Modern-Era Retrospective Analysis For Research And Applications Reanalysis Research Articles

Influence of atmospheric rivers in the occurrence of devastating flood associated with extreme precipitation events over Chennai using different reanalysis data sets

The main focus of the present study is to examine the presence of Atmospheric Rivers (ARs) in the occurrence of Chennai (13.5° N, 80.5° E) flood event over Tamil Nadu which is south-eastern part of Indian peninsular region of India during November to December 2015. The vertically integrated horizontal water vapor transport (IVT) algorithm was used for the detection of ARs using three different reanalysis products, namely, the NCEP-NCAR (National Center for Atmospheric Research), NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and ECMWF Interim Re-Analysis (ERA-Interim). It is noticed that the occurrence of heavy precipitation events (HPEs) prior to the flood in the Chennai city, has been in good agreement with the presence of ARs during that time. The distribution from TRMM-3B42RT, TRMM-3B42 are validated with the with in situ rain gauge observations over the Chennai city. We have conducted quantitative analysis of IVT and their impact on heavy precipitation events and flood occurred over Chennai city. It is seen that MERRA reanalysis could be able to provide better presence of ARs. The study mainly reveals that persistent ARs of >18 h resulted in extremely heavy precipitation and lead to associated flood over Chennai. Also, the atmospheric conditions, ARs and rainfall simulated from Advanced Research Weather Research and Forecasting model (ARW) show good agreement with reanalysis and observations. Over the given reference period 1979–2015, correlation between IVT and HPEs is statistically significant at 99.5% confidence level. But the correlation between IVT during persistent ARs and corresponding HPEs is statistically significant at 90% confidence level. A large fraction of HPEs occur after ARs, with a small portion of ARs would lead to HPEs. The Chennai gird historical rainfall data is suitably fitted by Extreme Value Distribution (EVD) models. Inference model using the Maximum Likelihood Estimation (MLE) was applied on EVD considering their impact on the shape parameter and the confidence interval width. A Non-stationary generalized extreme value (GEV) analysis, was used to determine the strength of association between the precipitation extremes and IVT. The influence of the location and the scale parameter in the GEV model on different return levels (2-year, 20-year, and 100-year) are explicitly described. The return-level threshold values are found to change with IVT considerably. This study advocates that the detection of ARs can be used as important proxy in identifying the likelihood of occurrence of heavy precipitation/flash flood events for a given location using reanalysis data sets.

Characteristics and mechanisms of the diurnal variation of winter precipitation in Taiwan

Using gridded precipitation data remapping from rain‐gauge observations of the time period of 2001–2015 winter months (December, January and February), this study examines the spatio‐temporal characteristics of the climatological diurnal winter precipitation in Taiwan. Our results show that the timings of the maximum values of the diurnal precipitation in Taiwan exhibit clear east–west regional differences, with night‐time maxima over eastern Taiwan but early morning maxima over western Taiwan. Analyses also show that the climatological characteristics of diurnal winter precipitation documented in this study are not controlled by some unusual, heavy precipitation events and can be seen as the common features. By examining the changes in meteorological variables (including winds, relative humidity and temperature) extracted from the in situ observations and the MERRA (Modern‐Era Retrospective Analysis for Research and Applications) reanalysis, this study further suggests that (a) the radiative cooling effect and (b) the surface wind convergence induced by the interaction between the local orography, the local land–sea breeze and the large‐scale diurnal circulation changes over the East Asian–western North Pacific (EAWNP) region are two of the possible formation mechanisms responsible for the spatio‐temporal differences of the climatological diurnal winter precipitation in Taiwan. This finding sheds light on the importance of understanding the role of the large‐scale diurnal circulation changes over the EAWNP region in modulating local diurnal precipitation properties during the winter months.

A climatology of Rossby wave generation in the middle atmosphere of the Southern Hemisphere from MERRA reanalysis

AbstractA climatological characterization of Rossby wave generation events in the middle atmosphere of the Southern Hemisphere is conducted using 20 years of Modern‐Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. An automatic detection technique of wave generation events is developed and applied to MERRA reanalysis. The Rossby wave generation events with wave period of 1.25 to 5.5 days and zonal wave number from one to three dominate the Eliassen‐Palm flux divergence around the stratopause at high latitudes in the examined 20 year period. These produce an eastward forcing of the general circulation between May and mid‐August in that region. Afterward from mid‐August to the final warming date, Rossby wave generation events are still present but the Eliassen‐Palm flux divergence in the polar stratopause is dominated by low‐frequency Rossby waves that propagate from the troposphere. The Rossby wave generation events are associated with potential vorticity gradient inversion, and so they are a manifestation of the dominant barotropic/baroclinic unstable modes that grow at the cost of smearing the negative meridional gradient of potential vorticity. The most likely region of wave generation is found between 60° and 80°S and at a height of 0.7 hPa, but events were detected from 40 hPa to 0.3 hPa (which is the top of the examined region). The mean number of events per year is 24, and its mean duration is 3.35 days. The event duration follows an exponential distribution.

Non-Gaussian Analysis of Observations from the Atmospheric Infrared Sounder Compared with ERA and MERRA Reanalyses

AbstractStatistical relationships between higher-order moments of probability density functions (PDFs) are used to analyze top-of-atmosphere radiance measurements made by the Atmospheric Infrared Sounder (AIRS) and radiance calculations from the ECMWF Re-Analysis (ERA) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) over a 10-yr period. The statistical analysis used in this paper has previously been applied to sea surface temperature, and here the authors show that direct satellite radiance observations of atmospheric variability also exhibit stochastic forcing characteristics. The authors have chosen six different AIRS channels based on the sensitivity of their measured radiances to a variety of geophysical properties. In each of these channels, the authors have found evidence of correlated additive and multiplicative (CAM) stochastic forcing. In general, channels sensitive to tropospheric humidity and surface temperature show the strongest evidence of CAM forcing, while those sensitive to stratospheric temperature and ozone exhibit the weakest forcing. Radiance calculations from ERA and MERRA agree well with AIRS measurements in the Gaussian part of the PDFs but show some differences in the tails, indicating that the reanalyses may be missing some extrema there. The CAM forcing is investigated through numerical simulation of simple stochastic differential equations (SDEs). The authors show how measurements agree better with weaker CAM forcing, achieved by reducing the multiplicative forcing or by increasing the spatial correlation of the added noise in the case of an SDE with one spatial dimension. This indicates that atmospheric models could be improved by adjusting nonlinear terms that couple long and short time scales.

Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration–Clouds and the Earth’s Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

The impact of gravity waves and cloud nucleation threshold on stratospheric water and tropical tropospheric cloud fraction

AbstractUsing the Modern Era Retrospective‐Analysis for Research and Applications (MERRA) and MERRA‐2 reanalysis winds, temperatures, and anvil cloud ice, we explore the impact of varying the cloud nucleation threshold relative humidity (RH) and high‐frequency gravity waves on stratospheric water vapor (H2O) and upper tropical tropopause cloud fraction (TCF). Our model results are compared to 2008/2009 winter TCF derived from Cloud‐Aerosol Lidar with Orthogonal Polarization and H2O observations from the Microwave Limb Sounder (MLS). The RH threshold affects both model H2O and TCF, while high‐frequency gravity waves mostly impact TCF. Adjusting the nucleation RH and the amplitude of high‐frequency gravity waves allows us to tune the model to observations. Reasonable observational agreement is obtained with a nucleation threshold between 130% and 150% RH consistent with airborne observations. For the MERRA reanalysis, we lower the tropopause temperature by 0.5 K roughly consistent with GPS radio occultation measurements and include ~0.1 K high‐frequency gravity wave temperature oscillations in order to match TCF and H2O observations. For MERRA‐2 we do not need to adjust the tropopause temperature nor add gravity waves, because there are sufficient high‐frequency temperature oscillations already present in the MERRA‐2 reanalysis to reproduce the observed TCF.

Modeling of Soybean under Present and Future Climates in Mozambique

This study aims to calibrate and validate the generic crop model (CROPGRO-Soybean) and estimate the soybean yield, considering simulations with different sowing times for the current period (1990–2013) and future climate scenario (2014–2030). The database used came from observed data, nine climate models of CORDEX (Coordinated Regional climate Downscaling Experiment)-Africa framework and MERRA (Modern Era Retrospective-Analysis for Research and Applications) reanalysis. The calibration and validation data for the model were acquired in field experiments, carried out in the 2009/2010 and 2010/2011 growing seasons in the experimental area of the International Institute of Tropical Agriculture (IITA) in Angónia, Mozambique. The yield of two soybean cultivars: Tgx 1740-2F and Tgx 1908-8F was evaluated in the experiments and modeled for two distinct CO2 concentrations. Our model simulation results indicate that the fertilization effect leads to yield gains for both cultivars, ranging from 11.4% (Tgx 1908-8F) to 15% (Tgx 1740-2Fm) when compared to the performance of those cultivars under current CO2 atmospheric concentration. Moreover, our results show that MERRA, the RegCM4 (Regional Climatic Model version 4) and CNRM-CM5 (Centre National de Recherches Météorologiques – Climatic Model version 5) models provided more accurate estimates of yield, while others models underestimate yield as compared to observations, a fact that was demonstrated to be related to the model’s capability of reproducing the precipitation and the surface radiation amount.

Trends of regional precipitation and their control mechanisms during 1979–2013

Trends in precipitation are critical to water resources. Considerable uncertainty remains concerning the trends of regional precipitation in response to global warming and their controlling mechanisms. Here, we use an interannual difference method to derive trends of regional precipitation from GPCP (Global Precipitation Climatology Project) data and MERRA (Modern- Era Retrospective Analysis for Research and Applications) reanalysis in the near-global domain of 60°S–60°N during a major global warming period of 1979–2013. We find that trends of regional annual precipitation are primarily driven by changes in the top 30% heavy precipitation events, which in turn are controlled by changes in precipitable water in response to global warming, i.e., by thermodynamic processes. Significant drying trends are found in most parts of the U.S. and eastern Canada, the Middle East, and eastern South America, while significant increases in precipitation occur in northern Australia, southern Africa, western India and western China. In addition, as the climate warms there are extensive enhancements and expansions of the three major tropical precipitation centers–the Maritime Continent, Central America, and tropical Africa–leading to the observed widening of Hadley cells and a significant strengthening of the global hydrological cycle.

Indian summer monsoon precipitating clouds: role of microphysical process rates

The budget analysis of microphysical process rates based on Modern Era Retrospective-analysis for Research and Applications (MERRA) products are presented in the study. The relative importance of different microphysical process rates, which is crucial for GCMs, is investigated. The autoconversion and accretion processes are found to be vital for Indian Summer Monsoon (ISM). The map-to-map correlations are examined between observed precipitation and MERRA reanalysis. The pattern correlations connote the fidelity of the MERRA datasets used here. Results of other microphysical parameters (e.g. ice water content from CloudSat, high cloud fraction from CALIPSO and MODIS, latent heating from TRMM, cloud ice mixing ratio from MERRA) are presented in this study. The tropospheric temperature from reanalysis product of MERRA and NCEP are also analyzed. Furthermore, the linkages between cloud microphysics production rates and dynamics, which are important for North–South tropospheric temperature gradient for maintaining the ISM circulation, are also discussed. The study demonstrates the microphysical process rates, which are actually responsible for the cloud hydrometeors and precipitation formation on the monsoon intraseasonal oscillations timescale. Cloud to rain water auto-conversion and snow accretion rates are the dominant processes followed by the rain accretion. All these tendency terms replicates the similar spatial patterns as that of precipitation. The quantification of microphysical process rates and precipitation over different regions are shown here. The freezing rate is also imperative for the formation of cloud ice as revealed by the observation. Freezing rates at upper level and snow accretion at middle level may have effect on latent heating release. Further it can modulate the north–south temperature gradient which can influence the large-scale monsoon dynamics. The rain water evaporation is also considered as a key aspect for controlling the low level moisture convergence (source of water vapor) in ISM. This study has highlighted the importance of detailed microphysical production rates for warm and mixed-phase cloud processes, which is a major source of uncertainty in the climate models. Better understanding of these processes will definitely add value to the present generation climate models. Therefore the hypothesis/pathway emerged from the present study may be helpful for the future model development research.

Comparisons of polar processing diagnostics from 34 years of the ERA-Interim and MERRA reanalyses

Abstract. We present a comprehensive comparison of polar processing diagnostics derived from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective-analysis for Research and Applications (MERRA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim). We use diagnostics that focus on meteorological conditions related to stratospheric chemical ozone loss based on temperatures, polar vortex dynamics, and air parcel trajectories to evaluate the effects these reanalyses might have on polar processing studies. Our results show that the agreement between MERRA and ERA-Interim changes significantly over the 34 years from 1979 to 2013 in both hemispheres and in many cases improves. By comparing our diagnostics during five time periods when an increasing number of higher-quality observations were brought into these reanalyses, we show how changes in the data assimilation systems (DAS) of MERRA and ERA-Interim affected their meteorological data. Many of our stratospheric temperature diagnostics show a convergence toward significantly better agreement, in both hemispheres, after 2001 when Aqua and GOES (Geostationary Operational Environmental Satellite) radiances were introduced into the DAS. Other diagnostics, such as the winter mean volume of air with temperatures below polar stratospheric cloud formation thresholds (VPSC) and some diagnostics of polar vortex size and strength, do not show improved agreement between the two reanalyses in recent years when data inputs into the DAS were more comprehensive. The polar processing diagnostics calculated from MERRA and ERA-Interim agree much better than those calculated from earlier reanalysis data sets. We still, however, see fairly large differences in many of the diagnostics in years prior to 2002, raising the possibility that the choice of one reanalysis over another could significantly influence the results of polar processing studies. After 2002, we see overall good agreement among the diagnostics, which demonstrates that the ERA-Interim and MERRA reanalyses are equally appropriate choices for polar processing studies of recent Arctic and Antarctic winters.

The MOPITT Version 6 product: algorithm enhancements and validation

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) Version 6 (V6) product for carbon monoxide (CO) incorporates several enhancements which will benefit many users of MOPITT data. V6 algorithm improvements are described in detail, and V6 validation results are presented. First, a geolocation bias related to the orientation of the MOPITT instrument relative to the TERRA platform was characterized and eliminated. Second, the variable a priori for CO concentrations for V6 is based on simulations performed with the chemical transport model Community Atmosphere Model with Chemistry (CAM-chem) for the years 2000–2009 instead of the model-derived climatology for 1997–2004 used for V5. Third, meteorological fields required for V6 retrieval processing are extracted from the MERRA (Modern-Era Retrospective Analysis For Research And Applications) reanalysis. Finally, a significant latitude-dependent retrieval bias in the upper troposphere in Version 5 products has been substantially reduced.

Changes in the Brewer-Dobson circulation for 1980–2009 revealed in MERRA reanalysis data

Changes in the Brewer-Dobson circulation (BDC) during the 30 years 1980–2009 are investigated using Modern Era Retrospective-analysis for Research and Applications (MERRA) reanalysis data. The mass streamfunction that is induced by wave forcings in the transformed Eulerian-mean (TEM) equation through the downward-control principle is used as a proxy for the BDC. The changes in the BDC are investigated using two aspects: the wave propagation conditions in the stratosphere and the wave activity in the upper troposphere. They are compared in the first (P1) and second (P2) 15-year periods. The resolved wave forcing, expressed by the Eliassen-Palm (EP) flux divergence (EPD), is significantly enhanced during the December-January-February (DJF) season in P2 in both the Northern Hemisphere (NH) high latitudes and the Southern Hemisphere (SH) mid- and high latitudes. The increased zonal mean zonal wind at high latitudes in the SH, caused by ozone depletion, leads to an upward shift of the Rossby-wave critical layer and this allows more transient planetary waves to propagate into the stratosphere. In the NH, the enhanced EPD in DJF leads to an increase in the frequency of Sudden Stratospheric Warming (SSW) events. The gravity wave drag (GWD) is smaller than the EPD and the change in it between the two time periods is insignificant. The residual term in the TEM equation is similar to the GWD in the two periods, but its change between the two periods is as large as the change in the EPD. Among the four components of the EP flux at 250 hPa, the meridional heat flux played a dominant role in the enhancement of the BDC in P2.

Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface

This paper compares the daily solar irradiation available at surface estimated by the MERRA (Modern-Era Retrospective Analysis for Research and Applications) re-analysis of the NASA and the ERA-Interim re-analysis of the European Center for Medium-range Weather Forecasts (ECMWF) against qualified ground measurements made in stations located in Europe, Africa and Atlantic Ocean. Using the clearness index, also known as atmospheric transmissivity or transmittance, this study evidences that the re-analyses often predict clear sky conditions while actual conditions are cloudy. The opposite is also true though less pronounced: actual clear sky conditions are predicted as cloudy. This overestimation of occurrence of clear sky conditions leads to an overestimation of the irradiation and clearness index by MERRA. The overall overestimation is less pronounced for ERA-Interim because the overestimation observed in clear sky conditions is counter-balanced by underestimation in cloudy conditions. The squared correlation coefficient for clearness index ranges between 0.38 and 0.53, showing that a very large part of the variability in irradiation is not captured by the re-analyses. Within an irradiation homogeneous area, the variability of the bias, root mean square error and correlation coefficient are surprisingly large. MERRA and ERA-Interim should only be used in solar energy with proper understanding of the limitations and uncertainties. In regions where clouds are rare, e.g. North Africa, MERRA or ERA-Interim may be used to provide a gross estimate of monthly or yearly irradiation. Satellite-derived data sets offer less uncertainty and should be preferred.

Tidal signatures in temperatures derived from daylight lidar soundings above Kühlungsborn (54°N, 12°E)

We have developed a new Rayleigh–Mie–Raman (RMR) lidar at the mid-latitude station in Kühlungsborn (54°N, 12°E) for analyzing geophysical phenomena at day and night, e.g., temperature tides and Noctilucent Clouds. For this study we have used about 3100h of data since April 2011 with additional data from summer 2010. The RMR lidar was in operation day and night in addition to the existing daylight-capable potassium resonance lidar. We show for the first time an overview of the altitude structure and seasonal variation of temperature tides, observed with lidars between 40 and 100km altitude at a mid-latitude site. There is a gap around 80km altitude due to a decreasing signal-to-noise ratio during the day. We derive mean tidal amplitudes and phases with 24-, 12-, and 8-h period. In most of the months, the diurnal component dominates the other tidal components with mean amplitudes of 1–2K in the stratopause region (45–55km altitude), where it is up to three times higher than semidiurnal and terdiurnal tidal amplitudes. The diurnal tide is damped at ∼60km altitude. In the mid-mesosphere (65–70km) diurnal, semidiurnal, and terdiurnal tidal components have comparable mean amplitudes of about 1–1.5K, except around the equinoxes. Around the mesopause the diurnal tide dominates again, with mean amplitudes of about 4K, but with a large variability. The seasonal variation shows a conspicuous structure below ∼65km altitude with tidal amplitudes small in summer and large around the equinoxes. This structure vanishes above ∼65km. There, the amplitude increases in summer. The measured tidal amplitudes and phases are compared with the MERRA (Modern Era Retrospective analysis for Research and Applications) reanalysis data. Repeated soundings in subsequent years allow to examine the year-to-year variation. The data from March in both 2012 and 2013 show a prominent diurnal tide at around 45km altitude with amplitudes about three times larger than in the other months. The short-term variability can be examined from continuous lidar operations during clear-sky periods. In a case study we show a large variability of the tidal amplitudes, especially the 8-h variation. This can only be examined due to a good temporal coverage of the lidar data.

Dynamics of Landfalling Atmospheric Rivers over the North Pacific in 30 Years of MERRA Reanalysis

Abstract A large-scale analysis of landfalling atmospheric rivers (ARs) along the west coast of North America and their association with the upper-tropospheric flow is performed for the extended winter (November–March) for the years 1979–2011 using Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis data. The climatology, relationship to the El Niño–Southern Oscillation and the Madden–Julian oscillation, and upper-level characteristics of approximately 750 landfalling ARs are presented based on the 85th percentile of peak daily moisture flux. AR occurrence along the West Coast is dominated by early season events. In composites of upper-level fields during AR occurrences, certain characteristics stand out irrespective of the tropical climate indices. This suggests that extratropical dynamical processes play a key role in AR dynamics. The influence of the large-scale circulation on AR intensity prior to landfall is examined by objectively selecting an extreme subset of 112 landfalling AR dates representing the 95th percentile of strongest cases. Each landfalling AR date that is identified is traced backward in time using a novel semiautomated tracking algorithm based on spatially and temporally connected organized features in integrated moisture transport. Composites of dynamical fields following the eastward progression of ARs show a close relationship of the location of the jet, Rossby wave propagation, and anticyclonic Rossby wave breaking in the upper troposphere of the eastern Pacific and moisture transport in the lower troposphere. Comparison between the strongest and the weakest ARs within the most extreme subset shows differences in both the intensity of moisture transport and the scale and development of anticyclonic Rossby wave breaking in the eastern Pacific.

The Vorticity Budgets of North Atlantic Winter Extratropical Cyclone Life Cycles in MERRA Reanalysis. Part II: Decaying Phase*

Abstract The role of physical forcing mechanisms that contribute to the decay of winter North Atlantic extratropical cyclones during the period 1979–2009 are examined using the Modern-Era Retrospective Analysis for Research and Applications (MERRA). The paired Zwack–Okossi tendency equation and omega equation explained in part I of this paper is employed to investigate the total effects of forcing processes (the direct effect of the forcing mechanisms and the indirect effect of the induced adiabatic cooling) that dissipate the 950-hPa cyclonic geostrophic vorticity at the cyclone center. Composite analyses reveal that the commencement of the decay is associated mainly with the upper-level anticyclonic vorticity advection, cold-air advection, and positive ageostrophic vorticity tendency. The secondary contributor to the dissipation of cyclonic circulation is the lower-tropospheric adiabatic cooling induced mainly by friction and positive ageostrophic vorticity tendency. The dynamics is found to be different at the beginning of the decay than in the later stages. While the negative tilt of troughs aloft and the surface cyclone is required for cyclolysis to occur, low air processes show a greater effect in the termination of the low pressure systems. Further, the total effect of the vorticity advection and temperature advection terms are modest, while the ageostrophic vorticity tendency and friction terms show a greater total negative contribution. This is because the two latter terms decrease the cyclonic geostrophic vorticity at the low center through both their direct and indirect effects. The latent heat release maximizing at 800–700 hPa produces cyclonic circulation, thus reducing the spindown of decaying cyclones.

An Analogue Approach to Identify Heavy Precipitation Events: Evaluation and Application to CMIP5 Climate Models in the United States

Abstract An analogue method is presented to detect the occurrence of heavy precipitation events without relying on modeled precipitation. The approach is based on using composites to identify distinct large-scale atmospheric conditions associated with widespread heavy precipitation events across local scales. These composites, exemplified in the south-central, midwestern, and western United States, are derived through the analysis of 27-yr (1979–2005) Climate Prediction Center (CPC) gridded station data and the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). Circulation features and moisture plumes associated with heavy precipitation events are examined. The analogues are evaluated against the relevant daily meteorological fields from the MERRA reanalysis and achieve a success rate of around 80% in detecting observed heavy events within one or two days. The method also captures the observed interannual variations of seasonal heavy events with higher correlation and smaller RMSE than MERRA precipitation. When applied to the same 27-yr twentieth-century climate model simulations from Phase 5 of the Coupled Model Intercomparison Project (CMIP5), the analogue method produces a more consistent and less uncertain number of seasonal heavy precipitation events with observation as opposed to using model-simulated precipitation. The analogue method also performs better than model-based precipitation in characterizing the statistics (minimum, lower and upper quartile, median, and maximum) of year-to-year seasonal heavy precipitation days. These results indicate the capability of CMIP5 models to realistically simulate large-scale atmospheric conditions associated with widespread local-scale heavy precipitation events with a credible frequency. Overall, the presented analyses highlight the improved diagnoses of the analogue method against an evaluation that considers modeled precipitation alone to assess heavy precipitation frequency.

MERRA Analytic Services: Meeting the Big Data challenges of climate science through cloud-enabled Climate Analytics-as-a-Service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS built on this principle. MERRA/AS enables MapReduce analytics over NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRA/AS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers’ increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing’s capacity to engage communities in the construction of new capabilities is perhaps the most important link between Cloud Computing and Big Data.

Moist dynamics of active/break cycle of Indian summer monsoon rainfall from NCEPR2 and MERRA reanalysis

ABSTRACTThe vertically integrated moisture and moist static energy (MSE) budgets during the active and break phases of Indian summer monsoon are studied using National Centers for Environmental Prediction Reanalysis2 (NCEPR2) and Modern Era Retrospective Analysis for Research and Applications (MERRA) data. The different parameterization procedures adopted by the reanalysis models will impose inevitable differences between the reanalysis products, which will make an impact on their intraseasonal oscillation (ISO) also. At the same time, the agreement of the moisture budget terms of the reanalysis products has enabled us to come up with a common moisture mechanism responsible for the ISO. Estimates of the moisture budget indicates that the rainfall anomalies over the Indian monsoon region in both active and break phases are mainly (70–80%) balanced by local moisture divergence. The remaining 20–25% is accounted by the horizontal moisture advection. The moisture advection is found to lead the rainfall by 8–9 d, while there is no lead‐lag relationship is observed between the moisture divergence and rainfall. The anomalous moisture advection from the northwest pacific initiates the active phase of Indian monsoon and the dry air advection from the northwest of India after the onset of active convection sets off the break conditions. MSE budget over India is balanced by MSE divergence and moisture advection, indicating that the variation in MSE is mainly governed by moisture in the intraseasonal timescales. A positive covariance between radiative and surface fluxes and precipitation anomalies indicates that these flux terms slowdown the variation of MSE during active/break phase and may help to extend the ISO. The anomalous moisture advection has a major role in northward propagation of ISO also. A large residual of MSE budget during onset of ISO is the main caveat of the reanalysis products and it is the major constrain in the present analysis also.

Estimation of gross primary production over the terrestrial ecosystems in China

Gross primary production (GPP) is of significant importance for the terrestrial carbon budget and climate change, but large uncertainties in the regional estimation of GPP still remain over the terrestrial ecosystems in China. Eddy covariance (EC) flux towers measure continuous ecosystem-level exchange of carbon dioxide (CO2) and provide a promising way to estimate GPP. We used the measurements from 32 EC sites to examine the performance of a light use efficiency model (i.e., EC-LUE) at various ecosystem types, including 23 sites in China and 9 sites in adjacent areas with the similar climate environments. No significant systematic error was found in the EC-LUE model predictions, which explained 79% and 62% of the GPP variation at the validation sites with C3 and C4 vegetation, respectively. Regional patterns of GPP at a spatial resolution of 10km×10km from 2000 to 2009 were determined using the MERRA (Modern Era Retrospective-analysis for Research and Applications) reanalysis dataset and MODIS (MODerate resolution Imaging Spectroradiometer). China's terrestrial GPP decreased from southeast toward the northwest, with the highest values occurring over tropical forests areas, and the lowest values in dry regions. The annual GPP of land in China varied between 5.63PgC and 6.39PgC, with a mean value of 6.04PgC, which accounted for 4.90–6.29% of the world's total terrestrial GPP. The GPP densities of most vegetation types in China such as evergreen needleleaf forests, deciduous needleleaf forests, mixed forests, woody savannas, and permanent wetlands were much higher than the respective global GPP densities. However, a high proportion of sparsely vegetated area in China resulted in the overall low GPP. The inter-annual variability in GPP was significantly influenced by air temperature (R2=0.66, P<0.05), precipitation (R2=0.71, P<0.05), and normalized difference vegetation index (NDVI) (R2=0.83, P<0.05), respectively.