nasa-gesdisc/es-publications-researchareas huggingface dataset:
Characteristics of Extremely High PM 2.5 Episode and Emergency Reduction Measures Plan in Southeastern Region (2021)

This study analyzed the characteristics of high PM2.5 episodes that meets the concentration criteria of Emergency Reduction Measures Plan (ERMP) in Busan during the 2015-2020, and compared with those in Seoul. As a first step, the CAPSS-2017 emission data was employed to analyze the emission differences between Busan and Seoul, and pointed out that Busan emission included the dominance of ship emissions (37.7%) among total PM2.5 city emissions, whereas fugitive PM2,5 emission was the highest in Seoul. These emission characteristics are indicating that the controlling action plan should be uniquely applied to cope with ERMP in each region. We selected extremely high PM2.5 episode days that meet the criteria of ERMP levels. In Busan, Ulsan, and Gyeongnam region, 15, 16, and 8 days of extremely high PM2.5 cases were found, respectively, whereas Seoul showed approximately doubling of occurrences with 37 cases. However, the occurrences in summer season indicated big differences between two cities: the proportion of summer-season occurrence was 13-25% in Busan, whereas no single case have occurred in Seoul. This is suggesting the needs of comprehensive summer emission reduction plan with focusing on sulfur reduction to effectively cope with the ERMP levels in summer in the southeastern region, including Busan.

Research areas: Air Quality
Soil Erosion Estimation of Palasbari in Northeast India by RUSLE Model (2021)

Soil erosion is a serious problem and its estimation at a large scale is an urgent need. This study aims to estimate the annual soil loss in Palasbari town (639 km2) applying the Revised Universal Soil Loss Equation (RUSLE) model on a GIS platform. The study area comprising Palasbari town is located in the state of Assam in Northeast India. The annual soil loss rate varies from 0 to 3779t ha-1 yr-1 and the mean annual rate of soil loss is 42 t ha-1 yr-1. The soil loss values are categorised into four classes of severity i.e. slight, moderate, severe and extreme soil erosion. Based on spatial analysis, it is found that areas with high slope length and steep slope with heavy and high intensity precipitation are more prone to soil erosion. It is concluded that steep slopes, frequent flooding, sandy soil, destruction of vegetation cover are the main causes of soil erosion in the study area.

Research areas: Land Surface/Agriculture Indicators
Effect Of SARS-CoV-2 Pandemic Induced Lockdown On The Aerosol Loading Over The Coastal State, Goa (2021)

The SARS-CoV-2 pandemic resulted in India imposing a nationwide lockdown on 22 March 2020, bringing all human activities to a complete halt. The
current study focuses on the effect of lockdown on the
abundance of atmospheric aerosols over Goa. The
study focused on pre-lockdown, lockdown and period
corresponding to lockdown in 2019. The AOD spectra
depicted a decrease in the anthropogenically derived
fine mode aerosols during the lockdown compared to
the pre-lockdown period. Mean AOD500 for prelockdown and lockdown periods were 0.43  0.19 and
0.53  0.11 respectively. The higher AOD500 during
lockdown was due to an increase in naturally derived
coarse mode aerosols, which is further confirmed with
the lower Angstrom exponent values (1.04  0.11).
The mean black carbon mass concentration for the
respective periods were 1990.45  470.87 ng m3 and
1109.71  218.33 ng m3, and the mean atmospheric
forcing during the respective periods were 25.13 
5.72 W m2, 27.31  3.71 W m2 and 30.81  5.59 W m2
respectively.

Research areas: Air Quality, Environmental Impacts
Dynamics of Amphan Cyclone and associated changes in ocean, land meteorological and atmospheric parameters (2021)

The low-pressure system developed in the Bay of Bengal and the Andaman Sea during March-October, often forms tropical cyclones, depending upon the intensity widespread destruction occurs in the areas where landfall takes place along the Indian coastal region. On 20 May, 2020, tropical cyclone Amphan hit the Indian coast at Bakkhali, West Bengal, in the afternoon (1330 IST). On 19 May, 2020, the intensity strengthened into a super cyclonic storm, with a strong wind speed up to 220 km/h. This cyclone affected a large population of India and Bangladesh. More than twenty-two thousand houses were damaged and millions of people were shifted to a safe place and due to the spread of COVID-19, the rescue missions were quite challenging. The cyclone affected most of the eastern states of India, heavy rainfall occurred causing floods along the track of cyclones. Using multi-satellite, ground and Argo floats data, we have analyzed meteorological and atmospheric parameters during May 2020. Our detailed analysis shows pronounced changes in atmospheric (CO mole fraction, total ozone column) and ocean parameters (chlorophyll concentration, dissolved oxygen, salinity, sea surface and sub-surface temperature) before and after the cyclone. Changes in ocean parameters such as caused by the cyclone Amphan along its track and the atmospheric and meteorological parameters change as the cyclone moves over the land.

Research areas: Severe Storms
Validation of Global Solar Radiation Models on a Horizontal Surface in the Climatic Zones of Burkina (2022)

The evaluation of the solar deposit is essential for the sizing of photovoltaic systems. This requires the availability of radiation data. In Burkina Faso, weather data doesnt cover all the country. That makes that solar radiation measured are not available for the all country. Theorical methods can help about it. This paper is written to fill the gap of adapted solar models for the country. In this work, an analysis of the results provided by four models for the estimation of hourly values of global radiation on a horizontal plane was made. The radiation data for the year 2017 comes from the Burkina weather forecast. The validation of the models is carried out by a comparison between the radiation measured and that given by the various models provided by MATLAB code. The different models have been validated by several statistical indicators (RMSE and normalized MAE) and graphs for a clear sky. Scoring criteria have been established to assess the relative quality of each model. The models retained for the study are the Bird and Hulstrom model, the Davy and Hay model, the Capderou model and the Liu and Jordan model. Three sites were affected: Ouagadougou, Dori and Gaoua. We found that for some models, there is a good agreement between the measured values and those estimated by some models for the Dori site, while they are not with the values measured for the Ouagadougou and Gaoua sites. In the town of Dori, the most appropriate model for estimating solar radiation is that of Bird and Hulstrom. For the cities of Ouagadougou and Gaoua, the different models are not suitable.

Research areas: Sun-Earth Interactions
Assessment of Cloud Cover Characteristics in Satellite Datasets and Reanalysis Products for Greenland (2008)

Clouds have an important controlling influence on the radiation balance, and hence surface melting, over the Greenland ice sheet and need to be classified to derive reliable albedo estimates from visible imagery. Little is known, however, about the true cloud cover characteristics for the largest island on Earth, Greenland. Here, an attempt is made to address this knowledge gap by examining cloud characteristics, as determined by three complementary satellites sensors: the Advanced Very High Resolution Radiometer (AVHRR), the Along Track Scanning Radiometer-2 (ATSR-2), and the Moderate Resolution Imaging Spectroradiometer (MODIS). The first provides a multidecadal time series of clouds, albedo, and surface temperature, and is available, in the form of the extended AVHRR Polar Pathfinder dataset (APP-x), as a homogeneous, consistent dataset from 1982 until 2004. APP-x data, however, are also the most challenging to cloud classify over snow-covered terrain, due to the limited spectral capabilities of the instrument. ATSR-2 permits identification and classification using stereophotogrammetric techniques and MODIS has enhanced spectral sampling in the visible and thermal infrared but over more limited time periods. The spatial cloud fractions from the three sensors are compared and show good agreement in terms of both magnitude and spatial pattern. The cloud fractions, and inferred patterns of accumulation, are then assessed from three commonly used reanalysis datasets: NCEPNCAR, the second NCEPDepartment of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP-II), and the 40-yr ECMWF Re-Analysis (ERA-40). Poor agreement between the reanalysis datasets is found. NCEPDOE AMIP-II produces a cloud fraction similar to that observed by the satellites. NCEPNCAR and ERA-40, however, bear little similarity to the cloud fractions derived from the satellite observations. This suggests that they may produce poor accumulation estimates over the ice sheet and poor estimates of radiation balance. Using these reanalysis data to force a mass balance model of the ice sheet, without appropriate downscaling and correction for the substantial biases present, may, therefore, produce substantial errors in surface melt rate estimates.

Research areas: Atmospheric/Ocean Indicators, Cryospheric Indicators
Combining wavelets and linear spectral mixture model for MODIS satellite sensor time-series analysis (2008)

This work presents a methodology that uses digital fraction images derived from Linear Spectral Mixture Model and wavelets transform from MODIS satellite sensor time-series for land cover change analysis. Our approach uses MODIS surface reflectance images acquired from 2000 to 2006 time period. For this study, a test site was selected in the Mato Grosso State, Brazilian Amazonia. This site has shown high deforestation rates in the last years. The samples of land cover classes were collected during four field campaigns (2003, 2004, 2005 and 2006) to be used as ground truth. The linear spectral mixture model was applied to the MODIS surface reflectance images of red surface reflectance band (620-670 nm bandwidth), near infrared surface reflectance band (NIR, 841-876 nm bandwidth) and medium infrared surface reflectance band (MIR, 2105-2155 nm bandwidth). This model generated the vegetation, shade, and soil fraction images. In the next step, the Meyer orthogonal Discrete Wavelets Transform was used for filtering the time-series of MODIS fraction images. The filtered signal was reconstructed excluding high frequencies for each pixel in the fraction images (soil, vegetation, and shade) of the time-series. This computational procedure allows to observe the original signal without clouds and other noises. The results show that wavelets transform can provide a gain in multitemporal analysis and visualization on inter-annual fraction images variability patterns.

Research areas: Land Surface/Agriculture Indicators
Lobster (Panulirus argus) captures and their relation with environmental variables obtained by orbital sensors for Cuban waters (1997-2005) (2008)

Chlorophyll concentrations (Chl a) data obtained from the Sea Viewing Wide Field of View Sensor (SeaWIFS) ocean color monthly images, Sea Surface Temperature (SST) pathfinder data obtained from the Advanced Very High Resolution Radiometer (AVHRR) sensors, and lobster (Panulirus argus) captures at the Cuban shelf were examined in order to analyze their spatial and temporal variability. A cross-correlation analysis was made between the standardized anomalies of the environmental variables (Chl a and SST) and the standardized anomalies of lobster captures for each fishery zones for the period between 1997 and 2005. For the deep waters adjacent to the fishing zones it was not observed a clear Chl a seasonality and on average the lowest values occurred south of the Island. It is with the three years lag that Chl a had the greatest numbers of significant correlation coefficients for almost all fishing zones. However, the cross-correlation coefficients with SST showed higher values with 1,5 year lag at all zones. Since the two environmental variables obtained by satellite sensors (SST and Chl a) influence the lobsters mainly during the planktonic life cycle, the cross-correlation with lobster captures begin to show significant indexes with lags of 1.5 years or more.

Research areas: Agriculture, Ecosystems
Study of the spatio-temporal dynamics of the Pantanal biome using MODIS images (2008)

The objective of this work was to evaluate multitemporal data, obtained by moderate resolution imaging spectroradiometer (MODIS) sensor, for the study of spatial-temporal dynamics in two subregions of the Pantanal biome. One hundred and thirty nine enhanced vegetation index (EVI) images, from MOD13 vegetation index product, altimetry data from shuttle radar topography mission (SRTM) and tropical rainfall measuring mission (TRMM) precipitation data were used. In order to reduce data dimensionality, MODIS EVI images were sampled based on contour lines spacing of 10 m. The autocorrelation and cluster analysis were used for spatial and temporal evaluation of the samples; and the principal components analysis was applied to all dataset for spatial and temporal analysis. Results showed a spatial and temporal dependence between spectral response and precipitation. The cluster analysis indicated two spatial groups, suggesting the need for the analysis of the entire study area. The principal components analysis allowed to distinguish four behaviors: the areas permanently flooded; nonflooded areas composed by vegetation; flooded areas with higher spectral vegetation response; and riparian vegetation areas.

Research areas: Ecosystems
Dynamics and Predictability of a Heavy Dry-Season Precipitation Event over West AfricaSensitivity Experiments with a Global Model (2009)

In January 2002 the Cape Verde region in tropical West Africa was hit by an exceptionally heavy precipitation event. Rain rates of up to 116 mm (48 h)1 caused harmful impacts on the local population. The rainfall was triggered by a series of two upper-level disturbances penetrating from the extratropics to the West African coast. This study investigates the dynamics and predictability of this event on the basis of simulations with the global model Global Model Europe (GME) of the German Weather Service [i.e., Deutscher Wetterdienst (DWD)] initialized by the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data. Free forecasts satisfactorily reproduce the upper-level disturbances and the precipitation up to a lead time of 7 days. Several sensitivity experiments are conducted to unveil the reasons for this comparably high predictability and to identify dynamical precursors. The relevance of the upper-level wave structure in the extratropics is examined by modifications of the initial conditions using a quasigeostrophic potential vorticity (PV) inversion technique. While a reservoir of high PV over the North Atlantic and a PV ridge over Europe are found to be crucial for the upper-level wave amplification and the rainfall over West Africa, latent heating over the North Atlantic affects the event rather little in contrast to previous case studies. Surface properties like orography and sea surface temperature anomalies modify the precipitation quantity, but appear not to be essential for the occurrence of the extreme event on the simulated time scale.

Research areas: Atmospheric/Ocean Indicators
Numerical Simulations of the Impacts of the Saharan Air Layer on Atlantic Tropical Cyclone Development (2009)

In this study, the role of the Saharan air layer (SAL) is investigated in the development and intensification of tropical cyclones (TCs) via modifying environmental stability and moisture, using multisensor satellite data, long-term TC track and intensity records, dust data, and numerical simulations with a state-of-the-art Weather Research and Forecasting model (WRF). The long-term relationship between dust and Atlantic TC activity shows that dust aerosols are negatively associated with hurricane activity in the Atlantic basin, especially with the major hurricanes in the western Atlantic region. Numerical simulations with the WRF for specific cases during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) experiment show that, when vertical temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS) were assimilated into the model, detailed features of the warm and dry SAL, including the entrainment of dry air wrapping around the developing vortex, are well simulated. Active tropical disturbances are found along the southern edge of the SAL. The simulations show an example where the dry and warm air of the SAL intruded into the core of a developing cyclone, suppressing convection and causing a spin down of the vortical circulation. The cyclone eventually weakened.

To separate the contributions from the warm temperature and dry air associated with the SAL, two additional simulations were performed, one assimilating only AIRS temperature information (AIRST) and one assimilating only AIRS humidity information (AIRSH) while keeping all other conditions the same. The AIRST experiments show almost the same simulations as the full AIRS assimilation experiments, whereas the AIRSH is close to the non-AIRS simulation. This is likely due to the thermal structure of the SAL leading to low-level temperature inversion and increased stability and vertical wind shear. These analyses suggest that dry air entrainment and the enhanced vertical wind shear may play the direct roles in leading to the TC suppression. On the other hand, the warm SAL temperature may play the indirect effects by enhancing vertical wind shear; increasing evaporative cooling; and initiating mesoscale downdrafts, which bring dry air from the upper troposphere to the lower levels.

Research areas: Severe Storms, Atmospheric/Ocean Indicators
Prediction of Dry-Season Precipitation in Tropical West Africa and Its Relation to Forcing from the Extratropics (2009)

Precipitation during the boreal winter dry season in tropical West Africa is rare but occasionally results in significant impacts on the local population. The dynamics and predictability of this phenomenon have been studied very little. Here, a statistical evaluation of the climatology, dynamics, and predictions of dry-season wet events is presented for the region 7.515N, 10W10E. The analysis is based upon Global Precipitation Climatology Project (GPCP) merged satellitegauge pentad rainfall estimates and 5-day 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) precipitation forecasts, and covers the 23 dry seasons (NovemberFebruary) during 1979/802001/02. Wet events are defined as pentads with an area-averaged precipitation anomaly of more than +200% with respect to the mean seasonal cycle. Composites of the 43 identified events indicate an association with a trough over northwestern Africa, a tropical plume on its eastern side, unusual precipitation at the northern and western fringes of the Sahara, and reduced surface pressure over the Sahara, which allows an inflow of moist southerlies from the Gulf of Guinea to feed the unusual dry-season rainfalls. The results give evidence for a preconditioning by another disturbance about 1 week prior to the precipitation event. The ERA-40 forecasts show a high temporal correlation with observations, a general wet bias, but a somewhat too low number of wet events. With 53% of all identified events correctly forecasted and only 32% of forecasted events not verified, the model shows moderate skill in contrast to the prediction of many other tropical precipitation systems. A separate consideration of hits, misses, and false alarms corroborates the previously proposed hypothesis that a strong extratropical influence enhances the quality of predictions in this region. The results should encourage weather services in West Africa to take advantage of available dry-season precipitation forecasts in terms of the dissemination of early warnings.

Research areas: Validation
A Lagrangian Climatology of Tropical Moisture Exports to the Northern Hemispheric Extratropics (2010)

Case studies have shown that heavy precipitation events and rapid cyclogenesis in the extratropics can be fueled by moist and warm tropical air masses. Often the tropical moisture export (TME) occurs through a longitudinally confined region in the subtropics. Here a comprehensive climatological analysis of TME is constructed on the basis of seven-day forward trajectories started daily from the tropical lower troposphere using 6-hourly 40-yr ECMWF Re-Analysis (ERA-40) data from the 23-year period 19792001. The objective TME identification procedure retains only those trajectories that reach a water vapor flux of at least 100 g kg1 m s1 somewhere north of 35N. The results show four distinct activity maxima with different seasonal behavior: (i) The pineapple express, which connects tropical moisture sources near Hawaii with precipitation near the North American west coast, has a marked activity maximum in boreal winter. (ii) TME over the west Pacific is largest in summer, partly related to the East Asian monsoon and the mei-yubaiu front. This region alone is responsible for a large portion of TME across 35N. (iii) The narrow activity maximum over the Great Plains of North America is rooted over the Gulf of Mexico and the Caribbean Sea and has a clear maximum in summer and spring. (iv) TME over the western North Atlantic shows the smallest annual cycle with a maximum in winter and autumn. The interannual variability of (i) and (iv) is significantly modulated by El Nino. Over the AfricanEuropeanAsian region, high orographic barriers impede TME. A typical TME trajectory evolution is poleward and quasi-horizontal in the subtropics and then more eastward and upward in the southern midlatitudes, where TME contributes up to 60% to climatological precipitation. The TME dataset presented here can serve as a basis for future studies on extreme events.

Research areas: Atmospheric/Ocean Indicators