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NASA NTRS2018

Connecting Regional Aerosol Emissions Reductions to Local and Remote Precipitation Responses

The unintended climatic implications of aerosol and precursor emission reductions implemented to protect public health are poorly understood. We investigate the precipitation response to regional changes in aerosol emissions using three coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (CESM1), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160-240 years each). We perturb emissions of sulfur dioxide and/or carbonaceous aerosol within six world regions and assess the significance of precipitation responses relative to internal variability determined by the control simulation and across the models. Global and regional precipitation mostly increases when we reduce regional aerosol emissions in the models, with the strongest responses occurring for sulfur dioxide emissions reductions from Europe and the United States. Precipitation responses to aerosol emissions reductions are largest in the tropics and project onto the El Nino Southern Oscillation (ENSO). Regressing precipitation onto an Indo-Pacific zonal sea level pressure gradient index (a proxy for ENSO) indicates that the ENSO component of the precipitation response to regional aerosol removal can be as large as 20% of the total simulated response. Precipitation increases in the Sahel in response to aerosol reductions in remote regions because an anomalous interhemispheric temperature gradient alters the position of the Intertropical Convergence Zone (ITCZ). This mechanism holds across multiple aerosol reduction simulations and models.

Westervelt, Daniel M.↗

NASA NTRS2018

GEOS S2S-2_1: The GMAO High Resolution Seasonal Prediction System

A new version of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was recently released by the NASA/Goddard Global Modeling and Assimilation Office. The new version runs at higher atmospheric resolution than the previous, (approximately 1/2 degree globally), contains a substantially improved model description of the cryosphere, and includes additional interactive earth system model components (aerosol model). In addition, the Ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter, and now includes the assimilation of along-track sea surface height. Here will describe the new system, along with the plans for the future (GEOS S2S-3_0) which will include a higher resolution ocean model and more interactive earth system model components (interactive vegetation, biomass burning from fires). We will also present results from a series of retrospective seasonal forecasts. Results show significant improvements in surface temperatures over much of the northern hemisphere and a much improved prediction of sea ice extent in both hemispheres. Analysis of the ensemble spread shows improvements relative to the previous system, including generally better reliability. The precipitation forecast skill is comparable to previous S2S systems, and the only tradeoff is an increased "double ITCZ", which is expected as we go to higher atmospheric resolution.

Molod, Andrea↗

NASA NTRS2019

Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction Model

Much work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves NiÃ±o3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.

Ocean↗

NASA NTRSDate not supplied

TPSAS-NF1676L-28151-DND

The proposed suborbital mission is to collect and analyze observations to help improve our ability to model and forecast these crucial monsoonal transports and their downstream effects. The objectives are 1) to observe and relate convective-scale to meso-scale changes in the three-dimensional circulation with the efficiency of the resulting convective transports (of air mass and heat) and the build-up of the large-scale anomalies, as they are modulated by the three-dimensional structure of the aerosol loading; and 2) to observe how fluctuations in the monsoon large-scale upper-level outflow affect downstream convection, especially within AEWs. The observations will be tailor-made to help understand the controls of the northward march of the monsoon isochrones, the initiation and magnitude of heat towers over the subcontinent during the monsoon, and how the mostly zonal land-sea differential heating interacts with the meridional progress of the Intertropical Convergence Zone (ITCZ) to constrain the intensities of the northern and western outflows. Unique contributions will be made by two airborne instruments, operated in concert: NASA-LARC's Doppler Aerosol Wind Lidar (DAWN) coherent-detection wind lidar which uses a pulsed laser with a wavelength of about two microns to measure vertical profiles of the three dimensional components of the wind field, and JPL's Airborne Second Generation Precipitation Radar (APR-2) precipitation radar which measures the three-dimensional structure of rain within a swath that is about10km wide (depending on the altitude of the plane) and extends from flight level down to the surface.

Upendra N Singh↗

NASA NTRS2020

Fast Responses on Pre-Industrial Climate from Present-Day Aerosols in A CMIP6 Multi-Model Study

In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014. In response to the pattern of all aerosols effective radiative forcing (ERF), the fast temperature responses are characterized by cooling over the continental areas, especially in the Northern Hemisphere, with the largest cooling over East Asia and India, sulfate being the dominant aerosol surface temperature driver for present-day emissions. In the Arctic there is a warming signal for winter in the ensemble mean of fast temperature responses, but the model-to-model variability is large, and it is presumably linked to aerosol-induced circulation changes. The largest fast precipitation responses are seen in the tropical belt regions, generally characterized by a reduction over continental regions and presumably a southward shift of the tropical rain belt. This is a characteristic and robust feature among most models in this study, associated with weakening of the monsoon systems around the globe (Asia, Africa and America) in response to hemispherically asymmetric cooling from a Northern Hemisphere aerosol perturbation, forcing possibly the Intertropical Convergence Zone (ITCZ) and tropical precipitation to shift away from the cooled hemisphere despite that aerosols' effects on temperature and precipitation are only partly realized in these simulations as the sea surface temperatures are kept fixed. An interesting feature in aerosol-induced circulation changes is a characteristic dipole pattern with intensification of the Icelandic Low and an anticyclonic anomaly over southeastern Europe, inducing warm air advection towards the northern polar latitudes in winter.

Pre-industrial climate↗

NASA NTRSDate not supplied

Global Precipitation Means and Variations with the New Version of GPCP

Knowledge of global precipitation means, patterns and variations is essential for understanding the global water cycle. The observation-based global analysis of the Global Precipitation Climatology Project (GPCP) has been a key input to many such studies, including those related to means of the global (and regional) water and energy cycles. A new version (Version 3.1) of the GPCP monthly analysis is now available (1983-2019), with finer spatial resolution (0.5º latitude/longitude), updated satellite algorithms, latest gauge analysis over land from the Global Precipitation Climatology Center (GPCC), and with ocean climatologies adjusted using information from the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission and CloudSat. The presentation will give key findings from the new analysis, compare with the previous version, link to studies of the water cycle and compare to CMIP6 climate model results. The GPCP Monthly V3.1 analysis uses a Tropical Composite Climatology (TCC) using 22 years (1998-2019) of TRMM and GPM-based surface precipitation estimates from passive microwave, radar and combined passive microwave and radar observations to adjust the long-term mean values in the tropics over ocean. At higher latitudes over ocean climatological values of merged CloudSat and GPM combined passive microwave and radar surface precipitation estimates are used. The result of the new algorithms and procedures is an ocean mean value 60º N to 60º S of 3.2 mm/d, an increase of 7% from the older V2.3. Over land the gauge analysis (from GPCC in Germany), combined with satellite estimates results in a small decrease (~ 0.5%) from the previous version, giving a total global precipitation mean of 2.81 mm/d for V3.1, an increase of 4.5%. Variations from inter-annual to trend scales over most of the ocean are driven by the Colorado State University (CSU) Goddard Profiling (GPROF) algorithm applied to SSMI/SSMIS satellite data. The new GPCP version retains a near zero trend of global precipitation, with significant positive trends in the deep tropics along the Pacific ITCZ and elsewhere, countered by middle latitude decreases, very similar to the previous version of the GPCP Monthly analysis. The pattern of trends is similar to that of AMIP climate model results, driven by observed SSTs for the period in question, but very different from results for “free-running” CMIP historical ensembles, likely due in part to the relatively short comparison period and effects of inter-decadal variations in the GPCP and AMIP results that are not in the “history” models. Interannual variations are also nearly the same in the new version, but with finer detail, although ENSO variations over the ocean have slightly larger amplitude than before, an effect likely related to the change in ocean satellite algorithm used in Version 3. For precipitation intensity (percentiles) at the monthly scale, especially in the tropics, GPCP shows a positive trend for the upper one third of the percentiles (Pct ≥ 70th) and a much weaker positive trend for the lowest percentiles (Pct ≤ 10th), while negative trends appear for the middle one-half percentiles (20th-65th). AMIP results agree with those from the GPCP in terms of the sign of the changes/trends for high and intermediate percentiles. The CMIP historical results also agree in the sign of the trends, but the trends are weaker. Comparisons with other types of CMIP historical simulations including the GHG-only, aerosol-only, and nature-only runs suggest that the observed changes/trends in precipitation amount and intensity during the GPCP period are dominated by a combination of the effects of the Pacific Decadal Oscillation (PDO) and anthropogenic GHG-related surface warming.

Robert Adler↗

NASA NTRS2021

Goddard Latent Heating Retrieval Algorithm for TRMM and GPM

The Goddard Convective-Stratiform Heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model (CRM) to simulate LH profiles to build look-up tables (LUTs). In this paper we describe the current V6 CSH and its differences/similarities versus the previous V5 CSH. Long-term CRM simulations are conducted to identify the impact of CRM resolution and the convective-stratiform separation method on LH structure/profiles. The TRMM and GPM Combined algorithm derived surface rainfall rates and their associated precipitation properties are the input to the CSH algorithm. Since there is no direct measurement of LH structure, the performance of the CSH V6 algorithm is examined by comparing its vertically-integrated heating (or equivalent surface rainfall rate) against the surface rainfall rate derived from the TRMM/GPM Combined algorithm. The results suggest the CSH three-month and zonal mean equivalent surface rain rates are in good agreement with the Combined rates over the ITCZ region; the agreement is best over ocean. CSH three-month and zonal mean equivalent surface rain rates are larger than the Combined rates over land in both the tropics and sub-tropics. CSH three-month mean equivalent surface rainfall rates also have local differences with the Combined rates that can be smoothed by area averaging to larger horizontal resolutions (from the CSH standard grid of 0.25° × 0.25° to 0.5° × 0.5° or 1.0° × 1.0°). CSH equivalent surface rainfall rates have more light rain rates but less larger rain rates compared to the GPM Combined surface rain rates.

Latent heating retrieval↗

NASA NTRS2021

Understanding the Global Three-Dimensional Distribution of Precipitation Mean Particle Size with the Global Precipitation Measurement Mission

This study addresses the global distribution of precipitation mean particle size using data from the Global Precipitation Measurement (GPM) mission. The mass-weighted mean diameter Dm is a characteristic parameter of the precipitation particle size distribution (PSD), estimated from the GPM Combined Radar–Radiometer Algorithm (CORRA) using data from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a 6-yr (2014–20) global climatology within 70°N–70°S. The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from ~0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest annual mean Dm (~0.8 mm) are found in the eastern oceans, and the largest values (~2 mm) occur above the melting levels in convection over land in summer. The standard deviation of the annual mean is generally <0.45 mm below 6 km. Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2–10 km). The U.S. Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the Southern Hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter. Relatively small Dm occurs over tropical oceans, including ITCZ, requiring further investigation.

Mei Han↗

NASA NTRS2023

Investigating Hydroclimatic Impacts of the 168–158 BCE Volcanic Quartet and Their Relevance to the Nile River Basin and Egyptian History

The Ptolemaic era (305–30 BCE) is an important period of Ancient Egyptian history known for its material and scientific advances, but also intermittent political and social unrest in the form of (sometimes widespread) revolts against the Ptolemaic elites. While the role of environmental pressures has long been overlooked in this period of Egyptian history, ice-core-based volcanic histories have identified the period as experiencing multiple notable eruptions, and a repeated temporal association between explosive volcanism and revolt has recently been noted. Here we analyze the global and regional (Nile River basin) hydroclimatic response to a unique historical sequence of four large and closely timed volcanic eruptions (first a tropical one, followed by three extratropical northern hemispheric events) between 168 and 158 BCE, a particularly troubled period in Ptolemaic history for which we now provide a more detailed hydroclimatic context. The NASA (National Aeronautics and Space Administration) GISS (Goddard Institute for Space Studies) ModelE2.1 Earth system model simulates a strong radiative response with a radiative forcing (top of atmosphere) of −7.5 W m−2 (following the first eruption) and −2.5 W m−2 (after each of the three remaining eruptions) at a global scale. Associated with this, we observe a global surface cooling of the order of 1.5 ∘C following the first (tropical) eruption, with the following three extratropical eruptions extending the cooling period for more than 15 years. Consequently, this series of eruptions is observed to constrain the northward migration of the inter-tropical convergence zone (ITCZ) during the Northern Hemisphere summer monsoon season, and major monsoon zones (African, South Asian, and East Asian) were seen to experience a suppression of rainfall of >1 mm d−1 during the monsoon (JJAS) season averaged for 2 years after each eruption. A substantial suppression of the Indian and North African summer monsoon (over the Nile River headwater region) was seen to strongly affect the modeled river flow in the catchment and discharge at river mouth. River mass flow over the basin was observed to decrease by 29 % and 38 % relative to an unperturbed (non-volcanic) annual mean flow in the first and second year, respectively, after the first (i.e., tropical) eruption. A moderate decrease ranging between 5 % and 18 % was observed after the third and fourth (extratropical) eruptions. These results indicate, in sum, that the first eruption likely produced a strong hydroclimate response, with the following extratropical eruptions prolonging this. These results also support the recently hypothesized association between ice-core-based signals of explosive volcanism and hydroclimatic variability during the Ptolemaic era, including the suppression of the agriculturally critical Nile summer flooding.

hydroclimate impacts↗

NASA NTRS1993

On the Problem of Measuring Interannual Wind Speed Variations Using SSMI Data

The first Special Sensor Microwave Imager (SSMI) was launched on the Defence Meteorological Satellite Program (DMSP) F8 spacecraft in July 1987, and wind speed was no longer retrieved after December 1991. A second SSMI was launched on DMSP F10 in December 1990. Interpretation of the 1987 - 1993 (or longer)SSMI wind speed time series is dependent upon the space and time characteristics of the differences between F8 and F10 SSMI measurements.

SSMI↗