Abstract

Eulerian kinetic energy budgets for the synoptic-scale flow over North America were computed for two cases of cyclone development associated with severe prefrontal convection. Horizontal flux convergence constitutes the major energy source in both cases and assumes major importance in maintaining the strength of the upper tropospheric jet maxima. Generation of kinetic energy via cross-counter flow is, surprisingly, a persistent sink in one case and only a weak energy source for the cyclone in the second case. Cross-contour flow toward higher heights is generally found ahead of the upper level troughs, where the jet stream is moving through regions in which the contour gradient weakens downstream. Generation of kinetic energy is largely confined to the lower troposphere, reflecting frictional influence near the earth's surface. Dissipation of kinetic energy, computed as a residual, has local maxima both in the lower troposphere (nearly balancing the generation) and near the jet stream level. Subgrid-scale sources of kinetic energy are apparent in both cases and, at times, are particularly important in regions of widespread deep convection. These sources are associated with longitudinal shear in the polar jet stream and with the presence of deep convection. Convective region budgets show that the maximum rate of kinetic energy gain occurs during periods when the convection increases most rapidly both in intensity and in areal extent.

Abstract

This paper investigates intraseasonal variability as represented by the recent NASA Global Modeling and Assimilation Office (GMAO) reanalysis, the Modern-Era Retrospective analysis for Research and Applications (MERRA). The authors examine the behavior of heat, moisture, and radiative fluxes emphasizing their contribution to intraseasonal variations in heat and moisture balance integrated over the tropical oceans. MERRA successfully captures intraseasonal signals in both state variables and fluxes, though it depends heavily on the analysis increment update terms that constrain the reanalysis to be near the observations. Precipitation anomaly patterns evolve in close agreement with those from the Tropical Rainfall Measuring Mission (TRMM) though locally MERRA may occasionally be smaller by up to 20%. As in the TRMM observations, tropical convection increases lead tropospheric warming by approximately 7 days. Radiative flux anomalies are dominated by cloud forcing and are found to replicate the top-of-the-atmosphere (TOA) energy loss associated with increased convection found by other observationally based studies. However, MERRA’s convectively produced clouds appear to deepen too soon as precipitation increases. Total fractional cloud cover variations appear somewhat weak compared to observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Evolution of the surface fluxes, convection, and TOA radiation is consistent with the “discharge–recharge” paradigm that posits the importance of lower-tropospheric moisture accumulation prior to the expansion of organized deep convection. The authors conclude that MERRA constitutes a very useful representation of intraseasonal variability that will support a variety of studies concerning radiative–convective–dynamical processes and will help identify pathways for improved moist physical parameterization in global models.

Despite the general agreement that clouds cool the earth–atmosphere, there are substantial differences in estimated magnitudes of the annual global mean of cloud radiative forcing. Recent estimates of globally averaged net cloud radiative forcing range from −2 to −27 W m⁻². The reasons for these differences have not been clarified in spite of the important role of clouds in maintaining global heat balance. Here, three estimation methods [Earth Radiation Budget Experiment (ERBE), Regression I, and Regression II] are compared using the same data source and analysis period.

Intercomparison has been done for the time period of February and March 1985 over which major satellite radiation budget and cloudiness datasets (ERBE radiation budget, Nimbus-7, and ISCCP cloudiness) are contemporaneous. The global averages of five sets of net cloud radiative forcing by three independent methods agree to within 3.5 W m⁻²; four of five cases agree to within 1 W m⁻². This suggests that differences in published global mean values of net cloud radiative forcing are mainly due to different data sources and analysis periods and a best estimated annual mean among all previous estimates appears to be the ERBE measurement, that is, −17.3 W m⁻². In contrast to the close agreement in the net cloud radiative forcing estimates, both longwave and shortwave cloud radiative forcing show more dependence on the chosen method and dataset. The bias of regression-retrieved values between Nimbus-7 and ISCCP cloud climatology is largely attributed to the difference in total cloudiness between two climatologies whereas the discrepancies between the ERBE and regression method appear to be, in part, due to the conceptually different definition of clear-sky flux.

Abstract

Spatial fields of satellite-measured deep-layer temperatures are examined in the context of quasigeostrophic theory. It is found that midtropospheric geostrophic vorticity and quasigeostrophic vertical motions can be diagnosed from microwave temperature measurements of only two deep layers. The lower- (1000–400 hPa) and upper- (400–50 hPa) layer temperatures are estimated from limb-corrected TIROS-N Microwave Sounding Units (MSU) channel 2 and 3 data, spatial fields of which can be used to estimate the midtropospheric thermal wind and geostrophic vorticity fields. Together with Trenberth's simplification of the quasigeostrophic omega equation, these two quantities can be then used to estimate the geostrophic vorticity advection by the thermal wind, which is related to the quasigeostrophic vertical velocity in the midtroposphere.

Critical to the technique is the observation that geostrophic vorticity fields calculated from the channel 3 temperature features are very similar to those calculated from traditional, “bottom-up” integrated height fields from radiosonde data. This suggests a lack of cyclone-scale height features near the top of the channel 3 weighting function, making the channel 3 cyclone-scale “thickness” features approximately the same as height features near the bottom of the weighting function. Thus, the MSU data provide observational validation of the LID (level of insignificant dynamics) assumption of Hirshberg and Fritsch.

Abstract

Sensitivity experiments with an atmospheric general circulation model (AGCM) show that parameterized rain reevaporation has a large impact on simulated precipitation patterns in the tropical Pacific, especially on the configuration of the model’s intertropical convergence zone (ITCZ). Weak reevaporation leads to the formation of a “double ITCZ” during the northern warm season. The double ITCZ is accompanied by strong correlation between precipitation and high-frequency vertical motion in the planetary boundary layer (PBL). Strong reevaporation leads to a better overall agreement of simulated precipitation with observations. The model’s double ITCZ bias is reduced. At the same time, correlation between high-frequency (periods < 15 days) vertical motion in the PBL and precipitation is reduced. Experiments with modified physics indicate that evaporative cooling by rain near the PBL top weakens the coupling between precipitation-related heating and vertical motion in high-frequency motions. The strength of high-frequency vertical motions in the PBL was also reduced directly through the introduction of a diffusive cumulus momentum transport (DCMT) parameterization. The DCMT had a visible impact on simulated precipitation in the Tropics but did not reduce the model’s double ITCZ bias in all cases.

Further analyses of mass and water vapor budgets, as well as vertical motion statistics, in the ITCZ complex, show that time-mean moisture convergence in the southern ITCZ is largely dominated by high-frequency modes, while in the northern ITCZ time-mean moisture convergence contains large contributions from slower modes. This may explain why the simulated southern ITCZ is more susceptible to parameterization changes that alter high-frequency coupling between moist heating and PBL convergence.

Abstract

Although El Niño events each have distinct evolutionary character, they typically provide systematic large-scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis and in a 10-member-model Atmospheric Model Intercomparison Project (AMIP) ensemble. The lagged response (3–4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, and the AMIP ensemble reproduces some regional responses that are similar to those observed and some regions that are not simulating the response well. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño-3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather-scale variability of the individual events while retaining the systematic features across all events. We find that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture, leads to warmer surface temperature, more sensible heating, and warming of the lower troposphere. The composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, but the regional and temporal responses can vary substantially for any given event. The 2015/16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Abstract

Reanalyses, retrospectively analyzing observations over climatological time scales, represent a merger between satellite observations and models to provide globally continuous data and have improved over several generations. Balancing the earth’s global water and energy budgets has been a focus of research for more than two decades. Models tend to their own climate while remotely sensed observations have had varying degrees of uncertainty. This study evaluates the latest NASA reanalysis, the Modern Era Retrospective-Analysis for Research and Applications (MERRA), from a global water and energy cycles perspective, to place it in context of previous work and demonstrate the strengths and weaknesses.

MERRA was configured to provide complete budgets in its output diagnostics, including the incremental analysis update (IAU), the term that represents the observations influence on the analyzed states, alongside the physical flux terms. Precipitation in reanalyses is typically sensitive to the observational analysis. For MERRA, the global mean precipitation bias and spatial variability are more comparable to merged satellite observations [the Global Precipitation and Climatology Project (GPCP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP)] than previous generations of reanalyses. MERRA ocean evaporation also has a much lower value, which is comparable to independently derived estimate datasets. The global energy budget shows that MERRA cloud effects may be generally weak, leading to excess shortwave radiation reaching the ocean surface.

Evaluating the MERRA time series of budget terms, a significant change occurs that does not appear to be represented in observations. In 1999, the global analysis increments of water vapor changes sign from negative to positive and primarily lead to more oceanic precipitation. This change is coincident with the beginning of Advanced Microwave Sounding Unit (AMSU) radiance assimilation. Previous and current reanalyses all exhibit some sensitivity to perturbations in the observation record, and this remains a significant research topic for reanalysis development. The effect of the changing observing system is evaluated for MERRA water and energy budget terms.

Abstract

Vertically integrated atmospheric moisture transport from ocean to land [vertically integrated atmospheric moisture flux convergence (VMFC)] is a dynamic component of the global climate system but remains problematic in atmospheric reanalyses, with current estimates having significant multidecadal global trends differing even in sign. Continual evolution of the global observing system, particularly stepwise improvements in satellite observations, has introduced discrete changes in the ability of data assimilation to correct systematic model biases, manifesting as nonphysical variability. Land surface models (LSMs) forced with observed precipitation P and near-surface meteorology and radiation provide estimates of evapotranspiration (ET). Since variability of atmospheric moisture storage is small on interannual and longer time scales, VMFC = P − ET is a good approximation and LSMs can provide an alternative estimate. However, heterogeneous density of rain gauge coverage, especially the sparse coverage over tropical continents, remains a serious concern.

Rotated principal component analysis (RPCA) with prefiltering of VMFC to isolate the artificial variability is used to investigate artifacts in five reanalysis systems. This procedure, although ad hoc, enables useful VMFC corrections over global land. The P − ET estimates from seven different LSMs are evaluated and subsequently used to confirm the efficacy of the RPCA-based adjustments. Global VMFC trends over the period 1979–2012 ranging from 0.07 to −0.03 mm day⁻¹ decade⁻¹ are reduced by the adjustments to 0.016 mm day⁻¹ decade⁻¹, much closer to the LSM P − ET estimate (0.007 mm day⁻¹ decade⁻¹). Neither is significant at the 90% level. ENSO-related modulation of VMFC and P − ET remains the largest global interannual signal, with mean LSM and adjusted reanalysis time series correlating at 0.86.

Abstract

Retrospective-analysis (or reanalysis) systems merge observations and models to provide global four-dimensional earth system data encompassing many physical and dynamical processes. Precipitation is one critical diagnostic that is not only sensitive to the observing system and model physics, but also reflects the general circulation. Climate records of observed precipitation through a merged satellite and gauge dataset provide a reference for comparison, though not without their own uncertainty. In this study, five reanalyses precipitation fields are compared with two observed data products to assess the strengths and weaknesses of the reanalyses. Taylor diagrams show the skill of the reanalyses relative to the reference dataset. While there is a general sense that the reanalyses precipitation data are improving in recent systems, it is not always the case. In some ocean regions, NCEP–NCAR reanalysis spatial patterns are closer to observed precipitation than NCEP–Department of Energy. The 40-yr ECMWF reanalysis (ERA-40) produces reasonable comparisons over Northern Hemisphere continents, but less so in the tropical oceans. On the other hand, the most recent reanalysis, the Japanese 25-yr reanalysis (JRA-25), shows good comparisons in both the Northern Hemisphere continents and the tropical oceans but contains distinct variation according to the available observing systems. The statistics and methods used are also tested on short experiments from a data assimilation system proposed to perform a satellite-era reanalysis.

Abstract

Like all reanalysis efforts, the Modern Era Retrospective-Analysis for Research and Applications (MERRA) must contend with an inhomogeneous observing network. Here the effects of the two most obvious observing system epoch changes, the Advanced Microwave Sounding Unit-A (AMSU-A) series in late 1998 and, to a lesser extent, the earlier advent of the Special Sensor Microwave Imager (SSM/I) in late 1987 are examined. These sensor changes affect model moisture and enthalpy increments and thus water and energy fluxes, since the latter result from model physics processes that respond sensitively to state variable forcing. Inclusion of the analysis increments in the MERRA dataset is a unique feature among reanalyses that facilitates understanding the relationships between analysis forcing and flux response.

In stepwise fashion in time, the vertically integrated global-mean moisture increments change sign from drying to moistening and heating increments drop nearly 15 W m⁻² over the 30 plus years of the assimilated products. Regression of flux quantities on an El Niño–Southern Oscillation sea surface temperature (SST) index analysis reveals that this mode of climate variability dominates interannual signals and its leading expression is minimally affected by satellite observing system changes. Conversely, precipitation patterns and other fluxes influenced by SST changes associated with Pacific decadal variability (PDV) are significantly distorted. Observing system changes also induce a nonstationary component to the annual cycle signals.

Principal component regression is found useful for identifying artifacts produced by changes of satellite sensors and defining appropriate adjustments. After the adjustments are applied, the spurious flux trend components are greatly diminished. Time series of the adjusted precipitation and the Global Precipitation Climatology Project (GPCP) data compare favorably on a global basis. The adjustments also provide a much better depiction of precipitation spatial trends associated with PDV-like forcing. The utility as well as associated drawbacks of this statistical adjustment and the prospects for future improvements of the methodology are discussed.