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The widely used open-source community Noah with multi-parameterization options (Noah-MP) land surface model (LSM) is designed for applications ranging from uncoupled land surface hydrometeorological and ecohydrological process studies to coupled numerical weather prediction and decadal global or regional climate simulations. It has been used in many coupled community weather, climate, and hydrology models. In this study, we modernize and refactor the Noah-MP LSM by adopting modern Fortran code standards and data structures, which substantially enhance the model modularity, interoperability, and applicability. The modernized Noah-MP is released as the version 5.0 (v5.0), which has five key features: (1) enhanced modularization as a result of re-organizing model physics into individual process-level Fortran module files, (2) an enhanced data structure with new hierarchical data types and optimized variable declaration and initialization structures, (3) an enhanced code structure and calling workflow as a result of leveraging the new data structure and modularization, (4) enhanced (descriptive and self-explanatory) model variable naming standards, and (5) enhanced driver and interface structures to be coupled with the host weather, climate, and hydrology models. In addition, we create a comprehensive technical documentation of the Noah-MP v5.0 and a set of model benchmark and reference datasets. The Noah-MP v5.0 will be coupled to various weather, climate, and hydrology models in the future. Overall, the modernized Noah-MP allows a more efficient and convenient process for future model developments and applications.

Because use of high-resolution hydrologic models is becoming more widespread and estimates are made over large domains, there is a pressing need for systematic evaluation of their performance. Most evaluation efforts to date have focused on smaller basins that have been relatively undisturbed by human activity, but there is also a need to benchmark model performance more comprehensively, including basins impacted by human activities. This study benchmarks the long-term performance of two process-oriented, high-resolution, continental-scale hydrologic models that have been developed to assess water availability and risks in the United States (US): the National Water Model v2.1 application of WRF-Hydro (NWMv2.1) and the National Hydrologic Model v1.0 application of the Precipitation–Runoff Modeling System (NHMv1.0). The evaluation is performed on 5390 streamflow gages from 1983 to 2016 (∼ 33 years) at a daily time step, including both natural and human-impacted catchments, representing one of the most comprehensive evaluations over the contiguous US. Using the Kling–Gupta efficiency as the main evaluation metric, the models are compared against a climatological benchmark that accounts for seasonality. Overall, the model applications show similar performance, with better performance in minimally disturbed basins than in those impacted by human activities. Relative regional differences are also similar: the best performance is found in the Northeast, followed by the Southeast, and generally worse performance is found in the Central and West areas. For both models, about 80 % of the sites exceed the seasonal climatological benchmark. Basins that do not exceed the climatological benchmark are further scrutinized to provide model diagnostics for each application. Using the underperforming subset, both models tend to overestimate streamflow volumes in the West, which could be attributed to not accounting for human activities, such as active management. Both models underestimate flow variability, especially the highest flows; this was more pronounced for NHMv1.0. Low flows tended to be overestimated by NWMv2.1, whereas there were both over and underestimations for NHMv1.0, but they were less severe. Although this study focused on model diagnostics for underperforming sites based on the seasonal climatological benchmark, metrics for all sites for both model applications are openly available online.

A detailed, physically based, one dimensional column snowpack model (Crocus) has been incorporated into the hydrological model, Weather Research and Forecasting (WRF)-Hydro, to allow for direct surface mass balance simulation of glaciers and subsequent modeling of meltwater discharge from glaciers. The new system (WRF-Hydro/Glacier) is only activated over a priori designated glacier areas. This glacier area is initialized with observed glacier thickness and assumed to be pure ice (with corresponding ice density). This allows for melting of the glacier to continue after all accumulated snow has melted. Furthermore, the simulation of surface albedo over the glacier is more realistic, as surface albedo is represented by snow, where there is accumulated snow, and glacier ice, when all accumulated snow is melted. To evaluate the WRF-Hydro/Glacier system over a glacier in southern Norway, WRF atmospheric model simulations were downscaled to 1 km grid spacing. This provided meteorological forcing data to the WRF-Hydro/Glacier system at 100 m grid spacing for surface and streamflow simulation. Evaluation of the WRF downscaling showed a good comparison with in situ meteorological observations for most of the simulation period. The WRF-Hydro/Glacier system reproduced the glacier surface winter/summer and net mass balance, snow depth, surface albedo and glacier runoff well compared to observations. The improved estimation of albedo has an appreciable impact on the discharge from the glacier during frequent precipitation periods. We have shown that the integrated snowpack system allows for improved glacier surface mass balance studies and hydrological studies.

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.

The Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) project seeks to understand the feedbacks and inter-relationships between hydrology, biogenic emissions, carbon assimilation, aerosol properties, clouds and associated feedbacks within water-limited ecosystems. The Manitou Experimental Forest Observatory (MEFO) was established in 2008 by the National Center for Atmospheric Research to address many of the BEACHON research objectives, and it now provides a fixed field site with significant infrastructure. MEFO is a mountainous, semi-arid ponderosa pine-dominated forest site that is normally dominated by clean continental air but is periodically influenced by anthropogenic sources from Colorado Front Range cities. This article summarizes the past and ongoing research activities at the site, and highlights some of the significant findings that have resulted from these measurements. These activities include - soil property measurements; - hydrological studies; - measurements of high-frequency turbulence parameters; - eddy covariance flux measurements of water, energy, aerosols and carbon dioxide through the canopy; - determination of biogenic and anthropogenic volatile organic compound emissions and their influence on regional atmospheric chemistry; - aerosol number and mass distributions; - chemical speciation of aerosol particles; - characterization of ice and cloud condensation nuclei; - trace gas measurements; and - model simulations using coupled chemistry and meteorology. In addition to various long-term continuous measurements, three focused measurement campaigns with state-of-the-art instrumentation have taken place since the site was established, and two of these studies are the subjects of this special issue: BEACHON-ROCS (Rocky Mountain Organic Carbon Study, 2010) and BEACHON-RoMBAS (Rocky Mountain Biogenic Aerosol Study, 2011).

We present the first eddy covariance flux measurements of volatile organic compounds (VOCs) using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS) above a ponderosa pine forest in Colorado, USA. The high mass resolution of the PTR-TOF-MS enabled the identification of chemical sum formulas. During a 30 day measurement period in August and September 2010, 649 different ion mass peaks were detected in the ambient air mass spectrum (including primary ions and mass calibration compounds). Eddy covariance with the vertical wind speed was calculated for all ion mass peaks. On a typical day, 17 ion mass peaks, including protonated parent compounds, their fragments and isotopes as well as VOC-H+-water clusters, showed a significant flux with daytime average emissions above a reliable flux threshold of 0.1 mg compound m−2 h−1. These ion mass peaks could be assigned to seven compound classes. The main flux contributions during daytime (10:00–18:00 LT) are attributed to the sum of 2-methyl-3-buten-2-ol (MBO) and isoprene (50%), methanol (12%), the sum of acetic acid and glycolaldehyde (10%) and the sum of monoterpenes (10%). The total MBO + isoprene flux was composed of 10% isoprene and 90% MBO. There was good agreement between the light- and temperature dependency of the sum of MBO and isoprene observed for this work and those of earlier studies. The above canopy flux measurements of the sum of MBO and isoprene and the sum of monoterpenes were compared to emissions calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1). The best agreement between MEGAN 2.1 and measurements was reached using emission factors determined from site-specific leaf cuvette measurements. While the modeled and measured MBO + isoprene fluxes agree well, the emissions of the sum of monoterpenes is underestimated by MEGAN 2.1. This is expected as some factors impacting monoterpene emissions, such as physical damage of needles and branches due to storms, are not included in MEGAN 2.1. After a severe hailstorm event, 22 ion mass peaks (attributed to six compound classes plus some unknown compounds) showed an elevated flux for the two following days. The sum of monoterpene emissions was 4–23 times higher compared to emissions prior to the hailstorm while MBO emissions remained unchanged. The monoterpene emission (in mg compound m−2) during this measurement period is underestimated by 40% if the effect of this disturbance source is not considered.

In this screening study, biogenic volatile organic compound (BVOC) emissions from intact branches of lodgepole pine (Pinus contorta) trees were measured from trees at two forested sites that have been impacted differently by the mountain pine beetle (MPB), with one having higher mortality and the other with lower mortality. Differences in the amounts and chemical diversity of BVOC between the two sites and from apparently healthy trees versus trees in different stages of MPB attack are presented, as well as (for one site) observed seasonal variability in emissions. A brief comparison is made of geological and climatic characteristics as well as prior disturbances (both natural and man-made) at each site. Trees sampled at the site experiencing high MPB-related tree mortality had lower chemodiversity in terms of monoterpene (MT) emission profiles, while profiles were more diverse at the lower-mortality site. Also at the higher-mortality site, MPB-infested trees in various stages of decline had lower emissions of sesquiterpenes (SQTs) compared to healthy trees, while at the site with lower mortality, MPB-survivors had significantly higher SQT emissions during part of the growing season when compared to both uninfested and newly infested trees. SQT profiles differed between the two sites and, like monoterpene and oxygenated VOC profiles, varied through the season. For the low-mortality site in which repeated measurements were made over the course of the early summer–late fall, higher chemical diversity was observed in early- compared to late-season measurements for all compound classes investigated (MT, oxygenated VOC, and SQT), with the amount of change appearing to correlate to the MPB status of the trees studied. Emissions of 2-methyl-3-buten-2-ol (MBO) had a distinct seasonal signal but were not much different between healthy or infested trees, except in trees with dead needles, from which emissions of this compound were negligible, and in late-season MPB survivors, in which they were higher than in newly infested or uninfested trees. Emissions of SQT were significantly higher in the MPB survivors during both mid- and late-season sampling at the low-mortality site. The changes in emissions could have implications for regional air quality and climate through changes in ozone and aerosol distributions, although this study was designed as a preliminary screening effort and not enough individuals were sampled for all of the observed differences to be statistically demonstrated. Despite this, the compelling differences in emissions observed between the sites and individual trees with differing MPB-infestation statuses and the potential impacts these have on regional atmospheric chemistry argue for further research in this topic.

Although groundwater is a major resource of water in the western US, little research has been done on the impacts of climate change on groundwater storage and recharge in the West. Here we assess the impact of projected changes in climate on groundwater recharge in the near (2021-2050) and far (2071-2100) future across the western US. Recharge is expected to decrease slightly (highly certain) in the West (-1.6%) and Southwest (-2.9%) regions in the near future and decrease considerably (highly certain) in the South region (-10.6%) in the far future. The Northern Rockies region is expected to get more recharge (highly certain) in both the near (+5.0%) and far (+9.0%) future. In general, southern portions of the western US are expected to get less recharge in the future and northern portions will get more. This study also shows that climate change interacts with land surface properties to affect the amount of recharge that occurs in the future.

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.