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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

1960 Chile - New estimate of polar motion excitation

A recent reanalysis of the International Latitude Serivce (ILS) polar motion data-day has been processed using Kalman filtering techniques to generate the polar motion excitation function over the time-span from 1960 to 1965. The resulting excitation function has been examined for the effects of 1960 Chile in an attempt to determine experimentally how large earthquake affect polar motion. The resulting upper bound of about 75 x 10 to the 22nd N-m for a 10-deg dip (about 36 x 10 to the 22nd N-m for 20-deg dip) is consistent with results obtained from previous seismic studies, including a recent normal mode excitation result. Following future great earthquakes, monitoring of polar motion by space-based techniques such as VLBI should continue at high temporal resolution for several weeks in order to directly measure the rheological parameters of the upper mantle.

Slade, M. A.↗
NASA NTRS1999

Interannual and Decadal Variability of Summer Rainfall over South America

Using the CPC (Climate Prediction Center) Merged Analysis of Precipitation product along with the Goddard Earth Observing System reanalysis and the Climate Analysis Center sea surface temperature (SST) data, we conduct a diagnostic study of the interannual and decadal scale variability of summer rainfall over South America. Results show three leading modes of rainfall variation identified with interannual, decadal, and long-term trend variability. Together, these modes explain more than half the total variance. The first mode is highly correlated with El Nino/southern oscillation (ENSO), showing severe drought over Northeast Brazil and copious rainfall over the Ecuador coast and the area of Uruguay-Southern Brazil in El Nino years. This pattern is attributed to the large scale zonal shift of the Walker circulation and local Hadley cell anomaly induced by positive (negative) SST anomaly over the eastern (western) equatorial Pacific. In El Nino years, two convective belts indicated by upper tropospheric velocity potential trough and mid-tropospheric rising motion, which are somewhat symmetric about the equator, extend toward the northeast and the southeast into the tropical North and South Atlantic respectively. Sandwiched between the ascent is a region of descending motion over Northeast Brazil. The southern branch of the anomalous Hadley cell is dynamically linked to the increase of rainfall over Uruguay-Southern Brazil. The regional response of anomalous circulation shows a stronger South American summer monsoon and an enhanced (weakened) subtropical high over the South Atlantic (South Pacific) Ocean. The decadal variation displays a meridional shift of the Intertropical Convergence Zone (ITCZ), which is tie to the anomalous cross-equatorial SST gradient over the Atlantic and the eastern Pacific. In conjunction with this mode is a large scale mass swing between the polar regions and midlatitudes in both hemispheres. Over the South Atlantic and the South Pacific, the changes of the strength of the subtropical high and the associated surface wind are dynamically consistent with the distribution of local SST anomalies, suggesting the importance of the atmospheric forcing in the decadal time scale. The decadal mode also presents a weak summer monsoon in its positive phase, which reduces the moisture supply from the equatorial Atlantic and the Amazon Basin and results in negative rainfall anomalies over the central Andes and Gran Chaco. The long-term trend shows decrease of rainfall from the northwest coast to the southeast subtropical region and a southward shift of Atlantic ITCZ that leads to increased rainfall over northern and eastern Brazil. Our result shows a close link of this mode to the observed SST warming trend over the subtropical South Atlantic and a remote connection to the interdecadal SST variation over the extratropical North Atlantic found in previous studies.

Zhou, Jiayu↗
NASA NTRS2000

Wintertime East Asian Jet Stream and Its Association with the Asian-Pacific Climate

Interannual variability of the wintertime East Asian westerly jet stream and the linkage between this variability and the Asian-Pacific climate are investigated. The study emphasizes on the variability of the jet core and its association with the Asian winter monsoon, tropical convection, upper tropospheric wave patterns, and the teleconnection of the jet with other climate systems. The relationship between the jet and North Pacific sea surface temperature pattern (SST) is also explored. NCEP/NCAR reanalysis, NASA GISS surface temperature, NASA GEOS reanalysis, NOAA reconstructed SST, GPCP precipitation, and NOAA snow cover data sets are analyzed in this study. An index of the East Asian jet has been defined by the December-February means of the 200 mb zonal winds that are averaged within a box enclosing the jet maximum, which shifts only moderately from one year to another especially in the south-north direction. The jet links to a teleconnection pattern whose major climate anomalies appear over the Asian continent and western Pacific (west of the dateline). This pattern differs distinctly from the teleconnection pattern associated with El Nino/Southern Oscillation (ENSO), which causes the Pacific/North American pattern to the east of the dateline. A strong jet is accompanied clearly by an increase in the intensity of the atmospheric circulation over Asia and the Pacific. In particular, the winter monsoon strengthens over East Asia, leading to cold climate in the region, and convection intensifies over the tropical Asia-Australia sector. Changes in the jet are associated with broad-scale modification in the upper tropospheric wave patterns that leads to downstream climate anomalies over the eastern Pacific. Through this downstream influence, the East Asian jet causes climate signals in North America as well. A strong jet gives rise to warming and less snow cover in the western United States but reverse climate anomalies in the eastern part of the country, although these signals are relatively weaker than the jet-related anomalies in East Asia. There is a strong association between the East Asian jet and the North Pacific SST (NPSST). A strong jet is accompanied by a cooling in the extratropical Pacific and a warming in the tropical-subtropical Pacific. Evidence also indicates that the extratropical NPSST pattern plays a role in modulating the intensity of the jet stream. ENSO, the jet, and the NPSST are mutually interactive on certain time scales and such an interaction links closely to the climate anomalies in the Asian-Pacific-American regions.

Yang, Song↗
NASA NTRS2003

The Reanalysis for Stratospheric Trace Gas Studies

The "Reanalysis for Stratospheric Trace Gas Studies" (ReSTS) project intends to provide a state-of-the-art meteorological dataset for use in chemistry-transport models (CTMs). The initial focus is on the period from May 1991 until April 1995, which encompasses the initial few years of observations from NASA's Upper Atmosphere Research Satellite (UARS) as well as the abrupt increase and slow decay of volcanic aerosol loading from Mount Pinatubo. The reanalysis is being performed using NASA's operational "GEOS-4" data assimilation system. The results presented in this paper will begin with an overview of the meteorology of the ReSTS period, validating the ReSTS data against independent analyses, followed by an evaluation of the system statistics (the "Observation minus Forecast" for different input data types). Some sensitivities to the assumptions made in the assimilation process will be presented, including aspects of the forecast model and the statistical model used in the observation-forecast merging. Aspects of trace-gas transport will be discussed, focussing on the on-line water vapor distribution (which is a quasi-inert trace gas in the stratosphere), off-line transport studies of ozone and selected long-lived species, as well as assimilated ozone. The results will be discussed in the context of transport studies and our ability to use reanalyzed datasets to examine long-term variations in the meteorology and composition of the middle atmosphere.

Pawson, Steven↗
NASA NTRS2020

Metrics for Improved Reanalyses in Polar Regions

Atmospheric reanalyses are widely used for a variety of scientific endeavors in the Arctic and Antarctic. Reanalyses are used as boundary conditions for a regional and process-based models, for climate model validation, and for diagnostic analysis of physical processes, weather and climatic events. However, reanalyses are typically global and often do not account for specific, regional considerations, such as for polar regions. In this work, we provide a brief evaluation of a prototype for a new GMAO reanalysis, which incorporates higher spatial resolution, an updated approach for data assimilation, and a revised atmospheric model. We identify differences in the representation of the Arctic atmosphere in comparison to recent reanalyses. Furthermore, we provide a forum for Arctic scientists to consider the future improvements for reanalyses, and seek feedback for the following questions: 1) What are important performance factors to consider in evaluating new reanalyses? 2) What physical processes should be incorporated into new reanalyses? 3) What spatio-temporal scales should be considered?

Parker, Chelsea L.↗
NASA NTRS2021

A High-Resolution Land Data Assimilation System Optimized for the Western United States

The Western Land Data Assimilation System (WLDAS) is a custom instance of the NASA Land Information System that combines land surface parameters, meteorological forcing data, and satellite products within a land surface model to produce daily estimates of the water and energy budget variables for the western United States. WLDAS was configured through discussions with partners, with the goal of groundwater sustainability planning for the state of California in mind. The publicly available output dataset has a 1-km grid resolution and spans 1979–present, which makes it suitable for water resources assessments. The data are also able to contextualize the recent drought events in California. Assimilation of Leaf Area Index, which is demonstrated herein to improve simulation over agricultural areas in California, specifically in terms of evapotranspiration in irrigation regions, will be included along with other data assimilation in subsequent releases of WLDAS.

land surface modeling↗
NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

The Goddard Earth Observing System (GEOS) is used by NASA’s Global Modeling and Assimilation Office (GMAO) to produce weather, climate, and air quality forecasts and reanalysis datasets. In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) system into GEOS it is necessary to provide a validated set of input observations in JEDI. The GMAO, in collaboration with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) in JEDI and adding all the necessary features to replicate the existing capability of the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures to assimilate the vast array of satellite and conventional observations assimilated in GEOS, including the GEOS all-sky microwave radiance assimilation framework to assimilate those observations in the UFO. Robust tests have been conducted to ensure correct configurations of observational data bias correction, quality control, and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations will be reported in this presentation.

Jianjun Jin↗
NASA NTRSDate not supplied

Composition Reanalyses at NASA’s Global Modeling and Assimilation Office

Scientific Assessments of Ozone Depletion 2018 and 2022 report the recovery of Antarctic ozone, consistent with diminishing concentrations of halogens in the stratosphere. Both the size and the depth of the springtime ozone holes exhibit downward trends, particularly in September. Superimposed on the recovery trend are significant year-to-year fluctuations arising from dynamical variability potentially influenced by climate forcing and volcanic eruptions. Since 2018 the Antarctic stratosphere has experienced a wild parade of austral spring seasons with a sudden stratospheric warming and exceptionally high ozone in 2019 followed by large and long-lasting ozone holes in the following years, prompting questions about the speed and detectability of Antarctic ozone recovery and its potential connections to human-induced climate change. From the Australian New Years’ wildfires of 2020 to volcanic aerosols to the unprecedented injection of water vapor by the Hunga volcanic eruption, recent scientific literature on the subject investigates many factors that may or may not have contributed to this remarkable interannual variability. This presentation summarizes dynamical influences on springtime Antarctic stratospheric ozone in recent years and discusses these results in the context of long-term trends. In particular, this work seeks to isolate dynamical and chemical contributions to the Antarctic springs since 2019 using a consistent methodological framework. Our analysis uses constituent and meteorological fields from the MERRA-2 Stratospheric Composition Reanalysis of Aura MLS (M2-SCREAM) in combination with data from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and from ozone sondes. Using the high spatial and temporal resolution of M2-SCREAM, we analyze the daily evolution of southern polar ozone, HCl, N2O, and water vapor in dynamical flow-following coordinates relative to the location, size, and shape of the polar vortex. For vertically integrated stratospheric ozone we emphasize the importance of the wave-influenced geometry of the polar vortex and its vertical alignment. The ultimate purpose of this project is to contribute to the quantification of the speed of the Antarctic ozone recovery and associated uncertainties.

Krzysztof Wargan↗
NASA NTRSDate not supplied

Uncertainties in an Observation-Based Estimate of the Global Aerosol Direct Radiative Effect

Aerosols impact Earth’s radiation budget directly through interactions with radiation and indirectly via interactions with clouds. Aerosols have significant radiative impacts on Earth’s energy budget and represent the largest uncertainty in the radiative forcing of the current climate. Although the magnitude of the aerosol direct radiative effect (DRE) is estimated to be less than that of the indirect effect, uncertainties are large. While model-based estimates of aerosol radiative forcing are subject to uncertainties in modeled aerosol properties and uncertainties in simulated cloud cover and albedo, most observation-based studies of global aerosol DRE have their own difficulties with aerosol optical properties and have been limited to cloud-free skies in most cases. Estimates of the uncertainty of the aerosol DRE are themselves uncertain and have varied widely among different published studies. In this study we use the CERES-CALIPSO-CloudSat-MODIS (C3M) product to estimate the global clear-sky and all-sky aerosol DRE. C3M merges collocated data from CERES, CALIPSO, CloudSat, and MODIS with information from reanalysis and an aerosol transport model. With CALIOP observations of aerosol below optically thin clouds and above clouds, co-located with cloud albedo from MODIS, the C3M dataset allows a detailed exploration of observational uncertainties. By perturbing the aerosol properties used and comparing radiative effects in perturbed cases with the base case we characterize uncertainties in estimated aerosol DRE due to uncertainties in the aerosol properties involved. The results also provide a basis for determining measurement requirements to improve the accuracy of DRE estimates. We will describe the approach and present results.

Dave Winker↗
NASA NTRS2014

Use Of EOS-AURA Observation In The MERRA-2 Reanalysis

Meteorological reanalyses provide multi-year gridded datasets that describe the evolution of the atmosphere. Such products use a data assimilation system, comprising of an atmospheric model, a broad suite of observations, and an analysis system that optimally combines the model forecast with the observations, using an algorithm that includes information about model and data accuracy. The mixture of observations is of central importance to the quality of the assimilated datasets. The Modern-era Retrospective Analysis for Research and Applications (MERRA) included constraints on the thermal structure of the middle atmosphere from nadir sounders on the NOAA polar-orbiting platforms (Stratospheric Sounding Units and Advanced Microwave Sounding Units). These instruments have peak sensitivities that occur well below the stratopause. As such, the radiance measurements do not provide strong constraints on stratopause temperature. The new MERRA-2 reanalysis is using EOS-MLS temperature retrievals after they are available: it will be demonstrated that these data lead to a more realistic stratopause structure in MERRA-2 than in MERRA. Similarly, the work demonstrates the improvements in lower stratospheric ozone in MERRA-2 than in MERRA, for the period when EOS-MLS ozone data are assimilated. This improvement occurs because of the ozone profile information offered by MLS in the low stratosphere, in contrast to the SBUV/2 data used for the rest of MERRA-2. The impacts of choosing to use the EOS-MLS datasets are discussed in context of the continuity of the data record in MERRA- 2.

Meteorological↗
DOE OSTI2025

ERA5-Land Data for LASSO-CACTI Overview Paper

The European Centre for Medium-Range Weather Forecasts (ECMWF) generated a soil reanalysis dataset for the land component of the fifth generation of European ReAnalysis (ERA5), referred to as ERA5-Land. This is a model-generated dataset, with the original version available for the period 1950 to present. The version archived in this DOE ARM product is a subset of the data is for the period of the CACTI field campaign plus several preceding months, specifically from August 1, 2018 through March 22, 2019 with hourly intervals. The ARM copy is also a sub-region of the original global product; the ARM copy is for -60 to -5 °N by -105 to -30 °W. Only variables necessary to drive the WRF-Hydro model are included, which are the 2-m temperature and specific humidity, 10-m wind components, surface pressure, rain rate, and downward surface short and longwave radiation. These data have been obtained from the Copernicus Data Store.

10m wind u-component↗
DOE OSTI2022

Dynamically Downscaled (WRF) 1km, Hourly Meteorological Conditions 1987-2020. East/Taylor Watersheds

This dataset contains meteorological output from the Weather Research and Forecasting (WRF) version 3.8.1. This dataset has been created to 1) investigate hydrometeorological processes impacting the East River and water-delivery to the Critical Zone, and 2) provide meteorological forcing data for distributed Earth-science modeling applications in the East River watershed. Variables have a 1 kilometer spatial resolution and hourly temporal resolution and encompass a rectangular region encompassing the East and Taylor River watersheds, Colorado, near the town of Crested Butte. WRF was forced using Climate Forecast System Reanalysis (CFSR) lateral boundary conditions. Each .zip file contains one "water year" of data (October 1 -- September 30; i.e. water year 2017 starts October 1, 2016 and ends September 30, 2017). Each zip folder contains 12 netcdf (.nc) files containing one month of hourly data each and are approximately 250mb. Model timestamps are in UTC time.The files contain the following data variables:EAST_MASK: binary mask of the watershed regionTAYLOR_MASK: binary mask of the watershed regionGLW downwelling longwave radiation (w/m2)HR_PRCP: Hourly Precipitation Rate (mm/hr). Includes all hydrometeors (solid+liquid). HFX NoahMP LSM total grid-cell modelled sensible heat flux (w/m2) [positive towards atmosphere]LH NoahMP LSM total grid-cell modelled latent heat flux (w/m2) [positive towards atmosphere; can be converted to ET]PSFC Surface Barometric Pressure (hPa)Q2 Two-meter specific humidity (kg/kg)SWDOWN Downwelling shortwave solar radiation (w/m2)SWNORM Terrain-normal downwelling shortwave radiation (w/m2)T2 Two-meter air temperature (deg K)U10 10-m U-component of wind velocity (m/s)V10 10m V-component of wind velocity (m/s)XLAT Latitude of grid-center point XLONG Longitude of grid-center point XTIME Model timestamp, **in UTC**

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

An Inversion Analysis of Recent Variability in Natural CO2 Fluxes Using GOSAT and In Situ Observations

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009.

Carbon dioxide↗
NASA NTRS2015

Evaluation of the Surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States

We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations.Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure

Air Pollution↗
DOE OSTI2023

Surface temperature comparison of the Arctic winter MOSAiC observations, ERA5 reanalysis, and MODIS satellite retrieval

Atmospheric model systems, such as those used for weather forecast and reanalysis production, often have significant and systematic errors in their representation of the Arctic surface energy budget and its components. The newly available observation data of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (2019/2020) enable a range of model analyses and validation in order to advance our understanding of potential model deficiencies. In the present study, we analyze deficiencies in the surface radiative energy budget over Arctic sea ice in the ERA5 global atmospheric reanalysis by comparing against the winter MOSAiC campaign data, as well as, a pan-Arctic level-2 MODIS ice surface temperature remote sensing product. We find that ERA5 can simulate the timing of radiatively clear periods, though it is not able to distinguish the two observed radiative Arctic winter states, radiatively clear and opaquely cloudy, in the distribution of the net surface radiative budget. The ERA5 surface temperature over Arctic sea ice has a conditional error with a positive bias in radiatively clear conditions and a negative bias in opaquely cloudy conditions. The mean surface temperature error is 4°C for radiatively clear situations at MOSAiC and up to 15°C in some parts of the Arctic. The spatial variability of the surface temperature, given by 4 observation sites at MOSAiC, is not captured by ERA5 due to its spatial resolution but represented in the level-2 satellite product. The sensitivity analysis of possible error sources, using satellite products of snow depth and sea ice thickness, shows that the positive surface temperature errors during radiatively clear events are, to a large extent, caused by insufficient sea ice thickness and snow depth representation in the reanalysis system. A positive bias characterizes regions with ice thickness greater than 1.5 m, while the negative bias for thinner ice is partly compensated by the effect of snow.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Identifying Meteorologic and Oceanic Conditions Contributing to a Unique Phytoplankton Bloom Occurrence in Micronesia during October 2013

On the first several days of October 2013, daily chlorophyll a (chl a) data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautics and Space Administration (NASA) Aqua satellite detected a marked increase in chlorophyll a concentrations (chl a) in the vicinity of Chuuk Lagoon and the Federated States of Micronesia. Such an increase, likely indicative of a phytoplankton bloom, has not been observed in this location at any other time during the MODIS-Aqua mission, which commenced in 2002 and continues to present. Examination of sea surface wind data from the Modern Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis dataset indicated that the region experienced a sequence of alternating elevated and very low wind speed events prior to the observation of the bloom. The influence of the winds can be seen in MERRA-2 sea surface skin temperature data. Elevated windspeeds for several days likely induced a mixing of deeper waters with higher nutrient levels to the surface, which was followed by stratification and phytoplankton growth during low wind intervals and finally transport induced by a brief high windspeed event. Analysis of hourly MERRA-2 maximum windspeed data over a 40-year period indicated that this sequence was climatologically rare.

Remote Sensing↗
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗