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Changes in precipitation patterns with climate change could have important impacts on human and natural systems. Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) report trends in daily precipitation patterns over the last five decades in the western United States, focusing on meteorological drought. They report that dry intervals (calculated at the annual or seasonal level) have increased across much of the southwestern U.S., with statistical assessment suggesting the results are statistically robust. However, Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) preprocess their annual (or seasonal) averages to compute 5‐year moving window averages before using established statistical techniques for trend analysis that assume independence about some fixed trend. Here we show that the moving window preprocessing violates that independence assumption and inflates the statistical significance of their trend estimates. This raises questions about the robustness of their results. We conclude by discussing the difficulty of adjusting for spatial structure when assessing time trends in a regional context. Plain Language Summary: A recent paper reports trends in drought in the western United States, in particular increases in drought in the southwestern United States, based on changes in the lengths of time intervals without precipitation. In this "comment" we note that the preprocessing approach used in the paper artificially increases the apparent statistical signal in the data and caution that the evidence for the trends reported is not as strong as presented in the paper. We conclude by discussing the difficulty of estimating trends in a statistically rigorous fashion across multiple weather stations. Key Points: Statistical uncertainty about trends in droughts in the southwestern US is larger than reported in a recent GRL letter [ABSTRACT FROM AUTHOR]

Paciorek and Wehner raise important questions around our use of the Mann‐Kendall nonparametric trend test on smoothed data for analyzing long‐term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p‐values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends). Plain Language Summary: Our colleagues Drs. Paciorek and Wehner have raised concerns about our paper (Zhang et al., 2021, https://doi.org/10.1029/2020gl092293), which showed widespread increases in the duration of drought events over the last five decades in the western United States. They point out that our decision to smooth the data using a moving average inflated the number of weather stations at which the trends toward longer droughts were deemed significant by a statistical test. We agree with them on this point, and we have recomputed all our results using unsmoothed data to determine the impacts. We find that for most stations and regions, trend magnitudes remained largely unchanged, with many stations nearby one another often suggesting similar trends. Finally, we agree with Paciorek and Wehner that there is a lack of statistical methods to test such coherent regional patterns, and we caution that over‐reliance on p‐values limits the power of regional data to identify important climate trends. Key Points: We agree that smoothing to 5‐year moving windows introduced serial correlation into time series of annual statistics of daily rainfall data, inflating the number of weather stations individually showing significant trends (p < 0.05) with the Mann‐Kendall testRecomputation with unsmoothed values produced substantially the same dry intervals trend magnitude and direction at most stations individually and had only minimal impacts on dry interval trends computed for National Ecological Observatory Network domains using the Regional Kendall testNo perfect statistical approach leverages the capacity of coherent regional patterns among spatially correlated weather stations, and an over‐reliance on p‐values as a binary (significant vs. insignificant) determinant of trends limits the power of regional data [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic‐scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long‐wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations. Plain Language Summary: Atmospheric rivers (ARs) are a weather pattern that brings high amounts of atmospheric water and winds in a relatively narrow region. ARs are typically considered a "west coast" phenomenon, largely because the majority of the scientific research on ARs has focused on ARs in western coastal regions: particularly the western United States (US). ARs occur in continental interiors, but there has been some debate about whether these ARs represent the same type of weather as those in western coastal regions. This paper uses two objective methods for identifying ARs and finds times when ARs are present in three locations in the eastern half of the US: Norman, OK, Bloomington, IN, and Washington, DC. Examination of weather conditions during these AR times shows remarkable similarity to conditions associated with west coast ARs. This gives strong evidence that ARs do occur in the eastern half of the US. This result is important because it suggests that ARs may be important for water resources and extreme weather in the eastern half of the US, just as they are in the western US. This result also suggests that ARs may be important for water resources and extremes in other continental interiors. Key Points: Atmospheric rivers (ARs) east of the Rockies are associated with baroclinic wavesWestern coastal ARs and eastern/midwest ARs are dynamically similarSynoptic‐scale uplift, combined with convective instability, provide efficient mechanisms for generating precipitation [ABSTRACT FROM AUTHOR]

A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined. Plain Language Summary: Due to limitations in computing power which necessitates coarse spatial resolution, climate models do not include many details on mountains and their impact on precipitation. For this reason, it is difficult to estimate the impact of climate change on the availability of water for human consumption in places like the western United States, where mountain snowpack is an important source of water. This paper presents a way to adjust precipitation estimates from climate models by using some simple statistics about nearby mountains and valleys. The adjusted precipitation is then used in a hydrologic model to calculate the runoff that is simulated with different precipitation inputs. Results show that in most cases, the precipitation adjustment improves estimates of the resultant runoff relative to simulations with observed precipitation. The main exceptions are in very dry areas where the climate model produces far too much precipitation. With further work, the proposed adjustment may be integrated into the climate model itself to make it easier for those managing water resources (e.g., controlling reservoir levels) to use the model output to plan and adapt to climate change. Key Points: A mass‐conserving method for downscaling orographic precipitation improves modeled runoff from the CESM2Considering upwind topography further improves modeled runoff compared to simpler adjustmentsNot tuning to individual model grid points makes this method more generalizable than many existing statistical downscaling methods [ABSTRACT FROM AUTHOR]

This paper analyzes the effects of pore pressure rate for a spring‐block system that is a simple model of a laboratory experiment. Pore pressure is increased at a constant rate in a remote reservoir, and slip is governed by rate and state friction. The frequency of rapid slip events increases with the increase of a nondimensional pressure rate that is the ratio of the time scale of frictional sliding to that for pressure increase. As the pressure rate increases, the more rapid increase of pore pressure on the slip surface quickly stabilizes slip events due to rate and state friction. Rate and state and pressure rate effects interact in a limited range of pressure rate and diffusivity. This range includes pressure rates and diffusivities representative of recent laboratory experiments. Plain Language Summary: Recent field observations have identified fluid injection as an important factor in causing the dramatic increase of earthquakes in the central United States, and recent laboratory experiments have observed effects of fluid pressure rate on frictional sliding. This paper studies a simple model of a laboratory experiment: a block resting on a frictional surface and pulled by a spring. The frictional resistance to sliding depends on the rate and history of sliding. Fluid pressure is increased at a constant rate at a distance remote from the surface. The paper calculates the types and characteristics of rapid slip events and their dependence on the pressure rate and how fast fluid can diffuse from the reservoir to the frictional surface. Key Points: Rapid slip events occur during the duration of a representative experiment in a limited range of pressure rate and diffusivityAbove a certain pressure rate slip events are strongly damped by a rapid decrease of effective stressInteraction between fluid diffusion and pressure rate affects the type, frequency, and magnitude of slip events [ABSTRACT FROM AUTHOR]

Catchments are complex systems containing channel networks and hillslopes. Channel networks interact with hillslopes and are pathways for transporting water, sediment, and nutrients. Understanding the branching and flux transport patterns of channel networks is critical for predicting the response of catchments to external forcing such as climate and tectonics. However, factors creating complexities in catchments are not fully understood. Here, we propose a new framework based on multiscale entropy approach to evaluate complexity of catchments using two different representations of channel networks. First, we investigate the structural complexity using the width‐function, which characterizes the spatial arrangement of channels. Second, we utilize the incremental area‐function along the main channel to study the functional complexity that captures the patterns of transport of fluxes. Our analysis reveals stronger controls of topological connectivity on the functional complexity than on structural complexity, indicating unchannelized surface (hillslope) contribution to the increase of heterogeneity in transport processes. Plain Language Summary: Catchments are complex natural landscape systems that contain hillslopes and channel networks. Understanding and quantifying features and processes that result in catchment complexity is important for predicting their response to changing human and climatic conditions. In this paper, we use an entropy‐based approach to explore the role of channel network and hillslope toward the contribution to catchment's complexity. Based on 40 natural catchments with minimum human impact across the United States in different climatic and geologic conditions, our results show that hillslopes add significant complexity to the catchments and suggest the amount of hillslope information one needs to account for in accurate predictive modeling of hydrologic processes at the catchment scale. Key Points: Topology controls structural and functional complexityFunctional complexity is higher than structural complexity due to contribution from hillslope processesScale of peak difference between the impact of topology on functional and structural complexity indicates the average hillslope length scale [ABSTRACT FROM AUTHOR]

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar‐induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower‐level observations and process‐based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30–50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower‐derived GPP and county‐level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R2 = 0.89). Spatially, county‐level TROPOMI SIF correlates with crop productivity (R2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring. Plain Language Summary: Crop monitoring is essential for ensuring food security, but reliable, instantaneous production estimates at the global scale are lacking. The monitoring of crop production in a changing climate is of paramount importance to sustainable food security. Accurate estimates of crop production are dependent on adequately quantifying crop photosynthesis. Our paper demonstrates that solar‐induced chlorophyll fluorescence (SIF), an emission of red to far‐red light from chlorophyll is highly correlated with crop photosynthesis. We show that a new high spatial resolution satellite SIF data set is highly correlated with crop productivity in the United States, which is benchmarked by the United States Department of Agriculture county‐level crop statistics. These results will improve the understanding of crop production and carbon flux over agricultural lands, as well as provide an accurate, large‐scale, and timely monitoring method for global crop production estimates. Key Points: The photosynthetic pathway (C3, C4) impacts the relationship between CO2 uptake and SIF, which helps to interpret satellite signalsTROPOMI SIF agrees well with the seasonality of crop gross primary production (GPP) when accounting for C3/C4 fractionationTROPOMI SIF is highly correlated with USDA reported crop productivity at the county scale [ABSTRACT FROM AUTHOR]