Droughts at several scales
A drought is measured against the local climate and over a duration: a dry month does not have the effects of a dry year. SPI compares rain with its usual distribution; SPEI subtracts the water demand of the atmosphere. Colour: 12-month SPEI.
- extreme drought (≤ −2)
- moderate to severe drought (−1 to −2)
- near normal
- wet (≥ 1)
GHCN-Daily stations; colour: SPEI-12 of the latest complete month (McKee classes).
New York GHCN station USW00094728 · latest complete month: 2026-09
Show the data as a table
Show the data as a table
| Decade | Months computed | Share |
|---|---|---|
| 1960s | 97 | 70 % |
| 1970s | 120 | 16 % |
| 1980s | 120 | 28 % |
| 1990s | 120 | 26 % |
| 2000s | 120 | 17 % |
| 2010s | 120 | 14 % |
| 2020s | 81 | 18 % |
Meteorological drought is a rain deficit over a few weeks to a few months (SPI-1 to SPI-3). Agricultural drought affects the soil water available to plants; it also depends on evaporation, hence on heat, and shows over 3 to 6 months (SPEI-3). Hydrological drought reaches rivers, lakes and aquifers after months of deficit (SPI-12, SPEI-12).
These indices describe the climate; they measure neither actual soil moisture nor river flow, which also depend on soil, vegetation and withdrawals.
| City | Month | SPI-3 | SPEI-3 | SPEI-12 | Class (SPEI-12) |
|---|---|---|---|---|---|
| Rome | 2025-07 | 0.20 | — | — | |
| New Delhi | — | — | — | — | |
| Lagos | — | — | — | — | |
| Paris | 2026-09 | -2.24 | -2.84 | -3.09 | Extreme drought |
| Tokyo | — | — | — | — | |
| Berlin | 2026-09 | -0.12 | -0.27 | -1.27 | Moderate drought |
| London | 2026-09 | -3.09 | -2.83 | — | |
| Madrid | 2026-09 | -1.05 | -2.26 | — | |
| Mexico | — | — | — | — | |
| Sydney | 2026-09 | -0.38 | -0.48 | -1.65 | Severe drought |
| Beijing | 2025-07 | 1.60 | — | — | |
| Chicago | 2026-09 | 0.81 | 1.05 | 0.52 | Near normal |
| Jakarta | — | — | — | — | |
| Nairobi | — | — | — | — | |
| New York | 2026-09 | 1.20 | 1.32 | -0.22 | Near normal |
| Phoenix | 2026-09 | 0.24 | 0.26 | -1.15 | Moderate drought |
| São Paulo | — | — | — | — | |
| Marseille | 2026-09 | -0.45 | -2.16 | -1.15 | Moderate drought |
| Buenos Aires | — | — | — | — |
Monthly rain totals of the GHCN-Daily stations since 1961, a month being kept only with at least 90% of days measured. SPI (McKee et al., 1993): total over 1, 3 or 12 months, gamma distribution fitted for each calendar month over 1991–2020 (Thom’s maximum-likelihood approximation), the probability of zero totals included, then transformed to a standard normal variable. SPEI (Vicente-Serrano et al., 2010): the same on the balance rain minus reference evapotranspiration, with a three-parameter log-logistic distribution fitted by probability-weighted moments.
Evapotranspiration is computed with the Hargreaves and Samani (1985) formula from the station maximum and minimum temperatures and the FAO-56 extraterrestrial radiation (Allen et al., 1998): the method recommended when humidity, wind and sunshine are missing, at the cost of a coarser estimate than Penman–Monteith. Values are bounded at ±3.09.
With a 30-year reference period, the extreme classes rest on the tails of the fitted distributions, uncertain beyond ±2. A warming climate shifts SPEI towards dry even with constant rain: this is intended, and it is what sets it apart from SPI.
One station poorly summarises a catchment; for the actual state of soils and aquifers, see the national hydrological services and, in Europe, the European Drought Observatory (Copernicus EDO).
- GHCN-Daily stations of the reference places (NOAA NCEI)
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Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E. and Houston, T. G. (2012). An overview of the Global Historical Climatology Network-Daily database. J. Atmos. Oceanic Technol., 29, 897–910. Menne, M. J., et al. (2012). Global Historical Climatology Network - Daily (GHCN-Daily), Version 3. NOAA NCEI.
· doi:10.7289/V5D21VHZ · source page ↗
Licence : U.S. Government work, public domain (data from national services under WMO Resolution 40); cite Menne et al. (2012) · retrieved on Oct 26, 2026 · SHA-256 1a169d65d0f1… - McKee et al. (1993)
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McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, American Meteorological Society, 179–184.
Licence : Published literature; cited - Vicente-Serrano et al. (2010)
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Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: the Standardized Precipitation Evapotranspiration Index. Journal of Climate, 23(7), 1696–1718.
· doi:10.1175/2009JCLI2909.1
Licence : Published literature; cited - Hargreaves et al. (1985)
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Hargreaves, G. H., & Samani, Z. A. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1(2), 96–99.
· doi:10.13031/2013.26773
Licence : Published literature; cited - Allen et al. (1998)
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Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration: guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. FAO, Rome.
Licence : Published literature; cited - Menne et al. (2012)
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Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., & Houston, T. G. (2012). An overview of the Global Historical Climatology Network-Daily database. Journal of Atmospheric and Oceanic Technology, 29(7), 897–910.
· doi:10.1175/JTECH-D-11-00103.1
Licence : Published literature; cited