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On behalf of the journal, AGU, and the scientific community, the editors would like to sincerely thank those who reviewed the manuscripts for Geophysical Research Letters in 2019. The hours reading and commenting on manuscripts not only improve the manuscripts but also increase the scientific rigor of future research in the field. We particularly appreciate the timely reviews in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers' efforts on multiple versions of some manuscripts. With the advent of AGU's data policy, many reviewers have helped immensely to evaluate the accessibility and availability of data associated with the papers they have reviewed, and many have provided insightful comments that helped to improve the data presentation and quality. We greatly appreciate the assistance of the reviewers in advancing open science, which is a key objective of AGU's data policy. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics.

© Author(s) 2017. How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "DLitton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.-iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g Cm-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 gCm-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C- LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem- Cleafratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types.Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.

Bristlecone pine (Pinus longaeva) (PILO) trees exhibit exceptional longevity. Their tree‐ring width (TRW) series offer valuable insights into climatic variability. Maximum latewood density (MXD) typically correlates better with temperature variations than TRW, yet PILO MXD records are non‐existent due to methodological challenges related to tree‐ring structure. Here, we used an X‐ray Computed Tomography (X‐ray CT) toolchain on 51 PILO cores from the California White Mountains to build a chronology that correlates significantly (r = 0.66, p < 0.01) with warm‐season (March‐September) temperature over a large spatial extent. This led to the first X‐ray CT‐based temperature reconstruction (1625–2005 CE). Good reconstruction skill (RE = 0.51, CE = 0.32) shows that extending MXD records across the full length of the PILO archive could yield a robust warm‐season temperature proxy for the American Southwest over millennia. This breakthrough opens avenues for measuring MXD in other challenging conifers, increasing our understanding of past climate further, particularly in lower latitudes. Plain Language Summary: Ancient Bristlecone pine trees can live for several millennia and hold invaluable climate information. Their annual rings were used to develop millennium‐length records of the Holocene climate. Maximum latewood density (MXD), which is the highest wood density value in the latewood of a tree ring, has been shown to closely follow summer temperature in different conifer species, but not yet in Bristlecone pine. The gnarly and twisted growth of these ancient trees has presented significant hurdles for MXD analysis. Here we apply an X‐ray Computed Tomography toolchain that allows us to 3D scan through the tissue of a tree ring and to map MXD variations. Using this new technique, we were able to reconstruct warm‐season temperature for the American Southwest back to 1625 CE. With these findings, we are confident that a full‐length reconstruction (back to 2575 BCE) can yield the longest annually resolved temperature reconstruction for this continent. Key Points: We present the first X‐ray Computed Tomography‐derived maximum latewood density‐based temperature reconstruction using Bristlecone pine tree coresBristlecone pine maximum latewood density is a reliable proxy for warm‐season temperature over a large part of the American SouthwestOur reconstruction (1625–2005 CE) contains low‐frequency variability and can be prolonged over a large part of the Holocene [ABSTRACT FROM AUTHOR]