondes observations are 0.65~0.72， and the standardized root-mean-square errors are 0.47~0.56； for the whole Northern Hemisphere region， the correlation coefficients between the TCR-2 tropospheric ozone column content and ozonesondes observations are 0.41~0.95， with standardized root-mean-square errors （RMSEs） of 0.18~0.48， which are better than the other two satellite data.Furthermore， the results indicate that the TCR-2 tropospheric ozone column trend is consistent with the trend direction of the ozonesondes observations.Through a more robust data assessment， it is evident that tropospheric ozone columns have increased in the equatorial Americas， Western Europe and China.Conversely， there has been a decrease in tropospheric ozone columns in the Arctic， Canada and the eastern United States.

Poulomi Ganguli, Ning Lin

Abstract The eastern coast of India is a hotspot of both heatwaves and tropical cyclones (TCs). However, the potential for TCs to trigger or contribute to subsequent humid heatwaves over land (HHLs) remains unexplored. We assess compound interactions between marine heatwaves (MHWs), landfalling TCs, and HHLs during 1982–2023 at the Bay of Bengal (BoB), considering 33 urban and peri-urban sites within 200 km of coastline. HHLs at these sites demonstrate a significant upward trend, increasing from ~2 events/year in 1982−1991 to 6 events/year in 2014−2023. In contrast, TC-compounded HHLs—comprising 17% HHLs—maintain a stable frequency of ~1.4 events/year. In half of these compound extremes, HHLs follow TCs, often with ~8% higher HHL magnitudes within 5 days of landfall compared to uncompounded HHLs, especially for coastal sites. During the post-monsoon season, 33% of at-site record HHLs follow TCs, with record compounded HHL magnitudes exceeding up to 14% of record uncompounded HHL magnitudes. Meanwhile, over broad ocean areas, MHWs precondition up to 50% of TCs, and strong MHWs precondition up to 33% of rapidly intensified (RI) TCs; for the study sites, up to 50% of RI TCs are followed by HHLs. TC-heat compounding in the BoB—largely affected by MHW−TC−HHL event chains—occurs at rates (identified using seasonally varying thresholds) that notably exceed the previously reported global averages based on fixed thresholds.

Xiang-Yu Li, Hailong Wang, TC Chakraborty et al.

Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projections. Among many challenges of understanding ACI, the question of whether ACI is deterministic or stochastic has not been explicitly formulated and asked. Here we attempt to answer this question by predicting cloud droplet number concentration Nc from aerosol number concentration Na and ambient conditions. We use aerosol properties, vertical velocity fluctuation w', and meteorological states (temperature T and water vapor mixing ratio q_v) from the ACTIVATE field observations (2020 to 2022) as predictor variables to estimate Nc. We show that the climatological Nc can be successfully predicted using a machine learning model despite the strongly nonlinear and multi-scale nature of ACI. However, the observation-trained machine learning model fails to predict Nc in individual cases while it successfully predicts Nc of randomly selected data points that cover a broad spatiotemporal scale, suggesting the stochastic nature of ACI at fine spatiotemporal scales.

Danlei Jian, Haikun Zhao, Min Liu et al.

As the most significant interannual signal in the tropical Pacific, the influence of ENSO on the interannual variability in TC genesis location in the western North Pacific (WNP) has received much attention in previous studies. This paper mainly emphasizes the underlying SST factors independent of the ENSO signal and explores how they modulate interannual tropical cyclone genesis (TCG) latitude variability. Our study finds that the meridional sea temperature gradient (SSTG) between the Kuroshio Extension and the WNP still has a significant effect on the interannual variability in the TCG latitude after removing the effect of ENSO (r = 0.6). The interannual forecasts of the TCG latitude were effectively improved from 0.67 to 0.81 when the ENSO-independent SSTG and ENSO were regressed together in a multi-linear regression. We then propose an ENSO-independent physical mechanism affecting the TCG latitude. The equatorward (poleward) SSTG excited the positive (negative) Pacific–Japan telecorrelation pattern over the WNP, forming Rossby wave trains and propagating northward. A significant cyclonic vortex (anticyclonic vortex) with strong convective development (suppression) developed near 20° N, leading more TCs to the northern (southern) part of the WNP. These findings provide a new perspective for the prediction of the interannual variability in the TCG latitude.

S. Sindhu, Chaithanya D. Jain, M. Venkat Ratnam et al.

Volatile Organic Compounds (VOCs) serve as precursors for tropospheric ozone (O3) and Secondary Organic Aerosol (SOA) formation. The formation of O3 and SOA are the indicators of the oxidative capacity specific to a given chemical environment. The current study investigates the oxidative capacity of the relatively less explored tropical rural atmosphere. This study is accomplished by measuring the concentrations of various VOCs and combining them with OH loss rates to estimate the potentials for O3 and SOA formation (OFP and SOAP, respectively). Continuous diel VOC measurement data from Gadanki (13.5°N, 79.2°E), Peninsular India, encompassing four distinct seasons and comprising over 4000 samples, have been utilized to estimate OFP and SOAP and their variations across different seasons. Additionally, efforts have been made to comprehend the contribution of different VOC sources to O3 and SOA formation. The results indicate that, 1, 3, 6-trimethyl benzene (20.09 %) among the VOCs and aromatics (44.37%) among the VOC groups exhibit the highest OFP at the observational site. Among seasons, the post-monsoon period exhibits the highest OFP (31.94%). The increased presence of biogenic VOCs, such as ethylene, propylene, and 1-butene during monsoon, likely due to the increased vegetation cover can be attributed for the elevated OFP. Similarly, n-dodecane (43.22%) and the VOC group of alkanes (50.79%) show the highest SOAP. The summer season has the highest SOAP (29.7%), owing to the enhanced concentrations and photochemistry initiated by OH radicals. Within the PMF-modelled sources, biomass-burning VOCs make a substantial contribution to both OFP and SOAP, distinguishing the rural atmosphere from its urban counterpart, where traffic emissions predominantly influence OFP and SOAP.

Eric W. Uhlhorn, Suz Tolwinski-Ward, Sylvie Lorsolo

Abstract A new parametric model of a tropical cyclone’s (TC) surface wind field is proposed, in which parameters are calibrated on over 20 years of direct surface wind measurements from aircraft reconnaissance. The model extends previous formulations by representing structural asymmetries in the inner core and far field. The surface wind representation eliminates the need for uncertain aircraft flight (gradient) level-to-surface extrapolation or pressure gradient formulation conversions to wind speed. Parameters are expanded to wavenumber-1 asymmetric Fourier components around symmetric mean values; symmetric values are found to depend primarily on maximum wind speed and geographic location, while some asymmetric parameters show statistically significant relationships with motion and environmental vertical shear, consistent with recent studies. Finally, a probabilistic representation of the climatology of basin-wide TC wind field structure is constructed by fitting a multivariate statistical distribution to the optimized model parameters. The low-dimensional formulation is suitable for computationally efficient reconstruction of historical TC wind fields, from depression to Saffir–Simpson category-5 intensities, as well as for stochastic simulation in the context of catastrophe risk modeling.

Konstantinos Moustris, Nastos Panagiotis

Monique Silva Coelho, Daniel Constantino Zacharias, Tayná Silva de Paulo et al.

In the second quarter of 2021, the companies at the Capuava Petrochemical Complex (CPC, Santo André, Brazil) carried out a 50-day scheduled shutdown for the maintenance and installation of new industrial equipment. This process resulted in severe uncontrolled emissions of particulate matter (PM) and volatile organic compounds (VOCs) in a densely populated residential area (~3400 inhabitants/km²). VOCs can be emitted directly into the atmosphere in urban areas by vehicle exhausts, fuel evaporation, solvent use, emissions of natural gas, and industrial processes. PM is emitted by vehicle exhausts, mainly those powered by diesel, industrial processes, and re-suspended soil dust, in addition to that produced in the atmosphere by photochemical reactions. Our statistical analyses compared the previous (2017–2020) and subsequent (2021–2022) periods from this episode (April–May 2021) from the official air quality monitoring network of the PM₁₀, benzene, and toluene hourly data to improve the proportion of this period of uncontrolled emissions. Near-field simulations were also performed to evaluate the dispersion of pollutants of industrial origin, applying the Gaussian plume model AERMOD (steady-state plume model), estimating the concentrations of VOC and particulate matter (PM₁₀) in which the population was exposed in the region surrounding the CPC. The results comparing the four previous years showed an increase in the mean concentrations by a factor of 2 for PM₁₀, benzene, and toluene, reaching maximum values during the episode of 174 µg m⁻³ (PM₁₀), 79.1 µg m⁻³ (benzene), and 58.7 µg m⁻³ (toluene). Meanwhile, these higher concentrations continued to be observed after the episode, but their variation cannot be fully explained yet. However, it is worth highlighting that this corresponds to the post-pandemic period and the 2022 data also correspond to the period from January to June, that is, they do not represent the annual variation. A linear correlation indicated that CPC could have been responsible for more than 60% of benzene measured at the Capuava Air Quality Station (AQS). However, the PM₁₀ behavior was not fully explained by the model. AERMOD showed that the VOC plume had the potential to reach a large part of Mauá and Santo André municipalities, with the potential to affect the health of more than 1 million inhabitants.

Xiaodan Yang, Ying Bao, Zhenya Song et al.

Abstract The tendency of El Niño/Southern Oscillation (ENSO) events to peak during boreal winter is known as ENSO phase-locking, whose accurate simulation is essential for ENSO prediction. However, the simulated peaks of ENSO events usually occur outside boreal winter in state-of-the-art climate models. Based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) models, the model with a more reasonable diurnal amplitude (DA) in the sea surface temperature (SST) had a better simulation ability for ENSO phase-locking compared with other models. Further experiments based on the earth system model revealed that the DA is vital for ENSO phase-locking simulation primarily due to the spatial inhomogeneities in seasonal DA anomaly variations in ENSO years with positive/negative DA anomalies in the central equatorial Pacific and negative/positive in the western or eastern Pacific during El Niño/La Niña. Our findings indicate that DA simulation in climate models is crucial for resolving the long-standing failure associated with the ENSO phase-locking simulation accuracy.

Chunxiu Shao, Yonghe Liu

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall.

Itamar Karbi, Rei Chemke

Abstract Temperature anomalies considerably influence the regional climate and weather of the extratropics. By the end of this century, climate models project an intensification of synoptic temperature variability in the Southern Hemisphere mid-latitudes. This intensification, however, comprises temperature anomalies with various length scales and periods, which might respond differently to anthropogenic emissions. Here, we find a shift, in coming decades, towards spatially larger and less persistent temperature anomalies in the Southern Hemisphere mid-latitudes. A shift towards larger length scales is also found during regional extreme heat events. The shift in length scale and duration is found to stem from changes in the meridional heat flux of atmospheric perturbations. Our results emphasize the importance of investigating the length scale and period-dependent changes in the mid-latitude climate, to prevent masking the different impacts of various length scales and periods, and thus provide more accurate climate projections for the mid-latitudes.

Petros A. Belimezis, Nikolaos Hatzianastassiou, Maria Gavrouzou et al.

Sukanta Basu, Albert A. M. Holtslag

In this study, we utilize a novel approach to solve the Ekman equations for eddy viscosity profiles in the stable boundary layer. By doing so, a well-known expression for the stable boundary layer height by Zilitinkevich (Boundary-Layer Meteorology, 1972, Vol. 3, 141--145) is rediscovered.

Richard B. Alley, Nick Holschuh, Byron Parizek et al.

Glacier-bed characteristics that are poorly known and modeled are important in projected sea-level rise from ice-sheet changes under strong warming, especially in the Thwaites Glacier drainage of West Antarctica. Ocean warming may induce ice-shelf thinning or loss, or thinning of ice in estuarine zones, reducing backstress on grounded ice. Models indicate that, in response, more-nearly-plastic beds favor faster ice loss by causing larger flow acceleration, but more-nearly-viscous beds favor localized near-coastal thinning that could speed grounding-zone retreat into interior basins where marine-ice-sheet instability or cliff instability could develop and cause very rapid ice loss. Interpretation of available data indicates that the bed is spatially mosaicked, with both viscous and plastic regions. Flow against bedrock topography removes plastic lubricating tills, exposing bedrock that is eroded on up-glacier sides of obstacles to form moats with exposed bedrock tails extending downglacier adjacent to lee-side soft-till bedforms. Flow against topography also generates high-ice-pressure zones that prevent inflow of lubricating water over distances that scale with the obstacle size. Extending existing observations to sufficiently large regions, and developing models assimilating such data at the appropriate scale, present large, important research challenges that must be met to reliably project future forced sea-level rise.