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Abstract
Turbulent fluxes of heat and moisture across the atmosphere–ocean interface are fundamental components of the earth’s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere–ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) product in terms of its turbulent surface fluxes. This assessment employs a large dataset of directly measured turbulent fluxes as well as other turbulent surface flux datasets. The spatial and temporal variability of the surface fluxes are examined in terms of their annual-mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of the incremental analysis update tendencies. It is found that MERRA turbulent surface fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm-track regions. The assimilation of observations generally acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds.
Abstract
Turbulent fluxes of heat and moisture across the atmosphere–ocean interface are fundamental components of the earth’s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere–ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) product in terms of its turbulent surface fluxes. This assessment employs a large dataset of directly measured turbulent fluxes as well as other turbulent surface flux datasets. The spatial and temporal variability of the surface fluxes are examined in terms of their annual-mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of the incremental analysis update tendencies. It is found that MERRA turbulent surface fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm-track regions. The assimilation of observations generally acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds.
Abstract
Closing and balancing Earth’s global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to inhomogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified, MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.
Abstract
Closing and balancing Earth’s global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to inhomogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified, MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.
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.
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.
Abstract
A methodology is developed for deriving atmospheric water vapor transports over the World Oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets. The motivation for developing the method is to understand climatically varying properties of transports, that is, year-to-year changes of the seasonally averaged divergent transport distribution fields, over regions where conventional data, in particular, winds, are sparse. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E − P datasets obtained from satellite measurements. Separate P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain the transport solutions.
In this opening study, a 7-yr climatological normal is derived for the January–February–March (JFM) period for years 1988–94, providing the basis for comparing vapor transport anomalies from the 1997/98 El Niño and 1999/2000 La Niña events. These are derived from JFM-averaged transport solutions for 1998 and 1999, respectively. These two periods correspond to times when the Multivariate ENSO Index (MEI) provided by the NOAA Climatic Data Center (CDC) was first at a relative maximum and then at a relative minimum in conjunction with back-to-back west Pacific warm and cold events. Because the El Niño–La Niña events produce such highly contrasting behavior in the transports, shifting from a largely meridionally oriented solution to a largely zonally oriented solution, focusing on this pairing, helps to explain why the methodology is reliable and effective in capturing important details embedded in full-coverage E − P fields.
The analysis includes a sensitivity study of the transport solution technique based on 20 combinations of four precipitation datasets (two satellite based and two model based) and five evaporation datasets (two satellite based, one in situ observation based, and two model based), which helps to explain the reliability of the method. The analysis also includes a comparison to water vapor transports derived with the same method, but applied to E − P datasets obtained from global analysis products prepared by the National Centers of Environmental Prediction (NCEP), again to help explain the reliability of the method. The study concludes by first showing how the anomaly JFM 1998 El Niño solution behaves in close correspondence to associated SST anomalies and is generally more realistic in comparison to the corresponding NCEP solution. Finally, its reliability is discussed in terms of the implications of the vapor transport features for the El Niño–La Niña transition, vis-à-vis north–south and east–west circulations and their accompanying impact on the atmospheric hydrological cycle.
Abstract
A methodology is developed for deriving atmospheric water vapor transports over the World Oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets. The motivation for developing the method is to understand climatically varying properties of transports, that is, year-to-year changes of the seasonally averaged divergent transport distribution fields, over regions where conventional data, in particular, winds, are sparse. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E − P datasets obtained from satellite measurements. Separate P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain the transport solutions.
In this opening study, a 7-yr climatological normal is derived for the January–February–March (JFM) period for years 1988–94, providing the basis for comparing vapor transport anomalies from the 1997/98 El Niño and 1999/2000 La Niña events. These are derived from JFM-averaged transport solutions for 1998 and 1999, respectively. These two periods correspond to times when the Multivariate ENSO Index (MEI) provided by the NOAA Climatic Data Center (CDC) was first at a relative maximum and then at a relative minimum in conjunction with back-to-back west Pacific warm and cold events. Because the El Niño–La Niña events produce such highly contrasting behavior in the transports, shifting from a largely meridionally oriented solution to a largely zonally oriented solution, focusing on this pairing, helps to explain why the methodology is reliable and effective in capturing important details embedded in full-coverage E − P fields.
The analysis includes a sensitivity study of the transport solution technique based on 20 combinations of four precipitation datasets (two satellite based and two model based) and five evaporation datasets (two satellite based, one in situ observation based, and two model based), which helps to explain the reliability of the method. The analysis also includes a comparison to water vapor transports derived with the same method, but applied to E − P datasets obtained from global analysis products prepared by the National Centers of Environmental Prediction (NCEP), again to help explain the reliability of the method. The study concludes by first showing how the anomaly JFM 1998 El Niño solution behaves in close correspondence to associated SST anomalies and is generally more realistic in comparison to the corresponding NCEP solution. Finally, its reliability is discussed in terms of the implications of the vapor transport features for the El Niño–La Niña transition, vis-à-vis north–south and east–west circulations and their accompanying impact on the atmospheric hydrological cycle.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
Abstract
Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) single-sensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s.
Abstract
Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) single-sensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s.
Abstract
The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.
By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses.
Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).
Abstract
The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.
By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses.
Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).
