Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 201

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis

Fall, Souleymane, Niyogi, Dev, Gluhovsky, Alexander, Pielke, Roger A., Kalnay, Eugenia, Rochon, Gilbert·2010·International Journal of Climatology

Abstract

We investigate the sensitivity of surface temperature trends to land use land cover change (LULC) over the conterminous United States (CONUS) using the observation minus reanalysis (OMR) approach. We estimated the OMR trends for the 1979–2003 period from the US Historical Climate Network (USHCN), and the NCEP‐NCAR North American Regional Reanalysis (NARR). We used a new mean square differences (MSDs)‐based assessment for the comparisons between temperature anomalies from observations and interpolated reanalysis data. Trends of monthly mean temperature anomalies show a strong agreement, especially between adjusted USHCN and NARR (r = 0.9 on average) and demonstrate that NARR captures the climate variability at different time scales. OMR trend results suggest that, unlike findings from studies based on the global reanalysis (NCEP/NCAR reanalysis), NARR often has a larger warming trend than adjusted observations (on average, 0.28 and 0.27 °C/decade respectively). OMR trends were found to be sensitive to land cover types. We analysed decadal OMR trends as a function of land types using the Advanced Very High Resolution Radiometer (AVHRR) and new National Land Cover Database (NLCD) 1992–2001 Retrofit Land Cover Change. The magnitude of OMR trends obtained from the NLDC is larger than the one derived from the ‘static’ AVHRR. Moreover, land use conversion often results in more warming than cooling. Overall, our results confirm the robustness of the OMR method for detecting non‐climatic changes at the station level, evaluating the impacts of adjustments performed on raw observations, and most importantly, providing a quantitative estimate of additional warming trends associated with LULC changes at local and regional scales. As most of the warming trends that we identify can be explained on the basis of LULC changes, we suggest that in addition to considering the greenhouse gases–driven radiative forcings, multi‐decadal and longer climate models simulations must further include LULC changes. Copyright © 2009 Royal Meteorological Society

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/joc.1996

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Cited by

See all 201

Metadata

Authors
Fall, S., Niyogi, D., Gluhovsky, A., Pielke, R. A., Kalnay, E., & Rochon, G.
Venue
International Journal of Climatology
Publisher
Wiley
Published
2009-08-24
Volume
30
Issue
13
Pages
1980-1993
ISSN
  • 0899-8418 (ISSN-L)
  • 1097-0088
OpenAlex
W1981150122
Cited by
201
References
4
FWCI
10.26
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis. https://app.cochat.ai/papers/10.1002/joc.1996
The paper
Fall, S., Niyogi, D., Gluhovsky, A., Pielke, R. A., Kalnay, E., & Rochon, G. (2010). Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis. International Journal of Climatology. https://doi.org/10.1002/joc.1996

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.