Analyses of the wind-driven response of tropical oceans

Numerical and analytical models are used to study the upper-ocean response to surface wind stress estimates from the tropical Atlantic and Pacific Oceans. These models are used to identify regions of important variability in the wind field, analyze the oceanic response, and demonstrate the applicability of remotely sensed vector wind stress and altimetry data. Both model and XBT depictions of the mean seasonal cycle, 1979 to 1981, were analyzed along the major ship tracks in the western, central, and eastern tropical Pacific. Model solutions were also used to address array design questions in observing system simulation experiments. Subsequent analyses of the 1982 to 1983 solutions will be performed with respect to differences from the mean seasonal cycle 1979 to 1981, as well as, differences in the three wind products

A simple mechanism for the climatological midsummer drought along the Pacific coast of Central America

© ATMOSFERA, 2013. This article is posted here by permission of ATMOSFERA for personal use, not for redistribution. The definitive version was published in Atmósfera 26 (2013): 261-281.The global distribution, seasonal evolution, and underlying mechanisms for the climatological midsummer drought (MSD) are investigated using a suite of relatively high spatial and temporal resolution station observations and reanalysis data with particular focus on the Pacific coast of Central America and southern Mexico. Although the MSD of Central America stands out in terms of spatial scale and coherence, it is neither unique to the Greater Caribbean Region (GCR) nor necessarily the strongest MSD on Earth based on an objective analysis of several global precipitation data sets. A mechanism for the MSD is proposed that relates the latitudinal dependence of the two climatological precipitation maxima to the biannual crossing of the solar declination (SD), driving two peaks in convective instability and hence rainfall. In addition to this underlying local mechanism, a number of remote processes tend to peak during the apex of the MSD, including the North American monsoon, the Caribbean low-level jet, and the North Atlantic subtropical high, which may also act to suppress rainfall along the Pacific coast of Central America and generate interannual variability in the strength or timing of the MSD. However, our findings challenge the existing paradigm that the MSD owes its existence to a precipitation-suppressing mechanism. Rather, aided by the analysis of higher-temporal resolution precipitation records and considering variations in latitude, we suggest the MSD is essentially the result of one precipitation-enhancing mechanism occurring twice.The authors gratefully acknowledge funding from the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions, and Projections (MAPP) Program, under awards NA10OAR0110239 to the Woods Hole Oceanographic Institution, NA10OAR4310253 to the University of Maryland, and NA10OAR4310252 to Columbia University

Spatial and temporal variations in dissolved and particulate organic nitrogen in the equatorial Pacific: biological and physical influences

To quote Libby and Wheeler (1997), "we have only a cursory knowledge of the distributions of dissolved and particulate organic nitrogen" in the equatorial Pacific. A decade later, we are still in need of spatial and temporal analyses of these organic nitrogen pools. To address this issue, we employ a basin scale physical-biogeochemical model to study the spatial and temporal variations of dissolved organic nitrogen (DON) and particulate organic nitrogen (PON). The model is able to reproduce many observed features of nitrate, ammonium, DON and PON in the central and eastern equatorial Pacific, including the asymmetries of nitrate and ammonium, and the meridional distributions of DON and PON. Modeled DON (5–8 mmol m<sup>−3</sup>) shows small zonal and meridional variations in the mixed layer whereas modeled PON (0.4–1.5 mmol m<sup>−3</sup>) shows considerable spatial variability. While there is a moderate seasonality in both DON and PON in the mixed layer, there is a much weaker interannual variability in DON than in PON. The interannual variability in PON is largely associated with the El Niño/Southern Oscillation (ENSO) phenomenon, showing high values during cold ENSO phase but low values during warm ENSO phase. Overall, DON and PON have significant positive correlations with phytoplankton and zooplankton in the mixed layer, indicting the biological regulation on distribution of organic nitrogen. However, the relationships with phytoplankton and zooplankton are much weaker for DON (r=0.18–0.71) than for PON (r=0.25–0.97). Such a difference is ascribed to a relatively larger degree of physical control (e.g., upwelling of low-organic-N deep waters into the surface) on DON than PON

The Role of the Indian Ocean Sector for Prediction of the Coupled Indo-Pacific System: Impact of Atmospheric Coupling

Indian Ocean (IO) dynamics impact ENSO predictability by influencing wind and precipitation anomalies in the Pacific. To test if the upstream influence of the IO improves ENSO validation statistics, a combination of forced ocean, atmosphere, and coupled models are utilized. In one experiment, the full tropical Indo-Pacific region atmosphere is forced by observed interannual SST anomalies. In the other, the IO is forced by climatological SST. Differences between these two forced atmospheric model experiments spotlight a much richer wind response pattern in the Pacific than previous studies that used idealized forcing and simple linear atmospheric models. Weak westerlies are found near the equator similar to earlier literature. However, at initialization strong easterlies between 30 deg. S to 10 deg. S and 0 deg. N to 25 deg. N and equatorial convergence of the meridional winds across the entire Pacific are unique findings from this paper. The large-scale equatorial divergence west of the dateline and northeasterly-to-northwesterly cross-equatorial flow converging on the equator east of the dateline in the Pacific are generated from interannual IO SST coupling. In addition, off-equatorial downwelling curl impacts large-scale oceanic waves (i.e., Rossby waves reflect as western boundary Kelvin waves). After 3 months, these downwelling equatorial Kelvin waves propagate across the Pacific and strengthen the NINO3 SST. Eventually Bjerknes feedbacks take hold in the eastern Pacific which allows this warm anomaly to grow. Coupled forecasts for NINO3 SST anomalies for 1993-2014 demonstrate that including interannual IO forcing significantly improves predictions for 3-9 month lead times

The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System

We assess the impact of satellite sea surface salinity (SSS) observations on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts. Our coupled model is composed of a primitive equation ocean model for the tropical Indo-Pacific region that is coupled with the global SPEEDY atmospheric model (Molteni, 2003). The Ensemble Reduced Order Kalman Filter is used to assimilate observations to constrain dynamics and thermodynamics for initialization of the coupled model. The baseline experiment assimilates satellite sea level, SST, and in situ subsurface temperature and salinity observations. This baseline is then compared with experiments that additionally assimilate Aquarius (version 4.0) and SMAP (version 2.0) SSS. Twelve-month forecasts are initialized for each month from Sep. 2011 to Dec. 2016. We find that including satellite SSS significantly improves NINO3.4 sea surface temperature anomaly validation after 1 out to 12 month forecast lead times. For initialization of the coupled forecast, the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. SST differences at initialization force wide-spread downwelling favorable curl over most of the tropical Pacific. Over an average forecast, SST remains warmer with SSS assimilation at the eastern edge of the warm pool. This warm SST propagates into the eastern Pacific and drags westerly wind anomalies eastward into the NINO3.4 region. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together lead to a funneling effect that provides the background state to amplify equatorial Kelvin waves. We show that the downwelling Kelvin waves are amplified by assimilating satellite SSS and lead to significantly improved forecasts particularly for the 2015 El Nino

Mapping tropical Pacific sea level: Data assimilation via a reduced state space Kalman filter

The well-known fact that tropical sea level can be usefully simulated by linear wind driven models recommends it as a realistic test problem for data assimilation schemes. Here we report on an assimilation of monthly data for the period 1975-1992 from 34 tropical Pacific tide gauges into such a model using a Kalman filter. We present an approach to the Kalman filter that uses a reduced state space representation for the required error covariance matrices. This reduction makes the calculation highly feasible. We argue that a more complete representation will be of no value in typical oceanographic practice, that in principle it is unlikely to be helpful, and that it may even be harmful if the data coverage is sparse, the usual case in oceanography. This is in part a consequence of ignorance of the correct error statistics for the data and model, but only in part. The reduced state space is obtained from a truncated set of multivariate empirical orthogonal functions (EOFs) derived from a long model run without assimilation. The reduced state space filter is compared with a full grid point Kalman filter using the same dynamical model for the period 1979-1985, assimilating eight tide gauge stations and using an additional seven for verification [Miller et al., 1995]. Results are not inferior to the full grid point filter, even when the reduced filter retains only nine EOFs. Five sets of reduced space filter assimilations are run with all tide gauge data for the period 1975-1992. In each set a different number of EOFs is retained: 5, 9, 17, 32, and 93, accounting for 60, 70, 80, 90, and 99% of the model variance, respectively. Each set consists of 34 runs, in each of which one station is withheld for verification. Comparing each set to the nonassimilation run, the average rms error at the withheld stations decreases by more than 1 cm. The improvement is generally larger for the stations at lowest latitudes. Increasing the number of EOFs increases agreement with data at locations where data are assimilated; the added structures allow better fits locally. In contrast, results at withheld stations are almost insensitive to the number of EOFs retained. We also compare the Kalman filter theoretical error estimates with the actual errors of the assimilations. Features agree on average, but not in detail, a reminder of the fact that the quality of theoretical estimates is limited by the quality of error models they assume. We briefly discuss the implications of our work for future studies, including the application of the method to full ocean general circulation models and coupled models.Copyrighted by American Geophysical Union

An Earth-system prediction initiative for the twenty-first century

International audienceSome scientists have proposed the Earth-System Prediction Initiative (EPI) at the 2007 GEO Summit in Cape Town, South Africa. EPI will draw upon coordination between international programs for Earth system observations, prediction, and warning, such as the WCRP, WWRP, GCOS, and hence contribute to GEO and the GEOSS. It will link with international organizations, such as the International Council for Science (ICSU), Intergovernmental Oceanographic Commission (IOC), UNEP, WMO, and World Health Organization (WHO). The proposed initiative will provide high-resolution climate models that capture the properties of regional high-impact weather events, such as tropical cyclones, heat wave, and sand and dust storms associated within multi-decadal climate projections of climate variability and change. Unprecedented international collaboration and goodwill are necessary for the success of EPI

Modeling sustainability : Population, inequality, consumption, and bidirectional coupling of the Earth and human systems

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth SystemModels must be coupled with Human SystemModels through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models.The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations