scholarly journals Added-value of GEO-hyperspectral Infrared Radiances for Local Severe Storm Forecasts Using the Hybrid OSSE Method

2021 ◽  
Author(s):  
Pei Wang ◽  
Zhenglong Li ◽  
Jun Li ◽  
Timothy J. Schmit
Keyword(s):  
Spectral Resolution ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Added Value ◽  
High Spectral Resolution ◽  
Vertical Resolution ◽  
Severe Storm ◽  
Impact Studies ◽  
High Vertical Resolution ◽  
The Impact

AbstractHigh spectral resolution (or hyperspectral) infrared (IR) sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction (NWP) models. In contrast, imagers on geostationary (GEO) satellites provide high temporal and spatial resolution which are important for monitoring the moisture associated with severe weather systems, such as rapidly developing local severe storms (LSS). A hyperspectral IR sounder onboard a geostationary satellite would provide four-dimensional atmospheric temperature, moisture, and wind profiles that have both high vertical resolution and high temporal/spatial resolutions. In this work, the added-value from a GEO-hyperspectral IR sounder is studied and discussed using a hybrid Observing System Simulation Experiment (OSSE) method. A hybrid OSSE is distinctively different from the traditional OSSE in that, (a) only future sensors are simulated from the nature run and (b) the forecasts can be evaluated using real observations. This avoids simulating the complicated observation characteristics of the current systems (but not the new proposed system) and allows the impact to be assessed against real observations. The Cross-track Infrared Sounder (CrIS) full spectral resolution (FSR) is assumed to be onboard a GEO for the impact studies, and the GEO CrIS radiances are simulated from the ECMWF Reanalysis v5 (ERA5) with the hyperspectral IR all-sky radiative transfer model (HIRTM). The simulated GEO CrIS radiances are validated and the hybrid OSSE system is verified before the impact assessment. Two LSS cases from 2018 and 2019 are selected to evaluate the value-added impacts from the GEO CrIS-FSR data. The impact studies show improved atmospheric temperature, moisture, and precipitation forecasts, along with some improvements in the wind forecasts. An added-value, consisting of an overall 5% Root Mean Square Error (RMSE) reduction, was found when a GEO CrIS-FSR is used in replacement of LEO ones indicating the potential for applications of data from a GEO hyperspectral IR sounder to improve local severe storm forecasts.

scholarly journals The Impact of Vertical Resolution on Fog Forecasting in the Kilometric-Scale Model AROME: A Case Study and Statistics

2016 ◽  
Vol 31 (5) ◽  
pp. 1655-1671 ◽  
Author(s):  
A. Philip ◽  
T. Bergot ◽  
Y. Bouteloup ◽  
F. Bouyssel
Keyword(s):  
Weather Prediction ◽  
Winter Season ◽  
Scale Model ◽  
Strong Impact ◽  
Vertical Resolution ◽  
Radiation Fog ◽  
Fog Forecasting ◽  
High Vertical Resolution ◽  
The Impact

Abstract The impact of vertical resolution on numerical fog forecasting is studied in detail for a specific case and evaluated statistically over a winter season. Three vertical resolutions are tested with the kilometric-scale Applications of Research to Operations at Mesoscale (AROME) numerical weather prediction model over Paris Charles de Gaulle Airport (Paris-CDG) in Paris, France. For the case studied, the vertical resolution has a strong impact on fog onset. The nocturnal jet and the turbulence created by wind shear at the top of the nocturnal boundary layer are more pronounced with a finer vertical resolution, and the turbulence close to the ground is also stronger with high vertical resolution. Local circulations created by the terrain induce different simulated processes during the fog onset. The fog is simulated as advection–radiation fog in the finer vertical resolution run and as radiation fog in the others. The vertical resolution has little impact on the mature and dissipation phases. A statistical study over a winter season confirms the results obtained in the fog case study. High vertical resolution simulates earlier onset, as well as longer-lasting and more spatially heterogeneous fogs. The high vertical resolution configuration simulates more fog events than are found at low resolution (LR); these fog events generally form north of Paris-CDG. No observations are available in this area, leading to many simulated but no observed fog events in the fine-resolution runs. The ceiling of low clouds is not well simulated by the numerical model no matter what vertical resolution is used.

High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit

2009 ◽  
Vol 26 (11) ◽  
pp. 2273-2292 ◽  
Author(s):  
Timothy J. Schmit ◽  
Jun Li ◽  
Steven A. Ackerman ◽  
James J. Gurka
Keyword(s):  
Temporal Resolution ◽  
Spectral Resolution ◽  
Weather Prediction ◽  
Trace Gases ◽  
Geostationary Orbit ◽  
Resolving Power ◽  
High Spectral Resolution ◽  
High Temporal Resolution ◽  
Vertical Resolution ◽  
Infrared Measurements

Abstract The first of the next-generation series of the Geostationary Operational Environmental Satellite (GOES-R) is scheduled for launch in 2015. The new series of GOES will not have an infrared (IR) sounder dedicated to acquiring high-vertical-resolution atmospheric temperature and humidity profiles. High-spectral-resolution sensors have a much greater vertical-resolving power of temperature, moisture, and trace gases than low-spectral-resolution sensors. Because of coarse vertical resolution and limited accuracy in the legacy sounding products from the current GOES sounders, placing a high-spectral-resolution IR sounder with high temporal resolution in the geostationary orbit can provide nearly time-continuous three-dimensional moisture and wind profiles. This would allow substantial improvements in monitoring the mesoscale environment for severe weather forecasting and other applications. Application areas include nowcasting (and short-term forecasts) and numerical weather prediction, which require products such as atmospheric moisture and temperature profiles as well as derived parameters, clear-sky radiances, vertical profiles of atmospheric motion vectors, sea surface temperature, cloud-top properties, and surface properties. Other application areas include trace gases/air quality, dust detection and characterization, climate, and calibration. This paper provides new analysis that further documents the available information regarding the anticipated improvements and their benefits.

Climate change impacts on viticulture in Italy

2021 ◽  
Author(s):  
Laura Massano ◽  
Giorgia Fosser ◽  
Marco Gaetani
Keyword(s):  
Climate Change ◽  
Horizontal Resolution ◽  
Wine Industry ◽  
Added Value ◽  
Extreme Weather Events ◽  
Wine Production ◽  
Bioclimatic Indices ◽  
Impact Of Climate Change ◽  
Impact Studies ◽  
The Impact

<p>In Italy the wine industry is an economic asset representing the 8% of the annual turnover of the Food & Beverage sector, according to Unicredit Industry Book 2019. Viticulture is strongly influenced by weather and climate, and winegrowers in Europe have already experienced the impact of climate change in terms of more frequent drought periods, warmer and longer growing seasons and an increased frequency of weather extremes. These changes impact on both yield production and wine quality.</p><p>Our study aims to understand the impact of climate change on wine production, to estimate the risks associated with climate factors and to suggest appropriate adaptation measurement. The weather variables that most influence grape growth are: temperature, precipitation and evapotranspiration. Starting for these variables we calculate a range of bioclimatic indices, selected following the International Organisation of Vine and Wine Guidelines (OIV), and correlate these with wine productivity data. According to the values of different indices it is possible to determine the more suitable areas for wine production, where we expect higher productivity, although the climate is not the only factor influencing yield.</p><p>Using the convection-permitting models (CPMs – 2.2 horizontal resolution) we investigate how the bioclimatic indices changed in the last 20 years, and the impact of this change on grapes productivity. We look at possible climate trends and at the variation in the frequency distribution of extreme weather events. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of surface and orography field, explicitly resolve deep convection and show an improved representation of extremes events. In our study, we compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to evaluate the possible added value of high resolution models for impact studies. To compare models' output to observation the same analysis it carried out using E-OBS dataset.</p><p>Through our impact study, we aim to provide a tool that winegrower and stakeholders involved in the wine business can use to make their activities more sustainable and more resilient to climate change.</p>

scholarly journals Impacts of Assimilating ATMS Radiances on Heavy Rainfall Forecast in RMAPS-ST

2020 ◽  
Vol 12 (7) ◽  
pp. 1147
Author(s):  
Yanhui Xie ◽  
Min Chen ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Jing He ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Added Value ◽  
Rainfall Forecast ◽  
Hourly Rainfall ◽  
Radiance Data ◽  
The Impact

The Advanced Technology Microwave Sounder (ATMS) mounted on the Suomi National Polar-Orbiting Partnership (NPP) satellite can provide both temperature and humidity information for a weather prediction model. Based on the rapid-refresh multi-scale analysis and prediction system—short-term (RMAPS-ST), we investigated the impact of ATMS radiance data assimilation on strong rainfall forecasts. Two groups of experiments were conducted to forecast heavy precipitation over North China between 18 July and 20 July 2016. The initial conditions and forecast results from the two groups of experiments have been compared and evaluated against observations. In comparison with the first group of experiments that only assimilated conventional observations, some added value can be obtained for the initial conditions of temperature, humidity, and wind fields after assimilating ATMS radiance observations in the system. For the forecast results with the assimilation of ATMS radiances, the score skills of quantitative forecast rainfall have been improved when verified against the observed rainfall. The Heidke skill score (HSS) skills of 6-h accumulated precipitation in the 24-h forecasts were overall increased, more prominently so for the heavy rainfall above 25 mm in the 0–6 h of forecasts. Assimilating ATMS radiance data reduced the false alarm ratio of quantitative precipitation forecasting in the 0–12 h of the forecast range and thus improved the threat scores for the heavy rainfall storm. Furthermore, the assimilation of ATMS radiances improved the spatial distribution of hourly rainfall forecast with observations compared with that of the first group of experiments, and the mean absolute error was reduced in the 10-h lead time of forecasts. The inclusion of ATMS radiances provided more information for the vertical structure of features in the temperature and moisture profiles, which had an indirect positive impact on the forecasts of the heavy rainfall in the RMAPS-ST system. However, the deviation in the location of the heavy rainfall center requires future work.

Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements

2011 ◽  
Vol 50 (6) ◽  
pp. 1225-1235 ◽  
Author(s):  
Zhigang Yao ◽  
Jun Li ◽  
Jinlong Li ◽  
Hong Zhang
Keyword(s):  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Retrieval Algorithm ◽  
Surface Emissivity ◽  
Angle Dependence ◽  
Infrared Radiance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

scholarly journals The NPOESS Airborne Sounding Testbed Interferometer—Remotely Sensed Surface and Atmospheric Conditions during CLAMS

2005 ◽  
Vol 62 (4) ◽  
pp. 1118-1134 ◽  
Author(s):  
W. L. Smith ◽  
D. K. Zhou ◽  
A. M. Larar ◽  
S. A. Mango ◽  
H. B. Howell ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Three Dimensional ◽  
Atmospheric Temperature ◽  
Satellite System ◽  
High Spectral Resolution ◽  
Aircraft Measurements ◽  
Atmospheric Conditions ◽  
Infrared Radiance ◽  
Cross Track ◽  
Temperature Water

Abstract During the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS), the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I), flying aboard the high-altitude Proteus aircraft, observed the spatial distribution of infrared radiance across the 650–2700 cm−1 (3.7–15.4 μm) spectral region with a spectral resolution of 0.25 cm−1. NAST-I scans cross track with a moderate spatial resolution (a linear ground resolution equal to 13% of the aircraft altitude at nadir). The broad spectral coverage and high spectral resolution of this instrument provides abundant information about the surface and three-dimensional state of the atmosphere. In this paper, the NAST-I measurements and geophysical product retrieval methodology employed for CLAMS are described. Example results of surface properties and atmospheric temperature, water vapor, ozone, and carbon monoxide distributions are provided. The CLAMS NAST-I geophysical dataset is available for use by the scientific community.

scholarly journals A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder

2018 ◽  
Vol 11 (2) ◽  
pp. 803-818 ◽  
Author(s):  
Javier Andrey-Andrés ◽  
Nadia Fourrié ◽  
Vincent Guidard ◽  
Raymond Armante ◽  
Pascal Brunel ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Weather Prediction ◽  
Simulated Data ◽  
The Public ◽  
Impact Studies ◽  
New Instrument ◽  
Atmospheric Sounding ◽  
Common Framework ◽  
New Generation ◽  
The Impact

Abstract. The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in numerical weather prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASI-NG simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals throughout the atmosphere, with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity.

scholarly journals The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

2011 ◽  
Vol 11 (3) ◽  
pp. 9705-9742
Author(s):  
A. M. Aghedo ◽  
K. W. Bowman ◽  
D. T. Shindell ◽  
G. Faluvegi
Keyword(s):  
Climate Change ◽  
Boundary Layer ◽  
Carbon Monoxide ◽  
Water Vapour ◽  
Climate Models ◽  
Atmospheric Temperature ◽  
Satellite Observations ◽  
Vertical Resolution ◽  
Upper Troposphere ◽  
The Impact

Abstract. Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC) assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the observations from the Tropospheric Emission Spectrometer (TES) satellite from January 2005 to December 2008. The results show that sampling and monthly averaging of the observation operators produce biases of less than ±3% for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling biases were also within the insignificant range of ±3% (that is ±0.14 g kg−1) in both models. Sampling led to a temperature bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to −1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8% bias was calculated in the upper troposphere water vapour due to monthly-mean operators, which may impact the detection of water vapour feedback in response to global warming. Our results reveal the importance of using the averaging kernel and the a priori profiles to account for the limited vertical resolution of a nadir observation during model application. Neglecting the observation operators resulted in large biases, which are more than 60% for ozone, ±30% for carbon monoxide, and range between −1.5 K and 5 K for atmospheric temperature, and between −60% and 100% for water vapour.

scholarly journals A simulated observation database to assess the impact of IASI-NG hyperspectral infrared sounder

2017 ◽  
Author(s):  
Javier Andrey-Andrés ◽  
Nadia Fourrié ◽  
Vincent Guidard ◽  
Raymond Armante ◽  
Pascal Brunel ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Weather Prediction ◽  
Simulated Data ◽  
The Public ◽  
Impact Studies ◽  
New Instrument ◽  
Atmospheric Sounding ◽  
Common Framework ◽  
New Generation ◽  
The Impact

Abstract. The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in Numerical Weather Prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASI-NG simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals along all the atmosphere with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity.

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