U.S. Climate Reference Network after One Decade of Operations: Status and Assessment

Diamond, Howard J.; Karl, Thomas R.; Palecki, Michael A.; Baker, C. Bruce; Bell, Jesse E.; Leeper, Ronald D.; Easterling, David R.; Lawrimore, J. H.; Meyers, Tilden P.; Helfert, Michael R.; Goodge, Grant; Thorne, Peter

doi:10.1175/bams-d-12-00170

Cited by 53 publications

(74 citation statements)

References 11 publications

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“…Both SURFRAD sites are located away from urban sources, so we expect them to be representative of the larger region. To verify consistency of SURFRAD trends against trends across the broader region, we compare the SURFRAD SWdn radiance data with pyranometer measurements from the US Climate Reference Network (USCRN; Diamond et al, 2013) SURFRAD also provides estimates of total clear-sky radiance using the all-sky observations, following the methods in Long and Ackerman (2000). Briefly, a power law model (Y = A × cos(θ )b) is fit, where the initial guess for Y is allsky SWdn, θ is the solar zenith angle, and A and b are the fitted coefficients.…”

Section: Methodsmentioning

confidence: 99%

Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

et al. 2017

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Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58-1.0 Wm −2 a −1 over the 2000-2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3-5.0 × 10 −3 a −1 . Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol-radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000-2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as "clear-sky" may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000-2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm −2 a −1 at Goodwin Creek, MS, and +0.93 Wm −2 a −1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20-26 % of the seasonal (June-September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990-2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000-2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

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Section: Methodsmentioning

confidence: 99%

Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

et al. 2017

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“…The assimilation results are evaluated using independent in situ measurements of surface and root-zone soil moisture from two sparse networks across the US: the US Natural Resources Conservation Service Soil Climate Analysis Network (SCAN; Schaefer et al, 2007) and the US Climate Reference Network (USCRN; Diamond et al, 2013;Bell et al, 2013). Surface soil moisture measurements are taken at approximately 5 cm depth.…”

Section: In Situ Soil Moisture Data and Metricsmentioning

confidence: 99%

“…Unlike biases in Tb innovations, the biases in the SM innovations are more stationary and do not depend on seasonal temperature variations. Therefore, the SM innovation biases are not corrected seasonally, but instead cumulative distribution function (CDF) matching between the observations and simulations is performed (Reichle and Koster, 2004) to reconcile the differences in long-term mean, variance, and higher moments, as in earlier retrieval assimilation studies Draper et al, 2012). The observed and simulated SM CDFs are computed for the entire study period, i.e., for 1 July 2010-1 May 2015, at each 36 km grid cell individually.…”

Section: Tb and Sm Innovation Biasmentioning

confidence: 99%

Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model

Lannoy¹,

Reichle²

2016

Hydrol. Earth Syst. Sci.

118

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Abstract. Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and rootzone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 • incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

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“…This network of 114 stations in the contiguous U.S. and more than 20 in Alaska and Hawaii provide climate quality records of SAT, precipitation, and soil moisture for climate monitoring (Figure 1). The USCRN [14] provides homogenous SAT, precipitation, and soil moisture measurements to traceable standards using triplicate instrument configurations for reducing uncertainty in the analysis of climate variability and change on a national scale. Measurements of SAT, wind speed at 1.5 m, relative humidity, and solar radiation are also made.…”

Section: Datamentioning

confidence: 99%

“…The USCRN hourly SAT data [14,18] is the base dataset for HIRS to be assessed against. This observational dataset is of very high quality and sufficient temporal scale for collocation of HIRS satellite SAT data.…”

Section: Datamentioning

confidence: 99%

An Assessment of HIRS Surface Air Temperature with USCRN Data

Stegall

Shi

2016

Remote Sensing

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Abstract:The surface air temperature retrievals from the High Resolution Infrared Radiation Sounder (HIRS) are evaluated by using observations from the U.S. Climate Reference Network (USCRN) for the period of 2006 to 2013. One year of the USCRN data is also used as ground truth in calibrating retrieval biases. The final retrieval results show that mean biases of HIRS retrievals from comparisons to all surface stations for each year are mostly in the range of˘0.2˝C, and the root mean square difference (RMSD) values are 3.2-3.5˝C. Results for biases of individual stations are mostly within 2˝C. In average, RMSDs are smaller over the eastern U.S. than over the western U.S., smaller at nighttime than at daytime, and smaller at lower elevations. The comparison patterns are consistent from year to year and for different satellites, showing the potential of HIRS data for long-term studies.

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U.S. Climate Reference Network after One Decade of Operations: Status and Assessment

Cited by 53 publications

References 11 publications

Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model

An Assessment of HIRS Surface Air Temperature with USCRN Data

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