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At least 271 records · Page 15

The Global Precipitation Measurement (GPM) Mission's Scientific Achievements and Societal Contributions: Reviewing Four Years of Advanced Rain and Snow Observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth’s atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° x 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Applications↗

Microwave radiometric observations near 19.35, 92 and 183 GHz of precipitation in tropical storm Cora

Observations of rain cells in the remains of a decaying tropical storm were made by Airborne Microwave Radiometers at 19.35,92 and three frequencies near 183 GHz. Extremely low brightness temperatures, as low as 140 K were noted in the 92 and 183 GHz observations. These can be accounted for by the ice often associated with raindrop formation. Further, 183 GHz observations can be interpreted in terms of the height of the ice. The brightness temperatures observed suggest the presence of precipitation sized ice as high as 9 km or more.

Wilheit, T. T.↗

Features of polar cusp electron precipitation associated with a large magnetic storm

Measurements of precipitating electrons made by the OGO-4 satellite reveal several interesting phenomena in the polar cusp. Extremely high fluxes of 0.7 keV electrons were observed in the polar cusp ninety minutes following the sudden commencement of a very large magnetic storm. Structured, fairly high fluxes of 7.3 keV electrons were also observed in the cusp region, accompanied by very strong search coil magnetometer fluctuations, indicative of strong field-aligned currents. The observations confirm previously reported latitudinal shifts in the location of the polar cusp in response to southward interplanetary magnetic fields.

Berko, F. W.↗

Formation of a planet orbiting pulsar 1829 - 10 from the debris of a supernova explosion

How the 10-earth mass planet in a nearly circular 0.7 AU orbit around PSR1829 - 10 might have been created inside the young SNR is described. It is proposed that the planet formed from a rotationally supported disk of about 0.02 solar mass of heavy elements that fell back from the supernova explosion to an initial radius of about 1000 km. Viscous evolution of the disk then concentrated most of its angular momentum into a small amount of material at the disk's outer extremity: 10 earth masses at 10 exp 13 cm. Here, dust grains that had condensed and precipitated toward the midplane grew through cohesive collisions and gravitational instabilities into 100-km planetesimals which coagulated into the planet on a million-yr time scale. The presence of a more massive and more distant second planet is found to be unlikely.

Lin, D. N. C.↗

Comparison of TRMM 2A25 Products Version 6 and Version 7 with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem was addressed in a previous paper by comparison of 2A25 version 6 (V6) product with reference values derived from NOAA/NSSL's ground radar-based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25 version 7 (V7) products that were recently released as a replacement of V6. This new version is considered superior over land areas. Several aspects of the two versions are compared and quantified including rainfall rate distributions, systematic biases, and random errors. All analyses indicate V7 is an improvement over V6.

Kirstetter, Pierre-Emmanuel↗

Climate and air quality impacts due to mitigation of non-methane near-term climate forcers

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry–climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with “weak” (SSP3-7.0) versus “strong” (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2.5) and ozone (O3) decrease by −2.2±0.32 µg m−3 and −4.6±0.88 ppb, respectively (changes quoted here are for the entire 2015–2055 time period; uncertainty represents the 95 % confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.25±0.12 K and 0.03±0.012 mm d−1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0.66±0.20 K and 0.03±0.02 mm d−1), south Asia (0.47±0.16 K and 0.17±0.09 mm d−1), and east Asia (0.46±0.20 K and 0.15±0.06 mm d−1). Relatively large warming and wetting of the Arctic also occur at 0.59±0.36 K and 0.04±0.02 mm d−1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals.

Climate↗

Simulating US Agriculture in a Modern Dust Bowl Drought

Drought-induced agricultural loss is one of the most costly impacts of extreme weather, and without mitigation, climate change is likely to increase the severity and frequency of future droughts. The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses approx.50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by approx.25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

climate change impacts↗

Convective and stratiform components of a Winter Monsoon Cloud Cluster determined from geosynchronous infrared satellite data

The horizontal precipitation structure of cloud clusters observed over the South China Sea during the Winter Monsoon Experiment (WMONEX) is analyzed using a convective-stratiform technique (CST) developed by Adler and Negri (1988). The technique was modified by altering the method for identifying convective cells in the satellite data, accounting for the extremely cold cloud tops characteristic of the WMONEX region, and modifying the threshold infrared temperature for the boundary of the stratiform rain area. The precipitation analysis was extended to the entire history of the cloud cluster by applying the modified CST to IR imagery from geosynchronous-satellite observations. The ship and aircraft data from the later period of the cluster's lifetime make it possible to check the locations of convective and stratiform precipitation identified by the CST using in situ observations. The extended CST is considered to be effective for determining the climatology of the convective-stratiform structure of tropical cloud clusters.

Goldenberg, Stanley B.↗

Creep Properties of NiAl-1Hf Single Crystals Re-Investigated

NiAl-1Hf single crystals have been shown to be quite strong at 1027 C, with strength levels approaching those of advanced Ni-based superalloys. Initial testing, however, indicated that the properties might not be reproducible. Study of the 1027 C creep behavior of four different NiAl-1Hf single-crystal ingots subjected to several different heat treatments indicated that strength lies in a narrow band. Thus, we concluded that the mechanical properties are reproducible. Recent investigations of the intermetallic NiAl have confirmed that minor alloying additions combined with single-crystal growth technology can produce elevated temperature strength levels approaching those of Ni-based superalloys. For example, General Electric alloy AFN 12 {Ni-48.5(at.%) Al-0.5Hf-1Ti-0.05Ga} has a creep rupture strength equivalent to Rene 80 combined with a approximately 30-percent lower density, a fourfold improvement in thermal conductivity, and the ability to form a self-protective alumina scale in aggressive environments. Although the compositions of strong NiAl single crystals are relatively simple, the microstructures are complex and vary with the heat treatment and with small ingot-toingot variations in the alloy chemistry. In addition, initial testing suggested a strong dependence between microstructure and creep strength. If these observations were true, the ability to utilize NiAl single-crystal rotating components in turbine machinery could be severely limited. To investigate the possible limitations in the creep response of high-strength NiAl single crystals, the NASA Glenn Research Center at Lewis Field initiated an in depth investigation of the effect of heat treatment on the microstructure and subsequent 1027 C creep behavior of [001]-oriented NiAl-1Hf with a nominal chemistry of Ni-47.5Al-1Hf-0.5Si. This alloy was selected since four ingots, grown over a number of years and possessing slightly different compositions, were available for study. Specimens taken from the ingots were subjected to several heat treatment schedules, examined by transmission electron microscopy, and tested in both compression and tension. An example of the microstructure found in a [001]-oriented NiAl-1Hf specimen after a solution treatment at 1317 C for 50 hr followed by air cooling is illustrated in the image on the left, where the NiAl matrix contains a uniform distribution of nanometer-scale Gphase (Ni16Hf6Si7) precipitates. Other heat treating schedules produced microstructures with nanometer-sized G-phase cubes and plates or, in an extreme case, produced a microstructure with all the G-phase converted to Heusler (Ni2AlHf) particles. The results of 1027 C creep strength and strain rate testing are illustrated which summarizes data from tensile and compressive testing of samples cut from all four NiAl-1Hf ingots and subjected to a variety of heat treatment schedules. With one exception, all the strength values lie in a narrow band that spans six orders of magnitude in strain rate. The only factor that produced results outside of this band was the heat treatment schedule that dissolved all the G-phase and replaced it with Heusler precipitates. The results portrayed in this figure lead to the important practical conclusion that the elevated-temperature creep properties of NiAl-1Hf single crystals are reproducible and are not affected by small variations in alloy chemistry from ingot to ingot or by different initial distributions of G-phase in the heat-treated alloy. The only variable in this study that produced a significant and delerious effect on mechanical strength was a post-solution heat treatment that lead to the complete disappearance of the G-phase in favor of Heusler precipitates.

Whittenberger, J. Daniel↗

Multispectral remote sensing contribution to land surface evaporation

The global water cycle is perhaps the most important of all the biogeochemical cycles and evaporation, which is a significant component of the water cycle, is also linked with the energy and carbon cycles. Long-term evaporation over large areas has generally been computed as the difference of precipitation and river runoff. Analysis of short-term evaporation rate and its spatial pattern, however, is extremely complex, and multispectral remotely sensed data could aid in such analysis. Multispectral data considered here are visible and near-infrared reflectances, infrared surface temperature and the 37 GHz brightness temperatures. These observations are found to be not totally independent of each other. A few of their relationships are established and discussed considering physically-based models.

Choudhury, B. J.↗

Characteristics of Vertical Profiles of Reflectivity and Doppler Derived From TRMM Field Campaigns

The TRMM Precipitation Radar (PR) measures the vertical profile of reflectivity from which the surface rain rate is estimated after attenuation corrections in the 2A21 algorithm. Characteristics of the vertical reflectivity profile is important for various reasons ranging from scientific to instrument algorithms. It is well known that different types of precipitation such as stratiform or convection, have different heating profiles. The vertical profile of reflectivity can provide information on precipitation classification. The vertical reflectivity structure also provides information on precipitation processes such as growth and aggregation. In terms of TRMM algorithms, an independent estimate of the vertical profiles are also extremely important since the PR returns can be attenuated in the rain layer near the surface. Corrections for attenuation are required in the lowest few kilometers, necessitating some assumptions about the rain size distributions and the reflectivity profile below the lowest measurement unaffected by the surface return. Furthermore, some assumptions about the vertical reflectivity profile are required for Ground Validation (GV) radars, since their lowest scan may be 1 or more kilometers above the surface. Statistics on the vertical reflectivity and Doppler structure are presented from the ER-2 Doppler Radar (EDOP) which participated in several TRMM field campaigns (TEFLUN-A, TEFLUN-B, and LBA) and CAMEX-3. The ER-2 aircraft overflew diverse precipitation types during these campaigns. EDOP is an X-band (9.6 GHz) radar for which returns are less attenuated than at the TRMM PR frequency. The EDOP profiles are first corrected for attenuation using the SRT method. The data from all the ER-2 campaigns are then classified by type (convection, stratiform, and other) and then statistics were performed on the vertical reflectivity and Doppler profiles in the form of CFAD's. These CFADs are compared and discussed. The computed CFAD's indicate significant differences as a function of precipitation type and location (hurricane versus non-hurricane, Brazil versus Florida). The implications of these profiles will be discussed.

Starr, David OC.↗

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Kirstettier, Pierre-Emmanual↗

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Kumar, Sujay↗

Observational and numerical studies of extreme frontal scale contraction

The general objective of this effort is to increase understanding of how frontal scale contraction processes may create and sustain intense mesoscale precipitation along intensifying cold fronts. The five-part project (an expansion of the originally proposed two-part project) employed conventional meteorological data, special mesoscale data, remote sensing measurements, and various numerical models. First an idealized hydrostatic modeling study of the scale contraction effects of differential cloud cover on low-level frontal structure and dynamics was completed and published in a peer-reviewed journal. The second objective was to complete and publish the results from a three dimensional numerical model simulation of a cold front in which differential sensible heating related to cloud coverage patterns was apparently crucial in the formation of a severe frontal squall line. The third objective was to use a nonhydrostatic model to examine the nonlinear interactions between the transverse circulation arising from inhomogeneous cloud cover, the adiabatic frontal circulation related to semi-geostrophic forcing, and diabatic effects related to precipitation processes, in the development of a density current-like microstructure at the leading edge of cold fronts. Although the development of a frontal model that could be used to initialize such a primitive equation model was begun, we decided to focus our efforts instead on a project that could be successfully completed in this short time, due to the lack of prospects for continued NASA funding beyond this first year (our proposal was not accepted for future funding). Thus, a fourth task was added, which was to use the nonhydrostatic model to test tentative hypotheses developed from the most detailed observations ever obtained on a density current (primarily sodar and wind profiler data). These simulations were successfully completed, the findings were reported at a scientific conference, and the results have recently been submitted to a peer-reviewed journal. The fifth objective was to complete the analysis of data collected during the Cooperative Oklahoma Profiler Studies (COPS-91) field project, which was supported by NASA. The analysis of the mesoscale surface and sounding data, Doppler radar imagery, and other remote sensing data from multi frequency wind profiler, microwave radiometer, and the Radio Acoustic Sounding System has been completed. This study is a unique investigation of processes that caused the contraction of a cold front to a microscale zone exhibiting an undular bore-like structure. Results were reported at a scientific conference and are being prepared for publication. In summary, considerable progress has been achieved under NASA funding in furthering our understanding of frontal scale contraction and density current - gravity wave interaction processes, and in utilizing models and remotely sensed data in such studies.

Koch, Steven E.↗

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling test bed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger toward the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g., reanalysis products) in the context of their integrated impacts on the process chain connecting the land surface to the PBL and in support of hydrological anomalies.

southern plains↗

Relationship between Mean Winds and Large 10-day Precipitation Anomalies over the Continental U.S.

To better understand the role of surface boundary forcing upon interannual and decadal variability of droughts and precipitation excesses over the continental U. S., an observational study has been carried out to better investigate the dynamical linkages between surface boundary forcing and droughts/floods. This study examines the relationship during the warm season between observed mean wind patterns on the 10-15 day time scale and anomalies in precipitation on that same time scale over the U. S. Each of the 7 cases of significant 10-day, warm-season drought over the U, S. since 1948 that has been investigated was accompanied by significant continental-scale ridging of the mean 10-day 250 mb wind pattern over the continental U.S. and a mid-Pacific relative maximum of 250 mb wind speed of at least 30 m/sec within 20 degrees of the international Date Line. This perhaps suggests the presence of a wave-guide phenomenon over the Pacific. The drought signal for each of these cases was still quite evident when averaged over the monthly time scale. While peak magnitudes of the precipitation anomalies were much larger for the 7 chosen cases of significant of precipitation excess were than for the drought cases none of the patterns of precipitation excess were as unambiguous or wide-spread as the drought cases. In only 2 to 3 cases was there evidence of a continental trough in the 250 mb winds. In fact, one case showed slight ridging over Canada and the extreme northern U.S. Strong southerly low-level jets, however, were evident in the 925 mb winds over south-central Texas or the nearby Gulf of Mexico in virtually all of the excessive precipitation cases, while the Great Plains LLJ was weak or displaced to the north of Texas in most of the drought cases. We will further investigate the asymmetry between droughts and precipitation excesses in their horizontal homogeneity and extent, in their temporal evolution, and in how the are forced by the combined effects of the mean 250 mb westerlies and the mean 925 mb southerly winds.

Helfand, H. Mark↗

Rainfall Field Reconstruction by Opportunistic Use of the Rain- Induced Attenuation on Microwave Satellite Signals: The July 2021 Extreme Rain Event in Germany as a Case Study

This paper presents a practical application of an opportunistic technique for the estimation of rainfall intensity and accumulated precipitation. The proposed technique is based upon signal strength measurements made by commercial-grade interactive satellite terminals. By applying some processing, the rain-induced attenuation on the microwave downlink from the satellite is first evaluated; then the rain attenuation is eventually mapped into a rainfall rate estimate via a tropospheric model. This methodology has been applied to a test area of 30 × 30 km 2 around the city of Dortmund (North Rhine-Westphalia, upper basin of Ermscher river), for the heavy rain event that devastated western Germany in July, 2021. A rainfall map on this area is obtained from the measurements collected by a set of satellite terminals deployed in the region, and successfully compared with a map obtained with a conventional weather radar.

Rainfall rate estimation↗