Atmospheric & Oceanic Science Research Works

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Formerly known as the Department of Meteorology.


Recent Submissions

Now showing 1 - 20 of 34
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    A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations
    (MDPI, 2017-09-07) Zhang, Hengyue; Jin, Menglin S.; Leach, Martin
    The urban heat island effect (UHI) for inner land regions was investigated using satellite data, ground observations, and simulations with an Single-Layer Urban Canopy Parameterization (SLUCP) coupled into the regional Weather Research Forecasting model (WRF, Specifically, using the satellite-observed surface skin temperatures (Tskin), the intensity of the UHI was first compared for two inland cities (Xi’an City, China, and Oklahoma City (OKC)), which have different city populations and building densities. The larger population density and larger building density in Xi’an lead to a stronger skin-level UHI by 2 °C. However, the ground observed 2 m surface air temperature (Tair) observations showed an urban cooling island effect (UCI) over the downtown region in OKC during the daytime of 19 July 2003, from a DOE field campaign (Joint Urban 2003). To understand this contrast between satellite-based Tskin and ground-based Tair, a sensitivity study using WRF/SLUCP was analyzed. The model reproduced a UCI in OKC. Furthermore, WRF/Noah/SLUCM simulations were also compared with the Joint Urban 2003 ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLUCM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions, and energy fluxes reasonably well.
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    Assessing Coastal SMAP Surface Salinity Accuracy and Its Application to Monitoring Gulf of Maine Circulation Dynamics
    (MDPI, 2018-08-06) Grodsky, Semyon A.; Vandemark, Douglas; Feng, Hui
    Monitoring the cold and productive waters of the Gulf of Maine and their interactions with the nearby northwestern (NW) Atlantic shelf is important but challenging. Although remotely sensed sea surface temperature (SST), ocean color, and sea level have become routine, much of the water exchange physics is reflected in salinity fields. The recent invention of satellite salinity sensors, including the Soil Moisture Active Passive (SMAP) radiometer, opens new prospects in regional shelf studies. However, local sea surface salinity (SSS) retrieval is challenging due to both cold SST limiting salinity sensor sensitivity and proximity to land. For the NW Atlantic, our analysis shows that SMAP SSS is subject to an SST-dependent bias that is negative and amplifies in winter and early spring due to the SST-related drop in SMAP sensor sensitivity. On top of that, SMAP SSS is subject to a land contamination bias. The latter bias becomes noticeable and negative when the antenna land contamination factor (LC) exceeds 0.2%, and attains maximum negative values at LC = 0.4%. Coastward of LC = 0.5%, a significant positive land contamination bias in absolute SMAP SSS is evident. SST and land contamination bias components are seasonally dependent due to seasonal changes in SST/winds and terrestrial microwave properties. Fortunately, it is shown that SSS anomalies computed relative to a satellite SSS climatology can effectively remove such seasonal biases along with the real seasonal cycle. SMAP monthly SSS anomalies have sufficient accuracy and applicability to extend nearer to the coasts. They are used to examine the Gulf of Maine water inflow, which displayed important water intrusions in between Georges Banks and Nova Scotia in the winters of 2016/17 and 2017/18. Water intrusion patterns observed by SMAP are generally consistent with independent measurements from the European Soil Moisture Ocean Salinity (SMOS) mission. Circulation dynamics related to the 2016/2017 period and enhanced wind-driven Scotian Shelf transport into the Gulf of Maine are discussed.
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    Tidal Mixing Signatures in the Hong Kong Coastal Waters from Satellite-Derived Sea Surface Temperature
    (MDPI, 2018-12-20) Susanto, R. Dwi; Pan, Jiayi; Devlin, Adam T.
    Tidal mixing in the coastal waters of Hong Kong was investigated using a combination of in situ observations and high-resolution satellite-derived sea surface temperature (SST) data. An indicator of tide-induced mixing is a fortnightly (spring-neap cycle) signature in SST due to nonlinear interactions between the two principal diurnal and the two principal semi-diurnal tides. Both semi-diurnal and diurnal tides have strong tidal amplitudes and currents near Hong Kong. As a result, both the near-fortnightly (Mf) and fortnightly (MSf) tides are enhanced due to nonlinear tidal signal interactions. In addition, these fortnightly tidal signals are modulated by seasonal variability, with the maximum seasonal modulation of fortnightly tides occurring during the monsoon transition periods in May and October. The largest fortnightly signals are found in the southwestern part of the Pearl River estuary. Tidal constituent properties vary by space and depth, and high-resolution SST plays a pivotal role in resolving the spatial characteristics of tidal mixing.
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    Validation and Improvement of the WRF Building Environment Parametrization (BEP) Urban Scheme
    (MDPI, 2019-09-10) Gohil, Kanishk; Jin, Menglin S.
    The building environment parameterization scheme (BEP) is a built-in “urban physics” scheme in the weather research and forecasting (WRF) model. The urbanized College Park (CP) in Maryland state (MD) in the United States (US) covers an approximate land area of 14.8 km2 and has a population of 32,000 (reported by The United States Census Bureau, as of 2017). This study was an effort to validate and improve the BEP urban physics scheme for a small urban setting, College Park, MD. Comparing the WRF/BEP-simulated two-meter air temperatures with the local rooftop WeatherBug® observations and with the airport observations, systemic deficiencies in BEP for urban heat island effect simulation are evident. Specifically, WRF/BEP overestimates the two-meter air temperature by about 10 °F during clear summer nights and slightly underestimates it during noon of the same days by about 1–3 °F. Similar deficiencies in skin temperature simulations are also evident in WRF/BEP. Modification by adding an anthropogenic heat flux term resulted in better estimates for both skin and two-meter air temperatures on diurnal and seasonal scales.
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    Towards a Unified and Coherent Land Surface Temperature Earth System Data Record from Geostationary Satellites
    (MDPI, 2019-06-12) Pinker, Rachel T.; Ma, Yingtao; Chen, Wen; Hulley, Glynn; Borbas, Eva; Islam, Tanvir; Hain, Chris; Cawse-Nicholson, Kerry; Hook, Simon; Basara, Jeff
    Our objective is to develop a framework for deriving long term, consistent Land Surface Temperatures (LSTs) from Geostationary (GEO) satellites that is able to account for satellite sensor updates. Specifically, we use the Radiative Transfer for TOVS (RTTOV) model driven with Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) information and Combined ASTER and MODIS Emissivity over Land (CAMEL) products. We discuss the results from our comparison of the Geostationary Operational Environmental Satellite East (GOES-E) with the MODIS Land Surface Temperature and Emissivity (MOD11) products, as well as several independent sources of ground observations, for daytime and nighttime independently. Based on a six-year record at instantaneous time scale (2004–2009), most LST estimates are within one std from the mean observed value and the bias is under 1% of the mean. It was also shown that at several ground sites, the diurnal cycle of LST, as averaged over six years, is consistent with a similar record generated from satellite observations. Since the evaluation of the GOES-E LST estimates occurred at every hour, day and night, the data are well suited to address outstanding issues related to the temporal variability of LST, specifically, the diurnal cycle and the amplitude of the diurnal cycle, which are not well represented in LST retrievals form Low Earth Orbit (LEO) satellites.
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    The College Park, Maryland, Tornado of 24 September 2001
    (MDPI, 2019-10-22) Pryor, Kenneth L.; Wawrzyniak, Tyler; Zhang, Da-Lin
    The 24 September 2001 College Park, Maryland, tornado was a long-track and strong tornado that passed within a close range of two Doppler radars. It was the third in a series of three tornadoes associated with a supercell storm that developed in Stafford County, Virginia, and initiated 3–4 km southwest of College Park and dissipated near Columbia, Howard County. The supercell tracked approximately 120 km and lasted for about 126 min. This study presents a synoptic and mesoscale overview of favorable conditions and forcing mechanisms that resulted in the severe convective outbreak associated with the College Park tornado. The results show many critical elements of the tornadic event, including a negative-tilted upper-level trough over the Ohio Valley, a jet stream with moderate vertical shear, a low-level warm, moist tongue of the air associated with strong southerly flow over south-central Maryland and Virginia, and significantly increased convective available potential energy (CAPE) during the late afternoon hours. A possible role of the urban heat island effects from Washington, DC, in increasing CAPE for the development of the supercell is discussed. Satellite imagery reveals the banded convective morphology with high cloud tops associated with the supercell that produced the College Park tornado. Operational WSR-88D data exhibit a high reflectivity “debris ball” or tornadic debris signature (TDS) within the hook echo, the evolution of the parent storm from a supercell structure to a bow echo, and a tornado cyclone signature (TCS). Many of the mesoscale features could be captured by contemporary numerical model analyses. This study concludes with a discussion of the effectiveness of the coordinated use of satellite and radar observations in the operational environment of nowcasting severe convection.
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    Impact of Fire Emissions on U.S. Air Quality from 1997 to 2016–A Modeling Study in the Satellite Era
    (MDPI, 2020-03-12) Tao, Zhining; He, Hao; Sun, Chao; Tong, Daniel; Liang, Xin-Zhong
    A regional modeling system that integrates the state-of-the-art emissions processing (SMOKE), climate (CWRF), and air quality (CMAQ) models has been combined with satellite measurements of fire activities to assess the impact of fire emissions on the contiguous United States (CONUS) air quality during 1997–2016. The system realistically reproduced the spatiotemporal distributions of the observed meteorology and surface air quality, with a slight overestimate of surface ozone (O3) by ~4% and underestimate of surface PM2.5 by ~10%. The system simulation showed that the fire impacts on primary pollutants such as CO were generally confined to the fire source areas but its effects on secondary pollutants like O3 spread more broadly. The fire contribution to air quality varied greatly during 1997-2016 and occasionally accounted for more than 100 ppbv of monthly mean surface CO and over 20 µg m−3 of monthly mean PM2.5 in the Northwest U.S. and Northern California, two regions susceptible to frequent fires. Fire emissions also had implications on air quality compliance. From 1997 to 2016, fire emissions increased surface 8-hour O3 standard exceedances by 10% and 24-hour PM2.5 exceedances by 33% over CONUS.
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    Hygroscopicity of Different Types of Aerosol Particles: Case Studies Using Multi-Instrument Data in Megacity Beijing, China
    (MDPI, 2020-03-01) Wu, Tong; Li, Zhanqing; Chen, Jun; Wang, Yuying; Wu, Hao; Jin, Xiao'ai; Liang, Chen; Li, Shangze; Wang, Wei; Cribb, Maureen
    Water uptake by aerosol particles alters its light-scattering characteristics significantly. However, the hygroscopicities of different aerosol particles are not the same due to their different chemical and physical properties. Such differences are explored by making use of extensive measurements concerning aerosol optical and microphysical properties made during a field experiment from December 2018 to March 2019 in Beijing. The aerosol hygroscopic growth was captured by the aerosol optical characteristics obtained from micropulse lidar, aerosol chemical composition, and aerosol particle size distribution information from ground monitoring, together with conventional meteorological measurements. Aerosol hygroscopicity behaves rather distinctly for mineral dust coarse-mode aerosol (Case I) and non-dust fine-mode aerosol (Case II) in terms of the hygroscopic enhancement factor, 𝑓𝛽(𝑅𝐻,𝜆532), calculated for the same humidity range. The two types of aerosols were identified by applying the polarization lidar photometer networking method (POLIPHON). The hygroscopicity for non-dust aerosol was much higher than that for dust conditions with the 𝑓𝛽(𝑅𝐻,𝜆532) being around 1.4 and 3.1, respectively, at the relative humidity of 86% for the two cases identified in this study. To study the effect of dust particles on the hygroscopicity of the overall atmospheric aerosol, the two types of aerosols were identified and separated by applying the polarization lidar photometer networking method in Case I. The hygroscopic enhancement factor of separated non-dust fine-mode particles in Case I had been significantly strengthened, getting closer to that of the total aerosol in Case II. These results were verified by the hygroscopicity parameter, κ (Case I non-dust particles: 0.357 ± 0.024; Case II total: 0.344 ± 0.026), based on the chemical components obtained by an aerosol chemical speciation instrument, both of which showed strong hygroscopicity. It was found that non-dust fine-mode aerosol contributes more during hygroscopic growth and that non-hygroscopic mineral dust aerosol may reduce the total hygroscopicity per unit volume in Beijing.
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    Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging
    (MDPI, 2020-02-26) Noyes, Katherine Junghenn; Kahn, Ralph; Sedlacek, Arthur; Kleinman, Lawrence; Limbacher, James; Li, Zhanqing
    Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.
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    The Urban–Rural Heterogeneity of Air Pollution in 35 Metropolitan Regions across China
    (MDPI, 2020-07-19) Han, Wenchao; Li, Zhanqing; Guo, Jianping; Su, Tianning; Chen, Tianmeng; Wei, Jing; Cribb, Maureen
    Urbanization and air pollution are major anthropogenic impacts on Earth’s environment, weather, and climate. Each has been studied extensively, but their interactions have not. Urbanization leads to a dramatic variation in the spatial distribution of air pollution (fine particles) by altering surface properties and boundary-layer micrometeorology, but it remains unclear, especially between the centers and suburbs of metropolitan regions. Here, we investigated the spatial variation, or inhomogeneity, of air quality in urban and rural areas of 35 major metropolitan regions across China using four different long-term observational datasets from both ground-based and space-borne observations during the period 2001–2015. In general, air pollution in summer in urban areas is more serious than in rural areas. However, it is more homogeneously polluted, and also more severely polluted in winter than that in summer. Four factors are found to play roles in the spatial inhomogeneity of air pollution between urban and rural areas and their seasonal differences: (1) the urban–rural difference in emissions in summer is slightly larger than in winter; (2) urban structures have a more obvious association with the spatial distribution of aerosols in summer; (3) the wind speed, topography, and different reductions in the planetary boundary layer height from clean to polluted conditions have different effects on the density of pollutants in different seasons; and (4) relative humidity can play an important role in affecting the spatial inhomogeneity of air pollution despite the large uncertainties.
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    Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign
    (MDPI, 2020-11-21) Junghenn Noyes, Katherine T.; Kahn, Ralph A.; Limbacher, James A.; Li, Zhanqing; Fenn, Marta A.; Giles, David M.; Hair, Johnathan W.; Katich, Joseph M.; Moore, Richard H.; Robinson, Claire E.; Sanchez, Kevin J.; Shingler, Taylor J.; Thornhill, Kenneth L.; Wiggins, Elizabeth B.; Winstead, Edward L.
    Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.
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    Diurnal Variability of Surface Temperature over Lakes: Case Study for Lake Huron
    (MDPI, 2021-02-13) Chen, Wen; Pinker, Rachel T.; Rivera, Gerardo; Hook, Simon
    The significance of the diurnal variability of Lake Surface Temperature (LST) has been recognized; yet, its magnitude in terms of spatial and temporal variability is not well known. Attempts have been made to derive such information from satellites at a high spatial resolution; however, most have been made from polar orbiting satellites that sample only twice per day. We have developed an approach to derive such information from geostationary satellites at an hourly time scale and at a spatial resolution of about 5 km. The approach to derive LST uses the Radiative Transfer for TIROS Operational Vertical Sounder (TOVS) (RTTOV) model driven by the Modern-Era Retrospective analysis for Research and Applications (MERRA)-2 information. The methodology has been implemented over Lake Huron for about six years. We present the results of the evaluation against various independent satellite products and demonstrate that there is a strong diurnal variability in the skin temperature over the lake and that the lowest and highest values, as derived twice per day from polar orbiting satellites, may not represent the magnitude of the Diurnal Temperature Range (DTR).
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    A 7-Year Climatology of Warm-Sector Heavy Rainfall over South China during the Pre-Summer Months
    (MDPI, 2021-07-15) Chen, Tao; Zhang, Da-Lin
    In view of the limited predictability of heavy rainfall (HR) events and the limited understanding of the physical mechanisms governing the initiation and organization of the associated mesoscale convective systems (MCSs), a composite analysis of 58 HR events over the warm sector (i.e., far ahead of the surface cold front), referred to as WSHR events, over South China during the months of April to June 2008~2014 is performed in terms of precipitation, large-scale circulations, pre-storm environmental conditions, and MCS types. Results show that the large-scale circulations of the WSHR events can be categorized into pre-frontal, southwesterly warm and moist ascending airflow, and low-level vortex types, with higher frequency occurrences of the former two types. Their pre-storm environments are characterized by a deep moist layer with >50 mm column-integrated precipitable water, high convective available potential energy with the equivalent potential temperature of ≥340 K at 850 hPa, weak vertical wind shear below 400 hPa, and a low-level jet near 925 hPa with weak warm advection, based on atmospheric parameter composite. Three classes of the corresponding MCSs, exhibiting peak convective activity in the afternoon and the early morning hours, can be identified as linear-shaped, a leading convective line adjoined with trailing stratiform rainfall, and comma-shaped, respectively. It is found that many linear-shaped MCSs in coastal regions are triggered by local topography, enhanced by sea breezes, whereas the latter two classes of MCSs experience isentropic lifting in the southwesterly warm and moist flows. They all develop in large-scale environments with favorable quasi-geostrophic forcing, albeit weak. Conceptual models are finally developed to facilitate our understanding and prediction of the WSHR events over South China.
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    Seasonal and Interannual Variability of Tidal Mixing Signatures in Indonesian Seas from High-Resolution Sea Surface Temperature
    (MDPI, 2022-04-16) Susanto, Raden Dwi; Ray, Richard D.
    With their complex narrow passages and vigorous mixing, the Indonesian seas provide the only low-latitude pathway between the Pacific and Indian Oceans and thus play an essential role in regulating Pacific-Indian Ocean exchange, regional air-sea interaction, and ultimately, global climate phenomena. While previous investigations using remote sensing and numerical simulations strongly suggest that this mixing is tidally driven, the impacts of monsoon and El Niño Southern Oscillation (ENSO) on tidal mixing in the Indonesian seas must play an important role. Here we use high-resolution sea surface temperature from June 2002 to June 2021 to reveal monsoon and ENSO modulations of mixing. The largest spring-neap (fortnightly) signals are found to be localized in the narrow passages/straits and sills, with more vigorous tidal mixing during the southeast (boreal summer) monsoon and El Niño than that during the northwest (boreal winter monsoon) and La Niña. Therefore, tidal mixing, which necessarily responds to seasonal and interannual changes in stratification, must also play a feedback role in regulating seasonal and interannual variability of water mass transformations and Indonesian throughflow. The findings have implications for longer-term variations and changes of Pacific–Indian ocean water mass transformation, circulation, and climate.
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    On Investigating the Dynamical Factors Modulating Surface Chlorophyll-a Variability along the South Java Coast
    (MDPI, 2022-04-05) Mandal, Samiran; Susanto, Raden Dwi; Ramakrishnan, Balaji
    Twelve years of remotely sensed all-sat merged chlorophyll-a concentration unveils strong signatures of chlorophyll-a blooms along the south Java coast. An unprecedented three-times increase in chlorophyll-a concentration is significantly observed along the south Java coast during the southeast monsoon (June–October) than the northwest monsoon (December–April). The multiple regression analysis of dynamic factors evidently indicates that seasonal upwelling is predominantly controlled by the seasonally evolving coastal eddies associated with the seasonally reversing south Java coastal currents (SJCC) and Ekman mass transport (EMT), followed by the relative roles of sea surface temperature (SST) and wind stress curl. The eddy-induced upwelling and EMT-induced coastal upwelling lead to chlorophyll-a blooms during southeast monsoon, well-supported by the entrainment of cold and saline waters (thermocline doming) with low spiciness. On the other hand, the coastal eddies associated with SJCC and SST anomalies play a significant role in modulating the interannual surface chlorophyll-a variability in the domain. Intense chlorophyll-a blooms are observed during the positive IOD years, whereas the least chlorophyll-a concentration is observed during the negative IOD years. The unprecedentedly least chlorophyll-a concentrations during 2010 and 2016 are attributed to the intense and prolonged surface marine heatwaves.
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    Effect of Urban Built-Up Area Expansion on the Urban Heat Islands in Different Seasons in 34 Metropolitan Regions across China
    (MDPI, 2022-12-31) Han, Wenchao; Tao, Zhuolin; Li, Zhangqing; Chengg, Miaomiao; Fan, Hao; Cribb, Maureen; Wang, Qi
    The urban heat island (𝑈𝐻𝐼) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion (𝑈𝐵𝐴𝐸), a topic that has been extensively studied. However, the impact of 𝑈𝐵𝐴𝐸 on the LST differences between urban areas and rural areas (𝑈𝐻𝐼𝑈−𝑅) and between urban areas and emerging urban areas (𝑈𝐻𝐼𝑈−𝑆) in different seasons has seldom been investigated. Here, the 𝑈𝐻𝐼𝑈−𝑆 and 𝑈𝐻𝐼𝑈−𝑅 in 34 major metropolitan regions across China, and their spatiotemporal variations based on long-term space-borne observations during the period 2001–2020 were analyzed. The 𝑈𝐵𝐴𝐸 quantified by the difference in landscape metrics of built-up areas between 2020 and 2000 and their impact on 𝑈𝐻𝐼 was further analyzed. The 𝑈𝐵𝐴𝐸 is impacted by the level of economic development and topography. The 𝑈𝐵𝐴𝐸 of cities located in more developed regions was more significant than that in less developed regions. Coastal cities experienced the most obvious 𝑈𝐵𝐴𝐸, followed by plain and hilly cities. The 𝑈𝐵𝐴𝐸 in mountainous regions was the weakest. On an annual basis, 𝑈𝐻𝐼𝑈−𝑅 was larger than 𝑈𝐻𝐼𝑈−𝑆, decreasing more slowly with 𝑈𝐵𝐴𝐸 than 𝑈𝐻𝐼𝑈−𝑆. In different seasons, the 𝑈𝐻𝐼𝑈−𝑆 and 𝑈𝐻𝐼𝑈−𝑅 were larger, more clearly varying temporally with 𝑈𝐵𝐴𝐸 in summer than in winter, and their temporal variations were significantly correlated with 𝑈𝐵𝐴𝐸 in summer but not in winter. The seasonal difference in 𝑈𝐻𝐼𝑈−𝑅 was larger than that of 𝑈𝐻𝐼𝑈−𝑆. Both the 𝑈𝐻𝐼𝑈−𝑆 and 𝑈𝐻𝐼𝑈−𝑅 in coastal cities were the lowest in summer, decreasing the fastest with 𝑈𝐵𝐴𝐸, while those in mountain cities decreased the slowest. The change in the density of built-up lands was the primary driver affecting the temporal variations in 𝑈𝐻𝐼𝑈−𝑆 and 𝑈𝐻𝐼𝑈−𝑅 during 𝑈𝐵𝐴𝐸, followed by changes in proportion and shape, while the impact of the speed of expansion was the smallest, all of which were more obvious in summer than in winter. The decreased density of built-up lands can reduce 𝑈𝐻𝐼. These findings provide a new perspective for a deeper understanding of the effect of urban expansion on LST in different seasons.
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    A Neural-Network Based MPAS—Shallow Water Model and Its 4D-Var Data Assimilation System
    (MDPI, 2023-01-10) Tian, Xiaoxu; Conibear, Luke; Steward, Jeffrey
    The technique of machine learning has been increasingly applied in numerical weather predictions. The aim of this study is to explore the application of a neural network in data assimilation by making use of the convenience in obtaining the tangent linear and adjoint (TL/AD) of a neural network (NN) and formulating a NN-based four-dimensional variational (4D-Var) DA system. A NN-based shallow water (SW) model is developed in this study. The NN model consists of three layers. The weights and biases in the NN-based SW model are trained with 60 years of hourly ERA5 geopotentials and wind field at 500 hPa as initial conditions and the corresponding 12-h forecasts by Model for Prediction Across Scales (MPAS)-SW, in total of 534,697 sets of samples. The 12-h forecasts from independent dates made by NN-based SW prove to closely emulate the simulations by the actual MPAS-SW model. This study further shows that the TL/AD of an NN model can be easily developed and validated. The ease of obtaining the TL/AD makes NN conveniently applicable in various aspects within a data assimilation (DA) system. To demonstrate such, a continuous 4D-Var DA system is also developed with the forward NN and its adjoint. To demonstrate the functionality of the NN-based 4D-Var DA system, the results from a higher resolution simulation will be treated as observations and assimilated to analyze the low resolution initial conditions. The forecasts starting from the analyzed initial conditions will be compared with those without assimilation to demonstrate improvements.
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    Tracking Changes in Vegetation Structure Following Fire in the Cerrado Biome Using ICESat-2
    (Wiley, 2023-04-10) Konduri, Venkata Shashank; Morton, Douglas C.; Andela, Niels
    Fires mediate grass and tree competition and alter vegetation structure in savanna ecosystems, with important implications for regional carbon, water, and energy fluxes. However, direct observations of how fire frequency influences vegetation structure and post-fire recovery have been limited to small experimental field studies. Here, we combined lidar-derived canopy height and canopy cover from NASA's Ice, Cloud, and land Elevation Satellite-2 with over two decades of burned area data from the Moderate Resolution Imaging Spectroradiometer sensors to provide the first biome-wide estimates of post-fire changes in canopy structure for major vegetation types in the Cerrado (Brazil). Mean canopy height decreased with increasing burn frequency for all natural cover types, with the greatest decline observed for forests and savannas. The ability to separate changes in fractional canopy cover from height growth using lidar data highlighted the long-time scales of vegetation recovery in forests and savannas after fire. For forests in medium and high precipitation areas, canopy cover returned to unburned values within 5 years following fire, whereas mean canopy height remained below unburned values, even in the oldest fires (14–20 years). Recovery times increased with decreasing rainfall, with average values of both fractional cover and canopy height below unburned areas after 14–20 years for savannas. We observed gradual recovery of vegetation height and cover over decades, even in mesic or wet savanna regions like the Cerrado. Infrequent fire activity, particularly in areas with greater land management, influences ecosystem structure across the biome, with important consequences for biodiversity conservation.
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    The Impact of Urbanization on Mesoscale Convective Systems in the Yangtze River Delta Region of China: Insights Gained From Observations and Modeling
    (Wiley, 2023-01-17) Xian, Tian; Guo, Jianping; Zhao, Runze; Su, Tianning; Li, Zhanqing
    Urbanization is an important factor that may influence the formation and development of clouds and precipitation. In this study, we focus on studying the influence of urbanization on mesoscale convective systems (MCS) over the Yangtze River Delta region in China under different synoptic conditions using a combination of radiosonde, meteorological station, and satellite observations. It demonstrates that synoptic forcing can be used to distinguish the effect of land cover and land use on MCS. When the synoptic-scale forcing is weak, the urban heat island (UHI) is the main factor affecting the vertical development of clouds. The UHI decreases atmospheric stability and enhances horizontal convergence, invigorating clouds over and downwind of cities. On the other hand, when strong synoptic-scale forcing is present, buildings in cities cause clouds to bifurcate upwind of cities, moving around them, primarily through their dynamic effects. The heights of cloud tops in central and downwind parts of cities thus drop. Using the Weather Research and Forecasting model simulations of different atmospheric forcings also demonstrate similar patterns around major urban areas. The joint analyses of observations and model simulations provide new insights into the net effects of urbanization on cloud systems.
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    Implementation of a Discrete Dipole Approximation Scattering Database Into Community Radiative Transfer Model
    (Wiley, 2022-12-07) Moradi, Isaac; Stegmann, Patrick; Johnson, Benjamin; Barlakas, Vasileios; Eriksson, Patrick; Geer, Alan; Gelaro, Ronald; Kalluri, Satya; Kleist, Daryl; Liu, Quanhua; Mccarty, Will
    The Community Radiative Transfer Model (CRTM) is a fast model that requires bulk optical properties of hydrometeors in the form of lookup tables to simulate all-sky satellite radiances. Current cloud scattering lookup tables of CRTM were generated using the Mie-Lorenz theory thus assuming spherical shapes for all frozen habits, while actual clouds contain frozen hydrometeors with different shapes. The Discrete Dipole Approximation (DDA) technique is an effective technique for simulating the optical properties of non-spherical hydrometeors in the microwave region. This paper discusses the implementation and validation of a comprehensive DDA cloud scattering database into CRTM for the microwave frequencies. The original DDA database assumes total random orientation in the calculation of single scattering properties. The mass scattering parameters required by CRTM were then computed from single scattering properties and water content dependent particle size distributions. The new lookup tables eliminate the requirement for providing the effective radius as input to CRTM by using the cloud water content for the mass dimension. A collocated dataset of short-term forecasts from Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data was used for the evaluation of results. The results overall showed that the DDA lookup tables, in comparison with the Mie tables, greatly reduce the differences among simulated and observed values. The Mie lookup tables especially introduce excessive scattering for the channels operating below 90 GHz and low scattering for the channels above 90 GHz.