Remote influences of ENSO are known to vary with different phases of the interdecadal Pacific oscillation (IPO). Here, observational and reanalysis data from 1920 to 2014 are analyzed to present a global synthesis of the IPO’s modulation on ENSO teleconnections, followed by a modeling investigation. Regressions of surface air temperature T, precipitation P, and atmospheric circulations upon IPO and ENSO indices reveal substantial differences between ENSO and IPO teleconnections to regional T and P in terms of spatial pattern, magnitude, and seasonality. The IPO’s modulation on ENSO teleconnections asymmetrically varies with both IPO and ENSO phases. For a given ENSO phase, IPO’s modulations are not symmetric between its two phases; for a given IPO SST anomaly, its influence depends on whether it is superimposed on El Niño, La Niña, or neutral ENSO. The IPO modulations are linked to the atmospheric response to tropical SST anomalies, manifested in the local Hadley circulation and the local Walker circulation at low latitudes and the Rossby wave train in the extratropics, including the Pacific–North American (PNA) pattern in the Northern Hemisphere. A set of numerical experiments using CAM5 forced with different combinations of the IPO- and ENSO-related SSTs further shows that the asymmetric modulation arises from the nonlinear Clausius–Clapeyron relation, so that the atmospheric circulation response to the same IPO-induced SST departure is larger during a warm rather than a cold ENSO phase, and the response to a warm IPO state is larger than that to a cold IPO state. The asymmetry depends primarily on the tropical Pacific mean state and tropical SST anomalies and secondarily on extratropical SST anomalies.

We present a simple smoother designed for smooth data adjustments in sequentially generated reanalysis products by utilizing knowledge of future assimilation increments. A decay time parameter is applied to the smoother increments to account for memory decay timescales in the ocean. The result is different from simply time smoothing the reanalysis itself as only the increments are smoothed so the reanalysis product can retain high frequency variability that is being internally generated by the model and the atmospheric forcing. The smoother is applied first to the Lorenz 1963 model and then to the daily Met Office GloSea5 Global ¼° ocean reanalysis during 2016. Results show significant improvement over the original reanalysis in the 3D temperature and salinity state and variability, as well as in the sea surface height (SSH) and ocean currents. Comparisons are made directly against temperature, salinity and SSH observations, as well as independent 15 m drifter velocities. The impact on the time variability of conservative quantities, particularly ocean heat and salt content, as well as kinetic energy and the Atlantic Meridional Overturning Circulation (AMOC), is also demonstrated.

Variations in climate have important influences on the hydrologic cycle. Observations over the continental United States in recent decades show substantial changes in hydrologically significant variables, such as decreases in cloud cover and increases in solar radiation (i.e., solar brightening), as well as increases in air temperature, changes in wind speed, and seasonal shifts in precipitation rate and rain/snow ratio. Impacts of these changes on the regional water cycle from 1984 to 2007 are evaluated using a terrestrial ecosystem/land surface hydrologic model (Agro-IBIS). Results show an acceleration of various components of the surface water balance in the Upper Mississippi, Missouri, Ohio, and Great Lakes basins over the 24-yr period, but with significant seasonal and spatial complexity. Evapotranspiration (ET) has increased across most of our study domain and seasons. The largest increase is found in fall, when solar brightening trends are also particularly significant. Changes in runoff are characterized by distinct spatial and seasonal variations, with the impact of precipitation often being muted by changes in ET and soil-water storage rate. In snow-dominated regions, such as the northern Great Lakes basin, spring runoff has declined significantly due to warmer air temperatures and an associated decreasing ratio of snow in total precipitation during the cold season. In the northern Missouri basin, runoff shows large increases in all seasons, primarily due to increases in precipitation. The responses to these changes in the regional hydrologic cycle depend on the underlying land cover type—maize, soybean, and natural vegetation. Comparisons are also made with other hydroclimatic time series to place the decadal-scale variability in a longer-term context.

Quantifying regional water and energy fluxes much more accurately from observations is essential for assessing the capability of climate and Earth system models and their ability to simulate future change. This study uses satellite observations to produce monthly flux estimates for each component of the terrestrial water and energy budget over selected large river basins from 2002 to 2013. Prior to optimisation, the water budget residuals vary between 1.5 % and 35 % precipitation by basin, and the magnitude of the imbalance between the net radiation and the corresponding turbulent heat fluxes ranges between 1 and 12 W m⁻² in the long-term average. In order to further assess these imbalances, a flux-inferred surface storage (S_fi) is used for both water and energy, based on integrating the flux observations. This exposes mismatches in seasonal water storage in addition to important inter-annual variability between GRACE (Gravity Recovery and Climate Experiment) and the storage suggested by the other flux observations. Our optimisation ensures that the flux estimates are consistent with the total water storage changes from GRACE on short (monthly) and longer timescales, while also balancing a coupled long-term energy budget by using a sequential approach. All the flux adjustments made during the optimisation are small and within uncertainty estimates, using a χ² test, and inter-annual variability from observations is retained. The optimisation also reduces formal uncertainties for individual flux components. When compared with results from the previous literature in basins such as the Mississippi, Congo, and Huang He rivers, our results show better agreement with GRACE variability and trends in each case.

The paper presents a simplification of the Kalman smoother that can be run as a post-processing step using only minimal stored information from a Kalman filter analysis, which is intended for use with large model products such as the reanalyses of the Earth system. A simple decay assumption is applied to cross-time error covariances, and we show how the resulting equations relate formally to the fixed-lag Kalman smoother and how they can be solved to give a smoother analysis along with an uncertainty estimate. The method is demonstrated in the Lorenz (1963) idealised system which is applied to both an extended and ensemble Kalman filter and smoother. In each case, the root mean square errors (RMSEs) against the truth, for both assimilated and unassimilated (independent) data, of the new smoother analyses are substantially smaller than for the original filter analyses, while being larger than for the full smoother solution. Up to 70 % (40 %) of the full smoother error reduction, with respect to the extended (ensemble) filters, respectively, is achieved. The uncertainties derived for the new smoother also agree remarkably well with the actual RMSE values throughout the assimilation period. The ability to run this smoother very efficiently as a post-processor should allow it to be useful for really large model reanalysis products and especially for ensemble products that are already being developed by various operational centres.