Browse

You are looking at 1 - 10 of 397 items for :

  • Earth Interactions x
  • Refine by Access: Content accessible to me x
Clear All
Ashley E. Van Beusekom and Grizelle González

Abstract

Understanding near-surface atmosphere behavior in the tropics is imperative given the role of tropical energy fluxes in Earth’s climate cycles, but this area is complicated by a land-atmosphere interaction that includes rugged topography, seasonal weather drivers, and frequent environmental disturbances. This study examines variation in near-surface atmosphere behaviors in northeastern Puerto Rico using a synthesis of data from lowland and montane locations under different land covers (forest, urban, and rural) during 2008 to 2021, when a severe drought, large hurricanes (Irma and Maria), and the COVID-19 mobility-reducing lockdown occurred. Ceilometer, weather, air quality, radiosonde, and satellite data were analyzed for annual patterns and monthly time series of data and data correlations. The results showed a system strongly dominated by easterly trade-winds transmitting regional oceanic patterns over terrain. Environmental disturbances affected land-atmosphere interaction for short time periods after events. Events that reduce the land signature, (reducing greenness: e.g., drought and hurricanes, or reducing land pollution: e.g., COVID-19 lockdown) were evidenced to strengthen the transmission of the oceanic pattern. The most variation in near-surface atmosphere behavior was seen in the mountainous areas that were influenced by both factors, trade-winds and terrain-induced orographic lifting. As an exception to the rest of the near-surface atmosphere behavior, pollutants other than ozone did not correlate positively or negatively with stronger trade-winds at all sites across the region. Instead, these pollutants were hypothesized to be more anthropogenically influenced. Once Covid-19 lockdown persisted for three months, urban pollution decreased, and cloud base may have increased.

Free access
Odin Marc, Romulo A. Jucá Oliveira, Marielle Gosset, Robert Emberson, and Jean-Philippe Malet

Abstract

Rainfall-induced landsliding is a global and systemic hazard, likely to increase with the projections of increased frequency of extreme precipitation with current climate change. However, our ability to understand and mitigate landslide risk is strongly limited by th availability of relevant rainfall measurements in many landslide prone areas. In the last decade, global satellite multi-sensor precipitation products (SMPPs) have been proposed as a solution but very few studies have assessed their ability to adequately characterize rainfall events triggering landsliding. Here, we address this issue by testing the rainfall pattern retrieved by 2 SMPPs (IMERG and GSMaP) and one hybrid product (MSWEP) against a large, global database of 20 comprehensive landslide inventories associated with well-identified storm events. We found that after converting total rainfall amounts to an anomaly relative to the 10-year return rainfall, R*, the three products do retrieve the largest anomaly (of the last 20 years) during the major landslide event for many cases. However, the degree of spatial collocation of R* and landsliding varies from case to case and across products, and we often retrieved R*>1 in years without reported landsliding. Additionally, the few (4) landslide events caused by short and localized storms are most often undetected. We also show that, in at least five cases, the SMPPs spatial pattern of rainfall anomaly matches landsliding less well than ground-based radar rainfall pattern or lightning maps, underlining the limited accuracy of the SMPPs. We conclude on some potential avenues to improve SMPPs retrieval, and their relation to landsliding.

Free access
Matthew S. Van Den Broeke

Abstract

Tropical cyclones (TCs) routinely transport organisms at their centers of circulation. The TC center of circulation is also often marked by an inversion, and the height of the inversion base may change as the TC intensifies or weakens. In this study, a dataset of 49 dropsonde-measured inversions in 20 separate Atlantic Ocean TCs is compared with spatiotemporally collocated polarimetric radar measurements of bioscatter. Bioscatter signature maximum altitude is found to be a function of temperature lapse rate across the inversion base (r = 0.473), and higher inversion bases were generally associated with denser bioscatter signatures, especially when strong hurricanes (minimum pressure < 950 hPa) were considered (r = 0.601). Characteristics of the bioscatter signature had some skill in predicting TC inversion characteristics (adjusted r 2 of 16%–40%), although predictability was increased when TC intensity was also included as a predictor (adjusted r 2 of 40%–59%). These results indicate promise for using the bioscatter signature to monitor the TC inversion and represent an example of a situation in which the behavior of organisms in the airspace may be indicative of ongoing atmospheric processes.

Significance Statement

Tropical cyclone centers of circulation are often associated with an inversion, the base of which changes altitude with system strengthening and weakening. They may also contain a radar-observable bioscatter signature. In this study, we wanted to determine how the bioscatter signature relates to inversion characteristics for the benefit of meteorologists and biologists. Bioscatter signature characteristics were related to strength of the temperature and dewpoint lapse rates across the inversion base, and deeper/denser bioscatter signatures were typically associated with higher inversion bases. The findings suggest that trends in tropical cyclone inversion characteristics could be remotely monitored via the bioscatter signature. They also support prior speculation that some birds may seek the relatively laminar flow above an inversion base.

Full access
Hongbo Yang, Arika Ligmann-Zielinska, Yue Dou, Min Gon Chung, Jindong Zhang, and Jianguo Liu

Abstract

Rural areas are increasingly subject to the effects of telecouplings (socioeconomic and environmental interactions over distances) whereby their human and natural dynamics are linked to socioeconomic and environmental drivers operating far away, such as the growing demand for labor and ecosystem services in cities. Although there have been many studies evaluating the effects of telecouplings, telecouplings in those studies were often investigated separately, and how telecouplings may interact and affect dynamics of rural coupled human and natural systems (CHANS) jointly was rarely evaluated. In this study, we developed an agent-based model and simulated the impacts of two globally common telecouplings, nature-based tourism and labor migration, on forest dynamics of a rural CHANS, China’s Wolong Nature Reserve (Wolong). Nature-based tourism and labor migration can facilitate forest recovery, and the predicted forest areas in Wolong in 2030 would be reduced by 26.2 km2 (6.8%) and 23.9 km2 (6.2%), respectively, without their effects. However, tourism development can significantly reduce the probability of local households to have member(s) outmigrate to work in cities and decrease the positive impact of labor migration on forest recovery. Our simulations show that the interaction between tourism and labor migration can reduce the potential forest recovery by 3.5 km2 (5.0%) in 2030. Our study highlights that interactions among different telecouplings can generate significant impacts on socioeconomic and environmental outcomes and should be jointly considered in the design, management, and evaluation of telecouplings for achieving sustainable development goals.

Significance Statement

Rural areas are increasingly connected with other places through telecouplings, such as tourism and labor migration. However, telecouplings’ effects were often evaluated separately, and their interaction remains poorly understood. In this study, we evaluated how two globally common telecouplings, tourism and labor migration, jointly affect forest dynamics in a demonstration site using an agent-based modeling approach. Although both tourism and labor migration can benefit forest conservation, we found that their interaction generates an antagonistic effect: households’ involvement in tourism activities reduces their probability to have members outmigrate to work in cities and significantly diminishes the beneficial impact of labor migration on forest recovery. Our study highlights the importance of considering interaction among telecouplings in the management of telecouplings for sustainability.

Full access
Gregory J. McCabe and David M. Wolock

Abstract

Extensive and severe droughts have substantial effects on water supplies, agriculture, and aquatic ecosystems. To better understand these droughts, we used tree-ring-based reconstructions of the Palmer drought severity index (PDSI) for the period 1475–2017 to examine droughts that covered at least 33% of the conterminous United States (CONUS). We identified 37 spatially extensive drought events for the CONUS and examined their spatial and temporal patterns. The duration of the extensive drought events ranged from 3 to 12 yr and on average affected 43% of the CONUS. The recent (2000–08) drought in the southwestern CONUS, often referred to as the turn-of-the-century drought, is likely one of the longest droughts in the CONUS during the past 500 years. A principal components analysis of the PDSI data from 1475 through 2017 resulted in three principal components (PCs) that explain about 48% of the variability of PDSI and are helpful to understand the temporal and spatial variability of the 37 extensive droughts in the CONUS. Analyses of the relations between the three PCs and well-known climate indices, such as indices of El Niño–Southern Oscillation, indicate statistically significant correlations; however, the correlations do not appear to be large enough (all with an absolute value less than 0.45) to be useful for the development of drought prediction models.

Significance Statement

To better understand the variability of spatially extensive U.S. droughts through time and across space, we examined tree-ring-based reconstructions of a relative dryness/wetness index for the period 1475–2017. We identified 37 extensive drought events with durations that ranged from 3 to 12 years and that on average affected 43% of the conterminous United States. Also, three of the seven longest droughts occurred after 1900. Because associations between indices of climatic conditions and drought are weak, use of climatic indices for predictive models of drought seems tenuous.

Free access
S. K. Yadav, E. Lee, and Y. He

Abstract

The Tibetan Plateau (TP) has undergone extreme changes in climatic and land surface conditions that are due to a warming climate and land-cover changes. We examined the change in vegetation dynamics from 1982 to 2015 and explored the associations of vegetation with atmospheric variables over the alpine grasslands in the western TP during May as an early growing season. The linear regression analysis of area-averaged normalized difference vegetation index (NDVI) over the western TP in May demonstrated a 7.5% decrease of NDVI during the period from 1982 to 2015, an increase of NDVI by 11.3% from 1982 to 1998, and a decrease of NDVI by 14.5% from 1999 to 2015. The significantly changed NDVI in the western TP could result in the substantial changes in surface energy balances as shown in the surface climatic variables of albedo, net solar radiation, sensible heat flux, latent heat fluxes, and 2-m temperature. The land and atmosphere associations were not confined to the surface but also extended into the upper-level atmosphere up to the 300-hPa level as indicated by the significant positive associations between NDVI and temperatures in both air temperature and equivalent temperature, resulting in more than a 1-K increase with NDVI. Therefore, we concluded that the increasing or decreasing vegetation cover in the western TP during May can respectively increase or decrease the temperatures near the surface and upper atmosphere through a positive physical linkage among the vegetation cover, surface energy fluxes, and temperatures. The positive energy processes of vegetation with temperature could further amplify the variations of temperature and thus water availability.

Significance Statement

The Tibetan Plateau (TP) is an important landmass that plays a significant role in both regional and global climates. This study aims to examine the vegetation change in the TP during May as an early growing season to examine the changes in the near-surface and upper-level climatic conditions associated with vegetation change and to identify the plausible physical processes of the vegetation effects on atmosphere. The satellite-derived vegetation index showed a 7.5% decrease from 1982 to 2015 in the western TP during May. This study identified the positive associations of vegetation activity with temperature and proposed a positive energy process for land–atmosphere interactions over the alpine grasslands in the western region of TP during the transition period from winter to spring.

Full access
Benjamin D. Abel, Balaji Rajagopalan, and Andrea J. Ray

Abstract

The Prairie Pothole Region (PPR) experiences considerable space–time variability in temperature and precipitation, and this variability is expected to increase. The PPR is sensitive to this variability—it plays a large role in the water availability of the region. Thousands of wetlands in the region, sometimes containing ponds, provide habitats and breeding grounds for various species. Many wildlife management decisions are planned and executed on subseasonal-to-seasonal time scales and would benefit from knowledge of seasonal conditions at longer lead times. Therefore, it is important to understand potential driving mechanisms and teleconnections behind space–time climate variability in the PPR. We performed principal component analysis on summer precipitation of the southeastern PPR (SEPPR) to determine the leading principal components (PCs) of variability. These PCs were used to establish teleconnections to large-scale climate variables and indices. They were also used to determine potential mechanisms driving the precipitation variability. There were teleconnections to Pacific and Atlantic Ocean sea surface temperatures (SST) resembling the Pacific decadal oscillation and El Niño–Southern Oscillation, low 500-hPa heights over the western United States, and the Palmer drought severity index over the SEPPR. A large-scale low pressure region over the northwestern United States and a pattern like the Great Plains low-level jet, observed in the 500- and 850-hPa heights and winds, are a potential mechanism of the precipitation variability by increasing precipitation during wet PC1 years. These findings can inform management actions to maintain and restore wildlife habitat and the resources used for those actions in the PPR.

Full access
Alexander R. Davies, Joseph P. Smith, David S. Mandell, George Davis, and Forest Y. Wan

Abstract

Like many coastal communities throughout the mid-Atlantic region, relative sea level rise and accelerating instances of coastal nuisance flooding are having a tangible negative impact on economic activity and infrastructure in Annapolis, Maryland. The drivers of coastal nuisance flooding, in general, are a superposition of global, regional, and local influences that occur across spatial and temporal scales that determine water levels relative to a coastal datum. Most of the research to date related to coastal flooding has been focused on high-impact episodic events, decomposing the global and regional drivers of sea level rise, or assessing seasonal-to-interannual trends. In this study, we focus specifically on the role of short-duration (hours) meteorological wind forcing on water level anomalies in Annapolis. Annapolis is an ideal location to study these processes because of the orientation of the coast relative to the prevailing wind directions and the long record of reliable data observations. Our results suggest that 3-, 6-, 9-, and 12-h sustained wind forcing significantly influences water level anomalies in Annapolis. Sustained wind forcing out of the northeast, east, southeast, and south is associated with positive water level anomalies, and sustained wind forcing out of the northwest and north is associated with negative water level anomalies. While these observational results suggest a relationship between sustained wind forcing and water level anomalies, a more robust approach is needed to account for other meteorological variables and drivers that occur across a variety of spatial and temporal scales.

Significance Statement

Coastal nuisance flooding, often the result of positive water level anomalies, is having a negative economic impact in Annapolis, Maryland. Coastal flooding research has primarily focused on high-impact episodic events, trends in sea level rise, or seasonal to interannual variability in flooding. In this study we show that short-duration wind forcing (≤12 h) likely has a significant impact on both positive and negative water level anomalies in Annapolis. While this was empirically known by local stakeholders, in this study we attempt to quantify the relationship. These results could help local stakeholders to mitigate against economic and infrastructure losses resulting from coastal nuisance flooding.

Full access
Lei Ji and Jesslyn F. Brown

Abstract

Assessment of temporal trends in vegetation greenness and related influences aids understanding of recent changes in terrestrial ecosystems and feedbacks from weather, climate, and environment. We analyzed 1-km normalized difference vegetation index (NDVI) time series data (1989–2016) derived from the Advanced Very High Resolution Radiometer (AVHRR) and developed growing-season time-integrated NDVI (GS-TIN) for estimating seasonal vegetation activity across stable natural land cover in the conterminous United States (CONUS). After removing areas from analysis that had experienced land-cover conversion or modification, we conducted a monotonic trend analysis on the GS-TIN time series and found that significant positive temporal trends occurred over 35% of the area, whereas significant negative trends were observed over only 3.5%. Positive trends were prevalent in the forested lands of the eastern one-third of CONUS and far northwest, as well as in grasslands in the north-central plains. We observed negative and nonsignificant trends mainly in the shrublands and grasslands across the northwest, southwest, and west-central plains. To understand the relationship of climate variability with these temporal trends, we conducted partial and multiple correlation analyses on GS-TIN, growing-season temperature, and water-year precipitation time series. The GS-TIN trends in northern forests were positively correlated with temperature. The GS-TIN trends in the central and western shrublands and grasslands were negatively correlated with temperature and positively correlated with precipitation. Our results revealed spatial patterns in vegetation greenness trends for different stable natural vegetation types across CONUS, enhancing understanding gained from prior studies that were based on coarser 8-km AVHRR data.

Significance Statement

Assessing vegetation trends, cycles, and related influences is important for understanding the responses and feedbacks of terrestrial ecosystems to climatic and environmental changes. We analyzed vegetation greenness trends (1989–2016) for stable natural land cover across the conterminous United States, based on vegetation index time series derived from coarse-resolution optical satellite sensors. We found greening trends in the forests of the east and far northwest and the grasslands of the northern central plains that correlated with increasing temperature in the regions. We observed browning and no trends mainly in the shrublands and grasslands across the northwest, southwest, and western central plains, associated with increasing temperature and decreasing precipitation. Future research should focus on vegetation greenness analysis using finer-resolution satellite data.

Full access
Cassia M. L. Beu and Eduardo Landulfo

Abstract

Low-level jets are a recurrent feature of our study area in Ipero municipality of southeastern Brazil. They grow very near the surface as shown by this case study. These two aspects increase the needs for a realistic modeling of the low-level jet to simulate the atmospheric dispersion of industrial emissions. In this concern, we applied a recently proposed technique to estimate the turbulence kinetic energy dissipation rate of a low-level jet case with Doppler lidar data. This low-level jet remained for its entire lifetime (around 12 h) within a shallow layer (under 300 m); beyond this, we did not notice a remarkable directional shear as in other studies. Even for a shallow layer as for this study case, we observed strong spatiotemporal variability of the turbulence kinetic energy dissipation rate. We also detected a channel connecting the layers above and below the low-level jet that may be an exchange channel of their properties.

Full access