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NASA NTRS2021

Evaluating the Impact of Model Resolutions and Cumulus Parameterization on Precipitation in NU-WRF: A Case Study in the Central Great Plains

Regional climate models are expected to exhibit improved skill at finer spatial resolutions due to improved representation of land surface heterogeneity. However, at spatial scales between 1 to 10 km (grey scales), these improvements are often illusive due to the competing benefits from spatial resolution and cumulus parameterization. This study provides insights into the impact of model resolution and cumulus parameterization on precipitation prediction in the Central Great Plains by using an object-based evaluation method. Our results show limited improvement solely from finer resolution but larger improvement without using the cumulus scheme at a 4-kmresolution. Compared to traditional evaluation methods, the object-based analysis shows that without the cumulus scheme the spatial properties of precipitation are better represented. In contrast, all model configurations show a dry bias in precipitation days and a tendency to produce widespread precipitation but with fewer hours with precipitationwhich indicates other shortcomings in the model.

Yuqi Zhang↗

NASA NTRS2022

Climate Change-Induced Peatland Drying in Southeast Asia

When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985–2005 and 2040–2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.

VIIRS↗

NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗

NASA NTRS2014

The Impact of the Atlantic Cold Tongue on West African Monsoon Onset in Regional Model Simulations for 1998-2002

The Atlantic cold tongue (ACT) develops during spring and early summer near the Equator in the Eastern Atlantic Ocean and Gulf of Guinea. The hypothesis that the ACT accelerates the timing of West African monsoon (WAM) onset is tested by comparing two regional climate model (RM3) simulation ensembles. Observed sea surface temperatures (SST) that include the ACT are used to force a control ensemble. An idealized, warm SST perturbation is designed to represent lower boundary forcing without the ACT for the experiment ensemble. Summer simulations forced by observed SST and reanalysis boundary conditions for each of five consecutive years are compared to five parallel runs forced by SST with the warm perturbation. The article summarizes the sequence of events leading to the onset of the WAM in the Sahel region. The representation of WAM onset in RM3 simulations is examined and compared to Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Project (GPCP) and reanalysis data. The study evaluates the sensitivity of WAM onset indicators to the presence of the ACT by analysing the differences between the two simulation ensembles. Results show that the timing of major rainfall events and therefore theWAM onset in the Sahel are not sensitive to the presence of the ACT. However, the warm SST perturbation does increase downstream rainfall rates over West Africa as a consequence of enhanced specific humidity and enhanced northward moisture flux in the lower troposphere.

Regional model simulation↗

NASA NTRS2010

Studies of 21st-Century Precipitation Trends Over West Africa

West Africa includes a semi-arid zone between the Sahara Desert and the humid Gulf of Guinea coast, approximately between 10 N and 20 N, which is irrigated by summer monsoon rains. This article refers to the region as the Sahel. Rain-fed agriculture is the primary sustenance for Sahel populations, and severe droughts (in the 1970s and 1980s), therefore, have devastating negative societal impacts. The future frequency of Sahel droughts and the evolution of its hydrological balance are therefore of great interest. The article reviews 10 recent research studies that attempt to discover how climate changes will affect the hydrology of the Sahel throughout the 21st century. All 10 studies rely on atmosphere ocean global climate model (AOGCM) simulations based on a range of greenhouse gas emissions scenarios. Many of the simulations are contained in the Intergovernmental Panel on Climate Change archives for Assessment Reports #3 and #4. Two of the studies use AOGCM data to drive regional climate models. Seven studies make projections for the first half of the 21st century and eight studies make projections for the second half. Some studies make projections of wetter conditions and some predict more frequent droughts, and each describes the atmospheric processes associated with its prediction. Only one study projects more frequent droughts before 2050, and that is only for continent-wide degradation in vegetation cover. The challenge to correctly simulate Sahel rainfall decadal trends is particularly daunting because multiple physical mechanisms compete to drive the trend upwards or downwards. A variety of model deficiencies, regarding the simulation of one or more of these physical processes, taints models climate change projections. Consequently, no consensus emerges regarding the impact of anticipated greenhouse gas forcing on the hydrology of the Sahel in the second half of the 21st century.

Druyan, Leonard M.↗

NASA NTRS2011

Impacts of Aerosol Direct Effects on the South Asian Climate: Assessment of Radiative Feedback Processes Using Model Simulations and Satellite/Surface Measurements

Current assessment of aerosol radiative effect is hindered by our incomplete knowledge of aerosol optical properties, especially absorption, and our current inability to quantify physical and microphysical processes. In this research, we investigate direct aerosol radiative effect over heavy aerosol loading areas (e.g., Indo-Gangetic Plains, South/East Asia) and its feedbacks on the South Asian climate during the pre-monsoon season (March-June) using the Purdue Regional Climate Model (PRCM) with prescribed aerosol data derived by the NASA Goddard Earth Observing System Model (GEOS-5). Our modeling domain covers South and East Asia (60-140E and 0-50N) with spatial resolutions of 45 km in horizontal and 28 layers in vertical. The model is integrated from 15 February to 30 June 2008 continuously without nudging (i.e., only forced by initial/boundary conditions). Two numerical experiments are conducted with and without the aerosol-radiation effects. Both simulations are successful in reproducing the synoptic patterns on seasonal-to-interannual time scales and capturing a pre-monsoon feature of the northward rainfall propagation over Indian region in early June which shown in Tropical Rainfall Measuring Mission (TRMM) observation. Preliminary result suggests aerosol-radiation interactions mainly alter surface-atmosphere energetics and further result in an adjustment of the vertical temperature distribution in lower atmosphere (below 700 hPa). The modifications of temperature and associated rainfall and circulation feedbacks on the regional climate will be discussed in the presentation.

Wang, Sheng-Hsiang↗

NASA NTRS2014

Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model

Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.

AGCM↗

NASA NTRS2015

North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends

The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and landatmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.

Cold Spells↗

NASA NTRS2021

Future Changes in Snowpack, Snowmelt, and Runoff Potential Extremes Over North America

Snowpack and snowmelt-driven extreme events (e.g., floods) have large societal consequences including infrastructure failures. However, it is not well understood how projected changes in the snow-related extremes differ across North America. Using dynamically downscaled regional climate model (RCM) simulations, we found that the magnitudes of extreme snow water equivalent, snowmelt, and runoff potential (RP; snowmelt plus precipitation) decrease by 72%, 73%, and 45%, respectively, over the continental United States and southern Canada but increase by up to 8%, 53%, and 41% in Alaska and northern Canada by the late 21st century. In California and the Pacific Northwest, there is a notable increase in extreme RP by 21% contrary to a decrease in snowmelt by 31% by the late century. These regions could be vulnerable to larger rain-on-snow floods in a warmer climate. Regions with a large variability among RCM ensembles are identified, which require further investigation to reduce the regional uncertainties.

Eunsang Cho↗

NASA NTRS2022

Assessing Bare-Ice Albedo Simulated By MAR Over the Greenland Ice Sheet (2000–2021) and Implications for Meltwater Production Estimates

Surface mass loss from the Greenland ice sheet (GrIS) has accelerated over the past decades, mainly due to enhanced surface melting and liquid water runoff in response to atmospheric warming. A large portion of runoff from the GrIS originates from exposure of the darker bare ice in the ablation zone when the overlying snow melts, where surface albedo plays a critical role in modulating the energy available for melting. In this regard, it is imperative to understand the processes governing albedo variability to accurately project future mass loss from the GrIS. Bare-ice albedo is spatially and temporally variable and contingent on non-linear feedbacks and the presence of light-absorbing constituents. An assessment of models aiming at simulating albedo variability and associated impacts on meltwater production is crucial for improving our understanding of the processes governing these feedbacks and, in turn, surface mass loss from Greenland. Here, we report the results of a comparison of the bare-ice extent and albedo simulated by the regional climate model Modèle Atmosphérique Régional (MAR) with satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the GrIS below 70∘ N. Our findings suggest that MAR overestimates bare-ice albedo by 22.8 % on average in this area during the 2000–2021 period with respect to the estimates obtained from MODIS. Using an energy balance model to parameterize meltwater production, we find this bare-ice albedo bias can lead to an underestimation of total meltwater production from the bare-ice zone below 70∘ N of 42.8 % during the summers of 2000–2021.

albedo↗

NASA NTRS2001

Enhanced Climatic Warming Over the Tibetan Plateau Due to Doubling CO2: A Model Study

A number of studies have presented the evidences that surface climate change associated with global warming at high elevation sites shows more pronounced warming than at low elevations, i.e. an elevation dependency of climatic warming pointed out that snow-albedo feedback may be responsible for the excessive warming in the Swiss Alps. From an ensemble of climate change experiments of increasing greenhouse gases and aerosols using an air-sea coupled climate model, Eyre and Raw (1999) found a marked elevation dependency of the simulated surface screen temperature increase over the Rocky Mountains. Using almost all available instrumental records, Liu and Chen (2000) showed that the main portion of the Tibetan Plateau (TP) has experienced significant ground temperature warming since the middlebrows, especially in winter, and that there is a tendency for the warming trend to increase with elevation in the TP as well as its surrounding areas. In this paper, we will investigate the mechanism of elevation dependency of climatic warming in the TP by using a high-resolution regional climate model.

Chen, Baode↗

NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗

NASA NTRS2004

A LEO Hyperspectral Mission Implementation for Global Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, high resolution (less than l0 nm) imaging spectrometers capable of acquiring multiple regional to global scale observations per day should enable the development of new remote sensing measurements for important but as yet unobservable variables, with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere a needed to id- the geographical locations and temporal dynamics of carbon sources/sinks and to improve regional climate models and climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage and sparse spectral information provided by most single polar-orbiting, earth-looking satellite. The available satellite observations lack a sufficient number of well-placed narrow bands from which to derive spectral indices that capture vegetation responses to stress conditions associated with down-regulation of photosynthesis. Physiological status can best be assessed with spectral indices based on continuous, narrow bands in the visible/near infrared spectra, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world's coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of ocean carbon uptake and its role in climate change.

Gervin, Janette C.↗

NASA NTRS2018

Southeast Greenland Winter Precipitation Strongly Linked to the Icelandic Low Position

Greenland's largest precipitation flux occurs in its southeast (SE) region during the winter, controlled primarily by easterly winds and frequent cyclogenesis in the North Atlantic. Several studies have attempted to link SE Greenland precipitation to the North Atlantic Oscillation (NAO) but results are inconsistent. This work uses reanalysis, automatic weather station data, and regional climate model output to show that the east-west position of the Icelandic low is a better predictor of SE Greenland precipitation (average correlation of r equals -0.48 in DJF (December January February)) than climate indices such as the NAO (r equals -0.06 in DJF). In years when the Icelandic low is positioned extremely west, moisture transport increases up to approximately 40 percent (or up to 40 kilograms per meter per second) off the SE Greenland coast compared to when the low is in an extreme east position. Furthermore, in years when the Icelandic low is positioned extremely west, storm track density and intensity increase just off the SE coast of Greenland. Thus, the Icelandic low's longitudinal position dominates SE Greenland ice sheet's wintertime precipitation, a positive term in the ice sheet mass balance. Given SE Greenland's importance in the overall ice sheet mass balance, the position of the Icelandic low is therefore important for making projections of future sea level.

Arctic↗

NASA NTRS2012

Human Settlements in the South-Central U.S., Viewed at Night from the International Space Station

A recent innovation of astronauts observing Earth from the International Space Station (ISS) is documenting human footprints by photographing city lights at night time. One of the earliest night-time images from the ISS was the US-Mexico border at El Paso-Ciudad Juarez. The colors, patterns and density of city lights document the differences in the cultural settlement patterns across the border region, as well as within the urban areas themselves. City lights help outline the most populated areas in settlements around the world, and can be used to explore relative population densities, changing patterns of urban/suburban development, transportation networks, spatial relationship to geographic features, and more. The data also provides insight into parameters such as surface roughness for input into local and regional climate modeling and studies of light pollution. The ground resolution of night-time astronaut photography from the ISS is typically an order of magnitude greater than current Defense Meteorological Satellite Program (DMSP) data, and therefore can serve as a "zoom lens" for selected urban areas. Current handheld digital cameras in use on the ISS, optimized for greater light sensitivity, provide opportunities to obtain new detailed imagery of atmospheric phenomena such as airglow, aurora, and noctilucent clouds in addition to documenting urban patterns. ISS astronauts have taken advantage of increasingly sensitive digital cameras to document the world at night in unprecedented detail. In addition, the capability to obtain time-lapse imagery from fixed cameras has been exploited to produce dynamic videos of both changing surface patterns around the world and atmospheric phenomena. We will profile some spectacular images of human settlements over the South-Central U.S., and contrast with other images from around the world. More data can be viewed at http://eol.jsc.nasa.gov/Videos/CrewEarthObservationsVideos/. US-Mexico border is obvious by the different lighting pattern. Not surprisingly, the densely illuminated city of Juarez indicates a higher population; El Paso's smaller population is spread out over a larger area.

Dawson, Melissa↗

NASA NTRS2011

An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface Reflectance and MODIS BRDF

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

Shuai, Yanmin↗

NASA NTRS2011

Global Precipitation Measurement: Methods, Datasets and Applications

This paper reviews the many aspects of precipitation measurement that are relevant to providing an accurate global assessment of this important environmental parameter. Methods discussed include ground data, satellite estimates and numerical models. First, the methods for measuring, estimating, and modeling precipitation are discussed. Then, the most relevant datasets gathering precipitation information from those three sources are presented. The third part of the paper illustrates a number of the many applications of those measurements and databases. The aim of the paper is to organize the many links and feedbacks between precipitation measurement, estimation and modeling, indicating the uncertainties and limitations of each technique in order to identify areas requiring further attention, and to show the limits within which datasets can be used.

Global Climate Models (GCM)↗

NASA NTRS2016

Arctic Cut-Off High Drives the Poleward Shift of a New Greenland Melting Record

Large-scale atmospheric circulation controls the mass and energy balance of the Greenland ice sheet through its impact on radiative budget, runoff and accumulation. Here, using reanalysis data and the outputs of a regional climate model, we show that the persistence of an exceptional atmospheric ridge, centered over the Arctic Ocean, was responsible for a poleward shift of runoff, albedo and surface temperature records over the Greenland during the summer of 2015. New records of monthly mean zonal winds at 500 hPa and of the maximum latitude of ridge peaks of the 5,700+/-50 m isohypse over the Arctic were associated with the formation and persistency of a cutoff high. The unprecedented (1948-2015) and sustained atmospheric conditions promoted enhanced runoff, increased the surface temperatures and decreased the albedo in northern Greenland, while inhibiting melting in the south, where new melting records were set over the past decade. Subject terms: Earth sciences Atmospheric science Climate science

drainage↗