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NASA NTRS1985

Theoretical and software considerations for general dynamic analysis using multilevel substructured models

The dynamic analysis of complex structural systems using the finite element method and multilevel substructured models is presented. The fixed-interface method is selected for substructure reduction because of its efficiency, accuracy, and adaptability to restart and reanalysis. This method is extended to reduction of substructures which are themselves composed of reduced substructures. The implementation and performance of the method in a general purpose software system is emphasized. Solution algorithms consistent with the chosen data structures are presented. It is demonstrated that successful finite element software requires the use of software executives to supplement the algorithmic language. The complexity of the implementation of restart and reanalysis porcedures illustrates the need for executive systems to support the noncomputational aspects of the software. It is shown that significant computational efficiencies can be achieved through proper use of substructuring and reduction technbiques without sacrificing solution accuracy. The restart and reanalysis capabilities and the flexible procedures for multilevel substructured modeling gives economical yet accurate analyses of complex structural systems.

Schmidt, R. J.↗

NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗

NASA NTRS2002

Configuration and Intraseasonal Duration of Interannual Anomalies of the Great Plains Low-Level Jet

Despite the fact that the low-level jet of the southern Great Plains (the GPLLJ) of the U.S. is primarily a nocturnal phenomenon that virtually vanishes during the daylight hours, it is one of the most persistent and stable climatological features of the low-level continental flow during the warm-season months, May through August. We have used significant-level data to validate the skill of the GEOS-1 Data Assimilation System (DAS) in realistically detecting this jet and inferring its structure and evolution. We have then carried out a 15-year reanalysis with the GEOS-1 DAS to determine its climatology and mean diurnal cycle and to study its interannual variability. Interannual anomalies of the meridional flow associated with the GPLLJ are much smaller than the mean diurnal fluctuations, than random intraseasonal anomalies, and than the mean wind itself. There are three maxima of low-level meridional flow variance over the Great Plains and the Gulf of Mexico: a 1.2 m2 s-2 peak over the southeast Texas, to the east and south of the mean velocity peak, a 1.0 m2 s-2 peak over the western Gulf of Mexico, and a .8 m2 s-2 peak over the upper Great Plains (UGP), near the Nebraska/South Dakota border. Each of the three variance maxima corresponds to a spatially coherent, jet-like pattern of low-level flow interannual variability. There are also three dominant modes of interannual variability corresponding to the three variance maxima, but not in a simple one-to-one relationship. Cross-sectional profiles of mean southerly wind over Texas remain relatively stable and recognizable from year to year with only its eastward flank showing significant variability. This variability, however, exhibits a distinct, biennial oscillation during the first six to seven years of the reanalysis period and only then. This intermittent biennial oscillation (IBO, one of the three modes discussed in the previous paragraph) in the lowlevel flow is restricted to the region surrounding eastern Texas and is also evident in the NCEP/NCAR reanalysis data set from about 1978 to 1985 or 1986 and again from 1995 to 2000. It is evident as well in surface pressure in both the GEOS-1 and NCEP/NCAR sets. The interannual anomalies do not necessarily persist uniformly throughout an entire season, but can fluctuate from one part of the season to the next. To estimate the characteristic sub-seasonal time scales for coherence of these fluctuations, we have taken the weekly anomaly of low-level wind at each point of the domain from the climatological average for that given point and that given week of the season and computed the covariance of its fluctuations over all weeks and over all years with the weekly climatological anomaly of the meridional wind at each of the three reference points discussed above. The typical duration of a coherent interannual anomaly within a given warm season increases with decreasing latitude from 2 to 3 weeks over the UGP, to 6 to 7 weeks over eastern Texas. Coherence over the western Gulf of Mexico is intermediate between the two with a typical duration of 4 to 5 weeks. There appears to be evidence that the interannual anomalies over Texas the Gulf propagate to the UGP after a week and those over the Gulf propagate there after 2 to 3 weeks. There also appears to be some reverse propagation of interannual anomalies over the UGP to Texas and to the Gulf after a period of about one week. The interannual anomalies in southerly flow over eastern Texas seem to correlate well with interannual anomalies of surface temperature and (negative) ground wetness and over western Texas.

Helfand, H. M.↗

NASA NTRS2002

Is There Really an Intermittent Biennial Oscillation in the Great Plains Low-Level Jet Over Texas?

In the 15-year GEOS-1 reanalysis data set, a maximum of interannual variance of low- level meridional flow for the warm season (May through August) occurs over southeast Texas. This variance maximum seems to be dominated by a marked biennial oscillation that occurs only during the first 6 (or possibly 8) years of the reanalysis period (1980-85 or possibly 1980-1987) and then completely disappears by the 9th year. This biennial oscillation seems to be associated with interannual fluctuations in ground wetness, surface temperature and surface pressure gradients over Texas. The periods of drier soil lead to warmer surface temperatures, lower surface pressures, stronger pressure gradients between Texas and the Gulf of Mexico and stronger southerly winds. This intermittent biennial oscillation is also evident in corresponding fields for the the NCEP/NCAR reanalysis data set for the years 1978-1985 (and possibly from 1978- 1987) and 1995-2000, but not during other periods. There are also obvious biennial oscillations evident during these periods in U.S. Climate Division records for the Palmer Drought Severity Index (PDSI) for Texas. Month-by-month correlations of this index with certain el Nino related indices are as high as .45 for the first period and as high as .55 or .6 for the second period for some regions in Texas. The seasonal cycle of the biennial signal in the PDSI and precipitation for the first period suggest that the drought in Texas and Mexico is ended (caused) by a reversal in the sign of anomalies in precipitation rate for the fall/winter season. Analysis of tropical Pacific SST patterns shows a .5 to .75 K biennial oscillation of SSTs along the precipitation-free track to the southwest of the Mexican coast during the fall and winter months of the 1978 to 1985 period that might explain the reversal in precipitation anomalies and hence the entire intermittent biennial oscillation in ground hydrology and low-level flow.

Helfand, H. Mark↗

NASA NTRS2007

Evidence for Interannual to Decadal Variations in Hadley and Walker Circulations and Links to Water and Energy Fluxes

Mass and energy transports associated with the Hadley and Walker circulations are important components of the earth s climate system and are strongly linked to hydrologic processes. Interannual to decadal variation in these flows likely signify a combination of natural climate noise as well as a response to anthropgenic forcing. There remains considerable uncertainty in quantifying variations in these flows. Evidence in the surface pressure record supports a weakening of the Walker circulation over the Pacific in recent decades. Conversely the NCEP / NCAR and ERA 40 reanalyses indicate that the Hadley circulation has increased in strength over the last two decades, though these analyses depict significantly different mass circulation changes. Interestingly, the NCEP - II / DOE reanalysis contains essentially no Hadley circulation changes. Most climate model integrations anticipate a weakening of both tropical circulations associated with stronger static stability. Clearly there is much uncertainty not only with the mass transports, but also how they are linked to water and energy balance of the planet through variations in turbulent heat and radiative fluxes and horizontal exports / imports of energy. Here we examine heat and water budget variations from a number of reanalysis products and focus on the linear and nonlinear response of ENSO warm and cold events as opportunities to study budget variations over the past 15-20 years. Our analysis addresses such questions as To what extent do Hadley and Walker Cell variations compensate each other on mass and energy transport? Do static stability adjustments appear to constrain fractional precipitation response vs. fractional water vapor response? We appeal to constraints offered by GPCP precipitation, SSWI ocean evaporation estimates, and ISCCP-FD radiative fluxes, and other satellite data sets to interpret and confirm reanalysis-based diagnostics. Using our findings we also attempt to place in context the recent findings that tropical ocean evaporation increased by order 5% or more during the 1990s, reconciling this with GPCP precipitation variations.

Robertson, Franklin↗

NASA NTRS2006

Vertical Moist Thermodynamic Structure and Spatial-Temporal Evolution of the MJO in AIRS Observations

The atmospheric moisture and temperature profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit on the NASA Aqua mission, in combination with the precipitation from the Tropical Rainfall Measuring Mission (TRMM), are employed to study the vertical moist thermodynamic structure and spatial-temporal evolution of the Madden-Julian oscillation (MJO). The AIRS data indicate that, in the Indian Ocean and western Pacific, the temperature anomaly exhibits a trimodal vertical structure: a warm (cold) anomaly in the free troposphere (800-250 hPa) and a cold (warm) anomaly near the tropopause (above 250 hPa) and in the lower troposphere (below 800 hPa) associated with enhanced (suppressed) convection. The AIRS moisture anomaly also shows markedly different vertical structures as a function of longitude and the strength of convection anomaly. Most significantly, the AIRS data demonstrate that, over the Indian Ocean and western Pacific, the enhanced (suppressed) convection is generally preceded in both time and space by a low-level warm and moist (cold and dry) anomaly and followed by a low-level cold and dry (warm and moist) anomaly. The MJO vertical moist thermodynamic structure from the AIRS data is in general agreement, particularly in the free troposphere, with previous studies based on global reanalysis and limited radiosonde data. However, major differences in the lower-troposphere moisture and temperature structure between the AIRS observations and the NCEP reanalysis are found over the Indian and Pacific Oceans, where there are very few conventional data to constrain the reanalysis. Specifically, the anomalous lower-troposphere temperature structure is much less well defined in NCEP than in AIRS for the western Pacific, and even has the opposite sign anomalies compared to AIRS relative to the wet/dry phase of the MJO in the Indian Ocean. Moreover, there are well-defined eastward-tilting variations of moisture with height in AIRS over the central and eastern Pacific that are less well defined, and in some cases absent, in NCEP. In addition, the correlation between MJO-related mid-tropospheric water vapor anomalies and TRMM precipitation anomalies is considerably more robust in AIRS than in NCEP, especially over the Indian Ocean. Overall, the AIRS results are quite consistent with those predicted by the frictional Kelvin-Rossby wave/conditional instability of the second kind (CISK) theory for the MJO.

troposhere↗

NASA NTRS2007

Spacebased Estimation of Moisture Transport in Marine Atmosphere Using Support Vector Regression

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.

Support vector regression↗

NASA NTRS2010

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Koren, Ilan↗

NASA NTRS2010

Using MERRA Gridded Innovations for Quantifying Uncertainties in Analysis Fields and Diagnosing Observing System Inhomogeneities

MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum-likelihood estimates of background and observation errors, as well as global bias estimates. Starting with the joint PDF of innovations and analysis increments at observation locations we propose a technique for diagnosing bias among the observing systems, and document how these contextual biases have evolved during the satellite era covered by MERRA.

da Silva, Arlindo↗

NASA NTRS2011

Reanalyses and Essential Climate Variables

Reanalyses are a potentially powerful climate data collection driven by observations but also subjected to model bias. Additionally, reanalyses can produce and use essential climate variables in a consistent method. For example, snow cover and soil moisture (among other variables) will eventually be assimilated into the reanalyses, but also provide crucial validation data. Sea surface temperature can be prescribed or assimilated in a coupled reanalysis. The strength of reanalysis lies in the ancillary data that is produced from the modeling components but not routinely observed thereby providing more complete Earth system information. The weakness in this concept is that the model derived data can be affected by model bias and may also change relative to the available observing system. Here, we will review the status of existing reanalyses and the ECVs being considered for the workshop. Purpose of Michael Bosilovich's contribution to the workshop: Michael Bosilovich will represent US reanalysis community in this international discussion of Essential Climate Variables (ECVs) and the relative nature of reanalyses to ECVs.

Bosilovich, Michael↗

NASA NTRS2011

The Sensitivity of African Easterly Waves to Eastern Tropical Atlantic Sea-Surface Temperatures

The results of two regional atmospheric model simulations are compared to assess the influence of the eastern tropical Atlantic sea-surface temperature maximum on local precipitation, transient easterly waves and the West African summer monsoon. Both model simulations were initialized with reanalysis 2 data (US National Center for Environmental Prediction and Department of Energy) on 15 May 2006 and extended through 6 October 2006, forced by synchronous reanalysis 2 lateral boundary conditions introduced four times daily. One simulation uses 2006 reanalysis 2 sea-surface temperatures, also updated four times daily, while the second simulation considers ocean forcing absent the sea-surface temperature maximum, achieved here by subtracting 3 K at every ocean grid point between 0 and 15 N during the entire simulation. The simulation with 2006 sea-surface temperature forcing produces a realistic distribution of June-September mean precipitation and realistic westward propagating swaths of maximum rainfall, based on validation against Tropical Rainfall Measuring Mission (TRMM) estimates. The simulation without the sea-surface temperature maximum produces only 57% of the control June-September total precipitation over the eastern tropical Atlantic and about 83% of the Sahel precipitation. The simulation with warmer ocean temperatures generates generally stronger circulation, which in turn enhances precipitation by increasing moisture convergence. Some local precipitation enhancement is also attributed to lower vertical thermal stability above the warm water. The study shows that the eastern tropical Atlantic sea-surface temperature maximum enhances the strength of transient easterly waves and broadens the spatial extent of associated precipitation. However, large-scale circulation and its interaction with the African continent, and not sea-surface temperatures, control the timing and trajectories of the waves.

Druyan, Leonard M.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Robertson, F. R.↗

NASA NTRS2013

Air Pollution over North-West Bay of Bengal in the Early Post-Monsoon Season Based on NASA MERRAero Data

The MERRA Aerosol Reanalysis (MERRAero) has been recently developed at NASA's Global Modeling Assimilation Office (GMAO). This reanalysis is based on a version of the GEOS-5 model radiatively coupled with GOCART aerosols, and it includes assimilation of bias-corrected Aerosol Optical Thickness (AOT) from the MODIS sensor on both Terra and Aqua satellites. Our main finding is that, in October, in the absence of aerosol sources in north-west Bay of Bengal (BoB), MERRAero showed increasing AOT trends over north-west BoB exceeding those over the east of the Ganges basin. The Ganges basin is characterized by significant population growth accompanied by developing industry, agriculture, and increasing transportation: this has resulted in declining air quality. MERRAero data for the period 2002-2009 was used to study AOT trends over north-west Bay of Bengal (BoB) in the early post-monsoon season. This season is characterized by aerosol transport from the Ganges basin to north-west BoB by prevailing winds; and still significant rainfall of over 150 mmmonth. Different aerosol components showed strong increasing AOT trends over north-west BoB. The following factors contributed to the increasing AOT trend over the area in question in October: an increasing number of days when prevailing winds blew from land to sea, resulting in a drier environment and an increase in air pollution over north-west BoB; wind convergence was observed over north-west BoB causing the accumulation of aerosol particles over that region, when prevailing winds blew from land to sea. MERRAero aerosol reanalysis can be used on a global scale.

AOT↗

NASA NTRS2014

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

surface energy↗

NASA NTRS2015

Assessment of Precipitation Anomalies in California Using TRMM and MERRA Data

Using modern satellite (Tropical Rainfall Measuring Mission, TRMM, 1998-2014) and reanalysis (Modern-Era Retrospective Analysis for Research and Applications, MERRA, 1979-2015) data, we reassess certain aspects of the precipitation climate in California from the past decades. California has a well-pronounced rain season that peaks in December-February. However, the 95% confidence interval around the climatological precipitation during these months imply that deviations on the order of 60% of the expected amounts are very likely during the most important period of the rain season. While these positive and negative anomalies alternate almost every year and tend to cancel each other, severe multiyear declines of precipitation in California appear on decadal scales. The 1986-1994 decline of precipitation was similar to the current one that started in 2011 and is apparent in the reanalysis data. In terms of accumulated deficits of precipitation, that episode was no less severe than the current one. While El Niño (the warm phase of the El Nino-Southern Oscillation, ENSO) is frequently cited as the natural forcing expected to bring a relief from drought, our assessment is that ENSO has been driving at best only 6% of precipitation variability in California in the past three decades. Using fractional risk analysis of precipitation during typical versus drying periods, we show that the likelihood of losing the most intensive precipitation events drastically increases during the multiyear drying events. Storms delivering up to 50% of the precipitation in California are driven by atmospheric rivers making landfall. However, these phenomena can be suppressed and even blocked by persistent ridges of atmospheric pressure in the northeast Pacific. The reanalysis and satellite data are proven to be reliable to the extent where they yield information on developing conditions and observed precipitation anomalies.

precipitation↗

NASA NTRS2015

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

simulation↗

NASA NTRS2016

Ensemble-Based Assimilation of Aerosol Observations in GEOS-5

MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.

LDE↗