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Abstract
Large expanses of snow leopard habitat overlap with extensively used areas for livestock grazing. A fundamental question for conservationists is to determine whether livestock production can be reconciled with the conservation of rare and threatened large carnivores. Therefore, numerous studies focus on the relationship between carnivore densities and space use and environmental, anthropogenic, and topographic variables. Using snow leopard sign surveys in areas with high and low grazing disturbance, Hong et al. posit that livestock grazing directly impacts fine-scale habitat selection by snow leopards. The authors recommend controlling livestock grazing to help restore habitat complexity and alpine environment diversity. However, the approach by which Hong et al. have reached this conclusion is inadequate and is based on a methodology that fails to address the research question appropriately. We argue that 1) identification of a biologically relevant scale of study is the first essential step toward inferring carnivore–habitat relationships, 2) the authors draw inconsistent conclusions from their data on sign densities in high and low grazing disturbance areas, 3) ideally, the snow leopard–livestock relationship needs to be examined across a gradient of livestock grazing intensities and at multiple spatial scales, and 4) it is inappropriate to draw conclusions for landscape/regional scales from a study conducted at a finer and undefined scale. We suggest that future studies should clearly define the scale of the study, identify appropriate habitat variables of interest, and use meaningful measurement instruments to serve as proxies for variables of interest.
Abstract
Large expanses of snow leopard habitat overlap with extensively used areas for livestock grazing. A fundamental question for conservationists is to determine whether livestock production can be reconciled with the conservation of rare and threatened large carnivores. Therefore, numerous studies focus on the relationship between carnivore densities and space use and environmental, anthropogenic, and topographic variables. Using snow leopard sign surveys in areas with high and low grazing disturbance, Hong et al. posit that livestock grazing directly impacts fine-scale habitat selection by snow leopards. The authors recommend controlling livestock grazing to help restore habitat complexity and alpine environment diversity. However, the approach by which Hong et al. have reached this conclusion is inadequate and is based on a methodology that fails to address the research question appropriately. We argue that 1) identification of a biologically relevant scale of study is the first essential step toward inferring carnivore–habitat relationships, 2) the authors draw inconsistent conclusions from their data on sign densities in high and low grazing disturbance areas, 3) ideally, the snow leopard–livestock relationship needs to be examined across a gradient of livestock grazing intensities and at multiple spatial scales, and 4) it is inappropriate to draw conclusions for landscape/regional scales from a study conducted at a finer and undefined scale. We suggest that future studies should clearly define the scale of the study, identify appropriate habitat variables of interest, and use meaningful measurement instruments to serve as proxies for variables of interest.
Abstract
We thank Luxom and Sharma for their attention to and comments on our study. In recent years, livestock have been expanding into snow leopard habitat, and we conducted this study to examine the effects of that encroachment on snow leopard habitat within Wolong Nature Reserve. Specific responses to Luxom and Sharma’s comments include the following: 1) Many habitat factors influence carnivore–habitat relationships at varying spatial scales, and it is difficult for any single study to address the full suite of factors acting across all scales of selection. Given this fact and the limited spatial scale of our snow leopard sign survey, we mainly focused on snow leopard space use and microhabitat selection. 2) Our results are not necessarily conflicting, but more research is required to further explain how high sign densities, concentrated space use, and weak habitat selection behaviors might relate to each other. 3) We agree that examining a gradient of grazing intensities would be preferable, but because of the difficulty in collecting sufficient field data and the nature of livestock grazing patterns in our study area, we think that dividing our survey area into high- and low-grazing-disturbance areas was appropriate. 4) The original intent of this study was to examine habitat factors and response to livestock within our study area in Wolong Nature Reserve, and we did not intend for our specific results to be used for management recommendations beyond Wolong but instead encourage similar studies to be conducted in other areas.
Abstract
We thank Luxom and Sharma for their attention to and comments on our study. In recent years, livestock have been expanding into snow leopard habitat, and we conducted this study to examine the effects of that encroachment on snow leopard habitat within Wolong Nature Reserve. Specific responses to Luxom and Sharma’s comments include the following: 1) Many habitat factors influence carnivore–habitat relationships at varying spatial scales, and it is difficult for any single study to address the full suite of factors acting across all scales of selection. Given this fact and the limited spatial scale of our snow leopard sign survey, we mainly focused on snow leopard space use and microhabitat selection. 2) Our results are not necessarily conflicting, but more research is required to further explain how high sign densities, concentrated space use, and weak habitat selection behaviors might relate to each other. 3) We agree that examining a gradient of grazing intensities would be preferable, but because of the difficulty in collecting sufficient field data and the nature of livestock grazing patterns in our study area, we think that dividing our survey area into high- and low-grazing-disturbance areas was appropriate. 4) The original intent of this study was to examine habitat factors and response to livestock within our study area in Wolong Nature Reserve, and we did not intend for our specific results to be used for management recommendations beyond Wolong but instead encourage similar studies to be conducted in other areas.
Abstract
Most agricultural soils have experienced substantial soil organic carbon losses in time. These losses motivate recent calls to restore organic carbon in agricultural lands to improve biogeochemical cycling and for climate change mitigation. Declines in organic carbon also reduce soil infiltration and water holding capacity, which may have important effects on regional hydrology and climate. To explore the regional hydroclimate impacts of soil organic carbon changes, we conduct new global climate model experiments with NASA Goddard Institute for Space Studies ModelE that include spatially explicit soil organic carbon concentrations associated with different human land management scenarios. Compared to a “no land use” case, a year 2010 soil degradation scenario, in which organic carbon content (OCC; weight %) is reduced by a factor of ∼0.12 on average across agricultural soils, resulted in soil moisture losses between 0.5 and 1 temporal standard deviations over eastern Asia, northern Europe, and the eastern United States. In a more extreme idealized scenario where OCC is reduced uniformly by 0.66 across agricultural soils, soil moisture losses exceed one standard deviation in both hemispheres. Within the model, these soil moisture declines occur primarily due to reductions in porosity (and to a lesser extent infiltration) that overall soil water holding capacity. These results demonstrate that changes in soil organic carbon can have meaningful, large-scale effects on regional hydroclimate and should be considered in climate model evaluations and developments. Further, this also suggests that soil restoration efforts targeting the carbon cycle are likely to have additional benefits for improving drought resilience.
Abstract
Most agricultural soils have experienced substantial soil organic carbon losses in time. These losses motivate recent calls to restore organic carbon in agricultural lands to improve biogeochemical cycling and for climate change mitigation. Declines in organic carbon also reduce soil infiltration and water holding capacity, which may have important effects on regional hydrology and climate. To explore the regional hydroclimate impacts of soil organic carbon changes, we conduct new global climate model experiments with NASA Goddard Institute for Space Studies ModelE that include spatially explicit soil organic carbon concentrations associated with different human land management scenarios. Compared to a “no land use” case, a year 2010 soil degradation scenario, in which organic carbon content (OCC; weight %) is reduced by a factor of ∼0.12 on average across agricultural soils, resulted in soil moisture losses between 0.5 and 1 temporal standard deviations over eastern Asia, northern Europe, and the eastern United States. In a more extreme idealized scenario where OCC is reduced uniformly by 0.66 across agricultural soils, soil moisture losses exceed one standard deviation in both hemispheres. Within the model, these soil moisture declines occur primarily due to reductions in porosity (and to a lesser extent infiltration) that overall soil water holding capacity. These results demonstrate that changes in soil organic carbon can have meaningful, large-scale effects on regional hydroclimate and should be considered in climate model evaluations and developments. Further, this also suggests that soil restoration efforts targeting the carbon cycle are likely to have additional benefits for improving drought resilience.
Abstract
Achievement of the United Nations Sustainable Development Goals (SDGs) is contingent on understanding the potential interactions among human and natural systems. In Kenya, the goal of conserving and expanding forest cover to achieve SDG 15 “Life on Land” may be related to other SDGs because it plays a role in regulating some aspects of Kenyan precipitation. We present a 40-yr analysis of the sources of precipitation in Kenya and the fate of the evaporation that arises from within Kenya. Using MERRA-2 climate reanalysis and the Water Accounting Model 2 layers, we examine the annual and seasonal changes in moisture sources and sinks. We find that most of Kenya’s precipitation originates as oceanic evaporation but that 10% of its precipitation originates as evaporation within Kenya. This internal recycling is concentrated in the mountainous and forested Kenyan highlands, with some locations recycling more than 15% of evaporation to Kenyan precipitation. We also find that 75% of Kenyan evaporation falls as precipitation elsewhere over land, including 10% in Kenya, 25% in the Democratic Republic of the Congo, and around 5% falling in Tanzania and Uganda. Further, we find a positive relationship between increasing rates of moisture recycling and fractional forest cover within Kenya. By beginning to understand both the seasonal and biophysical interactions taking place, we may begin to understand the types of leverage points that exist for integrated atmospheric water cycle management. These findings have broader implications for disentangling environmental management and conservation and have relevance for large-scale discussions about sustainable development.
Abstract
Achievement of the United Nations Sustainable Development Goals (SDGs) is contingent on understanding the potential interactions among human and natural systems. In Kenya, the goal of conserving and expanding forest cover to achieve SDG 15 “Life on Land” may be related to other SDGs because it plays a role in regulating some aspects of Kenyan precipitation. We present a 40-yr analysis of the sources of precipitation in Kenya and the fate of the evaporation that arises from within Kenya. Using MERRA-2 climate reanalysis and the Water Accounting Model 2 layers, we examine the annual and seasonal changes in moisture sources and sinks. We find that most of Kenya’s precipitation originates as oceanic evaporation but that 10% of its precipitation originates as evaporation within Kenya. This internal recycling is concentrated in the mountainous and forested Kenyan highlands, with some locations recycling more than 15% of evaporation to Kenyan precipitation. We also find that 75% of Kenyan evaporation falls as precipitation elsewhere over land, including 10% in Kenya, 25% in the Democratic Republic of the Congo, and around 5% falling in Tanzania and Uganda. Further, we find a positive relationship between increasing rates of moisture recycling and fractional forest cover within Kenya. By beginning to understand both the seasonal and biophysical interactions taking place, we may begin to understand the types of leverage points that exist for integrated atmospheric water cycle management. These findings have broader implications for disentangling environmental management and conservation and have relevance for large-scale discussions about sustainable development.
Abstract
The middle Rio Grande is a vital source of water for irrigation in the region. Climate change is impacting regional hydrology and is likely to put additional stress on a water supply that is already stretched thin. To gain insight on the hydrologic effects of climate change on reservoir storage, a simple water balance model was used to simulate the Elephant Butte–Caballo Reservoir system (southern New Mexico). The water balance model was forced by hydrologic inputs generated by 97 climate simulations derived from CMIP5 global climate models, coupled to a surface hydrologic model. Results suggest that the percentage of years that reservoir releases satisfy agricultural water rights allocations over the next 50 years (2021–70) will decrease relative to the past 50 years (1971–2020). The modeling also projects an increase in multiyear drought events that hinder reservoir management strategies to maintain high storage levels. In most cases, changes in reservoir inflows from distant upstream snowmelt is projected to have a greater influence on reservoir storage and water availability downstream of the reservoirs than will changes in local evaporation and precipitation from the reservoir surfaces.
Abstract
The middle Rio Grande is a vital source of water for irrigation in the region. Climate change is impacting regional hydrology and is likely to put additional stress on a water supply that is already stretched thin. To gain insight on the hydrologic effects of climate change on reservoir storage, a simple water balance model was used to simulate the Elephant Butte–Caballo Reservoir system (southern New Mexico). The water balance model was forced by hydrologic inputs generated by 97 climate simulations derived from CMIP5 global climate models, coupled to a surface hydrologic model. Results suggest that the percentage of years that reservoir releases satisfy agricultural water rights allocations over the next 50 years (2021–70) will decrease relative to the past 50 years (1971–2020). The modeling also projects an increase in multiyear drought events that hinder reservoir management strategies to maintain high storage levels. In most cases, changes in reservoir inflows from distant upstream snowmelt is projected to have a greater influence on reservoir storage and water availability downstream of the reservoirs than will changes in local evaporation and precipitation from the reservoir surfaces.
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.
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.
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.
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.
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.
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.
Abstract
Rainfall-induced landsliding is a global and systemic hazard that is 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 the availability of relevant rainfall measurements in many landslide prone areas. In the last decade, global satellite multisensor precipitation products (SMPP) 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 two SMPPs (IMERG and GSMaP) and one hybrid product [Multi-Source Weighted-Ensemble Precipitation (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-yr 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. In addition, the few (four) landslide events caused by short and localized storms are most often undetected. We also show that, in at least five cases, the SMPP’s spatial pattern of rainfall anomaly matches landsliding less well than does 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.
Significance Statement
Rainfall-induced landsliding is a global hazard that is expected to increase as a result of anthropogenic climate change. Our ability to understand and mitigate this hazard is strongly limited by the lack of rainfall measurements in mountainous areas. Here, we perform the first global assessment of the potential of three high-resolution precipitation datasets, derived from satellite observations, to capture the rainfall characteristics of 20 storms that led to widespread landsliding. We find that, accounting for past extreme rainfall statistics (i.e., the rainfall returning every 10 years), most storms causing landslides are retrieved by the datasets. However, the shortest storms (i.e., ∼3 h) are often undetected, and the detailed spatial pattern of extreme rainfall often appears to be distorted. Our work opens new ways to study global landslide hazard but also warns against overinterpreting rainfall derived from satellites.
Abstract
Rainfall-induced landsliding is a global and systemic hazard that is 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 the availability of relevant rainfall measurements in many landslide prone areas. In the last decade, global satellite multisensor precipitation products (SMPP) 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 two SMPPs (IMERG and GSMaP) and one hybrid product [Multi-Source Weighted-Ensemble Precipitation (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-yr 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. In addition, the few (four) landslide events caused by short and localized storms are most often undetected. We also show that, in at least five cases, the SMPP’s spatial pattern of rainfall anomaly matches landsliding less well than does 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.
Significance Statement
Rainfall-induced landsliding is a global hazard that is expected to increase as a result of anthropogenic climate change. Our ability to understand and mitigate this hazard is strongly limited by the lack of rainfall measurements in mountainous areas. Here, we perform the first global assessment of the potential of three high-resolution precipitation datasets, derived from satellite observations, to capture the rainfall characteristics of 20 storms that led to widespread landsliding. We find that, accounting for past extreme rainfall statistics (i.e., the rainfall returning every 10 years), most storms causing landslides are retrieved by the datasets. However, the shortest storms (i.e., ∼3 h) are often undetected, and the detailed spatial pattern of extreme rainfall often appears to be distorted. Our work opens new ways to study global landslide hazard but also warns against overinterpreting rainfall derived from satellites.
