Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Trends”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Contiguous US summer maximum temperature and heat stress trends in CRU and NOAA Climate Division data plus comparisons to reanalyses

Abstract Warming is a major climate change concern, but the impact of high maximum temperatures depends upon the air’s moisture content. Trends in maximum summertime temperature, moisture, and heat index are tracked over three time periods: 1900–2011, 1950–2011, and 1979–2011; these trends differ notably from annual temperature trends. Trends are emphasized from two CRU datasets (CRUTS3.25 and CRUTS4.01) and two reanalyses (ERA-20C and 20CRv2). Maximum temperature trends tend towards warming that is stronger over the Great Lakes, the interior western and the northeastern contiguous United States. A warming hole in the Midwest generally decreases in size and magnitude when heat stress trends are calculated because the region has increasing moisture. CRU and nearly all reanalyses find cooling in the northern high plains that is not found in NOAA Climate Division trends. These NOAA trends are captured better by CRUTS401. Moistening in the northeast amplifies the heat stress there. Elsewhere the moisture trends are less clear. Drying over northern Texas (after 1996) in CRUTS401 translates into decreasing heat stress there (less so in CRUTS325). Though other reanalyses are not intended for long-term trends, MERRA-2 and ERA-Interim match observed trends better than other reanalyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Trend analysis for large solid rocket motors - A program level approach

This paper defines a program-level trend analysis effort that can be applied to large solid rocket motors. The effort is especially applicable to large segmented rocket motors such as the Space Transportation System's solid rocket boosters. Five types of trend analysis are discussed for different aspects of a rocket motor program, (performance, reliability, problem, supportability, and programmatic). Ideas are offered for implementing and performing a program-level trend analysis effort by giving suggestions for selecting computer capabilities, choosing parameters, selecting statistical processes, routine screening for trends, analyzing significant trends (for example, looking for related trends and determining if adverse trends are resolved), and reporting results of trend analysis. The use of program-level trending allows for the ability to easily transfer data between organizations and easily use the data to correlate trends from the various organizations to find causal relationships. Efficiency is enhanced from upper level management to the shop floor at vendor locations by using the same trend analysis software and methodology at all organizations.

Babbitt, Norman E., III↗
NASA NTRS1992

Trends in column ozone based on TOMS data - Dependence on month, latitude, and longitude

On the basis of the TOMS satellite column ozone data in latitudes 70 deg S-70 deg N from November 1978 to May 1990, a statistical model is used to estimate the trends in ozone as a function of latitude, longitude, and month. The trends in the TOMS ozone data are highly seasonal and dependent on location. Near the equator, the estimated monthly trends are not significantly different from zero. For high latitudes, most of the estimated monthly trends are negative. In January, February, and March, there are some positive trend estimates in the western hemisphere around latitude 60 deg N. The most negative trends for these three months also appear in the high latitudes of the northern hemisphere. Starting in June, more negative trends appear in the latitudes 50 deg S-70 deg S than the trends in the rest of the world considered. A large depletion develops during the spring time (September to November) in the southern high-latitude region, and the area of peak ozone decline is moving eastward during the period. The largest negative trends (about -29 percent per decade) for the area considered in this study appear in October around the latitude 70 deg S and longitudes 20 deg W-100 deg W region. For the northern hemisphere, the year-round trend estimates for latitudes 30 deg N-70 deg N range from -0.96 percent to -7.43 percent per decade. In the latitudes 30 deg N-50 deg N, the winter trend estimates are more negative than those for the summer and the fall. However, this pattern did not hold for latitudes 50 deg N-70 deg N.

Niu, Xufeng↗
NASA NTRS1994

Comparison of satellite measurements of ozone and ozone trends

Measurements of ozone retrieved from satellite instruments over the 1979-1991 period are compared. The instruments used are the total ozone mapping spectrometer (TOMS), the solar backscattered ultraviolet experiment (SBUV), and stratospheric aerosol and gas experiments (SAGE) I and II. Although there is good agreement between the absolute densities of ozone as measured by the various instruments, the long-term changes (1979-1990) disagree sharply as a function of pressure and in the integrated ozone amount. In the upper stratosphere, SBUV trends are negative with maximum values of about -1.5%/year at high latitudes. Combined SAGE I and II trends are slightly positive in this region and peak near 0.5%/year at equatorial latitudes. In the lower stratosphere, SBUV trends reflect small decreases in ozone, generally less than -0.4%/year except at high southern latitudes where the trends rearch values of approximately -1.5%/year. SAGE ozone trends exhibit large decreases particularly in the equatorial regions where decreases of 3-6%/year are seen at pressures between 60 and 90 mbar. At higher latitudes, SAGE trends are more comparable to SBUV trends in the lower stratosphere. Total ozone trends from TOMS and SBUV agree within their uncertainties. Near-zero trends are indicated at low latitudes, and larger, negative trends (approximately -0.5%/year) are indicated near the poles. The SAGE column ozone trends depend upon the base level altitude of integration but do not exhibit a strong latitude dependence.

Rusch, D. W.↗
NASA NTRS2010

AIRS Water Vapor and Cloud Products Validate and Explain Recent Negative Global and Tropical OLR Trends Observed by CERES

This paper compares spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS retrieved surface and atmospheric geophysical parameters over the time period September 2002 February 2010. This time period is marked by a substantial decreasing OLR trend on the order of -0.1 W/m2/yr averaged over the globe. There are very large spatial variations of these trends however, with local values ranging from -2.6 W/m2/yr to +3.0 W/m2/yr in the tropics. The spatial patterns of the AIRS and CERES trends are in essentially perfect agreement with each other, as are the anomaly time series averaged over different spatial regions. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate. The agreement of anomalies and trends of OLR as observed by CERES and computed from AIRS derived products also indirectly validates the anomalies and trends of the AIRS derived products as well. We used the anomalies and trends of AIRS derived water vapor and cloud products to explain why global OLR has had a large negative trend over the time period September 2002 through February 2010. Tropical OLR began to decrease significantly at the onset of a strong La Nina in mid-2007. AIRS products show that cloudiness and mid-tropospheric water vapor began to increase in the region 5degN - 20degS latitude extending eastward from 150degW - 30 E longitude at that time, with a corresponding very large drop in OLR in this region. Late 2009 is characterized by a strong El-Nino, with a corresponding change in sign of observed anomalies of mid-tropospheric water vapor, cloud cover, and OLR in this region, as we] l as that of OLR anomalies in the tropics and globally. Monthly mean anomalies of OLR, water vapor and cloud cover over this region are all shown to be highly correlated in time with those of an El Nino anomaly index four months previously. The El Nino index is defined as the SST anomaly averaged over the area 15S to 15N and 160W eastward to 30E. If one excludes the area 5degN - 20degS, 150degW - 30degE from the statistics, the negative area mean tropical OLR trends, as well as OLR trends over the rest of the globe, are substantially

Susskind, Joel↗
DOE OSTI2014

Tropical temperature trends in Atmospheric General Circulation Model simulations and the impact of uncertainties in observed SSTs

Abstract The comparison of trends in various climate indices in observations and models is of fundamental importance for judging the credibility of climate projections. Tropical tropospheric temperature trends have attracted particular attention as this comparison may suggest a model deficiency. One can think of this problem as composed of two parts: one focused on tropical surface temperature trends and the associated issues related to forcing, feedbacks, and ocean heat uptake and a second part focusing on connections between surface and tropospheric temperatures and the vertical profile of trends in temperature. Here we focus on the atmospheric component of the problem. We show that two ensembles of Geophysical Fluid Dynamics Laboratory HiRAM model runs (similar results are shown for National Center for Atmospheric Research's CAM4 model) with different commonly used prescribed sea surface temperatures (SSTs), namely, the HadISST1 and “Hurrell” data sets, have a difference in upper tropical tropospheric temperature trends (∼0.1 K/decade at 300 hPa for the period 1984–2008) that is about a factor 3 larger than expected from moist adiabatic scaling of the tropical average SST trend difference. We show that this surprisingly large discrepancy in temperature trends is a consequence of SST trend differences being largest in regions of deep convection. Further, trends, and the degree of agreement with observations, not only depend on SST data set and the particular atmospheric temperature data set but also on the period chosen for comparison. Due to the large impact on atmospheric temperatures, these systematic uncertainties in SSTs need to be resolved before the fidelity of climate models' tropical temperature trend profiles can be assessed.

Flannaghan, T. J.↗
DOE OSTI2016

Effects of linear trends on estimation of noise in GNSS position time-series

A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that the effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.

58 GEOSCIENCES↗
DOE OSTI2015

Comparing Trends in the Southern Annular Mode and Surface Westerly Jet

This paper examines trends in the southern annular mode (SAM) and the strength, position, and width of the Southern Hemisphere surface westerly wind jet in observations, reanalyses, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). First the period over 1951–2011 is considered, and it is shown that there are differences in the SAM and jet trends between the CMIP5 models, the Hadley Centre gridded SLP (HadSLP2r) dataset, and the Twentieth Century Reanalysis. The relationships between these trends demonstrate that the SAM index cannot be used to directly infer changes in any one kinematic property of the jet. The spatial structure of the observed trends in SLP and zonal winds is shown to be largest, but also most uncertain, in the southeastern Pacific. To constrain this uncertainty six reanalyses are included and compared with station-based observations of SLP. The CMIP5 mean SLP trends generally agree well with the direct observations, despite some climatological biases, while some reanalyses exhibit spuriously large SLP trends. Similarly, over the more reliable satellite era the spatial pattern of CMIP5 SLP trends is in excellent agreement with HadSLP2r, whereas several reanalyses are not. Then surface winds are compared with a satellite-based product, and it is shown that the CMIP5 mean trend is similar to observations in the core region of the westerlies, but that several reanalyses overestimate recent trends. The authors caution that studies examining the impact of wind changes on the Southern Ocean could be biased by these spuriously large trends in reanalysis products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

NASA trend analysis procedures

This publication is primarily intended for use by NASA personnel engaged in managing or implementing trend analysis programs. 'Trend analysis' refers to the observation of current activity in the context of the past in order to infer the expected level of future activity. NASA trend analysis was divided into 5 categories: problem, performance, supportability, programmatic, and reliability. Problem trend analysis uncovers multiple occurrences of historical hardware or software problems or failures in order to focus future corrective action. Performance trend analysis observes changing levels of real-time or historical flight vehicle performance parameters such as temperatures, pressures, and flow rates as compared to specification or 'safe' limits. Supportability trend analysis assesses the adequacy of the spaceflight logistics system; example indicators are repair-turn-around time and parts stockage levels. Programmatic trend analysis uses quantitative indicators to evaluate the 'health' of NASA programs of all types. Finally, reliability trend analysis attempts to evaluate the growth of system reliability based on a decreasing rate of occurrence of hardware problems over time. Procedures for conducting all five types of trend analysis are provided in this publication, prepared through the joint efforts of the NASA Trend Analysis Working Group.

Source record↗
NASA NTRS1994

Comparison of trend analyses for Umkehr data using new and previous inversion algorithms

Ozone vertical profile Umkehr data for layers 3-9 obtained from 12 stations, using both previous and new inversion algorithms, were analyzed for trends. The trends estimated for the Umkehr data from the two algorithms were compared using two data periods, 1968-1991 and 1977-1991. Both nonseasonal and seasonal trend models were fitted. The overall annual trends are found to be significantly negative, of the order of -5% per decade, for layers 7 and 8 using both inversion algorithms. The largest negative trends occur in these layers under the new algorithm, whereas in the previous algorithm the most negative trend occurs in layer 9. The trend estimates, both annual and seasonal, are substantially different between the two algorithms mainly for layers 3, 4, and 9, where trends from the new algorithm data are about 2% per decade less negative, with less appreciable differences in layers 7 and 8. The trend results from the two data periods are similar, except for layer 3 where trends become more negative, by about -2% per decade, for 1977-1991.

Reinsel, Gregory C.↗
NASA NTRS2002

Upper-Stratospheric Ozone Trends 1979-1998

Extensive analyses of ozone observations between 1978 and 1998 measured by Dobson Umkehr, Stratospheric Aerosol and Gas Experiment (SAGE) I and II, and Solar Backscattered Ultraviolet (SBUV) and (SBUV)/2 indicate continued significant ozone decline throughout the extratropical upper stratosphere from 30-45 km altitude. The maximum annual linear decline of -0.8 +/- 0.2 %/yr(2sigma) occurs at 40 km and is well described in terms of a linear decline modulated by the 11-year solar variation. The minimum decline of -0.110.1% yr-1(2o) occurs at 25 km in midlatitudes, with remarkable symmetry between the Northern and Southern Hemispheres at 40 km altitude. Midlatitude upper-stratospheric zonal trends exhibit significant seasonal variation (+/- 30% in the Northern Hemisphere, +/- 40% in the Southern Hemisphere) with the most negative trends of -1.2%/yr occurring in the winter. Significant seasonal trends of -0.7 to -0.9%/yr occur at 40 km in the tropics between April and September. Subjecting the statistical models used to calculate the ozone trends to intercomparison tests on a variety of common data sets yields results that indicate the standard deviation between trends estimated by 10 different statistical models is less than 0.1%/yr in the annual-mean trend for SAGE data and less than 0.2%/yr in the most demanding conditions (seasons with irregular, sparse data) [World Meteorological Organization (WMO), 1998]. These consistent trend results between statistical models together with extensive consistency between the independent measurement-system trend observations by Dobson Umkehr, SAGE I and II, and SBUV and SBUV/2 provide a high degree of confidence in the accuracy of the declining ozone amounts reported here. Additional details of ozone trend results from 1978 to 1996 (2 years shorter than reported here) along with lower-stratospheric and tropospheric ozone trends, extensive intercomparisons to assess relative instrument drifts, and retrieval algorithm details are given by WMO [1998].

Newchurch, M. J.↗
NASA NTRS2009

Short-term Aerosol Trends: Reality or Myth?

The main questions addressed in this slide presentation involve short-term trends of MODIS aerosol optical thickness (AOT) over 6 years: (1) Why are the trends different in different regions? (2) How are these trends so high? (3) Why are they "coherent" in many areas? (4) Are these changes in aerosol concentrations real, i.e., are they monotonic changes in emissions? Several views of the Spatial Distribution of AOT from Terra are shown. In conclusion there are several trends: (1) There is a broad spatial inhomogenueity in AOT trends over 6 years of MODIS Terra and Aqua (2) Some of the areas demonstrate clear positive trends related to increase of emission (e.g., Eastern China) (3) Strong trends in some other areas are superficial and might be attributed, in part, to: (3a) Least squares linear trend sensitivity to outliers (need to use more robust linear fitting method) (3b) Spatial and temporal shifts or trends in meteorological conditions, especially in wind patterns responsible for aerosol transport (6) Aerosol trends should be studied together with changes in meteorology patterns as they might closely linked together

Leptoukh, Gregory↗
NASA NTRS2010

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Trends for GCM Validation

Mainly due to their global nature, satellite observations can provide a very useful basis for GCM validations. In particular, satellite sounders such as AIRS provide 3-D spatial information (most useful for GCMs), so the question arises: can we use AIRS datasets for climate variability assessments? We show that the recent (September 2002 February 2010) CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. The correspondence can be seen even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics, for example. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate, and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by EI-Nino-La Nina cycles . We have created climate parameter anomaly datasets using AIRS retrievals which can be compared directly with coupled GCM climate variability assessments. Moreover, interrelationships of these anomalies and trends should also be similar between the observed and GCM-generated datasets, and, in cases of discrepancies, GCM parameterizations could be improved based on the relationships observed in the data. First, we assess spatial "trends" of variability of climatic parameter anomalies [since anomalies relative to the seasonal cycle are good proxies of climate variability] at the common 1x1 degree GCM grid-scale by creating spatial anomaly "trends" based on the first 7+ years of AIRS Version 5 Leve13 data. We suggest that modelers should compare these with their (coupled) GCM's performance covering the same period. We evaluate temporal variability and interrelations of climatic anomalies on global to regional e.g., deep Tropical Hovmoller diagrams, El-Nino-related variability scales, and show the effects of El-Nino-La Nina activity on tropical anomalies and trends of water vapor cloud cover and OLR. For GCMs to be trusted highly for long-term climate change predictions, they should be able to reproduce findings similar to these. In summary, the AIRS-based climate variability analyses provide high quality, informative and physically plausible interrelationships among OLR, temperature, humidity and cloud cover both on the spatial and temporal scales. GCM validations can use these results even directly, e. g., by creating 1x1 degree trendmaps for the same period in coupled climate simulations.

Molnar, Gyula I.↗
NASA NTRS2014

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than I% in most of climate regions although it could be as large as 10%.

remote sensing↗
NASA NTRSDate not supplied

Trends in Asian Summer Monsoon Anticyclone Dynamical Diagnostics in Reanalyses

The area of the Asian summer monsoon anticyclone (ASMA), as defined by contours of Montgomery stream function (MSF) on isentropic surfaces, has been increasing over at least the last four decades. Here we analyze the relationship of the trend in ASMA area to trends in dynamical diagnostics in the ASM region, both inside and outside the ASMA, for 1979 through 2020 in the MERRA-2, JRA-55, and ERA5 reanalyses. Trends in geopotential height (GPH) and temperature (from which MSF is calculated) indicate that MSF increases are dominated by increasing temperature (GPH) at levels that are primarily in the troposphere (stratosphere). Trends in MSF, GPH, and temperature are much less clear within the ASMA circulation than those for the entire ASM region, suggesting that other mechanisms, besides the direct effects of increasing tropospheric temperatures, are at play. To further explore these results, we present trends in lapse rate and dynamical tropopause altitudes, easterly and westerly windspeeds bounding the ASMA, and potential vorticity. Overall, weak or inconsistent trends inside the ASMA in most diagnostics likely arise from a complex interplay of mechanisms in this region (which spans tropospheric/stratospheric and tropical/midlatitude conditions), and suggest that the previously reported area trends do not necessarily indicate an increase in “intensity" of the ASMA. In regions both with and without robust trends in dynamical diagnostics, trend results are typically consistent between the three reanalyses studied even when there are biases in the magnitudes of those diagnostics. This generally good agreement indicates that these reanalyses are suitable for more detailed studies needed to fully understand the mechanisms for trends in the ASMA.

Gloria Manney↗
DOE OSTI2020

Climate-Related Trends of Within-Storm Intensities Using Dimensionless Temporal-Storm Distributions

Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. As such, the goal of this paper is to fill this gap by studying Huff curve patterns in a watershed with demonstrated increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve this goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km 2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939 to 2010 were investigated using dimensionless depth (with the frequency of 50%, $d_{50}$) and the curve variability $(V = d_{80} - d_{20})$ at three dimensionless within-storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ρ and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ρ and p were computed: (1) by averaging the individual ρ and p obtained from 10 gauges (AvgI); and (2) by grouped averaging of all individual gauge values of $d_{50}$ and V and then computing ρ and p (AvgG). The test results of individual gauges showed that 4 cases for $d_{50}$ and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for $d_{50}$ and V and AvgG for $d_{50}$ showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is insufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ρ of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V; however, this analysis may be affected by the nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Interpreting Space-Based Trends in Carbon Monoxide with Multiple Models

We use a series of chemical transport model and chemistry climate model simulations to investigate the observed negative trends in MOPITT CO over several regions of the world, and to examine the consistency of timedependent emission inventories with observations. We find that simulations driven by the MACCity inventory, used for the Chemistry Climate Modeling Initiative (CCMI), reproduce the negative trends in the CO column observed by MOPITT for 2000-2010 over the eastern United States and Europe. However, the simulations have positive trends over eastern China, in contrast to the negative trends observed by MOPITT. The model bias in CO, after applying MOPITT averaging kernels, contributes to the model-observation discrepancy in the trend over eastern China. This demonstrates that biases in a model's average concentrations can influence the interpretation of the temporal trend compared to satellite observations. The total ozone column plays a role in determining the simulated tropospheric CO trends. A large positive anomaly in the simulated total ozone column in 2010 leads to a negative anomaly in OH and hence a positive anomaly in CO, contributing to the positive trend in simulated CO. These results demonstrate that accurately simulating variability in the ozone column is important for simulating and interpreting trends in CO.

carbon monoxide↗
DOE OSTI2024

Recalibration of missing low-frequency variability and trends in the North Atlantic Oscillation

Abstract Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple “reddening” approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output.

Meteorology & Atmospheric Sciences↗