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Michael G. Bosilovich and Wen-yih Sun

Abstract

During the summer of 1993, persistent and heavy precipitation caused a long-lived, catastrophic flood in the midwestern United States. In this paper, Midwest hydrology, atmospheric circulation of the 1993 summer, and feedback between the surface and precipitating systems were investigated using the Purdue Regional Model (PRM). The 30-day PRM control simulations reproduced the large-scale atmospheric features that characterized the summer of 1993. Specifically, the upper-level jet stream and trough over the northwestern United States are present in control cases, as well as the Great Plains low-level jet, general pattern of moisture transport, and heavy precipitation in the Midwest. The daily precipitation record (area averaged over the heaviest rainfall) indicates that the model also reproduces the evolution and periodicity of precipitation events comparable with the observations and correctly depicts the differences between June and July.

The sensitivity of the low-level jet, planetary boundary layer, and heavy precipitation were examined by imposing various soil moisture and surface anomalies in the model simulation. The increased surface heating, caused by a strong dry anomaly, induced a large-scale surface pressure perturbation, centered in the southeastern United States, that weakened the low-level jet and moisture convergence within the flood region. Separate cases considering both wet and dry regional anomalies in the southern Great Plains caused less precipitation in the flood region. The uniform soil moisture of both anomalies leads to a reduction of the differential heating, surface pressure gradient, and the low-level jet.

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Richard I. Cullather and Michael G. Bosilovich

Abstract

The atmospheric moisture budget from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) is evaluated in polar regions for the period 1979–2005 and compared with previous estimates, accumulation syntheses over polar ice sheets, and in situ Arctic precipitation observations. The system is based on a nonspectral background model and utilizes the incremental analysis update scheme. The annual moisture convergence from MERRA for the north polar cap is comparable to previous estimates using 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) and earlier reanalyses but it is more than 50% larger than MERRA precipitation minus evaporation (PE) computed from physics output fields. This imbalance is comparable to earlier reanalyses for the Arctic. For the south polar cap, the imbalance is 20%. The MERRA physics output fields are also found to be overly sensitive to changes in the satellite observing system, particularly over data-sparse regions of the Southern Ocean. Comparisons between MERRA and prognostic fields from two contemporary reanalyses yield a spread of values from 6% of the mean over the Antarctic Ice Sheet to 61% over a domain of the Arctic Ocean. These issues highlight continued problems associated with the representation of cold-climate physical processes in global data assimilation models. The distribution of MERRA surface fluxes over the major polar ice sheets emphasizes larger values along the coastal escarpments, which agrees more closely with recent assessments of ice sheet accumulation using regional models. Differences between these results and earlier assessments illustrate a continued ambiguity in the surface moisture flux distribution over Greenland and Antarctica. The higher spatial and temporal resolution as well as the availability of all budget components, including analysis increments in MERRA, offer prospects for an improved representation of the high-latitude water cycle in reanalyses.

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Richard I. Cullather and Michael G. Bosilovich

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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 budget is reflected by the analysis increments term, which indicates an energy surplus of 11 W m−2 over the North Polar cap (70°–90°N) and 22 W m−2 over the South Polar cap (70°–90°S). Total atmospheric energy convergence from MERRA compares favorably with previous studies for northern high latitudes but exceeds the available previous estimate for the South Polar cap by 46%. Discrepancies with the Southern Hemisphere energy 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 top of atmosphere (TOA) and surface radiative fluxes are largest 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 m−2 larger than MERRA, while the MERRA downwelling longwave flux is underestimated by 12 W m−2 throughout the year. Over grounded ice sheets, the annual mean net surface energy flux in MERRA is erroneously nonzero. 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 reanalyses also disagree 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.

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Michael G. Bosilovich, Siegfried D. Schubert, and Gregory K. Walker

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In this study, numerical simulations of the twentieth-century climate are evaluated, focusing on the changes in the intensity of the global water cycle. A new model diagnostic of atmospheric water vapor cycling rate is developed and employed that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values with more variability.

Climate simulations were performed using SSTs of the early (1902–21) and late (1979–98) twentieth century along with the appropriate CO2 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-yr climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the simulated hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend, while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America, experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These model diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

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Allison B. Marquardt Collow, Richard I. Cullather, and Michael G. Bosilovich

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Surface air temperatures have recently increased more rapidly in the Arctic than elsewhere in the world, but large uncertainty remains in the time series and trend. Over the data-sparse sea ice zone, the retrospective assimilation of observations in numerical reanalyses has been thought to offer a possible, but challenging, avenue for adequately reproducing the historical time series. Focusing on the central Arctic Ocean, output is analyzed from 12 reanalyses with a specific consideration of two widely used products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereafter ERA-I). Among the reanalyses considered, a trend of 0.9 K decade−1 is indicated but with an uncertainty of 6%, and a large spread in mean values. There is a partitioning among those reanalyses that use fractional sea ice cover and those that employ a threshold, which are colder in winter by an average of 2 K but agree more closely with in situ observations. For reanalyses using fractional sea ice cover, discrepancies in the ice fraction in autumn and winter explain most of the differences in air temperature values. A set of experiments using the MERRA-2 background model using MERRA-2 and ERA-I sea ice and sea surface temperature indicates significant effects of boundary condition differences on air temperatures, and a preferential warm bias inherent in the MERRA-2 model sea ice representation. Differences between experiments and reanalyses suggest the available observations apply a significant constraint on reanalysis mean temperatures.

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Michael G. Bosilovich, Franklin R. Robertson, and Paul W. Stackhouse

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.

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Franklin R. Robertson, Michael G. Bosilovich, and Jason B. Roberts

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.

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Michael G. Bosilovich, Franklin R. Robertson, and Junye Chen

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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.

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Mark Decker, Michael A. Brunke, Zhuo Wang, Koichi Sakaguchi, Xubin Zeng, and Michael G. Bosilovich

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Reanalysis products produced at the various centers around the globe are utilized for many different scientific endeavors, including forcing land surface models and creating surface flux estimates. Here, flux tower observations of temperature, wind speed, precipitation, downward shortwave radiation, net surface radiation, and latent and sensible heat fluxes are used to evaluate the performance of various reanalysis products [NCEP–NCAR reanalysis and Climate Forecast System Reanalysis (CFSR) from NCEP; 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ECMWF Interim Re-Analysis (ERA-Interim) from ECMWF; and Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Global Land Data Assimilation System (GLDAS) from the Goddard Space Flight Center (GSFC)]. To combine the biases and standard deviation of errors from the separate stations, a ranking system is utilized. It is found that ERA-Interim has the lowest overall bias in 6-hourly air temperature, followed closely by MERRA and GLDAS. The variability in 6-hourly air temperature is again most accurate in ERA-Interim. ERA-40 is found to have the lowest overall bias in latent heat flux, followed closely by CFSR, while ERA-40 also has the lowest 6-hourly sensible heat bias. MERRA has the second lowest and is close to ERA-40. The variability in 6-hourly precipitation is best captured by GLDAS and ERA-Interim, and ERA-40 has the lowest precipitation bias. It is also found that at monthly time scales, the bias term in the reanalysis products are the dominant cause of the mean square errors, while at 6-hourly and daily time scales the dominant contributor to the mean square errors is the correlation term. Also, it is found that the hourly CFSR data have discontinuities present due to the assimilation cycle, while the hourly MERRA data do not contain these jumps.

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Michael G. Bosilovich, Jiun-Dar Chern, David Mocko, Franklin R. Robertson, and Arlindo M. da Silva

Abstract

The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model or perhaps assimilating data from an inconsistent observing system. In the MERRA reanalysis, an area of long-term moisture flux divergence over land has been identified over the central United States. Here, the water vapor budget is evaluated in this region, taking advantage of two unique features of the MERRA diagnostic output: 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output dataset of the assimilated observations and their innovations (e.g., forecast departures).

In the central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRA’s Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 0600 and 1800 UTC analysis cycles, when radiosonde information is not prevalent. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSU-A (mainly window channels) and Atmospheric Infrared Sounder (AIRS). This effort also shows the complexities of the observing system and the reactions of the regional water budgets in reanalyses to the assimilated observations.

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