Large-Scale Influences on Atmospheric River Induced Extreme Precipitation Events Along the Coast of Washington State

Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. In order to accurately predict AR events in numerical weather prediction, subseasonal and seasonal timescales, it is important to understand the large-scale meteorological influence on extreme AR events.Here, characteristics of ARs that result in an extreme precipitation event are compared to typical ARs on the coast of WashingtonState. In addition to more intense water vapor transport, notable differences in the synoptic forcing are present during extreme precipitation events that are not present during typical AR events.In particular, a negatively tilted low pressure system is positioned to the west in the Gulf of Alaska, alongside an upper level jet streak. Subseasonal and seasonal teleconnection patterns are known to influence the weather in the Pacific Northwest. The Madden JulianOscillation (MJO) is shown to be particularly important in determining the strength of precipitation associated with in AR ont he Washington coast

El Nino-Induced Tropical Ocean/Land Energy Exchange in MERRA-2 and M2AMIP

Studies have shown the correlation and connection of surface temperatures across the globe, ocean and land, related to Tropical SSTs especially El Nino. This climate variability greatly influences regional weather and hydroclimate extremes (e.g. drought and flood). In this paper, we evaluate the relationship of temperatures across the tropical oceans and continents in MERRA-2, and also in a newly developed MERRA-2 AMIP ensemble simulation (M2AMIP). M2AMIP uses the same model and spatial resolution as MERRA-2, producing the same output diagnostics over 10 ensemble members. Composite El Nino temperature data are compared with observations to evaluate the land/sea contrast, variations and phase relationship. The temperature variations are related to surface heat fluxes and the atmospheric temperatures and transport, to identify the processes that lead to the lagged redistribution of heat in the tropics and beyond. Discernable cloud, radiation and data assimilation changes accompany the onset of El Nino affecting continental regions through the progression to and following the peak values. While the model represents these variations in general, regional strengths and weaknesses can be identified

The Energy Budget of the Polar Atmosphere in MERRA

Components of the atmospheric energy budget from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are evaluated in polar regions for the period 1979-2005 and compared with previous estimates, in situ observations, and contemporary reanalyses. Closure of the energy budget is reflected by the analysis increments term, which results from virtual enthalpy and latent heating contributions and averages -11 W/sq m over the north polar cap and -22 W/sq m over the south polar cap. Total energy tendency and energy convergence terms from MERRA agree closely with previous study for northern high latitudes but convergence exceeds previous estimates for the south polar cap by 46 percent. Discrepancies with the Southern Hemisphere transport are largest in autumn and may be related to differences in topography with earlier reanalyses. For the Arctic, differences between MERRA and other sources in TOA and surface radiative fluxes maximize in May. These differences are concurrent with the largest discrepancies between MERRA parameterized and observed surface albedo. For May, in situ observations of the upwelling shortwave flux in the Arctic are 80 W/sq m larger than MERRA, while the MERRA downwelling longwave flux is underestimated by 12 W/sq m throughout the year. Over grounded ice sheets, the annual mean net surface energy flux in MERRA is erroneously non-zero. Contemporary reanalyses from the Climate Forecast Center (CFSR) and the Interim Re-Analyses of the European Centre for Medium Range Weather Forecasts (ERA-I) are found to have better surface parameterizations, however these collections are also found to have significant discrepancies with observed surface and TOA energy fluxes. Discrepancies among available reanalyses underscore the challenge of reproducing credible estimates of the atmospheric energy budget in polar regions

Global Energy and Water Budgets in MERRA

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, called the Modern Era Retrospective-analysis for Research and Applications (MERRA), from a global water and energy cycles perspective. 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 (GPCP and CMAP) than previous generations of reanalyses. Ocean evaporation also has a much lower value which is comparable to observed data sets. 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, which 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 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

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model

Water Cycle Variability over the Oceans Estimated Using Homogenized Reanalysis Fluxes

No abstract availabl

Reconciling Land-Ocean Moisture Transport Variability in Reanalyses with P-ET in Observationally-Driven Land Surface Models

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 equals P minus 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 minus 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 minus 0.03 millimeters per day per decade are reduced by the adjustments to 0.016 millimeters per day per decade, much closer to the LSM P minus ET estimate (0.007 millimeters per day per decade). Neither is significant at the 90 percent level. ENSO (El Nino-Southern Oscillation)-related modulation of VMFC and P minus ET remains the largest global interannual signal, with mean LSM and adjusted reanalysis time series correlating at 0.86

Ocean / Land Moisture Transport: Estimates from Reanalyses, Satellites and Land Surface Models

No abstract availabl

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus

Inter-Annual to Inter-Decadal Variability in Ocean / Land Moisture Transport: Estimates from Reanalyses, Satellites and Land Surface Models

No abstract availabl