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NASA NTRS2022

Correction of Path Integrated Attenuation Estimates Considering the Soil Moisture Effect for the Gpm Dual-Frequency Precipitation Radar

Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by s0e) over land increased in the presence of precipitation. This behavior, called the soil moisture effect, causes an underestimate of the PIA by the SRT as the method does not explicitly consider this effect. In this study, measurements made by Ku-band Precipitation Radar (KuPR) and Ka-band Precipitation Radar (KaPR), which comprise the DPR, were analyzed to examine whether KuPR and KaPR exhibit similar dependencies on the soil moisture as does the PR. For both KuPR and KaPR, an increase in s0e was observed for a large portion of the land area, except for forests and deserts. Results from the Hitschfeld–Bordan (HB) method suggest that s0e increases with the surface precipitation rate for light precipitation events. Meanwhile, for heavy precipitation, owing to the degradation of the HB method, it is difficult to estimate s0e quantitatively. Thus, a correction method for PIA that considers the soil moisture effect was developed and implemented into the DPR standard algorithm. With this correction, the surface precipitation rate estimates increased by approximately 18%for KuPR and 15%for the normal scan of KaPR over land.

Shinta Seto↗

NASA NTRS2016

Ice-Covered Lakes in Gale Crater Mars: The Cold and Wet Hypothesis

Recent geological discoveries from the Mars Science Laboratory provide evidence that Gale crater may have intermittently hosted a fluvio-lacustine environment during the Hesperian, with individual lakes lasting for a period of tens to hundreds of thousands of years. (Grotzinger et al., Science, 350 (6257), 2015). Estimates of the CO2 content of the atmosphere at the time the Gale sediments formed are far less than needed by any climate model to warm early Mars (Bristow et al., Geology, submitted), given the low solar energy input available at Mars 3.5 Gya. We have therefore explored the possibility that the lakes in Gale during the Hesperian were perennially covered with ice using the Antarctic Lakes as an analog. Using our best estimate for the annual mean surface temperature at Gale at this time (approx. 230K) we computed the thickness of an ice-covered lake. These thickness range from 10-30 meters depending on the ablation rate and ice transparency and would likely inhibit sediments from entering the lake. Thus, a first conclusion is that the ice must not be too cold. Raising the mean temperature to 245K is challenging, but not quite as hard as reaching 273K. We found that a mean annual temperature of 245K ice thicknesses range from 3-10 meters. These values are comparable to the range of those for the Antarctic lakes (3-6 m), and are not implausible. And they are not so thick that sediments cannot penetrate the ice. For the ice-covered lake hypothesis to work, however, a melt water source is needed. This could come from subaqueous melting of a glacial dam in contact with the lakes (as is the case for Lake Untersee) or from seasonal melt water from nearby glaciers (as is the case for the Dry Valley lakes). More work is needed to better assess these possibilities. However, the main advantage of the ice-covered lake model (and the main reason we pursued it) is that it relaxes the requirement for a long-lived active hydrological cycle involving rainfall and runoff, which no climate model is able to produce given known constraints on the early Mars environment.

Antarctic lakes↗

NASA NTRS2003

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) observations and it is based on models that simulate high-resolution brightness temperatures as functions of observed reflectivity profiles and a parameter related to the rain drop-size-distribution. The modeled high-resolution brightness temperatures are used to determine normalized brightness temperature polarizations at the microwave radiometer resolution. An optimal estimation procedure is employed to minimize the differences between the simulated and observed normalized polarizations by adjusting the drop-size-distribution parameter. The impact of other unknowns that are not independent variables in the optimal estimation but affect the retrievals is minimized through statistical parameterizations derived from cloud model simulations. The retrieval technique is investigated using TRMM observations collected during the Kwajalein Experiment (KWAJEX). These observations cover an area extending from 5 deg to deg N latitude and 166 deg to 172 deg E longitude from July to September 1999, and are coincident with various ground-based observations, facilitating a detailed analysis of the retrieved precipitation. Using the method developed in this study, precipitation estimates consistent with both the passive and active TRMM observations are obtained. Various parameters characterizing these estimates, i.e. the rain rate, the precipitation water content, the drop-size-distribution intercept, and the mass weighted mean drop diameter, are in good qualitative agreement with independent experimental and theoretical estimates. Combined rain estimates are in general higher than the official TRMM Precipitation Radar (PR) only estimates for the area and the period considered in the study. Ground-based precipitation estimates, derived from an analysis of rain gauge and ground radar data, are in better agreement with the combined estimates than with the TRMM PR-only estimates, which suggests that information useful for improving the radar-only estimates is contained in the brightness temperature data.

Grecu, Mircea↗

DOE OSTI2021

Increased extreme rains intensify erosional nitrogen and phosphorus fluxes to the northern Gulf of Mexico in recent decades

Abstract Soil erosion delivers enormous amounts of macro-nutrients including nitrogen (N) and phosphorus (P) from land to rivers, potentially sustaining water column bioavailable nutrient levels for decades. In this study, we represent erosional N and P fluxes in the Energy Exascale Earth System Model (E3SM) and apply the model to the continental United States. We estimate that during 1991–2019 soil erosion delivers 775 Gg yr −1 (1 Gg = 10 9 g) of particulate N (PN) and 328 Gg yr −1 of particulate P (PP) on average to the drainage basins of the northern Gulf of Mexico, including the Mississippi/Atchafalaya River and other rivers draining to the Texas Gulf and the Eastern Gulf. Our model simulation shows that in these rivers PP is the dominant P constituent and over 55% of P exported by erosion comes from soil P pools that could become bioavailable within decades. More importantly, we find that during 1991–2019 erosional N and P fluxes increase at rates of about 15 Gg N yr −1 and 6 Gg P yr −1 , respectively, due to increased extreme rains in the Mississippi/Atchafalaya river basin, and this intensification of erosional N and P fluxes drive the significant increase of riverine PN and PP yields to the northern Gulf of Mexico. With extreme rains projected to increase with warming, erosional nutrient fluxes in the region would likely continue to rise in the future, thus complicating the effort of reducing eutrophication in the inland and coastal waters.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Convective and stratiform rain: Multichannel microwave sensing over oceans

Measurements made by the Special Sensor Microwave/Imager (SSM/I) radiometer over the oceans, at 19, 37, and 85 GHz in dual polarization, are used to develop a model to classify rain into light-stratiform, moderately convective, and heavy convective types in the mesoscale convective systems (MCS). It is observed that the bulk of the 19- and 37-GHz data are linearly correlated with respect to one another, and generally increase together in brightness as the mean rain rate in the field of view (FOV) of the radiometer increases. However, a significant fraction of the data from these channels departs from this linear relationship, reflecting the nonuniform rain that is convective vs. the relatively light stratiform rain. It is inferred from the SSM/I data, in a MCS, when the slope dT sub 3/dT sub 19 is greater than unity there are optically thin clouds which produce light uniform rain. On the other hand, when dT sub 3/dT sub 19 is close to unity, the rain cells have an open structure and correspond to the convective type of rain. The openings between the cells are apparently a result of the downdrafts and/or entrainment. Relatively low values of 85-GHz brightness temperatures that are present when dT sub 37/dT sub 19 is close to unity support these views and, in addition, leads us to conclude that when the convection is heavy this brightness temperature decreases due to scattering by hydrometeors. On the basis of this explanation of the SSM/I data, an empirical rain retrieval algorithm is developed. Radar backscatter observations over the Atlantic Ocean next to Florida are used to demonstrate the applicability of this method. Three monthly mean maps of rainfall over the oceans from 50 degrees N to 50 degrees S, are presented to illustrate the ability of this method to sense seasonal and interannual variations of rain.

Prabhakara, C.↗

DOE OSTI2024

Spatial patterns of historical crop yields reveal soil health attributes in US Midwest fields

Abstract Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers’ fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ.

Fowler, Ames↗

NASA NTRS2015

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the flash rate) was calculated for storms having 85 GHz PCT greater than 150 K. NLDN data was used to determine if a CG strike occurred for a storm. This probability of CG lightning was plotted as a function of minimum 85 GHz PCT and minimum 37 GHz PCT. These probabilities were used in conjunction with the linear model to estimate the CG flash rate for weaker storms with minimum 85 GHz PCTs greater than 150 K. Results from the investigation of CG lightning and passive microwave radiation signals agree with the previous research investigating total lightning and brightness temperature. Future work will take the established relationships and apply them to the decades of available DMSP data for the USA to derive a map of CG lightning flash rates. Validation of this method and uncertainty analysis will be done by comparing the derived maps of CG lightning flash rates against existing NLDN maps of CG lightning flash rates.

Winesett, Thomas↗

DOE OSTI2024

Congo Basin Water Balance and Terrestrial Fluxes Inferred From Satellite Observations of the Isotopic Composition of Water Vapor

Large spatio-temporal gradients in the Congo basin vegetation and rainfall are observed. However, its water-balance (evapotranspiration minus precipitation, or ET - P) is typically measured at basin-scales, limited primarily by river-discharge data, spatial resolution of terrestrial water storage measurements, and poorly constrained ET. We use observations of the isotopic composition of water vapor to quantify the spatio-temporal variability of net surface water fluxes across the Congo Basin between 2003 and 2018. These data are calibrated at basin scale using satellite gravity and total Congo river discharge measurements and then used to estimate time-varying ET - P over four quadrants representing the Congo Basin, providing first estimates of this kind for the region. We find that the multi-year record, seasonality, and interannual variability of ET - P from both the isotopes and the gravity/river discharge based estimates are consistent. Additionally, we use precipitation and gravity-based estimates with our water vapor isotope-based ET - P to calculate time and space averaged ET and net river discharge within the Congo Basin. These quadrant-scale moisture flux estimates indicate (a) substantial recycling of moisture in the Congo Basin (temporally and spatially averaged ET/P > 70%), consistent with models and visible light-based ET estimates, and (b) net river outflow is largest in the Western Congo where there are more rivers and higher flow rates. Our results confirm the importance of ET in modulating the Congo water cycle relative to other water sources.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗

NASA NTRS2010

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Jonathan L. Case↗

DOE OSTI2022

Understanding Recent Global Hydroclimate Change Using Multivariate Detection and Attribution Techniques and GCM Experiments

The observed slowdown in the rate of global average surface temperature (T) warming during the post-1998 decade (referred to at the time as the “global warming hiatus”) posed a challenge for climate researchers because it was not captured in global climate models projection. Observational and modeling evidence hinted that that leveling of the T trend was linked with the simultaneous appearance of cold surface temperature in the eastern equatorial Pacific that formed a protracted La Niña-like state, a phenomenon known as the Inter-decadal Pacific Oscillation (IPO). It was however not clear whether the concurrent equatorial Pacific cooling was a regional response to the rise in atmospheric greenhouse gas levels or anthropogenic aerosols that is not captured by the climate models or whether it was an unrelated, serendipitous manifestation of a natural phenomenon, internal to the climate system. To resolve this issue, we proposed in this project to develop and apply fingerprinting methods to differentiate between the observed climate response to various external forcing agents and the manifestations of internal climate variability. The project also sought to find out if climate models are able to reproduce the change signals detected in key observational phenomena and if they can be used to investigate the underlying processes. As such we examined changes in global hydroclimate variability and in an outstanding example of regional hydroclimate change, namely the multi-decadal 20 th century change in Sahel rainfall.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

Correlation of S-Band Weather Radar Reflectivity and ACTS Propagation Data in Florida

Previous work has shown that Ka-band attenuation due to rainfall and corresponding S-band reflectivity are highly correlated. This paper reports on work whose goal is to determine the feasibility of estimation and, by extension, prediction of one parameter from the other using the Florida ACTS propagation terminal (APT) and the nearby WSR-88D S-band Doppler weather radar facility operated by the National Weather Service. This work is distinguished from previous efforts in this area by (1) the use of a single-polarized radar, preventing estimation of the drop size distribution (e.g., with dual polarization) and (2) the fact that the radar and APT sites are not co-located. Our approach consists of locating the radar volume elements along the satellite slant path and then, from measured reflectivity, estimating the specific attenuation for each associated path segment. The sum of these contributions yields an estimation of the millimeter-wave attenuation on the space-ground link. Seven days of data from both systems are analyzed using this procedure. The results indicate that definite correlation of S-band reflectivity and Ka-band attenuation exists even under the restriciton of this experiment. Based on these results, it appears possible to estimate Ka-band attenuation using widely available operational weather radar data. Conversely, it may be possible to augment current radar reflectivity data and coverage with low-cost attenuation or sky temperature data to improve the estimation of rain rates.

Wolfe, Eric E.↗

NASA NTRS1996

Compilation and Analysis of 20 and 30 GHz Rain Fade Events at the ACTS NASA Ground Station: Statistics and Model Assessment

The purpose of the propagation studies within the ACTS Project Office is to acquire 20 and 30 GHz rain fade statistics using the ACTS beacon links received at the NGS (NASA Ground Station) in Cleveland. Other than the raw, statistically unprocessed rain fade events that occur in real time, relevant rain fade statistics derived from such events are the cumulative rain fade statistics as well as fade duration statistics (beyond given fade thresholds) over monthly and yearly time intervals. Concurrent with the data logging exercise, monthly maximum rainfall levels recorded at the US Weather Service at Hopkins Airport are appended to the database to facilitate comparison of observed fade statistics with those predicted by the ACTS Rain Attenuation Model. Also, the raw fade data will be in a format, complete with documentation, for use by other investigators who require realistic fade event evolution in time for simulation purposes or further analysis for comparisons with other rain fade prediction models, etc. The raw time series data from the 20 and 30 GHz beacon signals is purged of non relevant data intervals where no rain fading has occurred. All other data intervals which contain rain fade events are archived with the accompanying time stamps. The definition of just what constitutes a rain fade event will be discussed later. The archived data serves two purposes. First, all rain fade event data is recombined into a contiguous data series every month and every year; this will represent an uninterrupted record of the actual (i.e., not statistically processed) temporal evolution of rain fade at 20 and 30 GHz at the location of the NGS. The second purpose of the data in such a format is to enable a statistical analysis of prevailing propagation parameters such as cumulative distributions of attenuation on a monthly and yearly basis as well as fade duration probabilities below given fade thresholds, also on a monthly and yearly basis. In addition, various subsidiary statistics such as attenuation rate probabilities are derived. The purged raw rain fade data as well as the results of the analyzed data will be made available for use by parties in the private sector upon their request. The process which will be followed in this dissemination is outlined in this paper.

Manning, Robert M.↗

NASA NTRS2000

Tropical Cyclone Lightning Distribution and Its Relationship to Convection and Intensity Change

The long distance National Lightning Detection Network (NLDN) was used to monitor the distribution of lightning strokes in various 1998 and 1999 western North Atlantic tropical cyclones. These ground-based lightning observations together with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and the Tropical Rain Mapping Mission (TRMM) Microwave Instrument (TMI) derived convective rain rates were used to monitor the propagation of electrically charged convective rain bands aid to qualitatively estimate intensification. An example of the lightning analyses was performed on hurricane George between 25-28 September, 1998 when the system left Key West and moved towards the Louisiana coast. During this period of time, George's maximum winds increased from 38 to 45 meters per second on 25 September and then remained steady state until it made landfall. Time-radius displays of the lightning strokes indicated that the greatest number of lightning strokes occurred within the outer core region (greater than 165 km) with little or no lightning strokes at radii less than 165 km. The trend in these lightning strokes decreased as George move into the Gulf of Mexico and showed no inward propagation. The lack inward propagating lightning strokes with time indicated that there was no evidence that an eye wall replacement was occurring that could alter George's intensity. Since George was steady state at this time, this result is not surprising. Time-azimuth displays of lightning strokes in an annulus whose outer and inner radii were respectively, 222 and 333 km from George's center were also constructed. A result from this analysis indicated that the maximum number of strokes occurred in the forward and rear right quadrant when George was over the Gulf of Mexico. This result is, consistent with the aircraft and satellite observations of maximum rainfall.

Rodgers, Edward↗

NASA NTRS2007

Observations of Lightning on Earth from the Lunar Surface

The NASA Optical Transient Detector (OTD) launched into a 70deg inclination orbit in April 1995 aboard the MicroLab-1 satellite and the Lightning Imaging Sensor (LIS) launched into a 35deg inclination orbit in November 1997 (and still operating today) aboard the Tropical Rainfall Measuring Mission have produced the most comprehensive global observations of lightning activity on Earth. The OTD collected data for 5-yr from an altitude of 740 km while the LIS, in its 10th year of operations, is still collecting data from its current altitude of 402 km. From these altitudes the OTD observes an individual storm within its field of view for approx.3 min and the LIS for approx.90 sec as the satellites orbit the earth. Figures 1-4 show the combined LIS/OTD distribution of lightning for day and night during the Northern Hemisphere warm season from April through August (Fig. 1,2) and the cool season from October through February (Fig. 3,4) as might be observed from the lunar surface (12-h daylight and 12-h nighttime observations). The day and night plots are for the twelve hour periods centered on local noon and midnight. The total viewtime of the global lightning activity is 200 hours or less, depending on latitude (Fig. 5). Most of the observed lightning occurs over the northern hemisphere land areas as reported in previous studies. More lightning activity is seen at the higher northern latitudes during the day. The greatest lightning maxima occurs in the southeastern US, during the day. The corresponding region at night shows much less lightning activity. In contrast, there is a maxima in lightning activity at night over the high Plains area of the U.S. This region had lower lightning rates during the daytime period. During the cold season, the southern hemisphere has significantly more lightning. The maxima in Central Africa is still present, and a secondary maxima is observed in South Africa. In South America, the maxima in Argentina occurs at night in association with large-scale mesoscale convective storm complexes. This is the region on the earth having the greatest frequency of extreme storms with flash rates exceeding 1000 flashes/min. daytime maxima is seen extending from Northern Argentina to Brazil. In the US., the Gulf of Mexico and the Gulf Coast states exhibit a maximum in lightning activity both day and night.

Goodman, S. J.↗

NASA NTRS2013

The Effect of Agricultural Growing Season Change on Market Prices in Africa

Local agricultural production is a key element of food security in many agricultural countries in Africa. Climate change and variability is likely to adversely affect these countries, particularly as they affect the ability of smallholder farmers to raise enough food to feed themselves. Seasonality influences farmers' decisions about when to sow and harvest, and ultimately the success or failure of their crops. At a 2009 conference in the United Kingdom hosted by the Institute of Development Studies, Jennings and Magrath (2009) described farmer reports from East Asia, South Asia, Southern Africa, East Africa and Latin America. Farmers indicate significant changes in the timing of rainy seasons and the pattern of rains within seasons, including: More erratic rainfall, coming at unexpected times in and out of season; Extreme storms and unusually intense rainfall are punctuated by longer dry spells within the rainy season; Increasing uncertainty as to the start of rainy seasons in many areas; Short or transitional second rainy seasons are becoming stronger than normal or are disappearing altogether. These farmer perceptions of change are striking in that they are geographically widespread and are remarkably consistent across diverse regions (Jennings and Magrath, 2009). The impact of these changes on farmers with small plots and few resources is large. Farming is becoming riskier because of heat stress, lack of water, pests and diseases that interact with ongoing pressures on natural resources. Lack of predictability in the start and length of the growing season affects the ability of farmers to invest in appropriate fertilizer levels or improved, high yielding varieties. These changes occur at the same time as the demand for food is rising and is projected to continue to rise for the next fifty years (IAASTD, 2008). Long-term data records derived from satellite remote sensing can be used to verify these reports, providing necessary analysis and documentation required to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices and land surface phenology and to determine which markets are vulnerable to land surface phenology changes and variability and which market prices are not correlated.

Prices↗

NASA NTRS2017

Integrating Growth Stage Deficit Irrigation into a Process Based Crop Model

Current rates of agricultural water use are unsustainable in many regions, creating an urgent need to identify improved irrigation strategies for water limited areas. Crop models can be used to quantify plant water requirements, predict the impact of water shortages on yield, and calculate water productivity (WP) to link water availability and crop yields for economic analyses. Many simulations of crop growth and development, especially in regional and global assessments, rely on automatic irrigation algorithms to estimate irrigation dates and amounts. However, these algorithms are not well suited for water limited regions because they have simplistic irrigation rules, such as a single soil-moisture based threshold, and assume unlimited water. To address this constraint, a new modeling framework to simulate agricultural production in water limited areas was developed. The framework consists of a new automatic irrigation algorithm for the simulation of growth stage based deficit irrigation under limited seasonal water availability; and optimization of growth stage specific parameters. The new automatic irrigation algorithm was used to simulate maize and soybean in Gainesville, Florida, and first used to evaluate the sensitivity of maize and soybean simulations to irrigation at different growth stages and then to test the hypothesis that water productivity calculated using simplistic irrigation rules underestimates WP. In the first experiment, the effect of irrigating at specific growth stages on yield and irrigation water use efficiency (IWUE) in maize and soybean was evaluated. In the reproductive stages, IWUE tended to be higher than in the vegetative stages (e.g. IWUE was 18% higher than the well watered treatment when irrigating only during R3 in soybean), and when rainfall events were less frequent. In the second experiment, water productivity (WP) was significantly greater with optimized irrigation schedules compared to non-optimized irrigation schedules in water restricted scenarios. For example, the mean WP across 38 years of maize production was 1.1 kg/cu m for non-optimized irrigation schedules with 50 mm of seasonal available water and 2.1 kg/cu m optimized ion schedules, a 91% improvement in WP with optimized irrigation schedules. The framework described in this work could be used to estimate WP for regional to global assessments, as well as derive location specific irrigation guidance.

crop model↗

NASA NTRS2010

Electrically-Active Convection and Tropical Cyclogenesis in the Atlantic and East Pacific

It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves and to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and over various smaller longitude bands by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged IR brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5deg by 2.5deg box covered by IR brightness temperatures less than 210 K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130degW-95degW) were observed in that band to have a flash rate of 56.4 flashes/day, a coverage by brightness temperatures less than 210 K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g/kg, and a 300-hPa omega value of -0.04 Pascals/s in the trough phase compared to the non-developing wave trough values of 22.1 flashes/day, a coverage by brightness temperatures less than 210 K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g/kg, and a 300-hPa omega value of -0.01 Pascals/s.

Leppert, Kenneth D., II↗