Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA-Interim, NASA MERRA, and AIRS data

We construct a 9-year data record (2007–2015) of the tropospheric specific humidity using Global Positioning System radio occultation (GPS RO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. This record covers the ±40∘ latitude belt and includes estimates of the zonally averaged monthly mean specific humidity from 700 up to 400 hPa. It includes three major climate zones: (a) the deep tropics (±15∘), (b) the trade winds belts (±15–30∘), and (c) the subtropics (±30–40∘). We find that the RO observations agree very well with the European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-Interim), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and the Atmospheric Infrared Sounder (AIRS) by capturing similar magnitudes and patterns of variability in the monthly zonal mean specific humidity and interannual anomaly over annual and interannual timescales. The JPL and UCAR specific humidity climatologies differ by less than 15 % (depending on location and pressure level), primarily due to differences in the retrieved refractivity. In the middle-to-upper troposphere, in all climate zones, JPL is the wettest of all data sets, AIRS is the driest of all data sets, and UCAR, ERA-Interim, and MERRA are in very good agreement, lying between the JPL and AIRS climatologies. In the lower-to-middle troposphere, we present a complex behavior of discrepancies, and we speculate that this might be due to convection and entrainment. Conclusively, the RO observations could potentially be used as a climate variable, but more thorough analysis is required to assess the structural uncertainty between centers and its origin.

Assessing the Significance of Changes in ENSO Amplitude Using Variance Metrics

The variance of time series records relating to ENSO, such as the interannual anomalies or bandpass filtered components of equatorial Pacific SST indices, provides one approach to quantifying changes in ENSO amplitude. Robust assessment of the significance of changes in amplitude defined in this way is, however, hampered by uncertainty regarding the sampling distributions of such variance metrics within an unforced climate system. The present study shows that the empirical constraints on these sampling distributions provided by a range of unforced CGCM simulations are consistent with the expected parametric form, suggesting that standard parametric testing strategies can be robustly applied, even in the case of the nonlinear ENSO system. Under such an approach, the sampling distribution of unforced relative changes in variance may be constrained by a single parameter τd: the value of which depends on the choice of method used to extract the ENSO-related component of time series variability. In the case of interannual anomaly records, the value of τd is also substantially dependent on the overall spectral properties of the climatic variable under consideration. In contrast, the τd value for bandpass filtered records can be conservatively constrained from the lower edge of the filter passband, allowing for the direct but robust assessment of the significance of relative changes in ENSO amplitude, regardless of the climatic variable under consideration. Example applications of this approach confirm marginally significant F-test p values for multidecadal changes in central Pacific instrumental SST variance and highly significant ones for centennial changes in central Pacific coral δ18O variance.

Interannual Biases Induced by Freshwater Flux and Coupled Feedback in the Tropical Pacific

Freshwater flux (FWF) forcing–induced feedback has not been represented adequately in many coupled ocean–atmosphere models of the tropical Pacific. Previously, various approximations have been made in representing the FWF forcing in climate modeling. In this article, using a hybrid coupled model (HCM), sensitivity experiments are performed to examine the extent to which this forcing and related feedback effects can contribute to tropical biases in interannual simulations of the tropical Pacific. The total FWF into the ocean, represented by precipitation (P) minus evaporation (E), (P − E), is separated into its climatological part and interannual anomaly part: FWFTotal = (P − E)clim + FWFinter. The former can be prescribed (seasonally varying); the latter can be captured using an empirical model linking with large-scale sea surface temperature (SST) variability. Four cases are considered with different FWFinter specifications: interannual (P − E) forcing [FWFinter = (P − E)inter], interannual P forcing (FWFinter = Pinter), interannual E forcing (FWFinter = −Einter), and climatological (P − E) forcing (FWFinter = 0.0), respectively. The HCM-based experiments indicate that different FWFinter approximations can modulate interannual variability in a substantial way. The HCM with the interannual (P − E) forcing, in which a positive SST − (P − E)inter feedback is included explicitly, has a reasonably realistic simulation of interannual variability. When FWFinter is approximated in some ways, the simulated interannual variability can be modulated significantly: it is weakened with the climatological (P − E) forcing and is even more damped with the interannual E forcing, but is exaggerated with the interannual P forcing. Quantitatively, taking the interannual (P − E) forcing run as a reference, the Niño-3 SST variance can be reduced by about 12% and 26% in the climatological (P − E) forcing run and interannual E forcing run, respectively, but overestimated by 11% in the Pinter forcing run. It is demonstrated that FWF can be a clear bias source for coupled model simulations in the tropical Pacific.