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Abstract
Understanding near-surface atmospheric 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 atmospheric behaviors in northeastern Puerto Rico using a synthesis of data from lowland and montane locations under different land covers (forest, urban, and rural) during 2008–21, 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 that is 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 atmospheric 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 atmospheric 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 had persisted for 3 months, urban pollution decreased and cloud base may have increased.
Abstract
Understanding near-surface atmospheric 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 atmospheric behaviors in northeastern Puerto Rico using a synthesis of data from lowland and montane locations under different land covers (forest, urban, and rural) during 2008–21, 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 that is 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 atmospheric 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 atmospheric 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 had persisted for 3 months, urban pollution decreased and cloud base may have increased.
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.
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.
Abstract
Parts of southeast Alaska experienced record drought in 2019, followed by record daily precipitation in late 2020 with substantial impacts to human health and safety, energy resources, and fisheries. To help ascertain whether these types of events can be expected more frequently, this study investigated observed trends and projected changes of hydroclimatic extremes indices across southeast Alaska, including measures of precipitation variability, seasonality, magnitude, and type. Observations indicated mixed tendencies of interannual precipitation variability, but there were consistent trends toward warmer and wetter conditions. Projected changes were assessed using dynamically downscaled climate model simulations at 4-km spatial resolution from 2031 to 2060 that were compared with a historical period from 1981 to 2010 using two models—NCAR CCSM4 and GFDL CM3. Consistent directional changes were found for five of the analyzed indices. The CCSM indicated increased maximum 1-day precipitation (RX1; 12.6%), increased maximum consecutive 5-day precipitation (RX5; 7.4%), longer periods of consecutive dry days (CDD; 11.9%), fewer snow cover days (SNC; −21.4%) and lower snow fraction (SNF; −24.4%); for GFDL these changes were 19.8% for RX1, 16.0% for RX5, 20.1% for CDD, −21.9% for SNC, and −26.5% for SNF. Although both models indicated substantial snow losses, they also projected annual snowfall increases at high elevations; this occurred above 1500 m for CCSM and above 2500 m for GFDL. Significance testing was assessed at the 95% confidence level using Theil–Sen’s slope estimates for the observed time series and the Wilcoxon–Mann–Whitney U test for projected changes of the hydroclimatic extremes indices relative to their historical distributions.
Abstract
Parts of southeast Alaska experienced record drought in 2019, followed by record daily precipitation in late 2020 with substantial impacts to human health and safety, energy resources, and fisheries. To help ascertain whether these types of events can be expected more frequently, this study investigated observed trends and projected changes of hydroclimatic extremes indices across southeast Alaska, including measures of precipitation variability, seasonality, magnitude, and type. Observations indicated mixed tendencies of interannual precipitation variability, but there were consistent trends toward warmer and wetter conditions. Projected changes were assessed using dynamically downscaled climate model simulations at 4-km spatial resolution from 2031 to 2060 that were compared with a historical period from 1981 to 2010 using two models—NCAR CCSM4 and GFDL CM3. Consistent directional changes were found for five of the analyzed indices. The CCSM indicated increased maximum 1-day precipitation (RX1; 12.6%), increased maximum consecutive 5-day precipitation (RX5; 7.4%), longer periods of consecutive dry days (CDD; 11.9%), fewer snow cover days (SNC; −21.4%) and lower snow fraction (SNF; −24.4%); for GFDL these changes were 19.8% for RX1, 16.0% for RX5, 20.1% for CDD, −21.9% for SNC, and −26.5% for SNF. Although both models indicated substantial snow losses, they also projected annual snowfall increases at high elevations; this occurred above 1500 m for CCSM and above 2500 m for GFDL. Significance testing was assessed at the 95% confidence level using Theil–Sen’s slope estimates for the observed time series and the Wilcoxon–Mann–Whitney U test for projected changes of the hydroclimatic extremes indices relative to their historical distributions.
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.
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.
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.
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.
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.
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.
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.
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.
Abstract
The major tributary of the lower Colorado River, the Gila River, is a critical source of water for human and natural environments in the southwestern United States. Warmer and drier than the upper Colorado River basin, with less snow and a bimodal precipitation regime, the Gila River is controlled by a set of climatic conditions that is different from the controls on upper Colorado River flow. Unlike the Colorado River at Lees Ferry in Arizona, the upper Gila River and major Gila River tributaries, the Salt and Verde Rivers, do not yet reflect significant declines in annual streamflow, despite warming trends. Annual streamflow is dominated by cool-season precipitation, but the monsoon influence is discernable as well, variable across the basin and complicated by an inverse relationship with cool-season precipitation in the Salt and Verde River basins. Major multiyear streamflow droughts in these two basins have frequently been accompanied by wet monsoons, suggesting that monsoon precipitation may partially offset the impacts of a dry cool season. While statistically significant trends in annual streamflow are not evident, decreases in autumn and spring streamflow reflect warming temperatures and some decreases in spring precipitation. Because climatic controls vary with topography and the influence of the monsoon, the impact of warming on streamflow in the three subbasins is somewhat variable. However, given relationships between climate and streamflow, current trends in hydroclimate, and projections for the future, it would be prudent to expect declines in Gila River water supplies in the coming decades.
Significance Statement
This research investigates the climatic controls on the Gila River and its major tributaries, the Verde and Salt Rivers, to gain insights on how trends in climate may impact future water supply. The Gila River is the major tributary of the lower Colorado River, but, unlike the situation for the upper Colorado River, no significant decreasing trends in annual streamflow are evident despite warming temperatures. Climate–streamflow relationships are more complex in this part of the Colorado River basin, and several factors may be buffering streamflow to the impact of warming. However, given the key climatic controls on streamflow, current and emerging trends in climate, and projections for the future, declines in streamflow should be expected in the future.
Abstract
The major tributary of the lower Colorado River, the Gila River, is a critical source of water for human and natural environments in the southwestern United States. Warmer and drier than the upper Colorado River basin, with less snow and a bimodal precipitation regime, the Gila River is controlled by a set of climatic conditions that is different from the controls on upper Colorado River flow. Unlike the Colorado River at Lees Ferry in Arizona, the upper Gila River and major Gila River tributaries, the Salt and Verde Rivers, do not yet reflect significant declines in annual streamflow, despite warming trends. Annual streamflow is dominated by cool-season precipitation, but the monsoon influence is discernable as well, variable across the basin and complicated by an inverse relationship with cool-season precipitation in the Salt and Verde River basins. Major multiyear streamflow droughts in these two basins have frequently been accompanied by wet monsoons, suggesting that monsoon precipitation may partially offset the impacts of a dry cool season. While statistically significant trends in annual streamflow are not evident, decreases in autumn and spring streamflow reflect warming temperatures and some decreases in spring precipitation. Because climatic controls vary with topography and the influence of the monsoon, the impact of warming on streamflow in the three subbasins is somewhat variable. However, given relationships between climate and streamflow, current trends in hydroclimate, and projections for the future, it would be prudent to expect declines in Gila River water supplies in the coming decades.
Significance Statement
This research investigates the climatic controls on the Gila River and its major tributaries, the Verde and Salt Rivers, to gain insights on how trends in climate may impact future water supply. The Gila River is the major tributary of the lower Colorado River, but, unlike the situation for the upper Colorado River, no significant decreasing trends in annual streamflow are evident despite warming temperatures. Climate–streamflow relationships are more complex in this part of the Colorado River basin, and several factors may be buffering streamflow to the impact of warming. However, given the key climatic controls on streamflow, current and emerging trends in climate, and projections for the future, declines in streamflow should be expected in the future.
Abstract
It has been 10 years since the start of the Syrian uprisings. While relative stability is improving overall, a new disaster, wildfires, impacted an already food-insecure population by burning through key production areas, damaging crops, soil, and livestock and causing air quality to deteriorate. As observed with remotely sensed data, fire affected 4.8% of Syria in 2019, as compared with the average 0.2%, and most fires were observed within agricultural land in the northeast. Abnormal amounts of rainfall during the 2019 growing season and, consequently, high soil moisture explained about 62% of the drastic increase in the burned area extent. In contrast, in 2020, fires continued despite the average amount of rainfall. Extremely high temperature could partially explain a 10-fold increase in the extent of burned area in 2020 but only within forested regions in the northwest. We argue that the abrupt changes in Syria’s fire activity were driven by the complex interactions among conflict, migration, land use, and climate. On one side, the ongoing conflict leads to a drastic increase in the number of accidental and deliberate fires and reduced capacity for fire response. On the other side, years of insecurity, widespread displacement, and economic instability left no choice for locals other than exploiting fires to remove natural vegetation for expanding farming, logging, and charcoal trading. The loss of agricultural production and natural vegetation to fire can have serious implications for food security, soil property, biodiversity, and ecosystem services, which can further exacerbate the already unstable economy and make ongoing violence even more intense.
Abstract
It has been 10 years since the start of the Syrian uprisings. While relative stability is improving overall, a new disaster, wildfires, impacted an already food-insecure population by burning through key production areas, damaging crops, soil, and livestock and causing air quality to deteriorate. As observed with remotely sensed data, fire affected 4.8% of Syria in 2019, as compared with the average 0.2%, and most fires were observed within agricultural land in the northeast. Abnormal amounts of rainfall during the 2019 growing season and, consequently, high soil moisture explained about 62% of the drastic increase in the burned area extent. In contrast, in 2020, fires continued despite the average amount of rainfall. Extremely high temperature could partially explain a 10-fold increase in the extent of burned area in 2020 but only within forested regions in the northwest. We argue that the abrupt changes in Syria’s fire activity were driven by the complex interactions among conflict, migration, land use, and climate. On one side, the ongoing conflict leads to a drastic increase in the number of accidental and deliberate fires and reduced capacity for fire response. On the other side, years of insecurity, widespread displacement, and economic instability left no choice for locals other than exploiting fires to remove natural vegetation for expanding farming, logging, and charcoal trading. The loss of agricultural production and natural vegetation to fire can have serious implications for food security, soil property, biodiversity, and ecosystem services, which can further exacerbate the already unstable economy and make ongoing violence even more intense.
Abstract
Cropland abandonment has been a major land-use concern, threatening food security globally. Understanding the factors contributing to cropland abandonment advances land-use change science and provides essential information for policy making, both of which aim to improve agriculture land management. Despite many studies conducted on this topic, we still lack in-depth understanding on how feedbacks from the natural system influence cropland-use decisions at the household level in the human system. We fill this knowledge gap by conducting this study in the Middle Hills of Nepal, where community forestry is an integral part of the land-use system. We collected qualitative data through focus-group discussions, key-informant interviews, and review of local community-forest management documents, and we collected quantitative socioeconomic data through a household survey of 415 households. We geolocated 1264 cropland parcels owned by these households and recorded their use statuses. We found that there is an increasing trend of cropland abandonment that is due to multiple socioeconomic, ecological, and biophysical factors. A higher likelihood of cropland abandonment is linked to households that have more out-migrants, female heads, nonagricultural occupation of the household heads, and larger areas of agriculture landholding. The study also found that cropland parcels that are far from the households, close to the forest edge, and on steeper slopes are more likely to be abandoned. These findings provide key information for policy makers to devise effective measures on managing cropland and developing sustainable agriculture in rural Nepal.
Abstract
Cropland abandonment has been a major land-use concern, threatening food security globally. Understanding the factors contributing to cropland abandonment advances land-use change science and provides essential information for policy making, both of which aim to improve agriculture land management. Despite many studies conducted on this topic, we still lack in-depth understanding on how feedbacks from the natural system influence cropland-use decisions at the household level in the human system. We fill this knowledge gap by conducting this study in the Middle Hills of Nepal, where community forestry is an integral part of the land-use system. We collected qualitative data through focus-group discussions, key-informant interviews, and review of local community-forest management documents, and we collected quantitative socioeconomic data through a household survey of 415 households. We geolocated 1264 cropland parcels owned by these households and recorded their use statuses. We found that there is an increasing trend of cropland abandonment that is due to multiple socioeconomic, ecological, and biophysical factors. A higher likelihood of cropland abandonment is linked to households that have more out-migrants, female heads, nonagricultural occupation of the household heads, and larger areas of agriculture landholding. The study also found that cropland parcels that are far from the households, close to the forest edge, and on steeper slopes are more likely to be abandoned. These findings provide key information for policy makers to devise effective measures on managing cropland and developing sustainable agriculture in rural Nepal.
