Assessment of soil trafficability across the agricultural region of the Canadian Prairies with the gridded climate data set

Abstract. We present hourly climate data to force land surface process models and assessments over the Merced and Tuolumne watersheds in the Sierra Nevada, California, for the water year 2010–2014 period. Climate data (38 stations) include temperature and humidity (23), precipitation (13), solar radiation (8), and wind speed and direction (8), spanning an elevation range of 333 to 2987 m. Each data set contains raw data as obtained from the source (Level 0), data that are serially continuous with noise and nonphysical points removed (Level 1), and, where possible, data that are gap filled using linear interpolation or regression with a nearby station record (Level 2). All stations chosen for this data set were known or documented to be regularly maintained and components checked and calibrated during the period. Additional time-series data included are available snow water equivalent records from automated stations (8) and manual snow courses (22), as well as distributed snow depth and co-located soil moisture measurements (2–6) from four locations spanning the rain–snow transition zone in the center of the domain. Spatial data layers pertinent to snowpack modeling in this data set are basin polygons and 100 m resolution rasters of elevation, vegetation type, forest canopy cover, tree height, transmissivity, and extinction coefficient. All data are available from online data repositories (https://doi.org/10.6071/M3FH3D).

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Nimbus 7 earth radiation budget wide field of view climate data set improvement: 2. Deconvolution of earth radiation budget products and consideration of 1982–1983 El Niño event

Journal of Geophysical Research Atmospheres ◽

10.1029/jd092id04p04125 ◽

1987 ◽

Vol 92 (D4) ◽

pp. 4125 ◽

Cited By ~ 7

Author(s):

Phillip E. Ardanuy ◽

H. Lee Kyle ◽

Richard R. Hucek ◽

Brian S. Groveman

Keyword(s):

El Nino ◽

Field Of View ◽

Radiation Budget ◽

Wide Field ◽

Climate Data ◽

Data Set ◽

El Niño Event ◽

Wide Field Of View ◽

Earth Radiation Budget ◽

Earth Radiation

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Global Instrumental Meteorological Database Before 1890 – a useful overview

10.5194/egusphere-egu21-15903 ◽

2021 ◽

Author(s):

Elin Lundstad ◽

Yuri Brugnera ◽

Stefan Brönnimann

Keyword(s):

Meteorological Parameters ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Meteorological Station ◽

Climate Data ◽

Data Set ◽

Instrumental Data ◽

The World ◽

Climate Model Simulations

This work describes the compilation of global instrumental climate data with a focus on the 18th and early 19th centuries. This database provides early instrumental data recovered for thousands of locations around the world. Instrumental meteorological measurements from periods prior to the start of national weather services are designated &#8220;early instrumental data&#8221;. Much of the data is taken from repositories we know (GHCN, ISTI, CRUTEM, Berkeley Earth, HISTALP). In addition, many of these stations have not been digitized before. Therefore,&#160; we provide a new global collection of monthly averages of multivariable meteorological parameters before 1890 based on land-based meteorological station data. The product will be form as the most comprehensive global monthly climate data set, encompassing temperature, pressure, and precipitation as ever done. These data will be quality controlled and analyzed with respect to climate variability and they be assimilated into global climate model simulations to provide monthly global reconstructions. The collection has resulted in a completely new database that is uniform, where no interpolations are included. Therefore, we are left with climate reconstruction that becomes very authentic. This compilation will describe the procedure and various challenges we have encountered by creating a unified database that can later be used for e.g. models. It will also describe the strategy for quality control that has been adopted is a sequence of tests.

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Epidemic waves in relief against a structured climatic background

10.5194/dach2022-85 ◽

2021 ◽

Author(s):

Peter Carl

Keyword(s):

Climate Modeling ◽

Sunshine Duration ◽

Climate Data ◽

Data Set ◽

Seir Model ◽

Epidemic Curve ◽

Surface Climate ◽

Spatially Distributed

For directly transmissible infectious diseases, seasonality in the course of epidemics may manifest in four major ways: susceptibility of the hosts, their individual and collective behavior, transmissibility of the pathogen, and survival of the latter under evolving environmental conditions. Mechanisms and concepts are not finally settled, notably in a pandemic setting. Climatic seasonality by itself is an aggregate, structured phenomenon that provides a spatially distributed background to the epidemic outbreak and its evolution at multiple timescales. Using advanced methods of data and systems analysis, including epidemiological and climate modeling, the RKI data of the COVID-19 epidemic curve for Berlin and a five-parameter climate data set of the nearby station Lindenberg (Mark) are analyzed in daily resolution over the period March 2020 to October 2021. Aimed to identify extrinsic impacts due to organized intraseasonal climate dynamics, as seen in sunshine duration and surface climate (pressure, temperature, humidity, wind), on intrinsic dynamics of the epidemic system, an established (SEIR) model of the latter and modifications thereof have been subjected to in-depth studies with a view on both genesis and timing of epidemic waves and their potential synchronization with climatic background dynamics. Starting with a case study for the spring 2020 period of shutdown, which unveils remarkable synchronies with the seasonal transition, estimates are given and applied to the follow-up period of individual and combined impacts of climate variables on the SEIR model in different oscillatory (non-equilibrium, lately endemic) regimes of operation.

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The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets

Remote Sensing ◽

10.3390/rs10101640 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1640 ◽

Cited By ~ 3

Author(s):

Ralph Ferraro ◽

Brian Nelson ◽

Tom Smith ◽

Olivier Prat

Keyword(s):

Land Surface ◽

Snow Water Equivalent ◽

Precipitable Water ◽

Climate Data ◽

Sea Ice Concentration ◽

Data Set ◽

Data Record ◽

Microwave Imager ◽

Global Precipitation ◽

Climate Data Record

Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.

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A method for merging nadir-sounding climate records, with an application to the global-mean stratospheric temperature data sets from SSU and AMSU

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-9271-2015 ◽

2015 ◽

Vol 15 (16) ◽

pp. 9271-9284 ◽

Cited By ~ 13

Author(s):

C. McLandress ◽

T. G. Shepherd ◽

A. I. Jonsson ◽

T. von Clarmann ◽

B. Funke

Keyword(s):

Michelson Interferometer ◽

Data Sets ◽

Climate Data ◽

Data Set ◽

Linear Temperature ◽

Temperature Changes ◽

Stratospheric Temperature ◽

Temperature Trends ◽

Microwave Sounding ◽

Global Mean

Abstract. A method is proposed for merging different nadir-sounding climate data records using measurements from high-resolution limb sounders to provide a transfer function between the different nadir measurements. The two nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global-mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present, and providing a simple framework for extending the SSU record into the future using AMSU. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The near-global-mean linear temperature trends for extended SSU for 1980–2012 are −0.63 ± 0.13, −0.71 ± 0.15 and −0.80 ± 0.17 K decade−1 (95 % confidence) for channels 1, 2 and 3, respectively. The extended SSU temperature changes are in good agreement with those from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004 to 2012. The extended SSU record is found to be in agreement with high-top coupled atmosphere–ocean models over the 1980–2012 period, including the continued cooling over the first decade of the 21st century.

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A New Highly Stable Multi-Decade Satellite Climate Data Set Derived from Polar Hyperspectral Infrared Sensors

10.5194/egusphere-egu2020-3754 ◽

2020 ◽

Author(s):

Chris Hepplewhite ◽

Larrabee Strow ◽

Howard Motteler ◽

Sergio de Souza-Machad ◽

Steven Buczkowski

Keyword(s):

Spectral Resolution ◽

Virtual Instrument ◽

Spectral Response ◽

Short Wave ◽

High Spectral Resolution ◽

Climate Data ◽

Climate Trends ◽

Polar Orbit ◽

Data Set ◽

Long Wave

NASA's Atmospheric Infrared Sounder (AIRS) started the continuous measurement of the Earth's upwelling infrared radiation at high spectral resolution in Sept. 2002 in a 13:30 polar orbit. &#160;The AIRS record was supplemented by the CrIS sensor flying on the NASA SNPP platform, also in the 13:30 polar orbit, in 2012. &#160;In 2018 a second CrIS sensor on NOAA's JPSS-1 platform (NOAA-20) began operation, also in the 13:30 orbit. &#160;Two more CrIS sensors are presently being procured for the JPSS-2 and 3 satellites, which will extend this record from 2002 through ~2040. &#160;EUMETSAT's METOP-A/B/C provide very similar hyperspectral observations starting with the IASI sensors in the 09:30 orbit, starting in 2007, which will be continued with METOP-SG for years to come. &#160;Inter-calibration of all of the operating sensors shows agreement generally to 0.2K or better in brightness temperature. &#160;More importantly, we have shown that the radiometric stability of the AIRS sensors is in the 0.002 K/year range or 0.02K/decade, based on measurements of CO2 and SST trends. &#160; Similar stability is expected for CrIS and IASI. &#160;Community consensus suggests that direct radiance trending, followed by conversion of these trends to geophysical quantities will yield the most accurate climate trends. &#160;Here we introduce a new satellite hyperspectral infrared radiance product we call the "Climate Hyperspectral InfraRed Product (CHIRP)" that combines AIRS, CrIS, and IASI into a homogeneous Level 1 radiance product with a common spectral response and channel centers for all three satellites. &#160;This grid is equivalent to an interferometer with optical path differences of 0.8/0.6/0.4 cm for the long-wave/mid-wave/short-wave spectral bands. &#160;This corresponds to a virtual instrument with the same spectral resolution of the JPSS-1 CrIS sensor in the long-wave, with 25/50% degradation in spectral resolution in the mid-wave/short-wave. &#160;This choice allows accurate conversion of the long AIRS record to an equivalent interferometer record. &#160;Conversion of IASI to CHIRP is trivial. &#160;Conversion of all sensors to the CHIRP spectra grid permits simple adjustments of inter-satellite radiometric bias differences since all measurements are first converted to a common spectral grid. &#160;Multiple methods (SNOs, statistical inter-comparisons) indicate these adjustments can be made to the 0.03K level or better. &#160;&#160;A sample application of CHIRP to climate trending will be given by showing multi-decade anomalies of temperature, humidity, and ozone profiles retrieved from CHIRP radiance anomalies, a retrieval that requires almost no a-priori information. &#160;This data set should yield definitive measurements of water-vapor feedback and heavily contribute to our understanding of both tropospheric and stratospheric temperature trends. &#160; Initial production of CHIRP radiances that combine AIRS and CrIS are expected to begin in late 2020. &#160;

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