A substantial fraction of the freshwater needed to sustain natural and anthropogenic systems has its origin in mountain regions. Mountain areas are highly vulnerable to climate change, and anthropogenically caused changes to mountain hydrology are documented for most major mountain ranges. Yet, our current methods for observing mountain precipitation and its changes are extremely limited due to, high spatial heterogeneity of precipitation in complex topography, sampling biases from preferentially measuring precipitation in valleys, challenges in observing solid precipitation, the prohibitive cost in establishing and maintaining long term benchmarking sites, and severe measurement deficiencies in most remotely sensing products. These factors cause large uncertainties in precipitation estimates (spatial and temporal) over mountainous areas. In addition to precipitation, mountain hydrology is heavily influenced by snow redistribution and transfer across catchments, evapotranspiration, accumulation and melt, and anthropogenic water management.
Recent work that used water budget modeling over mountain catchments revealed that gridded precipitation estimates underestimate mountain precipitation by up to a factor of two or more. Under sampling biases were identified in all major mountain ranges but are most severe in snow-dominated regions and areas with low-density gauge networks such as the Andes, Himalayas, New Zealand and Australian alpine regions or Alaskan Rocky mountains. Also, remote sensing precipitation analyses are heavily underestimating accumulated precipitation over these regions mainly due to radar beam blocking, underestimations of orographic enhancement of precipitation in satellite observations, and convoluted measurements of snowfall. There is increasing evidence that kilometer-scale models might have bypassed our observational capabilities in prescribing integrated precipitation in mountain catchments, opening new opportunities to constrain hydrologic processes in mountain regions. Our inability to observationally constrain precipitation in areas of complex topography limits our capability to quantify, conceptualize and model relevant hydrologic processes in these regions. Most importantly, it obscures our ability to detect and predict changes in mountain hydrology, inhibiting early mitigation and adaptation efforts that could attenuate severe changes to mountain ecosystems and water resources.
This Research Topic welcomes Original Research articles, Perspectives, Brief Research Reports, Method focused articles, Reviews, and Opinions from observers and modelers focusing on challenges and opportunities in quantifying precipitation in mountain regions. We welcome contributions focusing on hydrology, meteorology, in-situ and remote sensing, and high-resolution atmospheric modeling. Data-driven approaches including methods that combine different sources of observational and modeling information are also welcome.
A substantial fraction of the freshwater needed to sustain natural and anthropogenic systems has its origin in mountain regions. Mountain areas are highly vulnerable to climate change, and anthropogenically caused changes to mountain hydrology are documented for most major mountain ranges. Yet, our current methods for observing mountain precipitation and its changes are extremely limited due to, high spatial heterogeneity of precipitation in complex topography, sampling biases from preferentially measuring precipitation in valleys, challenges in observing solid precipitation, the prohibitive cost in establishing and maintaining long term benchmarking sites, and severe measurement deficiencies in most remotely sensing products. These factors cause large uncertainties in precipitation estimates (spatial and temporal) over mountainous areas. In addition to precipitation, mountain hydrology is heavily influenced by snow redistribution and transfer across catchments, evapotranspiration, accumulation and melt, and anthropogenic water management.
Recent work that used water budget modeling over mountain catchments revealed that gridded precipitation estimates underestimate mountain precipitation by up to a factor of two or more. Under sampling biases were identified in all major mountain ranges but are most severe in snow-dominated regions and areas with low-density gauge networks such as the Andes, Himalayas, New Zealand and Australian alpine regions or Alaskan Rocky mountains. Also, remote sensing precipitation analyses are heavily underestimating accumulated precipitation over these regions mainly due to radar beam blocking, underestimations of orographic enhancement of precipitation in satellite observations, and convoluted measurements of snowfall. There is increasing evidence that kilometer-scale models might have bypassed our observational capabilities in prescribing integrated precipitation in mountain catchments, opening new opportunities to constrain hydrologic processes in mountain regions. Our inability to observationally constrain precipitation in areas of complex topography limits our capability to quantify, conceptualize and model relevant hydrologic processes in these regions. Most importantly, it obscures our ability to detect and predict changes in mountain hydrology, inhibiting early mitigation and adaptation efforts that could attenuate severe changes to mountain ecosystems and water resources.
This Research Topic welcomes Original Research articles, Perspectives, Brief Research Reports, Method focused articles, Reviews, and Opinions from observers and modelers focusing on challenges and opportunities in quantifying precipitation in mountain regions. We welcome contributions focusing on hydrology, meteorology, in-situ and remote sensing, and high-resolution atmospheric modeling. Data-driven approaches including methods that combine different sources of observational and modeling information are also welcome.