Cloud tolerance of remote-sensing technologies to measure land surface
temperature

Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

doi:https://doi.org/10.5194/hess-20-3263-2016

Articles | Volume 20, issue 8

https://doi.org/10.5194/hess-20-3263-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-20-3263-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 8

Research article

|

11 Aug 2016

Research article |

| 11 Aug 2016

Cloud tolerance of remote-sensing technologies to measure land surface temperature

Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow

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Month	HTML	PDF	XML	Total
Apr 2016	80	25	2	107
May 2016	51	14	1	66
Jun 2016	16	4	0	20
Jul 2016	6	8	0	14
Aug 2016	165	19	1	185
Sep 2016	22	19	3	44
Oct 2016	19	8	5	32
Nov 2016	54	6	6	66
Dec 2016	2	5	1	8
Jan 2017	22	13	0	35
Feb 2017	7	8	0	15
Mar 2017	23	8	1	32
Apr 2017	31	11	1	43
May 2017	24	11	1	36
Jun 2017	17	7	1	25
Jul 2017	16	7	0	23
Aug 2017	5	6	0	11
Sep 2017	18	14	0	32
Oct 2017	7	12	0	19
Nov 2017	8	11	0	19
Dec 2017	14	18	0	32
Jan 2018	7	4	0	11
Feb 2018	22	14	1	37
Mar 2018	10	6	0	16
Apr 2018	6	4	0	10
May 2018	5	12	2	19
Jun 2018	8	6	1	15
Jul 2018	7	11	2	20
Aug 2018	17	6	1	24
Sep 2018	21	13	0	34
Oct 2018	16	13	1	30
Nov 2018	11	7	0	18
Dec 2018	13	9	1	23
Jan 2019	7	5	0	12
Feb 2019	7	8	0	15
Mar 2019	11	9	1	21
Apr 2019	7	6	1	14
May 2019	10	4	0	14
Jun 2019	13	12	0	25
Jul 2019	18	13	0	31
Aug 2019	15	13	0	28
Sep 2019	12	17	0	29
Oct 2019	6	8	1	15
Nov 2019	15	18	1	34
Dec 2019	11	7	1	19
Jan 2020	19	4	1	24
Feb 2020	23	7	0	30
Mar 2020	24	13	0	37
Apr 2020	19	10	1	30
May 2020	25	9	0	34
Jun 2020	25	14	0	39
Jul 2020	28	11	2	41
Aug 2020	16	7	3	26
Sep 2020	18	10	0	28
Oct 2020	11	13	1	25
Nov 2020	17	8	0	25
Dec 2020	10	8	0	18
Jan 2021	20	7	0	27
Feb 2021	12	8	0	20
Mar 2021	10	6	0	16
Apr 2021	14	12	0	26
May 2021	10	7	0	17
Jun 2021	9	7	1	17
Jul 2021	7	6	1	14
Aug 2021	5	6	0	11
Sep 2021	10	11	0	21
Oct 2021	11	37	0	48
Nov 2021	3	22	1	26
Dec 2021	12	5	0	17
Jan 2022	18	12	0	30
Feb 2022	7	6	2	15
Mar 2022	10	7	1	18
Apr 2022	8	5	1	14
May 2022	6	8	0	14
Jun 2022	6	3	3	12
Jul 2022	5	2	0	7
Aug 2022	17	5	0	22
Sep 2022	8	7	0	15
Oct 2022	7	5	2	14
Nov 2022	10	12	0	22
Dec 2022	19	8	1	28
Jan 2023	12	13	1	26
Feb 2023	16	8	1	25
Mar 2023	32	10	7	49
Apr 2023	2	1	1	4
May 2023	20	12	0	32
Jun 2023	31	8	0	39
Jul 2023	14	10	2	26
Aug 2023	13	11	1	25
Sep 2023	6	6	1	13
Oct 2023	12	6	4	22
Nov 2023	9	1	1	11
Dec 2023	14	8	2	24
Jan 2024	11	3	1	15
Feb 2024	9	9	0	18
Mar 2024	15	11	1	27
Apr 2024	13	7	5	25
May 2024	13	10	5	28
Jun 2024	14	8	3	25
Jul 2024	19	5	4	28
Aug 2024	36	8	4	48
Sep 2024	20	7	1	28
Oct 2024	17	10	1	28
Nov 2024	9	4	2	15
Dec 2024	12	9	2	23
Jan 2025	23	7	3	33
Feb 2025	32	9	2	43
Mar 2025	19	11	5	35
Apr 2025	28	9	0	37
May 2025	33	10	0	43
Jun 2025	39	14	0	53
Jul 2025	26	19	4	49
Aug 2025	32	20	2	54
Sep 2025	62	12	0	74
Oct 2025	29	20	3	52
Nov 2025	7	2	0	9

Cumulative views and downloads (calculated since 21 Apr 2016)

Month	HTML	PDF	XML	Total
Apr 2016	80	25	2	107
May 2016	51	14	1	66
Jun 2016	16	4	0	20
Jul 2016	6	8	0	14
Aug 2016	165	19	1	185
Sep 2016	22	19	3	44
Oct 2016	19	8	5	32
Nov 2016	54	6	6	66
Dec 2016	2	5	1	8
Jan 2017	22	13	0	35
Feb 2017	7	8	0	15
Mar 2017	23	8	1	32
Apr 2017	31	11	1	43
May 2017	24	11	1	36
Jun 2017	17	7	1	25
Jul 2017	16	7	0	23
Aug 2017	5	6	0	11
Sep 2017	18	14	0	32
Oct 2017	7	12	0	19
Nov 2017	8	11	0	19
Dec 2017	14	18	0	32
Jan 2018	7	4	0	11
Feb 2018	22	14	1	37
Mar 2018	10	6	0	16
Apr 2018	6	4	0	10
May 2018	5	12	2	19
Jun 2018	8	6	1	15
Jul 2018	7	11	2	20
Aug 2018	17	6	1	24
Sep 2018	21	13	0	34
Oct 2018	16	13	1	30
Nov 2018	11	7	0	18
Dec 2018	13	9	1	23
Jan 2019	7	5	0	12
Feb 2019	7	8	0	15
Mar 2019	11	9	1	21
Apr 2019	7	6	1	14
May 2019	10	4	0	14
Jun 2019	13	12	0	25
Jul 2019	18	13	0	31
Aug 2019	15	13	0	28
Sep 2019	12	17	0	29
Oct 2019	6	8	1	15
Nov 2019	15	18	1	34
Dec 2019	11	7	1	19
Jan 2020	19	4	1	24
Feb 2020	23	7	0	30
Mar 2020	24	13	0	37
Apr 2020	19	10	1	30
May 2020	25	9	0	34
Jun 2020	25	14	0	39
Jul 2020	28	11	2	41
Aug 2020	16	7	3	26
Sep 2020	18	10	0	28
Oct 2020	11	13	1	25
Nov 2020	17	8	0	25
Dec 2020	10	8	0	18
Jan 2021	20	7	0	27
Feb 2021	12	8	0	20
Mar 2021	10	6	0	16
Apr 2021	14	12	0	26
May 2021	10	7	0	17
Jun 2021	9	7	1	17
Jul 2021	7	6	1	14
Aug 2021	5	6	0	11
Sep 2021	10	11	0	21
Oct 2021	11	37	0	48
Nov 2021	3	22	1	26
Dec 2021	12	5	0	17
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Feb 2022	7	6	2	15
Mar 2022	10	7	1	18
Apr 2022	8	5	1	14
May 2022	6	8	0	14
Jun 2022	6	3	3	12
Jul 2022	5	2	0	7
Aug 2022	17	5	0	22
Sep 2022	8	7	0	15
Oct 2022	7	5	2	14
Nov 2022	10	12	0	22
Dec 2022	19	8	1	28
Jan 2023	12	13	1	26
Feb 2023	16	8	1	25
Mar 2023	32	10	7	49
Apr 2023	2	1	1	4
May 2023	20	12	0	32
Jun 2023	31	8	0	39
Jul 2023	14	10	2	26
Aug 2023	13	11	1	25
Sep 2023	6	6	1	13
Oct 2023	12	6	4	22
Nov 2023	9	1	1	11
Dec 2023	14	8	2	24
Jan 2024	11	3	1	15
Feb 2024	9	9	0	18
Mar 2024	15	11	1	27
Apr 2024	13	7	5	25
May 2024	13	10	5	28
Jun 2024	14	8	3	25
Jul 2024	19	5	4	28
Aug 2024	36	8	4	48
Sep 2024	20	7	1	28
Oct 2024	17	10	1	28
Nov 2024	9	4	2	15
Dec 2024	12	9	2	23
Jan 2025	23	7	3	33
Feb 2025	32	9	2	43
Mar 2025	19	11	5	35
Apr 2025	28	9	0	37
May 2025	33	10	0	43
Jun 2025	39	14	0	53
Jul 2025	26	19	4	49
Aug 2025	32	20	2	54
Sep 2025	62	12	0	74
Oct 2025	29	20	3	52
Nov 2025	7	2	0	9

Latest update: 07 Nov 2025

Short summary

We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.