Towards the validation of a traceable climate model hierarchies

This is the final version of the article. Available from OUP via the DOI in this recordBackground It is a common practice to use a simple model to explain the mechanisms or processes that occur in a much more complex, complete and computationally expensive model. Many such examples can be found in climate change research. Objective This paper uses two illustrative examples to show how we can quantitatively relate the mechanisms or processes observed in a simple climate model to similar mechanisms in a more complex one. Method A simple model can only explain a more complex solution’s mechanisms if outcomes are tested over a broad range of inputs. By carefully sampling the full set of inputs for both the simple and complex models, we can robustly compare the process or mechanistic outcomes, statistically, between them. Thus, by examining the similarity or differences in the relationship between the inputs and outputs. The method can reject an incorrect simple model. Results The examples are, first, analytic and numerical solutions to the heat equation and, second, the 1948 Stommel model of horizontal ocean circulation and a more complex quasi-geostrophic ocean model. We quantitatively state how similar the simple model’s mechanisms are to the mechanisms in the more complex representation. In addition, when a simple solution may be correct, we give the percentage of the variance of the complex model’s outcomes that is explained by the simple response along with an uncertainty estimate. Conclusion We successfully tested a methodology for robustly quantifying how the physics encapsulated by a simple model of a process may exhibit itself in another, more complex formulation. Suggestions are given as a guide for use of the methodology with more complex and realistic models.Funding: NSF (0851065)

Influence of initial ocean conditions on temperature and precipitation in a coupled climate model’s solution

This is the final version. Available on open access from Copernicus Publications via the DOI in this recordCode and data availability: Model output and software code are available through a request to the authors.This paper describes results of an experiment that perturbed the initial conditions for the ocean’s temperature field of the Community Earth System Model (CESM) with a well defined design. The resulting thirty member ensemble of CESM simulations, each of ten years in length is used to create an emulator (a non-linear regression relating the initial conditions to various outcomes) from the simulators. Through the use of the emulator to expand the output distribution space, we estimate the spatial uncertainties at 10 years for surface air temperature, 25m ocean temperature, precipitation, and rain. Basin averages, outside the tropics, for the uncertainty in the ocean temperature field range between 0.48◦C (Indian Ocean) and 0.87◦C (North Pacific) (two standard deviations). The tropical Pacific uncertainty is the largest due to different phasings of the ENSO signal. Over land areas, the regional temperature uncertainty varies from 1.03◦C (South America) to 10.82◦C (Europe) (two standard deviations). Similarly, the regional average uncertainty in precipitation varies from 0.001 cm/day over Antarctica to 0.163 cm/day over Australia with the global average of 0.075 cm/day. In general, both temperature and precipitation uncertainties are larger over land than over the ocean. A maximum covariance analysis is used to examine how ocean temperatures affect both surface air temperatures and precipitation over land. The analysis shows that the tropical Pacific influences the temperature over North America, but the North America surface temperature is also moderated by the state of the North Pacific outside the tropics. It also indicates which regions show a high degree of variance between the simulations in the ensemble and are, therefore, less predictable. The calculated uncertainties are also compared to an estimate of internal variability within CESM. Finally, the importance of feedback processes on the solution of the simulation over the ten years of the experiment is quantified. These estimates of uncertainty are without the consideration of anthropogenic effect on warming of the atmosphere and ocean.National Science Foundation: NS

Large-Scale Forcing of the Agulhas Variability: The Seasonal Cycle

In this article the authors examine the kinematics and dynamics of the seasonal cycle in the western Indian Ocean in an eddy-permitting global simulation [Parallel Ocean Circulation Model, model run 4C (POCM-4C)]. Seasonal changes of the transport of the Agulhas Current are linked to the large-scale circulation in the tropical region. According to the model, the Agulhas Current transport has a seasonal variation with a maximum at the transition between the austral winter and the austral spring and a minimum between the austral summer and the austral autumn. Regional and basin-scale mass balances indicate that although the mean flow of the Agulhas Current has a substantial contribution from the Indonesian Throughflow, there appears to be no dynamical linkage between the seasonal oscillations of these two currents. Instead, evidence was found that the seasonal cycle of the western Indian Ocean is the result of the oscillation of barotropic modes forced directly by the wind

Global ocean modeling and state estimation in support of climate research

During the last decade it has become obvious that the ocean circulation shows vigorous variability on a wide range of time and space scales and that the concept of a "sluggish" and slowly varying circulation is rather elusive. Increasing emphasis has to be put, therefore, on observing the rapidly changing ocean state on time scales ranging from weeks to decades and beyond, and on understanding the ocean's response to changing atmospheric forcing conditions. As outlined in various strategy and implementation documents (e.g., the implementation plans of WOCE, AMS, CLIVAR, and GODAE) a combination of the global ocean data sets with a state-of-the-art numerical circulation model is required to interpret the various diverse data sets and to produce the best possible estimates of the time-varying ocean circulation. The mechanism of ocean state estimates is a powerful tool for such a "synthesis" of observations, obtained on very complex space-time pattern, into one dynamically consistent picture of the global time-evolving ocean circulation. This process has much in common with ongoing analysis and reanalysis activities in the atmospheric community. But because the ocean is, and will remain for the foreseeable future, substantially under-sampled, the burden put on the modeling and estimations components is substantially larger than in the atmosphere. Moreover, the smaller dynamical eddy scales which need to be properly parameterized or resolved in ocean model simulations, put stringent requirements on computational resources for ongoing and participated climate research

An ocean model’s response to scatterometer winds

The article of record as published may be located at http://dx.doi.org/10.1016/j.ocemod.2004.04.005Two simulations of the North Atlantic have been run using the POP ocean model for approximately two and one half years each. One simulation used the 1.25 wind product from ECMWF and the other used the JPL Quikscat 0.25 gridded product. The resulting sea level anomaly fields from the simulations are quantified by using tide gauge and altimetric sea level anomaly data. In addition, upper ocean quantities were compared, such as the mix layer depths, to understand the difference in the ocean’s response when using the different wind products. The analysis found that significant improvements were made in the representation at the surface, and in particular areas where comparison data exists such as the Labrador Sea. There was also improvement in the scatterometer forced run with more realistic depths of the mixed layer

Monitoring North Pacific Heat Content Variability: An Indicator of Fish Quantity?

Fields of modeled sea surface heights and temperatures are used to develop an algorithm to monitor the low-frequency heat content variability of the North Pacific’s midlatitudes associated with regime shifts in the circulation patterns of the Alaskan and the California Currents. Data from altimetric and infrared satellites are then used to apply the method using observational measurements. The model shows that the midlatitude Pacific subsurface circulation variability is primarily due to large, low-frequency horizontal north–south gyre movement. The changes may also be due to largescale atmospheric changes in wind patterns, local mixing, as well as internal dynamics. It is proposed that this type of monitoring might be useful to help with understanding the variability in fisheries.This work is funded by grants from NASA JSWT, DOE, and from NOAA GLOBEC (in the northeastern Pacific)

On the joint estimation of model and satellite sea surface height anomaly errors

We describe a technique to estimate the error ®eld in the sea surface height (SSH) anomaly ®eld of an ocean model through the joint use of SSH anomaly ®elds measured from two satellites, Topex/Poseidon (T/P) and ERS-2. The joint error maps for the model, T/P and ERS-2 show distributions distinctly di erent from one another and globally inhomogeneous. Both sampling errors and instrument errors are represented in the mapped ®elds. Additionally, we compare the joint error estimation method to a technique using the model and only one satellite, and show the importance of the cross covariance between the measured SSH and the true SSH ®eld in the estimation of the error ®eld. Finally, we look at the distribution of the error versus the variance of the SSH at a location. This logged distribution suggests that the model errors are generally proportional to the model's variance (regression coe cient of 0.99, globally) while the satellites' errors do not exhibit this linear relationship (regression coe cients on the average of 0.60). The comparison of the two satellite distributions implies that ERS-2 has a lower sampling error than the T/P instrument except in the tropical region

On the multiple time scales of variability in the Northeast Pacific Ocean

The spatial and temporal sea surface height energy distribution of the Northeast Pacific Ocean is described and discussed. Using an altimetric data set covering 15 years (1993–2007), the energy within the 3–9 month band is primarily located within 10° of the coast. In the Gulf of Alaska, this energy signal is on the shelf, while further south, west of the California/Oregon coast, the significant energy in this band is west of the shelf break. In both cases, it is primarily forced by the local wind. Within the 2–3 year band, the signal reflects energy generated by local changes to the wind stress from large atmospheric shifts indicated by the Pacific North American Index and by advective or propagating processes related to El Niño-Southern Oscillation. Over the two 4–6 year periods within this data set, the change is primarily due to the large scale shift in atmospheric systems north of about 30° N which also affect changes in current strengths. Based on the distribution of the energy signal and its variability, a set of three winter-time indices are suggested to characterize the distinct differences in the SSH anomalies in these areas

Large-Scale Forcing of the Agulhas Variability: The Seasonal Cycle

In this article the authors examine the kinematics and dynamics of the seasonal cycle in the western Indian Ocean in an eddy-permitting global simulation [Parallel Ocean Circulation Model, model run 4C (POCM-4C)]. Seasonal changes of the transport of the Agulhas Current are linked to the large-scale circulation in the tropical region. According to the model, the Agulhas Current transport has a seasonal variation with a maximum at the transition between the austral winter and the austral spring and a minimum between the austral summer and the austral autumn. Regional and basin-scale mass balances indicate that although the mean flow of the Agulhas Current has a substantial contribution from the Indonesian Throughflow, there appears to be no dynamical linkage between the seasonal oscillations of these two currents. Instead, evidence was found that the seasonal cycle of the western Indian Ocean is the result of the oscillation of barotropic modes forced directly by the wind.This work was supported by the National Science Foundation Grant OCE-9819223 and the Jet Propulsion Laboratory Contract 1206714