Journal of Geophysical Research: Atmospheres最新文献

{"title":"Vehicle Non-Exhaust Emissions Significantly Contribute to Urban PM Pollution in New Energy Vehicles Era","authors":"Qijun Zhang,&nbsp;Tiange Fang,&nbsp;Jiawei Yin,&nbsp;Zhengyu Men,&nbsp;Jianfei Peng,&nbsp;Lin Wu,&nbsp;Hongjun Mao","doi":"10.1029/2024JD042126","DOIUrl":"https://doi.org/10.1029/2024JD042126","url":null,"abstract":"<p>The non-exhaust emissions of motor vehicles derived from brake and tire wear have caused great concern, thereby requiring an investigation of their impact on air quality. We develop a high-resolution vehicle non-exhaust emissions inventory for Tianjin City based on detailed link-level traffic profiles and localized emission factors. We conduct atmospheric simulations of ambient particulate matter (PM) concentrations contributed by vehicle non-exhaust emissions. The results show that brake and tire wear emissions surpassed exhaust emissions for the first time in 2013 (PM_2.5). Areas with high emission intensities are primarily concentrated in central urban areas with high human activity and population and motor vehicle density. Local vehicle non-exhaust emissions can be responsible for approximately 3% of the urban PM concentrations, and may reach 7.13% in some time periods. In the future, controlling vehicle non-exhaust emissions will effectively alleviate urban PM pollution during the new energy vehicles era.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Robust Method for Calculating Carbon Dioxide Emissions From Cities and Power Stations Using OCO-2 and S5P/TROPOMI Observations","authors":"Janne Hakkarainen,&nbsp;Iolanda Ialongo,&nbsp;Tomohiro Oda,&nbsp;David Crisp","doi":"10.1029/2025JD043358","DOIUrl":"https://doi.org/10.1029/2025JD043358","url":null,"abstract":"&lt;p&gt;We introduce a new method for calculating the carbon dioxide (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) emissions from point sources (e.g., power stations) and cities using the cross-sectional flux method constrained by space-based &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and nitrogen dioxide (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;NO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{NO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) observations. First, we derive a proxy estimate for &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; enhancements from &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;NO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{NO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; observations through linear regression near the plume cross-section. Then, we fit a Gaussian function to the resulting &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;NO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{NO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;-based &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; enhancement data. We apply this method to data from the Orbiting Carbon Observatory-2 (OCO-2) and the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (S5P/TROPOMI) starting from May 2018. The method is tested on the Matimba and Medupi power stations in South Africa, as well as the ci","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025JD043358","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Temperature Forecasting Incrementally Improved by Model Output Statistics","authors":"Tongtiegang Zhao,&nbsp;Zeqing Huang,&nbsp;Xiaohong Chen,&nbsp;Hao Wang","doi":"10.1029/2024JD042461","DOIUrl":"https://doi.org/10.1029/2024JD042461","url":null,"abstract":"<p>Skillful global temperature forecasting is crucial for mitigating the escalating impacts of rising temperature on human society and natural ecosystems. While global climate models generate invaluable dynamical temperature forecasts, the crucial role of model output statistics (MOS) in enhancing forecast skill has not been thoroughly investigated. This paper aims to unravel the potential of MOS methods for improving global temperature forecasts. It is achieved by developing a MOS toolkit to iteratively incorporate the attributes of bias, spread, trend, and association into forecast post-processing, resulting in a series of methodical one-factor-at-a-time experiments. A case study is devised for monthly forecasts of July 2-m air temperature (T2m) over land and sea surface temperature (SST) generated by the National Center for Environmental Prediction's Climate Forecast System version 2. The results expose the detrimental impacts of biases and unreliable ensemble spreads within raw temperature forecasts. At the lead time of 0 months, the continuous ranked probability skill score (CRPSS) is −128.51 ± 252.46% for T2m over land and 7.72 ± 76.66% for SST over ocean, indicating considerable underperformance of raw forecasts against reference climatological forecasts across numerous grid cells. The incremental considerations of bias, spread, trend, and association of the MOS methods result in substantial skill enhancements across global land and marine grid cells. Notably, the CRPSS of T2m is improved to 21.00 ± 23.63% and the SST forecast skill is improved to 42.26 ± 22.43%. Despite the anticipated degradation of skill with lead time, the results underscore MOS's efficacy in exploiting the information of raw forecasts to generate skillful temperature forecasts.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduction in Global Lightning Activity During the COVID Pandemic","authors":"Yakun Liu,&nbsp;Earle Williams,&nbsp;Anirban Guha,&nbsp;Gabriella Satori,&nbsp;Osmar Pinto Neto,&nbsp;Ryan Said,&nbsp;Robert Holzworth,&nbsp;Katrina Virts,&nbsp;Timothy Lang,&nbsp;Yanan Zhu,&nbsp;Jeff LaPierre,&nbsp;Elizabeth DiGangi","doi":"10.1029/2024JD042319","DOIUrl":"https://doi.org/10.1029/2024JD042319","url":null,"abstract":"<p>The effect of anthropogenic aerosols on lightning is one of the least understood aspects of human-induced climate change. Global aerosol clearly diminished during the COVID pandemic by 7.6%. A pronounced decrease in global lightning activity in the range 3.0%–5.8% is identified from various detection systems during this natural experiment. The Maritime Continent lightning chimney shows the largest reduction of 7.0% in aerosol accompanied by a lightning drop of 15%. The COVID period in 2020 also experiences a transition from pre-COVID El Niño to a strong and sustained La Niña. Compensation for ENSO forcing of lightning activity is implemented to disclose the distinct responses of three global lightning chimneys to competing thermodynamic and aerosol effects. Our observational findings indicate a marked influence of aerosol on a global scale by virtue of the extraordinary COVID-induced aerosol alteration.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JD042319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Large-Scale Topography Surrounding the Sichuan Basin on Its Regional Hourly Extreme Precipitation in Summer Under Specific Weather Patterns: Multi-Case Study","authors":"Xiaoke Xu,&nbsp;Anning Huang,&nbsp;Yan Zhang,&nbsp;Xianyu Yang,&nbsp;Wei Zhao","doi":"10.1029/2024JD042239","DOIUrl":"https://doi.org/10.1029/2024JD042239","url":null,"abstract":"<p>The influence mechanism of large-scale topography surrounding the Sichuan Basin (SCB) on its precipitation under two dominant weather patterns that typically trigger the regional hourly extreme precipitation events (RHEPEs) in summer remains unclear. Based on multi-case simulations, this study revealed how the Tibetan Plateau (TP) and Yunnan–Guizhou Plateau (YGP) affect the precipitation over SCB under different dominant weather patterns of RHEPEs in summer through sensitivity experiments. Results show that under the weather pattern featured by a low-level vortex (LLV) over western SCB with water vapor transport by southerly winds, the YGP and TP can increase the precipitation in western SCB by 86% and 46%, respectively. The large-scale terrains of TP and YGP tend to enhance the thermal gradient between the plateau and basin and shape the windward slope over western SCB, accounting for increased precipitation there. Under the weather pattern featured by a LLV over central and eastern SCB with southwesterly winds, the TP can only increase the precipitation in the eastern SCB by 20% due to its limited effects on the atmospheric circulations along the windward slope there, however, the YGP can decrease the precipitation in eastern SCB by 26%, which is attributed to the anomalous northeasterly winds weakening the water vapor transport from the Bay of Bengal, leading to the strengthened stability of stratification and weakened dynamic uplifting along the windward slope in eastern SCB. Finding of this study provides a new perspective on the mechanisms of large-scale terrain influencing the RHEPEs over SCB.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143884120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air Temperature Trends and Extreme Warming Events Across Regions of Antarctica for the Period 2003–2021","authors":"Eva Bendix Nielsen,&nbsp;Marwan Katurji,&nbsp;Peyman Zawar-Reza,&nbsp;Nicolas Cullen","doi":"10.1029/2024JD043042","DOIUrl":"https://doi.org/10.1029/2024JD043042","url":null,"abstract":"&lt;p&gt;We have characterized the magnitude and spatial extent of observed regional and inter-regional air temperature trends and warming extremes across Antarctica. Prior studies have used localized observational records to analyze air temperature trends across distinct geographical regions, leaving local and inter-regional variations to be undetected. Using the high-resolution temperature product AntAir ICE, air temperature trends and extreme warming events were identified across Antarctica for the period 2003–2021. Unsupervised clustering was applied to austral summer and annual mean air temperature trends to divide Antarctica into 12 regions exhibiting similarity in temperature trends. Our results show a significant annual mean cooling trend of ‒&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0.12&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mfrac&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;°&lt;/mo&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mtext&gt;Yr&lt;/mtext&gt;\u0000 &lt;/mfrac&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $0.12,sfrac{{}^{circ}mathrm{C}}{text{Yr}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; for the terrestrial Antarctic Peninsula, and an austral summer (annual) warming trend of +&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0.08&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mfrac&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;°&lt;/mo&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mtext&gt;Yr&lt;/mtext&gt;\u0000 &lt;/mfrac&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $0.08,sfrac{{}^{circ}mathrm{C}}{text{Yr}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; (+&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0.07&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mfrac&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;°&lt;/mo&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mtext&gt;Yr&lt;/mtext&gt;\u0000 &lt;/mfrac&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $0.07,sfrac{{}^{circ}mathrm{C}}{text{Yr}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) in the Ross Sea region's Victoria Land and Transantarctic Mountains. The spatial extent of each of the 12 clusters' extreme air temperature events was mapped in austral summer revealing that West Antarctica has spatially confined events, while East Antarctica events are widespread. ERA5 data indicate that West Antarctica's extreme air temperature events are associated with consistent meridional atmospheric flows. Local to regional extreme warming events in East Antarctica are associated with inland high-pressure systems, which enhance katabatic","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JD043042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanisms of Persistent Extreme Rainfall Event in North China, July 2023: Role of Atmospheric Diabatic Heating","authors":"Wei Zhao,&nbsp;Shangfeng Chen,&nbsp;Xiadong An,&nbsp;Renguang Wu,&nbsp;Wen Chen,&nbsp;Fanghua Zhang,&nbsp;Yuli Zhang,&nbsp;Lu Yang,&nbsp;Linye Song,&nbsp;Leying Wang","doi":"10.1029/2024JD042717","DOIUrl":"https://doi.org/10.1029/2024JD042717","url":null,"abstract":"<p>During 29th July–1st August in 2023, a persistent heavy rainfall event (“23·7” event) hit North China causing severe floods, enormous infrastructure damage, and large economy loss. Observational analysis shows that the extremely large accumulation of precipitation and long duration of this event are closely related to a slowly moving landfall typhoon “Dusuari” over North China due to the blocking effect of an anomalous high over the mid-high latitude Asia. The anomalous southeasterly flow induced by the typhoon “Dusuari” and another typhoon “Khanun” over the East China Sea jointly built a highly efficient channel of water vapor supply from southern oceans toward North China. A water vapor budget analysis indicates that precipitation of this event is mainly caused by the dynamic process involving strong ascending motion. Accompanying strong water vapor transportation and convergence over North China, large amount of latent heat is released in the middle and the lower troposphere. The physical mechanisms of heavy rainfall-induced diabatic heating in maintaining the precipitation over North China is further investigated using statistical analysis and numerical experiments. On one hand, the latent heating released by heavy rainfall induces significant uplifting flows which causes more precipitation. On the other hand, the heavy rainfall-induced diabatic heating contributes to the enhancement of the westward extension of high-pressure dam over mid-high latitude through a regional meridional circulation. This strengthened high-pressure dam sustained the cyclonic circulation of “Dusuari” over North China, leading to continuous heavy rainfall there.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Summer Mesoscale Convective Systems in Convection-Permitting Simulation Using WRF Over East China","authors":"Yutong Lu,&nbsp;J. H. Marsham,&nbsp;Jianping Tang,&nbsp;D. J. Parker,&nbsp;Juan Fang","doi":"10.1029/2025JD043653","DOIUrl":"https://doi.org/10.1029/2025JD043653","url":null,"abstract":"<p>Mesoscale convective systems (MCSs) are active precipitation systems in East China. The increasing frequency and intensity of MCSs highlight the need for better simulation and forecasting. This study conducted a 22-year (2000–2021) JJA simulation at a CP resolution (4-km grid spacing) using the WRF model (WRF-CPM) over East China. The WRF-CPM model's ability to reproduce MCSs was evaluated against satellite infrared-retrieved cloud top temperature, IMERG V06 precipitation, and global reanalysis data ERA5. Results show that WRF-CPM captures the observed MCS frequency and precipitation patterns but overestimates them in most areas, which might be related to the overestimated moisture and CAPE. The model also reproduces the eastward propagation of MCSs, albeit at a slightly faster speed and longer duration. MCSs in WRF-CPM exhibits realistic life cycles in terms of cloud top temperature, convective core area, and precipitation. WRF-CPM tends to overestimate rainfall frequency over 20 mm/hr while underestimates rainfall per MCS, possibly due to an overestimated number and area. The model captures the diurnal cycle of MCSs well in most of East China, though it shows a 2-hr delay in southeast China and produces the peak a few hours earlier to the east of Tibetan Plateau. Total column water vapor (TCWV) and wind shear are well-established factors controlling MCS behavior and rainfall, yet capturing the effects remains a challenge for CP models. This study is the first to show that WRF-CPM can capture the shear effect on MCS precipitation, showing an increase in precipitation with stronger shear and higher TCWV.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Sensitivity of Land-Atmosphere Coupling to Soil Moisture Over the Tibetan Plateau Based on the Improved Noah-MP Model","authors":"Yaling Chen,&nbsp;Xianhong Meng,&nbsp;Lele Shu,&nbsp;Jun Wen,&nbsp;Zhaoguo Li,&nbsp;Hao Chen,&nbsp;Lin Zhao,&nbsp;Mingshan Deng,&nbsp;Xinyi Gu,&nbsp;Qiang Zhang","doi":"10.1029/2024JD042895","DOIUrl":"https://doi.org/10.1029/2024JD042895","url":null,"abstract":"<p>While land-atmosphere water-heat exchange critically influences climate variability and the water cycle, particularly in cold regions, it is inadequately comprehended due to insufficient observational data. This study aims to improve the performance of the community Noah land surface model with multiparameterization options (Noah-MP) model in water and heat transfer simulations and explore the sensitivity of regional land-atmosphere coupling to soil moisture over the Tibetan Plateau. The model is evaluated against data from eight eddy covariance sites, four soil temperature and moisture networks, and seven reanalysis products. Various sensibility tests are conducted, including the replacement of soil property, surface drag coefficient scheme, canopy stomatal resistance scheme, soil surface resistance scheme, and their different combinations. The results indicate that different schemes can improve certain aspects of model simulations. Specifically, the modified surface drag coefficient scheme reduces the overestimation in sensible heat flux by adjusting the surface heat exchange coefficient, while the improved stomatal and soil resistance schemes enhance latent heat flux and soil moisture simulations. The optimal combination significantly reduces average bias by 61.3% for the Bowen ratio, 9.6% for soil temperature, and 50.0% for soil moisture. Regional simulations demonstrate that sensible heat flux constitutes the primary constituent within the energy partitioning, characterized by a mean Bowen ratio of 1.84. In arid and semiarid zones, the Bowen ratios are 3.10 and 1.75, respectively, underscoring stronger surface energy exchange capacity over drier soil conditions.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration of the High-Resolution Common Land Model in Simulating the Soil Moisture Over the Northeastern China Using an Adaptive Parameter Learning Method","authors":"Luyao Yang,&nbsp;Jianduo Li,&nbsp;Yongjiu Dai,&nbsp;Xingjie Lu,&nbsp;Chaopeng Shen,&nbsp;Ping Zhao,&nbsp;Guo Zhang,&nbsp;Yanwu Zhang","doi":"10.1029/2024JD043230","DOIUrl":"https://doi.org/10.1029/2024JD043230","url":null,"abstract":"<p>The growing complexity of land surface models (LSMs) presents significant challenges for parameter calibration. Compared to traditional optimization algorithms, the deep learning-based optimization framework, namely differentiable parameter learning (dPL), reduces computational costs and achieves greater spatial generalizability. However, the effectiveness of the parameter values derived from dPL in enhancing land surface modeling needs further verification. This study introduced a deep learning-based adaptive parameter learning (APL) framework for efficiently optimizing key parameters in the Common Land Model (CoLM) to simulate high-resolution soil moisture (SM) across Northeast China. We began by constructing a surrogate model using long short-term memory networks to capture the relationships between CoLM parameters, meteorological forcing data, and simulated SM. Initial parameter optimization using the dPL framework improved SM simulations but revealed discrepancies between the performances of surrogate and process-based models. The APL framework builds upon dPL by iteratively refining surrogate models with expanded training data sets enhancing their ability to approximate the behavior of process-based models. Evaluations using four metrics—bias, root mean square error, correlation, and Kling–Gupta efficiency—demonstrated that APL outperformed dPL with both frameworks providing robust parameter estimates. This study underscored the potential of deep learning-based parameter optimization frameworks to overcome traditional calibration challenges in LSMs by improving computational efficiency, enhancing spatial consistency and increasing resilience to uncertainties in forcing and reference data. Finally, we recommended that improving physical coherence in LSMs should not rely solely on adjusting a few parameters but requires a comprehensive approach, including identifying key parameters, employing multiobjective parameter optimization, and, critically, utilizing high-precision land surface benchmarking data sets.</p>","PeriodicalId":15986,"journal":{"name":"Journal of Geophysical Research: Atmospheres","volume":"130 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}