Earth Observation Satellite (EOS)-04 launched on 14th February 2022, carries a C-band Synthetic Aperture Radar (SAR) for Agriculture, Forestry, Hydrology and Flood mapping applications. In this paper, we have used C-band SAR images and near-simultaneous observations from the Global Precipitation Measurements (GPM) to study the signatures of multiple convective rain cells. The bright patches are found on C-band SAR imagery, which depicts the information of hydrometeors such as graupels or hails in the melting layer. For the first time, unambiguously estimated the diameter of the convective core rain cells from the C-band SAR backscattered signal and compared near-simultaneous observations from GPM-GMI and Ku-band radar to confirm our findings. In future, we will decipher between convective and stratiform rain signatures on C-band SAR imagery and the possibility between C-band backscattered signals with lighting events. Thus, the present study demonstrates the potential of C-band SAR for the signatures of convective rain cells.
Earth Observations (EO) systems aim to monitor nearly all aspects of the global Earth environment. Observations of Essential Water Variables (EWVs) together with advanced data assimilation models, could provide the basis for systems that deliver integrated information for operational and policy level decision making that supports the Water-Energy-Food-Nexus (EO4WEF), and concurrently the UN Sustainable Development Goals (SDGs), and UN Framework Convention on Climate Change (UNFCCC). Implementing integrated EO for GEO-WEF (EO4WEF) systems requires resolving key questions regarding the selection and standardization of priority variables, the specification of technologically feasible observational requirements, and a template for integrated data sets. This paper presents a concise summary of EWVs adapted from the GEO Global Water Sustainability (GEOGLOWS) Initiative and consolidated EO observational requirements derived from the GEO Water Strategy Report (WSR). The UN-SDGs implicitly incorporate several other Frameworks and Conventions such as The Sendai Framework for Disaster Risk Reduction; The Ramsar Convention on Wetlands; and the Aichi Convention on Biological Diversity. Primary and Supplemental EWVs that support WEF Nexus & UN-SDGs, and Climate Change are specified. The EO-based decision-making sectors considered include water resources; water quality; water stress and water use efficiency; urban water management; disaster resilience; food security, sustainable agriculture; clean & renewable energy; climate change adaptation & mitigation; biodiversity & ecosystem sustainability; weather and climate extremes (e.g., floods, droughts, and heat waves); transboundary WEF policy.
Natural hazards such as floods, hurricanes, heatwaves, and wildfires cause significant economic losses (e.g., agricultural and property damage) as well as a high number of fatalities. Natural hazards are often driven by univariate or multivariate hydrometeorological drivers. Therefore, it is crucial to understand how and which hydrometeorological variables (i.e., drivers) combine to contribute to the impacts of these hazards. Additionally, when multiple drivers are associated with a hazard, traditional univariate risk assessment approaches are insufficient to cover the full spectrum of impact-relevant conditions originating from different combinations of multiple drivers. Based on historical socioeconomic loss data, we develop an impact-based approach to assess the influence of different hydrometeorological drivers on the impacts caused by different hazard event types. We use the Spatial Hazard Events and Losses Database for the United States (SHELDUS™) to identify the historical hazard events that caused socioeconomic impacts (property and crop damage, injuries, and fatalities) in our case study area, Miami-Dade County, in south Florida. For 9 different hazard types, we obtained data for 13 hydrometeorological drivers from historical in-situ observations and reanalysis products corresponding to the timing and locations of the hazard events found in the SHELDUS database. The relative importance of each hazard driver in generating impacts and the frequency of multiple drivers was then assessed. We found that many high-impact events were caused by multiple hydrometeorological drivers (i.e., compound events). For example, 61% of the recorded flooding events were compound events rather than univariate hazards and these contributed 99% of total property damage and 98.2% of total crop damage in Miami-Dade County. For several hazards, such as hurricanes/tropical storms and wildfires, all the events that caused damage are classified as compound events in our framework. Our findings emphasize the benefit of including socioeconomic impact information when analyzing hazard events, as well as the importance of analyzing all relevant hydrometeorological drivers to identify compound events.
Biomass burning has shaped many of the ecosystems of the planet and for millennia humans have used it as a tool to manage the environment. When widespread fires occur, the health and daily lives of millions of people can be affected by the smoke, often at unhealthy to hazardous levels leading to a range of short-term and long-term health consequences such as respiratory issues, cardiovascular issues, and mortality. It is critical to adequately represent and include smoke and its consequences in atmospheric modeling systems to meet needs such as addressing the global climate carbon budget and informing and protecting the public during smoke episodes. Many scientific and technical challenges are associated with modeling the complex phenomenon of smoke. Variability in fire emissions estimates has an order of magnitude level of uncertainty, depending upon vegetation type, natural fuel heterogeneity, and fuel combustion processes. Quantifying fire emissions also vary from ground/vegetation-based methods to those based on remotely sensed fire radiative power data. These emission estimates are input into dispersion and air quality modeling systems, where their vertical allocation associated with plume rise, and temporal release parameterizations influence transport patterns, and, in turn affect chemical transformation and interaction with other sources. These processes lend another order of magnitude of variability to the downwind estimates of trace gases and aerosol concentrations. This chapter profiles many of the global and regional smoke prediction systems currently operational or quasi-operational in real time or near-real time. It is not an exhaustive list of systems, but rather is a profile of many of the systems in use to give examples of the creativity and complexity needed to simulate the phenomenon of smoke. This chapter, and the systems described, reflect the needs of different agencies and regions, where the various systems are tailored to the best available science to address challenges of a region. Smoke forecasting requirements range from warning and informing the public about potential smoke impacts to planning burn activities for hazard reduction or resource benefit. Different agencies also have different mandates, and the lines blur between the missions of quasi-operational organizations (e.g. research institutions) and agencies with operational mandates. The global smoke prediction systems are advanced, and many are self-organizing into a powerful ensemble, as discussed in section 2. Regional and national systems are being developed independently and are discussed in sections 3-5 for Europe (11 systems), North America (7 systems), and Australia (3 systems). Finally, the World Meteorological Organization (WMO) effort (section 6) is bringing together global and regional systems and building the Vegetation Fire and Smoke Pollution Advisory and Assessment Systems (VFSP-WAS) to support countries with smoke issues and who lack resources.
An international joint research project, entitled Interhemispheric Coupling Study by Observations and Modelling (ICSOM), is ongoing. In the late 2000s, an interesting form of interhemispheric coupling (IHC) was discovered: when warming occurs in the winter polar stratosphere, the upper mesosphere in the summer hemisphere also becomes warmer with a time lag of days. This IHC phenomenon is considered to be a coupling through processes in the middle atmosphere (i.e., stratosphere, mesosphere, and lower thermosphere). Several plausible mechanisms have been proposed so far, but they are still controversial. This is mainly because of the difficulty in observing and simulating gravity waves (GWs) at small scales, despite the important role they are known to play in middle atmosphere dynamics. In this project, by networking sparsely but globally distributed radars, mesospheric GWs have been simultaneously observed in seven boreal winters since 2015/16. We have succeeded in capturing five stratospheric sudden warming events and two polar vortex intensification events. This project also includes the development of a new data assimilation system to generate long-term reanalysis data for the whole middle atmosphere, and simulations by a state-of-art GW-permitting general circulation model using reanalysis data as initial values. By analyzing data from these observations, data assimilation, and model simulation, comprehensive studies to investigate the mechanism of IHC are planned. This paper provides an overview of ICSOM, but even initial results suggest that not only gravity waves but also large-scale waves are important for the mechanism of the IHC.
Total evaporation from the vast terrain of the Tibetan Plateau (TP) may strongly influence downwind regions. However, the ultimate fate of this moisture remains unclear. This study tracked and quantified TP-originating moisture. The results show that the TP moisture participation in downwind regions’ precipitation is the strongest around the eastern edge of the TP and then weakens gradually toward the east. Consequently, TP moisture in the composition of precipitation over the central-eastern TP is the largest of over 30%. 44.9-46.7% of TP annual evaporation is recycled over the TP, and about 2/3 of the TP evaporation is reprecipitated over terrestrial China. Moisture cycling of TP origin shows strong seasonal variation, with seasonal patterns largely determined by precipitation, evaporation and wind fields. High levels of evaporation and precipitation over the TP in summer maximize local recycling intensity and recycling ratios. Annual precipitation of TP origin increased mainly around the northeastern TP during 2000-2020. This region consumed more than half of the increased TP evaporation. Further analyses showed that changes in reprecipitation of TP origin were consistent with precipitation trends in nearby downwind areas: when intensified TP evaporation meets intensified precipitation, more TP moisture is precipitated out. The model estimated an annual precipitation recycling ratio (PRR) of 26.9-30.8% in forward moisture tracking. However, due to the non-closure issue of the atmospheric moisture balance equation, the annual PRR in backward tracking can be ~6% lower.
A novel method for estimating spatial-temporal modes of time varying data containing complex non-linear interacting multivariate fields, called the entropy field decomposition (EFD), is applied to the problem of characterizing the formation and intensification of atmosphere rivers (ARs), and reveals two novel findings. First, analysis of global time-varying interacting wind (w) and specific humidity (q) fields produces spatiotemporal modes consistent with observed global distribution of ARs detected by Integrated Water Vapor Transport (IVT). Secondly, space-time information trajectories (STITs) generated from coupled w-q EFD modes, representing optimal (in the sense of maximum entropy) parameter pathways, reveal a clear connection between ARs and planetary-scale circulation with structure similar to Rossby waves and reveal that ARs appear to be dynamically linked with the outflow region of the wave troughs. These findings provide an automated quantitative method to examine impacts of interacting multiscale dynamics on AR formation and activities.
Cold surges are synoptic weather systems that occur over the Maritime Continent during the boreal winter. They are characterised by the strengthening of prevailing low-level northerly to north-easterly winds, temperature falls of a few degrees over several days, and in some cases, extreme prolonged rainfall and flooding. We investigate the synoptic structure and development of cold surges through composites of dry, moderate and wet surges. Each surge category is defined by the distribution of precipitation averaged within a specified domain over the equatorial South China Sea. Over the Maritime Continent, most of the dry (wet) surges occur during the suppressed (active) phases of the Madden-Julian Oscillation (MJO). Dry surges are characterised by cross-equatorial flow and positive mean sea-level pressure anomalies which reach the Southern Hemisphere, and enhanced descent or weaker ascent. Wet surges coincide with a cyclonic circulation over Borneo, a lack of cross-equatorial flow, and enhanced moisture and ascent. We find that diurnal precipitation patterns are consistent with convective onset being controlled by the mid-tropospheric buoyancy of an idealised entraining plume. This buoyancy diagnostic suggests that wet surges are characterised by a moister free troposphere because this reduces the effect of entrainment and allows convection to penetrate the lower troposphere. Finally, deep (shallow) and relatively strong (weak) westerlies are found over southern Java and northern Australia during the dry (wet) surges. Consequently, Australian summer monsoon bursts are more likely to occur following dry cold surges. The westerlies are also explained as part of the larger-scale MJO circulations.
Elevated ozone (O3) pollution in the warm season is an emerging environmental concern affecting global highly urbanized megacities. In southwestern China, full characterization of causes for O3 pollution has been stymied by limited observations and the dominant factors that influence O3 variability on a long-term basis still lack understanding. Herein, we identified O3 variations and inferred trends in precursor emissions in Chengdu over 2013–2020 based on extensive ambient measurements, emission inventory, and satellite data. Numerical models were used to investigate the changes in meteorological variability and biogenic emissions. Trends of O3 in urban areas show deterioration (+14.0% yr−1) between 2013 and 2016 followed by a slight decrease over 2017–2020, while O3 levels in rural areas generally show a downward trend (−2.9% yr−1) during 2014–2020. Both emission inventory (−3.7% yr−1) and OMI satellite columns (−4.5% yr−1) depict strong decline trends in NOx emissions, while satellite HCHO columns exhibit a flattened downward trend of VOC emissions (−1.8% yr−1), which caused rural areas shifted from VOCs-limited to transitional or NOx-limited regime since 2016. Considering metropolitan Chengdu remains VOCs-limited regime over time, the existing regulatory framework involving simultaneous NOx and VOCs control would result in evident O3 improvements in the near future. Despite benefits from anthropogenic emission reductions, we demonstrate that meteorological conditions and enhanced biogenic emissions over the warm season could partially or even fully offset effects attributed to emission changes, making the net effects obscure. This finding provides robust evidence of reductions in NOx and VOCs emission and informs effective O3 mitigation policies for megacities which undergo similar emission pathways in Chengdu.
Extreme solar particle events (ESPEs) are rare and the most potent known processes of solar eruptive activity. During ESPEs, a vast amount of cosmogenic isotopes (CIs) 10Be, 36Cl and 14C can be produced in the Earth’s atmosphere. Accordingly, CI measurements in natural archives allow us to evaluate particle fluxes during ESPEs. In this work, we present a new method of ESPE fluence (integral flux) reconstruction based on state-of-the-art modeling advances, allowing to fit together different CI data within one model. We represent the ESPE fluence as an ensemble of scaled fluence reconstructions for ground-level enhancement (GLE) events registered by the neutron monitor network since 1956 coupled with satellite and ionospheric measurements data. Reconstructed ESPE fluences appear softer in its spectral shape than earlier estimates, leading to significantly higher estimates of the low-energy (E<100 MeV) fluence. This makes ESPEs even more dangerous for modern technological systems than previously believed. Reconstructed ESPE fluences are fitted with a modified Band function, which eases the use of obtained results in different applications.
This study investigates the representation of stratocumulus (Sc) clouds, cloud variability, and precipitation statistics over the Southern Ocean (SO) to understand the dominant ice processes within the Icosahedral Nonhydrostatic (ICON) model at the kilometer scale using real case simulations. The simulations are evaluated using the shipborne observations as open-cell stratocumuli were continuously observed during two days (26th -27th of March 2016), south of Tasmania. The radar retrievals are used to effectively analyze the forward- simulated radar signatures from Passive and Active Microwave TRAnsfer (PAMTRA). We contrast cloud-precipitation statistics, and microphysical process rates between simulations performed with one-moment (1M) and two-moment (2M) microphysics schemes. We further analyze their sensitivity to primary and secondary ice-phase processes (Hallett–Mossop and collisional breakup). Both processes have previously been shown to improve the ice properties of simulated shallow mixed-phase clouds over the SO in other models. We find that only simulations with continuous formation, growth, and subsequent melting of graupel, and the effective riming of in-cloud rain by graupel, capture the observed cloud-precipitation vertical structure. In particular, the 2M microphysics scheme requires additional tuning for graupel processes in SO stratocumuli. Lowering the assumed graupel density and terminal velocity, in combination with secondary ice processes, enhances graupel formation in 2M microphysics ICON simulations. Overall, all simulations capture the observed intermittency of precipitation irrespective of the microphysics scheme used, and most of them sparsely distribute intense precipitation (>1mm h-1 ) events. Furthermore, the simulated clouds are too reflective as they are optically thick and/or have high cloud cover.
As the largest natural source of sulfur-containing gases into the atmosphere, ocean organism-derived dimethyl sulfide (DMS) has been considered to play a critical role in the Earth’s climate system. Yet there are great uncertainties in modeling the spatiotemporal variations of DMS and incomplete knowledge of influencing factors in different oceanic regions. Moreover, little is known about the future change of global DMS, which limits our understanding of the feedback of marine ecosystem to climate change. Here we develop an artificial neural network model and combine data mining approaches to address these issues. Phytoplankton biomass and salinity are currently predominant factors associated with DMS variability in the coastal and Arctic regions, respectively. In the mid- and low-latitude open oceans, nutrients and temperature are also crucial factors in addition to radiation and mixed layer depth, and their relationships with DMS show reversals when passing certain thresholds. Although the global average DMS concentration and emission slightly decline from 2005 to 2100, they may change considerably in specific regions. In contrast to the DMS decreases in the low-latitudes mainly related with phosphate reduction and temperature rise and in the North Atlantic subpolar gyre attributed to salinity decline, warming will cause DMS increase in the Southern Ocean and sea ice loss will dramatically enhance DMS emission in the Arctic. Although the global negative feedback loop between oceanic DMS and climate may not operate, the future spatial redistribution of DMS may lead to the change in cloud cover pattern and significantly affect regional climate.
We simulated the Nov 4, 2021 geomagnetic storm event penetrating electric field using the Multiscale Atmosphere-Geospace Environment (MAGE) and compared with the NASA ICON observation. The ICON observation showed enhancement of the vertical ion drift when the penetrating electric field arrived at the equatorial region. The simulated vertical ion drifts are consistent with ICON observation. Hence, we are able to verify the MAGE simulation with ICON observation. On the dusk side, the MAGE simulation showed strong pre-reversal enhancement (PRE), whereas the ICON observation did not display any sign of the PRE. The MAGE simulation did show that PRE amplitude decreases as altitude increase. Because the ICON orbital height is above the model upper boundary, it could be a factor for the discrepancy. Instrumental issue cannot be ruled out at this moment. GOLD UV image at the same time exhibits multiple plasma bubbles, which seem to suggest the existence of the PRE.
Searches for phosphine in Venus’ atmosphere have sparked a debate. Cordiner et al. 2022 analyse spectra from the Stratospheric Observatory For Infrared Astronomy (SOFIA) and infer <0.8 ppb of PH3. We noticed that spectral artefacts arose mainly from inessential calibration-load signals. By-passing these signals allows simpler post-processing, and 6.5σ detection of 1 ppb of PH3 at ~75 km altitude (just above the clouds). Compiling six phosphine results would suggest the abundance inverts: decreasing above the clouds but rising again in the mesosphere from some unexplained source. However, no such extra source is needed if phosphine is undergoing destruction by sunlight (photolysis), as it does on Earth. Low values/limits were found where the viewed part of the super-rotating Venusian atmosphere had passed through sunlight, while the high values are from views moving into sunlight. We suggest Venusian phosphine is indeed present, and so merits further work on models of its origins.
Dynamic influences on summertime seasonal United States rainfall variability are not well understood. A major cause of moisture transport is the Great Plains low-level jet (LLJ). Using observations and a dry atmospheric general circulation model, this study explored the distinct and combined impacts of two prominent atmospheric teleconnections - the East Asian monsoon (EAM) and North Atlantic subtropical high (NASH) - on the Great Plains LLJ in the summer. Separately, a strong EAM and strong western NASH are linked to a strengthened LLJ and positive rainfall anomalies in the Plains/ Midwest. Overall, NASH variability is more important for considering the LLJ impacts, but strong EAM events amplify western NASH-related Great Plains LLJ strengthening and associated rainfall signals. This occurs when the EAM-forced Rossby wave pattern over North America constructively interferes with low-level wind field, providing upper-level support for the LLJ and increasing mid- to upper-level divergence.
Within the Charlotte, North Carolina, to Atlanta, Georgia, megaregion (Charlanta), the Atlanta metropolitan area has been shown to augment proximal cloud-to-ground (CG) lightning occurrence. Although numerous studies have documented this “urban lightning effect” (ULE) with regard to CG lightning, relatively few have investigated urban effects on distributions of total lightning (TL). Moreover, there has yet to be a study of the ULE using TL observations from the Geostationary Lightning Mapper (GLM). In an effort to fill this gap, we investigated spatial distributions of TL around the cities of Atlanta, GA, Greenville, SC, and Charlotte, NC, using GLM data collected during the warm seasons of 2018–2021. Analyses reveal augmentation of total lightning intensity and frequency over the major cities of Atlanta and Charlotte, with a diminished urban signal over the smaller city of Greenville. This work also demonstrated the potential efficacy of the emerging satellite-based TL climatology in ULE studies.
The Hunga Tonga-Hunga Ha’apai (HTHH) volcanic eruption in January 2022 injected extreme amounts of water vapor (H2O) and a moderate amount of the aerosol precursor (SO2) into the Southern Hemisphere (SH) stratosphere. The H2O and aerosol perturbations have persisted and resulted in large-scale SH stratospheric cooling, equatorward shift of the Antarctic polar vortex, and slowing of the Brewer-Dobson circulation associated with a substantial ozone reduction in the SH winter midlatitudes. Chemistry-climate model simulations forced by realistic HTHH inputs of H2O and SO2 reproduce the observed stratospheric cooling and circulation effects, demonstrating the observed behavior is due to the volcanic influences. Furthermore, the combination of aerosol transport to polar latitudes and a cold polar vortex enhances springtime Antarctic ozone loss, consistent with observed polar ozone behavior in 2022.
Natural aerosols and their interactions with clouds remain an important uncertainty within climate models, especially at the poles. Here, we study the behavior of sea salt aerosols (SSaer) in the Arctic and Antarctic within 12 climate models from CMIP6. We investigate the driving factors that control SSaer abundances and show large differences based on the choice of the source function, and the representation of aerosol processes in the atmosphere. Close to the poles, the CMIP6 models do not match observed seasonal cycles of surface concentrations, likely due to the absence of wintertime SSaer sources such as blowing snow. Further away from the poles, simulated concentrations have the correct seasonality, but have a positive mean bias of up to one order of magnitude. SSaer optical depth is derived from the MODIS data and compared to modeled values, revealing good agreement, except for winter months. Better agreement for AOD than surface concentration may indicate a need for improving the vertical distribution, the size distribution and/or hygroscopicity of modeled polar SSaer. Source functions used in CMIP6 emit very different numbers of small SSaer, potentially exacerbating cloud-aerosol interaction uncertainties in these remote regions. For future climate scenarios SSP126 and SSP585, we show that SSaer concentrations increase at both poles at the end of the 21st century, with more than two times mid-20th century values in the Arctic. The pre-industrial climate CMIP6 experiments suggest there is a large uncertainty in the polar radiative budget due to SSaer.