A regionally refined quarter-degree global atmospheric rivers database based on ERA5.

Atmospheric rivers (ARs) are narrow, elongated, synoptic jets of water vapor that play important roles in the global water cycle. The continually developing Tracking Atmospheric Rivers Globally as Elongated Targets (tARget) algorithm identifies AR objects at individual time steps based on thresholding integrated water vapor transport (IVT) and other requirements, and tracks each AR object in time and space. Building on previous versions of tARget, this paper discusses further refinements to the algorithm to better handle ARs in tropical and polar areas, as well as "zonal" ARs which the previous versions of the algorithm were not designed to capture. This further regionally refined algorithm is applied to the ERA5 reanalysis over 1940-2023 at 6 h intervals and a 0.25° × 0.25° horizontal resolution. The AR detection results are evaluated in terms of key AR characteristics. We anticipate this regionally refined global AR database will aid further understanding of ARs such as AR process studies, evaluation of AR simulations and predictions, and assessment of climate change impacts on ARs.

A multimodel evaluation of the water vapor budget in atmospheric rivers.

Atmospheric rivers (ARs) are narrow regions of strong horizontal water vapor transport that play important roles in the global water cycle, weather, and hydrology. Motivated by challenges in simulating ARs with state-of-the-art global models, this paper diagnoses model errors with a focus on relative contributions of moisture convergence, evaporation, and precipitation to AR column-integrated water vapor (IWV) budget. Using 20-year simulations by 24 global weather/climate models, budget terms are calculated for four AR sectors: postfrontal, frontal, prefrontal, and pre-AR, with biases assessed against two reanalysis products. The results indicate that each sector is unique in terms of the dominant water vapor balance, and that the terms exhibiting the largest intermodel spread are the same terms dominating the water vapor balance in each sector. Overall, simulated bulk AR characteristics (e.g., geometry, frequency, and intensity) are more sensitive to biases in IVT convergence and IWV tendency than to biases in evaporation and precipitation, although evaporation/precipitation biases do affect key AR bulk characteristics in selected sectors. The large intermodel spread (particularly for precipitation) and, in certain cases, discrepancies between the reanalysis references themselves (particularly for precipitation types) highlight the need for observational efforts that target better constraining AR processes in weather/climate models and reanalyses.

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range.

An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Surface mass balance contributions to acceleration of Antarctic ice mass loss during 2003-2013.

Recent observations from satellite gravimetry (the Gravity Recovery and Climate Experiment (GRACE) mission) suggest an acceleration of ice mass loss from the Antarctic Ice Sheet (AIS). The contribution of surface mass balance changes (due to variable precipitation) is compared with GRACE-derived mass loss acceleration by assessing the estimated contribution of snow mass from meteorological reanalysis data. We find that over much of the continent, the acceleration can be explained by precipitation anomalies. However, on the Antarctic Peninsula and other parts of West Antarctica, mass changes are not explained by precipitation and are likely associated with ice discharge rate increases. The total apparent GRACE acceleration over all of the AIS between 2003 and 2013 is -13.6 ± 7.2 Gt/yr2. Of this total, we find that the surface mass balance component is -8.2 ± 2.0 Gt/yr2. However, the GRACE estimate appears to contain errors arising from the atmospheric pressure fields used to remove air mass effects. The estimated acceleration error from this effect is about 9.8 ± 5.8 Gt/yr2. Correcting for this yields an ice discharge acceleration of -15.1 ± 6.5 Gt/yr2.

Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation.

Carbon dioxide (CO(2)) is the most important anthropogenic greenhouse gas in the present-day climate. Most of the community focuses on its long-term (decadal to centennial) behaviors that are relevant to climate change, but there are relatively few discussions of its higher-frequency forms of variability, and none regarding its subseasonal distribution. In this work, we report a large-scale intraseasonal variation in the Atmospheric Infrared Sounder CO(2) data in the global tropical region associated with the Madden-Julian oscillation (MJO). The peak-to-peak amplitude of the composite MJO modulation is ∼1 ppmv, with a standard error of the composite mean < 0.1 ppmv. The correlation structure between CO(2) and rainfall and vertical velocity indicate positive (negative) anomalies in CO(2) arise due to upward (downward) large-scale vertical motions in the lower troposphere associated with the MJO. These findings can help elucidate how faster processes can organize, transport, and mix CO(2) and provide a robustness test for coupled carbon-climate models.